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295 Commits

Author SHA1 Message Date
Zamil Majdy
7a9b0827bc Merge branch 'dev' into fix/copilot-stream-errors-and-queue-bubbles 2026-04-30 12:48:13 +07:00
Zamil Majdy
7cc1edc61f dx(pr-polish): use --json bucket instead of awk text-column parsing (#12951)
## Why

`/pr-polish` was prematurely emitting `CLEAN-POLL` while CI was still
pending, because the polish-polling loop's CI gate parsed `gh pr checks
$PR` text columns with `awk '{print $2}'`. That works fine for plain job
names, but breaks on jobs with spaces or parens like `test (3.11)`,
`Analyze (python)`, where column 2 is the version `(3.11)` — so `grep -q
"pending"` matched on column 2 of OTHER rows but missed the actual
pending entries. Real symptom on PR #12948: the orchestrator reported
`ORCHESTRATOR:DONE` while `test (3.11/3.12/3.13)` and `Check PR Status`
were still running.

## What

Add a "Concrete CI fetch" subsection right after the polish-polling
pseudocode block, showing the `--json bucket` shape that bypasses the
column-parsing trap entirely. Also flag the `bucket` vs `conclusion`
gotcha (the REST API uses `conclusion`; `gh pr checks --json` only
exposes `bucket`).

## How

Surgical additive edit — the existing pseudocode + state machine is
preserved; the new subsection just translates the abstract
`fetch_check_runs(PR)` into a concrete one-liner so the next implementer
doesn't reach for `awk` again.

## Test plan

- [x] Verified the regression against PR #12948: bucket-based polling
correctly identified 4 pending checks the awk path missed
- [x] Confirmed `gh pr checks {N} --json conclusion` errors with
`Unknown JSON field: "conclusion"` (this gotcha is now noted in the
skill)
2026-04-30 12:44:25 +07:00
majdyz
9969b1ac07 fix(copilot): make CoPilotExecutor picklable for forkserver start
`self._active_tasks_lock = threading.Lock()` in `__init__` (added in #12877
to make `_cleanup_completed_tasks` thread-safe) holds a `_thread.lock`
that the forkserver/spawn start method cannot serialize. With it set
eagerly, `Process(target=self.execute_run_command).start()` from
`AppProcess.start()` raises `TypeError: cannot pickle '_thread.lock'
object` and `poetry run app` aborts at startup before the REST server
binds.

Move the lock to a lazy `@property _active_tasks_lock` so the parent
process never holds a real `threading.Lock` instance — the lock is
materialized inside the forked child the first time
`_cleanup_completed_tasks` runs, where pickling is no longer in play.
This mirrors the existing lazy-init pattern already used for the
ThreadPoolExecutor, RabbitMQ clients, and consumer threads in this
class.
2026-04-30 12:31:02 +07:00
majdyz
d765715fbc fix(copilot): warn on path-traversal in delete_stale_cli_session_file
Self-review: the projects-base guard was returning silently. Mirror the
warn-shape from `_write_cli_session_to_disk` so an out-of-base resolve
surfaces as a Sentry-visible warning. Unreachable in normal operation
(server-generated UUID + deterministic `cli_session_path`), but a hit
would indicate a config or tampering issue worth seeing.
2026-04-30 12:06:21 +07:00
majdyz
8e13d4cb27 fix(copilot/frontend): guard mid-turn poll against session switches
Mirror the request-time-sessionId pattern from usePeekOnBoundary into
useMidTurnDrainPromotion: capture sessionId at request time, compare to
a live ref on resolve, bail if the user switched sessions while the GET
was in flight. Without this, a slow peek for session A could promote
chips into session B's message list after a switch.

Cancellation-flag was tried first but is too broad — this effect re-runs
on every chip-append, which would wrongly invalidate an in-flight poll
for the same session. The sessionId comparison only invalidates on
actual session changes, preserving the chip-append-during-poll race
guarantee.

Added a regression test that holds a peek in flight, switches sessions
mid-resolve, and asserts no promotion fires on the old session's
setMessages.
2026-04-30 11:47:13 +07:00
majdyz
e59fe5af76 fix(copilot): address CodeRabbit review
- delete_stale_cli_session_file: drop exists() TOCTOU; catch
  FileNotFoundError; log basename + strerror only on unexpected OSError.
- useCopilotPendingChips: unify bubble id across auto-continue and
  mid-turn promotion paths via `bubbleIdFor(chip) = pending-chip-{uuid}`,
  so a poll resolving after auto-continue already promoted the same chip
  no longer renders it twice.
- usePeekOnBoundary: capture sessionId at request time and guard the
  .then() callback against a stale response that resolves after the user
  switched sessions (prevents old-session chips bleeding into the new
  session).
2026-04-30 11:17:32 +07:00
majdyz
9e8622c1d1 fixup(copilot): logger.info/warn (not debug); restore chip state diagram 2026-04-30 10:40:39 +07:00
Zamil Majdy
0dcd25f73f Merge branch 'dev' into fix/copilot-stream-errors-and-queue-bubbles 2026-04-30 10:28:57 +07:00
majdyz
78619ba090 fix(copilot): persist context-rescued retry, dedupe error UI, race-safe chips
Three user-reported regressions on dev (chat-mode-option flag), all in one
PR because they share the same surface area:

1. Disappearing queued messages — chips were stored as bare strings keyed
   by array index; the mid-turn poll captured a stale snapshot and used a
   slice-based ``setQueuedMessages(remaining)`` that overwrote any chip the
   user appended during the in-flight peek. Fixed by giving each chip a
   frontend-only UUID, promoting one bubble per chip, and using a functional
   ``setChips(prev => prev.filter(c => !drainedIds.has(c.id)))`` so newly
   appended chips survive the race.

2. Prompt-too-long recurring on the same session for days (SENTRY-1207,
   191 occurrences) — the T2+ context-error retry branch dropped session_id
   to dodge "Session ID already in use", so the recovery CLI wrote to a
   random path and the post-turn upload silently grabbed the stale
   pre-failure file. Next turn re-resumed from the same bloated GCS copy
   and re-tripped, ad infinitum. Fixed by clearing the local session file
   first via the new ``delete_stale_cli_session_file`` helper, then keeping
   ``session_id`` so the CLI's recovery write lands on the predictable
   path that ``upload_transcript`` reads.

3. Double error UI — backend appends a persisted error marker to
   ``session.messages`` AND yields a ``StreamError`` SSE event on the same
   final-failure path. Frontend rendered the marker as an in-line ErrorCard
   bubble and ``error`` from useChat as a trailing red banner — same string,
   twice. Fixed by adding a top-level ``lastAssistantHasErrorMarker`` memo
   in ChatMessagesContainer and gating the banner on ``!lastIsErrorMarker``.

Tests: 216 backend SDK tests pass, 29 focused frontend tests pass
(useCopilotPendingChips, ChatMessagesContainer error-banner-dedup,
makePromotedBubble, plus regression coverage for the new
delete_stale_cli_session_file helper and the retry session_id reuse).
2026-04-30 10:27:02 +07:00
Zamil Majdy
4a1741cc15 fix(platform): cancel-banner copy + clearer 422 on currency mismatch (#12947)
## Why

Two regressions surfaced after
[#12933](https://github.com/Significant-Gravitas/AutoGPT/pull/12933)
merged to `dev`:

1. **Cancel-pending banner shows wrong copy.** The merged PR moved
cancel-at-period-end from `BASIC` → `NO_TIER`, but
`PendingChangeBanner.isCancellation` was still keyed on `"BASIC"`. As a
result, a user who cancels their sub now sees *"Scheduled to downgrade
to No subscription on …"* instead of the intended *"Scheduled to cancel
your subscription on …"*. Caught by Sentry on the merged PR.

2. **Currency-mismatch downgrade returns 502 (looks like outage).** A
user with an existing GBP-active sub (Max Price has
`currency_options.gbp`) tried to downgrade to Pro and got 502. The
backend logs show:
   ```
stripe._error.InvalidRequestError: The price specified only supports
`usd`.
   This doesn't match the expected currency: `gbp`.
   ```
The Pro Price is USD-only; Stripe rejects `SubscriptionSchedule.modify`
because phases must share currency. Wrapping that in a generic 502 hid
the real cause and made it read like a Stripe outage.

## What

* Frontend: flip `PendingChangeBanner.isCancellation` from `pendingTier
=== "BASIC"` to `"NO_TIER"`. Update both component and page-level tests
that exercised the cancellation branch.
* Backend: catch `stripe.InvalidRequestError` whose message mentions
`currency` in `update_subscription_tier`, and return **422** with *"Tier
change unavailable for your current billing currency. Cancel your
subscription and re-subscribe at the target tier, or contact support."*
— so users see the actual reason, not a misleading outage message. Other
`StripeError` paths still return 502.
* New backend test asserts the currency-mismatch branch returns 422 with
the new copy.

## How

* `PendingChangeBanner.tsx` line 28: 1-char change (`"BASIC"` →
`"NO_TIER"`).
* `subscription_routes_test.py` and `PendingChangeBanner.test.tsx`
updated to use `NO_TIER` for the cancellation fixture.
* `v1.py` `update_subscription_tier` adds a typed `except
stripe.InvalidRequestError` branch ahead of the generic `StripeError`;
only currency-mismatch messages get the special 422, everything else
falls through to the existing 502.

## The real fix lives in Stripe config

The defensive 422 here is just a clearer error surface. To actually
unblock GBP/EUR users from changing tiers, the per-tier Stripe Prices
(Pro, and Basic if priced) need `currency_options` for GBP added — Max
already has this, which is why Max checkout shows the £/$ toggle. Stripe
locks `currency_options` after a Price has been transacted, so the
procedure is: create a new Price with USD + GBP from the start → update
the `stripe-price-ids` LD flag to the new Price ID. No further code
change required; same Price ID stays per tier, multiple currencies
inside it.

## Checklist

- [x] Component test for new banner copy
- [x] Backend test for 422 currency-mismatch branch
- [x] Format / lint / types pass
- [x] No protected route added — N/A
2026-04-30 10:25:02 +07:00
Krzysztof Czerwinski
c08b9774dc fix(backend/push): skip OS push for onboarding payloads (#12944)
## Why

[#12723](https://github.com/Significant-Gravitas/AutoGPT/pull/12723)
wired Web Push fanout into `AsyncRedisNotificationEventBus.publish()` so
copilot completion events reach users with the tab closed. But the bus
is also used by `data/onboarding.py` for in-page step toasts, and those
started firing OS-level system notifications (`increment_runs`,
`step_completed`, etc.) — unwanted noise.

## What

Smallest possible patch: skip the OS push fanout when `payload.type ==
"onboarding"`. WebSocket delivery is unchanged.

## How

```python
async def publish(self, event: NotificationEvent) -> None:
    await self.publish_event(event, event.user_id)
    # Skip OS push for onboarding step toasts — those are in-page only.
    # TODO: remove once the onboarding/wallet rework lands.
    if event.payload.model_dump().get("type") == "onboarding":
        return
    ...
```

Five-line addition in `backend/data/notification_bus.py`. Marked `TODO`
to remove once the upcoming onboarding/wallet rework decides per-event
whether a system notification is desired.

Tests: added `test_publish_skips_web_push_for_onboarding`; existing
fanout tests continue to validate the happy path with non-onboarding
payloads.

## Test plan

- [x] `poetry run format` (ruff + isort + black + pyright)
- [ ] CI: `poetry run pytest backend/data/notification_bus_test.py`
- [ ] Manual on dev: trigger onboarding step → confirm no OS
notification; finish copilot session → confirm OS notification still
fires.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

---------

Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-29 16:20:53 +00:00
Zamil Majdy
fe3d6fb118 feat(platform): subscription credit grants + paywall gate + dialog UX + cross-pod cache (#12933)
## Why

Started as a regression fix for admin-granted user downgrades hitting
Stripe Checkout, broadened to close the surrounding gaps in the Stripe
billing flow that surfaced during testing. Three concrete user-facing
problems the PR resolves:

1. **Admin-granted users couldn't change tier in-app** when their
current tier had no `stripe-price-id-*` LD configured — clicking
Downgrade silently routed to a paid-signup Stripe Checkout instead of
just changing the tier.
2. **Subscription payments granted nothing visible to users** — paying
£20–£320/mo gave higher rate-limit multipliers but no AutoPilot credits
in the user's balance, despite a dialog promising "credit to your next
Stripe invoice" (which users naturally read as AutoGPT credits).
3. **Tier oscillated across page refreshes** — `get_user_by_id` was
process-local cached, so dev's 4 server pods each held their own copy.
Tier could read MAX on one pod and BASIC on another for ~5 min after a
webhook update, depending on which pod the request landed on.

Plus three structural improvements caught during review:

4. **No paywall enforcement for paid-cohort users without subscription**
— non-beta users on `BASIC` (no Stripe sub) could freely use AutoPilot.
5. **Upgrade/downgrade dialog copy was misleading** — implied a Stripe
redirect that doesn't happen for existing-sub modifications, used
"credit" ambiguously, and didn't surface the next-invoice date.
6. **Top-up Checkout created an ephemeral Stripe Product per session** —
no canonical Product for dashboard reporting, no way to scope coupons to
top-ups.

## What

### 1. Admin-granted downgrades skip Checkout (price-id-pruning
regression)

`update_subscription_tier()` used to gate its modify-or-DB-flip block on
`current_tier_price_id is not None`. When a tier was pruned from
`stripe-price-ids` LD, that gate skipped the inner DB-flip branch and
the request fell through to Checkout — sending admin-granted users to a
paid-signup flow when they were trying to *reduce* their tier. Drop the
gate and call `modify_stripe_subscription_for_tier()` unconditionally —
the function self-reports `False` when there's no Stripe sub. One
uniform path for everyone now.

### 2. Subscription credit grant on every paid Stripe invoice

New `invoice.payment_succeeded` webhook handler at
[`credit.py:handle_subscription_payment_success`](autogpt_platform/backend/backend/data/credit.py)
adds a `GRANT` transaction equal to `invoice.amount_paid`, keyed by
`INVOICE-{id}` for idempotency (Stripe webhook retries cannot
double-grant). Initial signup, monthly renewal, and prorated upgrade
charges all surface as AutoGPT balance bumps the moment Stripe confirms
the charge. Skipped: non-subscription invoices, $0 invoices, ENTERPRISE
users.

### 3. Cross-pod user cache

[`user.py:31`](autogpt_platform/backend/backend/data/user.py#L31)
`cache_user_lookup = cached(maxsize=1000, ttl_seconds=300,
shared_cache=True)`. Single line — moves the cache to Redis so all
server pods read/write the same key. The existing
`get_user_by_id.cache_delete(user_id)` invalidations now propagate
cross-pod.

### 4. PaywallGate

New
[`PaywallGate`](autogpt_platform/frontend/src/app/(platform)/PaywallGate/PaywallGate.tsx)
wraps the `(platform)/layout.tsx` route group. When
`ENABLE_PLATFORM_PAYMENT === true` (paid cohort) AND `subscription.tier
=== "BASIC"`, redirects to `/profile/credits` where the credits page
shows a "Pick a plan to continue using AutoGPT" banner above the tier
picker.

Notes:
- **Beta cohort skips entirely** (flag off → `useGetSubscriptionStatus`
query disabled, no redirect).
- **Gates on DB tier, not `has_active_stripe_subscription`** — Sentry
caught that a transient Stripe API error in
`get_active_subscription_period_end()` would set `has_active=false` for
paying users, locking them out. The DB tier is set by webhooks and
persists locally; Stripe API hiccups don't flip it.
- **Exempt routes**: `/profile`, `/admin`, `/auth`, `/login`, `/signup`,
`/reset-password`, `/error`, `/unauthorized`, `/health`. Onboarding
lives in the sibling `(no-navbar)` group, so this gate doesn't conflict
with the in-flight onboarding-paywall integration.

### 5. Upgrade/downgrade dialog clarity

`SubscriptionStatusResponse` now exposes
`has_active_stripe_subscription: bool` and `current_period_end: int |
None`, computed via a new
[`get_active_subscription_period_end`](autogpt_platform/backend/backend/data/credit.py)
helper. Frontend dialogs branch on those:

**Upgrade — modify-in-place** (existing sub):
> Your subscription is upgraded to MAX immediately. On your next invoice
on May 21, 2026, your saved card is charged for the upgrade proration
since today plus the next month at the new rate, with the unused portion
of your current plan automatically deducted. Credits matching the paid
amount are added to your AutoGPT balance once Stripe confirms the
charge.

**Upgrade — Checkout** (no sub):
> You'll be redirected to Stripe to enter payment details and start your
MAX subscription. The first invoice's amount is added to your AutoGPT
balance once Stripe confirms the charge.

**Downgrade (paid → paid)**:
> Switching to PRO takes effect at the end of your current billing
period on May 21, 2026 — no charge today. You keep your current plan
until then. From that date your saved card is billed at the PRO rate,
and matching credits are added to your AutoGPT balance with each paid
invoice.

Toast wording on success matches dialog. Tier labels run through
`getTierLabel()` so we render "Pro/Max/Business" not "PRO/MAX/BUSINESS"
(Sentry-flagged in review).

### 6. Top-up Stripe Product ID via LD flag

New `STRIPE_PRODUCT_ID_TOPUP` LD flag. **Unset (default)** → legacy
inline `product_data` (Stripe creates an ephemeral product per Checkout
— backward-compatible with current behavior). **Set to a Stripe Product
ID** → line item references that Product so all top-ups group under one
entity in Stripe Dashboard reporting; per-session amount stays dynamic
via `price_data.unit_amount`. The two paths are mutually exclusive
(Stripe rejects `product` + `product_data` together).

## How

- Backend changes confined to
[`v1.py`](autogpt_platform/backend/backend/api/features/v1.py),
[`credit.py`](autogpt_platform/backend/backend/data/credit.py),
[`user.py`](autogpt_platform/backend/backend/data/user.py),
[`feature_flag.py`](autogpt_platform/backend/backend/util/feature_flag.py).
- Frontend changes: new
[`PaywallGate`](autogpt_platform/frontend/src/app/(platform)/PaywallGate/PaywallGate.tsx)
component + small edits to
[`(platform)/layout.tsx`](autogpt_platform/frontend/src/app/(platform)/layout.tsx),
`SubscriptionTierSection.tsx`, `useSubscriptionTierSection.ts`,
`helpers.ts`.
- Both backend and frontend pass `user.id` to LD context (verified in
[`feature_flag.py:_fetch_user_context_data`](autogpt_platform/backend/backend/util/feature_flag.py)
and
[`feature-flag-provider.tsx`](autogpt_platform/frontend/src/services/feature-flags/feature-flag-provider.tsx))
for proper per-user targeting.

### Out of scope (follow-ups)

- Hard-paywall onboarding integration (Lluis's work — coordinated;
PaywallGate wraps `(platform)/layout.tsx` and onboarding lives in
`(no-navbar)`, so they don't conflict).
- Beta-users-as-Stripe-trial migration.
- Max-cap usage alerting + "Contact us" routing.
- "No Active Subscription" state rename.
- "Your credits" → "Automation Credits" rename + helper tooltip.
- BASIC tier resurface as a free / cancel-subscription option
(deliberately deferred per current product direction).

## Test plan

### Backend (all green in CI)

- [x] `poetry run pytest
backend/api/features/subscription_routes_test.py` — 41 passed.
- [x] `poetry run pytest backend/data/credit_subscription_test.py`
covering: `handle_subscription_payment_success` (grants credits, skips
non-sub/zero/missing-customer/unknown-user/ENTERPRISE, idempotent on
retry), `get_active_subscription_period_end` (happy path, no-customer
short-circuit, Stripe error swallow), top-up Product ID flag both
branches.
- [x] Type-check (3.11/3.12/3.13) — green after explicit
`list[stripe.checkout.Session.CreateParamsLineItem]` typing on top-up
`line_items`.
- [x] Codecov patch — both backend + frontend green.

### Frontend (all green in CI)

- [x] `pnpm test:unit` — 2154/2154 pass, including 5 new PaywallGate
tests (beta-cohort skip, paid-cohort BASIC redirect, no-redirect for
PRO/MAX/BUSINESS, exempt-prefix matrix, loading-state guard) and updated
`formatCost`/dialog-copy assertions.
- [x] `pnpm types`, `pnpm format`, `pnpm lint` — clean.

### Live verification on `dev-builder.agpt.co` (5/5 pass — see PR
comments)

- [x] Login + credits page renders correctly with Pro + Max cards, BASIC
+ BUSINESS hidden, no paywall banner for active subscriber.
- [x] Downgrade dialog shows new copy with concrete date + "no charge
today" + credit-grant explanation.
- [x] PaywallGate does NOT redirect paying users (MAX tier with active
sub).
- [x] PaywallGate REDIRECTS BASIC user (DB-flipped via `kubectl exec`
for testing, restored after) → `/build` redirects to `/profile/credits`,
violet "Pick a plan to continue using AutoGPT" banner displayed.
- [x] Upgrade dialog (modify-in-place) shows the corrected proration
phrasing.
- [ ] Manual: real production-like test of `invoice.payment_succeeded`
granting credits — fires on next billing cycle (2026-05-21 for the dev
test user); not testable today without manipulating Stripe webhook.
2026-04-29 23:15:29 +07:00
Ubbe
c6d31f8252 feat(frontend): gate onboarding SubscriptionStep behind ENABLE_PLATFORM_PAYMENT (#12943)
### Why / What / How

**Why:** The onboarding `SubscriptionStep` (added in #12935) is
currently shown to every new user, but the platform payment system is
rolled out behind the `ENABLE_PLATFORM_PAYMENT` LaunchDarkly flag. We
need the onboarding plan-selection step to honor the same flag so users
in flag-off cohorts don't hit a payment surface that the rest of the
product won't support.

**What:** Conditionally render the `SubscriptionStep` based on
`ENABLE_PLATFORM_PAYMENT`. When the flag is off the wizard runs `Welcome
→ Role → PainPoints → Preparing` (3 user-interactive steps +
transition); when on, behavior is unchanged (`Welcome → Role →
PainPoints → Subscription → Preparing`).

**How:**
- `page.tsx` reads the flag, computes `totalSteps` (3 vs. 4) and
`preparingStep` (4 vs. 5), and only renders `SubscriptionStep` when the
flag is on.
- `useOnboardingPage.ts` threads the same `preparingStep` into the URL
`parseStep` clamp and into the "submit profile when entering Preparing"
effect, so both adapt to the flag state.
- The Zustand store is left unchanged — its hard `Math.min(5, …)` clamp
is unreachable in flag-off flow because PainPointsStep advances 3 → 4
(Preparing) and that's the terminal step.
- `playwright/utils/onboarding.ts`: with `NEXT_PUBLIC_PW_TEST=true`
LaunchDarkly returns `defaultFlags` (`ENABLE_PLATFORM_PAYMENT: false`),
so the helper now waits up to 2s for the Subscription header and only
clicks a plan CTA if the step is actually rendered.

### Changes 🏗️

- `autogpt_platform/frontend/src/app/(no-navbar)/onboarding/page.tsx` —
gate `SubscriptionStep` on `ENABLE_PLATFORM_PAYMENT`; derive
`totalSteps`/`preparingStep` from the flag.
-
`autogpt_platform/frontend/src/app/(no-navbar)/onboarding/useOnboardingPage.ts`
— make `parseStep` and the profile-submission effect respect the
flag-derived `preparingStep`.
- `autogpt_platform/frontend/src/playwright/utils/onboarding.ts` — make
the Subscription step optional in `completeOnboardingWizard` so E2E
works in both flag states.

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [ ] I have tested my changes according to the test plan:
- [x] Existing onboarding unit tests pass (`pnpm test:unit` — 2447
passed, including `PainPointsStep`, `RoleStep`, `SubscriptionStep`,
store)
  - [x] `pnpm format`, `pnpm lint`, `pnpm types` clean
- [ ] Manual: with flag **off**, walk onboarding and confirm wizard goes
Welcome → Role → PainPoints → Preparing → /copilot, progress bar shows 3
steps
- [ ] Manual: with flag **on** (LD or
`NEXT_PUBLIC_FORCE_FLAG_ENABLE_PLATFORM_PAYMENT=true`), walk onboarding
and confirm SubscriptionStep is present at step 4, progress bar shows 4
steps
- [ ] Manual: with flag **off**, hit `/onboarding?step=5` directly and
confirm it clamps back to step 1 (no orphan Subscription state)
- [ ] Playwright: `completeOnboardingWizard` E2E flow continues to pass
under default `NEXT_PUBLIC_PW_TEST=true` (flag off path)

#### For configuration changes:
- [x] `.env.default` is updated or already compatible with my changes
(no config changes — flag already exists in LaunchDarkly +
`defaultFlags`)
- [x] `docker-compose.yml` is updated or already compatible with my
changes
- [x] I have included a list of my configuration changes in the PR
description (none needed)

---------

Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-29 23:12:04 +07:00
John Ababseh
28ae7ebac8 feat(onboarding): add subscription plan selection step (#12935)
## Summary

Adds a new **Subscription Step** (Step 4) to the onboarding wizard,
allowing users to choose a plan (Pro, Max, or Team) before reaching the
"Preparing" step.

## Changes

### New files
- **`steps/SubscriptionStep.tsx`** — Full subscription UI with:
  - Three plan cards (Pro $50/mo, Max $320/mo, Team — coming soon)
- Monthly / yearly billing toggle (yearly shows annual total with 20%
discount, plus monthly equivalent)
- Country selector (28 Stripe-supported countries) that opens upward as
a search modal
  - Localized pricing using live exchange rates
- **`steps/countries.ts`** — Currency data module with exchange rates,
`formatPrice()` helper, and zero-decimal currency handling (JPY, KRW,
HUF, CLP)

### Modified files
- **`store.ts`** — Extended `Step` type to `1 | 2 | 3 | 4 | 5`, added
`selectedPlan` and `selectedBilling` state/actions
- **`page.tsx`** — Wired `SubscriptionStep` as Step 4, moved
`PreparingStep` to Step 5, adjusted progress bar and dot indicators
- **`useOnboardingPage.ts`** — Updated `parseStep` range to 1–5, profile
submission now triggers at Step 5

## Design decisions
- Follows existing component patterns: uses `FadeIn`, `Text`, `Button`
atoms, `cn()` utility, Phosphor icons
- Country selector opens **upward** to avoid clipping below the viewport
- Plan selection advances to Step 5 immediately (Stripe integration is
TODO)
- Exchange rates are hardcoded for now — should be fetched from an API
in production

## TODO
- [ ] Integrate with Stripe checkout / backend subscription API
- [ ] Fetch live exchange rates instead of hardcoded values
- [ ] Add responsive layout for mobile viewports

---------

Co-authored-by: Nicholas Tindle <nicholas.tindle@agpt.co>
Co-authored-by: Lluis Agusti <hi@llu.lu>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Co-authored-by: Ubbe <hi@ubbe.dev>
2026-04-29 21:26:18 +07:00
Krzysztof Czerwinski
e0f9146d54 feat(platform): add Web Push notifications via VAPID for background delivery (#12723)
### Why / What / How

**Why:** When a user kicks off an AutoPilot task and leaves the platform
(closes the tab, switches to another page, or minimizes the browser),
they have no way of knowing when it completes unless they come back and
check. This breaks the "set it and forget it" promise of automation.

**What:** Adds Web Push notifications using the standard Push API
(VAPID). Push notifications are delivered through free browser vendor
services (Google FCM, Apple APNs, Mozilla Push) to a service worker —
even when all AutoGPT tabs are closed, as long as the browser process is
running. The system is generic and extensible to all notification types,
with copilot session completion as the first integration.

**How:**
- **Backend:** A new `PushSubscription` Prisma model stores per-user
push subscriptions. When a `NotificationEvent` is published to the Redis
notification bus, the existing `notification_worker` in `ws_api.py`
fires a tracked background `send_push_for_user()` task. This uses
`pywebpush` to call the browser push services with VAPID authentication.
Includes per-user TTL-bounded debounce (5s), per-user subscription cap
(20), 410/404 auto-cleanup, periodic scheduler-driven cleanup of
high-failure rows, and route-level SSRF rejection of untrusted
endpoints.
- **Frontend:** A `push-sw.js` service worker handles `push` events and
shows OS notifications via `self.registration.showNotification()`, with
click-to-navigate. A `PushNotificationProvider` mounted at the platform
layout registers the SW and subscription on all pages, posts the current
URL to the SW on every Next.js navigation (since Chrome's
`WindowClient.url` is stale for SPA routing), forwards the user's
notifications-toggle setting to the SW, and tears down on logout. The
copilot in-page notification path defers to the SW when a push
subscription is active so users don't get duplicate alerts.

### Behavior — when does an OS notification fire?

| Where the user is focused | Notifications toggle | OS notification? |
|---|---|---|
| Any `/copilot` page (any session, tab visible + browser focused) | on
| suppressed — sidebar green check + title badge handle it |
| `/library` (or any non-`/copilot` route) | on | **fires** |
| `/copilot` but tab hidden (Cmd-Tab away, minimized, different tab) |
on | **fires** |
| All AutoGPT tabs closed (browser process still running) | on |
**fires** |
| Any state | off | suppressed |
| Anywhere | permission not granted / no push subscription | falls back
to in-page `Notification()` if user is away on `/copilot`; nothing
otherwise |

Click any OS notification → focuses an existing tab and navigates it to
`/copilot?sessionId=<id>`, or opens a new window if no AutoGPT tab is
open.

### Test plan

#### Setup
- [ ] Generate VAPID keys via the snippet in `backend/.env.default` and
set `VAPID_PRIVATE_KEY`, `VAPID_PUBLIC_KEY`, `VAPID_CLAIM_EMAIL` in
`backend/.env`
- [ ] Leave `NEXT_PUBLIC_VAPID_PUBLIC_KEY` unset on the frontend (single
source of truth via `/api/push/vapid-key`)
- [ ] Start backend + frontend, grant notification permission on the
copilot page
- [ ] Verify `push-sw.js` is "activated and is running" in DevTools →
Application → Service Workers
- [ ] Verify `POST /api/push/subscribe` created exactly one DB row in
`PushSubscription` for your user

#### Notification show / suppress matrix
- [ ] Trigger completion **on `/copilot` viewing the same session**, tab
visible + focused → no OS notification (sidebar green check appears)
- [ ] Trigger completion **on `/copilot` viewing a different session**,
tab visible + focused → no OS notification (still considered "in the
feature")
- [ ] Trigger completion **on `/library`**, tab visible + focused → OS
notification fires
- [ ] Trigger completion **on `/copilot`** but with the tab hidden
(Cmd-Tab to another app) → OS notification fires
- [ ] Trigger completion with all AutoGPT tabs closed → OS notification
fires (browser must still be running)
- [ ] Toggle notifications **off** in the copilot UI → trigger
completion → no OS notification
- [ ] Toggle notifications **back on** → trigger completion → OS
notification fires

#### Click behavior
- [ ] OS notification → click → focuses an existing AutoGPT tab and
navigates to `/copilot?sessionId=<id>`
- [ ] OS notification with no AutoGPT tab open → click → opens a new tab
on `/copilot?sessionId=<id>`

#### Lifecycle
- [ ] Logout → DB row removed, browser unsubscribed; no further OS
notifications until login + re-subscribe
- [ ] Stale subscription (e.g. unsubscribed externally) → backend gets
410 from FCM → row auto-deleted; second push attempts no longer fan out
to it

### Changes 🏗️

**Backend — New files:**
- `backend/data/push_subscription.py` — CRUD for push subscriptions:
`upsert` (with `MAX_SUBSCRIPTIONS_PER_USER` cap), `find_many`, `delete`,
`increment_fail_count`, `cleanup_failed_subscriptions`,
`validate_push_endpoint` (HTTPS + push-service hostname allowlist for
SSRF prevention)
- `backend/data/push_sender.py` — Fire-and-forget push delivery with
`cachetools.TTLCache`-bounded debounce, defense-in-depth re-validation
at send time, 410/404 auto-cleanup with regex-based status extraction
(covers pywebpush versions where `e.response` is unset)
- `backend/api/features/push/routes.py` — 3 endpoints: `GET
/api/push/vapid-key`, `POST /api/push/subscribe`, `POST
/api/push/unsubscribe` (all with `requires_user` auth and 400 on invalid
endpoints)
- `backend/api/features/push/model.py` — Pydantic models with
`min_length`/`max_length` constraints on endpoint and crypto keys

**Backend — Modified files:**
- `schema.prisma` — Added `PushSubscription` model + `User` relation
- `pyproject.toml` — Added `pywebpush ^2.3` dependency
- `backend/util/settings.py` — VAPID key fields on `Secrets`;
`push_subscription_cleanup_interval_hours` config
- `backend/api/rest_api.py` — Registered push router at `/api/push`
- `backend/api/ws_api.py` — Notification worker now fires
`send_push_for_user()` as a tracked background task (strong-ref set +
done callback so asyncio doesn't GC it mid-run)
- `backend/data/db_manager.py` — Exposed push subscription RPC methods
on the DB manager async client
- `backend/executor/scheduler.py` — Periodic
`cleanup_failed_push_subscriptions` job (default 24h)
- `backend/.env.default` — VAPID env vars with key generation snippet

**Frontend — New files:**
- `public/push-sw.js` — Service worker: routes pushes via
`NOTIFICATION_MAP`, suppresses when user is on `/copilot`, accepts
`CLIENT_URL` and `NOTIFICATIONS_ENABLED` postMessages so SW logic stays
in sync with SPA navigation and the toggle, click handler with focus →
navigate → openWindow fallback, `pushsubscriptionchange` re-subscribe
with `credentials: include`
- `src/services/push-notifications/registration.ts`, `api.ts`,
`helpers.ts` — SW registration / Push API subscription / backend API
helpers
- `src/services/push-notifications/usePushNotifications.ts` — Hook that
auto-subscribes on login and tears down on logout
- `src/services/push-notifications/useReportClientUrl.ts` — Posts
current pathname+search to SW on every Next.js route change (works
around stale `WindowClient.url`)
- `src/services/push-notifications/useReportNotificationsEnabled.ts` —
Forwards the user's notifications toggle to the SW
- `src/services/push-notifications/PushNotificationProvider.tsx` —
Mounts all three hooks at the platform layout level

**Frontend — Modified files:**
- `src/app/(platform)/layout.tsx` — Mounted `<PushNotificationProvider
/>`
- `src/app/(platform)/copilot/useCopilotNotifications.ts` — Skips
in-page `Notification()` when a SW push subscription is active (avoids
duplicate alerts)
- `src/services/storage/local-storage.ts` — Added
`PUSH_SUBSCRIPTION_REGISTERED` key
- `frontend/.env.default` — Optional `NEXT_PUBLIC_VAPID_PUBLIC_KEY`
(left unset by default to keep `/api/push/vapid-key` as the single
source of truth)

**Configuration changes:**
- New env vars: `VAPID_PRIVATE_KEY`, `VAPID_PUBLIC_KEY`,
`VAPID_CLAIM_EMAIL` (backend); optional `NEXT_PUBLIC_VAPID_PUBLIC_KEY`
(frontend)
- New `push_subscription_cleanup_interval_hours` setting (default 24,
range 1–168)
- New DB migration: `PushSubscription` table
(`20260420120000_add_push_subscription`)

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] All blockers and should-fixes from the autogpt-pr-reviewer review
have been addressed (see PR thread)
- [x] All inline review threads resolved (49 threads addressed)

#### For configuration changes:
- [x] `.env.default` is updated or already compatible with my changes
- [x] `docker-compose.yml` is updated or already compatible with my
changes
- [x] I have included a list of my configuration changes in the PR
description (under **Changes**)

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-29 13:28:21 +00:00
Bently
c3c2737c42 feat(platform): copilot-bot (Python / discord.py) (#12618)
## Why

AutoPilot needs to reach users on chat platforms — Discord first,
Telegram / Slack / Teams / WhatsApp next. This PR adds the bot service
that bridges those platforms to the AutoPilot backend via the
`PlatformLinkingManager` AppService introduced in #12615.

Two independent linking flows (see #12615 for the rationale):

- **SERVER links**: first person to run `/setup` in a guild claims it.
Anyone in the server can mention the bot; all usage bills to the owner.
- **USER links**: an individual DMs the bot, links their personal
account, DMs bill to their own AutoPilot. A server owner still has to
link their DMs separately.

## What

A Python service using `discord.py`, living alongside the rest of the
backend. Connects to the platform_linking service via cluster-internal
RPC (no shared bearer token) and subscribes to copilot streams directly
on Redis (no HTTP SSE proxy).

Originally prototyped in Node.js with Vercel's Chat SDK — rewritten in
Python after team feedback: the rest of the platform is Python,
`discord.py` was already a dependency, and the Chat SDK's streaming-UI
abstractions don't apply to a headless chat bot.

### Deployment

- **Shares the existing backend Docker image** — no separate Dockerfile,
no separate Artifact Registry. A `copilot-bot` poetry script entry lets
the same image run with `command: ["copilot-bot"]` in the Helm chart.
- **Auto-starts with `poetry run app`** when
`AUTOPILOT_BOT_DISCORD_TOKEN` is set, so the full local dev stack
includes the bot without extra setup.
- **Runs standalone** via `poetry run copilot-bot` for the production
pod.

Infra PR:
[AutoGPT_cloud_infrastructure#310](https://github.com/Significant-Gravitas/AutoGPT_cloud_infrastructure/pull/310).

### File layout

```
backend/copilot/bot/
├── app.py              # CoPilotChatBridge(AppService) + adapter factory + outbound @expose
├── config.py           # Shared (platform-agnostic) config
├── handler.py          # Core logic: routing, linking, batched streaming
├── platform_api.py     # Thin facade over PlatformLinkingManagerClient + stream_registry
├── platform_api_test.py
├── text.py             # split_at_boundary + format_batch
├── threads.py          # Redis-backed thread subscription tracking
├── README.md
└── adapters/
    ├── base.py         # PlatformAdapter ABC + MessageContext
    └── discord/
        ├── adapter.py  # Gateway connection, events, thread creation, buttons
        ├── commands.py # /setup, /help, /unlink
        └── config.py   # Discord token + message limits
```

**Locality rule:** anything platform-specific lives under
`adapters/<platform>/`. `app.py` is the only file that names specific
platforms — it's the factory that picks adapters based on which tokens
are set. Adding Telegram later = drop in `adapters/telegram/` with the
same shape.

### `CoPilotChatBridge` — now an `AppService`

Previously `AppProcess`. Now inherits `AppService`, runs its RPC server
on `Config.copilot_chat_bridge_port=8010`, and exposes two scaffolding
`@expose` methods for the backend→chat-platform direction:

- `send_message_to_channel(platform, channel_id, content)` — stub
- `send_dm(platform, platform_user_id, content)` — stub

Both currently raise `NotImplementedError` — they unlock the
architecture for future features (scheduled agent outputs piped to
Discord, etc.) without another structural change. A matching
`CoPilotChatBridgeClient` + `get_copilot_chat_bridge_client()` factory
lets other services call the bot by the same `AppServiceClient` pattern
used for `NotificationManager` and `PlatformLinkingManager`.

### Bot behaviour

- `/setup` — server only, ephemeral, returns a "Link Server" button.
Rejects DM invocations up front.
- `/help` — ephemeral usage info.
- `/unlink` — ephemeral, opens a "Settings" button pointing at
`AUTOGPT_FRONTEND_URL/profile/settings` (real unlinking needs JWT auth).
- **Thread per conversation**: @mentioning the bot in a channel creates
a thread and routes the reply there. Subsequent messages in that thread
don't need another @mention — thread subscriptions are tracked in Redis
with a 7-day TTL.
- **Batched follow-ups**: messages arriving mid-stream append to a
per-thread pending list; drained as a single follow-up turn when the
current stream ends.
- **Persistent typing indicator**: 8-second re-fire loop.
- **Per-user identity prefix**: every forwarded message tagged `[Message
sent by {name} (Discord user ID: ...)]`.
- **Platform-aware chunking**: long responses split at paragraph → line
→ sentence → word boundaries (1900 chars for Discord).
- **Link buttons** for DM link prompts and `/setup` / `/unlink`
responses.
- **Duplicate message guard**: on `DuplicateChatMessageError` the bot
stays quiet — no double response.

### Env vars

| Variable | Purpose |
|----------|---------|
| `AUTOPILOT_BOT_DISCORD_TOKEN` | Discord bot token — enables the
Discord adapter |
| `AUTOGPT_FRONTEND_URL` | Frontend base URL for link confirmation pages
|
| `REDIS_HOST` / `REDIS_PORT` | Shared with backend — session +
thread-subscription state + direct copilot stream subscription |
| `PLATFORMLINKINGMANAGER_HOST` | Cluster DNS name of the
`PlatformLinkingManager` service (RPC target) |

Gone vs. the previous REST design: `AUTOGPT_API_URL`,
`PLATFORM_BOT_API_KEY`, `SSE_IDLE_TIMEOUT`.

## How

- **Adapter pattern**: `PlatformAdapter` ABC defines `start`, `stop`,
`send_message`, `send_link`, `start_typing`, `create_thread`,
`max_message_length`, `chunk_flush_at`, etc. Each platform implements
the interface; the shared `MessageHandler` calls through it.
- **Control plane over RPC**: `PlatformAPI` (~180 lines) is a thin
facade over `PlatformLinkingManagerClient` — `resolve_server`,
`resolve_user`, `create_link_token`, `create_user_link_token`,
`stream_chat`. The bot never constructs HTTP requests or handles an API
key.
- **Streaming over Redis Streams**: `stream_chat` calls
`start_chat_turn` (backend `@expose`), receives a
`ChatTurnHandle(session_id, turn_id, user_id, subscribe_from="0-0")`,
then subscribes directly via
`stream_registry.subscribe_to_session(...)`. Yields text from
`StreamTextDelta`, terminates on `StreamFinish`, surfaces
`StreamError.errorText` to the user. No SSE parsing, no X-Session-Id
header dance.
- **Error model**: backend domain exceptions (`NotFoundError`,
`LinkAlreadyExistsError`, `DuplicateChatMessageError`) cross the RPC
boundary cleanly (all `ValueError`-based, registered in
`backend.util.exceptions`). The bot catches them by type instead of
inspecting HTTP status codes.
- **Cooperative batching**: `TargetState.processing` flag + per-target
`pending` list. Messages arriving while `processing=True` append; the
running stream's finally block loops to drain the list before releasing.
- **Typing helper for `endpoint_to_async`**: added an `@overload` so
`async def` `@expose` methods on the server type-check correctly on the
client side (the scheduler pattern avoids this by using sync `@expose`,
but the new managers are async).

## Tests

- `backend/copilot/bot/platform_api_test.py` — new. Covers resolve
(server + user), create link tokens (success + `LinkAlreadyExistsError`
propagation), stream chat (yields deltas, terminates on `StreamFinish`,
surfaces `StreamError`, propagates `DuplicateChatMessageError` and
`NotFoundError`, handles `subscribe_to_session` returning `None`).
- `poetry run pyright backend/copilot/bot/` — clean.
- `poetry run ruff check backend/copilot/bot/` — clean.
- `poetry run copilot-bot` starts and connects to Discord Gateway, syncs
slash commands.
- `/setup` in a guild → confirm on frontend → mention bot → AutoPilot
streams back in a created thread.
- Thread follow-ups work without re-mentioning.
- Spamming messages mid-stream produces one batched follow-up.
- Long responses chunk at natural boundaries.
- DM to unlinked user → "Link Account" button → confirm → DMs stream as
that user's AutoPilot.

## Stack

- Backend API: #12615 — merge first
- Frontend link page: #12624
- Infra:
[AutoGPT_cloud_infrastructure#310](https://github.com/Significant-Gravitas/AutoGPT_cloud_infrastructure/pull/310)

---------

Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
Co-authored-by: CodeRabbit <noreply@coderabbit.ai>
2026-04-29 08:12:15 +00:00
Abhimanyu Yadav
37f247c795 feat(frontend): creator dashboard page for settings v2 (SECRT-2281) (#12934)
### Why / What / How

**Why:** The creator dashboard route under settings v2 currently shows a
"Coming soon" placeholder. SECRT-2281 fills it in so creators can manage
their store submissions from one place.

**What:** Implements the full creator dashboard at
`/settings/creator-dashboard` — stats overview, desktop submissions
table, mobile submissions list, filtering/sorting, selection bar, edit
modal, and empty/loading/error states.

**How:** Page logic lives in `useCreatorDashboardPage.ts` (data fetch,
filter state, modal state, CRUD callbacks); pure transforms in
`helpers.ts`; UI broken into colocated `components/*` (one folder per
component, each ~200–400 lines). Reuses generated API hooks,
`ErrorCard`, and `EditAgentModal` from the design system. Mobile/desktop
split via Tailwind `md:` breakpoints rather than runtime detection.

### Changes 🏗️

- Replace placeholder `page.tsx` with the real dashboard, wired to
`useCreatorDashboardPage`
- Add `useCreatorDashboardPage.ts` (page-level state + handlers) and
`helpers.ts` (filter/sort/stat utilities)
- Add components: `DashboardHeader`, `DashboardSkeleton`, `EmptyState`,
`StatsOverview`, `SubmissionsList` (+ `columns/*`,
`useSubmissionSelection`), `SubmissionItem` (+ `useSubmissionItem`),
`SubmissionSelectionBar`, `MobileSubmissionsList` (+
`MobileSelectionBar`), `MobileSubmissionItem`, `ColumnFilter`
- Set document title to "Creator dashboard – AutoGPT Platform"
- Surface fetch errors via `ErrorCard` with retry; show
`DashboardSkeleton` while loading; show `EmptyState` when there are no
submissions

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [ ] I have tested my changes according to the test plan:
  - [ ] Loading state renders skeleton until submissions load
  - [ ] Empty state renders when the creator has no submissions
  - [ ] Error state renders `ErrorCard` and retry refetches the list
  - [ ] Stats overview reflects approved/pending/rejected/draft counts
- [ ] Desktop list: sort/filter by status and other columns updates the
visible rows
- [ ] Desktop list: selection bar appears on row select and clears on
reset
- [ ] Mobile list (≤ md breakpoint): renders mobile items + selection
bar
- [ ] Edit modal opens for a submission, saves, and refreshes the list
on success
  - [ ] Delete action removes the submission and updates stats
  - [ ] View action navigates to the submission's public detail
  - [ ] Submit/publish entry point opens the publish modal
  - [ ] Document title shows "Creator dashboard – AutoGPT Platform"
2026-04-28 16:51:52 +00:00
Abhimanyu Yadav
ae4a421620 fix(platform): small fixes and stagger animations on settings pages (#12937)
## Why

The new Settings v2 surfaces (preferences, api-keys, integrations,
profile) shipped with a few rough edges spotted in self-review:

- **Timezone saves silently dropped on refresh.** Backend `GET
/auth/user/timezone` resolved the user via
`get_or_create_user(user_data)` (a 5-min in-process cache keyed by the
JWT-payload dict). `update_user_timezone` only invalidates
`get_user_by_id`'s cache, so the GET kept returning the pre-save tz
until TTL expired — looked exactly like "save did nothing."
- **Confusing "Looks like you're in X" CTA on the Time zone card** that
did nothing in the common case (server tz already matched the browser
tz, so clicking it produced no dirty state).
- **Save was disabled out of the gate when server tz was `"not-set"`** —
the hook substituted the browser tz into both `formState` and
`savedState`, so they were equal and `dirty` was false.
- **Lists felt static.** No motion when API keys / integrations mount,
and the loading skeletons popped in all at once instead of handing off
cleanly to the loaded rows.
- **Profile bio textarea** corner clipped against the rounded-3xl border
and the scrollbar overflowed the rounded container.

## What

### Bug fixes
- `GET /auth/user/timezone` now reads via `get_user_by_id(user_id)` —
the same cache `update_user_timezone` already invalidates — so a save
followed by refresh shows the new tz immediately.
- `usePreferencesPage` now treats the raw server tz (`"not-set"`
included) as the saved baseline, while `formState` uses the browser tz
only as a *display* fallback. Effect: when the user has never set a tz,
Save is enabled on first paint and a single click persists the detected
tz.
- Frontend save flow swapped `setQueryData` for `invalidateQueries`,
mirroring the older `/profile/(user)/settings` page so we always re-read
the persisted value.
- Removed the auto-detect "Looks like you're in X" button + its dead
helpers.

### Animations (per Emil Kowalski's guidelines)
Added orchestrated stagger animations that run on both the loaded list
**and** its skeleton, so the loading→loaded handoff is continuous
in-position:

- **API keys list + skeleton:** 280ms ease-out `cubic-bezier(0.16, 1,
0.3, 1)`, 40ms stagger, opacity + 6px translate.
- **Integrations list + skeleton:** 300ms ease-out, 80ms stagger,
opacity + 16px translate (rows are bigger / fewer).
- Both honor `prefers-reduced-motion` via `useReducedMotion`; only
`opacity` and `transform` are animated.

### Misc polish
- Profile bio textarea: `!rounded-tr-md` so the top-right corner doesn't
fight the surrounding `rounded-3xl`, plus a thin styled scrollbar
(`scrollbar-thin scrollbar-thumb-zinc-200
hover:scrollbar-thumb-zinc-300`) that lives inside the rounded container
instead of breaking out of it.

## How

| File | Change |
| --- | --- |
| `backend/api/features/v1.py` | `get_user_timezone_route` now uses
`get_user_by_id` + `Security(get_user_id)` instead of
`get_or_create_user(user_data)` |
| `frontend/.../preferences/usePreferencesPage.ts` | Split init into
`initialFormState` (browser-fallback display) vs `initialSavedState`
(raw server value); swap optimistic `setQueryData` for
`invalidateQueries` after tz mutate |
| `frontend/.../preferences/components/TimezoneCard/TimezoneCard.tsx` |
Drop `initialValue` prop, remove auto-detect button + unused imports |
| `frontend/.../preferences/page.tsx` | Drop `savedState`/`initialValue`
wiring |
| `frontend/.../api-keys/components/APIKeyList/APIKeyList.tsx` | Wrap
rows in container `motion.div` with `staggerChildren`; per-row
`motion.div` with opacity + y variants |
|
`frontend/.../api-keys/components/APIKeyListSkeleton/APIKeyListSkeleton.tsx`
| Same stagger config so loading→loaded matches |
|
`frontend/.../integrations/components/IntegrationsList/IntegrationsList.tsx`
+ `IntegrationsListSkeleton.tsx` | Same pattern for the providers list |
| `frontend/.../profile/components/ProfileForm/ProfileForm.tsx` |
Tailwind classes only — `!rounded-tr-md` + `scrollbar-thin
scrollbar-thumb-zinc-200 hover:scrollbar-thumb-zinc-300` |

## Test plan

- [ ] On `/settings/preferences`: pick a different tz → Save →
hard-refresh → new tz still selected.
- [ ] First-time user (server tz = `not-set`): land on page, Save button
should already be enabled; click Save → toast confirms; refresh → tz
persists.
- [ ] No "Looks like you're in X" button visible.
- [ ] On `/settings/api-keys`: rows fade/slide in staggered on first
mount; loading skeleton uses the same motion.
- [ ] On `/settings/integrations`: provider groups fade/slide in
staggered; skeleton matches.
- [ ] OS "Reduce motion" enabled → no transforms, content appears
instantly on all four surfaces.
- [ ] On `/settings/profile`: bio textarea top-right corner is no longer
hard-cornered against the card; scrollbar fits inside the rounded shape.
- [ ] Existing unit tests still pass: `pnpm test:unit
src/app/\(platform\)/settings/preferences` and `.../api-keys`.
2026-04-28 16:51:40 +00:00
Zamil Majdy
2879528308 feat(backend): Redis Cluster client support (#12900)
## Why

Pre-launch scaling. Redis is currently a single-master pod — a real
SPOF, and not scalable horizontally. To move it to a sharded Redis
Cluster (via KubeBlocks in GKE), the backend has to speak the cluster
protocol.

Keeping both "standalone" and "cluster" code paths would have local dev
not reflect prod. Going **cluster-only**.

## What

- `backend.data.redis_client` now always constructs `RedisCluster`
(sync) / `redis.asyncio.cluster.RedisCluster` (async). Type aliases
`RedisClient` / `AsyncRedisClient` point at the cluster classes.
- `RedisCluster` uses the existing `REDIS_HOST` / `REDIS_PORT` as a
startup node and auto-discovers peers via `CLUSTER SLOTS`.
- Classic Redis pub/sub is broadcast cluster-wide and redis-py's async
`RedisCluster` has no `.pubsub()`; dedicated `get_redis_pubsub[_async]`
helpers return plain `(Async)Redis` clients to the seed node. All
pub/sub callers (`event_bus`, `notification_bus`,
`copilot.pending_messages`) route through these helpers.
- `rate_limit.py` MULTI/EXEC pipelines are split per-counter — daily and
weekly counters hash to different slots, which `RedisCluster` correctly
rejects as `CrossSlotTransactionError`. Per-counter `INCRBY + EXPIRE`
atomicity is preserved; the counters are logically independent budgets.
- `util/cache.py` shared-cache client is also `RedisCluster` now.
- Pre-existing mock-based unit tests updated; new `redis_client_test.py`
covers the swap.

## Local dev

`docker-compose.platform.yml` now runs **2-master Redis Cluster**
(`redis` + `redis-2`, 16384 slots split 0-8191 / 8192-16383). A one-shot
`redis-init` sidecar bootstraps it on first boot via raw `CLUSTER MEET`
+ `CLUSTER ADDSLOTSRANGE` (bundled `redis-cli --cluster create` enforces
a 3-node minimum).

This deliberately catches cross-slot bugs on a laptop rather than in
prod:

```
>>> ALL SMOKE TESTS PASS <<<
[sync] class: RedisCluster
[sync] 20 keys across slots: OK
[sync] colocated MULTI/EXEC: OK [5, 12, 1]
[sync] cross-slot MULTI/EXEC rejected as expected: CrossSlotTransactionError
[sync] EVAL single-key: OK
[sync] pub/sub (classic, broadcast): OK
[async] class: RedisCluster
[async] 15 keys across slots: OK
[async] colocated pipeline: OK
[async] pub/sub: OK
```

`rest_server` `/health` → 200, both shards have connected clients + keys
distributed 19/19 under the smoke run. `executor` boots + connects to
RabbitMQ + Redis cleanly.

For a 3-shard override (6 pods, with replicas) when you want to test
real KubeBlocks topology:
```
docker compose -f docker-compose.yml -f docker-compose.redis-cluster.yml up -d
```

## Deploy order (companion infra PR:
[cloud_infrastructure#312](https://github.com/Significant-Gravitas/AutoGPT_cloud_infrastructure/pull/312))

The existing `helm/redis` chart is updated in that PR to run as a
1-shard cluster (backwards-compatible toggle, default on). That rollout
must land before this PR's image goes live so the backend's
`RedisCluster` client has something to discover.

Sequence:
1. Infra: `helm upgrade redis` (1-shard cluster-enabled)
2. Infra: `helm upgrade rabbit-mq` (3-node cluster)
3. Backend: merge + deploy this PR
4. Follow-up: swap to KubeBlocks `redis-cluster` chart (3-shard sharded,
already staged in infra PR)

## Caveats / follow-ups

- Classic pub/sub via seed node means every node in the cluster sees
every message (broadcast). Fine at current volume; if it becomes hot,
migrate to `SPUBLISH`/`SSUBSCRIBE` (Redis 7+ sharded pub/sub).
- Per-user rate-limit counters (daily vs weekly) lost cross-counter
transactionality, but per-counter atomicity is preserved — the two
counters are independent budgets so no correctness regression.
- Local 2-master cluster crashes lose the cluster state; `redis-init`
idempotently rebootstraps.

## Checklist

- [x] Lint + format pass (`poetry run format` + `poetry run lint`)
- [x] Unit tests pass — `redis_client_test`, `redis_helpers_test`,
`event_bus_test`, `pending_messages_test`, `rate_limit_test`,
`cluster_lock_test`
- [x] Live smoke against 2-master cluster — sync + async; MULTI/EXEC;
EVAL; pub/sub; cross-slot rejection
- [x] Full stack smoke — `rest_server` /health, `executor` boot, keys
distributed across both shards
- [ ] Dev deploy (pending infra PR merge + manual validation)
2026-04-28 22:21:23 +07:00
Ubbe
1974ec6260 fix(frontend/copilot): fix streaming reconnect races, hydration ordering, and reasoning split (#12813)
## Summary

Improves Copilot/AutoPilot streaming reliability across frontend and
backend. The diff now covers the original streaming investigation issues
plus follow-up CI and review fixes from the latest merge with `dev`.

Addresses [SECRT-2240](https://linear.app/autogpt/issue/SECRT-2240),
[SECRT-2241](https://linear.app/autogpt/issue/SECRT-2241), and
[SECRT-2242](https://linear.app/autogpt/issue/SECRT-2242).

## Changes

- Fixes reasoning vs response rendering so action tools such as
`run_block` and `run_agent` do not cause assistant response text to be
hidden inside the collapsed reasoning section.
- Reworks Copilot session lifecycle handling: active-stream hydration,
resume ordering, reconnect timeout recovery, wake resync, session
deletion, title polling, stop handling, and session-switch stale
callback guards.
- Adds a per-session Copilot stream store/registry and transport helpers
to prevent duplicate resumes, duplicate sends, and cross-session
contamination during reconnect or reload flows.
- Adds pending follow-up message support and backend pending-message
safeguards, including sanitization of queued user content and
requeue-on-persist-failure behavior.
- Improves backend stream and executor robustness: active stream
registry checks, bounded cancellation drain with sync fail-close
fallback, Redis helper coverage, and updated SDK response adapter
expectations for post-tool status events.
- Adds and polishes usage-limit UI, including reset gate behavior,
backdrop blending behind the usage-limit card, and usage panel/card
coverage.
- Fixes a chat input Enter-submit race where Playwright and fast users
could fill the textarea and press Enter before React had re-enabled the
submit button, causing the visible message not to send.
- Refactors the Copilot page into smaller hooks/components and adds
focused tests around stream recovery, hydration, pending queueing,
rate-limit gates, and message rendering.

## Test plan

- [x] `poetry run format`
- [x] `poetry run pytest backend/copilot/sdk/response_adapter_test.py
backend/copilot/executor/processor_test.py`
- [x] `pnpm prettier --write` on touched frontend files
- [x] `pnpm vitest run
src/app/(platform)/copilot/components/ChatInput/__tests__/useChatInput.test.ts`
- [x] `pnpm types`
- [x] `pnpm lint` (passes with existing unrelated `next/no-img-element`
warnings)
- [ ] Full GitHub CI after latest push

## Review notes

- The Sentry review thread about unbounded cancellation cleanup is
addressed in `375ec9d5f`: cancellation now waits for normal async
cleanup but exits after `_CANCEL_GRACE_SECONDS` and falls through to the
sync fail-close path.
- The previous backend CI failures were stale test expectations around
the new `StreamStatus("Analyzing result…")` event after tool output;
tests now assert that event explicitly.
- The previous full-stack E2E failure was the Copilot input Enter race;
the input now submits from the live form value instead of depending on a
possibly stale disabled button state.

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: Nicholas Tindle <nicholas.tindle@agpt.co>
2026-04-28 15:40:37 +07:00
Zamil Majdy
932ecd3a07 fix(backend/copilot): normalize model name based on actual transport, not config shape (#12932)
## Summary

When `CHAT_USE_CLAUDE_CODE_SUBSCRIPTION=true` is paired with a populated
`CHAT_BASE_URL=https://openrouter.ai/api/v1` (e.g. left over from an
earlier OpenRouter setup), the SDK was passing the OpenRouter slug
`anthropic/claude-opus-4.7` straight through to the Claude Code CLI
subprocess. The CLI uses OAuth and ignores
`CHAT_BASE_URL`/`CHAT_API_KEY`, so it rejects the slug:

> There's an issue with the selected model (anthropic/claude-opus-4.7).
It may not exist or you may not have access to it.

The bug was in `_normalize_model_name`, which gated on
`config.openrouter_active` (config-shape check) instead of the transport
the CLI actually uses for the turn.

## Changes

- Add `ChatConfig.effective_transport` property returning `subscription`
| `openrouter` | `direct_anthropic`, detected in that priority order.
Subscription wins over OpenRouter config because the CLI subprocess uses
OAuth and ignores the OpenRouter env vars (see `build_sdk_env` mode 1).
- Switch `_normalize_model_name` to gate on `effective_transport`.
Subscription and direct-Anthropic transports both produce the
CLI-friendly hyphenated form (`claude-opus-4-7`) and reject
non-Anthropic vendors loudly.
- `_resolve_sdk_model_for_request` already routes any LD-served override
through `_normalize_model_name`, so a per-user advanced-tier override
under subscription now correctly becomes `claude-opus-4-7` instead of
the OpenRouter slug. The standard-tier \"no LD override → return None\"
behaviour is preserved.
- Update two existing service tests to assert the corrected behaviour
(Kimi LD override under subscription falls back to tier default
normalised for the CLI; Opus advanced override returns hyphenated form).

## Test plan

- [x] `poetry run pytest backend/copilot/sdk/service_helpers_test.py
backend/copilot/sdk/service_test.py backend/copilot/config_test.py -v` —
165 passed.
- [x] `poetry run pytest backend/copilot/sdk/env_test.py
backend/copilot/sdk/p0_guardrails_test.py` — 136 passed (other call
sites of `openrouter_active` unchanged).
- [x] `poetry run ruff format` + `ruff check` clean on touched files.

### New tests added (service_helpers_test.py)

- Subscription transport with OpenRouter base URL set + advanced-tier LD
override → returns `claude-opus-4-7` (not the OpenRouter slug, not
None).
- Subscription transport with OpenRouter base URL set + standard-tier no
override → returns None (existing behaviour preserved).
- Subscription transport rejects non-Anthropic vendor (`moonshotai/...`)
→ ValueError.
- `effective_transport` returns `subscription` when subscription is on
regardless of OpenRouter config; returns `openrouter` when subscription
is off and OpenRouter is fully configured; returns `direct_anthropic`
otherwise.
2026-04-28 11:40:31 +07:00
Zamil Majdy
4a567a55a4 fix(backend/copilot): pause idle timer during pending tools (#12927)
## Summary

Pause the SDK idle timer while a tool call is pending, with a 2-hour
hung-tool cap as backstop. Fixes SECRT-2239 — long-running tools (10+
min, e.g. sub-agent execution) were being silently aborted by the
10-minute idle timeout introduced in #12660.

## What changed (backend only)

- `_IDLE_TIMEOUT_SECONDS = 1800` (30 min) — soft cap when no tool
pending (raised from 10 min)
- `_HUNG_TOOL_CAP_SECONDS = 7200` (2 h) — hard cap when a tool is
pending; protects against truly hung tool calls without false-aborting
legitimate long-running ones
- `_idle_timeout_threshold(adapter)` — returns the appropriate threshold
based on whether any tool is currently pending in the adapter

Backed by 7 regression tests in
`service_test.py::TestIdleTimeoutThreshold`.

## Frontend coordination

The original cherry-pick batch included a `useStreamActivityWatchdog`
hook for client-side wire-silence detection. That hook is dropped from
this PR because it overlaps with Lluis's #12813, which ships the same
component as part of a comprehensive copilot streaming refactor. End
state on dev: his PR contributes the watchdog, this PR contributes the
backend pause + cap.

## Test plan

- 7/7 unit tests in
`backend/copilot/sdk/service_test.py::TestIdleTimeoutThreshold` pass
- pyright clean on `service.py` + `service_test.py`
- /pr-test --fix posted with native-stack run + screenshots:
https://github.com/Significant-Gravitas/AutoGPT/pull/12927#issuecomment-4328320714

## Linear

SECRT-2239
2026-04-28 09:07:16 +07:00
John Ababseh
2b28434786 feat(platform/backend): Filter store creators with approved agents (#10014)
Filtering store creators to only show profiles with an approved agent
keeps the marketplace focused on usable inventory and prevents empty
creator cards.
 
### Changes 🏗️
 
- add a `num_agents > 0` filter to `get_store_creators`
- add a regression test ensuring we only return creators with approved
agents
- keep the existing SQL injection regression tests intact after rebasing
onto `dev`
 
### Checklist 📋
 
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [ ] I have tested my changes according to the test plan:
- [ ] python3 -m pytest
autogpt_platform/backend/backend/server/v2/store/db_test.py -k
get_store_creators_only_returns_approved *(blocked: repo environment
lacks pytest and related deps)*
 
<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> Filter `get_store_creators` to creators with `num_agents > 0` and add
a test to validate the behavior.
> 
> - **Store backend**:
> - Update `get_store_creators` in `backend/server/v2/store/db.py` to
filter creators by `num_agents > 0`.
> - **Tests**:
> - Add `test_get_store_creators_only_returns_approved` in
`backend/server/v2/store/db_test.py` to verify filtering and pagination
count calls.
> 
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
c2fca584cce5a8c26dbdadd68696a0033642f193. This will update automatically
on new commits. Configure
[here](https://cursor.com/dashboard?tab=bugbot).</sup>
<!-- /CURSOR_SUMMARY -->

---------

Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Nicholas Tindle <ntindle@users.noreply.github.com>
Co-authored-by: Nicholas Tindle <nicholas.tindle@agpt.co>
Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: ntindle <8845353+ntindle@users.noreply.github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-27 22:01:24 +00:00
Zamil Majdy
5d1cdc2bad fix(backend/copilot): surface empty-success ResultMessage as stream error (SECRT-2252) (#12926)
## Summary

- Detect ghost-finished sessions where the SDK returns a `ResultMessage`
with `subtype="success"`, empty `result`, no produced content, and
`output_tokens == 0`.
- Emit `StreamError(code="empty_completion")` instead of silently
calling `StreamFinish`, so the caller (and the user) sees the failure.

## Background

Linear: [SECRT-2252](https://linear.app/agpt/issue/SECRT-2252) — SDK
silent empty completion not retried, leaving the user with a blank
stream (`start -> start-step -> finish-step -> finish`).

## Changes

- `response_adapter.py::convert_message`: in the `ResultMessage` branch,
check `_is_empty_completion()` before falling through to the existing
success path. When matched, close any open step, emit `StreamError`, and
skip `StreamFinish`.
- `response_adapter.py::_is_empty_completion`: new helper that returns
`True` only when `result` is falsy, no text/reasoning was emitted, no
tool calls were registered, no tool results were seen, and
`usage["output_tokens"]` is `0`.
- `response_adapter_test.py`: 4 new unit tests covering empty-success
(None and empty-string variants), non-empty success, and the
non-empty-tokens-but-empty-result fallthrough.

## Out of scope (per ticket)

- Retry-once behavior. This PR only surfaces the error; the caller
decides retry semantics. Follow-up work can wire automatic retry on
`code="empty_completion"`.

## Test plan

- [x] `poetry run pytest backend/copilot/sdk/response_adapter_test.py` —
all 58 tests pass (4 new + 54 existing).
- [x] `poetry run pyright backend/copilot/sdk/response_adapter.py
backend/copilot/sdk/response_adapter_test.py` — clean.

## Checklist

- [x] My code follows the style of this project.
- [x] I have added tests covering my changes.
- [x] I have updated the documentation accordingly. (N/A — internal
adapter behavior)
2026-04-27 17:24:57 +00:00
Abhimanyu Yadav
3c08b90500 feat(frontend): preferences v2 page (SECRT-2279) (#12925)
### Why / What / How

**Why** — Settings v2 needs a dedicated Preferences page covering
account info (email, password reset), time zone, and notification
preferences with a single, predictable save flow. The existing legacy
page at `/profile/(user)/settings` mixes concerns and uses `__legacy__`
UI primitives we are migrating away from. SECRT-2279.

**What** — A new preferences page at `/settings/preferences` built from
atomic / molecular design-system components. Three cards (Account, Time
zone, Notifications) share one inline Save / Discard bar at the bottom.
The page replaces the legacy settings page from a UX standpoint while
keeping the same backend mutations.

<img width="1511" height="899" alt="Screenshot 2026-04-27 at 6 43 09 PM"
src="https://github.com/user-attachments/assets/5762fc41-1654-4764-8fbf-d5dd262e031a"
/>

**How**
- **Page composition (`page.tsx`)** uses a single `usePreferencesPage`
hook that owns dirty/saved/form state. Renders `PreferencesHeader`,
`AccountCard`, `TimezoneCard`, `NotificationsCard`, and the inline
`SaveBar` below the cards.
- **Account card** — Email row shows the current address with a compact
pencil button that opens a width-constrained `Dialog` for editing
(Cancel / Update). Password row is a `NextLink` button that routes to
`/reset-password`.
- **Time zone card** — Single row inside a card: label + info-icon
tooltip on the left; small-size `Select` and the GMT offset chip on the
right. The "auto-detect" prompt shows up only when the saved tz differs
from the browser tz, rendered as a pill on the right side of the card.
- **Notifications card** — Tabs for Agents / Marketplace / Credits;
toggling a switch flips a flag in formState and enables Save.
- **Save flow** — `usePreferencesPage` keeps a `savedState` snapshot
(mirrors the old `react-hook-form` `defaultValues` capture-once
semantics) so the dirty check is fully decoupled from any backend GET
refetch. After a successful mutation, `savedState ← formState`, and the
timezone query cache gets an optimistic `setQueryData` write so the
value isn't snapped back by the (cached) GET endpoint.
- **Skeleton** — `PreferencesSkeleton` mirrors the real layout — header,
Account card with the two row shapes, Time zone single row,
Notifications tabs + toggle rows, and the Save / Discard buttons.
- **Sidebar** — Renames the entry "Settings" → "Preferences" with
`SlidersHorizontalIcon`. Profile and Creator Dashboard get clearer
affordances (`UserIcon`, `ChartLineUpIcon`).

### Changes 🏗️

- New page: `src/app/(platform)/settings/preferences/page.tsx` and
`usePreferencesPage.ts`
- New components: `AccountCard`, `TimezoneCard`, `NotificationsCard`,
`PreferencesHeader`, `PreferencesSkeleton`, `SaveBar`
- Helpers: `helpers.ts` (timezones list, GMT-offset formatter, dirty
utilities, notification-group definitions)
- Sidebar: rename "Settings" → "Preferences", swap to
`SlidersHorizontalIcon` + cleaner Profile / Creator Dashboard icons
(`SettingsSidebar/helpers.ts`)
- Tests:
- `preferences/__tests__/main.test.tsx` — page render, edit-email dialog
open/cancel, time zone info trigger, Save/Discard disabled-on-clean,
notification toggle → save submission, discard revert
- Updated `SettingsSidebar.test.tsx` and `SettingsMobileNav.test.tsx`
for the "Preferences" label

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [ ] I have tested my changes according to the test plan:
- [ ] Sidebar shows "Preferences" with the new icon; clicking routes to
`/settings/preferences`
- [ ] Account card: pencil button opens a 420px-wide dialog; Update
button stays disabled until the email differs and is valid; Cancel
closes the dialog
- [ ] Password row: "Reset password" button navigates to
`/reset-password`
- [ ] Time zone: changing the select enables Save; clicking Save
persists the value and the form keeps showing the saved value (does not
snap back), the inline GMT offset chip updates, info tooltip appears on
hover
- [ ] Auto-detect prompt appears only when saved tz ≠ browser tz;
clicking it sets the select to the browser tz
- [ ] Notifications: toggling any switch enables Save; saving flips the
flag in the request body; switching tabs preserves toggles; Discard
reverts unsaved toggles
- [ ] Save / Discard render below the cards on the right and stay
disabled until any field is dirty
  - [ ] Loading state shows the new skeleton that mirrors the layout
- [ ] `pnpm test:unit` passes (covers the page-level integration tests
above)

#### For configuration changes:

- [x] `.env.default` is updated or already compatible with my changes
- [x] `docker-compose.yml` is updated or already compatible with my
changes
- [x] I have included a list of my configuration changes in the PR
description (under **Changes**)
2026-04-27 15:13:51 +00:00
Abhimanyu Yadav
599f370206 feat(frontend): add settings v2 profile page (#12924)
### Why / What / How

**Why:** SECRT-2278 — settings v2 needs a Profile page so users can
manage how they appear on the marketplace (display name, handle, bio,
links, avatar) without hopping into the legacy settings UI.

**What:** Adds the `/settings/profile` page end-to-end:
- Form fields for display name, handle, bio, avatar, and up to 5 links —
wired to the `getV2GetUserProfile`, `postV2UpdateUserProfile`, and
`postV2UploadSubmissionMedia` endpoints.
- Bio editor gets a markdown toolbar (bold / italic / strikethrough /
link / bulleted list) with a live preview toggle that renders via
`react-markdown` + `remark-gfm`.
- Save/Discard bar with full validation (handle regex, bio length, dirty
tracking) and toast feedback for success and failure paths.
- Forward refs through the `Input` atom so consumers can target the
underlying `<textarea>` / `<input>` (needed for the toolbar's
selection/cursor manipulation).
- Comprehensive integration tests (Vitest + RTL + MSW) at the page level
plus pure-helper unit tests, in line with the project's
"integration-first" testing strategy. Coverage is reported via
`cobertura` for Codecov.

**How:**
- The toolbar applies markdown syntax by reading `selectionStart` /
`selectionEnd` from a forwarded textarea ref. To avoid the textarea
jumping to the top on click: buttons `preventDefault` on `mousedown` (so
the textarea keeps focus), and the handler captures `scrollTop` before
mutation and restores it (with `focus({ preventScroll: true })`) after
React commits the new value in the next animation frame.
- The preview pane styles markdown elements via Tailwind arbitrary child
selectors (`[&_ul]:list-disc` etc.) instead of pulling in
`@tailwindcss/typography`, since the plugin isn't installed and the
project's `prose` usage was a no-op.
- Profile data hydration tolerates nullish API fields by mapping through
`profileToFormState`, padding `links` to 3 slots so the UI always has
the initial layout.
- Tests use Orval-generated MSW handlers from `store.msw.ts`, mock
`useSupabase` to inject an authenticated user, and assert UI behavior
via Testing Library queries.

### Changes 🏗️

- New: `app/(platform)/settings/profile/__tests__/helpers.test.ts`,
`__tests__/main.test.tsx`
- Updated: `settings/profile/page.tsx`, `useProfilePage.ts`,
`helpers.ts`, plus `ProfileForm`, `ProfileHeader`, `ProfileSkeleton`,
`LinksSection`, `SaveBar`
- Updated: `settings/layout.tsx` (settings v2 chrome adjustments to host
the profile page)
- Atom change: `components/atoms/Input/Input.tsx` now forwards refs
(`HTMLInputElement | HTMLTextAreaElement`) — backward-compatible for
existing consumers

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] Open `/settings/profile` and confirm the page hydrates the
existing display name, handle, bio, avatar, and links
- [x] Edit each field and verify validation messages (empty name,
invalid handle with spaces, bio over 280 chars)
- [x] Bio markdown toolbar: select text and click Bold / Italic / Strike
— selection wraps, cursor stays in place, textarea does not scroll to
top
- [x] Bio toolbar with no selection: each button inserts the markdown
placeholder template
- [x] Click Bulleted list twice on the same line — line is prefixed with
`- ` only once
- [x] Toggle Preview — bio renders bullets, bold, italic, strikethrough,
links correctly; toolbar buttons dim and become inert
  - [x] Toggle Edit — textarea returns with the same content
- [x] Add link → 4th and 5th slots appear; the 6th attempt is blocked by
the "Limit of 5 reached" button label
  - [x] Remove link 1 — the rest reorder correctly
- [x] Avatar upload — happy path replaces the avatar; failure path
surfaces a destructive toast
- [x] Save with valid data → success toast, query invalidates, save
button disables until next edit
  - [x] Save with a server 422 → destructive toast, no state corruption
  - [x] Discard reverts every field back to the loaded profile
- [x] `pnpm test:unit` passes locally; `coverage/cobertura-coverage.xml`
shows ≥ 80% line coverage for `src/app/(platform)/settings/profile/**`
2026-04-27 10:34:09 +00:00
Otto
8786c00f9c feat(blocks): add Claude Opus 4.7 model support (#12826)
Requested by @Bentlybro

Anthropic released [Claude Opus
4.7](https://www.anthropic.com/news/claude-opus-4-7) today. This PR adds
it to the platform's supported model list.

## Why

Users and developers need access to `claude-opus-4-7` via the platform's
LLM block and API. The model is available on Anthropic's API today.

## What

- Adds `CLAUDE_4_7_OPUS = "claude-opus-4-7"` to the `LlmModel` enum
- Adds corresponding `ModelMetadata` entry: 200k context, 128k output,
price tier 3 ($5/M input, $25/M output — same as Opus 4.6)

## How

Two lines added to `llm.py`, following the exact same pattern as all
other Anthropic model additions. No migrations, no frontend changes
needed — the frontend reads model metadata from the backend's JSON
schema endpoint automatically.

Closes SECRT-2248

---------

Co-authored-by: Bentlybro <Github@bentlybro.com>
2026-04-27 07:00:00 +00:00
SymbolStar
384cbd3ccd fix(frontend): redirect www to non-www with 308 to preserve request method (#9188) (#12920)
## Summary
Fixes #9188 — redirects `www.` to non-www to prevent cookie/auth domain
mismatch.

Uses **308** (Permanent Redirect) instead of 301, which preserves the
HTTP method and request body. This is important because the middleware
matcher runs on `/auth/authorize` and `/auth/integrations/*`, where
OAuth callbacks may use POST.

Split from #12895 per reviewer request.

## Changes
- Added www→non-www redirect in Next.js middleware using
`NextResponse.redirect(url, 308)`

---------

Co-authored-by: majdyz <zamil.majdy@agpt.co>
2026-04-27 06:35:56 +00:00
SymbolStar
8be9cf70af fix(frontend): filter null query params in buildUrlWithQuery (#11237) (#12921)
## Summary
Fixes #11237 — `buildUrlWithQuery` now filters out `null` values in
addition to `undefined`, preventing them from being serialized as
literal `"null"` strings in URL query parameters.

Split from #12895 per reviewer request.

## Changes
- Added `value !== null` check alongside existing `value !== undefined`
in `buildUrlWithQuery`

---------

Co-authored-by: majdyz <zamil.majdy@agpt.co>
2026-04-27 06:31:34 +00:00
Abhimanyu Yadav
a723966e0b feat(platform): settings v2 integrations page + provider description SDK (#12911)
### Why / What / How

**Why:** The settings v2 integrations surface renders from a hardcoded
`MOCK_PROVIDERS` array — no real user credentials, no delete, no way to
connect a new service. Provider display metadata (descriptions +
supported auth types) was scattered across frontend maps with no backend
source of truth, leaving each new provider to be manually registered in
two places.

**What:** Full-featured settings v2 integrations page driven by live
backend data, plus a backend SDK extension so every provider carries a
description **and** declares its supported auth types. Settings UI uses
both to render the connect-a-service dialog: descriptions in the list,
auth types to pick the right tabs in the detail view.

**How:**
- **Credentials list** — single-fetch via `useGetV1ListCredentials`,
grouped client-side by provider, debounced (250 ms) Unicode-normalized
in-memory search (no roundtrip per keystroke), managed/system creds
filtered via the shared `filterSystemCredentials` helper from
`CredentialsInput`. Loading → skeletons that mirror the real accordion
shape, error → `ErrorCard` with retry, empty → `IntegrationsListEmpty`
with custom marquee illustration.
- **Delete flow** — `useDeleteIntegration` returns per-target `succeeded
/ failed / needsConfirmation` so the UI can name failed items and keep
them selected for one-click retry. Single + bulk both gated by
`DeleteConfirmDialog`. Per-row delete button disables + shows a spinner
via `isDeletingId` so double-clicks can't fire two requests. Success
toast names the credential ("Removed GitHub key").
- **Connect-a-service dialog** — backend-driven (`useGetV1ListProviders`
returns `ProviderMetadata[]` with description + supported_auth_types),
Emil-spec animations (150 ms ease-out step swap, 200 ms ease-out height
resize, 180 ms entry fade+slide+blur on tab swap, all respecting
`prefers-reduced-motion`). Detail view picks tab order via deterministic
`TAB_PRIORITY` (oauth → api_key → user_password → host_scoped) and
remembers last-selected tab per provider for the session.
- **OAuth tab** → `openOAuthPopup` + `getV1InitiateOauthFlow` →
`postV1ExchangeOauthCodeForTokens`
- **API key tab** → zod-validated form with
`autoComplete="new-password"` + `spellCheck=false` so browsers don't
autofill the wrong stored key → `postV1CreateCredentials`
- **Provider metadata SDK** — chainable
`ProviderBuilder.with_description(...)` +
`.with_supported_auth_types(...)` (the latter populated automatically by
`with_oauth` / `with_api_key` / `with_managed_api_key` /
`with_user_password`; explicit form reserved for legacy providers whose
auth lives outside the builder chain). `GET /integrations/providers`
upgraded from `List[str]` → `List[ProviderMetadata]` carrying both
fields.
- **Backward compat** — `BackendAPI.listProviders()` maps the new
`ProviderMetadata[]` shape down to `string[]` so the deprecated
`CredentialsProvider` (used by the builder/library credential pickers)
keeps working without ripple changes.
- **Routing** — page lives at `/settings/integrations` directly. No
feature flag gate (settings v2 layout is already on dev).

### Changes 🏗️

**Backend**
- `backend/sdk/builder.py` — `with_description()` +
`with_supported_auth_types()` chain methods; the latter is
auto-populated by every existing auth-method chain call so explicit
declaration is only needed for legacy providers.
- `backend/sdk/provider.py` — `description` + `supported_auth_types`
fields on `Provider`.
- `backend/api/features/integrations/router.py` — `GET /providers` now
returns `List[ProviderMetadata]`; calls `load_all_blocks()` (cached
`@cached(ttl_seconds=3600)`) before reading `AutoRegistry`.
- `backend/api/features/integrations/models.py` — `ProviderMetadata`
with `name + description + supported_auth_types`;
`get_provider_description` + `get_supported_auth_types` helpers reading
from `AutoRegistry`.
- 13 existing `_config.py` files updated with `.with_description(...)`:
agent_mail, airtable, ayrshare, baas, bannerbear, dataforseo, exa,
firecrawl, linear, stagehand, wordpress, wolfram, generic_webhook.
- 20 new `_config.py` files (one per provider block dir): apollo,
compass, discord, elevenlabs, enrichlayer, fal, github, google, hubspot,
jina, mcp, notion, nvidia, replicate, slant3d, smartlead, telegram,
todoist, twitter, zerobounce. Each declares
`with_supported_auth_types(...)` because their auth handlers live in
`backend/integrations/oauth/` (legacy) or are block-level
`CredentialsMetaInput` declarations — outside the builder chain.
- 1 new `backend/blocks/_static_provider_configs.py` registering
description + auth types for ~24 providers that live in shared files
(openai, anthropic, groq, ollama, open_router, v0, aiml_api, llama_api,
reddit, medium, d_id, e2b, http, ideogram, openweathermap, pinecone,
revid, screenshotone, unreal_speech, webshare_proxy, google_maps, mem0,
smtp, database). Comment documents the migration path (each entry
retires when the provider graduates to its own `_config.py`).

**Frontend**
- `src/app/(platform)/settings/integrations/page.tsx` — replaces mock
page; composes header + list + connect dialog.
-
`src/app/(platform)/settings/integrations/components/IntegrationsList/`
— list + skeleton + selection (Record<string, true> instead of Set) +
delete orchestration hook.
-
`src/app/(platform)/settings/integrations/components/ConnectServiceDialog/`
— split per the 200-line house rule into `ConnectServiceDialog`,
`ListView`, `ProviderRow`, `useMeasuredHeight`. DetailView's nested
helpers extracted to siblings: `MethodPanel`, `UnsupportedNotice`,
`ProviderAvatar`. Tabs render in deterministic priority order;
last-selected tab persisted per provider in module-scope.
-
`src/app/(platform)/settings/integrations/components/DeleteConfirmDialog/`
— new confirm dialog gating single + bulk deletes (shows up to 3 names +
remaining count for bulk).
-
`src/app/(platform)/settings/integrations/components/IntegrationsListEmpty/components/IntegrationsMarquee.tsx`
— switched from `next/image unoptimized` to plain `<img loading="lazy"
decoding="async">` for decorative logos (no LCP candidate, avoids Next
Image runtime overhead).
-
`src/app/(platform)/settings/integrations/components/hooks/useDeleteIntegration.ts`
— bulk delete now returns per-target
`succeeded/failed/needsConfirmation`; failed items stay selected for
retry; per-id pending tracking via `isDeletingId`; toast names the
credential.
-
`src/app/(platform)/settings/integrations/components/hooks/useDebouncedValue.ts`
— small reusable debounce hook (250 ms, used by both list + dialog
search).
- `src/app/(platform)/settings/integrations/helpers.ts` —
`formatProviderName` guarded against non-string input; `filterProviders`
now Unicode-normalized (NFKD + strip combining marks) so accented
queries match.
- `src/providers/agent-credentials/helper.ts` — `toDisplayName` same
`typeof string` guard.
- `src/components/contextual/CredentialsInput/helpers.ts` — loosened
`filterSystemCredentials` / `getSystemCredentials` generic constraint to
accept `title?: string | null` so it consumes `CredentialsMetaResponse`
directly.
- `src/lib/autogpt-server-api/client.ts` — `listProviders()` maps the
new shape to `string[]` for backward compat.
- `src/app/api/openapi.json` — regenerated spec includes
`ProviderMetadata` with `supported_auth_types`.

### PR feedback addressed 🛠️

Round of fixes after the first review pass:
- Bulk delete: per-item names in failure toast, failed items kept
selected for retry.
- Confirmation dialog before any delete (single or bulk) —
`DeleteConfirmDialog`.
- Per-row delete button disabled + spinner while pending (no
double-click double-fire).
- Toast names the credential ("Removed GitHub key") instead of generic
copy.
- API key input: `autoComplete="new-password"` + `spellCheck=false`;
title field `autoComplete="off"`.
- Search debounced 250 ms on both list + dialog; Unicode-normalized so
"Açai" matches "acai".
- `toDisplayName` / `formatProviderName` guarded against non-string
input (`provider.split is not a function` was reproducible).
- Skeleton mirrors the real accordion shape — no layout shift on data
load.
- Selection bar sticky position fixed for <375 px (`top-2 sm:top-0`).
- Last-selected auth tab persisted per provider for the session.
- Tabs ordered deterministically (oauth → api_key → user_password →
host_scoped) instead of insertion order.
- `useMemo` removed from `useIntegrationsList` per project rule (no
measured perf need).
- Selection state migrated from `Set<string>` to `Record<string, true>`
(idiomatic React state shape).
- ConnectServiceDialog 288 LoC → ~130 (extracted `ListView`,
`ProviderRow`, `useMeasuredHeight`); DetailView helpers → siblings.
- `next/image unoptimized` → plain `<img>` for decorative logos in
marquee + provider rows + avatar.
- `with_supported_auth_types(...)` pruned in 11 `_config.py` files where
it was redundant with `with_oauth` / `with_api_key` /
`with_managed_api_key` / `with_user_password`. Kept in legacy ones
(github, discord, google, notion, ...) where the docstring says it's
required because auth handlers live outside the builder chain.
- Tab swap + dialog step animations re-tuned vs Emil Kowalski's
animation rules: ease-out default, under 300 ms,
transform+opacity+filter only, blur-bridge to soften swap, willChange to
dodge the 1px shift, reduced-motion fallbacks via `useReducedMotion`.
- Merged latest `dev` (api-keys SECRT-2273 took dev's version, no
api-keys diff in this PR; settings layout took dev's version, no
`SETTINGS_V2` feature flag in this PR; `scroll-area` took dev's
version).

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [ ] I have tested my changes according to the test plan:
- [ ] Navigate to `/settings/integrations` — loading skeletons appear,
then user's real credentials grouped by provider.
- [ ] Type in the search box — filters client-side after 250 ms, no new
network requests (DevTools → Network stays quiet). Try "açai" with
diacritics — matches "acai" providers.
- [ ] Connect a service → dialog loads provider list with backend
descriptions; search matches name, slug, and description.
- [ ] Click a provider → dialog tweens height smoothly (no jump); header
shows provider avatar + name + description; tabs render in oauth →
api_key priority; last-used tab restored on reopen.
- [ ] Open `linear` (oauth + api_key) — switching tabs animates with a
quick fade+slide+blur entry, no flash.
- [ ] OAuth tab → "Continue with X" opens popup, completes consent,
popup closes, dialog closes, new credential appears with success toast.
- [ ] API key tab → paste a key (browser does NOT offer to autofill any
stored password), Save → toast names the credential, dialog closes.
- [ ] Delete (single) via trash icon → confirmation dialog → button
disables with spinner during the request → toast names the credential.
- [ ] Delete (bulk) via selection bar → confirmation lists up to 3 names
→ if some fail, failed ones stay selected for retry; toast lists which
failed.
  - [ ] Double-click a delete button rapidly — only one request fires.
- [ ] Managed credentials (e.g. "Use Credits for AI/ML API") do **not**
appear in the list.
- [ ] Test on a fresh account (no credentials) — `IntegrationsMarquee`
empty state renders.
- [ ] Throttle network to Slow 3G — skeleton (mirroring real shape)
visible, then list slides in.
  - [ ] Block `/api/integrations/credentials` → `ErrorCard` with retry.
- [ ] `curl /api/integrations/providers` returns `[{ name, description,
supported_auth_types }, ...]` with every provider carrying both fields.
- [ ] `prefers-reduced-motion: reduce` set → all motion collapses to
opacity-only fades.
  - [ ] On <375 px viewport — selection bar clears the mobile nav.
- [ ] `pnpm format && pnpm lint && pnpm types && pnpm test:unit` all
pass.

#### For configuration changes:
- [x] `.env.default` is updated or already compatible with my changes
- [x] `docker-compose.yml` is updated or already compatible with my
changes
- [x] I have included a list of my configuration changes in the PR
description (under **Changes**) — no flag changes in this PR.
2026-04-27 06:28:31 +00:00
Zamil Majdy
5b1d9763ed fix(backend/copilot): preserve interrupted SDK partial work on final-failure exit (#12918)
## Background

[SECRT-2275](https://linear.app/autogpt/issue/SECRT-2275). User report:
when a copilot ("autopilot") turn is interrupted by a usage-limit,
tool-call-limit, or other run interruption, the user's recent work
disappears. User described it as: "my initial message was lost 3 times
and it disappeared, then when I would say 'continue' it would do a
random old task."

Investigation surfaced two distinct failure modes. This PR addresses
both.

- **Mode 1** — rate-limit (or other pre-stream rejection) at turn start:
the user's text only ever lives in the optimistic `useChat` bubble; the
backend rejects before the message is persisted, so the bubble is a lie
and a refresh / retry would lose the text.
- **Mode 2** — long-running turn interrupted mid-stream: the entire
turn's progress (assistant text, tool calls, reasoning) vanishes on
interruption — what users describe as "the turn is gone."

## Mode 1 — frontend: restore unsent text on 429

Backend can't recover this on its own: `check_rate_limit` raises before
`append_and_save_message`, so by the time the 429 surfaces there is no
DB row to roll forward. See
`autogpt_platform/backend/backend/api/features/chat/routes.py:916-922`
(rate-limit check) and `routes.py:945` (later append-and-save).

Frontend fix in
`autogpt_platform/frontend/src/app/(platform)/copilot/useCopilotStream.ts`:
when `useChat`'s `onError` reports a usage-limit error, we

- drop the optimistic user bubble (DB has no record of it, so leaving it
would be a phantom),
- push `lastSubmittedMsgRef.current` back into the composer via the
existing `setInitialPrompt` slot — the same slot URL pre-fills use, so
`useChatInput`'s `consumeInitialPrompt` effect picks it up
automatically,
- clear `lastSubmittedMsgRef` so the dedup guard doesn't block re-send.

In-memory only; surviving a hard refresh while rate-limited is a
separate follow-up (would need localStorage persistence with TTL).

Test:
`autogpt_platform/frontend/src/app/(platform)/copilot/__tests__/useCopilotStream.test.ts`
— verifies the composer is repopulated and the optimistic bubble is
dropped on a 429.

## Mode 2 — backend: preserve interrupted partial in DB

### Root cause

The SDK retry loop in `stream_chat_completion_sdk` always rolls back
`session.messages` to the pre-attempt watermark on any exception. That
rollback is correct **before a retry** so attempt #2 doesn't duplicate
attempt #1's content. But it runs **before the retry decision is made**,
so when retries are exhausted (or no retry is attempted) the partial
work is discarded too.

Three branches of the retry loop ended in a final-failure state with
side effects worse than just losing the partial:
- `_HandledStreamError` non-transient: rollback then add error marker —
partial gone
- `Exception` with `events_yielded > 0`: rollback then break — **no
error marker added either**, so on refresh the chat looks like nothing
happened even though the user just watched tokens stream live
- `Exception` non-context-non-transient + the while-`else:` exhaustion
path: same, no marker
- Outer except (cancellation, GeneratorExit cleanup): didn't restore
captured partial

### Fix

`autogpt_platform/backend/backend/copilot/sdk/service.py`:

1. **`_InterruptedAttempt` dataclass** — holds the rolled-back `partial:
list[ChatMessage]` + optional `handled_error: _HandledErrorInfo`. Three
methods drive the contract:
- `capture(session, transcript_builder, transcript_snap,
pre_attempt_msg_count)` — slices `session.messages`, restores the
transcript, strips trailing error markers to prevent duplicate markers
after restore.
- `clear()` — drops captured state on a successful retry so outer
cleanup paths don't replay pre-retry content.
- `finalize(session, state, display_msg, retryable=...) ->
list[StreamBaseResponse]` — re-attaches partial, synthesizes
`tool_result` rows for orphan `tool_use` blocks, appends the canonical
error marker, and returns the flushed events so the caller can yield
them to the client (no double-flush).
2. **`_flush_orphan_tool_uses_to_session(session, state) ->
list[StreamBaseResponse]`** — synthesizes `tool_result` rows for any
`tool_use` that never resolved before the error so the next turn's LLM
context stays API-valid (Anthropic rejects orphan tool_use). Uses the
public `adapter.flush_unresolved_tool_calls` and returns the events for
the caller to yield.
3. **`_classify_final_failure(...) -> _FinalFailure | None`** — picks
the display message + stream code + retryable flag for the final-failure
exit. One source of truth for the in-history error marker and the
client-facing `StreamError` SSE yield so they can't drift.
4. **Consolidated post-loop emit**: the former three scattered blocks
(partial restore + redundant re-flush + two separate `yield StreamError`
sites) collapsed to one block driven by `_classify_final_failure` →
`_FinalFailure` → `finalize()` → yield events + single `StreamError`.
5. **Adapter `flush_unresolved_tool_calls`** (renamed from
`_flush_unresolved_tool_calls` to drop the `# noqa: SLF001` suppressors
on cross-module callers).

Each retry-loop rollback site calls `interrupted.capture(...)`; the
success break calls `interrupted.clear()`; the post-loop failure block
calls `interrupted.finalize(...)` exactly once.

The baseline service already preserves partial work via its existing
finally block — no change needed there.

## Tests

Backend (`backend/copilot/sdk/interrupted_partial_test.py`, new, 18
tests):

- `TestInterruptedAttemptCapture` — slice semantics + stale-marker
stripping
- `TestInterruptedAttemptFinalize` — appends partial then marker,
handles empty partial, no-op on `None` session, flushes unresolved tools
between partial and marker, returns flushed events for caller to yield
- `TestFlushOrphanToolUses` — synthesizes `tool_result` rows, returns
events, no-op on None state / no unresolved
- `TestClassifyFinalFailure` — handled_error wins, attempts_exhausted,
transient_exhausted, stream_err fallback, returns None on success path
- `TestRetryRollbackContract` — end-to-end: capture + finalize yields
the exact content the user saw streaming live plus the error marker

1022 total SDK tests pass (baseline + new).

Frontend (`useCopilotStream.test.ts`): 1 new test — `restores the unsent
text and drops the optimistic user bubble on 429 usage-limit`.

## Out of scope

- Frontend rendering tweaks for the interrupted-turn marker (existing
error-marker rendering already works).
- Refresh-survival of the unsent text in Mode 1 (would require
localStorage persistence with TTL) — separate follow-up.
- Hard process-kill / OOM where Python `finally` doesn't run — needs a
different mechanism (pod-level checkpoint sweeper).

## Checklist

- [x] My code follows the style guidelines of this project
(black/isort/ruff via `poetry run format`)
- [x] I have performed a self-review of my own code
- [x] I have added relevant unit tests
- [x] I have run lint and tests locally (1022 SDK tests pass)

## Test plan

- [ ] Verify a long-running turn that hits transient-retry exhaustion
preserves partial assistant text + tool results in chat history after
refresh
- [ ] Verify the next user message after an interrupted turn carries
enough context that the model can continue the prior task instead of
inventing a new one
- [ ] Verify a successful retry (attempt #1 fails, attempt #2 succeeds)
shows ONLY attempt #2's content (no leaked partial from #1)
- [ ] Verify hitting daily usage limit at turn start re-populates the
composer with the unsent text and removes the optimistic user bubble

---------

Co-authored-by: Claude <noreply@anthropic.com>
2026-04-25 14:21:18 +07:00
Zamil Majdy
10ea46663f fix(backend/notifications): atomic upsert + drop eager include (#12919)
## Problem

`create_or_add_to_user_notification_batch` does:
1. `find_unique(..., include={"Notifications": True})` — loads ALL
notifications for the batch (thousands for heavy AGENT_RUN users),
causing Postgres `statement_timeout` in dev.
2. Find-then-update is non-atomic — concurrent invocations either hit
`@@unique([userId, type])` violations or drop notifications.

Real Sentry: `canceling statement due to statement timeout` on this
exact query, traced to `database-manager` pod.

## Fix

Use Prisma `upsert` (atomic) and skip the eager include. Only load
notifications if the caller actually needs them (audited — the sole
caller `NotificationManager._should_batch` ignores the returned DTO and
separately fetches the oldest message via
`get_user_notification_oldest_message_in_batch`).

## Tests

- Single + existing-batch upsert paths
- Concurrent race regression

## Out of scope

Unrelated to PR #12900 (Redis Cluster migration). Separate change.
2026-04-25 13:28:28 +07:00
Zamil Majdy
06188a86a6 refactor(platform/copilot): consolidate 4 model-routing LD flags into 1 JSON flag (#12917)
## What

Replaces 4 string-valued LaunchDarkly flags with a single JSON-valued
flag for copilot model routing:

- ~~`copilot-fast-standard-model`~~
- ~~`copilot-fast-advanced-model`~~
- ~~`copilot-thinking-standard-model`~~
- ~~`copilot-thinking-advanced-model`~~

**New:** `copilot-model-routing` (JSON), keyed `{mode: {tier: model}}`:
```json
{
  "fast":     { "standard": "anthropic/claude-sonnet-4-6", "advanced": "anthropic/claude-opus-4-6" },
  "thinking": { "standard": "moonshotai/kimi-k2.6",         "advanced": "anthropic/claude-opus-4-6" }
}
```

## Why

Same pattern as the sibling consolidation in #12915 (pricing /
cost-limits flags) and the merged #12910 (tier-multipliers):

- One flag per config domain — less LD UI clutter, easier audit trail.
- Atomic updates — rotating fast.standard + thinking.standard is a
single save.
- Fewer LD entities to name, version, target, explain.
- Mirrors the now-uniform copilot-* JSON-flag shape.

## How

- `backend/util/feature_flag.py`: drop the four `COPILOT_*_MODEL` enum
values, add `COPILOT_MODEL_ROUTING`.
- `backend/copilot/model_router.py`: rewrite `resolve_model` to fetch
the JSON flag once per call and walk `payload[mode][tier]`. Missing
mode, missing tier-within-mode, non-string cell value, non-dict payload,
or LD failure all fall back to the corresponding `ChatConfig` default
(same user-visible semantics as before). `_FLAG_BY_CELL` removed
entirely; `_config_default` / `ModelMode` / `ModelTier` unchanged.
- Per-user LD targeting preserved — cohorts can still receive different
routing.
- No caching added (preserves existing uncached behaviour).
- Docstring references in `copilot/config.py` + `copilot/sdk/service.py`
updated to point at the new nested key path; one docstring in
`service_test.py` likewise.

## Operator action required BEFORE merging

This PR removes 4 LD flags and introduces 1 replacement.

1. In LaunchDarkly, create `copilot-model-routing` (type: **JSON**,
server-side only). Default variation = union of the current four string
flags, shaped as:
   ```json
   {
"fast": { "standard": "<current copilot-fast-standard-model>",
"advanced": "<current copilot-fast-advanced-model>" },
"thinking": { "standard": "<current copilot-thinking-standard-model>",
"advanced": "<current copilot-thinking-advanced-model>" }
   }
   ```
Omit any cell that's currently unset (its `ChatConfig` default will be
used).

2. Merge this PR.

3. After deploy + smoke, delete the four legacy flags:
   - `copilot-fast-standard-model`
   - `copilot-fast-advanced-model`
   - `copilot-thinking-standard-model`
   - `copilot-thinking-advanced-model`

## Testing

- `backend/copilot/model_router_test.py` rewritten — 27 tests pass:
  - LD unset / `None` payload → fallback for every cell.
  - Full JSON → each cell maps to its value (parametrized).
- Partial JSON (missing mode, missing tier-within-mode, mode value not a
dict).
  - Non-dict payloads (str / list / int / bool) → fallback + warning.
- Non-string cell values (number, list, bool, dict) → fallback +
'non-string' warning.
- Empty-string cell → fallback + 'empty string' warning (not
'non-string').
  - LD raises → fallback + warning with `exc_info`.
  - `user_id=None` → skip LD entirely.
- Single-LD-call regression guard against re-introducing per-cell flag
fan-out.
- `backend/copilot/sdk/service_test.py`: 61 tests still pass (it mocks
`_resolve_thinking_model_for_user`, so the inner flag change is
transparent).
- `black --check` / `ruff check` / `isort --check` all clean.

## Sibling

- #12915 — same consolidation pattern for stripe-price / cost-limits
flags.

## Checklist

- [x] I have read the project's contributing guide.
- [x] I have clearly described what this PR changes and why.
- [x] My code follows the style guidelines of this project.
- [x] I have added tests that prove my fix is effective or that my
feature works.
- [ ] New and existing unit tests pass locally with my changes (CI will
confirm).
2026-04-25 08:15:36 +07:00
Zamil Majdy
2deac2073e fix(block_cost_config): audit + correct stale LLM/block rates + migrate generic ReplicateModelBlock to COST_USD (#12912)
## Why

PR #12909's pricing refresh was sourced from aggregators (pricepertoken,
blog mirrors) instead of provider pricing pages. Follow-up audit against
**official provider docs** caught **22 stale entries** — 9 LLM token
rates + 12 non-LLM block rates + 1 block that needed a code refactor to
bill dynamically. Also flagged by Sentry: Mistral models were sitting on
the wrong provider's rate table.

Cross-verified JS-rendered pages (docs.x.ai, DeepSeek, Kimi) via
agent-browser.

## Corrections applied

### LLM TOKEN_COST (9 entries)

| Model | Old | New | Reason |
|---|---|---|---|
| `GPT5` | 94/750 | **188/1500** | Was OpenAI Batch API rate; Standard
is $1.25/$10 |
| `DEEPSEEK_CHAT` | 42/63 | **21/42** | Unified to deepseek-v4-flash at
$0.14/$0.28 (Sept 2025) |
| `DEEPSEEK_R1_0528` | 82/329 | **21/42** | Same v4-flash routing |
| `MISTRAL_LARGE_3` | 300/900 | **300/900** (restored after brief 75/225
detour) | Routes via OpenRouter ($2/$6), not Mistral direct |
| `MISTRAL_NEMO` | 3/6 → 23/23 | **5/5** | Routes via OpenRouter
($0.035/$0.035); Mistral-direct $0.15 doesn't apply |
| `KIMI_K2_0905` | 82/330 | **90/375** | Matches K2 family $0.60/$2.50 |
| `KIMI_K2_5` | 90/450 | **66/300** | OpenRouter pass-through $0.44/$2 |
| `KIMI_K2_6` | 143/600 | **112/698** | OpenRouter pass-through
$0.7448/$4.655 |
| `META_LLAMA_4_MAVERICK` | 30/90 | **75/116** | Groq $0.50/$0.77
(deprecated 2026-02-20) |

### Non-LLM BLOCK_COSTS — rate corrections (11 entries)

Under-billing fixes:
- `AIVideoGeneratorBlock` (FAL) SECOND 3 → **15 cr/s**
- `CreateTalkingAvatarVideoBlock` (D-ID) RUN 15 → **100 cr**
- Nano Banana Pro/2 across 3 blocks: RUN 14 → **21 cr**
- `UnrealTextToSpeechBlock` RUN 5 → **COST_USD 150 cr/$** (block now
emits `chars × $0.000016`)

Over-billing fixes:
- `IdeogramModelBlock` default 16 → **12**, V_3 18 → **14**
- `AIImageEditorBlock` FLUX_KONTEXT_MAX 20 → **12**
- `ValidateEmailsBlock` 250 → **150 cr/$**
- `SearchTheWebBlock` 100 → **150 cr/$**
- `GetLinkedinProfilePictureBlock` 3 → **1 cr**

### Non-LLM BLOCK_COSTS — block refactored for dynamic billing (1 entry)

- **`ReplicateModelBlock`** (the generic "run any Replicate model"
wrapper) migrated from flat RUN 10 cr → **COST_USD 150 cr/$**. Block now
uses `client.predictions.async_create + async_wait` instead of
`async_run(wait=False)` so it can read `prediction.metrics.predict_time`
and bill `predict_time × $0.0014/s` (Nvidia L40S mid-tier, where most
popular public models run).

Additionally (addressing CodeRabbit's critical review on this refactor):
`async_wait()` returns normally regardless of terminal status — it
doesn't raise on `failed`/`canceled` like the old `async_run` did. The
block now explicitly checks `prediction.status` after `async_wait()` and
raises `RuntimeError` on `failed` (with `prediction.error` as context)
or `canceled` **before** `merge_stats`, so failed runs are never billed
for partial compute time.

**Why this matters:** flat 10 cr was 10–500× under-billing long
video/LLM runs (users could wire in a $50/hr A100 Llama inference and
pay us $0.10). It was also 20× over-billing trivial SDXL runs. Now
scales with real compute time AND no longer bills failed predictions.

### Documentation-only

- **Grok legacy models** (grok-3, grok-4-0709, grok-4-fast,
grok-code-fast-1): dropped from docs.x.ai's public pricing page but
still callable via the API. Added inline comment noting this; rates kept
at their verified launch pricing.
- **Mistral routing**: added comment explaining why TOKEN_COST for
MISTRAL_* is the OpenRouter safety floor (not Mistral-direct) since
`ModelMetadata.provider = "open_router"` for all Mistral entries.

## How

- For each entry, opened the **official provider pricing page** directly
and computed `our_cr = round(1.5 × provider_usd × 100)`.
- For JS-rendered pages (docs.x.ai, api-docs.deepseek.com), used
agent-browser headless to render + extract rates from the DOM.
- Migrated 2 blocks (`UnrealTextToSpeechBlock`, `ReplicateModelBlock`)
from flat RUN to COST_USD — the Replicate migration touched the block's
SDK interaction.
- Updated 2 FAL-video unit tests that asserted the old `3 cr/s` rate.
- Updated 3 stale test assertions: 2 for Unreal TTS (still on
`characters` cost_type) + 1 for ZeroBounce (old 250 cr).

## Known remaining risk (explicitly out of scope)

- **`ReplicateFluxAdvancedModelBlock`** not migrated — bounded to Flux
models ($0.04–$0.08), flat 10 cr stays within 1.25–2.5× margin. Separate
PR if desired.
- **AgentMail** on free tier (1 RUN). When paid pricing publishes,
revisit.
- **Live Replicate API verification**: mitigated via 9 unit tests
covering the refactored path (`async_create` version-vs-model branching,
metrics-based billing emission, failed/canceled raises,
zero/missing-metrics no-emission, `async_wait` ordering), and SDK
signature confirmed via `inspect.signature` — but no real API call
executed. A smoke test on a cheap model before merge is still
recommended.

## Test plan

- [x] `poetry run pytest backend/data/block_cost_config_test.py
backend/executor/block_usage_cost_test.py
backend/blocks/claude_code_cost_test.py
backend/blocks/cost_leak_fixes_test.py
backend/blocks/block_cost_tracking_test.py
backend/copilot/tools/helpers_test.py
backend/blocks/replicate/replicate_block_cost_test.py -q` — all passing
(80+ tests).
- [x] Sources: openai.com/api/pricing, claude.com/pricing,
api-docs.deepseek.com, mistral.ai/pricing,
platform.kimi.ai/docs/pricing, docs.x.ai, groq.com/pricing,
replicate.com, fal.ai, d-id.com, ideogram.ai, zerobounce.net, jina.ai,
unrealspeech.com, enrichlayer.com.
- [ ] Live Replicate API call to verify `predictions.async_create +
async_wait + metrics.predict_time` path.
2026-04-25 06:10:16 +07:00
Zamil Majdy
24406dfcec refactor(platform): consolidate 6 LD flags into 2 JSON flags (#12915)
## What

Consolidates two groups of LaunchDarkly flags into single JSON-valued
flags, matching the pattern established by `copilot-tier-multipliers`
(merged in #12910):

**Stripe prices** — 4 string flags → 1 JSON flag:
- ~~`stripe-price-id-basic`~~ / ~~`-pro`~~ / ~~`-max`~~ /
~~`-business`~~
- **New:** `copilot-tier-stripe-prices` (JSON)
  ```json
  { "PRO": "price_xxx", "MAX": "price_yyy" }
  ```

**Cost limits** — 2 number flags → 1 JSON flag:
- ~~`copilot-daily-cost-limit-microdollars`~~ /
~~`copilot-weekly-cost-limit-microdollars`~~
- **New:** `copilot-cost-limits` (JSON)
  ```json
  { "daily": 625000, "weekly": 3125000 }
  ```

## Why

- One flag to manage per config domain (LD UI less cluttered, easier
audit trail).
- Atomic updates — e.g., rotating Pro + Max prices happens in a single
save.
- Fewer LD entities to name, version, target, and explain.
- Mirrors the just-merged `copilot-tier-multipliers` shape so the whole
pricing/limits config is uniform.

## How

- `get_subscription_price_id(tier)` now parses
`copilot-tier-stripe-prices` and looks up `tier.value` — returns `None`
when the flag is unset, non-dict, tier key missing, or value isn't a
non-empty string.
- `get_global_rate_limits` uses a new sibling
`_fetch_cost_limits_flag()` helper (60s cache, `cache_none=False`) that
extracts `daily` / `weekly` int keys independently and falls back to the
existing `ChatConfig` defaults when any key is missing / non-int /
negative. A broken `daily` doesn't wipe out `weekly` (or vice versa).
- Tests rewritten to mock the new JSON shapes + cover partial / invalid
/ missing-key fallbacks.

## ⚠️ Operator action required BEFORE merging

This PR **removes 6 LD flags** and introduces 2 replacements. To avoid a
pricing/rate-limit outage, do this in LaunchDarkly first:

1. Create `copilot-tier-stripe-prices` (type: **JSON**). Default
variation = union of the current `stripe-price-id-*` values:
   ```json
{ "PRO": "<current stripe-price-id-pro>", "MAX": "<current
stripe-price-id-max>" }
   ```
   Omit BASIC / BUSINESS if those flags are unset today.

2. Create `copilot-cost-limits` (type: **JSON**). Default variation =
the current two flags' values:
   ```json
{ "daily": <current daily microdollars>, "weekly": <current weekly
microdollars> }
   ```

3. Merge this PR.

4. After deploy + smoke test, delete the six legacy flags:
   - `stripe-price-id-{basic,pro,max,business}`
   - `copilot-daily-cost-limit-microdollars`
   - `copilot-weekly-cost-limit-microdollars`

## Testing

- Backend unit tests: `pytest backend/copilot/rate_limit_test.py
backend/data/credit_subscription_test.py
backend/api/features/subscription_routes_test.py` — rewritten to
exercise the JSON flag shapes + fallback paths; passes locally.
- `black --check` / `ruff check` / `isort --check` — all clean.

## Checklist

- [x] I have read the project's contributing guide.
- [x] I have clearly described what this PR changes and why.
- [x] My code follows the style guidelines of this project.
- [x] I have added tests that prove my fix is effective or that my
feature works.
- [ ] New and existing unit tests pass locally with my changes (CI will
confirm).
2026-04-25 06:08:09 +07:00
Zamil Majdy
000ddb007a dx: use $REPO_ROOT in pr-test skill instead of hardcoded absolute path (#12914)
## Summary
- `.claude/skills/pr-test/SKILL.md` referenced
`/Users/majdyz/Code/AutoGPT/.ign.testing.{lock,log}` in 5 places, which
breaks the skill for anyone else who clones the repo.
- Replaced with `$REPO_ROOT`, which is already defined in Step 0 as `git
-C "$WORKTREE_PATH" worktree list | head -1 | awk '{print $1}'`. That
resolves to the main/primary worktree from any sibling worktree,
preserving the original "always pin the lock to the root checkout so all
siblings see the same file" semantics.
- No behavior change for the existing user; repo becomes portable for
everyone else.

## Test plan
- [x] `grep -n "/Users/majdyz" .claude/skills/pr-test/SKILL.md` returns
only the two intentional mentions in the "never paste absolute paths
into PR comments" warning.
- [x] `$REPO_ROOT` is defined in Step 0 before any Step 3.0 usage.
2026-04-24 23:10:20 +07:00
Zamil Majdy
408b205515 feat(platform): LD-configurable rate-limit multipliers + relative UI display (#12910)
## Summary

- **Backend (`copilot/rate_limit`)** — ``TIER_MULTIPLIERS`` is now
float-typed and resolvable through a new LaunchDarkly flag
``copilot-tier-multipliers``. The integer defaults live on as
``_DEFAULT_TIER_MULTIPLIERS`` and are merged with whatever LD returns
(missing / invalid keys inherit defaults; LD failures fall back to
defaults without raising). ``get_global_rate_limits`` now honours the
flag per-user and casts ``int(base * multiplier)`` so downstream
microdollar math stays integer even when LD hands back a fractional
multiplier (e.g. 8.5×). Cached for 60 s via ``@cached(ttl_seconds=60,
maxsize=8, cache_none=False)`` to match the pattern in
``get_subscription_price_id``.
- **Backend (`api/features/v1`)** — ``SubscriptionStatusResponse`` gains
``tier_multipliers: dict[str, float]``, populated for the same set of
tiers that make it into ``tier_costs`` so hidden tiers never get a
rendered badge.
- **Frontend (`SubscriptionTierSection`)** — drops the hard-coded ``"5x"
/ "20x"`` strings from ``TIERS`` and introduces
``formatRelativeMultiplier(tierKey, tierMultipliers)``: the lowest
*visible* multiplier becomes the baseline (no badge), every other tier
renders ``"N.Nx rate limits"`` relative to it. Fractional LD values like
8.5× round to one decimal.

The admin rate-limit page (``/admin/rate-limits``) keeps the static
``TIER_MULTIPLIERS`` defaults — it's admin-facing, infrequently viewed,
and fine to lag the LD value until next deploy (noted in-code).

Related upstream: this PR stacks logically after #12903 (which added the
``MAX`` tier + LD-configurable prices) but does **not** require it —
each PR can merge in either order. No schema changes, no migration.

## Test plan

- [x] ``poetry run black backend/... --check`` + ``poetry run ruff check
backend/...`` pass
- [x] ``pnpm format`` pass (modified files unchanged)
- [x] New backend tests: ``TestGetTierMultipliers`` (defaults, LD
override, invalid JSON, unknown tier / non-positive values, LD failure)
— **5 / 5 pass**
- [x] New backend test:
``TestGetGlobalRateLimitsWithTiers::test_ld_override_applies_fractional_multiplier``
— **pass**
- [x] ``backend/copilot/rate_limit_test.py`` — non-DB subset **72 / 72
pass**; ``TestGetUserTier`` / ``TestSetUserTier`` require the full
test-server fixture (Redis + Prisma) and are not run in this worktree —
same behaviour on clean ``dev``
- [x] ``backend/api/features/subscription_routes_test.py`` — **40 / 40
pass** (includes new
``test_get_subscription_status_tier_multipliers_ld_override``)
- [x] Frontend vitest targeted suite — **51 / 51 pass**
- ``helpers.test.ts`` — new ``formatRelativeMultiplier`` cases
(lowest-tier null, integer ratio, fractional ratio, hidden-tier null,
fractional LD)
- ``SubscriptionTierSection.test.tsx`` — three new cases for relative
badges, rebasing when the lowest tier is hidden, fractional LD overrides
2026-04-24 22:05:55 +07:00
Zamil Majdy
f8c123a8c3 feat(blocks): dynamic COST_USD billing + close 8 cost-leak surfaces (#12909)
## Why

`ClaudeCodeBlock` was a flat `RUN, 100 cr/run` entry when real cost is
**$0.02–$1.50/run**. Plugging that leak surfaced the question "are other
blocks doing the same?" — an audit found **7 more cost-leak surfaces**.
This PR closes all of them atomically so the cost pipeline is uniform
post-#12894.

## What

### 1. ClaudeCodeBlock → COST_USD 150 cr/$ (the headline)

Claude Code CLI's `--output-format json` already returns
`total_cost_usd` on every call, rolling up Anthropic LLM + internal
tool-call spend. Block now emits it via `merge_stats`:
```python
total_cost_usd = output_data.get("total_cost_usd")
if total_cost_usd is not None:
    self.merge_stats(NodeExecutionStats(
        provider_cost=float(total_cost_usd),
        provider_cost_type="cost_usd",
    ))
```
Registered as `COST_USD, 150 cr/$` — matches the 1.5× margin baked into
every `TOKEN_COST` entry.

### 2. Exa websets — ~40 blocks instrumented

Registered as `COST_USD 100 cr/$` but **never emitted `provider_cost`**
→ ran wallet-free. Added `extract_exa_cost_usd` + `merge_exa_cost`
helpers in `exa/helpers.py` and threaded `merge_exa_cost(self,
response)` through every Exa SDK call across 14 files (59 call sites).
Future-proof: lights up as soon as `exa_py` surfaces `cost_dollars` on
webset response types.

### 3. AIConditionBlock — registered under LLM_COST

Full LLM block with token-count instrumentation already in place, but
**no `BLOCK_COSTS` entry at all** → wallet-free. One-line fix: added to
the LLM_COST group next to AIConversationBlock.

### 4. Pinecone × 3 — added BLOCK_COSTS

- `PineconeInitBlock` + `PineconeQueryBlock`: 1 cr/run RUN (platform
overhead; user pays Pinecone directly).
- `PineconeInsertBlock`: ITEMS scaling with `len(vectors)` emitted via
`merge_stats`.

### 5. Perplexity Sonar (all 3 tiers) → COST_USD 150 cr/$

Block already extracted OpenRouter's `x-total-cost` header into
`execution_stats.provider_cost`; just tagged it `cost_usd` and flipped
the registry. **Deep Research was under-billing up to 30×** ($0.20–$2.00
real vs flat 10 cr).

### 6. CodeGenerationBlock (Codex / GPT-5.1-Codex) → COST_USD 150 cr/$

Block computes USD from `response.usage.input_tokens / output_tokens`
using GPT-5.1-Codex rates ($1.25/M in + $10/M out) and emits `cost_usd`.
Was flat 5 cr for arbitrary-length generations.

### 7. VideoNarrationBlock (ElevenLabs) → COST_USD 150 cr/$

Block computes USD from `len(script) × $0.000167` (Starter tier per-char
price) and emits `cost_usd`. **Was under-billing ~25–30× on long
scripts** (5K-char narration: flat 5 cr vs ~$0.83 real = 125 cr).

### 8. Meeting BaaS FetchMeetingData → COST_USD 150 cr/$

Join block keeps its flat 30 cr commit. FetchMeetingData now extracts
`duration_seconds` from the response metadata, computes USD via
`duration × $0.000192/sec`, and emits `cost_usd`. Long meetings (hours)
no longer fit inside the 30 cr deposit.

## Why 150 cr/$

Matches the **1.5× margin already baked into `TOKEN_COST` for every
direct LLM block**:

| Model | Real | Our rate (per 1M) | Markup |
|---|---|---|---|
| Claude Sonnet 4 | $3/$15 | 450/2250 cr | 1.5× |
| GPT-5 | $2.50/$10 | 375/1500 cr | 1.5× |
| Gemini 2.5 Pro | $1.25/$5 | 187/750 cr | 1.5× |

Applying the same ratio to `total_cost_usd` ≡ `cost_amount=150` (1 cr ≈
$0.01 → 100 cr/$ pass-through × 1.5× = 150).

## Test plan

- [x] **Unit**: new `claude_code_cost_test.py` (9 tests) + existing
`exa/cost_tracking_test.py` (16 tests) + full cost pipeline. **119/119
pass**.
- [x] `poetry run ruff format` + `poetry run ruff check backend/` —
clean.
- [ ] Live E2E: real ClaudeCode / Perplexity Deep Research / Codex run
with balance delta verification (post-merge).

## Follow-ups (not in this PR)

- `exa_py` SDK update to surface `cost_dollars` on Webset response types
(upstream) — unlocks real billing for the 40 webset blocks.
- Replicate suite: migrate per-model RUN entries to COST_USD via
`prediction.metrics["predict_time"] × per-model $/sec`.
2026-04-24 22:05:42 +07:00
Abhimanyu Yadav
34374dfd55 feat(frontend): Settings v2 API keys page (SECRT-2273) (#12907)
### Why / What / How

**Why:** The Settings v2 API keys page was a UI-only stub with 100 mock
rows, a noop "Create Key" button, noop delete buttons, and no
empty/loading states. Users couldn't actually manage their keys from the
new Settings UI. Ships SECRT-2273.

**What:** Replaces the mock with a working page: paginated list
(15/page) with infinite scroll, create flow with one-time plaintext
reveal, single + batch revoke with confirmation dialogs, per-key details
dialog, skeleton loader, animated empty state, toast + mutation-loading
feedback, and responsive header.



https://github.com/user-attachments/assets/bc576de3-0369-4e73-b945-c66c142ebfe5

<img width="397" height="860" alt="Screenshot 2026-04-24 at 11 26 53 AM"
src="https://github.com/user-attachments/assets/ed8681ea-7d16-40cc-96f7-72d798857229"
/>


**How:**
- **Backend** adds a new `GET /api/api-keys/paginated` route returning
`{ items, total_count, page, page_size, has_more }`. The legacy `GET
/api/api-keys` is untouched so the existing profile page keeps working.
The list fn runs `find_many` + `count` in parallel and filters to
`ACTIVE` status by default so revoked keys stay hidden.
- **Frontend** fetches via TanStack Query. Right now the hook consumes
the legacy endpoint with client-side slicing (15/page) so the page works
against staging today; once the paginated route ships we swap to the
generated `useGetV1ListUserApiKeysPaginatedInfinite` hook that's already
in the regenerated client.
- All new UI lives in `src/app/(platform)/settings/api-keys/components/`
— no legacy components reused. Shared primitives (Dialog, Form, Toast,
Skeleton, InfiniteScroll, BaseTooltip) come from the atoms/molecules
design system.
- Empty state uses a vertical marquee of ghost key-cards (framer-motion,
translateY 0→-50% on a duplicated stack, linear easing, symmetric mask
fade). Respects `prefers-reduced-motion`.
- Settings layout ScrollArea switched to `h-full` on mobile and
`md:h-[calc(100vh-60px)]` on desktop to remove a double scrollbar that
appeared when the mobile nav took space above the fixed-height scroll
region.

### Changes 🏗️

**Backend**
- `GET /api/api-keys/paginated` — new route, page + page_size query
params, `ListAPIKeysPaginatedResponse`.
- `list_user_api_keys_paginated` — new data fn, gathers find_many +
count, default ACTIVE-only filter.
- Existing `/api/api-keys` routes untouched.

**Frontend (settings/api-keys)**
- `page.tsx` + `components/APIKeyList/`, `APIKeyRow/`, `APIKeysHeader/`,
`APIKeySelectionBar/` — real-data wiring, drop mock array.
- `components/hooks/` — `useAPIKeysList`, `useCreateAPIKey`,
`useRevokeAPIKey`.
- `components/CreateAPIKeyDialog/` — zod-validated form + success view
with copy.
- `components/DeleteAPIKeyDialog/` — confirm with loading state; single
+ batch.
- `components/APIKeyInfoDialog/` — shows masked key, scopes,
description, created/last_used.
- `components/APIKeyListEmpty/` +
`APIKeyListEmpty/components/APIKeyMarquee.tsx` — animated empty state.
- `components/APIKeyListSkeleton/` — 6-row skeleton.

**Other**
- `settings/layout.tsx` — responsive ScrollArea height (fixes
double-scrollbar on mobile).
- `components/ui/scroll-area.tsx` — optional `showScrollToTop` FAB.
- `__tests__/placeholder-pages.test.tsx` — drop api-keys from
placeholder list.
- `AGENTS.md` — Phosphor `-Icon` suffix convention note.
- `api/openapi.json` — regenerated with new paginated endpoint.

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [ ] I have tested my changes according to the test plan:
  - [ ] Page loads → skeleton → list with real keys
- [ ] Empty state renders with the vertical marquee (and stays static
with `prefers-reduced-motion`)
- [ ] Create key dialog: name + description + permissions validates;
success view shows plaintext once + copy works; closing resets state
- [ ] Revoke single key via row trash icon → confirm dialog → toast on
success → row disappears
  - [ ] Batch-revoke via selection bar → confirm dialog → all revoked
- [ ] Info icon next to each key opens the details dialog (scopes,
timestamps, masked key)
- [ ] Infinite scroll loads more rows when scrolling past page 1 (≥16
keys)
- [ ] Mobile (<640px): single scrollbar, Create Key button below title
at size=small
- [ ] Desktop (md+): same layout as before, scroll-to-top FAB appears
after scrolling

#### For configuration changes:
- [x] `.env.default` is updated or already compatible with my changes
- [x] `docker-compose.yml` is updated or already compatible with my
changes
- [x] I have included a list of my configuration changes in the PR
description (under **Changes**)
2026-04-24 14:08:18 +00:00
Abhimanyu Yadav
2cb52e5d19 feat(frontend): add Settings v2 page layout behind SETTINGS_V2 flag (SECRT-2272) (#12885)
### Why / What / How

**Why:** The Settings area is getting a redesign (per Figma
[Settings-Page](https://www.figma.com/design/YGck0Hb0GEgFzwbX47kSNs/Settings-Page?node-id=1-2)).
Ticket SECRT-2272 covers just the shell so content/forms for each
section can land in follow-up PRs without blocking on the nav
restructure. v1 at `/profile/settings` must stay intact for end users
during the rollout.

**What:** Adds a new parallel Settings hub at `/settings` (dedicated
sidebar + 7 placeholder sub-routes) behind a new `SETTINGS_V2`
LaunchDarkly flag. Default `false` so nothing changes for users until
the flag flips. Backend is untouched.


https://github.com/user-attachments/assets/dd680eaf-3d41-4a9a-87f3-d06d536a2503


**How:**
- New `Flag.SETTINGS_V2 = "settings-v2"` added to `use-get-flag.ts` with
`defaultFlags[Flag.SETTINGS_V2] = false`. Gate the whole route group at
`layout.tsx` via existing `FeatureFlagPage` HOC which redirects to
`/profile/settings` when the flag is off.
- `SettingsSidebar` replicates the Figma spec (237px, 7 items at 217×38,
`gap-[7px]`, rounded-[8px], active `bg-[#EFEFF0]` + text `#1F1F20` Geist
Medium, inactive text `#505057` Geist Regular, icon 16px Phosphor
light/regular at `#1F1F20`). Colors + typography use the canonical
tokens exported by Figma (zinc-50 `#F9F9FA`, zinc-200 `#DADADC` for the
right-border, etc.).
- `SettingsNavItem` is extracted as its own component and owns its
per-item entrance variant.
- Per-link loading indicator uses Next.js 15's `useLinkStatus()` hook —
spinner appears on the right of the clicked item and clears
automatically once the target page renders.
- `SettingsMobileNav` (< md breakpoint): sidebar hides; a pill trigger
with the current section's icon + label opens a Radix Popover listing
all 7 sections.
- Entrance animations via framer-motion, tuned to Emil Kowalski's
guidelines — `cubic-bezier(0, 0, 0.2, 1)` ease-out, all durations ≤
280ms, only `transform` and `opacity`, `useReducedMotion` disables
movement but keeps fade. Sidebar items stagger in (40ms offset). Main
content re-animates on every route change via `key={pathname}`.
- All 7 placeholder pages render the section title (Poppins Medium 22/28
via `variant="h4"`, `#1F1F20`) + "Coming soon" copy; they are
intentionally client components to avoid hook-order issues with the
client-side flag gate in the layout.

### Changes 🏗️

- `src/services/feature-flags/use-get-flag.ts`: register
`Flag.SETTINGS_V2` + default `false`
- `src/app/(platform)/settings/layout.tsx`: flag gate + responsive shell
+ route-keyed content animation
- `src/app/(platform)/settings/page.tsx`: client-side redirect to
`/settings/profile`
- `src/app/(platform)/settings/components/SettingsSidebar/`:
  - `SettingsSidebar.tsx` — aside with staggered entrance
- `SettingsNavItem.tsx` — per-item Link + icon + label + loader
(extracted)
- `useSettingsSidebar.ts` — hook mapping nav items with `isActive` from
`usePathname`
- `helpers.ts` — typed nav item config (label / href / Phosphor icon) ×
7
-
`src/app/(platform)/settings/components/SettingsMobileNav/SettingsMobileNav.tsx`:
mobile Popover trigger
- 7 placeholder pages: `profile`, `creator-dashboard`, `billing`,
`integrations`, `preferences`, `api-keys`, `oauth-apps`

**Follow-up PRs will migrate real content into each tab.** LaunchDarkly
flag key `settings-v2` must be created in the LD dashboard before
enabling for users.

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] `NEXT_PUBLIC_FORCE_FLAG_SETTINGS_V2=true` → `/settings` redirects
to `/settings/profile`, sidebar renders 7 items with "Profile" active
- [x] Click each nav item → URL changes, active item highlights, content
pane re-animates, per-link spinner shows during navigation
- [x] Viewport < 768px → sidebar hides, mobile pill trigger opens
Popover with all 7 items; selecting one navigates and closes
- [x] Without the flag env override, `/settings` redirects to
`/profile/settings` (v1 unchanged)
  - [x] `pnpm types` clean; prettier clean on touched files
- [x] Manual a11y pass with `prefers-reduced-motion` enabled — fade
remains, translations disabled

#### For configuration changes:
- [x] `.env.default` is updated or already compatible with my changes
*(no new env vars required; existing `NEXT_PUBLIC_FORCE_FLAG_*` pattern
covers local override)*
- [x] `docker-compose.yml` is updated or already compatible with my
changes *(no docker changes)*
- [x] I have included a list of my configuration changes in the PR
description *(LaunchDarkly dashboard must have `settings-v2` flag
created before enabling; no other config changes)*
2026-04-24 10:39:54 +00:00
Zamil Majdy
ab88d03b13 refactor(backend/integrations): clearer naming + docs for managed-cred sweep (#12908)
## Why

Review comments on #12883 (thanks @Pwuts) surfaced a few spots where the
managed-credential plumbing's names and docstrings didn't match what the
code actually does:

- `_read_or_create_profile_key` suggests "read from any source or create
new", but only migrates the legacy
`managed_credentials.ayrshare_profile_key` side-channel — it doesn't
read an existing managed credential. (That check lives in the outer
`_provision_under_lock`.)
- Docstrings refer to "the startup sweep" in several places — there's no
startup hook; the sweep runs on `/credentials` fetches.
- `is_available` / `auto_provision` relationship wasn't explicit;
readers couldn't tell whether `is_available` was a config check or a
liveness check, or which of the two gates the sweep checks first.

## What

Naming + docstring cleanup. **Zero behavior changes.**

- Rename `_read_or_create_profile_key` →
`_migrate_legacy_or_create_profile_key` with docstring explaining why it
doesn't re-check the managed cred.
- Replace "startup sweep" → "credentials sweep" everywhere.
- `ManagedCredentialProvider` class docstring now names the two gates:
1. `auto_provision` — does this provider participate in the sweep at
all?
  2. `is_available` — are the required env vars / secrets set?
- `is_available` docstring now spells out: what it checks (env vars),
what it does NOT check (upstream health), and that it's only consulted
when `auto_provision=True`.
- `ensure_managed_credentials` docstring defines "credentials sweep",
when it fires, how the per-user in-memory cache works.
- Module-level docstring drops the stale "non-blocking background task"
wording (#12883 made the sweep bounded-await).

## How

4 files, all backend:
- `backend/integrations/managed_credentials.py`
- `backend/integrations/managed_providers/ayrshare.py`
- `backend/integrations/managed_providers/ayrshare_test.py`
- `backend/api/features/integrations/router.py`

Tests: 13/13 Ayrshare tests pass against the rename.

## Checklist

- [x] Follows style guide
- [x] Existing tests still pass (no functional change)
- [x] No new tests needed — pure rename + docstring change
2026-04-24 16:22:09 +07:00
An Vy Le
3aa72b4245 feat(backend/copilot): inline picker-backed inputs via run_block + accept AgentInputBlock subclasses (#12880)
### Why / What / How

**Why:** Resolves #12875. CoPilot's agent-builder was hardcoding Google
Drive file IDs into consuming blocks' `input_default` instead of wiring
an `AgentGoogleDriveFileInputBlock`. A beta user hit this across **13
saved versions** of one agent. Root causes:

1. `validate_io_blocks` only accepted the literal base `AgentInputBlock`
/ `AgentOutputBlock` IDs, so even when CoPilot used a specialized
subclass like `AgentGoogleDriveFileInputBlock` as the only input, the
validator forced it to keep a throwaway base alongside — entrenching the
anti-pattern.
2. Running a Drive consumer directly via CoPilot's `run_block` silently
failed because the auto-credentials flow (picker attaches
`_credentials_id`) existed only in the graph executor, never in
CoPilot's direct-execution path.
3. Drive picker guidance lived in `agent_generation_guide.md` instead of
on the blocks themselves, so it duplicated and drifted from the code.
4. Observed in a live session: when asked to read a private sheet,
CoPilot refused with "share publicly or use the builder" instead of
calling `run_block` and letting the picker render — the prompt rule was
buried and the fallback path (omitted required picker field) returned a
generic schema preview.

**What:** Four coordinated platform + CoPilot improvements. No
block-specific validator rules, no Drive-specific code in UI or prompt.

**How:**

#### 1. `validate_io_blocks` subclass support

Accepts any block with `uiType == "Input"` / `"Output"` (populated from
`Block.block_type` at registration). `AgentGoogleDriveFileInputBlock`,
`AgentDropdownInputBlock`, `AgentTableInputBlock`, etc. stand alone.
Base-ID fallback preserved for call sites that pass a minimal blocks
list.

#### 2. Inline picker via `run_block`

- Extracted `_acquire_auto_credentials` from
`backend/executor/manager.py` into shared
`backend/executor/auto_credentials.py` (exports
`acquire_auto_credentials` + `MissingAutoCredentialsError`).
- Wired it into `backend/copilot/tools/helpers.py::execute_block`. When
`_credentials_id` is present, the block executes with creds injected
(chained flows work). When missing/null, `execute_block` returns the
existing `SetupRequirementsResponse` — frontend's `FormRenderer` renders
the picker inline via the existing
`GoogleDrivePickerField`/`GoogleDrivePickerInput`. On pick, the LLM
re-invokes `run_block` with the populated input — same continuation
pattern as OAuth-missing-credentials. No new response types, no new
continuation tool, no new frontend component.
- `run_block` now short-circuits to `SetupRequirementsResponse` when
missing required fields include a picker-backed field, skipping the
schema-preview round trip the LLM would otherwise take.
- `get_inputs_from_schema` spreads the full property schema (`**schema`)
instead of whitelisting — any `format` / `json_schema_extra` / custom
widget config flows through to the generic custom-field dispatch on the
frontend. Future picker formats (date pickers, file pickers, etc.) work
without backend changes.
- Frontend `SetupRequirementsCard/helpers.ts` uses index-signature
passthrough for arbitrary schema keys — no widget-specific code in that
layer.

#### 3. `validate_only` parameter on `run_block`

`run_block(id, {})` is not always a safe probe — for blocks with zero
required inputs, it executes. New `validate_only: true` parameter
returns `BlockDetailsResponse` (schema + missing-input list) without
executing, rendering picker cards, or charging credits. Same response
shape as the existing schema preview — no new branch, just an extra
condition on the existing one. LLM uses this for pre-flight when it's
unsure whether a block has required inputs.

#### 4. Block-local picker guidance

Agent-generation picker guidance relocated from the guide onto the
blocks themselves — surfaced at `find_block` time, exactly when the LLM
decides to wire a picker-backed consumer:

- `GoogleDriveFileField` (shared factory for every Drive field on
Sheets/Docs/etc.) appends a standard hint to the caller's description
covering: feed from the specialized input block, never hardcode (even
one parsed from a URL), picker is the only credential source.
- `AgentGoogleDriveFileInputBlock`'s block description now covers when
it's required, the `allowed_views` mapping, wiring direction, and a
concrete link-shape example.
- `agent_generation_guide.md` loses the dedicated 71-line Drive section.
The IO-blocks section now tells the LLM specialized subclasses satisfy
the requirement and carry their own usage guidance in block/field
descriptions — read them when `find_block` surfaces a match.
- New "Picker-backed inputs via `run_block`" section in the CoPilot
prompt, written generically (picker fields detected via `format` /
`auto_credentials` schema hints, no provider names hardcoded) — covers:
don't ask the user for URLs/IDs, don't refuse private-resource asks,
chained picker objects pass through as-is.
- Sharpened `MissingAutoCredentialsError` message so when a bare ID
reaches execution, the error explicitly tells the LLM the picker renders
inline (not "ask the user for something").

### Changes 🏗️

- `backend/copilot/tools/agent_generator/validator.py` —
`_collect_io_block_ids` + subclass-aware `validate_io_blocks`.
- `backend/executor/auto_credentials.py` (new) — shared
`acquire_auto_credentials` + `MissingAutoCredentialsError`.
- `backend/executor/manager.py` — imports from the shared module, drops
the local copy.
- `backend/copilot/tools/helpers.py` — `execute_block` calls
`acquire_auto_credentials`, merges kwargs, releases locks in `finally`,
returns `SetupRequirementsResponse` on missing creds.
`get_inputs_from_schema` spreads the full property schema.
- `backend/copilot/tools/run_block.py` — picker-field short-circuit +
`validate_only` parameter.
- `backend/copilot/prompting.py` — "Picker-backed inputs via
`run_block`" + "Pre-flight with `validate_only`" sections.
- `backend/blocks/google/_drive.py` — `GoogleDriveFileField` appends the
agent-builder hint to every Drive consumer's description.
- `backend/blocks/io.py` — `AgentGoogleDriveFileInputBlock` description
expanded.
- `backend/copilot/sdk/agent_generation_guide.md` — Drive section
removed, IO-blocks subclass note expanded.
- `frontend/.../SetupRequirementsCard/helpers.ts` — index-signature
passthrough for arbitrary schema keys; schema fields propagate into the
generated RJSF schema.
- Tests: new `TestExecuteBlockAutoCredentials` (4 cases) +
`validate_only` + picker-short-circuit cases in `run_block_test.py`;
`manager_auto_credentials_test.py` moved to new import path; 6 new
frontend cases in `SetupRequirementsCard/__tests__/helpers.test.ts`
covering schema passthrough.
- Also: one-line hoist of `import secrets` in
`backend/integrations/managed_providers/ayrshare.py` — ruff E402
introduced by #12883 was blocking our lint post-merge.

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] Backend unit suites: validator_test (48), helpers_test (40),
run_block_test (19), manager_auto_credentials_test (15) — **all green**
- [x] Frontend `SetupRequirementsCard` helpers — **75/75 pass**
(including 6 new passthrough cases)
- [x] `poetry run format` (ruff + isort + black) clean on touched files
(pre-existing pyright errors in unrelated `graphiti_core` /
`StreamEvent` / etc. files not introduced by this PR)
- [x] Live CoPilot chat on dev-builder confirmed the setup card renders
`custom/google_drive_picker_field` for a Drive consumer block called via
`run_block`
- [x] Live agent-generation confirmed CoPilot creates a subclass-only
agent (`AgentGoogleDriveFileInputBlock` → `GoogleSheetsReadBlock` →
`AgentOutputBlock`) with no throwaway base `AgentInputBlock`

#### For configuration changes:
- [x] N/A — no config changes

---------

Co-authored-by: majdyz <zamil.majdy@agpt.co>
2026-04-24 13:05:11 +07:00
Zamil Majdy
cc1f692fec feat(platform): add MAX tier + LD-configurable pricing + hide unconfigured tiers (#12903)
## What

Introduces a new `MAX` tier slot between `PRO` and `BUSINESS`
(self-service $320/mo at 20× capacity), routes every self-service tier's
Stripe price ID through LaunchDarkly, and hides tiers from the UI when
their price isn't configured. `BUSINESS` stays in the enum at 60× as a
reserved/future self-service slot (hidden by default until its LD price
flag is set). ENTERPRISE stays admin-managed.

## Tier shape after this PR

| Enum | UI label | Multiplier | LD price flag | Surfaced in UI by
default |
|---|---|---|---|---|
| `FREE` | Basic | 1× | `stripe-price-id-basic` | no (flag unset) |
| `PRO` | Pro | 5× | `stripe-price-id-pro` | yes (already live) |
| `MAX` **(new)** | Max | 20× | `stripe-price-id-max` | no (flag unset
until $320 price ready) |
| `BUSINESS` | Business | 60× | `stripe-price-id-business` | no
(reserved / future) |
| `ENTERPRISE` | — | 60× | — (admin-managed) | no (Contact-Us only) |

## Prisma

- Added `MAX` between `PRO` and `BUSINESS` in `SubscriptionTier`.
- Migration `add_subscription_tier_max/migration.sql` uses `ALTER TYPE
... ADD VALUE IF NOT EXISTS 'MAX' BEFORE 'BUSINESS'` (transactional
since PG 12). No data migration — no rows currently on BUSINESS via
self-service flows.

## Backend

- `get_subscription_price_id` flag map covers
`FREE`/`PRO`/`MAX`/`BUSINESS`. ENTERPRISE returns `None`.
- `GET /credits/subscription.tier_costs` only includes tiers whose LD
price ID is set. Current tier always present as a safety net.
- `POST /credits/subscription` routes by LD-resolved prices instead of
hard-coding `tier == FREE`:
- Target `FREE` + `stripe-price-id-basic` unset → legacy
cancel-at-period-end (unchanged behaviour).
- Target has LD price → modify in-place when user has an active sub,
else Checkout Session.
- Priced-FREE users with no sub fall through to Checkout (admin-granted
DB-flip shortcut gated on `current_tier != FREE`).
- `sync_subscription_from_stripe` + `get_pending_subscription_change`
cover FREE/PRO/MAX/BUSINESS in the price-to-tier map so every tier's
Stripe webhook reconciles cleanly.
- Pending-tier mapping collapsed into a single membership check.
- `TIER_MULTIPLIERS`: `FREE=1, PRO=5, MAX=20, BUSINESS=60,
ENTERPRISE=60`.

## Frontend

- UI labels: FREE→"Basic", MAX→"Max", BUSINESS→"Business" (PRO
unchanged). `TIER_ORDER` now `[FREE, PRO, MAX, BUSINESS, ENTERPRISE]`.
- `SubscriptionTierSection` filters by `tier_costs` — any tier without a
backend-provided price is hidden (current tier always visible).
- `formatCost` surfaces "Free" only when `FREE` is actually `$0`;
non-zero `stripe-price-id-basic` renders `$X.XX/mo`.
- Admin rate-limit display lists all five tiers with multiplier badges.

## LaunchDarkly flag actions (operator)

- **New:** `stripe-price-id-basic` → FREE tier. Set to `""` or a `$0`
Stripe price.
- **New:** `stripe-price-id-max` → MAX tier. Point at the `$320` Stripe
price when you launch the Max tier.
- **Unchanged:** `stripe-price-id-pro` (PRO), `stripe-price-id-business`
(BUSINESS — leave unset until you're ready for the 60× Business tier).
- Base rate limits stay on `copilot-daily-cost-limit-microdollars` /
`copilot-weekly-cost-limit-microdollars` (Basic's limit; everything else
= × tier multiplier).

## Out of scope

- Subscription-required onboarding screen / middleware gating (separate
PR).
- "Pricing available soon" vs Stripe-failure disambiguation in the UI
(follow-up).

## Testing

- Backend: 213 tests across `subscription_routes_test.py`,
`credit_subscription_test.py`, `rate_limit_test.py`,
`admin/rate_limit_admin_routes_test.py` — all passing.
- Frontend: 91 tests across `credits/` + `admin/rate-limits/` — all
passing.
- Fresh-backend manual E2E on the pre-MAX commit confirmed tier-hiding
works (`tier_costs` returns only the current tier when LD flags are
unset).

## Checklist

- [x] I have read the project's contributing guide.
- [x] I have clearly described what this PR changes and why.
- [x] My code follows the style guidelines of this project.
- [x] I have added tests that prove my fix is effective or that my
feature works.
- [ ] New and existing unit tests pass locally with my changes (CI will
confirm).
2026-04-24 11:11:33 +07:00
Zamil Majdy
be61dc4304 fix(backend): use {schema_prefix} in raw SQL migrations instead of hardcoded 'platform.' (#12905)
### Why / What / How

**Why.** Backend CI was failing at startup with `relation
"platform.AgentNode" does not exist`. Prisma's `migrate deploy` uses the
`schema.prisma` datasource, which doesn't declare a schema, so when
`DATABASE_URL` has no `?schema=platform` query param (as in CI / raw
Supabase), Prisma creates tables in `public` — but the lifespan
migration `backend.data.graph.migrate_llm_models` hardcoded
`platform."AgentNode"` in its raw SQL and crashed the boot.

**What.** Switched `migrate_llm_models` to use the
`execute_raw_with_schema` helper and the `{schema_prefix}` placeholder —
the same pattern already used by the sibling
`fix_llm_provider_credentials` migration in the same file. The helper in
`backend/data/db.py` reads the schema from `DATABASE_URL` at runtime and
substitutes `"platform".` or an empty prefix, so the query works in both
dev (schema=platform) and CI / raw Supabase (public).

**How.**
- Template change: `UPDATE platform."AgentNode"` → `UPDATE
{{schema_prefix}}"AgentNode"` (f-string double-brace escape so
`{schema_prefix}` survives to `.format()` inside
`execute_raw_with_schema`).
- Replace `db.execute_raw(...)` with `execute_raw_with_schema(...)`;
drop the now-unused `prisma as db` import.
- Regression test: mocks `execute_raw_with_schema` and asserts every
emitted query contains `{schema_prefix}` and no longer contains
`platform."AgentNode"`.

### Audit

Audited the other three lifespan migrations in
`backend/api/rest_api.py::lifespan_context`:
- `backend.data.user.migrate_and_encrypt_user_integrations` — uses
Prisma ORM, no raw SQL. OK.
- `backend.data.graph.fix_llm_provider_credentials` — already uses
`query_raw_with_schema` + `{schema_prefix}`. OK.
- `backend.integrations.webhooks.utils.migrate_legacy_triggered_graphs`
— uses Prisma ORM, no raw SQL. OK.

Also grepped the whole backend for `platform."` in Python files —
`migrate_llm_models` was the only offender; the other hits were
unrelated string content (docstrings, error messages, test data).

### Changes

- `autogpt_platform/backend/backend/data/graph.py`: `migrate_llm_models`
now uses `execute_raw_with_schema` with the `{schema_prefix}`
placeholder; unused `prisma as db` import dropped.
- `autogpt_platform/backend/backend/data/graph_test.py`: added
`test_migrate_llm_models_uses_schema_prefix_placeholder` regression
test.

### Checklist

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] Ran `migrate_llm_models` under mocked `execute_raw_with_schema` —
all 7 emitted UPDATE queries contain `{schema_prefix}` and none hardcode
`platform."AgentNode"`.
- [x] Verified the f-string double-brace escape by evaluating the
template and running `.format(schema_prefix=...)` — substitution is
correct for both `"platform".` and empty-prefix (public-schema) cases.
- [x] `poetry run pyright backend/data/graph.py` clean (pre-existing
pyright error on `backend/api/features/v1.py:834` on `origin/dev` is
unrelated).
- [x] Grepped the whole backend for other hardcoded `platform."..."`
raw-SQL occurrences — none found.

#### For configuration changes:
- [x] `.env.default` is updated or already compatible with my changes
(N/A — no config changes)
- [x] `docker-compose.yml` is updated or already compatible with my
changes (N/A — no config changes)
2026-04-24 10:00:22 +07:00
Zamil Majdy
575f75edf4 refactor(platform): migrate Ayrshare to standard managed-credential flow (#12883)
## Why

Beta user report: AutoPilot told them to sign up for Ayrshare themselves
— which AutoGPT actually manages — because AutoPilot inferred the
requirement from the block description string rather than any structured
schema. Root cause: Ayrshare was the only block family whose
"credential" lived in a bespoke
`UserIntegrations.managed_credentials.ayrshare_profile_key` side channel
and whose blocks declared **no** `credentials` field. `find_block` /
`resolve_block_credentials` had nothing to show the LLM, so the LLM
guessed.

(An initial commit added a runtime `gh` CLI bootstrap for a separate "gh
isn't installed in the sandbox" report — that work was empirically
verified unnecessary and reverted; see the commit history for the bench
results.)

## What

**Ayrshare now goes through the standard managed-credential flow:**

- New `AyrshareManagedProvider` alongside the existing
`AgentMailManagedProvider`. Provisions the per-user profile as
`APIKeyCredentials(provider="ayrshare", is_managed=True)` via the shared
`add_managed_credential` path. Reuses any legacy
`managed_credentials.ayrshare_profile_key` value on first provision so
existing users keep their linked social accounts.
- `AyrshareManagedProvider.is_available()` returns `False` so the
`ensure_managed_credentials` startup sweep **never** auto-provisions
Ayrshare (profile quota is a real per-user subscription cost). New
public `ensure_managed_credential(user_id, store, provider)` helper lets
the `/api/integrations/ayrshare/sso_url` route provision on demand,
reusing the same distributed Redis lock + upsert path as AgentMail.
- New `ProviderBuilder.with_managed_api_key()` method registers
`api_key` as a supported auth type without the env-var-backed default
credential that `with_api_key()` creates — so the org-level Ayrshare
admin key cannot leak to blocks as a "profile key".
- `BaseAyrshareInput` gains a shared `credentials` field; all 13 social
blocks inherit it. Each `run()` now takes `credentials:
APIKeyCredentials`; the inline `get_profile_key` guard + "please link a
social account" error is gone. Standard `resolve_block_credentials`
pre-run check owns the "not connected" path, returning a normal
`SetupRequirementsResponse`.
- **Migration-ordering safety:** `post_provision` hook on
`ManagedCredentialProvider` clears the legacy `ayrshare_profile_key`
field **only after** `add_managed_credential` has durably stored the
managed credential. If persistence fails, the legacy key stays intact so
a retry can reuse it — covered by `TestMigrationOrderingSafety`.
- New public `IntegrationCredentialsStore.get_user_integrations()` —
reads no longer have to reach past the `_get_user_integrations` privacy
fence or abuse `edit_user_integrations` as a pseudo-read.
- `/api/integrations/ayrshare/sso_url` collapses from a 60-line
provision-then-sign dance to: pre-flight `settings_available()`,
`ensure_managed_credential`, fetch the credential, sign a JWT.
- `IntegrationCredentialsStore.set_ayrshare_profile_key` removed — the
managed credential is now the only write path.
- Legacy `UserIntegrations.ManagedCredentials.ayrshare_profile_key`
field is retained so the managed provider can migrate existing users on
first provision; removing the field is a follow-up once rollout has
propagated.

## How

After this PR, `find_block` returns Ayrshare blocks with a structured
`credentials_provider: ['ayrshare']`. AutoPilot sees the credential
requirement the same way it sees GitHub's or AgentMail's, calls
`run_block`, and gets a plain `SetupRequirementsResponse` when the
managed credential has not been provisioned yet. No more
description-string speculation; the whole Ayrshare flow is the normal
flow.

The Builder's `AyrshareConnectButton` (`BlockType.AYRSHARE`) still works
— it hits the same endpoint, now a thin wrapper over the managed
provider — so users still get the "Connect Social Accounts" popup for
OAuth'ing individual social networks.

## Test plan

- [x] `poetry run pytest backend/blocks/test/test_block.py -k "ayrshare
or PostTo"` — 26/26 pass.
- [x] `poetry run pytest
backend/integrations/managed_providers/ayrshare_test.py` — 10/10 pass.
- [x] `poetry run pytest
backend/api/features/integrations/router_test.py` — 21/21 pass.
- [x] `poetry run pyright` on all touched backend files — 0 errors.
- [x] Runtime sanity: `find_block` on `PostToXBlock` lists
`credentials_provider: ['ayrshare']` in the JSON schema.
- [ ] Manual QA in preview: connect social account via Builder's
"Connect Social Accounts" button → post to X via CoPilot end-to-end.
- [ ] Verify existing users with
`managed_credentials.ayrshare_profile_key` continue to work without
re-linking.
2026-04-24 09:37:38 +07:00
Zamil Majdy
0f6eea06c4 feat(platform/backend): dynamic BlockCostType (SECOND/ITEMS/COST_USD/TOKENS) + E2B/FAL migration (#12894)
## Why

PR #12893 shipped flat-floor credit charges so no provider sits
wallet-free. This PR is the next step: make dynamic pricing actually
dynamic. Blocks that scale with walltime, item count, provider-reported
USD, or token volume now get billed based on captured execution stats
instead of a fixed floor.

Before this PR `BlockCostType` only had `RUN` / `BYTE` / `SECOND`, and
`SECOND` was dead code — no caller ever passed `run_time > 0`, so every
per-second entry evaluated to 0. This PR wires the stats plumbing
through, adds the cost-type variants that cover the real billing models
our providers charge on, and migrates blocks across the codebase to use
them.

## What

### Machinery

- `BlockCostType` gains `ITEMS`, `COST_USD`, `TOKENS`. `BlockCost` gains
`cost_divisor: int = 1` so SECOND/ITEMS/TOKENS can express "1 credit per
N units" without fractional amounts.
- `block_usage_cost(..., stats: NodeExecutionStats | None = None)` —
pre-flight (no stats) dynamic types return 0 so the balance check isn't
blocked on unknown-future cost; post-flight (stats populated) they
consume captured execution stats.
- `TokenRate` model + `TOKEN_COST` table (~60 models: Claude family,
GPT-5 family, Gemini 2.5, Groq/Llama, Mistral, Cohere, DeepSeek, Grok,
Kimi, Perplexity Sonar). Rates are credits per 1M tokens with input /
output / cache-read / cache-creation split.
- `compute_token_credits(input_data, stats)` — reads
`stats.input_token_count / output_token_count / cache_read_token_count /
cache_creation_token_count`, multiplies by `TOKEN_COST[model]`, ceils to
integer credits. Falls back to flat `MODEL_COST[model]` for unmapped
models (no silent under-billing).
- `billing.charge_reconciled_usage(node_exec, stats)` — runs
post-flight, charges positive delta / refunds negative delta. RUN-only
blocks produce zero delta (no-op). Swallows `InsufficientBalanceError` +
unexpected errors so reconciliation never poisons the success path.
- Pre-flight balance guard — dynamic-cost blocks (0 pre-flight charge)
are blocked when the wallet is non-positive. Closes Sentry `r3132206798`
(HIGH).
- Reconciliation fires `handle_low_balance` on positive delta so users
still get alerted after post-flight reconciliation.

### Block migrations — cost-type changes

| Provider / block family | Old | New | Cost type |
|---|---|---|---|
| All LLM blocks (Anthropic / OpenAI / Groq / Open Router / Llama API /
v0 / AIML, via `LLM_COST` list) | RUN, flat per-model from `MODEL_COST`
| `TOKEN_COST` per-token rate table (input / output / cache-read /
cache-creation) | **TOKENS** |
| Jina `SearchTheWebBlock` | RUN, 1 cr | 100 cr / $ (≈ 1 cr per $0.01
call) | **COST_USD** |
| ZeroBounce `ValidateEmailsBlock` | RUN, 2 cr | 250 cr / $ (≈ 2 cr per
$0.008 validation) | **COST_USD** |
| Apollo `SearchOrganizationsBlock` | RUN, 2 cr flat | 1 cr / 2 orgs
(divisor=2) | **ITEMS** |
| Apollo `SearchPeopleBlock` (no enrich) | RUN, 10 cr flat | 1 cr /
person | **ITEMS** |
| Apollo `SearchPeopleBlock` (enrich_info=true) | RUN, 20 cr flat | 2 cr
/ person | **ITEMS** |
| Firecrawl (all blocks — Crawl, MapWebsite, Search, Extract, Scrape,
via `ProviderBuilder.with_base_cost`) | RUN, 1 cr | 1000 cr / $ (1 cr
per Firecrawl credit ≈ $0.001) | **COST_USD** |
| DataForSEO (KeywordSuggestions, RelatedKeywords, via `with_base_cost`)
| RUN, 1 cr | 1000 cr / $ | **COST_USD** |
| Exa (~45 blocks, via `with_base_cost`) | RUN, 1 cr | 100 cr / $ (Deep
Research $0.20 → 20 cr) | **COST_USD** |
| E2B `ExecuteCodeBlock` / `InstantiateCodeSandboxBlock` /
`ExecuteCodeStepBlock` | RUN, 2 cr flat | 1 cr / 10 s walltime
(divisor=10) | **SECOND** |
| FAL `AIVideoGeneratorBlock` | RUN, 10 cr flat | 3 cr / walltime s |
**SECOND** |

### Cost-leak fixes — interim values (flagged 🔴 CONSERVATIVE INTERIM in
Notion)

Separate from the type migrations above, these 3 providers had real API
costs but were under-billed (or wallet-free):

| Provider / block | Old | New | Cost type | Plan for proper fix |
|---|---|---|---|---|
| Stagehand (`StagehandObserve` / `Act` / `Extract`, via
`with_base_cost`) | RUN, 1 cr | 1 cr / 3 walltime s (divisor=3) |
**SECOND** | Have blocks emit `provider_cost` USD (session_seconds ×
$0.00028 + real LLM USD) → migrate to `COST_USD 100 cr/$`. |
| Meeting BaaS `BaasBotJoinMeetingBlock` (via `@cost` decorator
override) | RUN, 5 cr | RUN, 30 cr | RUN | Surface meeting duration on
`FetchMeetingData` response → migrate Join to `SECOND` or `COST_USD`
post-flight. |
| AgentMail (~37 blocks, via `with_base_cost`) | **0 cr (unbilled)** |
RUN, 1 cr | RUN | Revisit when AgentMail publishes paid-tier pricing
(currently beta). |

### UI

- `NodeCost.tsx` dynamic labels: RUN → `N /run`, SECOND → `~N /sec` (or
`~N / Xs` with divisor), ITEMS → `~N /item` (or `/ X items`), COST_USD →
`~N · by USD`, TOKENS → `~N · by tokens` (tooltip explains cache
discount).
- Floor amounts prefixed with `~` for dynamic types so users see an
estimate, not a hard guarantee.

## How

The resolver split is the key design decision. Instead of charging the
"true" cost entirely post-flight (which would let a user burn credits
they don't have), pre-flight returns a safe estimate:
- RUN: full `cost_amount` (same as before — backwards compatible).
- SECOND/ITEMS/COST_USD: `0` when stats aren't populated yet.
- TOKENS: `MODEL_COST[model]` as a flat floor from the existing rate
table.

Post-flight, the executor calls `charge_reconciled_usage`, which
evaluates the same resolver with stats and charges the positive delta
(or refunds the negative delta). RUN blocks get a 0-delta no-op; dynamic
blocks get their actual charge. Failure modes are bounded: insufficient
balance is logged (not raised; reconciliation must never poison a
success), unexpected errors are swallowed and alerted via Discord.

TOKENS routes through a dedicated `compute_token_credits` helper so the
rate table (`TOKEN_COST`) can grow organically without touching resolver
logic. Models not yet in `TOKEN_COST` fall back to the flat `MODEL_COST`
tier.

Migration for providers with a real USD spend (Exa, Firecrawl,
DataForSEO, Jina Search, ZeroBounce) is a one-line `_config.py` change
via the extended `ProviderBuilder.with_base_cost`. Each block's `run()`
populates `provider_cost` from the response (Exa's `cost_dollars.total`,
Firecrawl's `credits_used`, etc.) via `merge_stats`, and the post-flight
resolver multiplies by `cost_amount` credits/$.

## Test plan

- [x] 92/92 cost-pipeline tests pass — `block_usage_cost_test.py`,
`billing_reconciliation_test.py`, `manager_cost_tracking_test.py`,
`block_cost_config_test.py`.
- [x] Deep E2E against live stack (real DB, `database_manager` RPC): 8/8
scenarios pass — RUN pre-flight, dry-run no-charge, TOKENS refund, ITEMS
scaling, ITEMS zero-items short-circuit, COST_USD exact + ceil
semantics, pre-flight balance guard. Report:
https://github.com/Significant-Gravitas/AutoGPT/pull/12894#issuecomment-4307672357
- [x] `poetry run ruff check` / `ruff format` / `pnpm format` / `pnpm
lint` / `pnpm types` — clean.
- [x] Manual UI: `NodeCost.tsx` renders `~N · by tokens` for
AITextGeneratorBlock, `~N · by USD` for Jina/Exa/Firecrawl.

## Follow-ups (not in this PR)

- Stagehand / Meeting BaaS / Ayrshare: expose provider-side unit cost
(session-seconds, meeting duration, platform analytics credits) to
migrate from interim flat/walltime to fully dynamic `COST_USD`.
- Replicate / Revid: walltime-based billing once response cost is piped
through.
- AgentMail: final rate once paid tier is published.
2026-04-24 08:45:39 +07:00
Zamil Majdy
43b38f6989 fix(backend/copilot): surface non-zero E2B exits as real results, not sandbox errors (#12904)
## Why

`gh auth status` looked flaky in the E2B sandbox. Not actually flaky: it
fails deterministically when the user has not connected GitHub (or the
token is missing/expired), and our wrapper disguises that legitimate
exit-1 as a sandbox infrastructure failure.

Root cause: E2B's `sandbox.commands.run()` raises `CommandExitException`
for **any** non-zero exit. We caught it as a generic `Exception` and
returned an `ErrorResponse` with message:

```
E2B execution failed: Command exited with code 1 and error:
{stderr}
```

When the model runs `gh auth status 2>&1`, stderr is redirected to
stdout — so `exc.stderr` is empty **and** `exc.stdout` (which carries
the real info, e.g. "You are not logged into any GitHub hosts") is
discarded. The model sees a generic infra failure, can't tell it's an
auth-check signal, and prompts the user with broken-looking errors
instead of calling `connect_integration(provider="github")`.

Compare: the local bubblewrap path already handles non-zero exits
correctly by returning a `BashExecResponse` with `exit_code` set. The
E2B path was asymmetric.

## What

- Import `CommandExitException` and catch it explicitly in
`_execute_on_e2b` before the generic handler.
- Return a `BashExecResponse` with the real `exit_code`, `stdout`, and
`stderr` from the exception (scrubbed of injected secret values, same as
the success path).
- Extract shared scrub/build logic into `_build_response` to avoid
duplicating it across the success and exit-exception branches.
- Keep `TimeoutException` and the catch-all `except Exception` for real
infra failures.

## How

Result shape now matches bubblewrap: non-zero exit is a valid result,
not an error. The model sees:

```
message: "Command executed with status code 1"
exit_code: 1
stdout: "You are not logged into any GitHub hosts. ..."
stderr: ""
```

instead of the prior cryptic "E2B execution failed" message.

## Test plan

- [x] New unit test `test_nonzero_exit_returned_as_bash_exec_response`
in `bash_exec_test.py` — mocks `sandbox.commands.run` to raise
`CommandExitException`, asserts `BashExecResponse` with correct
`exit_code`, and verifies secret scrubbing on both `stdout` and
`stderr`.
- [x] `poetry run pytest backend/copilot/tools/bash_exec_test.py` — 5
passed.
- [x] `poetry run pyright` on changed files — 0 errors.
- [x] `poetry run ruff` — clean.
2026-04-24 07:49:57 +07:00
Nicholas Tindle
10e421cd3e fix(platform): resolve autopilot beta blockers (SECRT-2266/2267/2268/2269) (#12874)
### Why / What / How

**Why:** A beta user spent significant time trying to build and run
agents that read Google Sheets. Four separate failures compounded on
their session — all already open in Linear as SECRT-2266 through
SECRT-2269. Three in-flight PRs each addressed a piece but conflicted on
the same files (`backend/data/model.py`, `backend/blocks/_base.py`,
`autogpt_libs/.../types.py`), so landing them individually would have
been churn. One of the four reported issues (the credential-delete
crash) is also the top unresolved Sentry issue `AUTOGPT-SERVER-6HB` with
100+ events going back to 2025-10-20 — it was archived as "ignored" but
is a real regression. Bug #4 required new work; the others we got by
adopting the existing open PRs and addressing a pending review comment.

**What:** This PR consolidates the three in-flight PRs, adds the two
pieces of new work needed to fully close the beta blockers, and
addresses the pending review on one of the three PRs so it doesn't
require a second round.

- **Closes PR #12004** — Google Drive auto-credentials handling (merged
in)
- **Closes PR #12748** — Incremental OAuth for scope upgrades (merged
in)
- **Closes PR #12588** — superseded by the systemic None-guard here (see
"How" below)
- **Adds Bug 2 fix** — Google credential deletion no longer crashes on
`revoke_tokens`
- **Adds Bug 4 validator** — the agent builder can no longer save a
graph with a hardcoded Drive file ID

**How:**

1. **Adopt PR #12004 (Bug 1 — auto-credentials resolution).** Tags
Drive-file fields as `is_auto_credential` on `CredentialsFieldInfo`,
exposes `BlockSchema.get_auto_credentials_fields()` and
`Graph.regular_credentials_inputs` / `auto_credentials_inputs`, extracts
`_acquire_auto_credentials()` in the executor to resolve embedded
`_credentials_id` at run time, clears `_credentials_id` on agent fork so
cloned agents don't inherit the original author's credential, and fixes
the Firefox referrer policy on the Google Drive picker script load.

2. **Adopt PR #12748 (Bug 3 — credential accumulation).** OAuth callback
now merges scopes into an existing credential (explicit via
`credential_id` in OAuth state, or implicit via `provider + username`
match) instead of appending a new row on every reconnect. GitHub's
non-incremental OAuth path requests the union of existing + new scopes
at login so the upgrade path works there too.

3. **Replace PR #12588 with a systemic None-guard (addresses reviewer
feedback).** The original PR added a per-block `credentials:
GoogleCredentials | None = None` + early guard pattern that would need
to be repeated across 50+ blocks with `GoogleDriveFileField`. Per the
reviewer's ask, we moved the guard into `Block._execute()` once: after
the `setdefault` loop, if `kwargs[kwarg_name] is None` we raise
`BlockExecutionError` with a clean user-facing message. The per-block
change in `sheets.py` is dropped so `credentials: GoogleCredentials`
stays non-`Optional`. Dry-run path skips the guard (executor
intentionally runs blocks without resolved creds for schema validation).

4. **Fix Bug 2 — Google revoke_tokens (SECRT-2267,
AUTOGPT-SERVER-6HB).** `revoke_tokens()` was handing our Pydantic
`OAuth2Credentials` into google-auth's `AuthorizedSession`, which calls
`self.credentials.before_request(...)` on the object and crashes with
`AttributeError: 'OAuth2Credentials' object has no attribute
'before_request'`. Google's token revoke endpoint doesn't need any auth
header — just `token=<token>` in the form body per [Google's
docs](https://developers.google.com/identity/protocols/oauth2/web-server#tokenrevoke).
Switched to the platform's async `Requests` helper, matching how
`reddit.py` / `github.py` / `todoist.py` / other providers do
revocation. No google-auth objects involved.

5. **Fix Bug 4 — hardcoded Drive file IDs in agent graphs
(SECRT-2269).** Evidence from the beta user's session: CoPilot's
agent-builder produced 13 saved graph versions in one session where each
one stuffed either a bare string (`"1KAv…"`) or a partial object
(`{"id": "1KAv…"}`) into
`GoogleSheetsReadBlock.constantInput.spreadsheet`, never wiring an
`AgentGoogleDriveFileInputBlock` as the intended input. Bare-string
versions failed pydantic validation with `is not of type 'object'`;
object-with-only-`id` versions would have crashed at run time because
`_acquire_auto_credentials` has no `_credentials_id` to resolve. Added a
validator in `GraphModel._validate_graph_get_errors` that flags any
auto-credentials field whose `input_default.<field>` is a bare string OR
a dict missing `_credentials_id`, when there's no upstream link feeding
the field. Remediation text is format-aware: when
`field_schema["format"] == "google-drive-picker"` it names
`AgentGoogleDriveFileInputBlock` specifically; for any other future
auto-credentials format (OneDrive / Dropbox / etc.) the remediation is
generic, so we don't ship a stale Google-specific hint that doesn't
apply.

A companion handoff for the CoPilot agent-builder team is drafted at
`/tmp/agent-builder-ticket-drive-file-input.md` (to be filed in their
tracker). The validator here is a safety net so reviewers and the LLM
both get a clear error with the correct remediation; the agent-builder
itself still needs to learn the correct pattern so it stops trying to
hardcode Drive files in the first place.

### Changes 🏗️

**Backend**

- `backend/data/model.py` — merged `is_auto_credential` +
`input_field_name` (#12004) with `OAuthState.credential_id` (#12748);
kept HEAD's defensive `set()` copy on `discriminator_values`.
- `backend/blocks/_base.py` — `_execute()` runs the auto-credentials
setdefault loop + raises `BlockExecutionError` when a resolved value is
`None`.
- `backend/blocks/google/sheets_test.py` — 2 new tests (systemic
None-guard behaviour).
- `backend/blocks/google/_drive.py`, `_drive_test.py` — unchanged on
this branch (earlier bare-string validator was reverted after feedback;
see "Out of scope" below).
- `backend/data/graph.py` — auto-credentials anti-pattern validator in
`_validate_graph_get_errors`.
- `backend/data/graph_test.py` — 11 new tests for the validator.
- `backend/integrations/oauth/google.py` — `revoke_tokens` swapped to
`Requests().post`, removed `AuthorizedSession` misuse.
- `backend/integrations/oauth/google_test.py` — 3 new tests covering the
revoke happy path, no-access-token, and non-2xx-response.
- `backend/integrations/credentials_store.py` — from #12748.
- `backend/api/features/integrations/router.py` — incremental-OAuth
callback + scope upgrade helpers (from #12748).
- `backend/api/features/integrations/incremental_oauth_test.py` — 15
tests (from #12748).
- `backend/api/features/chat/tools/utils.py` → renamed to
`backend/copilot/tools/utils.py` during merge; now uses
`regular_credentials_inputs` for missing-creds + matching (from #12004).
- `backend/copilot/tools/utils_test.py` — moved from
`api/features/chat/tools/`, import paths updated.
- `backend/api/features/library/db.py` — library preset guard uses
`regular_credentials_inputs` (from #12004).
- `backend/data/graph.py` — `regular_credentials_inputs` /
`auto_credentials_inputs` properties + `_reassign_ids` clears
`_credentials_id` on fork (from #12004).
- `backend/executor/manager.py` — `_acquire_auto_credentials()`
extracted + validation (from #12004).
- `backend/executor/utils.py`, `utils_test.py`,
`manager_auto_credentials_test.py` — auto-credentials tests (from
#12004).

**Frontend**

- `frontend/src/components/contextual/GoogleDrivePicker/helpers.ts` —
Firefox referrer fix (from #12004).
-
`frontend/src/components/contextual/CredentialsInput/useCredentialsInput.ts`,
`src/hooks/useCredentials.ts`, `src/lib/autogpt-server-api/client.ts`,
`src/providers/agent-credentials/credentials-provider.tsx`,
`src/app/api/openapi.json` — incremental-OAuth scope upgrade UI (from
#12748).

**Shared libs**

- `autogpt_libs/supabase_integration_credentials_store/types.py` —
merged additions from both #12004 and #12748.

### Test plan 📋

- [x] `poetry run lint` — clean
- [x] `poetry run pytest backend/data/graph_test.py` — 55 passed
including 11 new validator tests
- [x] `poetry run pytest backend/integrations/oauth/google_test.py` — 3
new tests passing
- [x] `poetry run pytest backend/blocks/google/sheets_test.py` — 2 new
tests passing
- [x] `poetry run pytest backend/blocks/google/
backend/integrations/oauth/ backend/executor/ backend/data/graph_test.py
backend/api/features/integrations/ backend/copilot/tools/utils_test.py`
— 250 passed, 6 pre-existing failures that require the docker stack
(RabbitMQ/Redis/Postgres) and fail identically on `origin/dev`
- [x] `pnpm format` — clean
- [x] `pnpm lint` — 3 pre-existing `<img>` warnings on files I didn't
touch, no errors
- [x] `pnpm types` — pre-existing errors on `AgentActivityDropdown` that
also fail on `origin/dev` (unrelated to this PR; needs a separate fix on
dev)
- [x] Live repro on dev verified Bug 2 fires against current prod code —
two fresh Sentry events in `AUTOGPT-SERVER-6HB` at 2026-04-21T21:35:54Z
on `app:dev-behave:cloud` matching the exact `DELETE
/api/integrations/google/credentials/{cred_id}` path. Airtable OAuth2
delete as a control worked cleanly, confirming Google-specific.
- [x] Live repro on dev verified Bug 4 (CoPilot direct-run variant) —
`{"spreadsheet": {"id": "..."}}` → `Cannot use file 'None' (type: None)`
from `_validate_spreadsheet_file` mimeType check, as expected.

Reviewer post-merge verification:
- [ ] Delete a Google OAuth credential via the Integrations UI —
succeeds cleanly, no Sentry event fires
- [ ] Connect Google twice (same account, same scopes) — credential
count stays at 1 (dedup)
- [ ] Save an agent graph with
`GoogleSheetsReadBlock.constantInput.spreadsheet = "bare-id"` via API —
graph validator rejects with `AgentGoogleDriveFileInputBlock`
remediation
- [ ] Save an agent graph with `GoogleSheetsReadBlock` whose
`spreadsheet` is fed by an upstream
`AgentGoogleDriveFileInputBlock.result` — validator accepts, agent runs

### Out of scope (for follow-ups)

- **Bug 1 — "Failed to retrieve Google OAuth credentials"** in
`frontend/src/components/contextual/GoogleDrivePicker/useGoogleDrivePicker.ts:163`.
Zero hits for this string in the beta user's Langfuse traces and we
weren't able to reproduce it from a clean flow. Most likely a
stale-credential race condition (delete in another tab, picker queries a
stale React-Query cache). Tracked as a separate task; not blocking.
- **CoPilot first-attempt mimeType retry loop.** Observed on dev:
CoPilot's first call to `GoogleSheetsReadBlock` sends `{"spreadsheet":
{"id": "..."}}` without `mimeType`, hits `_validate_spreadsheet_file`,
retries with mimeType. Costs a round-trip. Two possible fixes (relax
`_validate_spreadsheet_file` to skip when mimeType is `None` and let
Google's API surface the real error; OR extend
`get_auto_credentials_fields` metadata so CoPilot's tool description
prompts it to always include mimeType). Deliberately deferred — fixing
only one of "API caller sends a bare string" or "CoPilot sends an
incomplete object" risked the same auth-ambiguity the bare-string commit
in this branch history hit.
- **CoPilot agent-builder prompt/guide update.** The validator here
produces the correct error message, but the agent-builder model still
needs to learn to use `AgentGoogleDriveFileInputBlock` upfront rather
than discover it through validator retries. Separate handoff ticket
filed.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> **Medium Risk**
> Touches OAuth credential issuance/upgrade paths and introduces a new
endpoint that returns raw access tokens (scope-gated), plus broad
changes to execution-time credential resolution/validation; mistakes
could impact auth/security or break integrations.
> 
> **Overview**
> Fixes several Google/Drive agent-builder blockers by **supporting
incremental OAuth scope upgrades** and by hardening how
credential-bearing file inputs (“auto-credentials”) are validated,
resolved, and cleared on graph fork.
> 
> On the integrations API, `/{provider}/login` now accepts
`credential_id` and persists it in `OAuthState` to upgrade an existing
OAuth2 credential on callback (explicit upgrade), with an implicit merge
path for same `provider+username`. The callback path now merges
scopes/metadata, preserves ID/title, preserves existing
`refresh_token`/`username` when missing from incremental responses,
blocks upgrades for managed/system credentials, and adds a **new
`/{provider}/credentials/{cred_id}/picker-token` endpoint** to return a
short-lived access token for provider-hosted pickers (currently
allowlisted to Google Drive scopes).
> 
> For auto-credentials, `CredentialsFieldInfo` gains
`is_auto_credential` + `input_field_name`, graphs now expose
`regular_credentials_inputs` vs `auto_credentials_inputs`, and multiple
callers switch from `aggregate_credentials_inputs()` to
`regular_credentials_inputs` so embedded picker credentials aren’t
treated as user-mapped inputs. Execution-time auto-credential
acquisition is extracted into `_acquire_auto_credentials()` with clearer
error handling and lock cleanup; block execution adds a systemic guard
to surface a clean `Missing credentials` error when auto-credentials are
absent.
> 
> Separately fixes Google credential deletion by rewriting
`GoogleOAuthHandler.revoke_tokens()` to use the platform `Requests`
helper (bounded retries) instead of `AuthorizedSession`, and expands
test coverage across these flows (incremental OAuth, picker-token,
auto-credential validation/acquisition, graph validator, and frontend
diagnostics test stubs).
> 
> <sup>Reviewed by [Cursor Bugbot](https://cursor.com/bugbot) for commit
cac36eae9f. Bugbot is set up for automated
code reviews on this repo. Configure
[here](https://www.cursor.com/dashboard/bugbot).</sup>
<!-- /CURSOR_SUMMARY -->

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-04-23 17:16:30 +00:00
Zamil Majdy
80bfde1ca6 feat(blocks): charge Ayrshare per-post + align Bannerbear/Jina floors (#12893)
## Why

The cost-tracking audit on 2026-04-23 ([Platform System
Credentials](https://www.notion.so/auto-gpt/4d251f343fe146bcb91b6a037d1bfc3c))
surfaced three gaps where the user wallet was silently subsidising
third-party spend:

1. **Ayrshare (13 blocks)** — zero charge on every social post. No
`BLOCK_COSTS` entry, no SDK `.with_base_cost` registration. Platform
absorbs the entire ~$149/mo Business plan.
2. **Bannerbear** — flat 1 credit/call below the ~$0.025/image unit cost
on the Starter tier ($49/mo / 2K images).
3. **JinaChunkingBlock** — wallet-free; siblings (`JinaEmbeddingBlock`,
`SearchTheWebBlock`) are charged.

## What

- New `backend/blocks/ayrshare/_cost.py` with two-tier
`AYRSHARE_POST_COSTS` (5 credits when `is_video=True`, 2 credits
otherwise — first-match wins in `block_usage_cost`).
- All 13 `PostTo*Block` classes decorated with
`@cost(*AYRSHARE_POST_COSTS)`.
- `BannerbearTextOverlayBlock` floor: 1 → 3 credits in
`bannerbear/_config.py`.
- `JinaChunkingBlock` added to `BLOCK_COSTS` with a flat 1-credit floor.
- `cost(...)` decorator generic-ized via `TypeVar`, so pyright retains
`PostToXBlock.Input/Output` narrowing.

## How

Ayrshare uses a decorator-based registration (not a direct `BLOCK_COSTS`
entry) because each `post_to_*.py` block imports from `backend.sdk`, and
`backend.sdk.cost_integration` imports `BLOCK_COSTS` — listing the
blocks in `block_cost_config.py` would create a circular import. The
`@cost` decorator defined in `sdk/cost_integration.py` was already the
approved escape hatch for this exact shape.

cost_filter in `block_usage_cost` already supports boolean-field
matching (see Apollo's `enrich_info` tier), so `{"is_video": True}` and
`{"is_video": False}` select the right tier at execution time.
`is_video` defaults to `False` on `BaseAyrshareInput`, so posts that
omit the field still land on the 2-credit default.

## Test plan

- [x] `poetry run pytest backend/data/block_cost_config_test.py` — new
6-test suite covers Ayrshare video/non-video/default tiers, the
Bannerbear floor, and the Jina chunking floor
- [x] `poetry run pytest backend/executor/manager_cost_tracking_test.py`
— no regressions (45 pre-existing tests still pass)
- [x] `poetry run ruff format` + `poetry run isort` + `poetry run ruff
check --fix`
- [x] `poetry run pyright` on touched files — 0 errors, 0 warnings
(pre-existing `LlmModel.KIMI_K2_*` errors are on dev and unrelated)
- [ ] Manual: run an Ayrshare post through the builder and confirm 2cr
(text/image) vs 5cr (video) charge
2026-04-23 20:39:35 +07:00
Zamil Majdy
81d6e91f37 feat(platform/copilot): message timestamps + accurate thought-for time (#12890)
## Why

The "Thought for 1m 46s" label under assistant replies has been
misleading
because the backend persists the whole-turn wall clock (from turn start
to
stream end) — which includes tool execution, browser sessions, graph
runs,
etc. Users also had no way to see when a message was actually sent /
received.

## What

- **Per-message timestamps** — `ChatMessage.created_at` (already on the
DB row)
is now serialised through the pydantic model and the
`SessionDetailResponse`,
then plumbed into the UI. Hovering the "Thought for X" label now shows
the
  absolute local date/time via a tooltip.
- **Accurate reasoning duration** — new
`ChatMessage.reasoningDurationMs`
  column. Backend accumulates time between `reasoning-start` and
`reasoning-end` SSE events inside `publish_chunk` (via the session meta
hash). `mark_session_completed` reads the total and persists it
alongside
the existing `durationMs`. Frontend prefers `reasoning_duration_ms` when
  present, falls back to `duration_ms` for legacy rows.

## How

- `schema.prisma` gains `reasoningDurationMs Int?`; migration
  `20260423120000_add_reasoning_duration_ms` adds the column.
- `publish_chunk` gains a side-effect that writes `reasoning_started_at`
/
`reasoning_ms_total` into the existing per-session Redis meta hash when
  reasoning events pass through. No extra IO path, no extra Redis key.
- `set_turn_duration` accepts an optional `reasoning_duration_ms` arg
and
  patches both the DB row and the cached session in place, mirroring the
  existing behaviour for `duration_ms`.
- Frontend: `convertChatSessionMessagesToUiMessages` now returns
`durations`, `reasoningDurations`, and `timestamps` maps. `TurnStatsBar`
picks the best available value and wraps the label in the design-system
  `BaseTooltip` so hover reveals the local timestamp.

## Test plan

- [x] `poetry run pytest
backend/copilot/db_test.py::test_set_turn_duration_*`
- [x] `poetry run pytest backend/copilot/stream_registry_test.py`
- [x] `pnpm format` / `pnpm lint` / `pnpm types` (copilot area)
- [x] `pnpm test:unit src/app/\(platform\)/copilot` — 705 tests pass (4
pre-existing `jszip` module resolution failures unrelated to this
change)
- [ ] Manual: open a session with a long tool run and confirm the new
"Thought for X" reflects only reasoning time (falls back for old rows)
      and the tooltip surfaces the local timestamp.
2026-04-23 18:55:34 +07:00
Zamil Majdy
39cdc0a5e0 fix(backend/copilot): tame Kimi compaction storm + tunable threshold + Langfuse cost backfill (#12889)
## Why

Investigation of two reported sessions
([85804387](https://dev-builder.agpt.co/copilot?sessionId=85804387-7708-4fdc-8ec9-64283cdd902d),
[19d69dec](https://dev-builder.agpt.co/copilot?sessionId=19d69dec-210f-4439-a94b-2d7d443b9909))
where Kimi K2.6 via OpenRouter was running ~30 min per turn with no
actions completed (Discord report from Toran). Langfuse traces showed:

- 31 generation calls per turn at p90 = 151s, max = 415s
- 2.57M uncached tokens, `cache_create=0`, ~4% cache_read — Moonshot's
OpenRouter endpoint silently drops Anthropic-style cache writes
- **3 SDK-internal compactions per turn** — each compaction is itself a
slow LLM round-trip
- Reconciled OpenRouter cost was being recorded to a DB row but never
surfaced on the Langfuse trace, leaving operators to grep pod logs

## What

Four commits, split by concern.

### 1. `fix(backend/copilot): skip CLAUDE_AUTOCOMPACT_PCT_OVERRIDE for
Moonshot/Kimi` (`5fd9c5aa`)

`env.py` was unconditionally setting
`CLAUDE_AUTOCOMPACT_PCT_OVERRIDE=50` (introduced in #12747 to cap
cache-creation cost on Anthropic where context >200K = 54% of total
cost). On Kimi where `cache_create=0` silently, the cache-cost rationale
doesn't apply — but the 50% threshold still made the bundled CLI
auto-compact at ~100K tokens, triggering 3+ compactions per turn against
Kimi's larger effective window. Each compaction added a slow LLM
round-trip (one in our test ran 166s and burned the budget cap before
the user got any output).

Threads the resolved `sdk_model` (and `fallback_model`) into
`build_sdk_env` and skips the env var when the model matches
`is_moonshot_model(...)`. The CLI then uses its default ~93% threshold,
cutting compaction passes to 0–1.

### 2. `feat(backend/copilot): backfill OpenRouter reconciled cost to
Langfuse trace` (`f3de3624` + follow-ups `5ce3d038`, `d2c1a2cd`,
`d8e08525`, `d243bf6c9`)

`record_turn_cost_from_openrouter` runs as a fire-and-forget task after
the OTel span closes, so the Langfuse trace UI showed the SDK CLI's
rate-card estimate only — for non-Anthropic OpenRouter routes that
estimate is Sonnet pricing on Kimi tokens (~5x too high).

The backfill captures `langfuse.get_current_trace_id()` and threads it
into the reconcile task, which emits an `openrouter-cost-reconcile`
child event with the authoritative cost + token usage. **Bug caught
during /pr-test:** `propagate_attributes` only annotates an existing
OTel span, it doesn't create one — by the time the `finally` block runs,
SDK-emitted spans have ended and `get_current_trace_id()` returns None.
Fixed in `d8e08525` by wrapping the turn in
`langfuse.start_as_current_span(name="copilot-sdk-turn")`. Also tags
fallback-path events with `cost_source` so operators can distinguish
reconciled vs estimated turns.

### 3. `feat(backend/copilot): expose CLAUDE_AUTOCOMPACT_PCT_OVERRIDE as
a config knob` (`72416f73`)

The previously-hardcoded `50` is now
`claude_agent_autocompact_pct_override` (default 50, env
`CHAT_CLAUDE_AGENT_AUTOCOMPACT_PCT_OVERRIDE`). Setting to 0 omits the
env var entirely so the CLI uses its native ~93% threshold — useful when
the post-compact floor (system prompt + tool defs ≈ 65–110K) sits close
to an aggressive trigger and operators see back-to-back compaction
cascades. Moonshot routes still skip the env var unconditionally
regardless of config.

### 4. `fix(backend/copilot): align SDK retry compaction target with CLI
autocompact threshold` (`730ad256`)

`_reduce_context` was calling `compact_transcript` without an explicit
`target_tokens`, so it fell back to `get_compression_target(model) =
context_window - 60K`. For Sonnet 200K that's 140K — well above the
CLI's PCT=50 trigger of 90K — and for Kimi 256K it's 196K, above the
CLI's default 167K trigger. Result: a successful retry compaction landed
at 140K/196K and the CLI immediately re-compacted on the next call →
**two compactions per recovered turn**.

New `_compaction_target_tokens(model)` mirrors the CLI's `i6_()` formula
(`min(window * pct/100, window - 13K)`) with a 20K safety buffer so the
post-compact context sits comfortably below the CLI's trigger.

## How — empirical validation against the actual long Kimi transcript

Replayed the 199-message transcript from session 85804387 through the
bundled CLI in two configurations:

| | Post-fix (no override) | Pre-fix (`PCT_OVERRIDE=50`) |
|---|---|---|
| `autocompact: tokens=` | 126,312 | 126,341 |
| `threshold=` | **167,000** | **90,000** |
| Decision | 126K < 167K → **skip** | 126K > 90K → **COMPACTION FIRES**
|
| Duration | 21s | **166s** (8x slower) |
| Cost | $0.34 | **$0.82** (2.4x more) |
| Output | PONG (success) | empty (hit $0.50 budget cap, exit 1) |

The pre-fix configuration burned $0.82 of compaction work over 166s and
never produced a user response — exactly the failure mode reported.

**Why cascade happens at 50%, not at 93%:** post-compaction context is
`summary (~5–10K) + system_prompt + tool_definitions + skills + active
TodoWrite + memory ≈ 65–110K floor`. With trigger at 90K, post-compact
floor sits AT or above the trigger → next assistant message tips over →
immediate re-compaction → cascade until the CLI's rapid-refill breaker
trips at 3 attempts. With trigger at 167K, the same floor sits
comfortably below trigger → no cascade.

## Considered but not done

- **Force `cache_control` markers to reach Moonshot**: bundled CLI sends
them by default; Moonshot silently drops them per their own docs (uses
`X-Msh-Context-Cache` headers, not body markers). Real fix needs
bypassing OpenRouter — out of scope.
- **Slim the system prompt + tool definitions** to lower the
post-compact floor: real win but separate refactor with tool-use
accuracy A/B.
- **LD-driven auto-fallback to Sonnet on Kimi degradation**:
`claude_agent_fallback_model` already wires `--fallback-model` for
overload (529); auto-flipping on slowness needs latency aggregation
infra that doesn't exist yet.

## Test plan

- [x] `poetry run pytest backend/copilot/sdk/env_test.py
backend/copilot/sdk/openrouter_cost_test.py
backend/copilot/sdk/service_helpers_test.py` — 111 passed (37 env + 23
cost + 51 helpers, including 6 new env tests, 3 backfill tests, 6 new
compaction-target tests)
- [x] `poetry run pytest backend/copilot/sdk/` — 970+ passed
- [x] `poetry run pyright .` — 0 errors
- [x] `poetry run format` — clean
- [x] /pr-test --fix end-to-end against dev — 5/5 scenarios PASS,
including Anthropic route ($0.0174 cost +0.0% delta) and Moonshot route
($0.028 vs $0.018 → +58.2% delta validates reconcile rationale)
- [x] Transcript replay validation: pre-fix vs post-fix on real
126K-token transcript → 8x slower / 2.4x more expensive / fails entirely
on pre-fix; clean PONG on post-fix
2026-04-23 18:46:35 +07:00
Zamil Majdy
4242da79f0 fix(backend/copilot): raise baseline tool-round limit to 100 + graceful finish hint (#12892)
## Why

On prod, longer copilot runs (complex feature implementations, multi-bug
fix chains) error out with `Exceeded 30 tool-call rounds without a final
response`, lose mid-stream assistant output, and the UI appears to
re-dispatch an older prompt. Reported by @itsababseh in #breakage for
session `661ba0cc-a905-4c66-bf11-61eb5423d775`.

Langfuse trace of that session shows 52 turns / 344 LLM calls; **two
turns hit exactly 30 rounds** (Turn 38: implementing kill-cam/headshot
juice pass; Turn 42: fixing multi-bug list). Both were legitimate,
non-looping work that simply needed more rounds to complete. Round 30
fired `bash_exec`, the loop cut off cold, no summary was ever produced,
and the stream surfaced `baseline_tool_round_limit`. Frontend
subsequently re-dispatched the same user message several times (turns
39–41 × 3, turns 43–47 × 5 with identical prompt), which is what the
user perceives as "falling back into acting on an older command."

Root cause: [`_MAX_TOOL_ROUNDS =
30`](https://github.com/Significant-Gravitas/AutoGPT/blob/cf6d7034f/autogpt_platform/backend/backend/copilot/baseline/service.py#L125)
has been unchanged since the baseline path was introduced (#12276).
Modern agent turns with Claude Code / Kimi / Sonnet routinely need more.

## What

- Raise `_MAX_TOOL_ROUNDS` from 30 → 100.
- Pass `last_iteration_message` to `tool_call_loop` so the final round
receives a "stop calling tools, wrap up" system hint. The model now
produces a graceful summary on the last round instead of being cut off
mid-tool.

## How

Two-line change in
[`backend/copilot/baseline/service.py`](https://github.com/Significant-Gravitas/AutoGPT/blob/fix/copilot-baseline-tool-round-limit/autogpt_platform/backend/backend/copilot/baseline/service.py):
- Bump the module-level constant.
- Define `_LAST_ITERATION_HINT` and wire it via the existing
`last_iteration_message` kwarg on
[`tool_call_loop`](https://github.com/Significant-Gravitas/AutoGPT/blob/cf6d7034f/autogpt_platform/backend/backend/util/tool_call_loop.py#L188).
The shared loop already handles appending it only on the final iteration
(see `tool_call_loop_test.py::test_last_iteration_message_appended`).

Frontend retry cascade on `baseline_tool_round_limit` is a separate UX
issue — logging it as a follow-up.

## Checklist

- [x] My code follows the project's style guidelines
- [x] I have performed a self-review
- [x] Existing `tool_call_loop_test.py` covers `last_iteration_message`
behavior (10/10 passing)
- [x] No new migrations
- [x] No breaking changes (constant/kwarg only)
2026-04-23 18:38:52 +07:00
Zamil Majdy
cf6d7034fa fix(backend/copilot): sync safety net for Redis-induced zombie sessions (#12886)
## Why

A 25-min-old copilot turn ended up a zombie in Redis (`status=running`
for 60+ min, queued user messages never drained) after a rolling deploy
of `autogpt-copilot-executor`. Root cause:

1. Cluster churn during the rollout broke a Redis call mid-turn.
2. `_execute_async`'s `finally` tried to publish the failure via
`mark_session_completed` on the same (now-broken) event loop +
thread-local Redis client.
3. That Redis call *also* failed; the exception was caught and logged
but never reached Redis — so the session meta stayed `running`.
4. `on_run_done` then completed the future normally, `active_tasks`
drained, the pod exited.
5. The zombie persisted until the 65-min stale-session watchdog reaped
it. While it was live, queued-message pushes succeeded (HTTP only checks
`status=running`), so the UI showed "Queued" bubbles that never drained.

## What

The fix is **one small addition** in the per-turn lifecycle:

### `sync_fail_close_session` — last line of defense in
`processor.execute`'s `finally`

Invoked from `CoPilotProcessor.execute()`'s `finally` on every turn
exit. Submits the CAS coroutine to the processor's long-lived
`self.execution_loop` via `asyncio.run_coroutine_threadsafe` — the same
pattern `ExecutionProcessor.on_graph_execution` uses at
[executor/manager.py:881-892](autogpt_platform/backend/backend/executor/manager.py#L881-L892)
to bridge sync→async through `node_execution_loop`.

- Calls `mark_session_completed(session_id,
error_message=SHUTDOWN_ERROR_MESSAGE)`, which is a CAS on `status ==
"running"`. If the async path already wrote a terminal state the CAS
no-ops; otherwise we mark `failed` and the UI transitions cleanly.
- Bounded by inner `asyncio.wait_for(timeout=10s)` and outer
`future.result(timeout=12s)` so a genuinely unreachable Redis can't hang
the safety net.
- Reuses the long-lived execution loop (no per-turn TCP connect, no
`@thread_cached` thrashing).

The outer `future.result()` in `_execute()` is bounded by
`_CANCEL_GRACE_SECONDS` (5s) so a wedged event loop can't trap the flow
before the safety net fires.

### `cleanup()` stays aligned with agent-executor

Mirrors the pattern from `backend.executor.manager.cleanup` — a single
method that:

1. Flags + tells the broker to stop consuming.
2. Passively waits for `active_tasks` to drain (up to
`GRACEFUL_SHUTDOWN_TIMEOUT_SECONDS`).
3. Worker / executor / lock teardown.

No pre-emptive cancellation of healthy turns, no fail-close step for
stuck turns. Same proven shape agent-executor uses.

### Timeout alignment

Raised both `COPILOT_CONSUMER_TIMEOUT_SECONDS` and
`GRACEFUL_SHUTDOWN_TIMEOUT_SECONDS` to 6h so a rolling deploy can let
the longest legitimate turn finish via its own lifecycle path. Matched
in infra at `terminationGracePeriodSeconds: 21600`
(Significant-Gravitas/AutoGPT_cloud_infrastructure#311).

### RabbitMQ policy — deploy prep

The `x-consumer-timeout` queue argument is changing from 1h → 6h. Tested
empirically on dev's RabbitMQ 4.1.4: `queue_declare` is tolerant of
`x-consumer-timeout` mismatches, so no queue delete is needed. To make
the new timeout **immediately effective for running consumers** (so pods
mid-shutdown don't have their consumer cancelled at the old 1h limit),
apply a policy before deploying:

```bash
rabbitmqctl set_policy copilot-consumer-timeout \
  "^copilot_execution_queue$" \
  '{"consumer-timeout": 21600000}' \
  --apply-to queues
```

Already applied on dev. Apply on prod before the PR's prod deploy.

### Incidental rename

- `_clear_pending_messages_unsafe` → `clear_pending_messages_unsafe`
(keeps the `_unsafe` warning suffix; importable without the
leading-underscore private marker).

## How

Before: transient Redis failure → async finally silently fails → zombie
session → queued messages never drain.
After: transient Redis failure → `execute()`'s sync finally runs
`mark_session_completed` on the processor's long-lived loop → session
correctly marked failed → UI sees terminal state immediately.

SIGTERM path unchanged from the "let in-flight work finish" design: old
pod stops taking new work, existing turns complete naturally.

## Test plan

- [x] `TestSyncFailCloseSession` unit tests — invokes
`mark_session_completed` with the shutdown error, swallows Redis
failures, bounded timeout fires when Redis hangs.
- [x] `TestExecuteSafetyNet` — verifies the `finally` always fires,
including SIGTERM-interrupted and zombie-Redis scenarios.
- [x] Existing `TestExecuteAsyncAclose` + pending_messages tests still
pass (18 passed).
- [x] `pyright` on touched files: 0 errors.
- [x] Manual E2E on native dev stack: sent a `sleep 300 && echo hewwo`
task, SIGTERMed mid-turn at +40s, observed:
   - `[CoPilotExecutor] [cleanup N] Starting graceful shutdown...`
   - Drain-wait ran for ~4.5 min ("1 tasks still active, waiting...")
- Turn finished with `result=Done! The command finished after 5 minutes
and printed: hewwo`
   - `Cleaned up completed session` → `Graceful shutdown completed`
   - No zombie.
- [x] `poetry run format` applied.
- [x] RabbitMQ policy verified on dev. Apply on prod before prod deploy.
- [ ] Verified behavior on next production rolling deploy.
2026-04-23 06:49:06 +07:00
Zamil Majdy
c56c1e5dd6 fix(backend/copilot): disable ask_question tool pending UX rework (#12887)
### Why / What / How

**Why:** The in-conversation Question GUI is unreliable in production —
users submitting answers can get their messages dropped and the agent
gets stuck on the auto-generated "please proceed" step with no way to
make progress. Discord report:
https://discord.com/channels/1126875755960336515/1496474512966029472/1496537943287005365
(see attached video). Pause/queue semantics still need a rework; until
then, the right call is to stop the model from reaching for this tool.

**What:** Removes `ask_question` from the copilot tool registry so the
model never sees or calls it. Historical sessions that already contain
`ask_question` tool calls still render (frontend renderers + response
model untouched), so this is non-destructive to existing chats.
Re-enabling once UX is reworked is a small revert.

**How:**
- Drop the `AskQuestionTool` import + registry entry from
`backend/copilot/tools/__init__.py`.
- Drop `"ask_question"` from the `ToolName` literal in
`backend/copilot/permissions.py` — required because a runtime
consistency check asserts the literal matches `TOOL_REGISTRY.keys()`.
- Delete the "Clarifying — Before or During Building" section from
`backend/copilot/sdk/agent_generation_guide.md` so the SDK-mode system
prompt no longer instructs the model to call `ask_question`.
- Drop the three `prompting_test.py` tests that asserted the guide
mentions that section.
- Keep `ask_question.py`, its unit test, `ClarificationNeededResponse`,
and the frontend `AskQuestion`/`ClarificationQuestionsCard` components
untouched so old sessions still render and re-enabling is a small
revert.

### Changes 🏗️

- `backend/copilot/tools/__init__.py` — remove `AskQuestionTool` import
and `"ask_question"` entry in `TOOL_REGISTRY`.
- `backend/copilot/permissions.py` — remove `"ask_question"` from the
`ToolName` literal.
- `backend/copilot/sdk/agent_generation_guide.md` — remove the
"Clarifying — Before or During Building" section.
- `backend/copilot/prompting_test.py` — remove
`TestAgentGenerationGuideContainsClarifySection` and the now-unused
`Path` import.

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [ ] I have tested my changes according to the test plan:
- [x] `poetry run pytest backend/copilot/tools/
backend/copilot/permissions_test.py backend/copilot/prompting_test.py` —
805+78 tests pass, consistency check between `ToolName` literal and
`TOOL_REGISTRY` still holds.
- [ ] Smoke-test in dev: start a copilot session and confirm the model
no longer lists/calls `ask_question` (its OpenAI tool schema is gone
from `get_available_tools()` and from the SDK `allowed_tools`).
- [ ] Load a historical session that contains an `ask_question` tool
call in its transcript — confirm the frontend still renders the question
card (no regression on legacy sessions).
2026-04-22 23:34:04 +07:00
Bentlybro
6fcbe95645 Merge branch 'master' into dev 2026-04-22 15:36:37 +01:00
Zamil Majdy
9703da3dfd refactor(backend/copilot): Moonshot module + cache_control widening + partial-messages default-on + title cost (#12882)
## Why

Several loose ends from the Kimi SDK-default merge (#12878), plus
follow-ups surfaced during review + E2E testing:

1. **Kimi-specific pricing lived inline in `sdk/service.py`** alongside
unrelated SDK plumbing — any future non-Anthropic vendor would have
piled onto the same file.
2. **Moonshot's Anthropic-compat endpoint honours `cache_control: {type:
ephemeral}`**, but the baseline cache-marking gate
(`_is_anthropic_model`) was narrow enough to exclude it → Moonshot fell
back to automatic prefix caching, which drifts readily between turns.
3. **Kimi reasoning rendered AFTER the answer text** on dev because the
summary-walk hoist only reorders within one `AssistantMessage.content`
list, and Moonshot splits each turn into multiple sequential
AssistantMessages (text-only, then thinking-only).
4. **Title generation's LLM call bypassed cost tracking** — admin
dashboard under-reported total provider spend by the aggregate of those
per-session calls.
5. **Cost override** was using the requested primary model, not the
actually-executed model — when the SDK fallback activates the override
mis-routes pricing.

## What

### Moonshot module
New `backend/copilot/moonshot.py`:
- `is_moonshot_model(model)` — prefix check against `moonshotai/`
- `rate_card_usd(model)` — published Moonshot rates, default `(0.60,
2.80)` per MTok with per-slug override slot
- `override_cost_usd(...)` — moved from `sdk/service.py`, replaces CLI's
Sonnet-rate estimate with real rate card
- `moonshot_supports_cache_control(model)` — narrow gate for cache
markers

Rate card is **not canonical** — authoritative cost comes from the
OpenRouter `/generation` reconcile; this module only improves the
in-turn estimate and the reconcile's lookup-fail fallback. Signal
authority: reconcile >> rate card >> CLI.

### Baseline cache-control widened to Moonshot
- New `_supports_prompt_cache_markers` = `_is_anthropic_model OR
is_moonshot_model`
- Both call sites (system-message cache dict, last-tool cache marker)
switched to the wider gate
- OpenAI / Grok / Gemini still return `false` — those endpoints 400 on
the unknown field

**Measured impact in /pr-test:** baseline Kimi continuation turns jumped
to ~98% cache hit (334 uncached + 12.8K cache_read on a 13.1K prompt).

### SDK partial-messages default-on (fixes the reasoning-order bug)
- `CHAT_SDK_INCLUDE_PARTIAL_MESSAGES` flipped from `default=False` →
`default=True`
- Kimi stream now emits `reasoning-start → reasoning-delta* →
reasoning-end → text-start → text-delta*` in the correct order —
verified in /pr-test
- Kill-switch: set `CHAT_SDK_INCLUDE_PARTIAL_MESSAGES=false` to fall
back to summary-only emission

### SDK cost override scoped to Moonshot
- Call site now explicitly gates `if _is_moonshot_model(active_model)` —
Anthropic turns trust CLI's number directly
- Added `_RetryState.observed_model` populated from
`AssistantMessage.model`, preferred over `state.options.model` so
fallback-model turns bill correctly (addresses CodeRabbit review)

### Title cost capture
- `_generate_session_title` now returns `(title, ChatCompletion)` so the
caller controls cost persistence
- `_update_title_async` runs title-persist and cost-record as
independent best-effort steps
- `_title_usage_from_response` helper reads `prompt_tokens /
completion_tokens / cost_usd` (OR's `usage.cost` off `model_extra`)
- Provider label derived from `ChatConfig.base_url` (`open_router` /
`openai`)
- No exception suppressors — `isinstance(cost_raw, (int, float))` check
replaces the inner `float()` try/except

### Misc
- Kimi tool-name whitespace strip in the response adapter — Kimi
occasionally emits tool names with leading spaces the CLI dispatcher
can't resolve
- TODO marker on the rate-card for post-prod-soak removal

## How

- Detection is **prefix-based** (`moonshotai/`) — future Kimi SKUs
transparently inherit rate card + cache-control gate
- Baseline cache-marking was already structured; only the gate changes
- Partial-messages default-on relies on the adapter's diff-based
reconcile (shipped in #12878) which has soaked stable
- Title cost path mirrors `tools/web_search.py`'s pattern for reading
OR's `usage.cost`

## Test plan

- [x] `pytest backend/copilot/moonshot_test.py` — 21 tests
- [x] `pytest backend/copilot/baseline/service_unit_test.py` — updated
for widened gate
- [x] `pytest backend/copilot/sdk/*_test.py
backend/copilot/service_test.py` — no regressions
- [x] Full E2E on local native stack — 10/10 scenarios pass (see
test-report comment)
- [x] Measured: baseline Kimi ~98% cache hit on continuation, SDK Kimi
~62% (capped by Moonshot's prefix ceiling)

## Deferred

SDK-path Moonshot cache hit rate stays at ~62% on long prompts.
`native_tokens_cached=18432` regardless of turn/session suggests a
Moonshot-side cap on cached prefix size. Not fixable by our code —
requires proxy rewriting requests or upstream Moonshot change.
2026-04-22 20:42:47 +07:00
Zamil Majdy
ebb0d3b95b feat(backend/copilot): LaunchDarkly per-user model routing (#12881)
## Summary

Per-user model routing for the copilot via LaunchDarkly. Replaces the
pure-env-var pick on every `(mode, tier)` cell of the model matrix with
an LD-first resolver that falls back to the `ChatConfig` default. Lets
us roll out non-default routes (e.g. Kimi K2.6 on baseline standard) to
a user cohort without shipping a deploy.

| | standard | advanced |

|----------|------------------------------------|------------------------------------|
| fast | `copilot-fast-standard-model` | `copilot-fast-advanced-model` |
| thinking | `copilot-thinking-standard-model` |
`copilot-thinking-advanced-model` |

All four flags are **string-valued** — the value IS the model identifier
(e.g. `"anthropic/claude-sonnet-4-6"` or `"moonshotai/kimi-k2.6"`).

## What ships

- **New module `backend/copilot/model_router.py`** with a single
`resolve_model(mode, tier, user_id, *, config)` coroutine. That's the
one place both paths consult.
- **4 new `Flag` enum values** in `backend/util/feature_flag.py`
(reusing the existing `get_feature_flag_value` helper which already
supports arbitrary return types).
- **`baseline/service.py::_resolve_baseline_model`** → async, takes
`user_id`.
- **`sdk/service.py::_resolve_sdk_model_for_request`** → takes
`user_id`, consults LD for both standard and advanced thinking cells.
- **Default flip**: `fast_standard_model` default goes back to
`anthropic/claude-sonnet-4-6`. Non-Anthropic routes now ship via LD
targeting — safer rollback, per-user cohort control, no redeploy
required to flip.

## Behavior preserved

- `config.claude_agent_model` explicit override still wins
unconditionally (existing escape hatch for ops).
- `use_claude_code_subscription=true` on the standard thinking tier
still returns `None` so the CLI picks the model tied to the user's
Claude Code subscription.
- All legacy env var aliases (`CHAT_MODEL`, `CHAT_ADVANCED_MODEL`,
`CHAT_FAST_MODEL`) still bind to their cells.
- LD client exceptions / misconfigured (non-string) flag values fall
back silently to config default with a single warning log — never fails
the request.

## Files

| File | Change |
|---|---|
| `backend/copilot/model_router.py` | new — `resolve_model` +
`_config_default` + `_FLAG_BY_CELL` map |
| `backend/copilot/model_router_test.py` | new — 11 cases |
| `backend/util/feature_flag.py` | add 4 string-valued `Flag` entries |
| `backend/copilot/config.py` | flip `fast_standard_model` default to
Sonnet |
| `backend/copilot/baseline/service.py` | `_resolve_baseline_model` →
async + LD resolver |
| `backend/copilot/sdk/service.py` | `_resolve_sdk_model_for_request` →
LD resolver + user_id |
| `backend/copilot/baseline/transcript_integration_test.py` | update
tests for new signature + default |

## Test plan

- [x] `poetry run pytest backend/copilot/model_router_test.py
backend/copilot/baseline/transcript_integration_test.py
backend/copilot/sdk/service_test.py backend/copilot/config_test.py` —
**112 passing**
- [x] 11 resolver cases: missing user → fallback, LD string wins,
whitespace stripped, non-string value → fallback, empty string →
fallback, LD exception → fallback + warn, each of 4 cells routes to its
distinct flag
- [x] Legacy env aliases still bind to their new fields
- [ ] Manual dev-env smoke: flip `copilot-fast-standard-model` LD
targeting to `moonshotai/kimi-k2.6` for one user and confirm baseline
uses Kimi while other users stay on Sonnet
- [ ] Confirm SDK path still honors subscription mode (LD not consulted
when `use_claude_code_subscription=true` + standard tier)

## Rollout

1. Merge this PR → default stays Sonnet / Opus across the matrix, no
behavior change.
2. Create the 4 LD flags as string-typed in the LaunchDarkly console
(defaults matching config, so no drift if targeting empty).
3. Add per-user / per-cohort targeting in LD for the routes we want to
roll out (Kimi on baseline standard for a percentage, etc.).
2026-04-22 20:08:37 +07:00
Zamil Majdy
b98bcf31c8 feat(backend/copilot): SDK fast tier defaults to Kimi K2.6 via OpenRouter + vendor-aware cost + cross-model fix (#12878)
## Summary

Make Kimi K2.6 the default for the SDK (extended-thinking) copilot path,
mirroring the baseline default landed in #12871. The SDK already routes
through OpenRouter (see
[`build_sdk_env`](autogpt_platform/backend/backend/copilot/sdk/env.py) —
`ANTHROPIC_BASE_URL` is set to OpenRouter's Anthropic-compatible
`/v1/messages` endpoint), but the model resolver was unconditionally
stripping the vendor prefix, which prevented routing to anything except
Anthropic models. This PR unblocks Kimi (and any other non-Anthropic
OpenRouter vendor) on the SDK fast tier and flips the default to match
the baseline path.

## Why

After #12871 the baseline (`fast_*`) path runs Kimi K2.6 by default —
~5x cheaper than Sonnet at SWE-Bench parity — but the SDK (`thinking_*`)
path was still pinned to Sonnet because:

1. **Model name normalization stripped the vendor prefix.**
`_normalize_model_name("moonshotai/kimi-k2.6")` returned `"kimi-k2.6"`,
which OpenRouter cannot route — the unprefixed form only resolves for
Anthropic models. The docstring on `thinking_standard_model` claimed
"the Claude Agent SDK CLI only speaks to Anthropic endpoints", but the
env builder shows the CLI happily talks to OpenRouter's `/messages`
endpoint, which routes to any vendor in the catalog.
2. **The default was `anthropic/claude-sonnet-4-6`.** Same model on a
more expensive route.
3. **Cost label was hardcoded to `provider="anthropic"`** on the SDK
path's `persist_and_record_usage` call, making cost-analytics rows
misleading once Kimi runs.

## What

1. **`_normalize_model_name`**
([sdk/service.py](autogpt_platform/backend/backend/copilot/sdk/service.py))
— when `config.openrouter_active` is True, the canonical `vendor/model`
slug is preserved unchanged so OpenRouter can route to the correct
provider. Direct-Anthropic mode keeps the existing strip-prefix +
dot-to-hyphen conversion (Anthropic API requires both) and now **raises
`ValueError`** when paired with a non-Anthropic vendor slug — silent
strip would have sent `kimi-k2.6` to the Anthropic API and produced an
opaque `model_not_found`.
2. **`thinking_standard_model`**
([config.py](autogpt_platform/backend/backend/copilot/config.py)) —
default flipped from `anthropic/claude-sonnet-4-6` to
`moonshotai/kimi-k2.6`. Field description rewritten; rollback to Sonnet
is one env var
(`CHAT_THINKING_STANDARD_MODEL=anthropic/claude-sonnet-4.6`).
3. **`@model_validator(mode="after")`** on `ChatConfig`
([config.py:_validate_sdk_model_vendor_compatibility](autogpt_platform/backend/backend/copilot/config.py))
— fail at config load when `use_openrouter=False` is paired with a
non-Anthropic SDK slug. The runtime guard in `_normalize_model_name` is
kept as defence-in-depth, but the validator turns a per-request 500 into
a boot-time error message the operator sees once, before any traffic
lands. Covers `thinking_standard_model`, `thinking_advanced_model`, and
`claude_agent_fallback_model`. Subscription mode is exempt (resolver
returns `None` and never normalizes). The credential-missing case
(`use_openrouter=True` + no `api_key`) is intentionally NOT a boot-time
error so CI builds and OpenAPI-schema export jobs that construct
`ChatConfig()` without secrets keep working — the runtime guard still
catches it on the first SDK turn.
4. **Cost provider attribution**
([sdk/service.py:stream_chat_completion_sdk](autogpt_platform/backend/backend/copilot/sdk/service.py))
— `persist_and_record_usage` now passes `provider="open_router" if
config.openrouter_active else "anthropic"` instead of hardcoded
`"anthropic"`. The dollar value still comes from
`ResultMessage.total_cost_usd`; this just fixes the analytics label.
5. **Baseline rollback example** ([config.py:fast_standard_model
description](autogpt_platform/backend/backend/copilot/config.py)) — same
dot-vs-hyphen footgun fix (CodeRabbit catch).
6. **Tests** — `TestNormalizeModelName` (sdk/) monkeypatches a
deterministic config per case (the helper-test variants were passing
accidentally based on ambient env). New
`TestSdkModelVendorCompatibility` class in `config_test.py` covers all
five validator shapes (default-Kimi + direct-Anthropic raises, anthropic
override succeeds, openrouter mode succeeds, subscription mode skips
check, advanced+fallback tier also validated, empty fallback skipped).
`_ENV_VARS_TO_CLEAR` extended to all model/SDK/subscription env aliases
so a leftover dev `.env` value can't mask validator behaviour. New
`_make_direct_safe_config` helper for direct-Anthropic tests.

## Test plan

- [x] `poetry run pytest backend/copilot/config_test.py
backend/copilot/sdk/service_test.py
backend/copilot/sdk/service_helpers_test.py
backend/copilot/sdk/env_test.py
backend/copilot/sdk/p0_guardrails_test.py` — 238 pass
- [x] `poetry run pytest backend/copilot/` — 2560 pass + 5 pre-existing
integration failures (need real API keys / browser env, unrelated)
- [x] CI green on `feat/copilot-sdk-kimi-default` (35 pass / 0 fail / 1
neutral)
- [x] Manual: SDK extended_thinking turn against Kimi K2.6 via
OpenRouter on the native dev stack — request lands with
`model=moonshotai/kimi-k2.6`, response streams back, multi-turn
`--resume` recalls facts across turns. Backend log: `[SDK] Per-request
model override: standard (moonshotai/kimi-k2.6)`.
- [x] Manual: rollback path —
`CHAT_THINKING_STANDARD_MODEL=anthropic/claude-sonnet-4.6` resumes
Sonnet routing.

## Known follow-ups (not in this PR)

These surfaced during manual testing and will need separate PRs:

- **SDK CLI cost is wrong for non-Anthropic models.**
`ResultMessage.total_cost_usd` comes from a static Anthropic pricing
table baked into the CLI binary; for Kimi K2.6 it falls back to Sonnet
rates, **over-billing ~5x** ($0.089 vs the real ~$0.018 for ~30K prompt
+ ~80 completion). The `provider` label is now correct but the dollar
value isn't. Needs either a per-model rate card override on our side or
a CLI patch upstream.
- **Mid-session model switch (Kimi → Opus) breaks.** Kimi's
`ThinkingBlock`s have no Anthropic `signature` field; when the user
toggles standard → advanced after a Kimi turn, Opus rejects the replayed
transcript with `Invalid signature in thinking block`. Needs transcript
scrubbing on model switch (similar to existing
`TestStripStaleThinkingBlocks` pattern).
- **Reasoning UI ordering on Kimi.** Moonshot/OpenRouter places
`reasoning` AFTER text in the response; the SDK's
`AssistantMessage.content` reflects that order, and `response_adapter`
emits SSE events in the same order — so reasoning lands BELOW the answer
in the UI instead of above. Needs `ThinkingBlock` hoisting in
`response_adapter.py`.
2026-04-22 18:35:01 +07:00
Zamil Majdy
4f11867d92 feat(backend/copilot): TodoWrite for baseline copilot (#12879)
## Summary

Add `TodoWrite` to baseline copilot so the "task checklist" UI works on
non-Claude models (Kimi, GPT, Grok, etc.) the same way it works on the
SDK path. Baseline previously had no `TodoWrite` tool at all — only SDK
mode did via the Claude Code CLI's built-in — so models on baseline just
couldn't reach for a planning checklist.

This closes the last clear feature gap blocking baseline from being the
primary copilot path without giving up model flexibility.

## What ships

- **New MCP tool `TodoWrite`** in `TOOL_REGISTRY`, schema matching the
one the frontend's `GenericTool.helpers.ts` (`getToolCategory → "todo"`)
already renders as the **Steps** accordion. The tool is a stateless echo
— the canonical list lives in the model's latest tool-call args and
replays from transcript on subsequent turns.
- **Prompt guidance** in `SHARED_TOOL_NOTES` teaching the model when to
use it (3+ step tasks; always send the full list; exactly one
`in_progress` at a time).
- **Sharpened `run_sub_session` guidance** in the same prompt section —
framed explicitly as the context-isolation primitive for baseline.
Clearer for the model, no dual-primitive confusion.

## How the SDK path stays untouched

- SDK mode keeps using the CLI-native `TodoWrite` built-in.
- `BASELINE_ONLY_MCP_TOOLS = {"TodoWrite"}` in `sdk/tool_adapter.py`
filters the baseline MCP wrapper out of SDK's `allowed_tools` — no name
shadowing.
- `SDK_BUILTIN_TOOL_NAMES` is now an explicit allowlist (not
auto-derived from capitalization) so the classification stays coherent
when a capitalized tool is platform-owned.

## Files

| File | Change |
|---|---|
| `backend/copilot/tools/todo_write.py` | new — `TodoWriteTool` |
| `backend/copilot/tools/__init__.py` | register in `TOOL_REGISTRY` |
| `backend/copilot/tools/models.py` | add `TodoItem` +
`TodoWriteResponse` + `ResponseType.TODO_WRITE` |
| `backend/copilot/permissions.py` | explicit `SDK_BUILTIN_TOOL_NAMES`;
`apply_tool_permissions` maps baseline-only tools to CLI name for SDK |
| `backend/copilot/sdk/tool_adapter.py` | `BASELINE_ONLY_MCP_TOOLS`
filter |
| `backend/copilot/prompting.py` | `TodoWrite` + sharpened
`run_sub_session` guidance |
| `backend/api/features/chat/routes.py` | add `TodoWriteResponse` to
`ToolResponseUnion` |
| `backend/copilot/tools/todo_write_test.py` | new — schema + execute
tests |
| `frontend/src/app/api/openapi.json` | regenerated |
| `tools/tool_schema_test.py` | budget bumped `32_800 → 34_000` (actual
33_865, +1_065 headroom) |

## Test plan

- [x] `poetry run pytest backend/copilot/
backend/api/features/chat/routes_test.py` — **1010 passing**
- [x] Tool schema char budget regression gate passes
- [x] `_assert_tool_names_consistent` passes
- [x] **E2E on local native stack (Kimi K2.6 via OpenRouter,
`CHAT_USE_CLAUDE_AGENT_SDK=false`)**: baseline called `TodoWrite` on a
3-step prompt, SSE stream carried the exact `{content, activeForm,
status}` shape the UI expects, "Steps" dialog renders `Task list — 0/3
completed` with all three items (see test-report comment below).
- [x] Negative cases covered: two `in_progress` → rejected, missing
`activeForm` → rejected, non-list `todos` → rejected.
2026-04-22 17:28:15 +07:00
Zamil Majdy
33a608ec78 feat(platform/copilot): live baseline streaming + render flag + Sonar web_search + simulator cost tracking + reconnect fixes (#12873)
### Why / What / How

**Why.** Three problems on the baseline copilot path that compound:
extended-thinking turns froze the UI for minutes because Kimi K2.6
events were buffered in `state.pending_events: list` until the full
`tool_call_loop` iteration finished (reasoning arrived in one lump at
the end); the SSE stream replayed 1000 events on every reconnect and the
frontend opened multiple SSE streams in quick succession on tab-focus
thrash (reconnect storm → UI flickers, tab freezes); the `web_search`
tool hit Anthropic's server-side beta directly via a dispatch-model
round-trip that fed entire page contents back through the model for a
second inference pass (observed $0.072 on a 74K-token call); and the
simulator dry-run path ran on Gemini Flash without any cost tracking at
all, so every dry-run was free on the platform's microdollar ledger.

**What.** Grouped deltas, all targeting reliability, cost, and UX of the
copilot live-answer pipeline:

- **Live per-token baseline streaming.** `state.pending_events` is now
an `asyncio.Queue` drained concurrently by the outer async generator.
The tool-call loop runs as a background task; reasoning / text / tool
events reach the SSE wire during the upstream OpenRouter stream, not
after it. `None` is the close sentinel; inner-task exceptions are
re-raised via `await loop_task` once the sentinel arrives. An
`emitted_events: list` mirror preserves post-hoc test inspection.
Coalescing widened 32/40 → 64/50 ms to halve the React re-render rate on
extended-thinking turns while staying under the ~100 ms perceptual
threshold.
- **Reasoning render flag** — `ChatConfig.render_reasoning_in_ui: bool =
True` wired through both `BaselineReasoningEmitter` and
`SDKResponseAdapter`. When False the wire `StreamReasoning*` events are
suppressed while the persisted `ChatMessage(role='reasoning')` rows
always survive (decoupled from the render flag so audit/replay is
unaffected); the service-layer yield filter does the gating. Tokens are
still billed upstream; operator kill-switch for UI-level flicker
investigations.
- **Reconnect storm mitigations** — `ChatConfig.stream_replay_count: int
= 200` (was hard-coded 1000) caps `stream_registry.subscribe_to_session`
XREAD size. Frontend `useCopilotStream::handleReconnect` adds a 1500 ms
debounce via `lastReconnectResumeAtRef`, so tab-focus thrash doesn't fan
out into 5–6 parallel replays in the same second.
- **web_search rewritten to Perplexity Sonar via OpenRouter** — single
unified credential, real `usage.cost` flows through
`persist_and_record_usage(provider='open_router')`. Two tiers via a
`deep` param: `perplexity/sonar` (~$0.005/call quick) and
`perplexity/sonar-deep-research` (~$0.50–$1.30/call multi-step
research). Replaces the Anthropic-native + server-tool dispatches; drops
the hardcoded pricing constants entirely.
- **Synthesised answer surfaced end-to-end** — Sonar already writes a
web-grounded answer on the same call we pay for; the new
`WebSearchResponse.answer` field passes it through and the accordion UI
renders it above citations so the agent doesn't re-fetch URLs that are
usually bot-protected anyway.
- **Deep-tier cost warning + UI affordances** — `deep` param description
is explicit that it's ~100× pricier; UI labels read "Researching /
Researched / N research sources" when `deep=true` so users know what's
running.
- **Simulator cost tracking + cheaper default** —
`google/gemini-2.5-flash` → `google/gemini-2.5-flash-lite` (3× cheaper
tokens) and every dry-run now hits
`persist_and_record_usage(provider='open_router')` with real
`usage.cost`. Previously each sim was free against the user's
microdollar budget.
- **Typed access everywhere** — cost extractors now use
`openai.types.CompletionUsage.model_extra["cost"]` and
`openai.types.chat.ChatCompletion` / `Annotation` /
`AnnotationURLCitation` with no `getattr` / duck typing. Mirrors the
baseline service's `_extract_usage_cost` pattern; keep in sync.

**How.** Key file touches:

1. `copilot/config.py` — `render_reasoning_in_ui`,
`stream_replay_count`, `simulation_model` default.
2. `copilot/baseline/service.py` — `_BaselineStreamState.pending_events:
asyncio.Queue`, `_emit` / `_emit_all` helpers, outer generator runs
`tool_call_loop` as a background task + yields from queue concurrently.
3. `copilot/baseline/reasoning.py` —
`BaselineReasoningEmitter(render_in_ui=...)`, coalescing bumped to 64
chars / 50 ms.
4. `copilot/sdk/service.py` — `state.adapter.render_reasoning_in_ui`
threaded through every adapter construction.
5. `copilot/sdk/response_adapter.py` — `render_reasoning_in_ui` wiring +
service-layer yield filter gating for wire suppression while persistence
stays intact.
6. `copilot/stream_registry.py` — `count=config.stream_replay_count`.
7. `frontend/.../useCopilotStream.ts::handleReconnect` — 1500 ms
debounce.
8. `copilot/tools/web_search.py` + `models.py` — Sonar quick/deep paths,
`WebSearchResponse.answer` + typed extractors.
9. `frontend/.../GenericTool/*` — `answer` render + deep-aware labels /
accordion titles.
10. `executor/simulator.py` + `executor/manager.py` +
`copilot/config.py` — cost tracking + model swap + `user_id` threading.

### Changes

- `copilot/config.py` — new `render_reasoning_in_ui`,
`stream_replay_count`; `simulation_model` default flipped to Flash-Lite.
- `copilot/baseline/service.py` — `pending_events: asyncio.Queue`
refactor; outer gen runs loop as task, yields from queue live.
- `copilot/baseline/reasoning.py` —
`BaselineReasoningEmitter(render_in_ui=...)` + 64/50 coalesce.
- `copilot/sdk/service.py` + `response_adapter.py` —
`render_reasoning_in_ui` wire suppression (persistence preserved).
- `copilot/stream_registry.py` — replay cap from config.
- `copilot/tools/web_search.py` + `models.py` — Sonar quick/deep +
`answer` field + typed extractors.
- `copilot/tools/helpers.py` — tool description tightens `deep=true`
cost warning.
- `frontend/.../useCopilotStream.ts` — reconnect debounce.
- `frontend/.../GenericTool/GenericTool.tsx` + `helpers.ts` + tests —
render `answer`, deep-aware verbs / titles.
- `executor/simulator.py` + `simulator_test.py` + `executor/manager.py`
— cost tracking + model swap + user_id plumbing.

### Follow-up (deferred to a separate PR)

SDK per-token streaming via `include_partial_messages=True` was
attempted (commits `599e83543` + `530fa8f95`) and reverted here. The
two-signal model (StreamEvent partial deltas + AssistantMessage summary)
needs proper per-block diff tracking — when the partial stream delivers
a subset of the final block content, emit only
`summary.text[len(already_emitted):]` from the summary rather than
gating on a binary flag. Binary gating truncated replies in the field
when the partial stream delivered less than the summary (observed: "The
analysis template you" cut off mid-sentence because partial had streamed
that much and the rest only lived in the summary). SDK reasoning still
renders end-of-phase (as today); this PR's baseline per-token streaming
is unaffected.

### Checklist

For code changes:
- [x] Changes listed above
- [x] Test plan below
- [x] Tested according to the test plan:
- [x] `poetry run pytest backend/copilot/baseline/ backend/copilot/sdk/
backend/copilot/tools/web_search_test.py
backend/executor/simulator_test.py` — all pass (155 baseline + 927 SDK +
web_search + simulator)
- [x] `pnpm types && pnpm vitest run
src/app/(platform)/copilot/tools/GenericTool/` — pass
- [x] Manual: baseline live-streaming — Kimi K2.6 reasoning arrives
token-by-token, coalesced (no end-of-stream burst).
- [x] Manual: quick web_search via copilot UI — ~$0.005/call, answer +
citations rendered, cost logged as `provider=open_router`.
- [x] Manual: deep web_search — dispatched only on explicit research
phrasing; `sonar-deep-research` billed, UI labels say "Researched" / "N
research sources".
- [x] Manual: simulator dry-run — Gemini Flash-Lite, `[simulator] Turn
usage` log entry, PlatformCostLog row visible.
- [x] Manual: reconnect debounce — tab-focus thrash no longer produces
parallel XREADs in backend log.
- [ ] Manual: `CHAT_RENDER_REASONING_IN_UI=false` smoke-check —
reasoning collapse absent, no persisted reasoning row on reload.

For configuration changes:
- [x] `.env.default` — new config knobs fall back to pydantic defaults;
existing `CHAT_MODEL`/`CHAT_FAST_MODEL`/`CHAT_ADVANCED_MODEL` legacy
envs still honored upstream (unchanged by this PR).

### Companion PR

PR #12876 closes the `run_block`-via-copilot cost-leak gap (registers
`PerplexityBlock` / `FactCheckerBlock` in `BLOCK_COSTS`; documents the
credit/microdollar wallet boundary). Separate because the credit-wallet
side is orthogonal to the copilot microdollar / rate-limit surface this
PR ships.
2026-04-22 13:52:18 +07:00
Zamil Majdy
e3f6d36759 feat(backend/blocks): register 13 paid blocks + document credit/microdollar wallet boundary (#12876)
### Why / What / How

**Why.** Audit of `BLOCK_COSTS` against `credentials_store.py` system
credentials revealed **13 paid blocks** running for free from the credit
wallet's perspective — `BLOCK_COSTS.get(type(block))` returned `None`,
`cost = 0`, no `spend_credits` deduction. Users without their own API
key consumed system credentials with zero credit drain. Separately, the
credit wallet (user-facing prepaid balance) and the copilot microdollar
counter (operator-side meter that gates `daily_cost_limit_microdollars`)
were never documented as separate systems, so future readers kept
tripping on the "why isn't this block charging my limit?" question.

**What.** Three deltas, all credit-wallet-side:

- **Register the 13 paid blocks in `BLOCK_COSTS`** with reasonable
per-call credit prices (1 credit = $0.01). Pricing researched against
the providers' published rates with ~2-3x markup.
- **Document the credit/microdollar boundary** in
`copilot/rate_limit.py`: credits = user-facing prepaid wallet with
marketplace-creator charging; microdollars = operator-side meter that
only ticks on copilot LLM turns (baseline / SDK / web_search /
simulator). Block execution bills credits, not microdollars — explicit
contract.
- **Populate `provider_cost`** on PerplexityBlock so PlatformCostLog
rows carry the real OpenRouter `x-total-cost` value via the existing
`executor/cost_tracking.log_system_credential_cost` path (separate flow
from credit deduction).

### Block costs registered

| Provider | Block | Credits | Raw cost / markup |
|---|---|---|---|
| Perplexity (OpenRouter) | PerplexityBlock — Sonar | 1 | $0.001-0.005 /
call |
| | PerplexityBlock — Sonar Pro | 5 | $0.025 / call |
| | PerplexityBlock — Sonar Deep Research | 10 | up to $0.05 / call |
| Jina | FactCheckerBlock | 1 | $0.005 / call |
| Mem0 | AddMemoryBlock | 1 | $0.0004 / call (1c floor) |
| | SearchMemoryBlock | 1 | $0.004 / call |
| | GetAllMemoriesBlock | 1 | $0.004 / call |
| | GetLatestMemoryBlock | 1 | $0.004 / call |
| ScreenshotOne | ScreenshotWebPageBlock | 2 | $0.0085 / call (2.4x) |
| Nvidia | NvidiaDeepfakeDetectBlock | 2 | est $0.005 (no public SKU) |
| Smartlead | CreateCampaignBlock | 2 | $0.0065 send-equivalent (3x) |
| | AddLeadToCampaignBlock | 1 | $0.0065 (1.5x) |
| | SaveCampaignSequencesBlock | 1 | config-only |
| ZeroBounce | ValidateEmailsBlock | 2 | $0.008 / email (2.5x) |
| E2B + Anthropic | ClaudeCodeBlock | **100** | $0.50-$2 / typical
session (E2B sandbox + in-sandbox Claude) |

**Not in scope** — already covered via the SDK
`ProviderBuilder.with_base_cost()` pattern in their respective
`_config.py`: Exa, Linear, Airtable, Bannerbear, Wolfram, Firecrawl,
Wordpress, Baas, Stagehand, Dataforseo.

### How

1. `backend/data/block_cost_config.py` — 13 new `BlockCost` entries (3
Perplexity models + Fact Checker + 11 from this round).
2. `backend/copilot/rate_limit.py` — boundary docstring.
3. `backend/blocks/perplexity.py` — populate
`NodeExecutionStats.provider_cost` so PlatformCostLog rows carry the
real OpenRouter `x-total-cost` value.
4. Tests — `TestUnregisteredBlockRunsFree` regression +
`TestNewlyRegisteredBlockCosts` pinning every new entry by `cost_amount`
so a future refactor can't quietly drop one.

The companion Notion "Platform System Credentials" database has been
updated with a new `Platform Credit Cost` column populated across all 30
provider rows.

### Scope trim

An earlier revision piped block execution cost into the **copilot
microdollar counter** via `_record_block_microdollar_cost` in
`copilot/tools/helpers.py::execute_block`. That was reverted in
`16ae0f7b5` — the microdollar counter stays scoped to copilot LLM turns
only, credit wallet handles block execution. The pipe-through crossed a
boundary we explicitly want to keep.

### Changes

- `backend/data/block_cost_config.py` — 13 × `BlockCost` entries across
7 providers.
- `backend/blocks/perplexity.py` — populate `provider_cost` on the
execution stats (feeds PlatformCostLog).
- `backend/copilot/rate_limit.py` — boundary docstring only (no
behaviour change).
- `backend/copilot/tools/helpers_test.py` —
`TestUnregisteredBlockRunsFree` + `TestNewlyRegisteredBlockCosts` (8 new
regression tests).
- `backend/blocks/block_cost_tracking_test.py` — provider-cost
extraction pins.

### Checklist

For code changes:
- [x] Changes listed above
- [x] Test plan below
- [x] Tested according to the test plan:
- [x] `poetry run pytest backend/copilot/tools/helpers_test.py
backend/copilot/tools/run_block_test.py
backend/copilot/tools/continue_run_block_test.py
backend/blocks/block_cost_tracking_test.py
backend/blocks/test/test_perplexity.py` — passes
- [x] `poetry run pytest backend/executor/manager_cost_tracking_test.py
backend/copilot/rate_limit_test.py
backend/copilot/token_tracking_test.py` — passes (confirms docstring
edits didn't regress the LLM-turn microdollar path)
  - [x] Pyright clean on all touched files
- [ ] Manual: run PerplexityBlock via copilot `run_block` — credits
deduct, PlatformCostLog row visible with `provider_cost`, no
microdollar-counter tick.
- [ ] Manual: run an unregistered block via copilot — no error, no
credit drain, no silent billing.
- [ ] Manual: run ClaudeCodeBlock via builder — 100 credits deducted
from wallet.

### Companion PR

PR #12873 ships the copilot microdollar / rate-limit work (web_search
cost, simulator cost, reasoning / reconnect fixes). This PR is
credit-wallet only.
2026-04-22 12:03:02 +07:00
Nicholas Tindle
c1b9ed1f5e fix(backend/copilot): allow multiple compactions per turn (#12834)
### Why / What / How

**Why:** The old `CompactionTracker` set a `_done` flag after the first
completion and short-circuited every subsequent compaction in the same
turn. That blocked the SDK-internal compaction from running after a
pre-query compaction had already fired, so prompt-too-long errors
couldn't actually recover — retries saw the flag, bailed, and we re-hit
the context limit.

**What:** Drop the `_done` flag, track attempts and completions as
separate lists, and expose counters + an observability metadata builder
so callers can record compaction activity per turn.

**How:**
- Remove `_done` and `_compact_start` short-circuits.
- Track `_attempted_sources` / `_completed_sources` /
`_completed_count`.
- Expose `attempt_count`, `completed_count`, and
`get_observability_metadata()` / `get_log_summary()` for downstream
instrumentation (no caller change required in this PR).

### Changes 🏗️

- `backend/copilot/sdk/compaction.py` — rewritten `CompactionTracker`
internals; adds properties + observability helpers.
- `backend/copilot/sdk/compaction_test.py` — tests for multi-compaction
flow + new counters.

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [ ] I have tested my changes according to the test plan:
- [ ] `poetry run pytest backend/copilot/sdk/compaction_test.py -xvs`
passes
- [ ] Local chat that hits prompt-too-long now recovers via SDK
compaction instead of failing the turn

<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> **Medium Risk**
> Changes core streaming compaction state transitions and persistence
timing, which could affect UI event sequencing or compaction completion
behavior under concurrency; coverage is improved with new
multi-compaction tests.
> 
> **Overview**
> Fixes `CompactionTracker` so compaction is no longer single-shot per
turn: removes the `_done`/event-gate behavior, queues multiple
`on_compact()` hook firings via a pending transcript-path deque, and
allows subsequent SDK-internal compactions after a pre-query compaction
within the same query.
> 
> Adds lightweight instrumentation by tracking attempt/completion
sources and counts, plus `get_observability_metadata()` and
`get_log_summary()` (including source summaries like `sdk_internal:2`).
Updates/expands tests to cover multi-compaction flows, transcript-path
handling, and the new counters/metadata.
> 
> <sup>Reviewed by [Cursor Bugbot](https://cursor.com/bugbot) for commit
9bf8cdd367. Bugbot is set up for automated
code reviews on this repo. Configure
[here](https://www.cursor.com/dashboard/bugbot).</sup>
<!-- /CURSOR_SUMMARY -->

---------

Co-authored-by: majdyz <zamil.majdy@agpt.co>
2026-04-22 02:02:03 +00:00
Zamil Majdy
45bc167184 feat(backend/copilot): Kimi K2.6 fast default + 4-config matrix + coalesced reasoning + web_search tool (#12871)
### Why / What / How

**Why.** Three unrelated but interlocking problems on the baseline
(OpenRouter) copilot path, all blocking us from making Kimi K2.6 the
default fast model:

1. **Cost / capability gap on the default.** Kimi K2.6 prices at $0.60 /
$2.80 per MTok — ~5x cheaper input and ~5.4x cheaper output than Sonnet
4.6 — while tying Opus on SWE-Bench Verified (80.2% vs 80.8%) and
beating it on SWE-Bench Pro (58.6% vs 53.4%). OpenRouter exposes the
same `reasoning` / `include_reasoning` extension on Moonshot endpoints
that #12870 plumbed for Anthropic, so the reasoning collapse lights up
end-to-end without per-provider code.
2. **Kimi reasoning deltas freeze the UI.** K2.6 emits ~4,700
reasoning-delta SSE events per turn vs ~28 on Sonnet — the AI SDK v6
Reasoning UIMessagePart can't keep up and the tab locks. Needs a
coalescing buffer upstream.
3. **Kimi loops on `require_guide_read`.** The guide-guard checks
`session.messages` for a prior `agent_building_guide` call, but tool
calls aren't flushed to `session.messages` until the end of the turn —
mid-turn the check keeps returning False and Kimi calls the guide-load
tool repeatedly in the same turn. Needs an in-flight tracker that lives
on `ChatSession`.
4. **No `web_search` tool on either path.** Kimi doesn't have a native
web-search equivalent and the SDK path's native `WebSearch` (the Claude
Code CLI's built-in) doesn't carry cost accounting. We need one
implementation that both paths share and that reports cost through the
same tracker as every other tool call.

**What.** Five grouped deltas on the baseline service, tool layer, and
config:

- **Kimi K2.6 default.** `fast_standard_model` defaults to
`moonshotai/kimi-k2.6`. Full 2×2 model matrix below. Rollback is one env
var.
- **4-config model matrix.** `fast_standard_model` /
`fast_advanced_model` / `thinking_standard_model` /
`thinking_advanced_model`. Each cell independent so baseline can run a
cheap provider at the standard tier without leaking into the SDK path
(which is Anthropic-only by CLI contract). Legacy env vars
(`CHAT_MODEL`, `CHAT_FAST_MODEL`, `CHAT_ADVANCED_MODEL`) stay aliased
via `validation_alias` so live deployments keep resolving to the same
effective cell.
- **Reasoning delta coalescing.** `BaselineReasoningEmitter` buffers
deltas and flushes on a char-count OR time-interval threshold (32 chars
/ 40 ms). ~4,700 → ~150 SSE events per turn on Kimi; no perceptible
change on Sonnet (which was already well under the threshold).
- **In-flight tool-call tracker.** `ChatSession._inflight_tool_calls`
PrivateAttr is populated when a tool-call block is emitted and cleared
at turn end. `session.has_tool_been_called_this_turn(name)` now returns
True mid-turn, not just after the tool-result lands in
`session.messages` — which is what `require_guide_read` needs to cut the
loop.
- **New `web_search` copilot tool.** Wraps Anthropic's server-side
`web_search_20250305` beta via `AsyncAnthropic` (direct — OpenRouter
can't proxy server-side tool execution). Dispatches through
`claude-haiku-4-5` with `max_uses=1`. Cost estimated from published
rates ($0.010 per search + Haiku tokens) since the Anthropic Messages
API doesn't report cost on the response; reported to
`persist_and_record_usage(provider='anthropic')` on both paths. SDK
native `WebSearch` moved from `_SDK_BUILTIN_ALWAYS` into
`SDK_DISALLOWED_TOOLS` so both paths now dispatch through
`mcp__copilot__web_search`.

**How.**

1. `copilot/config.py` — 2×2 model fields with `AliasChoices` preserving
legacy env var names. `populate_by_name = True` so
`ChatConfig(fast_standard_model=...)` works in tests.
2. `copilot/baseline/service.py::_resolve_baseline_model` — resolves the
active baseline cell from `mode` + `tier`, no longer delegates to the
SDK resolver.
3. `copilot/baseline/reasoning.py` — `BaselineReasoningEmitter` gains
`_pending_delta` / `_last_flush_monotonic` and flushes on
`len(_pending_delta) >= _COALESCE_MIN_CHARS` OR `monotonic() -
_last_flush_monotonic >= _COALESCE_MAX_INTERVAL_MS / 1000`.
`_is_reasoning_route` rewritten as an anchored prefix match covering
`anthropic/`, `anthropic.`, `moonshotai/`, and `openrouter/kimi-` —
split from the narrower `_is_anthropic_model` gate that still governs
`cache_control` markers (which Kimi doesn't support).
4. `copilot/model.py::ChatSession` — `_inflight_tool_calls: set[str] =
PrivateAttr(default_factory=set)` plus `announce_inflight_tool_call` /
`clear_inflight_tool_calls` / `has_tool_been_called_this_turn`.
5. `copilot/tools/helpers.py::require_guide_read` — check
`session.has_tool_been_called_this_turn(_AGENT_GUIDE_TOOL_NAME)` before
falling back to scanning `session.messages`.
6. `copilot/tools/web_search.py` — new `WebSearchTool` +
`_extract_results` + `_estimate_cost_usd`. `is_available` gated on
`Settings().secrets.anthropic_api_key` so the deployment can roll back
just by unsetting the key.
7. `copilot/tools/__init__.py` — registers `web_search` in
`TOOL_REGISTRY` so it becomes `mcp__copilot__web_search` in the SDK
path.
8. `copilot/sdk/tool_adapter.py` — `WebSearch` moves to
`SDK_DISALLOWED_TOOLS`.

### Changes

- `copilot/config.py` — 2×2 model matrix with legacy env alias
preservation; `populate_by_name=True`.
- `copilot/baseline/service.py::_resolve_baseline_model` — resolves
against the new matrix.
- `copilot/baseline/reasoning.py` — `BaselineReasoningEmitter`
coalescing buffer; `_is_reasoning_route` rewritten as anchored prefix
match (covers `anthropic/`, `anthropic.`, `moonshotai/`,
`openrouter/kimi-`).
- `copilot/model.py::ChatSession` — `_inflight_tool_calls` PrivateAttr +
helpers.
- `copilot/baseline/service.py::_baseline_tool_executor` — calls
`announce_inflight_tool_call` after emitting `StreamToolInputAvailable`;
`clear_inflight_tool_calls` in the outer `finally` before persist.
- `copilot/tools/helpers.py::require_guide_read` — reads the new tracker
first.
- `copilot/tools/web_search.py` (new) — Anthropic `web_search_20250305`
wrapper + cost estimator.
- `copilot/tools/web_search_test.py` (new) — extractor / cost / dispatch
/ registry tests (12 total).
- `copilot/tools/models.py` — `WebSearchResponse` + `WebSearchResult` +
`ResponseType.WEB_SEARCH`.
- `copilot/tools/__init__.py` — registers `web_search`.
- `copilot/sdk/tool_adapter.py` — moves native `WebSearch` to
`SDK_DISALLOWED_TOOLS`.

### Checklist

For code changes:
- [x] Changes listed above
- [x] Test plan below
- [ ] Tested according to the test plan:
  - [x] `poetry run pytest backend/copilot/baseline/` — all pass
- [x] `poetry run pytest backend/copilot/sdk/` — all pass (SDK resolver
untouched)
- [x] `poetry run pytest backend/copilot/tools/web_search_test.py` — 12
pass
- [ ] Manual: send a multi-step prompt on fast mode with default config;
confirm backend routes to `moonshotai/kimi-k2.6`, SSE stream carries
`reasoning-start/delta/end` (coalesced), Reasoning collapse renders +
survives hard reload.
- [ ] Manual: 43-tool payload reliability on Kimi — watch for malformed
tool-call JSON or wrong-tool selection.
- [ ] Manual: `CHAT_FAST_STANDARD_MODEL=anthropic/claude-sonnet-4-6`
restarts confirm Sonnet routing (rollback path works).
- [ ] Manual: SDK path (`CHAT_USE_CLAUDE_AGENT_SDK=true`) still selects
the SDK service and uses `thinking_standard_model` = Sonnet (no Kimi
leaked into extended thinking).
- [ ] Manual: prompt that forces `web_search` — confirm results render,
`persist_and_record_usage(provider='anthropic')` runs, cost lands in the
per-user ledger.
- [ ] Manual: ask Kimi a question that would require
`agent_building_guide` — confirm the guide loads exactly once per turn
(no loop).

For configuration changes:
- [x] `.env.default` — all four model fields fall back to the pydantic
defaults; legacy `CHAT_MODEL` / `CHAT_FAST_MODEL` /
`CHAT_ADVANCED_MODEL` remain honored via `AliasChoices`.
2026-04-22 08:47:08 +07:00
Nicholas Tindle
e4f291e54b feat(frontend): add AutoGPT logo to share page and zip download for outputs (#11741)
### Why / What / How

**Why:** The share page was unbranded (no logo/navigation) and images
from workspace files couldn't render because the proxy didn't handle
public share URLs. Zip downloads also had several gaps — no size limits,
no workspace file support, silent failures on data URLs, and single
files got wrapped in unnecessary zips.

**What:** Adds AutoGPT branding to the share page, secure public access
to workspace files via a SharedExecutionFile allowlist, and a hardened
zip download module.

**How:** Backend scans execution outputs for `workspace://` URIs on
share-enable and persists an allowlist in a new `SharedExecutionFile`
table. A new unauthenticated endpoint serves files validated against
this allowlist. Frontend proxy routing is extended (with UUID
validation) to handle the 7-segment public share download path as a
binary response. Download logic is consolidated into a shared module
with size limits, parallel fetches, filename sanitization, and
single-file direct download.

### Changes 🏗️

**Share page branding:**
- AutoGPT logo header centered at top, linking to `/`
- Dark/light mode variants with correct `priority` on visible variant
only

**Secure public workspace file access (backend):**
- New `SharedExecutionFile` Prisma model with `@@unique([shareToken,
fileId])` constraint
- `_extract_workspace_file_ids()` scans outputs for `workspace://` URIs
(handles nested dicts/lists)
- `create_shared_execution_files()` / `delete_shared_execution_files()`
manage allowlist lifecycle
- Re-share cleans up stale records before creating new ones (prevents
old token access)
- `GET /public/shared/{token}/files/{id}/download` — validates against
allowlist, uniform 404 for all failures
- `Content-Disposition: inline` for share page rendering
- Hand-written Prisma migration
(`20260417000000_add_shared_execution_file`)

**Frontend proxy fix:**
- `isWorkspaceDownloadRequest` extended to match public share path
(7-segment)
- UUID format validation on dynamic path segments (file IDs, share
tokens)
- 30+ adversarial security tests: path traversal, SQL injection, SSRF
payloads, unicode homoglyphs, null bytes, prototype pollution, etc.

**Download module (`download-outputs.ts`):**
- Consolidated from two divergent copies into single shared module
- `fetchFileAsBlob` with content-length pre-check before buffering
- `sanitizeFilename` strips path traversal, leading dots, falls back to
"file"
- `getUniqueFilename` deduplicates with counter suffix
- `fetchInParallel` with configurable concurrency (5)
- 50 MB per-file limit, 200 MB aggregate limit
- Data URL try-catch, relative URL support (`/api/proxy/...`)
- Single-file downloads skip zip, go directly to browser download
- Dynamic JSZip import for bundle optimization
- 26 unit tests

**Share page file rendering:**
- `WorkspaceFileRenderer` builds public share URLs when `shareToken` is
in metadata
- `RunOutputs` propagates `shareToken` to renderer metadata

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  - [x] Share page renders with centered AutoGPT logo
  - [x] Logo links to `/` and shows correct dark/light variant
  - [x] Workspace images render inline on share page
  - [x] Download all produces zip with workspace images included
  - [x] Single-file download skips zip, downloads directly
- [x] Re-sharing generates new token and cleans up old allowlist records
  - [x] Public file download returns 404 for files not in allowlist
  - [x] All frontend tests pass (122 tests across 3 suites)
  - [x] Backend formatter + pyright pass
  - [x] Frontend format + lint + types pass

#### For configuration changes:

- [x] `.env.default` is updated or already compatible with my changes
- [x] `docker-compose.yml` is updated or already compatible with my
changes
- [x] I have included a list of my configuration changes in the PR
description (under **Changes**)

> Note: New Prisma migration required. No env/docker changes needed.

<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> **Medium Risk**
> Adds a new unauthenticated file download path gated by a database
allowlist plus a new Prisma model/migration; mistakes here could expose
workspace files or break sharing. Frontend download behavior also
changes significantly (zipping/fetching), which could impact
large-output performance and edge cases.
> 
> **Overview**
> Enables **public rendering and downloading of workspace files on
shared execution pages** by introducing a `SharedExecutionFile`
allowlist tied to the share token and populating it when sharing is
enabled (and clearing it on disable/re-share).
> 
> Adds `GET /public/shared/{share_token}/files/{file_id}/download` (no
auth) that validates the requested file against the allowlist and
returns a uniform 404 on failure; workspace download responses now
support `inline` `Content-Disposition` via the exported
`create_file_download_response` helper.
> 
> Frontend updates the share page to pass `shareToken` into output
renderers so `WorkspaceFileRenderer` can build public-share download
URLs; the proxy matcher is extended/strictly UUID-validated for both
workspace and public-share download paths with extensive adversarial
tests. Output downloading is consolidated into `download-outputs.ts`
using dynamic `jszip` import, filename sanitization/deduping,
concurrency + size limits, and a single-file non-zip fast path.
> 
> <sup>Reviewed by [Cursor Bugbot](https://cursor.com/bugbot) for commit
e2f5bd9b5a. Bugbot is set up for automated
code reviews on this repo. Configure
[here](https://www.cursor.com/dashboard/bugbot).</sup>
<!-- /CURSOR_SUMMARY -->

---------

Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Nicholas Tindle <ntindle@users.noreply.github.com>
Co-authored-by: Otto <otto@agpt.co>
2026-04-21 16:26:37 +00:00
Bently
6efbc59fd8 feat(backend): platform server linking API for multi-platform CoPilot (#12615)
## Why
AutoPilot (CoPilot) needs to reach users across chat platforms — Discord
first, Telegram / Slack / Teams / WhatsApp next. To make usage and
billing coherent, every conversation resolves to one AutoGPT account.
There are two independent linking flows:

- **SERVER links**: the first person to claim a server (Discord guild,
Telegram group, …) becomes its owner. Anyone in the server can chat with
the bot; all usage bills to the owner.
- **USER links**: an individual links their 1:1 DMs with the bot to
their own AutoGPT account. Independent from server links — a server
owner still has to link their DMs separately.

## What
Backend for platform linking, split cleanly by trust boundary:

- **Bot-facing operations** run over cluster-internal RPC via a new
`PlatformLinkingManager(AppService)`. No shared bearer token; trust is
the cluster network itself.
- **User-facing operations** stay on REST under JWT auth (the same
pattern as every other feature).

### REST endpoints (JWT auth)

- `GET /api/platform-linking/tokens/{token}/info` — non-sensitive
display info for the link page
- `POST /api/platform-linking/tokens/{token}/confirm` — confirm a SERVER
link
- `POST /api/platform-linking/user-tokens/{token}/confirm` — confirm a
USER link
- `GET /api/platform-linking/links` / `DELETE /links/{id}` — manage
server links
- `GET /api/platform-linking/user-links` / `DELETE /user-links/{id}` —
manage DM links

### `PlatformLinkingManager` `@expose` methods (internal RPC)

- `resolve_server_link(platform, platform_server_id) -> ResolveResponse`
- `resolve_user_link(platform, platform_user_id) -> ResolveResponse`
- `create_server_link_token(req) -> LinkTokenResponse`
- `create_user_link_token(req) -> LinkTokenResponse`
- `get_link_token_status(token) -> LinkTokenStatusResponse`
- `start_chat_turn(req) -> ChatTurnHandle` — resolves the owner,
persists the user message, creates the stream-registry session, enqueues
the turn; returns `(session_id, turn_id, user_id, subscribe_from="0-0")`
so the caller subscribes directly to the per-turn Redis stream.

### New DB models
- `PlatformLink` — `(platform, platformServerId)` → owner's AutoGPT
`userId`
- `PlatformUserLink` — `(platform, platformUserId)` → AutoGPT `userId`
(for DMs)
- `PlatformLinkToken` — one-time token with `linkType` discriminator
(SERVER | USER) and 30-min TTL

## How

- **New `backend/platform_linking/` package**: `models.py` (Pydantic
types), `links.py` (link CRUD helpers — pure business logic), `chat.py`
(`start_chat_turn` orchestration), `manager.py`
(`PlatformLinkingManager(AppService)` + `PlatformLinkingManagerClient`).
Pattern matches `backend/notifications/` + `backend/data/db_manager.py`.
- **Exception translation at the edge**. Helpers raise domain exceptions
(`NotFoundError`, `LinkAlreadyExistsError`, `LinkTokenExpiredError`,
`LinkFlowMismatchError`, `NotAuthorizedError` — all `ValueError`
subclasses in `backend.util.exceptions` so they auto-register with the
RPC exception-mapping). REST routes translate to HTTP codes via a 7-line
`_translate()` helper.
- **Independent scopes, no DM fallback**. `find_server_link()` and
`find_user_link()` each query their own table. A user who owns a linked
server does not leak that identity into their DMs.
- **Race-safe token consumption**. Confirm paths do atomic `update_many`
with `usedAt = None` + `expiresAt > now` in the WHERE clause;
`create_*_token` invalidates pending tokens before issuing a new one.
- **Bug fix**: `start_chat_turn` persists the user message via
`append_and_save_message` before enqueueing the executor turn — mirrors
`backend/api/features/chat/routes.py`. The previous `chat_proxy.py`
skipped this and ran the executor with no user message in history.
- **Streaming**. Copilot streaming lives on Redis Streams (persistent,
replayable). The bot subscribes directly with `subscribe_from="0-0"`, so
late subscribers replay the full stream; no HTTP SSE proxy needed.
- **No PII in logs**: logs reference `session_id`, `turn_id`,
`server_id`, and AutoGPT `user_id` (last 8 chars), but never raw
platform user IDs.
- **New pod**. `PlatformLinkingManager` runs as its own `AppProcess` on
port `8009`; client via `get_platform_linking_manager_client()`. The
infra chart lands in
[cloud-infrastructure#310](https://github.com/Significant-Gravitas/AutoGPT_cloud_infrastructure/pull/310).

## Tests
- **Models** (`models_test.py`) — Platform / LinkType enums, request
validation (CreateLinkToken / ResolveServer / BotChat), response
schemas.
- **Helpers** (`links_test.py`) — resolve, token create (both flows, 409
on already-linked), token status (pending / linked / expired /
superseded-with-no-link), token info (404 / 410), confirm (404 / wrong
flow / already used / expired / same-user / other-user), delete authz.
- **AppService wiring** (`manager_test.py`) — `@expose` methods delegate
to helpers; client surface covers bot-facing ops and excludes
user-facing ones.
- **Adversarial** (`manager_test.py`, `routes_test.py`):
- `asyncio.gather` double-confirm with same user and with two different
users — exactly one winner, other gets clean `LinkTokenExpiredError`, no
double `PlatformLink.create`.
  - Server- and user-link confirm races.
- `TokenPath` regex guard: rejects `%24`, URL-encoded path traversal,
>64 chars; accepts `secrets.token_urlsafe` shape.
- DELETE `link_id` with SQL-injection-style and path-traversal inputs
returns 404 via `NotFoundError`.

## Stack
- #12618 — bot service (rebased onto this so it can consume
`PlatformLinkingManagerClient`)
- #12624 — `/link/{token}` frontend page
-
[cloud-infrastructure#310](https://github.com/Significant-Gravitas/AutoGPT_cloud_infrastructure/pull/310)
— Helm chart for `copilot-bot` + new `platform-linking-manager`

Merge order: this → #12618#12624, infra whenever.

---------

Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
Co-authored-by: CodeRabbit <noreply@coderabbit.ai>
2026-04-21 16:01:03 +00:00
Nicholas Tindle
6924cf90a5 fix(frontend/copilot): artifact panel fixes (SECRT-2254/2223/2220/2255/2224/2256/2221) (#12856)
### Why / What / How


https://github.com/user-attachments/assets/ca26e0b0-d35d-4a5b-b95f-2421b9907742


**Why** — The Artifact & Side Task List project
(https://linear.app/autogpt/project/artifact-and-side-task-list-ef863c93da3c)
accumulated seven related bugs in the copilot artifact panel. The user
kept seeing panels stuck open, previews broken, clicks not registering —
each ticket was small but they all lived in the same small surface area,
so one review pass is easier than five.

Closes SECRT-2254, SECRT-2223, SECRT-2220, SECRT-2255, SECRT-2224,
SECRT-2256, SECRT-2221.

**What** — Five independent fixes, each in its own commit, shipped
together:

1. **Fragment-link interceptor + render error boundary** (SECRT-2255
crash when clicking `<a href="#x">` in HTML artifacts). Sandboxed srcdoc
iframes resolve fragment links against the parent's URL, so clicking
`#activation` in a Plotly TOC tried to navigate the copilot page into
the iframe. Inject a click-capture script into every artifact iframe;
also wrap the renderer in `ArtifactErrorBoundary` so any future render
throw surfaces with a copyable error instead of a blank panel.
2. **Close panel on copilot page unmount** (SECRT-2254 / 2223 / 2220 —
panel stays open, reopens on unrelated navigation, opens by default on
session switch). The Zustand store outlived page unmounts, so `isOpen:
true` survived `/profile` → `/home` → back. One `useEffect` cleanup in
`useAutoOpenArtifacts` calls `resetArtifactPanel()` on unmount.
3. **Sync loading flip on Try Again** (SECRT-2224 "try again doesn't do
anything"). Retry was correct but the loading-state flip was deferred to
an effect, so a retry that re-failed was visually indistinguishable from
a no-op. `retry()` now sets `isLoading: true` / `error: null`
synchronously with the click so the skeleton flashes every time.
4. **Pointer capture on resize drag** (SECRT-2256 "can't drag right when
expanded far left, click doesn't stop it"). The sandboxed iframe was
eating `pointermove`/`pointerup` events when the cursor drifted over it,
freezing the drag and never delivering the release. `setPointerCapture`
on the handle routes all subsequent pointer events through it regardless
of what's under the cursor.
5. **Stop size-gating natively-rendered artifacts + cache-bust retry**
(SECRT-2221 "broken hi-res PNG preview"). The blanket >10 MB size gate
pushed large images / videos / PDFs into `download-only`, so clicking a
hi-res PNG offered a download instead of a preview. Split the gate so it
only applies to content we actually render in JS (text/html/code/etc).
Image and video retries also append a cache-bust query so the browser
can't silently reuse a negative-cached failure.

**How** — Five commits, one concern each, preserved in the order they
were written. Every fix lands with a regression test that fails on the
unfixed code and passes after.

### Changes 🏗️

- `iframe-sandbox-csp.ts` + usage sites —
`FRAGMENT_LINK_INTERCEPTOR_SCRIPT` injected into all three srcdoc iframe
templates (HTML artifact, inline HTMLRenderer, React artifact).
- `ArtifactErrorBoundary.tsx` (new) — class error boundary local to the
artifact panel with a copyable error fallback.
- `useAutoOpenArtifacts.ts` — unmount cleanup calls
`resetArtifactPanel()`.
- `useArtifactContent.ts` — `retry()` flips loading state synchronously.
- `ArtifactDragHandle.tsx` — `setPointerCapture` /
`releasePointerCapture`; `touch-action: none`.
- `helpers.ts` — split classifier; `NATIVELY_RENDERED` exempts
image/video/pdf from the size gate.
- `ArtifactContent.tsx` — image/video carry a retry nonce that appends
`?_retry=N` on Try Again.
- Test files — new
`ArtifactErrorBoundary`/`ArtifactDragHandle`/`HTMLRenderer` tests, plus
regression cases added to `ArtifactContent.test.tsx`, `helpers.test.ts`,
`iframe-sandbox-csp.test.ts`, `reactArtifactPreview.test.ts`,
`useAutoOpenArtifacts.test.ts`.

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] `pnpm vitest run src/app/\(platform\)/copilot
src/components/contextual/OutputRenderers
src/lib/__tests__/iframe-sandbox-csp.test.ts` — 247/247 pass
  - [x] `pnpm format && pnpm types` clean
- [x] Manual: open the Plotly-style TOC HTML artifact (SECRT-2255
repro), click each anchor — iframe scrolls internally, browser URL bar
stays put
- [x] Manual: open panel → navigate to /profile → navigate back → panel
closed (SECRT-2254)
- [x] Manual: panel open in session A → click different session → panel
closed (SECRT-2223)
- [ ] Manual: simulate a failed artifact fetch → click Try Again →
skeleton flashes before result (SECRT-2224)
- [x] Manual: expand panel to near-full width → drag back right,
crossing over the iframe → drag keeps working and release ends it
(SECRT-2256)
- [x] Manual: upload a ~25 MB PNG → clicking it previews in an `<img>`,
not a download button (SECRT-2221)

Replaces #12836, #12837, #12838, #12839, #12840 — same fixes, bundled
for review.


<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> **Medium Risk**
> Touches artifact rendering and iframe `srcDoc` generation (including
injected scripts) plus panel state/drag interactions; regressions could
break previews or resizing, but changes are scoped to the copilot
artifact UI with broad test coverage.
> 
> **Overview**
> Improves Copilot’s artifact panel resilience and UX by **resetting
panel state on page unmount/session changes**, making content retries
immediately show the loading skeleton, and fixing resize drags via
pointer capture so iframes can’t “steal” pointer events.
> 
> Hardens artifact rendering by adding a local `ArtifactErrorBoundary`
that reports to Sentry and shows a copyable error fallback instead of a
blank/crashed panel.
> 
> Fixes iframe-based previews by injecting a
`FRAGMENT_LINK_INTERCEPTOR_SCRIPT` into HTML and React artifact `srcDoc`
so `#anchor` clicks scroll within the iframe rather than navigating the
parent URL, and adjusts artifact classification/retry behavior so large
images/videos/PDFs remain previewable and image/video retries cache-bust
failed URLs.
> 
> <sup>Reviewed by [Cursor Bugbot](https://cursor.com/bugbot) for commit
bde37a13fd. Bugbot is set up for automated
code reviews on this repo. Configure
[here](https://www.cursor.com/dashboard/bugbot).</sup>
<!-- /CURSOR_SUMMARY -->

---------

Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-21 15:53:01 +00:00
Nicholas Tindle
07e5a6a9e4 [Snyk] Security upgrade next from 15.4.10 to 15.4.11 (#12715)
![snyk-top-banner](https://res.cloudinary.com/snyk/image/upload/r-d/scm-platform/snyk-pull-requests/pr-banner-default.svg)

### Snyk has created this PR to fix 1 vulnerabilities in the yarn
dependencies of this project.

#### Snyk changed the following file(s):

- `autogpt_platform/frontend/package.json`


#### Note for
[zero-installs](https://yarnpkg.com/features/zero-installs) users

If you are using the Yarn feature
[zero-installs](https://yarnpkg.com/features/zero-installs) that was
introduced in Yarn V2, note that this PR does not update the
`.yarn/cache/` directory meaning this code cannot be pulled and
immediately developed on as one would expect for a zero-install project
- you will need to run `yarn` to update the contents of the
`./yarn/cache` directory.
If you are not using zero-install you can ignore this as your flow
should likely be unchanged.



<details>
<summary>⚠️ <b>Warning</b></summary>

```
Failed to update the yarn.lock, please update manually before merging.
```

</details>



#### Vulnerabilities that will be fixed with an upgrade:

|  | Issue |  
:-------------------------:|:-------------------------
![high
severity](https://res.cloudinary.com/snyk/image/upload/w_20,h_20/v1561977819/icon/h.png
'high severity') | Allocation of Resources Without Limits or Throttling
<br/>[SNYK-JS-NEXT-15921797](https://snyk.io/vuln/SNYK-JS-NEXT-15921797)




---

> [!IMPORTANT]
>
> - Check the changes in this PR to ensure they won't cause issues with
your project.
> - Max score is 1000. Note that the real score may have changed since
the PR was raised.
> - This PR was automatically created by Snyk using the credentials of a
real user.

---

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---

**Learn how to fix vulnerabilities with free interactive lessons:**

🦉 [Allocation of Resources Without Limits or
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[//]: #
'snyk:metadata:{"breakingChangeRiskLevel":null,"FF_showPullRequestBreakingChanges":false,"FF_showPullRequestBreakingChangesWebSearch":false,"customTemplate":{"variablesUsed":[],"fieldsUsed":[]},"dependencies":[{"name":"next","from":"15.4.10","to":"15.4.11"}],"env":"prod","issuesToFix":["SNYK-JS-NEXT-15921797"],"prId":"f3cd7cb3-bc59-4d03-8a12-19100988d06e","prPublicId":"f3cd7cb3-bc59-4d03-8a12-19100988d06e","packageManager":"yarn","priorityScoreList":[null],"projectPublicId":"3d924968-0cf3-4767-9609-501fa4962856","projectUrl":"https://app.snyk.io/org/significant-gravitas/project/3d924968-0cf3-4767-9609-501fa4962856?utm_source=github&utm_medium=referral&page=fix-pr","prType":"fix","templateFieldSources":{"branchName":"default","commitMessage":"default","description":"default","title":"default"},"templateVariants":["updated-fix-title","pr-warning-shown"],"type":"auto","upgrade":["SNYK-JS-NEXT-15921797"],"vulns":["SNYK-JS-NEXT-15921797"],"patch":[],"isBreakingChange":false,"remediationStrategy":"vuln"}'

<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> **Medium Risk**
> Patch-level upgrade of a core runtime/build dependency (Next.js) can
affect app rendering/build behavior despite being scoped to
dependency/lockfile changes.
> 
> **Overview**
> Upgrades the frontend framework dependency `next` from `15.4.10` to
`15.4.11` in `package.json`.
> 
> Updates `pnpm-lock.yaml` to reflect the new Next.js version (including
`@next/env`) and re-resolves dependent packages that pin `next` in their
peer/optional dependency graphs (e.g., `@sentry/nextjs`,
`@vercel/analytics`, Storybook Next integration).
> 
> <sup>Reviewed by [Cursor Bugbot](https://cursor.com/bugbot) for commit
dc19e1f178. Bugbot is set up for automated
code reviews on this repo. Configure
[here](https://www.cursor.com/dashboard/bugbot).</sup>
<!-- /CURSOR_SUMMARY -->

---------

Co-authored-by: snyk-bot <snyk-bot@snyk.io>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-21 15:44:47 +00:00
Zamil Majdy
a098f01bd2 feat(builder): AI chat panel for the flow builder (#12699)
### Why

The flow builder had no AI assistance. Users had to switch to a separate
Copilot session to ask about or modify the agent they were looking at,
and that session had no context on the graph — so the LLM guessed, or
the user had to describe the graph by hand.

### What

An AI chat panel anchored to the `/build` page. Opens with a chat-circle
button (bottom-right), binds to the currently-opened agent, and offers
**only** two tools: `edit_agent` and `run_agent`. Per-agent session is
persisted server-side, so a refresh resumes the same conversation. Gated
behind `Flag.BUILDER_CHAT_PANEL` (default off;
`NEXT_PUBLIC_FORCE_FLAG_BUILDER_CHAT_PANEL=true` to enable locally).

### How

**Frontend — new**:
- `(platform)/build/components/BuilderChatPanel/` — panel shell +
`useBuilderChatPanel.ts` coordinator. Renders the shared Copilot
`ChatMessagesContainer` + `ChatInput` (thought rendering, pulse chips,
fast-mode toggle — all reused, no parallel chat stack). Auto-creates a
blank agent when opened with no `flowID`. Listens for `edit_agent` /
`run_agent` tool outputs and wires them to the builder in-place: edit →
`flowVersion` URL param + canvas refetch; run → `flowExecutionID` URL
param → builder's existing execution-follow UI opens.

**Frontend — touched (minimal)**:
- `copilot/components/CopilotChatActionsProvider` — new `chatSurface:
"copilot" | "builder"` flag so cards can suppress "Open in library" /
"Open in builder" / "View Execution" buttons when the chat is the
builder panel (you're already there).
- `copilot/tools/RunAgent/components/ExecutionStartedCard` — title is
now status-aware (`QUEUED → "Execution started"`, `COMPLETED →
"Execution completed"`, `FAILED → "Execution failed"`, etc.).
- `build/components/FlowEditor/Flow/Flow.tsx` — mount the panel behind
the feature flag.

**Backend — new**:
- `copilot/builder_context.py` — the builder-session logic module. Holds
the tool whitelist (`edit_agent`, `run_agent`), the permissions
resolver, the session-long system-prompt suffix (graph id/name + full
agent-building guide — cacheable across turns), and the per-turn
`<builder_context>` prefix (live version + compact nodes/links
snapshot).
- `copilot/builder_context_test.py` — covers both builders, ownership
forwarding, and cap behavior.

**Backend — touched**:
- `api/features/chat/routes.py` — `CreateSessionRequest` gains
`builder_graph_id`. When set, the endpoint routes through
`get_or_create_builder_session` (keyed on `user_id`+`graph_id`, with a
graph-ownership check). No new route; the former `/sessions/builder` is
folded into `POST /sessions`.
- `copilot/model.py` — `ChatSessionMetadata.builder_graph_id`;
`get_or_create_builder_session` helper.
- `data/graph.py` — `GraphSettings.builder_chat_session_id` (new typed
field; stores the builder-chat session pointer per library agent).
- `api/features/library/db.py` —
`update_library_agent_version_and_settings` preserves
`builder_chat_session_id` across graph-version bumps.
- `copilot/tools/edit_agent.py`, `run_agent.py` — builder-bound guard:
default missing `agent_id` to the bound graph, reject any other id.
`run_agent` additionally inlines `node_executions` into dry-run
responses so the LLM can inspect per-node status in the same turn
instead of a follow-up `view_agent_output`. `wait_for_result` docs now
explain the two dispatch modes.
- `copilot/tools/helpers.py::require_guide_read` — bypassed for
builder-bound sessions (the guide is already in the system-prompt
suffix).
- `copilot/tools/agent_generator/pipeline.py` + `tools/models.py` —
`AgentSavedResponse.graph_version` so the frontend can flip
`flowVersion` to the newly-saved version.
- `copilot/baseline/service.py` + `sdk/service.py` — inject the builder
context suffix into the system prompt and the per-turn prefix into the
current user message.
- `blocks/_base.py` — `validate_data(..., exclude_fields=)` so dry-run
can bypass credential required-checks for blocks that need creds in
normal mode (OrchestratorBlock). `blocks/perplexity.py` override
signature matches.
- `executor/simulator.py` — OrchestratorBlock dry-run iteration cap `1 →
min(original, 10)` so multi-role patterns (Advocate/Critic) actually
close the loop; `manager.py` synthesizes placeholder creds in dry-run so
the block's schema validation passes.

### Session lookup

The builder-chat session pointer lives on
`LibraryAgent.settings.builder_chat_session_id` (typed via
`GraphSettings`). `get_or_create_builder_session` reads/writes it
through `library_db().get_library_agent_by_graph_id` +
`update_library_agent(settings=...)` — no raw SQL or JSON-path filter.
Ownership is enforced by the library-agent query's `userId` filter. The
per-session builder binding still lives on
`ChatSession.metadata.builder_graph_id` (used by
`edit_agent`/`run_agent` guards and the system-prompt injection).

### Scope footnotes

- Feature flag defaults **false**. Rollout gate lives in LaunchDarkly.
- No schema migration required: `builder_chat_session_id` slots into the
existing `LibraryAgent.settings` JSON column via the typed
`GraphSettings` model.
- Commits that address review / CI cycles are interleaved with feature
commits — see the commit log for the per-change rationale.

### Test plan

- [x] `pnpm test:unit` + backend `poetry run test` for new and touched
modules
- [x] Agent-browser pass: panel toggle / auto-create / real-time edit
re-render / real-time exec URL subscribe / queue-while-streaming /
cross-graph reset / hard-refresh session persist
- [x] Codecov patch ≥ 80% on diff

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-21 22:47:23 +07:00
Nicholas Tindle
59273fe6a0 fix(frontend): forward sentry-trace and baggage across API proxy (#12835)
### Why / What / How

**Why:** Every request that went through Next's rewrite proxy broke
distributed tracing. The browser Sentry SDK emitted `sentry-trace` and
`baggage`, but `createRequestHeaders` only forwarded impersonation + API
key, so the backend started a disconnected transaction. The frontend →
backend lineage never appeared in Sentry. Same gap on
direct-from-browser requests: the custom mutator never attached the
trace headers itself, so even non-proxied paths lost the link.

**What:**
- **Server side:** forward `sentry-trace` and `baggage` from
`originalRequest.headers` alongside the existing impersonation/API key
forwarding.
- **Client side:** the custom mutator pulls trace data via
`Sentry.getTraceData()` and attaches it to outgoing headers when running
on the client.

**How:** Inline additions — no new observability module, no new
dependencies beyond `@sentry/nextjs` which the frontend already uses for
Sentry init.

### Changes 🏗️

- `src/lib/autogpt-server-api/helpers.ts` — forward `sentry-trace` +
`baggage` in `createRequestHeaders`.
- `src/app/api/mutators/custom-mutator.ts` — import `@sentry/nextjs`,
attach `Sentry.getTraceData()` on client-side requests.
- `src/app/api/mutators/__tests__/custom-mutator.test.ts` — three new
tests: trace-data present, trace-data empty, server-side no-op.

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [ ] I have tested my changes according to the test plan:
- [x] `pnpm vitest run
src/app/api/mutators/__tests__/custom-mutator.test.ts` passes (6/6
locally)
  - [x] `pnpm format && pnpm lint` clean
- [x] `pnpm types` clean for touched files (pre-existing unrelated type
errors on dev are untouched)
- [ ] In a local session with Sentry enabled, a `/copilot` chat turn
produces a distributed trace that spans frontend transaction → backend
transaction (single trace ID in Sentry)

<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> **Low Risk**
> Low risk: header-only changes to request construction for
observability, with added tests; primary risk is unintended header
propagation affecting upstream/proxy behavior.
> 
> **Overview**
> Restores **Sentry distributed tracing continuity** for
frontend→backend calls by propagating `sentry-trace`/`baggage` headers.
> 
> On the client, `customMutator` now reads `Sentry.getTraceData()` and
attaches string trace headers to outgoing requests (guarded for
server-side and older Sentry builds). On the server/proxy path,
`createRequestHeaders` now forwards `sentry-trace` and `baggage` from
the incoming `originalRequest` alongside existing impersonation/API-key
forwarding, with new unit tests covering these cases.
> 
> <sup>Reviewed by [Cursor Bugbot](https://cursor.com/bugbot) for commit
0f6946b776. Bugbot is set up for automated
code reviews on this repo. Configure
[here](https://www.cursor.com/dashboard/bugbot).</sup>
<!-- /CURSOR_SUMMARY -->

---------

Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-21 15:29:19 +00:00
Nicholas Tindle
38c2844b83 feat(admin): Add system diagnostics and execution management dashboard (#11235)
### Changes 🏗️
This PR adds a comprehensive admin diagnostics dashboard for monitoring
system health and managing running executions.


https://github.com/user-attachments/assets/f7afa3ed-63d8-4b5c-85e4-8756d9e3879e


#### Backend Changes:
- **New data layer** (backend/data/diagnostics.py): Created a dedicated
diagnostics module following the established data layer pattern
- get_execution_diagnostics() - Retrieves execution metrics (running,
queued, completed counts)
  - get_agent_diagnostics() - Fetches agent-related metrics
- get_running_executions_details() - Lists all running executions with
detailed info
- stop_execution() and stop_executions_bulk() - Admin controls for
stopping executions

- **Admin API endpoints**
(backend/server/v2/admin/diagnostics_admin_routes.py):
  - GET /admin/diagnostics/executions - Execution status metrics
  - GET /admin/diagnostics/agents - Agent utilization metrics
- GET /admin/diagnostics/executions/running - Paginated list of running
executions
  - POST /admin/diagnostics/executions/stop - Stop single execution
- POST /admin/diagnostics/executions/stop-bulk - Stop multiple
executions
  - All endpoints secured with admin-only access

#### Frontend Changes:
- **Diagnostics Dashboard**
(frontend/src/app/(platform)/admin/diagnostics/page.tsx):
- Real-time system metrics display (running, queued, completed
executions)
  - RabbitMQ queue depth monitoring
  - Agent utilization statistics
  - Auto-refresh every 30 seconds

- **Execution Management Table**
(frontend/src/app/(platform)/admin/diagnostics/components/ExecutionsTable.tsx):
- Displays running executions with: ID, Agent Name, Version, User
Email/ID, Status, Start Time
  - Multi-select functionality with checkboxes
  - Individual stop buttons for each execution
  - "Stop Selected" and "Stop All" bulk actions
  - Confirmation dialogs for safety
  - Pagination for handling large datasets
  - Toast notifications for user feedback

#### Security:
- All admin endpoints properly secured with requires_admin_user
decorator
- Frontend routes protected with role-based access controls
- Admin navigation link only visible to admin users

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  
  - [x] Verified admin-only access to diagnostics page
  - [x] Tested execution metrics display and auto-refresh
  - [x] Confirmed RabbitMQ queue depth monitoring works
  - [x] Tested stopping individual executions
  - [x] Tested bulk stop operations with multi-select
  - [x] Verified pagination works for large datasets
  - [x] Confirmed toast notifications appear for all actions

#### For configuration changes:

- [x] `.env.default` is updated or already compatible with my changes
(no changes needed)
- [x] `docker-compose.yml` is updated or already compatible with my
changes (no changes needed)
- [x] I have included a list of my configuration changes in the PR
description (no config changes required)



<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> **Medium Risk**
> Adds new admin-only endpoints that can stop, requeue, and bulk-mark
executions as `FAILED`, plus schedule deletion, which can directly
impact production workload and data integrity if misused or buggy.
> 
> **Overview**
> Introduces a **System Diagnostics** admin feature spanning backend +
frontend to monitor execution/schedule health and perform remediation
actions.
> 
> On the backend, adds a new `backend/data/diagnostics.py` data layer
and `diagnostics_admin_routes.py` with admin-secured endpoints to fetch
execution/agent/schedule metrics (including RabbitMQ queue depths and
invalid-state detection), list problem executions/schedules, and perform
bulk operations like `stop`, `requeue`, and `cleanup` (marking
orphaned/stuck items as `FAILED` or deleting orphaned schedules). It
also extends `get_graph_executions`/`get_graph_executions_count` with
`execution_ids` filtering, pagination, started/updated time filters, and
configurable ordering to support efficient bulk/admin queries.
> 
> On the frontend, adds an admin diagnostics page with summary cards and
tables for executions and schedules (tabs for
orphaned/failed/long-running/stuck-queued/invalid, plus confirmation
dialogs for destructive actions), wires it into admin navigation, and
adds comprehensive unit tests for both the new API routes and UI
behavior.
> 
> <sup>Reviewed by [Cursor Bugbot](https://cursor.com/bugbot) for commit
15b9ed26f9. Bugbot is set up for automated
code reviews on this repo. Configure
[here](https://www.cursor.com/dashboard/bugbot).</sup>
<!-- /CURSOR_SUMMARY -->

---------

Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Nicholas Tindle <ntindle@users.noreply.github.com>
Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
2026-04-21 15:28:44 +00:00
Zamil Majdy
24850e2a3e feat(backend/autopilot): stream extended_thinking on baseline via OpenRouter (#12870)
### Why / What / How

**Why:** Fast-mode autopilot never renders a Reasoning block. The
frontend already has `ReasoningCollapse` wired up and the wire protocol
already carries `StreamReasoning*` events (landed for SDK mode in
#12853), but the baseline (OpenRouter OpenAI-compat) path never asks
Anthropic for extended thinking and never parses reasoning deltas off
the stream. Result: users on fast/standard get a good answer with no
visible chain-of-thought, while SDK users see the full Reasoning
collapse.

**What:** Plumb reasoning end-to-end through the baseline path by opting
into OpenRouter's non-OpenAI `reasoning` extension, parsing the
reasoning delta fields off each chunk, and emitting the same
`StreamReasoningStart/Delta/End` events the SDK adapter already uses.

**How:**
- **New config:** `baseline_reasoning_max_tokens` (default 8192; 0
disables). Sent as `extra_body={"reasoning": {"max_tokens": N}}` only on
Anthropic routes — other providers drop the field, and
`is_anthropic_model()` already gates this.
- **Delta extraction:** `_extract_reasoning_delta()` handles all three
OpenRouter/provider variants in priority order — legacy
`delta.reasoning` (string), DeepSeek-style `delta.reasoning_content`,
and the structured `delta.reasoning_details` list (text/summary entries;
encrypted or unknown entries are skipped).
- **Event emission:** Reasoning uses the same state-machine rules the
SDK adapter uses — a text delta or tool_use delta arriving mid-stream
closes the open reasoning block first, so the AI SDK v5 transport keeps
reasoning / text / tool-use as distinct UI parts. On stream end, any
still-open reasoning block gets a matching `reasoning-end` so a
reasoning-only turn still finalises the frontend collapse.
- **Scope:** Live streaming only. Reasoning is not persisted to
`ChatMessage` rows or the transcript builder in this PR (SDK path does
so via `content_blocks=[{type: 'thinking', ...}]`, but that round-trip
requires Anthropic signature plumbing baseline doesn't have today).
Reload will still not show reasoning on baseline sessions — can follow
up if we decide it's worth the signature handling.

### Changes

- `backend/copilot/config.py` — new `baseline_reasoning_max_tokens`
field.
- `backend/copilot/baseline/service.py` — new
`_extract_reasoning_delta()` helper; reasoning block state on
`_BaselineStreamState`; `reasoning` gated into `extra_body`; chunk loop
emits `StreamReasoning*` events with text/tool_use transition rules;
stream-end closes any open reasoning block.
- `backend/copilot/baseline/service_unit_test.py` — 11 new tests
covering extractor variants (legacy string, deepseek alias, structured
list with text/summary aliases, encrypted-skip, empty), paired event
ordering (reasoning-end before text-start), reasoning-only streams, and
that the `reasoning` request param is correctly gated by model route
(Anthropic vs non-Anthropic) and by the config flag.

### Checklist

For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [ ] I have tested my changes according to the test plan:
- [x] `poetry run pytest backend/copilot/baseline/service_unit_test.py
backend/copilot/baseline/transcript_integration_test.py` — 103 passed
- [ ] Manual: with `CHAT_USE_CLAUDE_AGENT_SDK=false` and
`CHAT_MODEL=anthropic/claude-sonnet-4-6`, send a multi-step prompt on
fast mode and confirm a Reasoning collapse appears alongside the final
text
- [ ] Manual: flip `CHAT_BASELINE_REASONING_MAX_TOKENS=0` and confirm
baseline responses revert to text-only (no reasoning param, no reasoning
UI)
- [ ] Manual: with a non-Anthropic baseline model (`openai/gpt-4o`),
confirm the request does NOT include `reasoning` and nothing regresses

For configuration changes:
- [x] `.env.default` is compatible — new setting falls back to the
pydantic default
2026-04-21 21:05:00 +07:00
Zamil Majdy
e17e9f13c4 fix(backend/copilot): reduce SDK + baseline prompt cache waste (#12866)
## Summary

Four cost-reduction changes for the copilot feature. Consolidated into
one PR at user request; each commit is self-contained and bisectable.

### 1. SDK: full cross-user cache on every turn (CLI 2.1.116 bump)
Previous behavior: CLI 2.1.97 crashed when `excludeDynamicSections=True`
was combined with `--resume`, so the code fell back to a raw
`system_prompt` string on resume, losing Claude Code's default prompt
and all cache markers. Every Turn 2+ of an SDK session wrote ~33K tokens
to cache instead of reading.

Fix: install `@anthropic-ai/claude-code@2.1.116` in the backend Docker
image and point the SDK at it via
`CHAT_CLAUDE_AGENT_CLI_PATH=/usr/bin/claude`. CLI 2.1.98+ fixes the
crash, so we can use the preset with `exclude_dynamic_sections=True` on
every turn — Turn 1, 2, 3+ all share the same static prefix and hit the
**cross-user** prompt cache.

**Local dev requirement:** if `CHAT_CLAUDE_AGENT_CLI_PATH` is unset, the
bundled 2.1.97 fallback will crash on `--resume`. Install the CLI
globally (`npm install -g @anthropic-ai/claude-code@2.1.116`) or set the
env var.

### 2. Baseline: add `cache_control` markers (commit `756b3ecd9` +
follow-ups)
Baseline path had zero `cache_control` across `backend/copilot/**`.
Every turn was full uncached input (~18.6K tokens, ~$0.058). Two
ephemeral markers — on the system message (content-blocks form) and the
last tool schema — plus `anthropic-beta: prompt-caching-2024-07-31` via
`extra_headers` as defense-in-depth. Helpers split into `_mark_tools_*`
(precomputed once per session) and `_mark_system_*` (per-round, O(1)).
Repeat hellos: ~$0.058 → ~$0.006.

### 3. Drop `get_baseline_supplement()` (commit `6e6c4d791`)
`_generate_tool_documentation()` emitted ~4.3K tokens of `(tool_name,
description)` pairs that exactly duplicated the tools array already in
the same request. Deleted. `SHARED_TOOL_NOTES` (cross-tool workflow
rules) is preserved. Baseline "hello" input: ~18.7K → ~14.4K tokens.

### 4. Langfuse "CoPilot Prompt" v26 (published under `review` label)
Separate, out-of-repo change. v25 had three duplicate "Example Response"
blocks + a 10-step "Internal Reasoning Process" section. v26 collapses
to one example + bullet-form reasoning. Char count 20,481 → 7,075 (rough
4 chars/token → ~5,100 → ~1,770 tokens).

- v26 is published with label `review` (NOT `production`); v25 remains
active.
- Promote via `mcp__langfuse__updatePromptLabels(name="CoPilot Prompt",
version=26, newLabels=["production"])` after smoke-test.
- Rollback: relabel v25 `production`.

## Test plan
- [x] Unit tests for `_build_system_prompt_value` (fresh vs resumed
turns emit identical preset dict)
- [x] SDK compat tests pass including
`test_bundled_cli_version_is_known_good_against_openrouter`
- [x] `cli_openrouter_compat_test.py` passes against CLI 2.1.116
(locally verified with
`CHAT_CLAUDE_AGENT_CLI_PATH=/opt/homebrew/bin/claude`)
- [x] 8 new `_mark_*` unit tests + identity regression test for
`_fresh_*` helpers
- [x] `SHARED_TOOL_NOTES` public-constant test passes; 5 old tool-docs
tests removed
- [ ] **Manual cost verification (commit 1):** send two consecutive SDK
turns; Turn 2 and Turn 3 should both show `cacheReadTokens` ≈ 33K (full
cross-user cache hits).
- [ ] **Manual cost verification (commit 2):** send two "hello" turns on
baseline <5 min apart; Turn 2 reports `cacheReadTokens` ≈ 18K and cost ≈
$0.006.
- [ ] **Regression sweep for commit 3:** one turn per tool family —
`search_agents`, `run_agent`,
`add_memory`/`forget_memory`/`search_memory`, `search_docs`,
`read_workspace_file` — to verify no tool-selection regression from
dropping the prose tool docs.
- [ ] **Langfuse v26 smoke test:** 5-10 varied turns after relabelling
to `production`; compare responses vs v25 for regression on persona,
concision, capability-gap handling, credential security flows.

## Deployment notes
- Production Docker image now installs CLI 2.1.116 (~20 MB added).
- `CHAT_CLAUDE_AGENT_CLI_PATH=/usr/bin/claude` set in the Dockerfile;
runtime can override via env.
- First deploy after this merge needs a fresh image rebuild to pick up
the new CLI.
2026-04-21 16:34:10 +07:00
Zamil Majdy
f238c153a5 fix(backend/copilot): release session cluster lock on completion (#12867)
## Summary

Fixes a bug where a chat session gets silently stuck after the user
presses Stop mid-turn.

**Root cause:** the cancel endpoint marks the session `failed` after
polling 5s, but the cluster lock held by the still-running task is only
released by `on_run_done` when the task actually finishes. If the task
hangs past the 5s poll (slow LLM call, agent-browser step, etc.), the
lock lingers for up to 5 min — `stream_chat_post`'s `is_turn_in_flight`
check sees the flipped meta (`failed`) and enqueues a new turn, but the
run handler sees the stale lock and drops the user's message at
`manager.py:379` (`reject+requeue=False`). The new SSE stream hangs
until its 60s idle timeout.

### Fix

Two cooperating changes:

1. **`mark_session_completed` force-releases the cluster lock** in the
same transaction that flips status to `completed`/`failed`.
Unconditional delete — by the time we're declaring the session dead, we
don't care who the current lock holder is; the lock has to go so the
next enqueued turn can acquire. This is what closes the stuck-session
window.
2. **`ClusterLock.release()` is now owner-checked** (Lua CAS — `GET ==
token ? DEL : noop` atomically). Force-release means another pod may
legitimately own the key by the time the original task's `on_run_done`
eventually fires. Without the CAS, that late `release()` would wipe the
successor's lock. With it, the late `release()` is a safe no-op when the
owner has changed.

Together: prompt release on completion (via force-delete) + safe cleanup
when on_run_done catches up (via CAS). That re-syncs the API-level
`is_turn_in_flight` check with the actual lock state, so the contention
window disappears.

No changes to the worker-level contention handler: `stream_chat_post`
already queues incoming messages into the pending buffer when a turn is
in flight (via `queue_pending_for_http`). With these fixes, the worker
never sees contention in the common case; if it does (true multi-pod
race), the pre-existing `reject+requeue=False` behaviour still applies —
we'll revisit that path with its own PR if it becomes a production
symptom.

### Verification

- Reproduced the original stuck-session symptom locally (Stop mid-turn →
send new message → backend logs `Session … already running on pod …`,
user message silently lost, SSE stream idle 60s then closes).
- After the fix: cancel → new message → turn starts normally (lock
released by `mark_session_completed`).
- `poetry run pyright` — 0 errors on edited files.
- `pytest backend/copilot/stream_registry_test.py
backend/executor/cluster_lock_test.py` — 33 passed (includes the
successor-not-wiped test).

## Changes

- `autogpt_platform/backend/backend/copilot/executor/utils.py` — extract
`get_session_lock_key(session_id)` helper so the lock-key format has a
single source of truth.
- `autogpt_platform/backend/backend/copilot/executor/manager.py` — use
the helper where the cluster lock is created.
- `autogpt_platform/backend/backend/copilot/stream_registry.py` —
`mark_session_completed` deletes the lock key after the atomic status
swap (force-release).
- `autogpt_platform/backend/backend/executor/cluster_lock.py` —
`ClusterLock.release()` (sync + async) uses a Lua CAS to only delete
when `GET == token`, protecting against wiping a successor after a
force-release.

## Test plan

- [ ] Send a message in /copilot that triggers a long turn (e.g.
`run_agent`), press Stop before it finishes, then send another message.
Expect: new turn starts promptly (no 5-min wait for lock TTL).
- [ ] Happy path regression — send a normal message, verify turn
completes and the session lock key is deleted after completion.
- [ ] Successor protection — unit test
`test_release_does_not_wipe_successor_lock` covers: A acquires, external
DEL, B acquires, A.release() is a no-op, B's lock intact.
2026-04-21 16:27:01 +07:00
Zamil Majdy
01f1289aac feat(copilot): real OpenRouter cost + cost-based rate limits (percent-only public API) (#12864)
## Why

After d7653acd0 removed cost estimation, most baseline turns log with
`tracking_type="tokens"` and no authoritative USD figure (see: dashboard
flipped from `cost_usd` to `tokens` after 4/14/2026). Rate-limit
counters were also token-weighted with hand-rolled cache discounts
(cache_read @ 10%, cache_create @ 25%) and a 5× Opus multiplier — a
proxy for cost that drifts from real OpenRouter billing.

This PR wires real generation cost from OpenRouter into both the
cost-tracking log and the rate limiter, and hides raw spend figures from
the user-facing API so clients can't reverse-engineer per-turn cost or
platform margins.

## What

1. **Real cost from OpenRouter** — baseline passes `extra_body={"usage":
{"include": True}}` and reads `chunk.usage.cost` from the final
streaming chunk. `x-total-cost` header path removed. Missing cost logs
an error and skips the counter update (vs the old estimator that
silently under-counted).
2. **Cost-based rate limiting** — `record_token_usage(...)` →
`record_cost_usage(cost_microdollars)`. The weighted-token math, cache
discount factors, and `_OPUS_COST_MULTIPLIER` are gone; real USD already
reflects model + cache pricing.
3. **Redis key migration** — `copilot:usage:*` → `copilot:cost:*` so
stale token counters can't be misinterpreted as microdollars.
4. **LD flags + config** — renamed to
`copilot-daily-cost-limit-microdollars` /
`copilot-weekly-cost-limit-microdollars` (unit in the LD key so values
can't accidentally be set in dollars or cents).
5. **Public `/usage` hides raw $$** — new `CoPilotUsagePublic` /
`UsageWindowPublic` schemas expose only `percent_used` (0-100) +
`resets_at` + `tier` + `reset_cost`. Admin endpoint keeps raw
microdollars for debugging.
6. **Admin API contract** — `UserRateLimitResponse` fields renamed
`daily/weekly_token_limit` → `daily/weekly_cost_limit_microdollars`,
`daily/weekly_tokens_used` → `daily/weekly_cost_used_microdollars`.
Admin UI displays `$X.XX`.

## How

- `baseline/service.py` — pass `extra_body`, extract cost from
`chunk.usage.cost`, drop the `x-total-cost` header fallback entirely.
- `rate_limit.py` — rewritten around `record_cost_usage`,
`check_rate_limit(daily_cost_limit, weekly_cost_limit)`, new Redis key
prefix. Adds `CoPilotUsagePublic.from_status()` projector for the public
API.
- `token_tracking.py` — converts `cost_usd` → microdollars via
`usd_to_microdollars` and calls `record_cost_usage` only when cost is
present.
- `sdk/service.py` — deletes `_OPUS_COST_MULTIPLIER` and simplifies
`_resolve_model_and_multiplier` to `_resolve_sdk_model_for_request`.
- Chat routes: `/usage` and `/usage/reset` return `CoPilotUsagePublic`.
Internal server-side limit checks still use the raw microdollar
`CoPilotUsageStatus`.
- Admin routes: unchanged response shape (renamed fields only).
- Frontend: `UsagePanelContent`, `UsageLimits`, `CopilotPage`,
`BriefingTabContent`, `credits/page.tsx` consume the new public schema
and render "N% used" + progress bar. Admin `RateLimitDisplay` /
`UsageBar` keep `$X.XX`. Helper `formatMicrodollarsAsUsd` retained for
admin use.
- Tests + snapshots rewritten; new assertions explicitly check that raw
`used`/`limit` keys are absent from the public payload.

## Deploy notes

1. **Before rolling this out, create the new LD flags:**
`copilot-daily-cost-limit-microdollars` (default `500000`) and
`copilot-weekly-cost-limit-microdollars` (default `2500000`). Old
`copilot-*-token-limit` flags can stay in LD for rollback.
2. **One-time Redis cleanup (optional):** token-based counters under
`copilot:usage:*` are orphaned and will TTL out within 7 days. Safe to
ignore or delete manually.

## Test plan

- [x] `poetry run test` — all impacted backend tests pass (182/182 in
targeted scope)
- [x] `pnpm test:unit` — all 1628 integration tests pass
- [x] `poetry run format` / `pnpm format` / `pnpm types` clean
- [x] Manual sanity against dev env — Baseline turn logged $0.1221 for
40K/139 tokens on Sonnet 4 (matches expected pricing)
- [ ] `/pr-test --fix` end-to-end against local native stack
2026-04-21 14:34:43 +07:00
Zamil Majdy
343222ace1 feat(platform): defer paid-to-paid subscription downgrades + cancel-pending flow (#12865)
### Why / What / How

**Why:** Only downgrades to FREE were scheduled at period end; paid→paid
downgrades (e.g. BUSINESS→PRO) applied immediately via Stripe proration.
The asymmetry meant users lost their higher tier mid-cycle in exchange
for a Stripe credit voucher only redeemable on a future subscription — a
confusing pattern that produces negative-value paths for users actually
cancelling. There was also no way to cancel a pending downgrade or
paid→FREE cancellation once scheduled.

**What:** Standardize on "upgrade = immediate, downgrade = next cycle"
and let users cancel a pending change by clicking their current tier.
Harden the new code against conflicting subscription state, concurrent
tab races, flaky Stripe calls, and hot-path latency regressions.

**How:**

Subscription state machine:
- **Upgrade** (PRO→BUSINESS) — `stripe.Subscription.modify` with
immediate proration (unchanged). If a downgrade schedule is already
attached, release it first so the upgrade wins.
- **Paid→paid downgrade** (BUSINESS→PRO) — creates a
`stripe.SubscriptionSchedule` with two phases (current tier until
`current_period_end`, target tier after). No mid-cycle tier demotion.
Defensive pre-clear: existing schedule → release;
`cancel_at_period_end=True` → set to False.
- **Paid→FREE** — unchanged: `cancel_at_period_end=True`.
- **Same-tier update** — reuses the existing `POST
/credits/subscription` route. When `target_tier == current_tier`,
backend calls `release_pending_subscription_schedule` (idempotent) and
returns status. No dedicated cancel-pending endpoint — "Keep my current
tier" IS the cancel operation.
- `release_pending_subscription_schedule` is idempotent on
terminal-state schedules and clears both `schedule` and
`cancel_at_period_end` atomically per call.

API surface:
- New fields on `SubscriptionStatusResponse`: `pending_tier` +
`pending_tier_effective_at` (pulled from the schedule's next-phase
`start_date` so dashboard-authored schedules report the correct
timestamp).
- `POST /credits/subscription` now returns `SubscriptionStatusResponse`
(previously `SubscriptionCheckoutResponse`); the response still carries
`url` for checkout flows and adds the status fields inline.
- `get_pending_subscription_change` is cached with a 30s TTL — avoids
hammering Stripe on every home-page load.
- Webhook dispatches
`subscription_schedule.{released,completed,updated}` through the main
`sync_subscription_from_stripe` flow so both event sources converge to
the same DB state.

Implementation notes:
- New Stripe calls use native async (`stripe.Subscription.list_async`
etc.) and typed attribute access — no `run_in_threadpool` wrapping in
the new helpers.
- Shared `_get_active_subscription` helper collapses the "list
active/trialing subs, take first" pattern used by 4 callers.

Frontend:
- `PendingChangeBanner` sub-component above the tier grid with formatted
effective date + "Keep [CurrentTier]" button. `aria-live="polite"` for
screen readers; locale pinned to `en-US` to avoid SSR/CSR hydration
mismatch.
- "Keep [CurrentTier]" also available as a button on the current tier
card.
- Other tier buttons disabled while a change is pending — user must
resolve pending first to prevent stacked schedules.
- `cancelPendingChange` reuses `useUpdateSubscriptionTier` with `tier:
current_tier`; awaits `refetch()` on both success and error paths so the
UI reconciles even if the server succeeded but the client didn't receive
the response.

### Changes

**Backend (`credit.py`, `v1.py`)**
- Tier-ordering helpers (`is_tier_upgrade`/`is_tier_downgrade`).
- `modify_stripe_subscription_for_tier` routes downgrades through
`_schedule_downgrade_at_period_end`; upgrade path releases any pending
schedule first.
- `_schedule_downgrade_at_period_end` defensively releases pre-existing
schedules and clears `cancel_at_period_end` before creating the new
schedule.
- `release_pending_subscription_schedule` idempotent on terminal-state
schedules; logs partial-failure outcomes.
- `_next_phase_tier_and_start` returns both tier and phase-start
timestamp; warns on unknown prices.
- `get_pending_subscription_change` cached (30s TTL), narrow exception
handling.
- `sync_subscription_schedule_from_stripe` delegates to
`sync_subscription_from_stripe` for convergence with the main webhook
path.
- Shared `_get_active_subscription` +
`_release_schedule_ignoring_terminal` helpers.
- `POST /credits/subscription` absorbs the same-tier "cancel pending
change" branch.

**Frontend (`SubscriptionTierSection/*`)**
- `PendingChangeBanner` new sub-component (a11y, locale-pinned date,
paid→FREE vs paid→paid copy split, non-null effective-date assertion, no
`dark:` utilities).
- "Keep [CurrentTier]" button on current tier card.
- `useSubscriptionTierSection` — `cancelPendingChange` reuses the
update-tier mutation.
- Copy: downgrade dialog + status hint updated.
- `helpers.ts` extracted from the main component.

**Tests**
- Backend: +24 tests (95/95 passing): upgrade-releases-pending-schedule,
schedule-releases-existing-schedule, cancel-at-period-end collision,
terminal-state release idempotency, unknown-price logging, status
response population, same-tier-POST-with-pending, webhook delegation.
- Frontend: +5 integration tests (21/21 passing): banner render/hide,
Keep-button click from banner + current card, paid→paid dialog copy.

### Checklist

- [x] Backend unit tests: 95 pass
- [x] Frontend integration tests: 21 pass
- [x] `poetry run format` / `poetry run lint` clean
- [x] `pnpm format` / `pnpm lint` / `pnpm types` clean
- [ ] Manual E2E on live Stripe (dev env) — pending deploy: BUSINESS→PRO
creates schedule, DB tier unchanged until period end
- [ ] Manual E2E: "Keep BUSINESS" in banner releases schedule
- [ ] Manual E2E: cancel pending paid→FREE flips `cancel_at_period_end`
back to false
- [ ] Manual E2E: BUSINESS→PRO (scheduled) then attempt BUSINESS→FREE
clears the PRO schedule, sets cancel_at_period_end
- [ ] Manual E2E: BUSINESS→PRO (scheduled) then upgrade back to BUSINESS
releases the schedule
2026-04-21 14:01:09 +07:00
Zamil Majdy
a8226af725 fix(copilot): dedupe tool row, lift bash_exec timeout, Stop+resend recovery (#12862)
Closes #12861 · [OPEN-3096](https://linear.app/autogpt/issue/OPEN-3096)

## Why

Four related copilot UX / stability issues surfaced on dev once action
tools started rendering inline in the chat (see #12813):

### 1. Duplicate bash_exec row

`GenericTool` rendered two rows saying the same thing for every
completed tool call — a muted subtitle line ("Command exited with code
1" / "Ran: sleep 20") **and** a `ToolAccordion` with the command echoed
in its description. Previously hidden inside the "Show reasoning" /
"Show steps" collapse, now visibly duplicated.

### 2. `bash_exec` capped at 120s via advisory text

The tool schema said `"Max seconds (default 30, max 120)"`; the model
obeyed, so long-running scripts got clipped at 120s with a vague `Timed
out after 120s` even though the E2B sandbox has no such limit. Confirmed
via Langfuse traces — the model picks `120` for long scripts because
that's what the schema told it the max was. E2B path never had a
server-side clamp.

Originally added in #12103 (default 30) and tightened to "max 120"
advisory in #12398 (token-reduction pass).

### 3. 30s default was too aggressive

`pip install`, small data-processing scripts, etc. routinely cross 30s
and got killed before the model thought to retry with a bigger timeout.

### 4. Stop + edit + resend → "The assistant encountered an error"
([OPEN-3096](https://linear.app/autogpt/issue/OPEN-3096))

Two independent bugs both land on the same banner — fixing only one
leaves the other visible on the next action.

**4a. Stream lock never released on Stop** *(the error in the ticket
screenshot)*. The executor's `async for chunk in
stream_and_publish(...)` broke out on `cancel.is_set()` without calling
`aclose()` on the wrapper. `async for` does NOT auto-close iterators on
`break`, so `stream_chat_completion_sdk` stayed suspended at its current
`await` — still holding the per-session Redis lock (TTL 120s) until GC
eventually closed it. The next `POST /stream` hit `lock.try_acquire()`
at
[sdk/service.py](autogpt_platform/backend/backend/copilot/sdk/service.py)
and yielded `StreamError("Another stream is already active for this
session. Please wait or stop it.")`. The `except GeneratorExit →
lock.release()` handler written exactly for this case never fired
because nothing sent GeneratorExit.

**4b. Orphan `tool_use` after stop-mid-tool.** Even with the lock
released, the stop path persists the session ending on an assistant row
whose `tool_calls` have no matching `role="tool"` row. On the next turn,
`_session_messages_to_transcript` hands Claude CLI `--resume` a JSONL
with a `tool_use` and no paired `tool_result`, and the SDK raises a
vague error — same banner. The ticket's "Open questions" explicitly
flags this.

## What

**Frontend — `GenericTool.tsx`** split responsibilities between the two
rows so they don't duplicate:
- **Subtitle row** (always visible, muted): *what ran* — `Ran: sleep
120`. Never the exit code.
- **Accordion description**: *how it ended* — `completed` / `status code
127 · bash: missing-bin: command not found` / `Timed out after 120s` /
(fallback to command preview for legacy rows missing `exit_code` /
`timed_out`). Pulled from the first non-empty line of `stdout` /
`stderr` when available.
- **Expanded accordion**: full command + stdout + stderr code blocks
(unchanged).

**Backend — `bash_exec.py`**:
- Drop the "max 120" advisory from the schema description.
- Bump default `timeout: 30 → 120`.
- Clean up the result message — `"Command executed with status code 0"`
(no "on E2B", no parens).

**Backend — `executor/processor.py` + `stream_registry.py` (OPEN-3096
#4a)**: wrap the consumer `async for` in `try/finally: await
stream.aclose()`. Close now propagates through `stream_and_publish` into
`stream_chat_completion_sdk`, whose existing `except GeneratorExit →
lock.release()` releases the Redis lock immediately on cancel. Stream
types tightened to `AsyncGenerator[StreamBaseResponse, None]` so the
defensive `getattr(stream, "aclose", None)` goes away.

**Backend — `session_cleanup.py` (OPEN-3096 #4b)**: new
`prune_orphan_tool_calls()` helper walks the trailing session tail and
drops any trailing assistant row whose `tool_calls` have unresolved ids
(plus everything after it) and any trailing `STOPPED_BY_USER_MARKER`
system-stop row. Single backward pass — tolerates the marker being
present or absent. Called from the existing turn-start cleanup in both
`sdk/service.py` and `baseline/service.py`; takes an optional
`log_prefix` so both paths emit the same INFO log when something was
popped. In-memory only — the DB save path is append-only via
`start_sequence`.

## Test plan

- [x] `pnpm exec vitest run src/app/(platform)/copilot/tools/GenericTool
src/app/(platform)/copilot/components/ChatMessagesContainer` — 105 pass
(6 new for GenericTool subtitle/description variants + legacy-fallback
case).
- [x] `pnpm format` / `pnpm lint` / `pnpm types` — clean.
- [x] `poetry run pytest
backend/copilot/sdk/session_persistence_test.py` — 17 pass (6 + 3 new
covering the orphan-tool-call prune and its optional-log-prefix branch).
- [x] `poetry run pytest backend/copilot/stream_registry_test.py
backend/copilot/executor/processor_test.py` — 19 pass (2 for aclose
propagation on the `stream_and_publish` wrapper, 2 for `_execute_async`
aclose propagation on both exit paths, 1 for publish_chunk RedisError
warning ladder).
- [x] `poetry run ruff check` / `poetry run pyright` on touched files —
clean.
- [x] Manual: fire a `bash_exec` — one labelled row, accordion
description reads sensibly (`completed` / `status code 1 · …` / `Timed
out after 120s`).
- [x] Manual: script that needs >120s — no longer clipped.
- [x] Manual: Stop mid-tool + edit + resend — Autopilot resumes without
"Another stream is already active" and without the vague SDK error.

## Scope note

Does not touch `splitReasoningAndResponse` — re-collapsing action tools
back into "Show steps" is #12813's responsibility.
2026-04-21 10:18:52 +07:00
Ubbe
f06b5293de fix(frontend/library): compute monthly spend for AgentBriefingPanel (#12854)
### Why / What / How

<img width="900" alt="Screenshot 2026-04-20 at 19 52 22"
src="https://github.com/user-attachments/assets/c30d5f18-2842-4a8a-ac3d-5bfee18fcd56"
/>

**Why:** The "Spent this month" tile in the Agent Briefing Panel on the
Library page always showed `$0`, even for users with real execution
usage. The tile is meant to give a quick sense of monthly spend across
all agents.

**What:** Compute `monthlySpend` from actual execution data and format
it as currency.

**How:**
- `useLibraryFleetSummary` now sums `stats.cost` (cents) across every
execution whose `started_at` falls within the current calendar month.
Previously `monthlySpend` was hardcoded to `0`.
- `FleetSummary.monthlySpend` is documented as being in cents
(consistent with backend + `formatCents`).
- `StatsGrid` now uses `formatCents` from the copilot usage helpers to
render the tile (e.g. `$12.34` instead of the broken `$0`).

### Changes 🏗️

-
`autogpt_platform/frontend/src/app/(platform)/library/hooks/useLibraryFleetSummary.ts`:
aggregate `stats.cost` across executions started in the current calendar
month; add `toTimestamp` and `startOfCurrentMonth` helpers.
-
`autogpt_platform/frontend/src/app/(platform)/library/components/AgentBriefingPanel/StatsGrid.tsx`:
format the "Spent this month" tile via shared `formatCents` helper.
- `autogpt_platform/frontend/src/app/(platform)/library/types.ts`:
document that `FleetSummary.monthlySpend` is in cents.

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [ ] I have tested my changes according to the test plan:
- [ ] Load `/library` with the `AGENT_BRIEFING` flag enabled and at
least one completed execution in the current month — the "Spent this
month" tile shows the correct cumulative cost.
  - [ ] With no executions this month, the tile shows `$0.00`.
- [ ] Type-check (`pnpm types`), lint (`pnpm lint`), and integration
tests (`pnpm test:unit`) pass locally.

---------

Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-20 20:28:47 +07:00
Zamil Majdy
70b591d74f fix(copilot): persist reasoning, split steps/reasoning UX, fix mid-turn promote stream stall (#12853)
## Why

Four related issues that surfaced when queued follow-ups hit an
extended_thinking turn:

1. **Mid-turn promote stalled the SSE stream.** `pollBackendAndPromote`
used `setMessages((prev) => [...prev, bubble])` — Vercel AI SDK's
`useChat` streams SSE deltas into `messages[-1]`, so once a user bubble
ended up there, every subsequent chunk silently landed on the wrong
message. Chat sat frozen until a page refresh, even though the backend's
stream completed cleanly.
2. **Thinking-only final turn looked identical to a frozen UI.** When
Claude's last LLM call after a tool_result produced only a
`ThinkingBlock` (no `TextBlock`, no `ToolUseBlock`), the response
adapter silently dropped it and the UI hung on "Thought for Xs" with no
response text.
3. **Reasoning was invisible.** `ThinkingBlock` was dropped live and
never persisted in a way the frontend could render — sessions on reload
/ shared links showed no thinking, a confusing UX gap ("display for
nothing").
4. **Cross-pod Redis replay dropped reasoning events.** The
`stream_registry._reconstruct_chunk` type map had no entries for
`reasoning-*` types, so any client that subscribed mid-stream (share,
reload, cross-pod) silently dropped them with `Unknown chunk type:
reasoning-delta`.

## What

### Mid-turn promote — splice before the trailing assistant

In `useCopilotPendingChips.ts::pollBackendAndPromote`:

```ts
setMessages((prev) => {
  const bubble = makePromotedUserBubble(drained, "midturn", crypto.randomUUID());
  const lastIdx = prev.length - 1;
  if (lastIdx >= 0 && prev[lastIdx].role === "assistant") {
    return [...prev.slice(0, lastIdx), bubble, prev[lastIdx]];
  }
  return [...prev, bubble];
});
```

Streaming assistant stays at `messages[-1]`, AI SDK deltas keep routing
correctly. `useHydrateOnStreamEnd` snaps the bubble to the DB-canonical
position when the stream ends.

### Reasoning — end-to-end visibility (live + persisted)

- **Wire protocol**: new `StreamReasoningStart` / `StreamReasoningDelta`
/ `StreamReasoningEnd` events matching AI SDK v5's `reasoning-*` wire
names, so `useChat` accumulates them into a `type: 'reasoning'`
UIMessage part natively.
- **Response adapter**: every `ThinkingBlock` now emits reasoning
events; text/tool_use transitions close the open reasoning block so AI
SDK doesn't merge distinct parts.
- **Stream registry**: added `reasoning-*` types to
`_reconstruct_chunk`'s type_to_class map so Redis replay no longer drops
them on cross-pod / reload / share.
- **Persistence** (new): each `StreamReasoningStart` opens a
`ChatMessage(role="reasoning")` row in `session.messages`; deltas
accumulate into its content; `StreamReasoningEnd` closes it. No schema
migration — `ChatMessage.role` is already `String`.
`extract_context_messages` filters `role="reasoning"` out of LLM context
(the `--resume` CLI session already carries thinking separately) so the
model never re-ingests prior reasoning.
- **Frontend conversion**: `convertChatSessionMessagesToUiMessages` maps
`role="reasoning"` DB rows into `{type: "reasoning", text}` parts on the
surrounding assistant bubble, so reload / shared-link sessions render
reasoning identically to live stream.

### Steps / Reasoning UX — modal + accordion split

- **`StepsCollapse`** (new): a Dialog-backed "Show steps" modal wraps
the pre-final-answer group (tool timeline + per-block reasoning). Modal
keeps the steps visually grouped and out of the reading flow.
- **`ReasoningCollapse`** (rewritten): inline accordion with "Show
reasoning" / "Hide reasoning" toggle — no longer a modal, so it expands
*inside* the Steps modal without stacking two dialogs. Reasoning text
appears indented with a left border.
- **`splitReasoningAndResponse`**: reasoning parts now stay in the
reasoning group (instead of being pinned out), so they show up inside
the Steps modal alongside the tool-use timeline.

### Thinking-only final turn — synthesize a closing line
(belt-and-suspenders)

- **Prompt rule** (`_USER_FOLLOW_UP_NOTE`): "Every turn MUST end with at
least one short user-facing text sentence."
- **Adapter fallback**: tracks `_text_since_last_tool_result`; at
`ResultMessage success` with tools run + zero text since, opens a fresh
step (`UserMessage` already closed the previous one) and injects `"(Done
— no further commentary.)"` before `StreamFinish`. Only fires for the
pathological case — pure-text turns untouched.

## Test plan

- [x] `pnpm vitest run` on copilot files — all 638 prior tests pass;
**17 new tests** added covering:
- `convertChatSessionToUiMessages`: reasoning row alone / merged with
assistant text / multi-row / empty skip / duration capture
- `ReasoningCollapse`: initial collapsed, toggle, `rotate-90`,
`aria-expanded`
  - `StepsCollapse`: trigger + dialog open renders children
- `MessagePartRenderer`: reasoning → `<pre>` inside collapse,
whitespace/missing text → null
  - `splitReasoningAndResponse`: reasoning-stays-in-reasoning regression
- [x] `poetry run pytest backend/copilot/sdk/response_adapter_test.py` —
36 pass (7 new: 4 reasoning streaming, 3 thinking-only fallback)
- [x] Manual: reasoning streams live and persists across reload on a
fresh session
- [x] Manual: previously-created sessions (pre-persistence) don't have
`role="reasoning"` rows — behaves as a clean no-op (no reasoning shown,
no error), new sessions render reasoning inside Steps modal

## Notes

- No DB migration — `ChatMessage.role` is already an open `String`;
`role="reasoning"` is simply filtered out of LLM context builds but
rendered by the frontend.
- Addresses /pr-review blockers: (a) stream_registry missing reasoning
types in Redis round-trip, (b) fallback text emitted outside a step, (c)
dead `case "thinking"` in renderer (now uses the live `reasoning` type
uniformly).
2026-04-19 10:37:04 +07:00
Zamil Majdy
b1c043c2d8 feat(copilot): queue follow-up messages on busy sessions (UI + run_sub_session + AutoPilot block) (#12737)
## Why

Users and tools can target a copilot session that already has a turn
running. Before this PR there was no uniform behaviour for that case —
the UI manually routed to a separate queue endpoint, `run_sub_session`
and the AutoPilot block raced the cluster lock, and in-turn follow-ups
only reached the model at turn-end via auto-continue. Outcome: dropped
messages, duplicate tool rows, missed mid-turn intent, latent
correctness bugs in block execution.

## What

A single "message arrived → turn already running?" primitive, shared by
every caller:

1. **POST `/stream`** (UI chat): self-defensive. Session idle → SSE as
today; session busy → `202 application/json` with `{buffer_length,
max_buffer_length, turn_in_flight}`. The deprecated `POST
/messages/pending` endpoint is removed (`GET /messages/pending` peek
stays).
2. **`run_copilot_turn_via_queue`** (shared primitive from #12841, used
by `run_sub_session` + `AutoPilotBlock`): gains the same busy-check.
Busy session → push to pending buffer, return `("queued",
SessionResult(queued=True, pending_buffer_length=N))` without creating a
stream registry session or enqueueing a RabbitMQ job. All callers
inherit queueing.
3. **Mid-turn delivery**: drained follow-ups are attached to every
tool_result's `additionalContext` via the SDK's `PostToolUse` hook —
covers both MCP and built-in tools (WebSearch/Read/Agent/etc.), not just
`run_block`. Claude reads the queued text on the next LLM round of the
same turn.
4. **UI observability**: chips promote to a proper user bubble at the
correct chronological position (after the tool_result row that consumed
them). Auto-continue handles end-of-turn drainage; mid-turn backend poll
handles the tool-boundary drainage path.

## How

**Data plane**
- `backend/copilot/pending_messages.py` — Redis list per session
(LPOP-count for atomic drain), TTL, fire-and-forget pub/sub notify. MAX
10 per session.
- `backend/copilot/pending_message_helpers.py` — `is_turn_in_flight`,
`queue_user_message`, `drain_and_format_for_injection`,
`persist_pending_as_user_rows` (shared persist+rollback used by both
baseline and SDK paths).
- `backend/data/redis_helpers.py` — centralised `incr_with_ttl`,
`capped_rpush`, `hash_compare_and_set`; every Lua script and pipeline
atomicity lives in one place.

**Injection sites**
- `backend/copilot/sdk/security_hooks.py::post_tool_use_hook` — drains +
returns `additionalContext`. Single hook covers built-in + MCP tools.
- `backend/copilot/sdk/service.py` — `StreamToolOutputAvailable`
dispatch persists the drained follow-up as a real user row right after
the tool_result (UI bubble at the right index).
`state.midturn_user_rows` keeps the CLI upload watermark honest.
- `backend/copilot/baseline/service.py` — same drain at round
boundaries, uses the shared `persist_pending_as_user_rows` helper so
baseline + SDK code paths don't diverge.

**Dispatch**
- `backend/copilot/sdk/session_waiter.py::run_copilot_turn_via_queue` —
`is_turn_in_flight` short-circuit; `SessionResult` gains `queued` +
`pending_buffer_length`; `SessionOutcome` gains `"queued"`.
- `backend/api/features/chat/routes.py::stream_chat_post` — busy-check
returns 202 with `QueuePendingMessageResponse`; `POST /messages/pending`
deleted.
- `backend/copilot/tools/run_sub_session.py` / `models.py` —
`SubSessionStatusResponse.status` gains `"queued"`;
`response_from_outcome` renders a clear queued-state message with the
pending-buffer depth and a link to watch live.
- `backend/blocks/autopilot.py::execute_copilot` — surfaces queued state
as descriptive response text + empty `tool_calls`/history when
`result.queued`.

**Frontend**
- `src/app/(platform)/copilot/useCopilotPendingChips.ts` — hook owning
the chip lifecycle: backend peek on session load, auto-continue
promotion when a second assistant id appears, mid-turn poll that
promotes when the backend count drops.
- `src/app/(platform)/copilot/useHydrateOnStreamEnd.ts` —
force-hydrate-waits-for-fresh-reference dance extracted.
- `src/app/(platform)/copilot/helpers/stripReplayPrefix.ts` — pure
function with drop / strip / streaming-catch-up cases + helper
decomposition.
- `src/app/(platform)/copilot/helpers/makePromotedBubble.ts` — one-line
helper for the promoted bubble shape.
- `src/app/(platform)/copilot/helpers/queueFollowUpMessage.ts` — thin
`fetch` wrapper for the 202 path (AI SDK's `useChat` fetcher only
handles SSE, so we can't reuse `sendMessage` for the queued response).

## Test plan

Backend unit + integration (`poetry run pytest backend/copilot
backend/api/features/chat`):
- [x] 107 tests pass — pending buffer, drain helpers, routes,
session_waiter queue branch, run_sub_session outcome rendering,
autopilot block
- [x] New `session_waiter_test.py` proves the queue branch
short-circuits `stream_registry.create_session` + `enqueue_copilot_turn`
- [x] Mid-turn persist has a rollback-and-re-queue path tested for when
`session.messages` persist silently fails to back-fill sequences

Frontend unit (`pnpm vitest run`):
- [x] 630 tests pass incl. 22 new for extracted helpers + hooks
- [x] Frontend coverage on touched copilot files: 91%+ (patch 87.37%)

Manual (once merged):
- [ ] Queue two chips while a tool is running; Claude acknowledges both
on the next round, UI shows bubbles in typing order after the tool
output
- [ ] Hand AutoPilot block an existing session_id that has a live turn;
block returns queued status, in-flight turn drains the message on its
next round
- [ ] `run_sub_session` against a busy sub — status=`queued`,
`sub_autopilot_session_link` lets user watch live

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-19 00:48:59 +07:00
Zamil Majdy
fcaebd1bb7 refactor(backend/copilot): unified queue-backed copilot turns + async sub-AutoPilot + guide-read gate (#12841)
### Why / What / How

**Why:** the 10-min stream-level idle timeout was killing legitimate
long-running tool calls — notably sub-AutoPilot runs via
`run_block(AutoPilotBlock)`, which routinely take 15–45 min. The symptom
users saw was `"A tool call appears to be stuck"` even though AutoPilot
was actively working. A second long-standing rough edge was shipped
alongside: agents often skipped `get_agent_building_guide` when
generating agent JSON, producing schemas that failed validation and
burned turns on auto-fix loops.

**What:** three threaded pieces.

1. **Async sub-AutoPilot via `run_sub_session`.** New copilot tool that
delegates a task to a fresh (or resumed) sub-AutoPilot, and its
companion `get_sub_session_result` for polling/cancelling. The agent
starts with `run_sub_session(prompt, wait_for_result≤300s)` and, if the
sub isn't done inside the cap, receives a handle + polls via
`get_sub_session_result(wait_if_running≤300s)`. No single MCP call ever
blocks the stream for more than 5 min, so the 10-min stream-idle timer
stays simple and effective (derived as `MAX_TOOL_WAIT_SECONDS * 2`).

2. **Queue-backed copilot turn dispatch** — one code path for all three
callers.
- `run_sub_session` enqueues a `CoPilotExecutionEntry` on the existing
`copilot_execution` exchange instead of spawning an in-process
`asyncio.Task`.
- `AutoPilotBlock.execute_copilot` (graph block) now uses the **same
queue** instead of `collect_copilot_response` inline.
   - The HTTP SSE endpoint was already queue-backed.
- All three share a single primitive: `run_copilot_turn_via_queue` →
`create_session` → `enqueue_copilot_turn` → `wait_for_session_result`.
The event-aggregation logic (`EventAccumulator`/`process_event`) is a
shared module used by both the direct-stream path and the cross-process
waiter.
- Benefits: **deploy/crash resilience** (RabbitMQ redelivery survives
worker restarts), **natural load balancing** across copilot_executor
workers, **sessions as first-class resources** (UI users can
`/copilot?sessionId=<inner>` into any sub or AutoPilot block's session),
and every future stream-level feature (pending-messages drain #12737,
compaction policies, etc.) applies uniformly instead of bypassing
graph-block sessions.

3. **Guide-read gate on agent-generation tools.** `create_agent` /
`edit_agent` / `validate_agent_graph` / `fix_agent_graph` refuse until
the session has called `get_agent_building_guide`. The pre-existing soft
hint was routinely ignored; the gate makes the dependency enforceable.
All four tool descriptions advertise the requirement in one tightened
sentence ("Requires get_agent_building_guide first (refuses
otherwise).") that stays under the 32000-char schema budget.

**How:**

#### Queue-backed sub-AutoPilot + AutoPilotBlock

- `sdk/session_waiter.py` — new module. `SessionResult` dataclass
mirrors `CopilotResult`. `wait_for_session_result` subscribes to
`stream_registry`, drains events via shared `process_event`, returns
`(outcome, result)`. `wait_for_session_completion` is the cheaper
outcome-only variant. `run_copilot_turn_via_queue` is the canonical
three-step dispatch. Every exit path unsubscribes the listener.
- `sdk/stream_accumulator.py` — new module. `EventAccumulator`,
`ToolCallEntry`, `process_event` extracted from `collect.py`. Both the
direct-stream and cross-process paths now use the same fold logic.
- `tools/run_sub_session.py` / `tools/get_sub_session_result.py` —
rewritten around the shared primitive. `sub_session_id` is now the sub's
`ChatSession` id directly (no separate registry handle). Ownership
re-verified on every call via `get_chat_session`. Cancel via
`enqueue_cancel_task` on the existing `copilot_cancel` fan-out exchange.
- `blocks/autopilot.py` — `execute_copilot` replaced its inline
`collect_copilot_response` with `run_copilot_turn_via_queue`.
`SessionResult` carries response text, tool calls, and token usage back
from the worker so no DB round-trip is needed. The block's public I/O
contract (inputs, outputs, `ToolCallEntry` shape) is unchanged.
- `CoPilotExecutionEntry` gains a `permissions: CopilotPermissions |
None` field forwarded to the worker's `stream_fn` so the sub's
capability filter survives the queue hop. The processor passes it
through to `stream_chat_completion_sdk` /
`stream_chat_completion_baseline`.
- **Deleted**: `sdk/sub_session_registry.py` (module-level dict,
done-callback, abandoned-task cap, `notify_shutdown_and_cancel_all`,
`_reset_for_test`), plus the shutdown-notifier hook in
`copilot_executor.processor.cleanup` — redundant under queue-backed
execution.

#### Run_block single-tool cap (3)

- `tools/helpers.execute_block` caps block execution at
`MAX_TOOL_WAIT_SECONDS = 5 min` via `asyncio.wait_for` around the
generator consumption.
- On timeout: logs `copilot_tool_timeout tool=run_block block=…
block_id=… input_keys=… user=… session=… cap_s=…` (grep-friendly) and
returns an `ErrorResponse` that redirects the LLM to `run_agent` /
`run_sub_session`.
- Billing protection: `_charge_block_credits` is called in a `finally`
guarded by `asyncio.shield` and marked `charge_handled` **before** the
await so cancel-mid-charge doesn't double-bill and
cancel-mid-generator-before-charge still settles via the finally.

#### Guide-read gate

- `helpers.require_guide_read(session, tool_name)` scans
`session.messages` for any prior assistant tool call named
`get_agent_building_guide` (handles both OpenAI and flat shapes).
Applied at the top of `_execute` in `create_agent`, `edit_agent`,
`validate_agent_graph`, `fix_agent_graph`. Tool descriptions advertise
the requirement.

#### Shared timing constants

- `MAX_TOOL_WAIT_SECONDS = 5 * 60` + `STREAM_IDLE_TIMEOUT_SECONDS = 2 *
MAX_TOOL_WAIT_SECONDS` in `constants.py`. Every long-running tool
(`run_agent`, `view_agent_output`, `run_sub_session`,
`get_sub_session_result`, `run_block`) imports from one place; no more
hardcoded 300 / `10*60` literals drifting apart. Stream-idle invariant
("no single tool blocks close to the idle timeout") holds by
construction.

### Frontend

- Friendlier tool-card labels: `run_sub_session` → "Sub-AutoPilot",
`get_sub_session_result` → "Sub-AutoPilot result", `run_block` →
"Action" (matches the builder UI's own naming), `run_agent` → "Agent".
Fixes the double-verb "Running Run …" phrasing.
- `SubSessionStatusResponse.sub_autopilot_session_link` surfaces
`/copilot?sessionId=<inner>` so users can click into any sub's session
from the tool-call card — same pattern as `run_agent`'s
`library_agent_link`.

### Changes 🏗️

- **New modules**: `sdk/session_waiter.py`, `sdk/stream_accumulator.py`,
`tools/run_sub_session.py`, `tools/get_sub_session_result.py`,
`tools/sub_session_test.py`, `tools/agent_guide_gate_test.py`.
- **New response types**: `SubSessionStatusResponse`,
`SubSessionProgressSnapshot`, `SessionResult`.
- **New gate helper**: `require_guide_read` in `tools/helpers.py`.
- **Queue protocol**: `permissions` field on `CoPilotExecutionEntry`,
threaded through `processor.py` → `stream_fn`.
- **Hidden**: `AUTOPILOT_BLOCK_ID` in `COPILOT_EXCLUDED_BLOCK_IDS`
(run_block can't execute AutoPilotBlock; agents use `run_sub_session`
instead).
- **Deleted**: `sdk/sub_session_registry.py`, processor
shutdown-notifier hook.
- **Regenerated**: `openapi.json` for the new response types; block-docs
for the updated `ToolName` Literal.
- **Tool descriptions**: tightened the guide-gate hint across the four
agent-builder tools to stay under the 32000-char schema budget.
- **40+ tests** across sub_session, execute_block cap + billing races,
stream_accumulator, agent_guide_gate, frontend helpers.

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] Unit suite green on the full copilot tree; `poetry run format` +
`pyright` clean
- [x] Schema character budget test passes (tool descriptions trimmed to
stay under 32000)
- [x] Native UI E2E (`poetry run app` + `pnpm dev`):
`run_sub_session(wait_for_result=60)` returns `status="completed"` +
`sub_autopilot_session_link` inline;
`run_sub_session(wait_for_result=1)` returns `status="running"` +
handle, `get_sub_session_result(wait_if_running=60)` observes `running →
completed` transition
- [x] AutoPilotBlock (graph) goes through `copilot_executor` queue
end-to-end (verified via logs: ExecutionManager's AutoPilotBlock node
spawned session `f6de335b-…`, a different `CoPilotExecutor` worker
acquired its cluster lock and ran the SDK stream)
- [x] Guide gate: `create_agent` without a prior
`get_agent_building_guide` returns the refusal; agent reads the guide
and retries successfully
2026-04-18 23:11:41 +07:00
Toran Bruce Richards
1c0c7a6b44 fix(copilot): add gh auth status check to Tool Discovery Priority section (#12832)
## Problem

The CoPilot system prompt contains a `gh auth status` instruction in the
E2B-specific `GitHub CLI` section, but models pattern-match to
`connect_integration` from the **Tool Discovery Priority** section —
which is where the actual decision to call an external service is made.

Because the GitHub auth check lives in a separate, later section, it's
not salient at the point of decision-making. This causes the model to
call `connect_integration(provider='github')` even when `gh` is already
authenticated via `GH_TOKEN`, unnecessarily prompting the user.

## Fix

Add a 3-line callout directly inside the **Tool Discovery Priority**
section:

```
> 🔑 **GitHub exception:** Before calling `connect_integration` for GitHub,
> always run `gh auth status` first. If it shows `Logged in`, proceed
> directly with `gh`/`git` — no integration connection needed.
```

This places the rule at the exact location where the model decides which
tool path to take, preventing the miss.

## Why this works

- **Placement over repetition**: The existing instruction isn't wrong —
it's just in the wrong spot relative to where the decision is made
- **Negative framing**: Explicitly says "before calling
`connect_integration`" which directly intercepts the incorrect reflex
- **Minimal change**: 4 lines added, zero removed

Co-authored-by: Toran Bruce Richards <22963551+Torantulino@users.noreply.github.com>
2026-04-17 15:22:10 +00:00
Joe Munene
3a01874911 fix(frontend/builder): preserve agent name in AgentExecutor node title after reload (#12805)
## Summary

Fixes #11041

When an `AgentExecutorBlock` is placed in the builder, it initially
displays the agent's name (e.g., "Researcher v2"). After saving and
reloading the page, the title reverts to the generic "Agent Executor."

## Root Cause

The backend correctly persists `agent_name` and `graph_version` in
`hardcodedValues` (via `input_default` in `AgentExecutorBlock`).
However, `NodeHeader.tsx` always resolves the display title from
`data.title` (the generic block name), ignoring the persisted agent
name.

## Fix

Modified the title resolution chain in `NodeHeader.tsx` to check
`data.hardcodedValues.agent_name` between the user's custom name and the
generic block title:

1. `data.metadata.customized_name` (user's manual rename) — highest
priority
2. `agent_name` + ` v{graph_version}` from `hardcodedValues` — **new**
3. `data.title` (generic block name) — fallback

This is a frontend-only change. No backend modifications needed.

## Files Changed

-
`autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/components/NodeHeader.tsx`
(+11, -1)

## Test Plan

- [x] Place an AgentExecutorBlock, select an agent — title shows agent
name
- [x] Save graph, reload page — title still shows agent name (was "Agent
Executor" before)
- [x] Double-click to rename — custom name takes priority over agent
name
- [x] Clear custom name — falls back to agent name
- [x] Non-AgentExecutor blocks — unaffected, show generic title as
before

---------

Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
2026-04-17 15:20:32 +00:00
Zamil Majdy
6d770d9917 fix(platform/copilot): revert forward pagination, add visibility guarantee for blank chat (#12831)
## Why / What / How

**Why:** PR #12796 changed completed copilot sessions to load messages
from sequence 0 forward (ascending), which broke the standard chat UX —
users now land at the beginning of the conversation instead of the most
recent messages. Reported in Discord.

**What:** Reverts the forward pagination approach and replaces it with a
visibility guarantee that ensures every page contains at least one
user/assistant message.

**How:**
- **Backend**: Removed after_sequence, from_start, forward_paginated,
newest_sequence — always use backward (newest-first) pagination. Added
_expand_for_visibility() helper: after fetching, if the entire page is
tool messages (invisible in UI), expand backward up to 200 messages
until a visible user/assistant message is found.
- **Frontend**: Removed all forwardPaginated/newestSequence plumbing
from hooks and components. Removed bottom LoadMoreSentinel. Simplified
message merge to always prepend paged messages.

### Changes
- routes.py: Reverted to simple backward pagination, removed TOCTOU
re-fetch logic
- db.py: Removed forward mode, extracted _expand_tool_boundary() and
added _expand_for_visibility()
- SessionDetailResponse: Removed newest_sequence and forward_paginated
fields
- openapi.json: Removed after_sequence param and forward pagination
response fields
- Frontend hooks/components: Removed forward pagination props and logic
(-1000 lines)
- Updated all tests (backend: 63 pass, frontend: 1517 pass)

### Checklist
- [x] I have clearly listed my changes in the PR description
- [x] Backend unit tests: 63 pass
- [x] Frontend unit tests: 1517 pass
- [x] Frontend lint + types: clean
- [x] Backend format + pyright: clean
2026-04-17 19:23:28 +07:00
slepybear
334ec18c31 docs: convert in-code comments to MkDocs admonitions in block-sdk-gui… (#12819)
### Why / What / How

<!-- Why: Why does this PR exist? What problem does it solve, or what's
broken/missing without it? -->
This PR converts inline Python comments in code examples within
`block-sdk-guide.md` into MkDocs `!!! note` admonitions. This makes code
examples cleaner and more copy-paste friendly while preserving all
explanatory content.

<!-- What: What does this PR change? Summarize the changes at a high
level. -->
Converts inline comments in code blocks to admonitions following the
pattern established in PR #12396 (new_blocks.md) and PR #12313.

<!-- How: How does it work? Describe the approach, key implementation
details, or architecture decisions. -->
- Wrapped code examples with `!!! note` admonitions
- Removed inline comments from code blocks for clean copy-paste
- Added explanatory admonitions after each code block

### Changes 🏗️

- Provider configuration examples (API key and OAuth)
- Block class Input/Output schema annotations
- Block initialization parameters
- Test configuration
- OAuth and webhook handler implementations
- Authentication types and file handling patterns

### Checklist 📋

#### For documentation changes:
- [x] Follows the admonition pattern from PR #12396
- [x] No code changes, documentation only
- [x] Admonition syntax verified correct

#### For configuration changes:
- [ ] `.env.default` is updated or already compatible with my changes
- [ ] `docker-compose.yml` is updated or already compatible with my
changes

---

**Related Issues**: Closes #8946

Co-authored-by: slepybear <slepybear@users.noreply.github.com>
Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
2026-04-17 07:47:52 +00:00
slepybear
ea5cfdfa2e fix(frontend): remove debug console.log statements (#12823)
## Why
Debug console.log statements were left in production code, which can
leak
sensitive information and pollute browser developer consoles.

## What
Removed console.log from 4 non-legacy frontend components:
- useNavbar.ts: isLoggedIn debug log
- WalletRefill.tsx: autoRefillForm debug log  
- EditAgentForm.tsx: category field debug log
- TimezoneForm.tsx: currentTimezone debug log

## How
Simply deleted the console.log lines as they served no purpose 
other than debugging during development.

## Checklist
- [x] Code follows project conventions
- [x] Only frontend changes (4 files, 6 lines removed)
- [x] No functionality changes

Co-authored-by: slepybear <slepybear@users.noreply.github.com>
2026-04-17 07:31:51 +00:00
Ubbe
d13a85bef7 feat(frontend): surface scheduled agents in library & copilot briefings (#12818)
## Why

Scheduled agents weren't well-surfaced in the Library and Copilot
briefings:

- The Library fleet summary didn't count agents that are scheduled
purely via the scheduler (only those with a `recommended_schedule_cron`
set at the agent level).
- Sitrep items didn't distinguish scheduled or listening (trigger-based)
agents, so they often fell back to a generic "idle" state.
- Scheduled chips showed a generic message with no indication of when
the next run would happen.
- The Copilot Agent Briefing surfaced every scheduled agent regardless
of how far out the next run was — an agent scheduled a month away would
take a slot from something actually happening soon.
- Long sitrep messages overflowed the row.

## What

- Add `is_scheduled` to `LibraryAgent` (sourced from the scheduler) so
the frontend can reliably detect schedule-only agents.
- Count scheduled agents in `useLibraryFleetSummary`.
- Include scheduled and listening agents in sitrep items, with a
priority ordering (error → running → stale → success → listening →
scheduled → idle).
- Show a relative next-run time on scheduled sitrep chips (e.g.
"Scheduled to run in 2h" / "in 3d").
- Filter the Copilot Agent Briefing to scheduled agents whose next run
is within the next 3 days.
- Truncate long sitrep messages to 1 line with `OverflowText` and show
the full text in a tooltip on hover.

## How

- Scheduler → `LibraryAgent` mapping populates `is_scheduled` /
`next_scheduled_run`.
- `useSitrepItems` gains an optional `scheduledWithinMs` parameter.
Copilot's `usePulseChips` passes `3 * 24 * 60 * 60 * 1000`; the Library
briefing omits it to keep its existing (unbounded) behavior.
- Scheduled config-based sitrep items are skipped when
`next_scheduled_run` is missing or outside the window.
- `SitrepItem` wraps the message in `OverflowText` so a single-line
ellipsis + hover tooltip replaces raw overflow.

## Test plan

- [ ] `/library` — scheduled and listening agents appear in the sitrep
with accurate copy; fleet summary counts scheduled agents correctly;
long messages truncate with a tooltip on hover.
- [ ] `/copilot` — on an empty session with the `AGENT_BRIEFING` flag
on, the briefing only shows scheduled agents whose next run is within 3
days; agents scheduled further out no longer appear as "scheduled"
chips.
- [ ] Scheduled chip text reads "Scheduled to run in {Nm|Nh|Nd}"
matching `next_scheduled_run`.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-17 14:36:15 +07:00
Zamil Majdy
60b85640e7 fix(backend/copilot): replace dedup lock with idempotent append_and_save_message (#12814)
## Why

The Redis dedup lock (`chat:msg_dedup:{session}:{content_hash}`, 30s
TTL) was solving the wrong problem:

- Its purpose: block infra/nginx retries from calling
`append_and_save_message` twice after a client disconnect, writing a
duplicate user message to the DB.
- The approach: deliberately hold the lock for 30s on `GeneratorExit`.
- Why unnecessary: the executor's cluster lock already prevents
duplicate *execution*. The only real gap was duplicate *DB writes* in
the ~1s before the executor picks up the turn.

## What

- **Deleted** `message_dedup.py` and `message_dedup_test.py` (~150 lines
removed).
- **Removed** all dedup lock code from `routes.py` (~40 lines removed).
- **`append_and_save_message`** is now idempotent and self-contained:
- Uses redis-py's built-in `Lock(timeout=10, blocking_timeout=2)` —
Lua-script atomic acquire/release, no manual poll/sleep loop.
- Lock context manager yields `bool` (`True` = acquired, `False` =
degraded). When degraded (Redis down or 2s timeout), reads from DB
directly instead of cache to avoid stale-state duplicates.
- Idempotency check: if `session.messages[-1]` already matches the
incoming role+content, returns `None` instead of the session.
- Lock released explicitly as soon as the write completes; `try/except`
in `finally` so a cleanup error after a successful write never surfaces
a false 500.
- On cache-write failure, the stale cache entry is invalidated so future
reads fall back to the authoritative DB.
- **`routes.py`** uses the `None` signal: `is_duplicate_message = (await
append_and_save_message(...)) is None`
- Skips `create_session` and `enqueue_copilot_turn` for duplicates —
client re-attaches to the existing turn's Redis stream.
- `track_user_message` and `turn_id` generation only happen when
`is_duplicate_message` is false.
- **`subscribe_to_session`** retry window increased from 1×50ms to
3×100ms — covers the window where a duplicate request subscribes before
the original's `create_session` hset completes.
- **Cleaned up** `routes_test.py`: removed 5 dedup-specific tests and
the `mock_redis` setup from `_mock_stream_internals`; added
duplicate-skips-enqueue test.

## How

The idempotency guard distinguishes legit same-text messages from
retries via the **assistant turn between them**: if the user said "yes",
got a response, and says "yes" again, `session.messages[-1]` is the
assistant reply, so the role check fails and the second message goes
through. A retry (no response yet) sees the user message as the last
entry and is blocked.

```python
if (
    session.messages
    and session.messages[-1].role == message.role
    and session.messages[-1].content == message.content
):
    return None  # duplicate — caller skips enqueue
```

The Redis lock ensures this check always sees authoritative state even
in multi-replica deployments. When the lock is unavailable (Redis down
or contention), reading from DB directly (bypassing potentially stale
cache) provides the same safety guarantee at the cost of a DB
round-trip.

## Checklist

- [x] PR targets `dev`
- [x] Conventional commit title with scope
- [x] Tests added/updated (duplicate detection, lock degradation, DB
error, cache invalidation paths)
- [x] `poetry run format` and `poetry run pyright` pass clean
- [x] No new linter suppressors
2026-04-16 22:12:30 +07:00
Zamil Majdy
87e4d42750 fix(backend/copilot): fix initial load missing messages + forward pagination for completed sessions (#12796)
### Why / What / How

**Why:** Completed copilot sessions with many messages showed a
completely empty chat view. A user reported a 158-message session that
appeared blank on reload.

**What:** Two bugs fixed:
1. **Backend** — initial page load always returned the newest 50
messages in DESC order. For sessions heavy in tool calls, the user's
original messages (seq 0–5) were never included; all 50 slots consumed
by mid-session tool outputs.
2. **Frontend** — convertChatSessionToUiMessages silently dropped user
messages with null/empty content.

**How:** For completed sessions (no active stream), the backend now
loads from sequence 0 in ASC order. Active/streaming sessions keep
newest-first for streaming context. A new after_sequence forward cursor
enables infinite-scroll for subsequent pages (sentinel moves to bottom).
The frontend wires forward_paginated + newest_sequence end-to-end.

### Changes 🏗️

- db.py: added from_start (ASC) and after_sequence (forward cursor)
modes; added newest_sequence to PaginatedMessages
- routes.py: detect completed vs active on initial load; pass
from_start=True for completed; expose newest_sequence +
forward_paginated; accept after_sequence param
- convertChatSessionToUiMessages.ts: never drop user messages with empty
content
- useLoadMoreMessages.ts: forward pagination via after_sequence; append
pages to end
- ChatMessagesContainer.tsx: LoadMoreSentinel at bottom for
forward-paginated sessions
- Wire newestSequence + forwardPaginated end-to-end through
useChatSession/useCopilotPage/ChatContainer
- openapi.json: add after_sequence + newest_sequence/forward_paginated;
regenerate types
- db_test.py: 9 new unit tests for from_start and after_sequence modes

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] Open a completed session with many messages — first user message
visible on initial load
- [x] Scroll to bottom of completed session — load more appends next
page
- [x] Open active/streaming session — newest messages shown first,
streaming unaffected
  - [x] Backend unit tests: all 28 pass
  - [x] Frontend lint/format: clean, no new type errors

---------

Co-authored-by: chernistry <73943355+chernistry@users.noreply.github.com>
Co-authored-by: Nicholas Tindle <nicholas.tindle@agpt.co>
2026-04-16 14:16:54 +00:00
Ubbe
0339d95d12 fix(frontend): small UI fixes, sort menu bg, name update auth, stats grid overflow, pulse chips (#12815)
## Summary
- **LibrarySortMenu / AgentFilterMenu**: Force `!bg-transparent` and
neutralise legacy `SelectTrigger` styles (`m-0.5`, `ring-offset-white`,
`shadow-sm`) that caused a white background around the trigger
- **EditNameDialog**: Replace client-side `supabase.auth.updateUser()`
with server-side `PUT /api/auth/user` route — fixes "Auth session
missing!" error caused by `httpOnly` cookies being inaccessible to
browser JS
- **StatsGrid**: Swap label `Text` for `OverflowText` so tile labels
truncate with `…` and show a tooltip instead of wrapping when the grid
is squeezed
- **PulseChips**: Set fixed `15rem` chip width with `shrink-0`,
horizontal scroll, and styled thin scrollbar
- **Tests**: Updated `EditNameDialog` tests to use MSW instead of
mocking Supabase client; added 7 new `PulseChips` integration tests

## Test plan
- [x] `pnpm test:unit` — all 1495 tests pass (91 files)
- [x] `pnpm format && pnpm lint` — clean
- [x] `pnpm types` — no new errors (pre-existing only)
- [ ] QA `/library?sort=updatedAt` — sort menu trigger has no white bg
- [ ] QA `/library` — StatsGrid labels truncate with tooltip on narrow
viewports
- [ ] QA `/copilot` — PulseChips scroll horizontally at fixed width
- [ ] QA `/copilot` — Edit name dialog saves successfully (no "Auth
session missing!")

🤖 Generated with [Claude Code](https://claude.com/claude-code)

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-16 20:11:21 +07:00
Toran Bruce Richards
f410929560 feat(platform): Add xAI Grok 4.20 models from OpenRouter (#12620)
Requested by @Torantulino

Adds the 2 xAI Grok 4.20 models available on OpenRouter that are missing
from the platform.

## Why

`x-ai/grok-4.20` and `x-ai/grok-4.20-multi-agent` are xAI's current
flagship models (released March 2026) and are available via OpenRouter,
but weren't accessible from the platform's LLM blocks.

## Changes

**`autogpt_platform/backend/backend/blocks/llm.py`**
- Added `GROK_4_20` and `GROK_4_20_MULTI_AGENT` enum members
- Added corresponding `MODEL_METADATA` entries (open_router provider, 2M
context window, price tier 3)

**`autogpt_platform/backend/backend/data/block_cost_config.py`**
- Added `MODEL_COST` entries at 5 credits each (flagship tier, $2/M in)

**`docs/integrations/block-integrations/llm.md`**
- Added new model IDs to all LLM block tables

| Model | Pricing | Context |
|-------|---------|---------|
| `x-ai/grok-4.20` | $2/M in, $6/M out | 2M |
| `x-ai/grok-4.20-multi-agent` | $2/M in, $6/M out | 2M |

Both models use the standard OpenRouter chat completions API — no
special handling needed.

Resolves: SECRT-2196

---------

Co-authored-by: Torantulino <22963551+Torantulino@users.noreply.github.com>
Co-authored-by: Toran Bruce Richards <Torantulino@users.noreply.github.com>
Co-authored-by: Otto (AGPT) <otto@agpt.co>
2026-04-16 12:14:56 +00:00
Zamil Majdy
2bbec09e1a feat(platform): subscription tier billing via Stripe Checkout (#12727)
## Why

Introducing paid subscription tiers (PRO, BUSINESS) so we can charge for
AutoPilot capacity beyond the free tier. Without a billing integration,
all users share the same rate limits regardless of their willingness to
pay for additional capacity.

## What

End-to-end subscription billing system using Stripe Checkout Sessions:

**Backend:**
- `SubscriptionTier` enum (`FREE`, `PRO`, `BUSINESS`, `ENTERPRISE`) on
the `User` model
- `POST /credits/subscription` — creates a Stripe Checkout Session for
paid upgrades; for FREE tier or when `ENABLE_PLATFORM_PAYMENT` is off,
sets tier directly
- `GET /credits/subscription` — returns current tier, monthly cost
(cents), and all tier costs
- `POST /credits/stripe_webhook` — handles
`customer.subscription.created/updated/deleted`,
`checkout.session.completed`, `charge.dispute.*`, `refund.created`
- `sync_subscription_from_stripe()` — keeps `User.subscriptionTier` in
sync from webhook events; guards against out-of-order delivery
(cancelled event after new sub created), ENTERPRISE overwrite, and
duplicate webhook replay
- Open-redirect protection on `success_url`/`cancel_url` via
`_validate_checkout_redirect_url()`
- `_cancel_customer_subscriptions()` — cancels both active and trialing
subs; propagates errors so callers can avoid updating DB tier on Stripe
failure
- `_cleanup_stale_subscriptions()` — best-effort cancellation of old
subs when a new one becomes active (paid-to-paid upgrade), to prevent
double-billing
- `get_stripe_customer_id()` with idempotency key to prevent duplicate
Stripe customers on concurrent requests
- `cache_none=False` sentinel fix in `@cached` decorator so Stripe price
lookups retry on transient error instead of poisoning the cache with
`None`
- Stripe Price IDs read from LaunchDarkly (`stripe-price-id-pro`,
`stripe-price-id-business`). If not configured, upgrade returns 422.

**Frontend:**
- `SubscriptionTierSection` component on billing page: tier cards
(FREE/PRO/BUSINESS), upgrade/downgrade buttons, per-tier cost display,
Stripe redirect on upgrade
- Confirmation dialog for downgrades
- ENTERPRISE users see a read-only admin-managed banner
- Success toast on return from Stripe Checkout (`?subscription=success`)
- Uses generated `useGetSubscriptionStatus` /
`useUpdateSubscriptionTier` hooks

## How

- Paid upgrades use Stripe Checkout Sessions (not server-side
subscription creation) — Stripe handles PCI-compliant card collection
and the subscription lifecycle
- Tier is synced back via webhook on
`customer.subscription.created/updated/deleted`
- Downgrade to FREE cancels via Stripe API immediately; a
`stripe.StripeError` during cancellation returns 502 with a generic
message (no Stripe detail leakage)
- LaunchDarkly flags: `stripe-price-id-pro` (string),
`stripe-price-id-business` (string), `enable-platform-payment` (bool)
- `ENABLE_PLATFORM_PAYMENT=false` bypasses Stripe for beta/internal
access (sets tier directly)

## Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] `ENABLE_PLATFORM_PAYMENT=false` → tier change updates directly, no
Stripe redirect
- [x] `ENABLE_PLATFORM_PAYMENT=true` with price IDs configured → paid
upgrade redirects to Stripe Checkout
- [x] Stripe webhook `customer.subscription.created` →
`User.subscriptionTier` updated
  - [x] Unrecognised price ID in webhook → logs warning, tier unchanged
  - [x] ENTERPRISE user webhook event → tier not overwritten
  - [x] Empty `STRIPE_WEBHOOK_SECRET` → 503 (prevents HMAC bypass)
  - [x] Open-redirect attack on `success_url`/`cancel_url` → 422

#### For configuration changes:
- [x] No `.env` or `docker-compose.yml` changes
- [x] LaunchDarkly flags to create: `stripe-price-id-pro` (string),
`stripe-price-id-business` (string), `enable-platform-payment` (bool)

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: majdyz <majdy.zamil@gmail.com>
2026-04-16 17:52:06 +07:00
Ubbe
31b88a6e56 feat(frontend): add Agent Briefing Panel (#12764)
## Summary

<img width="800" height="772" alt="Screenshot_2026-04-13_at_18 29 19"
src="https://github.com/user-attachments/assets/3da6eaf2-1485-4c08-9651-18f2f4220eba"
/>
<img width="800" height="285" alt="Screenshot_2026-04-13_at_18 29 24"
src="https://github.com/user-attachments/assets/6a5f981a-1e1d-4d22-a33d-9e1b0e7555a7"
/>
<img width="800" height="288" alt="Screenshot_2026-04-13_at_18 29 27"
src="https://github.com/user-attachments/assets/f97b4611-7c23-4fc9-a12d-edf6314a77ef"
/>
<img width="800" height="433" alt="Screenshot_2026-04-13_at_18 29 31"
src="https://github.com/user-attachments/assets/e6d7241d-84f3-4936-b8cd-e0b12df392bb"
/>
<img width="700" height="554" alt="Screenshot_2026-04-13_at_18 29 40"
src="https://github.com/user-attachments/assets/92c08f21-f950-45cd-8c1d-529905a6e85f"
/>


Implements the Agent Intelligence Layer — real-time agent awareness
across the Library and Copilot pages.

### Core Features
- **Agent Briefing Panel** — stats grid with fleet-wide counts (running,
recently completed, needs attention, scheduled, idle, monthly spend) and
tab-driven content below
- **Enhanced Library Cards** — StatusBadge, run counts, contextual
action buttons (See tasks, Start, Chat) with consistent icon-left
styling
- **Situation Report Items** — prioritized sitrep with error-first
ranking, "See task" deep-links for completed runs, and "Ask AutoPilot"
bridge
- **Home Pulse Chips** — agent status chips on Copilot empty state with
hover-reveal actions (slide-up animation + backdrop blur on desktop,
always visible on touch)
- **Edit Display Name** — pencil icon on Copilot greeting to update
Supabase user metadata inline

### Backend
- **Execution count API** — batch `COUNT(*)` query on
`AgentGraphExecution` grouped by `agentGraphId` for the current user,
avoiding loading full execution rows. Wired into `list_library_agents`
and `list_favorite_library_agents` via `execution_count_override` on
`LibraryAgent.from_db()`

### UI Polish
- Subtler gradient on AgentBriefingPanel (reduced opacity on background
+ animated border)
- Consistent button styles across all action buttons (icon-left, same
sizing)
- Removed duplicate "Open in builder" menu item (kept "Edit agent")
- "Recently completed" tab replaces "Listening" in briefing panel,
showing agents with completed runs in last 72h

## Changes

### Backend
- `backend/api/features/library/db.py` — added
`_fetch_execution_counts()` batch COUNT query, wired into list endpoints
- `backend/api/features/library/model.py` — added
`execution_count_override` param to `LibraryAgent.from_db()`

### Frontend — New files
- `EditNameDialog/EditNameDialog.tsx` — modal to update display name via
Supabase auth
- `PulseChips/PulseChips.module.css` — hover-reveal animation + glass
panel styles

### Frontend — Modified files
- `EmptySession.tsx` — added EditNameDialog and PulseChips
- `PulseChips.tsx` — redesigned with See/Ask buttons, hover overlay on
desktop
- `usePulseChips.ts` — added agentID for deep-linking
- `AgentBriefingPanel.tsx` — subtler gradient, adjusted padding
- `AgentBriefingPanel.module.css` — reduced conic gradient opacity
- `BriefingTabContent.tsx` — added "completed" tab routing
- `StatsGrid.tsx` — replaced Listening with Recently completed,
reordered tabs
- `SitrepItem.tsx` — consistent button styles, "See task" link for
completed items, updated copilot prompt
- `ContextualActionButton.tsx` — icon-left, smaller icon, renamed Run to
Start
- `LibraryAgentCard.tsx` — icon-left on all buttons, EyeIcon for See
tasks
- `AgentCardMenu.tsx` — removed duplicate "Open in builder"
- `useAgentStatus.ts` — added completed count to FleetSummary
- `useLibraryFleetSummary.ts` — added recent completion tracking
- `types.ts` — added `completed` to FleetSummary and AgentStatusFilter

## Test plan
- [ ] Library page renders Agent Briefing Panel with stats grid
- [ ] "Recently completed" tab shows agents with completed runs in last
72h
- [ ] Agent cards show real execution counts (not 0)
- [ ] Action buttons have consistent styling with icon on the left
- [ ] "See task" on completed items deep-links to agent page with
execution selected
- [ ] "Ask AutoPilot" generates last-run-specific prompt for completed
items
- [ ] Copilot empty state shows PulseChips with hover-reveal actions on
desktop
- [ ] PulseChips show See/Ask buttons always on touch screens
- [ ] Pencil icon on greeting opens edit name dialog
- [ ] Name update persists via Supabase and refreshes greeting
- [ ] `pnpm format && pnpm lint && pnpm types` pass
- [ ] `poetry run format` passes for backend changes

🤖 Generated with [Claude Code](https://claude.com/claude-code)

---------

Co-authored-by: John Ababseh <jababseh7@gmail.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: Bentlybro <Github@bentlybro.com>
Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
Co-authored-by: CodeRabbit <noreply@coderabbit.ai>
Co-authored-by: majdyz <zamil.majdy@agpt.co>
2026-04-16 17:32:17 +07:00
Zamil Majdy
d357956d98 refactor(backend/copilot): make session-file helper fns public to fix Pyright warnings (#12812)
## Why
After PR #12804 was squashed into dev, two module-level helper functions
in `backend/copilot/sdk/service.py` remained private (`_`-prefixed)
while being directly imported by name in `sdk/transcript_test.py`.
Pyright reports `reportAttributeAccessIssue` when tests (even those
excluded from CI lint) import private symbols from outside their
defining module.

## What
Rename two helpers to remove the underscore prefix:
- `_process_cli_restore` → `process_cli_restore`
- `_read_cli_session_from_disk` → `read_cli_session_from_disk`

Update call sites in `service.py` and imports/calls/docstrings in
`sdk/transcript_test.py`.

## How
Pure rename — no logic change. Both functions were already module-level
helpers with no reason to be private; the underscore was convention
carried over during the refactor but they are directly unit-tested and
should be public.

All 66 `sdk/transcript_test.py` tests pass after the rename.

## Checklist
- [x] Tests pass (`poetry run pytest
backend/copilot/sdk/transcript_test.py`)
- [x] No `_`-prefixed symbols imported across module boundaries
- [x] No linter suppressors added
2026-04-16 17:00:02 +07:00
Zamil Majdy
697ffa81f0 fix(backend/copilot): update transcript_test to use strip_for_upload after upload_cli_session removal 2026-04-16 16:17:02 +07:00
Zamil Majdy
2b4727e8b2 chore: merge master into dev, resolve baseline/transcript conflicts
Conflicts in baseline/service.py, baseline/transcript_integration_test.py,
and transcript.py arose because dev-only commit 0cd0a76305
(baseline upload fix) overlapped with the same fix in PR #12804 which
landed in master. Took master's version for all three files — it is the
complete, reviewed implementation.
2026-04-16 15:38:46 +07:00
Zamil Majdy
0d4b31e8a1 refactor(backend/copilot): unified transcript context — extract_context_messages, mode-gated --resume, compaction-aware gap-fill (#12804)
### Why / What / How

**Why:** The copilot had two separate GCS paths (`cli-sessions/` and
`chat-transcripts/`), redundant function names
(`upload_cli_session`/`restore_cli_session`), and no shared context
strategy between modes. When switching from baseline→SDK or
SDK→baseline, the receiving mode discarded the stored transcript and
fell back to full DB reconstruction — loading all raw messages instead
of the compacted form — causing inflated context, wasted tokens, and
loss of CLI compaction summaries.

**What:**
- Single GCS path (`cli-sessions/`) for both modes — `chat-transcripts/`
removed
- Unified public API: `upload_transcript` / `download_transcript` /
`TranscriptDownload`
- `TranscriptMode = Literal["sdk", "baseline"]` persisted in
`.meta.json` — SDK skips `--resume` when `mode != "sdk"`
(baseline-written JSONL has stripped fields / synthetic IDs)
- `extract_context_messages(download, session_messages)` — shared
context primitive used by **both SDK and baseline**: reads compacted
transcript content + fills only the DB gap (messages after watermark),
so CLI compaction summaries are preserved across mode switches
- Watermark fix: `_jsonl_covered = transcript_msg_count + 2` when a real
transcript is present, preventing false gap detection after `--resume`
- Baseline gap-fill: `_append_gap_to_builder` converts `ChatMessage` →
JSONL entries; no more silently discarded stale transcripts

**How:**

```
SDK turn (mode="sdk" transcript available):
  ──► --resume  [full CLI session restored natively]
  ──► inject gap prefix if DB has messages after watermark

SDK turn (mode="baseline" transcript available):
  ──► cannot --resume (synthetic CLI IDs)
  ──► extract_context_messages(download, session_messages):
        returns transcript JSONL (compacted, isCompactSummary preserved) + gap
        excludes session_messages[-1] (current turn — caller injects it separately)
  ──► format as <conversation_history> + "Now, the user says: {current}"

Baseline turn (any transcript):
  ──► _load_prior_transcript → TranscriptDownload
  ──► extract_context_messages(download, session_messages) + session_messages[-1]
        replaces full session.messages DB read
  ──► LLM messages: [compacted history + gap] + [current user turn]

Transcript unavailable — both SDK (use_resume=False) and baseline:
  ──► extract_context_messages(None, session_messages) returns session_messages[:-1]
        (all prior DB messages except the current user turn at [-1])
  ──► graceful fallback — no crash, no empty context
  ──► covers: first turn, GCS error, corrupt JSONL, missing .meta.json
  ──► next successful response uploads a fresh transcript
```

`extract_context_messages` is the shared primitive — both modes call the
same function, which handles:
- `download=None` (first turn, GCS unavailable) → falls back to
`session_messages[:-1]`
- Empty/corrupt content → falls back to `session_messages[:-1]`
- `bytes` content (raw GCS) or `str` content (pre-decoded baseline path)
- `isCompactSummary=True` entries → preserved so CLI compaction survives
mode switches
- Missing/corrupt `.meta.json` → `message_count` defaults to `0`, `mode`
defaults to `"sdk"`

**Why `[:-1]` and not all messages?** `session_messages[-1]` is always
the current user turn being handled right now. Both callers inject it
separately — SDK wraps it as `"Now, the user says: ..."`, baseline
appends it as the final message in the LLM array. Returning it inside
`extract_context_messages` would double-inject it.

### Changes 🏗️

- **`transcript.py`**: `CliSessionRestore` → `TranscriptDownload` +
`mode` field; `upload_cli_session` → `upload_transcript`;
`restore_cli_session` → `download_transcript`; add `TranscriptMode`,
`detect_gap`, `extract_context_messages`; import `ChatMessage` via
relative path to match `service.py` style
- **`sdk/service.py`**: mode-check before `--resume`; `_RestoreResult`
carries `baseline_download` + `context_messages` + `transcript_content`;
`_build_query_message` accepts `prior_messages` override;
`_restore_cli_session_for_turn` populates `context_messages` via
`extract_context_messages` and sets `transcript_content` to prevent
duplicate DB reconstruction; watermark fix (`_jsonl_covered =
transcript_msg_count + 2`)
- **`baseline/service.py`**: `_load_prior_transcript` returns `(bool,
TranscriptDownload | None)`; LLM context replaced with
`extract_context_messages(download, messages)`; `_append_gap_to_builder`
+ `detect_gap` call; `upload_transcript(mode="baseline")`
- **`sdk/transcript.py`**: updated re-exports, old aliases removed
- **`scripts/download_transcripts.py`**: updated for `bytes | str`
content type
- **Test files**: 179 tests total; `transcript_test.py`,
`baseline/transcript_integration_test.py`,
`sdk/service_helpers_test.py`, `sdk/test_transcript_watermark.py`,
`test/copilot/test_transcript_watermark.py` all updated/added

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] 179 unit tests pass — `transcript_test`,
`baseline/transcript_integration_test`, `sdk/service_helpers_test`,
`sdk/test_transcript_watermark`
  - [x] pyright 0 errors on all changed files
- [x] SDK `--resume` path still works when `mode="sdk"` transcript is
present
- [x] SDK fallback uses `extract_context_messages` (compacted baseline
content + gap) when `mode="baseline"` transcript is stored — no more
full DB reconstruction
- [x] Baseline uses `extract_context_messages` per turn instead of full
`session.messages` DB read
  - [x] `isCompactSummary=True` entries preserved across mode switches
- [x] Watermark (`_jsonl_covered`) fix prevents false gap detection
after `--resume`
- [x] Baseline gap detection no longer silently discards stale
transcripts
- [x] `TranscriptDownload.content` accepts `bytes | str` — backward
compatible
- [x] Transcript unavailable (GCS error, first turn, corrupt file)
gracefully falls back to `session_messages[:-1]` without crash — applies
to both SDK and baseline paths

---------

Co-authored-by: chernistry <73943355+chernistry@users.noreply.github.com>
Co-authored-by: Nicholas Tindle <nicholas.tindle@agpt.co>
2026-04-16 15:35:18 +07:00
Zamil Majdy
0cd0a76305 fix(backend/copilot): baseline always uploads when GCS has no transcript
_load_prior_transcript was returning False for missing/invalid transcripts,
which caused should_upload_transcript to suppress the upload. The original
intent was to protect against overwriting a *newer* GCS version — but a
missing or corrupt file is not 'newer'. Only stale (watermark ahead) and
download errors (unknown GCS state) should suppress upload.

Also renames transcript_covers_prefix → transcript_upload_safe throughout
to accurately describe what the flag means.
2026-04-16 14:58:42 +07:00
Toran Bruce Richards
d01a51be0e Add check for GitHub account connection status (#12807)
Added instruction to check GitHub authentication status before prompting
user. This prevents repeated, unnecessary asking of the user to add
their GitHub credentials when they're already added, which is currently
a prevalent bug.

### Changes 🏗️
- Added one line to
`autogpt_platform/backend/backend/copilot/prompting.py` instructing
AutoPilot to run `gh auth status` before prompting the user to connect
their GitHub account.

Co-authored-by: Toran Bruce Richards <22963551+Torantulino@users.noreply.github.com>
2026-04-16 12:09:00 +07:00
chernistry
bd2efed080 fix(frontend): allow zooming out more in the builder (#12690)
Reduced minZoom on the builder canvas from 0.1 to 0.05 to allow zooming
out further when working with large agent graphs.

Fixes #9325

Co-authored-by: Nicholas Tindle <nicholas.tindle@agpt.co>
2026-04-15 21:25:07 +00:00
Zamil Majdy
5fccd8a762 Merge branch 'master' of github.com:Significant-Gravitas/AutoGPT into dev 2026-04-16 01:23:07 +07:00
Zamil Majdy
2740b2be3a fix(backend/copilot): disable fallback model to fix prod CLI rejection (#12802)
### Why / What / How

**Why:** `fffbe0aad8` changed both `ChatConfig.model` and
`ChatConfig.claude_agent_fallback_model` to `claude-sonnet-4-6`. The
Claude Code CLI rejects this with `Error: Fallback model cannot be the
same as the main model`, causing every standard-mode copilot turn to
fail with exit code 1 — the session "completes" in ~30s but produces no
response and drops the transcript.

**What:** Set `claude_agent_fallback_model` default to `""`.
`_resolve_fallback_model()` already returns `None` on empty string,
which means the `--fallback-model` flag is simply not passed to the CLI.
On 529 overload errors the turn will surface normally instead of
silently retrying with a fallback.

**How:** One-line config change + test update.

### Changes 🏗️

- `ChatConfig.claude_agent_fallback_model` default:
`"claude-sonnet-4-6"` → `""`
- Update `test_fallback_model_default` to assert the empty default

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  - [x] `poetry run pytest backend/copilot/sdk/p0_guardrails_test.py`

#### For configuration changes:
- [x] `.env.default` is updated or already compatible with my changes
- [x] `docker-compose.yml` is updated or already compatible with my
changes
2026-04-16 01:22:20 +07:00
Zamil Majdy
d27d22159d Merge branch 'master' of github.com:Significant-Gravitas/AutoGPT into dev 2026-04-16 00:05:32 +07:00
Nicholas Tindle
fffbe0aad8 fix(backend): default copilot sonnet to 4.6 (#12799)
### Why / What / How

Why: Copilot/Autopilot standard requests were still defaulting to Claude
Sonnet 4, while the expected default for this path is Sonnet 4.6.

What: This PR updates the backend Copilot defaults so the
standard/default path and fast path use Sonnet 4.6, and aligns the SDK
fallback model and related test expectations.

How: It changes `ChatConfig.model`, `ChatConfig.fast_model`, and
`ChatConfig.claude_agent_fallback_model` to Sonnet 4.6 values, then
updates backend tests that assert the default Sonnet model strings.

### Changes 🏗️

- Switch `ChatConfig.model` from `anthropic/claude-sonnet-4` to
`anthropic/claude-sonnet-4-6`
- Switch `ChatConfig.fast_model` from `anthropic/claude-sonnet-4` to
`anthropic/claude-sonnet-4-6`
- Switch `ChatConfig.claude_agent_fallback_model` from
`claude-sonnet-4-20250514` to `claude-sonnet-4-6`
- Update backend Copilot tests that assert the default Sonnet model
strings
- Configuration changes:
  - No new environment variables or docker-compose changes are required
- Existing `.env.default` and compose files remain compatible because
this only changes backend default model values in code

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  - [x] `poetry run format`
- [x] `poetry run pytest
backend/copilot/baseline/transcript_integration_test.py`
  - [x] `poetry run pytest backend/copilot/sdk/service_helpers_test.py`
  - [x] `poetry run pytest backend/copilot/sdk/service_test.py`
  - [x] `poetry run pytest backend/copilot/sdk/p0_guardrails_test.py`

<details>
  <summary>Example test plan</summary>
  
  - [ ] Create from scratch and execute an agent with at least 3 blocks
- [ ] Import an agent from file upload, and confirm it executes
correctly
  - [ ] Upload agent to marketplace
- [ ] Import an agent from marketplace and confirm it executes correctly
  - [ ] Edit an agent from monitor, and confirm it executes correctly
</details>

#### For configuration changes:

- [x] `.env.default` is updated or already compatible with my changes
- [x] `docker-compose.yml` is updated or already compatible with my
changes
- [x] I have included a list of my configuration changes in the PR
description (under **Changes**)

<details>
  <summary>Examples of configuration changes</summary>

  - Changing ports
  - Adding new services that need to communicate with each other
  - Secrets or environment variable changes
  - New or infrastructure changes such as databases
</details>

<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> **Medium Risk**
> Changes default/fallback LLM model identifiers for Copilot requests,
which can affect runtime behavior, cost, and availability
characteristics across both baseline and SDK paths. Risk is mitigated by
being a small, config-only change with updated tests.
> 
> **Overview**
> Updates Copilot backend defaults so both the standard (`model`) and
fast (`fast_model`) paths use `anthropic/claude-sonnet-4-6`, and aligns
the Claude Agent SDK fallback model to `claude-sonnet-4-6`.
> 
> Adjusts related test expectations in baseline transcript integration
and SDK helper tests to match the new Sonnet 4.6 model strings.
> 
> <sup>Reviewed by [Cursor Bugbot](https://cursor.com/bugbot) for commit
563361ac11. Bugbot is set up for automated
code reviews on this repo. Configure
[here](https://www.cursor.com/dashboard/bugbot).</sup>
<!-- /CURSOR_SUMMARY -->
2026-04-15 16:53:30 +00:00
Zamil Majdy
df205b5444 fix(backend/copilot): strip CLI session file to prevent auto-compaction context loss
The Claude Code CLI auto-compacts its native session JSONL when the context
approaches the model's token limit (~200K for Sonnet).  After compaction the
detailed conversation history is replaced by a ~27K-token summary, causing
the silent context loss users see as memory failures in long sessions.

Root cause identified from production logs for session 93ecf7c9:
- T6 CLI session: 233KB / ~207K tokens (near Sonnet limit)
- T7 CLI compacted session -> ~167KB / ~47K tokens (PreCompact hook missed)
- T12 second compaction -> ~176KB / ~27K tokens (just system prompt + summary)
- T14-T21: cache_read=26714 constantly -- only system prompt visible to Claude

The same stripping we already apply to our transcript (stale thinking blocks,
progress/metadata entries) now also runs on the CLI native session file.  At
~2x the size of the stripped transcript, unstripped sessions routinely hit the
compaction threshold within 6-10 turns of a heavy Opus/thinking session.
After stripping:
- same-pod turns reuse the stripped local file (no compaction trigger)
- cross-pod turns restore the stripped GCS file (same benefit)
2026-04-15 23:19:12 +07:00
majdyz
4efa1c4310 fix(copilot): set session_id on mode-switch T1 to enable --resume on subsequent turns
When a user switches from baseline (fast) mode to SDK (extended_thinking)
mode mid-session, the first SDK turn has has_history=True (prior baseline
messages in DB) but no CLI session file in storage.

The old code gated session_id on `not has_history`, so mode-switch T1
never received a session_id — the CLI generated a random ID that wasn't
uploaded under the expected key.  Every subsequent SDK turn would fail to
restore the CLI session and run without --resume, injecting the full
compressed history on each turn, causing model confusion.

Fix: set session_id whenever not using --resume (the `else` branch),
covering T1 fresh, mode-switch T1, and T2+ fallback turns.  The retry
path is updated to use `"session_id" in sdk_options_kwargs` as the
discriminator (instead of `not has_history`) so mode-switch T1 retries
also keep the session_id while T2+ retries (where T1 restored a session
file via restore_cli_session) still remove it to avoid "Session ID
already in use".
2026-04-15 23:19:11 +07:00
Nicholas Tindle
ab3221a251 feat(backend): MemoryEnvelope metadata model, scoped retrieval, and memory hardening (#12765)
### Why / What / How

**Why:** CoPilot's Graphiti memory system needed structured metadata to
distinguish memory types (rules, procedures, facts, preferences),
support scoped retrieval, enable targeted deletion, and track memory
costs under the AutoPilot billing account separately from the platform.

**What:** Adds the MemoryEnvelope metadata model, structured
rule/procedure memory types, a derived-finding lane for
assistant-distilled knowledge, two-step forget tools, scope-aware
retrieval filtering, AutoPilot-dedicated API key routing, and several
reliability fixes (streaming socket leaks, event-loop-scoped caches,
ingestion hardening).

**How:** MemoryEnvelope wraps every stored episode with typed metadata
(source_kind, memory_kind, scope, status, confidence) serialized as
JSON. Retrieval filters by scope at the context layer. The forget flow
uses a search-then-confirm two-step pattern. Ingestion queues and client
caches are scoped per event loop via WeakKeyDictionary to prevent
cross-loop RuntimeErrors in multi-worker deployments. API key resolution
falls back to AutoPilot-dedicated keys (CHAT_API_KEY,
CHAT_OPENAI_API_KEY) before platform-wide keys.

### Changes 🏗️

**New: MemoryEnvelope metadata model** (`memory_model.py`)
- Typed memory categories: fact, preference, rule, finding, plan, event,
procedure
- Source tracking: user_asserted, assistant_derived, tool_observed
- Scope namespacing: `real:global`, `project:<name>`, `book:<title>`,
`session:<id>`
- Status lifecycle: active, tentative, superseded, contradicted
- Structured `RuleMemory` and `ProcedureMemory` models for complex
instructions

**New: Targeted forget tools** (`graphiti_forget.py`)
- `memory_forget_search`: returns candidate facts with UUIDs for user
confirmation
- `memory_forget_confirm`: deletes specific edges by UUID after
confirmation

**New: Architecture test** (`architecture_test.py`)
- Validates no new `@cached(...)` usage around event-loop-bound async
clients
- Allowlists pre-existing violations for future cleanup

**Enhanced: memory_store tool** (`graphiti_store.py`)
- Accepts MemoryEnvelope metadata fields (source_kind, scope,
memory_kind, rule, procedure)
- Wraps content in MemoryEnvelope before ingestion

**Enhanced: memory_search tool** (`graphiti_search.py`)
- Scope-aware retrieval with hard filtering on group_id

**Enhanced: Ingestion pipeline** (`ingest.py`)
- Derived-finding lane: distills substantive assistant responses into
tentative findings
- Event-loop-scoped queues and workers via WeakKeyDictionary (fixes
multi-worker RuntimeError)
- Improved error handling and dropped-episode reporting

**Enhanced: Client cache** (`client.py`)
- Per-loop client cache and lock via WeakKeyDictionary (fixes "Future
attached to a different loop")

**Enhanced: Warm context** (`context.py`)
- Filters out non-global-scope episodes from warm context

**Fix: Streaming socket leak** (`baseline/service.py`)
- try/finally around async stream iteration to release httpx connections
on early exit

**Config: AutoPilot key routing** (`config.py`, `.env.default`)
- LLM key fallback: GRAPHITI_LLM_API_KEY → CHAT_API_KEY →
OPEN_ROUTER_API_KEY
- Embedder key fallback: GRAPHITI_EMBEDDER_API_KEY → CHAT_OPENAI_API_KEY
→ OPENAI_API_KEY
- Backwards-compatible: existing behavior unchanged until new keys are
provisioned

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] `poetry run pytest backend/copilot/graphiti/config_test.py` — 16
tests pass (key fallback priority)
- [x] `poetry run pytest backend/copilot/tools/graphiti_store_test.py` —
store envelope tests pass
- [x] `poetry run pytest backend/copilot/graphiti/ingest_test.py` —
ingestion tests pass
- [x] `poetry run pytest backend/util/architecture_test.py` — structural
validation passes
  - [x] Verify memory store/retrieve/forget cycle via copilot chat
- [x] Run AgentProbe multi-session memory benchmark (31 scenarios x3
repeats)
- [x] Confirm no CLOSE_WAIT socket accumulation under sustained
streaming load
- [x] Verify multi-worker deployment doesn't produce loop-binding errors

#### For configuration changes:
- [x] `.env.default` is updated or already compatible with my changes
- [x] `docker-compose.yml` is updated or already compatible with my
changes
- Configuration changes:
- New optional env var `CHAT_OPENAI_API_KEY` — AutoPilot-dedicated
OpenAI key for Graphiti embeddings (falls back to `OPENAI_API_KEY` if
not set)
- `CHAT_API_KEY` now used as first fallback for Graphiti LLM calls (was
`OPEN_ROUTER_API_KEY`)
- Infra action needed: add `CHAT_OPENAI_API_KEY` sealed secret in
`autogpt-shared-config` values (dev + prod)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> **Medium Risk**
> Touches Graphiti memory ingestion/retrieval and introduces hard-delete
capabilities plus event-loop–scoped caching/queues; failures could
affect memory correctness or delete the wrong edges. Also changes
streaming resource cleanup and key routing, which could surface as
connection or billing/cost attribution issues if misconfigured.
> 
> **Overview**
> **Graphiti memory is upgraded from plain text episodes to a structured
JSON `MemoryEnvelope`.** `memory_store` now wraps content with typed
metadata (source, kind, scope, status) and optional structured
`rule`/`procedure` payloads, and ingestion supports JSON episodes.
> 
> **Memory retrieval and lifecycle controls are expanded.**
`memory_search` adds optional scope hard-filtering to prevent
cross-scope leakage, warm-context formatting drops non-global scoped
episodes (and avoids empty wrappers), and new two-step tools
(`memory_forget_search` → `memory_forget_confirm`) enable targeted soft-
or hard-deletion of specific graph edges by UUID.
> 
> **Reliability and multi-worker safety improvements.** Graphiti client
caching and ingestion worker registries are now per-event-loop (avoiding
cross-loop `Future` errors), streaming chat completions explicitly close
async streams to prevent `CLOSE_WAIT` socket leaks, warm-context is
injected into the first user message to keep the system prompt
cacheable, and a new `architecture_test.py` blocks future process-wide
caching of event-loop–bound async clients. Config updates route Graphiti
LLM/embedder keys to AutoPilot-specific env vars first, and OpenAPI
schema exports include the new memory response types.
> 
> <sup>Reviewed by [Cursor Bugbot](https://cursor.com/bugbot) for commit
5fb4bd0a43. Bugbot is set up for automated
code reviews on this repo. Configure
[here](https://www.cursor.com/dashboard/bugbot).</sup>
<!-- /CURSOR_SUMMARY -->

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
2026-04-15 09:40:43 -05:00
Zamil Majdy
b2f7faabc7 fix(backend/copilot): pre-create assistant msg before first yield to prevent last_role=tool (#12797)
## Changes

**Root cause:** When a copilot session ends with a tool result as the
last saved message (`last_role=tool`), the next assistant response is
never persisted. This happens when:

1. An intermediate flush saves the session with `last_role=tool` (after
a tool call completes)
2. The Claude Agent SDK generates a text response for the next turn
3. The client disconnects (`GeneratorExit`) at the `yield
StreamStartStep` — the very first yield of the new turn
4. `_dispatch_response(StreamTextDelta)` is never called, so the
assistant message is never appended to `ctx.session.messages`
5. The session `finally` block persists the session still with
`last_role=tool`

**Fix:** In `_run_stream_attempt`, after `convert_message()` returns the
full list of adapter responses but *before* entering the yield loop,
pre-create the assistant message placeholder in `ctx.session.messages`
when:
- `acc.has_tool_results` is True (there are pending tool results)
- `acc.has_appended_assistant` is True (at least one prior message
exists)
- A `StreamTextDelta` is present in the batch (confirms this is a text
response turn)

This ensures that even if `GeneratorExit` fires at the first `yield`,
the placeholder assistant message is already in the session and will be
persisted by the `finally` block.

**Tests:** Added `session_persistence_test.py` with 7 unit tests
covering the pre-create condition logic and delta accumulation behavior.

**Confirmed:** Langfuse trace `e57ebd26` for session
`465bf5cf-7219-4313-a1f6-5194d2a44ff8` showed the final assistant
response was logged at 13:06:49 but never reached DB — session had 51
messages with `last_role=tool`.

## Checklist

- [x] My code follows the code style of this project
- [x] I have performed a self-review of my own code
- [x] I have commented my code, particularly in hard-to-understand areas
- [x] I have made corresponding changes to the documentation (N/A)
- [x] My changes generate no new warnings (Pyright warnings are
pre-existing)
- [x] I have added tests that prove my fix is effective
- [x] New and existing unit tests pass locally with my changes

---------

Co-authored-by: Zamil Majdy <zamilmajdy@gmail.com>
2026-04-15 21:09:44 +07:00
Zamil Majdy
c9fa6bcd62 fix(backend/copilot): make system prompt fully static for cross-user prompt caching (#12790)
### Why / What / How

**Why:** Anthropic prompt caching keys on exact system prompt content.
Two sources of per-session dynamic data were leaking into the system
prompt, making it unique per session/user — causing a full 28K-token
cache write (~$0.10 on Sonnet) on *every* first message for *every*
session instead of once globally per model.

**What:**
1. `get_sdk_supplement` was embedding the session-specific working
directory (`/tmp/copilot-<uuid>`) in the system prompt text. Every
session has a different UUID, making every session's system prompt
unique, blocking cross-session cache hits.
2. Graphiti `warm_ctx` (user-personalised memory facts fetched on the
first turn) was appended directly to the system prompt, making it unique
per user per query.

**How:**
- `get_sdk_supplement` now uses the constant placeholder
`/tmp/copilot-<session-id>` in the supplement text and memoizes the
result. The actual `cwd` is still passed to `ClaudeAgentOptions.cwd` so
the CLI subprocess uses the correct session directory.
- `warm_ctx` is now injected into the first user message as a trusted
`<memory_context>` block (prepended before `inject_user_context` runs),
following the same pattern already used for business understanding. It
is persisted to DB and replayed correctly on `--resume`.
- `sanitize_user_supplied_context` now also strips user-supplied
`<memory_context>` tags, preventing context-spoofing via the new tag.

After this change the system prompt is byte-for-byte identical across
all users and sessions for a given model.

### Changes 🏗️

- `backend/copilot/prompting.py`: `get_sdk_supplement` ignores `cwd` and
uses a constant working-directory placeholder; result is memoized in
`_LOCAL_STORAGE_SUPPLEMENT`.
- `backend/copilot/sdk/service.py`: `warm_ctx` is saved to a local
variable instead of appended to `system_prompt`; on the first turn it is
prepended to `current_message` as a `<memory_context>` block before
`inject_user_context` is called.
- `backend/copilot/service.py`: `sanitize_user_supplied_context`
extended to strip `<memory_context>` blocks alongside `<user_context>`.

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] `poetry run pytest backend/copilot/prompting_test.py
backend/copilot/prompt_cache_test.py` — all passed

#### For configuration changes:

- [x] `.env.default` is updated or already compatible with my changes
- [x] `docker-compose.yml` is updated or already compatible with my
changes
- [x] I have included a list of my configuration changes in the PR
description (under **Changes**)

---------

Co-authored-by: Zamil Majdy <zamilmajdy@gmail.com>
2026-04-15 20:40:24 +07:00
Krzysztof Czerwinski
c955b3901c fix(frontend/copilot): load older chat messages reliably and preserve scrollback across turns (#12792)
### Why / What / How

Fixes two SECRT-2226 bugs in copilot chat pagination.

**Bug 1 — can't load older messages when the newest page fits on
screen.** The `IntersectionObserver` in `LoadMoreSentinel` bailed when
`scrollHeight <= clientHeight`, which happens routinely once reasoning +
tool groups collapse. With no scrollbar and no button, users were stuck.
Fix: remove the guard, cap auto-fill at 3 non-scrollable rounds (keeps
the original anti-loop intent), and add a manual "Load older messages"
button as the always-available escape hatch.

**Bug 2 — older loaded pages vanish after a new turn, then reloading
them produces duplicates.** After each stream `useCopilotStream`
invalidates the session query; the refetch returns a shifted
`oldest_sequence`, which `useLoadMoreMessages` used as a signal to wipe
`olderRawMessages` and reset the local cursor. Scroll-back history was
lost on every turn, and the next load fetched a page that overlapped
with AI SDK's retained `currentMessages` — the "loops" users reported.
Fix: once any older page is loaded, preserve `olderRawMessages` and the
local cursor across same-session refetches. Only reset on session
change. The gap between the new initial window and older pages is
covered by AI SDK's retained state.

### Changes 🏗️

- `ChatMessagesContainer.tsx`: drop the scrollability guard; add
`MAX_AUTO_FILL_ROUNDS = 3` counter; add "Load older messages" button
(`ghost`/`small`); distinguish observer-triggered vs. button-triggered
loads so the button bypasses the cap; export `LoadMoreSentinel` for
testing.
- `useLoadMoreMessages.ts`: remove the wipe-and-reset branch on
`initialOldestSequence` change; preserve local state mid-session; still
mirror parent's cursor while no older page is loaded.
- New integration test `__tests__/LoadMoreSentinel.test.tsx`.

No backend changes.

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] Short/collapsed newest page: "Load older messages" button loads
older pages, preserves scroll
- [x] Full-viewport newest page: scroll-to-top auto-pagination still
works (no regression)
- [x] `has_more_messages=false` hides the button; `isLoadingMore=true`
shows spinner instead
- [x] Bug 2 reproduced locally with temporary `limit=5`: before fix
older page vanished and next load duplicated AI SDK messages; after fix
older page stays and next load fetches cleanly further back
- [x] `pnpm format`, `pnpm lint`, `pnpm types`, `pnpm test:unit` all
pass (1208/1208)

#### For configuration changes:

- [x] `.env.default` is updated or already compatible with my changes
- [x] `docker-compose.yml` is updated or already compatible with my
changes
- [x] I have included a list of my configuration changes in the PR
description (under **Changes**) — N/A

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-15 13:14:59 +00:00
Zamil Majdy
56864aea87 fix(copilot/frontend): align ModelToggleButton styling + add execution ID filter to platform cost page (#12793)
## Why

Two fixes bundled together:

1. **ModelToggleButton styling**: after merging the ModelToggleButton
feature, the "Standard" state was invisible — no background, no label —
while "Advanced" had a colored pill. This was inconsistent with
`ModeToggleButton` where both states (Fast / Thinking) always show a
colored background + label.

2. **Execution ID filter on platform cost admin page**: admins needed to
look up cost rows for a specific agent run but had no way to filter by
`graph_exec_id`. All other identifiers (user, model, provider, block,
tracking type) were already filterable.

## What

- **ModelToggleButton**: inactive (Standard) state now uses
`bg-neutral-100 text-neutral-700 hover:bg-neutral-200` (same palette as
ModeToggleButton inactive), always shows the "Standard" label.
- **Platform cost admin page**: added `graph_exec_id` query filter
across the full stack — backend service functions, FastAPI route
handlers, generated TypeScript params types, `usePlatformCostContent`
hook, and the filter UI in `PlatformCostContent`.

## How

### ModelToggleButton

Changed the inactive-state class from hover-only transparent to
always-visible neutral background, and added the "Standard" text label
(was empty before — only the CPU icon showed).

### Execution ID filter

Added `graph_exec_id: str | None = None` parameter to:
- `_build_prisma_where` — applies `where["graphExecId"] = graph_exec_id`
- `get_platform_cost_dashboard`, `get_platform_cost_logs`,
`get_platform_cost_logs_for_export`
- All three FastAPI route handlers (`/dashboard`, `/logs`,
`/logs/export`)
- Generated TypeScript params types
- `usePlatformCostContent`: new `executionIDInput` /
`setExecutionIDInput` state, wired into `filterParams`, `handleFilter`,
and `handleClear`
- `PlatformCostContent`: new Execution ID input field in the filter bar

## Changes

- [x] I have explained why I made the changes, not just what I changed
- [x] There are no unrelated changes in this PR
- [x] I have run the relevant linters and tests before submitting

---------

Co-authored-by: Zamil Majdy <zamilmajdy@gmail.com>
2026-04-15 20:20:55 +07:00
Zamil Majdy
d23ca824ad fix(copilot): set session_id on mode-switch T1 to enable --resume on subsequent SDK turns (#12795)
## Why

When a user switches from **baseline** (fast) mode to **SDK**
(extended_thinking) mode mid-session, every subsequent SDK turn started
fresh with no memory of prior conversation.

Root cause: two complementary bugs on mode-switch T1 (first SDK turn
after baseline turns):
1. `session_id` was gated on `not has_history`. On mode-switch T1,
`has_history=True` (prior baseline turns in DB) so no `session_id` was
set. The CLI generated a random ID and could not upload the session file
under a predictable path → `--resume` failed on every following SDK
turn.
2. Even if `session_id` were set, the upload guard `(not has_history or
state.use_resume)` would block the session file upload on mode-switch T1
(`has_history=True`, `use_resume=False`), so the next turn still cannot
`--resume`.

Together these caused every SDK turn to re-inject the full compressed
history, causing model confusion (proactive tool calls, forgetting
context) observed in session `8237a27b-45d0-4688-af20-c185379e926f`.

## What

- **`service.py`**: Change `elif not has_history:` → `else:` for the
`session_id` assignment — set it whenever `--resume` is not active.
Covers T1 fresh, mode-switch T1 (`has_history=True` but no CLI session
exists), and T2+ fallback turns where restore failed.
- **`service.py` retry path**: Replace `not has_history` with
`"session_id" in sdk_options_kwargs` as the discriminator, so
mode-switch T1 retries also keep `session_id` while T2+ retries (where
`restore_cli_session` put a file on disk) correctly remove it to avoid
"Session ID already in use".
- **`service.py` upload guard**: Remove `and not skip_transcript_upload`
and `and (not has_history or state.use_resume)` from the
`upload_cli_session` guard. The CLI session file is independent of the
JSONL transcript; and upload must run on mode-switch T1 so the next turn
can `--resume`. `upload_cli_session` silently skips when the file is
absent, so unconditional upload is always safe.

## How

| Scenario | Before | After |
|---|---|---|
| T1 fresh (`has_history=False`) | `session_id` set ✓ | `session_id` set
✓ |
| Mode-switch T1 (`has_history=True`, no CLI session) |  not set —
**bug** | `session_id` set ✓ |
| T2+ with `--resume` | `resume` set ✓ | `resume` set ✓ |
| T2+ retry after `--resume` failed | `session_id` removed ✓ |
`session_id` removed ✓ |
| Mode-switch T1 retry | `session_id` removed  | `session_id` kept ✓ |
| Upload on mode-switch T1 |  blocked by guard — **bug** | uploaded ✓ |

7 new unit tests in `TestSdkSessionIdSelection` document all session_id
cases.
6 new tests in `mode_switch_context_test.py` cover transcript bridging
for both fast→SDK and SDK→fast switches.

## Checklist

- [x] I have read the contributing guidelines
- [x] My changes are covered by tests
- [x] `poetry run format` passes

---------

Co-authored-by: Zamil Majdy <zamilmajdy@gmail.com>
2026-04-15 19:03:18 +07:00
Zamil Majdy
227c60abd3 fix(backend/copilot): idempotency guard + frontend dedup fix for duplicate messages (#12788)
## Why

After merging #12782 to dev, a k8s rolling deployment triggered
infrastructure-level POST retries — nginx detected the old pod's
connection reset mid-stream and resent the same POST to a new pod. Both
pods independently saved the user message and ran the executor,
producing duplicate entries in the DB (seq 159, 161, 163) and a
duplicate response in the chat. The model saw the same question 3× in
its context window and spent its response commenting on that instead of
answering.

Two compounding issues:
1. **No backend idempotency**: `append_and_save_message` saves
unconditionally — k8s/nginx retries silently produce duplicate turns.
2. **Frontend dedup cleared after success**:
`lastSubmittedMsgRef.current = null` after every completed turn wipes
the dedup guard, so any rapid re-submit of the same text (from a stalled
UI or user double-click) slips through.

## What

**Backend** — Redis idempotency gate in `stream_chat_post`:
- Before saving the user message, compute `sha256(session_id +
message)[:16]` and `SET NX ex=30` in Redis
- If key already exists → duplicate: return empty SSE (`StreamFinish +
[DONE]`) immediately, skip save + executor enqueue
- User messages only (`is_user_message=True`); system/assistant messages
bypass the check

**Frontend** — Keep `lastSubmittedMsgRef` populated after success:
- Remove `lastSubmittedMsgRef.current = null` on stream complete
- `getSendSuppressionReason` already has a two-condition check: `ref ===
text AND lastUserMsg === text` — so legitimate re-asks (after a
different question was answered) still work; only rapid re-sends of the
exact same text while it's still the last user message are blocked

## How

- 30 s Redis TTL covers infrastructure retry windows (k8s SIGTERM →
connection reset → ingress retry typically < 5 s)
- Empty SSE response is well-formed (StreamFinish + [DONE]) — frontend
AI SDK marks the turn complete without rendering a ghost message
- Frontend ref kept live means: submit "foo" → success → submit "foo"
again instantly → suppressed. Submit "foo" → success → submit "bar" →
proceeds (different text updates the ref).

## Tests

- 3 new backend route tests: duplicate blocked, first POST proceeds,
non-user messages bypass
- 5 new frontend `getSendSuppressionReason` unit tests: fresh ref,
reconnecting, duplicate suppressed, different-turn re-ask allowed,
different text allowed

## Checklist

- [x] I have read the [AutoGPT Contributing
Guide](https://github.com/Significant-Gravitas/AutoGPT/blob/master/CONTRIBUTING.md)
- [x] I have performed a self-review of my code
- [x] I have added tests that prove the fix is effective
- [x] I have run `poetry run format` and `pnpm format` + `pnpm lint`
2026-04-15 18:54:59 +07:00
Ubbe
0284614df0 fix(copilot): abort SSE stream and disconnect backend listeners on session switch (#12766)
## Summary

Fixes stream disconnection bugs where the UI shows "running" with no
output when users switch between copilot chat sessions. The root cause
is that the old SSE fetch is not aborted and backend XREAD listeners
keep running until timeout when switching sessions.

### Changes

**Frontend (`useCopilotStream.ts`, `helpers.ts`)**
- Call `sdkStop()` on session switch to abort the in-flight SSE fetch
from the old session's transport
- Fire-and-forget `DELETE` to new backend disconnect endpoint so
server-side listeners release immediately
- Store `resumeStream` and `sdkStop` in refs to fix stale closure bugs
in:
- Wake re-sync visibility handler (could call stale `resumeStream` after
tab sleep)
  - Reconnect timer callback (could target wrong session's transport)
- Resume effect (captured stale `resumeStream` during rapid session
switches)

**Backend (`stream_registry.py`, `routes.py`)**
- Add `disconnect_all_listeners(session_id)` to stream registry —
iterates active listener tasks, cancels any matching the session
- Add `DELETE /sessions/{session_id}/stream` endpoint — auth-protected,
calls `disconnect_all_listeners`, returns 204

### Why

Reported by multiple team members: when using Autopilot for anything
serious, the frontend loses the SSE connection — particularly when
switching between conversations. The backend completes fine (refreshing
shows full output), but the UI gets stuck showing "running". This is the
worst UX bug we have right now because real users will never know to
refresh.

### How to test

1. Start a long-running autopilot task (e.g., "build a snake game")
2. While it's streaming, switch to a different chat session
3. Switch back — the UI should correctly show the completed output or
resume the stream
4. Verify no "stuck running" state

## Test plan

- [ ] Manual: switch sessions during active stream — no stuck "running"
state
- [ ] Manual: background tab for >30s during stream, return — wake
re-sync works
- [ ] Manual: trigger reconnect (kill network briefly) — reconnects to
correct session
- [ ] Verify: `pnpm lint`, `pnpm types`, `poetry run lint` all pass

🤖 Generated with [Claude Code](https://claude.com/claude-code)

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: majdyz <zamil.majdy@agpt.co>
2026-04-15 09:50:19 +00:00
Zamil Majdy
f835674498 feat(copilot): standard/advanced model toggle with Opus rate-limit multiplier (#12786)
## Why

Users have different task complexity needs. Sonnet is fast and cheap for
most queries; Opus is more capable for hard reasoning tasks. Exposing
this as a simple toggle gives users control without requiring
infrastructure complexity.

Opus costs 5× more than Sonnet per Anthropic pricing ($15/$75 vs $3/$15
per M tokens). Rather than adding a separate entitlement gate, the
rate-limit multiplier (5×) ensures Opus turns deplete the daily/weekly
quota proportionally faster — users self-limit via their existing
budget.

## What

- **Standard/Advanced model toggle** in the chat input toolbar (sky-blue
star icon, label only when active — matches the simulation
DryRunToggleButton pattern but visually distinct)
- **`CopilotLlmModel = Literal["standard", "advanced"]`** —
model-agnostic tier names (not tied to Anthropic model names)
- **Backend model resolution**: `"advanced"` → `claude-opus-4-6`,
`"standard"` → `config.model` (currently Sonnet)
- **Rate-limit multiplier**: Opus turns count as 5× in Redis token
counters (daily + weekly limits). Does **not** affect `PlatformCostLog`
or `cost_usd` — those use real API-reported values
- **localStorage persistence** via `Key.COPILOT_MODEL` so preference
survives page refresh
- **`claude_agent_max_budget_usd`** reduced from $15 to $10

## How

### Backend
- `CopilotLlmModel` type added to `config.py`, imported in
routes/executor/service
- `stream_chat_completion_sdk` accepts `model: CopilotLlmModel | None`
- Model tier resolved early in the SDK path; `_normalize_model_name`
strips the OpenRouter provider prefix
- `model_cost_multiplier` (1.0 or 5.0) computed from final resolved
model name, passed to `persist_and_record_usage` → `record_token_usage`
(Redis only)
- No separate LD flag needed — rate limit is the gate

### Frontend
- `ModelToggleButton` component: sky-blue, star icon, "Advanced" label
when active
- `copilotModel` state in `useCopilotUIStore` with localStorage
hydration
- `copilotModelRef` pattern in `useCopilotStream` (avoids recreating
`DefaultChatTransport`)
- Toggle gated behind `showModeToggle && !isStreaming` in `ChatInput`

## Checklist
- [x] Tests added/updated (ModelToggleButton.test.tsx,
service_helpers_test.py, token_tracking_test.py)
- [x] Rate-limit multiplier only affects Redis counters, not cost
tracking
- [x] No new LD flag needed
2026-04-15 15:37:11 +07:00
Zamil Majdy
da18f372f7 feat(backend/copilot): add for_agent_generation flag to find_block (#12787)
## Why
When the agent generator LLM builds a graph, it may need to look up
schema details for graph-only blocks like `AgentInputBlock`,
`AgentOutputBlock`, or `OrchestratorBlock`. These blocks are correctly
hidden from regular CoPilot `find_block` results (they can't run
standalone), but that same filter was also preventing the LLM from
discovering them when composing an agent graph.

## What
Added a `for_agent_generation: bool = False` parameter to
`FindBlockTool`.

## How
- `for_agent_generation=false` (default): existing behaviour unchanged —
graph-only blocks are filtered from both UUID lookups and text search
results.
- `for_agent_generation=true`: bypasses `COPILOT_EXCLUDED_BLOCK_TYPES` /
`COPILOT_EXCLUDED_BLOCK_IDS` so the LLM can find and inspect schemas for
INPUT, OUTPUT, ORCHESTRATOR, WEBHOOK, etc. blocks when building agent
JSON.
- MCP_TOOL blocks are still excluded even with
`for_agent_generation=true` (they go through `run_mcp_tool`, not
`find_block`).

## Checklist
- [x] No new dependencies
- [x] Backward compatible (default `false` preserves existing behaviour)
- [x] No frontend changes
2026-04-15 14:57:17 +07:00
Zamil Majdy
d82ecac363 fix(backend/copilot): null-safe token accumulation for OpenRouter null cache fields (#12789)
## Why
OpenRouter occasionally returns `null` (not `0`) for
`cache_read_input_tokens` and `cache_creation_input_tokens` on the
initial streaming event, before real token counts are available.
Python's `dict.get(key, 0)` only falls back to `0` when the key is
**missing** — when the key exists with a `null` value, `.get(key, 0)`
returns `None`. This causes `TypeError: unsupported operand type(s) for
+=: 'int' and 'NoneType'` in the usage accumulator on the first
streaming chunk from OpenRouter models.

## What
- Replace `.get(key, 0)` with `.get(key) or 0` for all four token fields
in `_run_stream_attempt`
- Add `TestTokenUsageNullSafety` unit tests in `service_helpers_test.py`

## How
Minimal targeted fix — only the four `+=` accumulation lines changed. No
behaviour change for Anthropic-native models (they never emit null
values).

## Checklist
- [x] Tests cover null event, real event, absent keys, and multi-turn
accumulation
- [x] No behaviour change for Anthropic-native models
- [x] No API changes
2026-04-15 14:50:34 +07:00
Zamil Majdy
8a2e2365f7 fix(backend/executor): charge per LLM iteration and per tool call in OrchestratorBlock (#12735)
### Why / What / How

**Why:** The OrchestratorBlock in agent mode makes multiple LLM calls in
a single node execution (one per iteration of the tool-calling loop),
but the executor was only charging the user once per run via
`_charge_usage`. Tools spawned by the orchestrator also bypassed
`_charge_usage` entirely — they execute via `on_node_execution()`
directly without going through the main execution queue, producing free
internal block executions.

**What:**
1. Charge `base_cost * (llm_call_count - 1)` extra credits after the
orchestrator block completes — covers the additional iterations beyond
the first (which is already paid for upfront).
2. Charge user credits for tools executed inside the orchestrator, the
same way queue-driven node executions are charged.

**How:**

**1. Per-iteration LLM charging**
- New `Block.extra_runtime_cost(execution_stats)` virtual method
(default returns `0`)
- `OrchestratorBlock` overrides it to return `max(0, llm_call_count -
1)`
- New `resolve_block_cost` free function in `billing.py` centralises the
block-lookup + cost-calculation pattern (used by both `charge_usage` and
`charge_extra_runtime_cost`)
- New `billing.charge_extra_runtime_cost(node_exec, extra_count)`
function that debits `base_cost * min(extra_count,
_MAX_EXTRA_RUNTIME_COST)` via `spend_credits()`, running synchronously
in a thread-pool worker
- After `_on_node_execution` completes with COMPLETED status,
`on_node_execution` calls `charge_extra_runtime_cost` if
`extra_runtime_cost > 0` and not a dry run
- `InsufficientBalanceError` from post-hoc charging is treated as a
billing leak: logged at ERROR with `billing_leak: True` structured
fields, user is notified via `_handle_insufficient_funds_notif`, but the
run status stays COMPLETED (work already done)

**2. Tool execution charging**
- New public async `ExecutionProcessor.charge_node_usage(node_exec)`
wrapper around `charge_usage` (with `execution_count=0` to avoid
inflating execution-tier counters); also calls `_handle_low_balance`
internally
- `OrchestratorBlock._execute_single_tool_with_manager` calls
`charge_node_usage` after successful tool execution (skipped for dry
runs and failed/cancelled tool runs)
- Tool cost is added to the orchestrator's `extra_cost` so it shows up
in graph stats display
- `InsufficientBalanceError` from tool charging is re-raised (not
downgraded to a tool error) in all three execution paths:
`_execute_single_tool_with_manager`, `_agent_mode_tool_executor`, and
`_execute_tools_sdk_mode`

**3. Billing module extraction**
- All billing logic extracted from `ExecutionProcessor` into
`backend/executor/billing.py` as free functions — keeps `manager.py` and
`service.py` focused on orchestration
- `ExecutionProcessor` retains thin delegation methods
(`charge_node_usage`, `charge_extra_runtime_cost`) for backward
compatibility with blocks that call them

**4. Structured error signalling**
- Tool error detection replaced brittle `text.startswith("Tool execution
failed:")` string check with a structured `_is_error` boolean field on
the tool response dict

### Changes

- `backend/blocks/_base.py`: Add
`Block.extra_runtime_cost(execution_stats) -> int` virtual method
(default `0`)
- `backend/blocks/orchestrator.py`: Override `extra_runtime_cost`; add
tool charging in `_execute_single_tool_with_manager`; add
`InsufficientBalanceError` re-raise carve-outs in all three execution
paths; replace string-prefix error detection with `_is_error` flag
- `backend/executor/billing.py` (new): Free functions
`resolve_block_cost`, `charge_usage`, `charge_extra_runtime_cost`,
`charge_node_usage`, `handle_post_execution_billing`,
`clear_insufficient_funds_notifications` — extracted from
`ExecutionProcessor`
- `backend/executor/manager.py`: Thin delegation to `billing.*`; remove
~500 lines of billing methods from `ExecutionProcessor`
- `backend/data/credit.py`: Update lazy import source from `manager` to
`billing`
- `backend/blocks/test/test_orchestrator.py`: Add `charge_node_usage`
mock + assertion
- `backend/blocks/test/test_orchestrator_dynamic_fields.py`: Add
`charge_node_usage` async mock
- `backend/blocks/test/test_orchestrator_responses_api.py`: Add
`charge_node_usage` async mock
- `backend/blocks/test/test_orchestrator_per_iteration_cost.py`: New
test file — `extra_runtime_cost` hook, `charge_extra_runtime_cost` math
(positive/zero/negative/capped/zero-cost/block-not-found/IBE),
`charge_node_usage` delegation, `on_node_execution` gate conditions
(COMPLETED/FAILED/zero-charges/dry-run/IBE), tool charging guards
(dry-run/failed/cancelled/IBE propagation)

### Checklist

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [ ] I have tested my changes according to the test plan:
- [ ] Run `poetry run pytest
backend/blocks/test/test_orchestrator_per_iteration_cost.py`
- [ ] Verify on dev: an OrchestratorBlock run with
`agent_mode_max_iterations=5` and 5 actual iterations is charged 5x the
base cost
  - [ ] Verify tool executions inside the orchestrator are charged

🤖 Generated with [Claude Code](https://claude.com/claude-code)

---------

Co-authored-by: majdyz <majdy.zamil@gmail.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: majdyz <majdyz@users.noreply.github.com>
2026-04-15 13:46:08 +07:00
Zamil Majdy
55869d3c75 fix(backend/copilot): robust context fallback — upload gate, gap-fill, token-budget compression (#12782)
## Why

During a live production session, the copilot lost all conversation
context mid-session. The model stated \"I don't see any implementation
plan in our conversation\" despite 9 prior turns of context. Three
compounding bugs:

**Bug 1 — Self-perpetuating upload gate:** When `restore_cli_session`
fails on a T2+ turn, `state.use_resume=False`. The old gate `and (not
has_history or state.use_resume)` then skips the CLI session upload —
even though the T1 file may exist. Each turn without `use_resume` skips
upload → next turn can't restore → also skips → etc.

**Bug 2 — Blunt message-count cap on retries:** On `prompt-too-long`,
`_reduce_context` retried 3× but rebuilt the same oversized query each
time (transcript was empty, so all 3 attempts were identical). The
`max_fallback_messages` count-cap was a blunt instrument — it threw away
middle turns blindly instead of letting the compressor summarize
intelligently.

**Bug 3 — Gap-empty path returned zero context:** When a transcript
exists but no `--resume` (CLI session unavailable), and the gap is empty
(transcript is current), the code fell through to `return
current_message, False` — the model got no history at all.

## What

1. **Remove upload gate** — upload is attempted after every successful
turn; `upload_cli_session` silently skips when the file is absent.

2. **`transcript_msg_count` set on `cli_restored=False`** — enables the
gap path on the very next turn without waiting for a full upload cycle.

3. **Token-budget compression instead of message-count cap** —
`_reduce_context` now returns `target_tokens` (50K → 15K across
retries). `compress_context` decides what to drop via LLM summarize →
content truncate → middle-out delete → first/last trim. More context
preserved at any budget vs. blindly slicing the list.

4. **Fix gap-empty case** — when transcript is current but `--resume`
unavailable, fall through to full-session compression with the token
budget instead of returning no context.

5. **Transcript seeding after fallback** — after `use_resume=False` with
no stored transcript, compress DB messages to 30K tokens and serialise
as JSONL into `transcript_builder`. Next turn uses the gap path (inject
only new messages) instead of re-compressing full history. Only fires
once per broken session (`not transcript_content` guard).

6. **Seeding guard** — seeding skips when `skip_transcript_upload=True`
(avoids wasted compression work when the result won't be saved).

7. **Structured logging** — INFO/WARNING at every branch of
`_build_query_message` with path variables, context_bytes, compression
results.

## How

**Upload gate** (`sdk/service.py` finally-block): removed `and (not
has_history or state.use_resume)`; added INFO log showing
`use_resume`/`has_history` before upload.

**`transcript_msg_count`**: set from `dl.message_count` in the
`cli_restored=False` branch.

**`_build_query_message`**: `max_fallback_messages: int | None` →
`target_tokens: int | None`; gap-empty case falls through to
full-session compression rather than returning bare message.

**`_reduce_context`**: `_FALLBACK_MSG_LIMITS` → `_RETRY_TARGET_TOKENS =
(50_000, 15_000)`; returns `ReducedContext.target_tokens`.

**`_compress_messages` / `_run_compression`**: both now accept
`target_tokens: int | None` and thread it through to `compress_context`.

**Seeding block**: added `not skip_transcript_upload` guard; uses
`_SEED_TARGET_TOKENS = 30_000` so the seeded JSONL is always compact
enough to pass `validate_transcript`.

## Checklist

- [x] `poetry run format` passes
- [x] No new lint errors introduced (pre-existing pyright errors
unrelated)
- [x] Tests added for `attempt` parameter and `target_tokens` in
`_reduce_context`
2026-04-15 11:49:01 +07:00
Nicholas Tindle
142c5dbe99 fix(frontend): tighten artifact preview behavior (#12770)
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-14 20:21:05 -05:00
Abhimanyu Yadav
b06648de8c ci(frontend): add Playwright PR smoke suite with seeded QA accounts (#12682)
### Why / What / How

This PR simplifies frontend PR validation to one Playwright E2E suite,
moves redundant page-level browser coverage into Vitest integration
tests, and switches Playwright auth to deterministic seeded QA accounts.
It also folds in the follow-up fixes that came out of review and CI:
lint cleanup, CodeQL feedback, PR-local type regressions, and the flaky
Library run helper.

The approach is:
- keep Playwright focused on real browser and cross-page flows that
integration tests cannot prove well
- keep page-level render and mocked API behavior in Vitest
- remove the old PR-vs-full Playwright split from CI and run one
deterministic PR suite instead
- seed reusable auth states for fixed QA users so the browser suite is
less flaky and faster to bootstrap

### Changes 🏗️

- Removed the workflow indirection that selected different Playwright
suites for PRs vs other events
- Standardized frontend CI on a single command: `pnpm test:e2e:no-build`
- Consolidated the PR-gating Playwright suite around these happy-path
specs:
  - `auth-happy-path.spec.ts`
  - `settings-happy-path.spec.ts`
  - `api-keys-happy-path.spec.ts`
  - `builder-happy-path.spec.ts`
  - `library-happy-path.spec.ts`
  - `marketplace-happy-path.spec.ts`
  - `publish-happy-path.spec.ts`
  - `copilot-happy-path.spec.ts`
- Added the missing browser-only confidence checks to the PR suite:
  - settings persistence across reload and re-login
  - API key create, copy, and revoke
  - schedule `Run now` from Library
  - activity dropdown visibility for a real run
  - creator dashboard verification after publish submission
- Increased Playwright CI workers from `6` to `8`
- Migrated redundant page-level browser coverage into Vitest
integration/unit tests where appropriate, including marketplace,
profile, settings, API keys, signup behavior, agent dashboard row
behavior, agent activity, and utility/auth helpers
- Seeded deterministic Playwright QA users in
`backend/test/e2e_test_data.py` and reused auth states from
`frontend/src/tests/credentials/`
- Fixed CodeQL insecure randomness feedback by replacing insecure
randomness in test auth utilities
- Fixed frontend lint issues in marketplace image rendering
- Fixed PR-local type regressions introduced during test migration
- Stabilized the Library E2E run helper to support the current Library
action states: `Setup your task`, `New task`, `Rerun task`, and `Run
now`
- Removed obsolete Playwright specs and the temporary migration planning
doc once the consolidation was complete
- Reverted unintended non-test backend source changes; only backend test
fixture changes remain in scope

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  - [x] `pnpm lint`
  - [x] `pnpm types`
  - [x] `pnpm test:unit`
  - [x] `pnpm exec playwright test --list`
  - [x] `pnpm test:e2e:no-build` locally
  - [ ] PR CI green after the latest push

#### For configuration changes:
- [x] `.env.default` is updated or already compatible with my changes
- [x] `docker-compose.yml` is updated or already compatible with my
changes
- [x] I have included a list of my configuration changes in the PR
description (under **Changes**)

Notes:
- Current local Playwright run on this branch: `28 passed`, `0 flaky`,
`0 retries`, `3m 25s`.
- Latest Codecov report on this PR showed overall coverage `63.14% ->
63.61%` (`+0.47%`), with frontend coverage up `+2.32%` and frontend E2E
coverage up `+2.10%`.
- The backend change in this PR is limited to deterministic E2E test
data setup in `backend/test/e2e_test_data.py`.
- Playwright retries remain enabled in CI; this branch does not add
fail-on-flaky behavior.

---------

Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
Co-authored-by: Zamil Majdy <majdy.zamil@gmail.com>
2026-04-14 15:54:11 +00:00
Zamil Majdy
7240dd4fb1 feat(platform/admin): enhance cost dashboard with token breakdown and averages (#12757)
## Summary
- **Token breakdown in provider table**: Added separate Input Tokens and
Output Tokens columns to the By Provider table, making it easy to see
whether costs are driven by large contexts (input) or verbose
responses/thinking (output)
- **New summary cards (8 total)**: Added Avg Cost/Request, Avg Input
Tokens, Avg Output Tokens, and Total Tokens (in/out split) cards plus
P50/P75/P95/P99 cost percentile cards at the top of the dashboard for
at-a-glance cost analysis
- **Cost distribution histogram**: Added a cost distribution section
showing request count across configurable price buckets ($0–0.50,
$0.50–1, $1–2, $2–5, $5–10, $10+)
- **Per-user avg cost**: Added Avg Cost/Req column to the By User table
to identify users with unusually expensive requests
- **Backend aggregations**: Extended `PlatformCostDashboard` model with
`total_input_tokens`, `total_output_tokens`,
`avg_input_tokens_per_request`, `avg_output_tokens_per_request`,
`avg_cost_microdollars_per_request`,
`cost_p50/p75/p95/p99_microdollars`, and `cost_buckets` fields
- **Correct denominators**: Avg cost uses cost-bearing requests only;
avg token stats use token-bearing requests only — no artificial dilution
from non-cost/non-token rows

## Test plan
- [x] Verify the admin cost dashboard loads without errors at
`/admin/platform-costs`
- [x] Check that the new summary cards display correct values
- [x] Verify Input/Output Tokens columns appear in the By Provider table
- [x] Verify Avg Cost/Req column appears in the By User table
- [x] Confirm existing functionality (filters, export, rate overrides)
still works
- [x] Verify backward compatibility — new fields have defaults so old
API responses still work
2026-04-14 22:20:50 +07:00
Zamil Majdy
b4cd00bea9 dx(frontend): untrack auto-generated API client model files (#12778)
## Why
`src/app/api/__generated__/` is listed in `.gitignore` but 4 model files
were committed before that rule existed, so git kept tracking them and
they showed up in every PR that touched the API schema.

## What
Run `git rm --cached` on all 4 tracked files so the existing gitignore
rule takes effect. No gitignore content changes needed — the rule was
already correct.

## How
The `check API types` CI job only diffs `openapi.json` against the
backend's exported schema — it does not diff the generated TypeScript
models. So removing these from tracking does not break any CI check.

After this merges, `pnpm generate:api` output will be gitignored
everywhere and future API-touching PRs won't include generated model
diffs.
2026-04-14 22:19:32 +07:00
Zamil Majdy
e17914d393 perf(backend): enable cross-user prompt caching via SystemPromptPreset (#12758)
## Summary
- Use `SystemPromptPreset` with `exclude_dynamic_sections=True` in the
SDK path so the Claude Code default prompt serves as a cacheable prefix
shared across all users, reducing input token cost by ~90%
- Add `claude_agent_cross_user_prompt_cache` config field (default
`True`) to make this configurable, with fallback to raw string when
disabled
- Extract `_build_system_prompt_value()` helper for testability, with
`_SystemPromptPreset` TypedDict for proper type annotation

> **Depends on #12747** — requires SDK >=0.1.58 which adds
`SystemPromptPreset` with `exclude_dynamic_sections`. Must be merged
after #12747.

## Changes
- **`config.py`**: New `claude_agent_cross_user_prompt_cache: bool =
True` field on `ChatConfig`
- **`sdk/service.py`**: `_SystemPromptPreset` TypedDict for type safety;
`_build_system_prompt_value()` helper that constructs the preset dict or
returns the raw string; call site uses the helper
- **`sdk/service_test.py`**: Tests exercise the production
`_build_system_prompt_value()` helper directly — verifying preset dict
structure (enabled), raw string fallback (disabled), and default config
value

## How it works
The Claude Code CLI supports `SystemPromptPreset` which uses the
built-in Claude Code default prompt as a static prefix. By setting
`exclude_dynamic_sections=True`, per-user dynamic sections (working dir,
git status, auto-memory) are stripped from that prefix so it stays
identical across users and benefits from Anthropic's prompt caching. Our
custom prompt (tool notes, supplements, graphiti context) is appended
after the cacheable prefix.

## Test plan
- [x] CI passes (formatting, linting, unit tests)
- [x] Verify `_build_system_prompt_value()` returns correct preset dict
when enabled
- [x] Verify fallback to raw string when
`CHAT_CLAUDE_AGENT_CROSS_USER_PROMPT_CACHE=false`
2026-04-14 21:30:28 +07:00
Zamil Majdy
b3a58389e5 fix(copilot): baseline cost tracking and cache token display (#12762)
## Why
The baseline copilot path (OpenAI-compatible / OpenRouter) did not
record any cost when the `x-total-cost` response header was absent, even
though token counts were always available. The admin cost dashboard also
lacked cache token columns.

## What
- **`x-total-cost` header extraction**: Reads the OpenRouter cost header
per LLM call in the `finally` block (so cost is captured even when the
stream errors mid-way). Accumulated across multi-round tool-calling
turns.
- **Cache token extraction**: Extracts
`prompt_tokens_details.cached_tokens` and `cache_creation_input_tokens`
from streaming usage chunks and passes
`cache_read_tokens`/`cache_creation_tokens` through to
`persist_and_record_usage` for storage in `PlatformCostLog`.
- **Dashboard cache token display**: Adds cache read/write columns to
the Raw Logs and By User tables on the admin platform costs dashboard.
Adds `total_cache_read_tokens` and `total_cache_creation_tokens` to
`UserCostSummary`.
- **No cost estimation**: When `x-total-cost` is absent, `cost_usd` is
left as `None` and `persist_and_record_usage` records the entry under
`tracking_type="tokens"`. Token-based cost estimation was removed — the
platform dashboard already handles per-token cost display, and estimates
would introduce inaccuracy in the reported figures.

## How
- In `_baseline_llm_caller`: extract the `x-total-cost` header in the
`finally` block; accumulate to `state.cost_usd`.
- In `_BaselineStreamState`: add `turn_cache_read_tokens` /
`turn_cache_creation_tokens` counters, populated from streaming usage
chunks.
- In `persist_and_record_usage` / `record_cost_log`: pass through
`cache_read_tokens` and `cache_creation_tokens` to `PlatformCostEntry`.
- Frontend: add `total_cache_read_tokens` /
`total_cache_creation_tokens` fields to `UserCostSummary` and render
them as columns in the cost dashboard.

## Test plan
- [x] Verify baseline copilot sessions log cost when `x-total-cost`
header is present
- [x] Verify `cost_usd` stays `None` and token count is logged when
header is absent
- [x] Verify cache tokens appear in the dashboard logs table for
sessions using prompt caching
- [x] Verify the By User tab shows Cache Read and Cache Write columns
- [x] Unit tests: `test_cost_usd_extracted_from_response_header`,
`test_cost_usd_remains_none_when_header_missing`,
`test_cache_tokens_extracted_from_usage_details`
2026-04-14 21:08:31 +07:00
Zamil Majdy
a3846e1e74 fix(copilot): unified MCP file tools (Read/Write/Edit) to prevent truncation data loss (#12750)
### Why / What / How

**Why:** The Claude Agent SDK's built-in Write and Edit tools have no
defence against output-token truncation. When the LLM generates a large
`content` or `new_string` argument, the API truncates the response
mid-JSON, causing Ajv to reject it with the opaque `"'file_path' is a
required property"` error. The user's work is silently lost, and
retrying with the same approach loops infinitely.

**What:** Replaces the SDK's built-in Write and Edit tools with unified
MCP equivalents that detect truncation and return actionable recovery
guidance. Adds a new `read_file` MCP tool with offset/limit pagination.
Consolidates all file-tool handlers into a single module
(`e2b_file_tools.py`) covering both E2B (sandbox) and non-E2B (local SDK
working directory) modes.

**How:**
- `file_path` is placed first in every JSON schema so truncation is more
likely to preserve the path
- `"required"` is intentionally omitted from all MCP schemas so the MCP
SDK delivers empty/truncated args to the handler instead of rejecting
them with an opaque error
- Handlers detect two truncation patterns: complete (`{}`) and partial
(other fields present but `file_path` missing), returning actionable
error messages in both cases
- Edit uses a per-path `asyncio.Lock` (keyed by resolved absolute path)
to prevent parallel read-modify-write races when MCP tools are
dispatched concurrently
- Both E2B and non-E2B paths validate via `is_allowed_local_path()` /
`is_within_allowed_dirs()` to block directory traversal
- The SDK built-in Write and Edit are added to `SDK_DISALLOWED_TOOLS`;
the SDK built-in Read remains allowed only for workspace-scoped paths
(tool-results/tool-outputs) via `WORKSPACE_SCOPED_TOOLS`
- E2B write/edit tools are registered with `readOnlyHint=False`
(`_MUTATING_ANNOTATION`) to prevent parallel dispatch
- `bridge_to_sandbox` copies host-side tool-result files into the E2B
sandbox on read so `bash_exec` can process them

### Changes 🏗️

- **`e2b_file_tools.py`** — unified file-tool handlers for Write, Read
(`read_file`), Edit, Glob, Grep covering both E2B and non-E2B modes;
per-path edit locking; truncation detection; sandbox symlink-escape
check; `bridge_to_sandbox` for SDK→E2B file bridging
- **`tool_adapter.py`** — registers unified Write/Edit/read_file MCP
tools (non-E2B only); adds `Read` tool for workspace-scoped SDK-internal
reads (both modes); E2B tools use `_MUTATING_ANNOTATION`;
`get_copilot_tool_names` / `get_sdk_disallowed_tools` updated for both
modes
- **`security_hooks.py`** — `WORKSPACE_SCOPED_TOOLS` checked before
`BLOCKED_TOOLS` so SDK internal Read is allowed on tool-results paths;
Write/Edit removed from workspace scope
- **`prompting.py`** — improved wording for large-file truncation
warning
- **`e2b_file_tools_test.py`** — comprehensive tests for non-E2B
Write/Read/Edit (path validation, truncation detection, offset/limit,
binary rejection, schema validation); E2B sandbox symlink-escape,
`bridge_to_sandbox`, and `_sandbox_write` tests
- **`security_hooks_test.py`** — updated tests for revised tool-blocking
and workspace-scoped Read behaviour

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] Read: normal read, offset/limit, file not found, path traversal
blocked, binary file handling, truncation detection
- [x] Edit: normal edit, old_string not found, old_string not unique,
replace_all, partial truncation, path traversal blocked
- [x] Write: existing tests unchanged; truncation detection, path
validation, large-content warning
- [x] Schema validation: file_path first, required fields intentionally
absent
- [x] CLI built-in Write and Edit are in `SDK_DISALLOWED_TOOLS`; Read is
workspace-scoped only
  - [x] E2B write/edit use `_MUTATING_ANNOTATION` (not parallel)
  - [x] `black`, `ruff`, `pyright` pass on all modified files
  - [ ] CI pipeline passes
2026-04-14 20:51:22 +07:00
Zamil Majdy
e5b0b7f18e fix(copilot): store mode per session so indicator updates on switch (#12761)
## Summary
- Hide the mode toggle button while streaming (instead of disabling it)
to avoid confusing partial-toggle UI
- Remove localStorage mode persistence — mode is now transient in-memory
state only (no stale overrides across sessions)
- The copilot mode indicator now correctly reflects the active session's
mode because it reads from Zustand store which is updated on session
switch

## Changes
- `ChatInput.tsx` — hide `<ModeToggleButton>` when `isStreaming` instead
of passing `isStreaming` prop and showing a disabled button
- `ModeToggleButton.tsx` — remove `isStreaming` prop, disabled state,
and streaming-specific tooltip
- `store.ts` — remove localStorage read/write for `copilotMode`; mode
now defaults to `extended_thinking` and resets on page load
- `local-storage.ts` — keep `COPILOT_MODE` enum entry for backward
compatibility; remove unused `COPILOT_SESSION_MODES`
- `store.test.ts` — update tests to assert mode is NOT persisted to
localStorage
- `ChatInput.test.tsx` / `ModeToggleButton.stories.tsx` — update to
match hide-not-disable behavior

## Test plan
- [x] Create a session in fast mode, create another in extended_thinking
mode
- [x] Switch between sessions and verify the mode indicator updates
correctly
- [x] Mode toggle is hidden (not disabled) while a response is streaming
- [x] Refreshing the page resets mode to extended_thinking (no stale
localStorage override)
2026-04-14 20:39:00 +07:00
Zamil Majdy
92575ae76b fix(backend): fix sub-agent session hang and orphan on E2B API stall (#12774)
### Why / What / How

**Why:** AutoPilot sessions were silently dying with no response. Root
cause: `AsyncSandbox.create()` in the E2B SDK uses
`httpx.AsyncClient(timeout=None)` — infinite wait. When the E2B API
stalled during sandbox provisioning, executor goroutines hung
indefinitely. After 1h42m the RabbitMQ consumer timeout
(`COPILOT_CONSUMER_TIMEOUT_SECONDS = 3600`) killed the pod and all
in-flight sessions were orphaned — user sees no response, no error.

**What:**
1. Added per-attempt timeout + retry loop to `AsyncSandbox.create()`
calls in `e2b_sandbox.py` — 30s/attempt × 3 retries with exponential
backoff (~93s worst case vs infinite)
2. Added recovery enqueue in `AutoPilotBlock.run()` — on unexpected
failure, re-enqueues the session to RabbitMQ so a fresh executor pod
picks it up on the next turn
3. Added `_is_deliberate_block()` guard so recursion-limit errors are
not re-enqueued (they are expected terminations)
4. Unit tests for both new mechanisms

**How:**
- `asyncio.wait_for(AsyncSandbox.create(), timeout=30)` wraps each
attempt; `TimeoutError` triggers retry
- Redis creation sentinel TTL bumped 60→120s to cover the full retry
window (prevents concurrent callers from seeing stale sentinel)
- `_enqueue_for_recovery` calls `enqueue_copilot_turn()` with the
original prompt so the session resumes where it left off; dry-run
sessions are skipped; enqueue failures are logged but never mask the
original error
- `CancelledError` is re-raised after yielding the error output
(cooperative cancellation)

### Changes 🏗️

**`backend/copilot/tools/e2b_sandbox.py`**
- Added `_SANDBOX_CREATE_TIMEOUT_SECONDS = 30`,
`_SANDBOX_CREATE_MAX_RETRIES = 3`
- Bumped `_CREATION_LOCK_TTL` 60 → 120s
- Replaced bare `AsyncSandbox.create()` with `asyncio.wait_for` + retry
loop

**`backend/blocks/autopilot.py`**
- Added `_is_deliberate_block(exc)` — returns True for recursion-limit
RuntimeErrors
- Added `_enqueue_for_recovery(session_id, user_id, message, dry_run)` —
re-enqueues to RabbitMQ; no-ops on dry_run
- Exception handler in `run()` calls `_enqueue_for_recovery` for
transient failures; inner try/except prevents enqueue failure from
masking the original error

**`backend/blocks/test/test_autopilot.py`**
- `TestIsDeliberateBlock` — 4 unit tests for `_is_deliberate_block`
- `TestRecoveryEnqueue` — 5 tests: transient error triggers enqueue,
recursion limit skips, dry_run passes flag through, enqueue failure
doesn't mask original error, `ctx.dry_run` is OR-ed in

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] `poetry run pytest backend/blocks/test/test_autopilot.py -xvs` —
24/24 pass
- [x] Verified retry logic constants: 30s × 3 retries + 1s + 2s = 93s
worst case, sentinel TTL 120s covers it
- [x] Verified `_enqueue_for_recovery` is no-op for dry_run=True (no
RabbitMQ publish)
  - [x] Verified `CancelledError` re-raises after yield
2026-04-14 20:36:40 +07:00
Zamil Majdy
44b58ca22c fix(backend/copilot): fix T2+ --resume by using CLI native session file (#12777)
## Why

The Claude CLI 2.1.97 (bundled in `claude-agent-sdk 0.1.58`) changed the
`--resume` flag to accept a **session UUID**, not a file path. Our
service was incorrectly passing a temp file path (from
`write_transcript_to_tempfile`), causing the CLI subprocess to crash
with exit code 1 on every T2+ message — breaking all multi-turn CoPilot
conversations.

Additionally, using a file-per-pod approach meant pod affinity was
required for `--resume` to work (the file only existed on the pod that
handled T1).

## What

- Add `upload_cli_session()` to `transcript.py`: after each turn, upload
the CLI's native session JSONL (at
`{projects_base}/{encoded_cwd}/{session_id}.jsonl`) to remote storage
- Add `restore_cli_session()` to `transcript.py`: before T2+, download
and restore the CLI native session file to the expected path
- Pass `--session-id {app_uuid}` via `ClaudeAgentOptions` so the CLI
uses the app session UUID as its session ID → predictable file path
- On T2+: call `restore_cli_session()` and if successful, pass `--resume
{session_uuid}` (UUID, not file path)
- Remove `write_transcript_to_tempfile` from the resume path in
service.py (it only exists in transcript.py for compaction use)
- Keep DB reconstruction as last-resort fallback (populates builder
state only, no `--resume`)
- Compaction retry path now runs without `--resume` (compacted content
cannot be written in CLI native format)

## How

**Normal multi-turn flow (fixed):**
1. T1: SDK runs with `--session-id {app_uuid}` → CLI writes session to
predictable path
2. T1 finally: `upload_cli_session()` uploads native session to storage
(GCS/local)
3. T2+: `restore_cli_session()` downloads and writes the native session
back to disk
4. T2+: `--resume {app_uuid}` → CLI reads the restored session → full
context preserved

**Cross-pod benefit:**
The native session file is now in remote storage, so any pod can restore
it before a turn. Pod affinity for CoPilot is no longer required.

**Backward compatibility:**
- First turn: no native session in storage → runs without `--resume`
(same as before)
- If `restore_cli_session` fails: falls back gracefully to no
`--resume`, logs a warning
- DB reconstruction still available as last resort when no transcript
exists at all

## Checklist

- [x] Tests updated (service_helpers_test, retry_scenarios_test,
transcript_test all pass)
- [x] `poetry run ruff check` clean
- [x] `poetry run black --check` clean
- [x] `poetry run pyright` 0 errors on changed files
2026-04-14 20:36:05 +07:00
Bently
9de22eb053 fix(backend): remove extra blank line in platform_cost_test.py (#12768)
## Why
`platform_cost_test.py` had an extra blank line between
`TestUsdToMicrodollars.test_large_value` and `class TestMaskEmail`,
causing black to flag it. This failure was appearing in the CI merge
checks of unrelated PRs that target `dev`.

## What
Remove the extra blank line (3 → 2) to satisfy black's formatting rules.

## How
Single-character diff — no logic changes.
2026-04-14 09:25:28 +00:00
Zamil Majdy
55fe900650 fix(backend/copilot): keep credential setup inline on run and schedule paths (#12739)
## Why

When the AutoPilot copilot needed to connect credentials for an existing
agent, it was routing users to the Builder — flagged by @Pwuts in [the
AutoPilot Credential UX
thread](https://discord.com/channels/1126875755960336515/1492203735034892471/1492204936056930304).

Two root causes:

1. **Credential race-condition on the run/schedule path.**
`_check_prerequisites` only catches missing creds *before* the
executor/scheduler call. If creds are deleted (or drift) between the
prereq check and the actual call, the executor/scheduler raises
`GraphValidationError`. The tool returned a plain `ErrorResponse`, and
the LLM fell back to `create_agent`/`edit_agent` — whose
`AgentSavedResponse.agent_page_link=/build?flowID=...` is exactly the
Builder redirect the user saw.

2. **`GraphValidationError.node_errors` lost over RPC.** The scheduler
call goes through `get_scheduler_client()` (RPC). The server-side error
handler only preserved `exc.args` — the structured `node_errors` mapping
was stripped, making it impossible for the copilot to distinguish
credential failures from other validation errors on the schedule path.

## What

- **Race-condition handling for both run and schedule paths.**
`_run_agent` and `_schedule_agent` now catch `GraphValidationError`,
detect credential-flavoured node errors, and rebuild the inline
`SetupRequirementsResponse` so the credential setup card renders inline
without leaving chat. Mixed credential+structural errors fall through to
plain `ErrorResponse` so structural errors aren't hidden.

- **`GraphValidationError` round-trips over RPC.** `service.py` now
packs `node_errors` into a typed `RemoteCallExtras` field on
`RemoteCallError`, and the client-side handler re-threads it back into
the reconstructed exception.

- **Shared credential-error matcher.** The credential-string matching
logic is extracted to `is_credential_validation_error_message()` in
`backend/executor/utils.py`, backed by `CRED_ERR_*` module-level
constants that are referenced at both raise sites and in the matcher —
so adding a new credential error string doesn't silently break the
copilot fallback.

- **Tool-description guardrails.** `create_agent` and `edit_agent`
descriptions now explicitly say "Do NOT use this to connect credentials
— call run_agent instead." `agent_generation_guide.md` has the same
guardrail for the agent-building context.

## How

- `backend/copilot/tools/run_agent.py`: new
`_build_setup_requirements_from_validation_error()` helper; try/except
around `add_graph_execution` and `add_execution_schedule` in the
respective `_run_agent`/`_schedule_agent` paths; race-condition warnings
logged.

- `backend/executor/utils.py`: `CRED_ERR_*` constants +
`_CREDENTIAL_ERROR_MARKERS` typed tuple + public
`is_credential_validation_error_message()` exported; old private
`_is_credential_error` lambda replaced.

- `backend/util/service.py`: `RemoteCallExtras` Pydantic model with
`node_errors: Optional[dict[str, dict[str, str]]]`; server handler packs
it for `GraphValidationError`; client handler re-threads it;
`exception_class is GraphValidationError` identity check (not
`issubclass`).

- `backend/copilot/tools/create_agent.py`, `edit_agent.py`: added
credential-routing guardrail to tool descriptions.

- `backend/copilot/sdk/agent_generation_guide.md`: added
credential-routing guardrail.

## Test plan

- [x] Unit tests for `is_credential_validation_error_message` (all four
error templates matched, case-insensitive, non-credential messages
rejected).
- [x] Parity tests in `utils_test.py` that pin all `CRED_ERR_*`
constants against `is_credential_validation_error_message` — drift when
a new credential error is added fails immediately.
- [x] Unit tests for `_build_setup_requirements_from_validation_error`:
credential error → `SetupRequirementsResponse`; non-credential error →
`None`; mixed errors → `None`.
- [x] E2E test for `_schedule_agent` race path:
`get_scheduler_client().add_execution_schedule` mocked to raise
credential `GraphValidationError` → response is `setup_requirements`,
not generic error.
- [x] E2E test for `_run_agent` race path:
`execution_utils.add_graph_execution` mocked with `AsyncMock` to raise
credential `GraphValidationError` → response is `setup_requirements`.
- [x] `RemoteCallError` round-trip tests in `service_test.py`: server
handler packs `node_errors` into `extras`; client handler unpacks; full
round-trip preserves `node_errors`.
- [x] Backwards-compat test: old `RemoteCallError` without `extras`
still deserializes to `GraphValidationError` with empty `node_errors`.
2026-04-14 15:56:06 +07:00
Zamil Majdy
bc6709dda1 fix(copilot): strip <internal_reasoning> tags from Sonnet response stream (#12763)
## Summary
- Extract `ThinkingStripper` from `baseline/service.py` into a shared
`copilot/thinking_stripper.py` module
- Apply thinking-tag stripping to the SDK streaming path
(`_dispatch_response`) so `<internal_reasoning>` and `<thinking>` tags
emitted by non-extended-thinking models (e.g. Sonnet) are stripped
before reaching the SSE client
- Flush any buffered text from the stripper at stream end so no content
is lost
- Add unit tests for the shared `ThinkingStripper` and integration tests
for the SDK dispatch path

## Problem
When using Claude Sonnet (which doesn't have extended thinking), the
model sometimes outputs `<internal_reasoning>...</internal_reasoning>`
tags as visible text in the response stream. The baseline path already
stripped these, but the SDK path did not.

## Test plan
- [ ] CI passes (unit tests for ThinkingStripper and SDK dispatch
stripping)
- [ ] Manual test: send a message via Sonnet and verify no
`<internal_reasoning>` tags appear in the response
2026-04-14 15:53:22 +07:00
Zamil Majdy
b2b6f75420 fix(copilot): deduplicate SSE-replayed messages by content fingerprint (#12759)
## Summary
- Fixes duplicate message content shown in CoPilot during SSE
reconnections (page visibility change, network hiccups, wake-resync)
- The `resume_session_stream` backend always replays from `"0-0"`
(beginning of Redis stream), and replayed `UIMessage` objects get new
generated IDs from `useChat`, bypassing the old adjacent-only content
dedup
- Extends `deduplicateMessages` to track all seen `role +
preceding-user-context + content` fingerprints globally, catching
replayed messages regardless of different IDs or position in the list
- Scopes fingerprints by preceding user message text to avoid false
positives when the assistant legitimately gives the same answer to
different prompts

## Test plan
- [ ] Verify new unit tests pass in CI (`helpers.test.ts` - 7 new dedup
test cases)
- [ ] Manual: start a long tool-use session, switch tabs, return - no
duplicate content
- [ ] Manual: refresh page during active session - content loads from DB
without duplicates
- [ ] Manual: ask the same question twice in different turns - both
answers preserved
2026-04-14 15:49:47 +07:00
Zamil Majdy
573fb7163f feat(copilot): upgrade claude-agent-sdk to 0.1.58 with OpenRouter compat + cost controls (#12747)
## Why

We've been pinned at `claude-agent-sdk==0.1.45` (bundled CLI 2.1.63)
since PR #12294 because newer versions had two OpenRouter
incompatibilities:

1. **`tool_reference` content blocks** (CLI 2.1.69+) — OpenRouter's Zod
validation rejects them
2. **`context-management-2025-06-27` beta header** (CLI 2.1.91+) —
OpenRouter returns 400

Both are now resolved:
- **`tool_reference`: Fixed by CLI's built-in proxy detection.** CLI
2.1.70+ detects `ANTHROPIC_BASE_URL` pointing to a non-Anthropic
endpoint and disables `tool_reference` blocks automatically. Verified
working in CLI 2.1.97 — the bare CLI test only XFAILs on the beta
header, NOT on tool_reference.
- **`context-management` beta: Fixed by
`CLAUDE_CODE_DISABLE_EXPERIMENTAL_BETAS=1` env var.** Injected via
`build_sdk_env()` for all SDK subprocess calls. Verified in CI.

## What

- Upgrades `claude-agent-sdk` from **0.1.45 → 0.1.58** (bundled CLI
2.1.63 → 2.1.97)
- Injects `CLAUDE_CODE_DISABLE_EXPERIMENTAL_BETAS=1` in
`build_sdk_env()` (all modes)
- Adds `claude_agent_cli_path` config override with executable
validation
- Adds `claude_agent_max_thinking_tokens=8192` (was unlimited — 54% of
$14K/5-day spend was thinking tokens at $75/M)
- Lowers `max_budget_usd` from $100 → $15 and `max_turns` from 1000 → 50

### Features unlocked by the upgrade

| Feature | SDK | Impact |
|---|---|---|
| `exclude_dynamic_sections` | 0.1.57 | Cross-user prompt cache hits
(see #12758) |
| `AssistantMessage.usage` per-turn | 0.1.49 | Cost attribution per LLM
call |
| `task_budget` | 0.1.51 | Per-task cost ceiling at SDK level |
| `get_context_usage()` | 0.1.52 | Live context-window monitoring |
| MCP large-tool-result fix | 0.1.55 | No more silent truncation >50K
chars |
| MCP HTTP/SSE buffer leak fix | CLI 2.1.97 | Production memory creep
~50 MB/hr |
| 429 retry exponential backoff | CLI 2.1.97 | Rate-limit recovery (was
burning all retries in ~13s) |
| `--resume` cache miss fix | CLI 2.1.90 | Prompt cache works after
resume |
| SDK session quadratic-write fix | CLI 2.1.90 | No more slowdown on
long sessions |
| `max_thinking_tokens` | 0.1.57 | Cap extended thinking cost |

## How

- `build_sdk_env()` in `env.py` injects the env var unconditionally (all
3 auth modes)
- `service.py` passes `max_thinking_tokens` to `ClaudeAgentOptions`
- `config.py` adds 3 new fields with env var overrides
- Regression tests verify both OpenRouter compat issues are handled

## Test plan

- [x] CI green on all test matrices (3.11, 3.12, 3.13)
- [x] `test_disable_experimental_betas_env_var_strips_headers` passes —
verifies env var strips both patterns
- [x] `test_bare_cli_*` correctly XFAILs — documents the CLI regression
exists
- [x] `test_sdk_exposes_max_thinking_tokens_option` guards the new param
- [x] Config validation tests use real temp executables
2026-04-14 15:31:43 +07:00
Zamil Majdy
c0306b1d21 perf(backend/copilot): enable LLM prompt caching + harden user_context injection (#12725)
### Why

LLM token costs are significant, especially for the copilot feature. The
system prompt and tool definitions are the two largest static components
of every request — caching them dramatically reduces input token costs
(cache reads cost 10% of the base input price).

Previously, user-specific context (business understanding) was embedded
directly in the system prompt, making it unique per user and preventing
cache sharing across users or sessions. Every request paid full price
for the system prompt even when the content was functionally identical.

A secondary security concern was identified during review: because the
LLM is instructed to parse `<user_context>` blocks, a user could type a
literal `<user_context>…</user_context>` tag in any message and
potentially spoof or suppress their own personalisation context. This PR
includes a full defence-in-depth fix for that injection vector on the
first turn (including new users with no stored understanding), plus
GET-endpoint stripping so injected context is never surfaced back to the
client.

### What

- **`copilot/service.py`**: Added `USER_CONTEXT_TAG` constant (shared by
writer and reader). Added `_USER_CONTEXT_ANYWHERE_RE` /
`_USER_CONTEXT_PREFIX_RE` regexes, `format_user_context_prefix`,
`strip_user_context_prefix`, `sanitize_user_supplied_context`, and
`_sanitize_user_context_field` helpers. Replaced the old
`_build_cacheable_system_prompt` / `_build_system_prompt` pair with a
single `_build_system_prompt` that returns `(static_prompt,
understanding)`. Added `inject_user_context` which sanitizes user input,
optionally wraps trusted understanding, and persists the result to DB.
- **`copilot/sdk/service.py`**: On first turn calls
`inject_user_context` before `_build_query_message` so the query sees
the prefixed content. Passes `user_id if not has_history else None` to
avoid redundant DB lookups on subsequent turns.
- **`copilot/baseline/service.py`**: Same pattern —
`inject_user_context` called before transcript append and OpenAI message
list construction; `openai_messages` loop patches the first user entry
after injection.
- **`blocks/llm.py`**: System prompt sent as a structured block with
`cache_control: {"type": "ephemeral"}`. `cache_control` placed on the
last tool in the tool list. Guards against empty/whitespace-only system
blocks (Anthropic rejects them). Fixed `anthropic.omit` →
`anthropic.NOT_GIVEN` sentinel for the no-tools case.
- **`api/features/chat/routes.py`**: Added `_strip_injected_context`
which returns a shallow copy of each message with the server-injected
`<user_context>` prefix stripped before the GET `/sessions/{id}`
response, so the prefix is invisible to the frontend.
- **`copilot/db.py`**: Added defence-in-depth `result > 1` error log in
`update_message_content_by_sequence`. Added authorization note
documenting why a `userId` join is not required.
- **`data/db_manager.py`**: Registered
`update_message_content_by_sequence` on both the sync and async DB
manager clients.

### How it works

**Static system prompt**: The system prompt is now identical for every
user. The LLM is instructed to look for a `<user_context>` block in the
first user message when present, and to greet new users warmly when no
context is provided.

**User context injection**: On the first turn of a new session, the
caller's business understanding is prepended to the user's message as
`<user_context>…</user_context>`. The prefixed content is also persisted
to the DB so resumed sessions and page reloads retain personalisation.

**`<user_context>` tag sanitization (security)**: `inject_user_context`
calls `sanitize_user_supplied_context` unconditionally — even when
`understanding` is `None` — so new users cannot smuggle a
`<user_context>` tag to the LLM on the first turn. Fields from the
stored `BusinessUnderstanding` object are escaped with
`_sanitize_user_context_field` so user-controlled free-text cannot break
out of the trusted block. The GET endpoint strips the injected prefix
before returning message history to the client.

**All-turn sanitization**: `strip_user_context_tags` (a public alias of
`sanitize_user_supplied_context`) is called unconditionally on every
incoming message in both the SDK and baseline paths — before
`maybe_append_user_message` — so `<user_context>` tags typed by a user
on any turn (not just the first) are stripped before reaching the LLM.
Lone unpaired tags (e.g. `<user_context>spoof` without a closing tag)
are also caught by a second-pass `_USER_CONTEXT_LONE_TAG_RE`
substitution. The system prompt explicitly states the tag is
server-injected, only trusted on the first message, and must be ignored
on subsequent turns.

**Cache placement**: Per Anthropic's caching model, placing
`cache_control` on the system prompt block caches everything up to and
including it. Placing `cache_control` on the last tool definition caches
all tool schemas as a single prefix. Both cache points are set so
repeated requests from any user can hit both caches.

**Langfuse compatibility**: `_build_system_prompt` calls
`prompt.compile(users_information="")` so existing Langfuse prompt
templates remain static and cacheable.

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] Verify system prompt no longer contains user-specific information
- [x] Verify `<user_context>` block appears in the first user message on
new sessions
- [x] Verify returning users still receive personalised responses via
user context
- [x] Verify Langfuse-sourced prompts compile correctly with empty
`users_information`
- [x] Verify Anthropic API calls include `cache_control` on system block
and last tool
- [x] Verify user-supplied `<user_context>` tags are stripped on the
first turn (including when understanding is None)
- [x] Verify user-supplied `<user_context>` tags are stripped on all
turns (turn 2+ sanitization via `strip_user_context_tags`)
- [x] Verify lone unpaired `<user_context>` tags (no closing tag) are
also stripped
- [x] Verify GET `/sessions/{id}` does not expose the injected
`<user_context>` prefix to the client

---------

Co-authored-by: majdyz <majdy.zamil@gmail.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-14 14:50:09 +07:00
Zamil Majdy
b319c26cab feat(platform/admin): per-model cost breakdown, cache token tracking, OrchestratorBlock cost fix (#12726)
## Why

The platform cost tracking system had several gaps that made the admin
dashboard less accurate and harder to reason about:

**Q: Do we have per-model granularity on the provider page?**
The `model` column was stored in `PlatformCostLog` but the SQL
aggregation grouped only by `(provider, tracking_type)`, so all models
for a given provider collapsed into one row. Now grouped by `(provider,
tracking_type, model)` — each model gets its own row.

**Q: Why does Anthropic show `per_run` for OrchestratorBlock?**
Bug: `OrchestratorBlock._call_llm()` was building `NodeExecutionStats`
with only `input_token_count` and `output_token_count` — it dropped
`resp.provider_cost` entirely. For OpenRouter calls this silently
discarded the `cost_usd`. For the SDK (autopilot) path,
`ResultMessage.total_cost_usd` was never read. When `provider_cost` is
None and token counts are 0 (e.g. SDK error path), `resolve_tracking`
falls through to `per_run`. Fixed by propagating all cost/cache fields.

**Q: Why can't we get `cost_usd` for Anthropic direct API calls?**
The Anthropic Messages API does not return a dollar amount — only token
counts. OpenRouter returns cost via response headers, so it uses
`cost_usd` directly. The Claude Agent SDK *does* compute
`total_cost_usd` internally, so SDK-mode OrchestratorBlock runs now get
`cost_usd` tracking. For direct Anthropic LLM blocks the estimate uses
per-token rates (see cache section below).

**Q: What about labeling by source (autopilot vs block)?**
Already tracked: `block_name` stores `copilot:SDK`, `copilot:Baseline`,
or the actual block name. Visible in the raw logs table. Not added to
the provider group-by (would explode row count); use the logs table
filter instead.

**Q: Is there double-counting between `tokens`, `per_run`, and
`cost_usd`?**
No. `resolve_tracking()` uses a strict preference hierarchy — exactly
one tracking type per execution: `cost_usd` > `tokens` > provider
heuristics > `per_run`. A single execution produces exactly one
`PlatformCostLog` row.

**Q: Should we track Anthropic prompt cache tokens (PR #12725)?**
Yes — PR #12725 adds `cache_control` markers to Anthropic API calls,
which causes the API to return `cache_read_input_tokens` and
`cache_creation_input_tokens` alongside regular `input_tokens`. These
have different billing rates:
- Cache reads: **10%** of base input rate (much cheaper)
- Cache writes: **125%** of base input rate (slightly more expensive,
one-time)
- Uncached input: **100%** of base rate

Without tracking them separately, a flat-rate estimate on
`total_input_tokens` would be wrong in both directions.

## What

- **Per-model provider table**: SQL now groups by `(provider,
tracking_type, model)`. `ProviderCostSummary` and the frontend
`ProviderTable` show a model column.
- **Cache token columns**: New `cacheReadTokens` and
`cacheCreationTokens` columns in `PlatformCostLog` with matching
migration.
- **LLM block cache tracking**: `LLMResponse` captures
`cache_read_input_tokens` / `cache_creation_input_tokens` from Anthropic
responses. `NodeExecutionStats` gains `cache_read_token_count` /
`cache_creation_token_count`. Both propagate to `PlatformCostEntry` and
the DB.
- **Copilot path**: `token_tracking.persist_and_record_usage` now writes
cache tokens as dedicated `PlatformCostEntry` fields (was
metadata-only).
- **OrchestratorBlock bug fix**: `_call_llm()` now includes
`resp.provider_cost`, `resp.cache_read_tokens`,
`resp.cache_creation_tokens` in the stats merge. SDK path captures
`ResultMessage.total_cost_usd` as `provider_cost`.
- **Accurate cost estimation**: `estimateCostForRow` uses
token-type-specific rates for `tokens` rows (uncached=100%, reads=10%,
writes=125% of configured base rate).

## How

`resolve_tracking` priority is unchanged. For Anthropic LLM blocks the
tracking type remains `tokens` (Anthropic API returns no dollar amount).
For OrchestratorBlock in SDK/autopilot mode it now correctly uses
`cost_usd` because the Claude Agent SDK computes and returns
`total_cost_usd`. For OpenRouter through OrchestratorBlock it now
correctly uses `cost_usd` (was silently dropped before).

## Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  - [x] `ProviderCostSummary` SQL updated
- [x] Cache token fields present in `PlatformCostEntry` and
`PlatformCostLogCreateInput`
  - [x] Prisma client regenerated — all type checks pass
  - [x] Frontend `helpers.test.ts` updated for new `rateKey` format
  - [x] Pre-commit hooks pass (Black, Ruff, isort, tsc, Prisma generate)
2026-04-10 23:14:43 +07:00
Zamil Majdy
85921f227a Merge branch 'dev' of github.com:Significant-Gravitas/AutoGPT into preview/all-active-prs 2026-04-10 22:59:30 +07:00
Zamil Majdy
5844b13fb1 feat(backend/copilot): support multiple questions in ask_question tool (#12732)
### Why / What / How

**Why:** The `ask_question` copilot tool previously only accepted a
single question per invocation. When the LLM needs to ask multiple
clarifying questions simultaneously, it either crams them into one text
field (requiring users to format numbered answers manually) or makes
multiple sequential tool calls (slow and disruptive UX).

**What:** Replace the single `question`/`options`/`keyword` parameters
with a `questions` array parameter so the LLM can ask multiple questions
in one tool call, each rendered as its own input box.

**How:** Simplified the tool to accept only `questions` (array of
question objects). Each item has `question` (required), `options`, and
`keyword`. The frontend `ClarificationQuestionsCard` already supports
rendering multiple questions — no frontend changes needed.

### Changes 🏗️

- `backend/copilot/tools/ask_question.py`: Replaced dual
question/questions schema with single `questions` array. Extracted
parsing into module-level `_parse_questions` and `_parse_one` helpers.
Follows backend code style: early returns, list comprehensions, top-down
ordering, functions under 40 lines.
- `backend/copilot/tools/ask_question_test.py`: Rewritten with 18
focused tests covering happy paths, keyword handling, options filtering,
and invalid input handling.

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [ ] I have tested my changes according to the test plan:
- [ ] Run `poetry run pytest backend/copilot/tools/ask_question_test.py`
— all tests pass

🤖 Generated with [Claude Code](https://claude.com/claude-code)

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-10 21:54:53 +07:00
Zamil Majdy
c014e1aa35 merge(preview): merge all active PRs into preview/all-active-prs from fresh dev 2026-04-10 08:40:23 +07:00
Zamil Majdy
e59f576622 Merge remote-tracking branch 'origin/spare/13' into preview/all-active-prs 2026-04-10 08:39:34 +07:00
Zamil Majdy
c99fa32ae3 Merge remote-tracking branch 'origin/spare/3' into preview/all-active-prs 2026-04-10 08:39:34 +07:00
Zamil Majdy
b71789da50 Merge remote-tracking branch 'origin/feat/subscription-tier-billing' into preview/all-active-prs 2026-04-10 08:39:34 +07:00
Zamil Majdy
5661326e7e fix(platform): fetch real Stripe prices in subscription status endpoint
- Import get_subscription_price_id in v1.py
- get_subscription_status now calls stripe.Price.retrieve for PRO/BUSINESS
  tiers to return actual unit_amount instead of hardcoded zeros
- UI will now show correct monthly costs when LD price IDs are configured
- Fix Button import from __legacy__ to design system in SubscriptionTierSection
- Update subscription status tests to mock the new Stripe price lookup
2026-04-10 08:37:40 +07:00
Zamil Majdy
df3fe926f2 style(backend/copilot): apply Black formatting to ask_question
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-09 23:56:42 +00:00
Zamil Majdy
505af7e673 refactor(backend/copilot): simplify ask_question to questions-only API
Drop the dual question/questions schema in favor of a single
`questions` array parameter. This removes ~175 lines of complexity
(the _execute_single path, duplicate params, precedence logic).

Restructured per backend code style rules:
- Top-down ordering: public _execute first, helpers below
- Early return with guard clauses, no deep nesting
- List comprehensions via walrus operator in _parse_questions
- Helpers extracted as module-level functions (not methods)
- Functions under 40 lines each

The frontend ClarificationQuestionsCard already renders arrays of
any length — no UI changes needed.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-09 23:54:11 +00:00
Zamil Majdy
d896a1f9fa fix(backend/copilot): add missing isinstance assertion in test
Add isinstance narrowing in test_execute_multiple_questions_ignores_single_params
to fix Pyright type-check CI failure (reportAttributeAccessIssue).

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-09 23:48:02 +00:00
Zamil Majdy
6aa5a808e0 fix(backend/copilot): add isinstance assertions to fix type-check CI
Tests that access `result.questions` without first narrowing the type
from `ToolResponseBase` to `ClarificationNeededResponse` cause Pyright
type-check failures. Added `assert isinstance(result,
ClarificationNeededResponse)` before accessing `.questions` in 4 tests.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-09 23:40:08 +00:00
Zamil Majdy
18c88b4da0 fix(frontend/builder): always clear messages on flowID change to keep action state consistent
When navigating back to a cached session, appliedActionKeys was reset to empty
but messages were preserved. This caused previously applied actions to reappear
as unapplied in the UI, allowing them to be re-applied and creating duplicate
undo entries. Clearing messages unconditionally on navigation ensures the
displayed action buttons always reflect the actual applied state.
2026-04-10 02:03:56 +07:00
Zamil Majdy
3a5ce570e0 fix(backend/copilot): address PR review round 4
- Restore top-level `required: ["question"]` in schema for LLM tool-
  calling compatibility; validation handles the questions-only path
- Fix keyword null bug: `item.get("keyword")` returning None now
  correctly falls back to `question-{idx}` instead of producing "None"
- Filter empty-string options in _build_question (`str(o).strip()`)
  to avoid artifacts like "Email, , Slack"
- Revert session type hint to `ChatSession` to match base class contract
- Add tests for null keyword and empty-string options filtering

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-09 18:56:37 +00:00
Zamil Majdy
5a3739e54d fix(backend/copilot): address PR review round 2
- Remove top-level `required: ["question"]` from schema so the
  `questions`-only calling convention is valid for schema-compliant LLMs
- Move logger assignment below all imports (PEP 8 / isort)
- Remove duplicated option filtering in `_execute_single`; let
  `_build_question` own that responsibility
- Fix `session` type hint to `ChatSession | None` to match the guard
- Add test for `questions` as non-list type (falls back to single path)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-09 18:43:11 +00:00
Zamil Majdy
72bc8a92df fix(frontend/builder): guard msg.parts with nullish coalescing to prevent runtime error 2026-04-10 01:41:15 +07:00
Zamil Majdy
cc29cf5e20 fix(backend/copilot): address PR review round 1
- Fix falsy option filtering: use `if o is not None` instead of `if o`
  so valid values like "0" are preserved
- Improve multi-question `message` field: join all questions with ";"
  instead of only using the first question's text
- Add logging warnings for skipped invalid items in multi-question path
  instead of silently dropping them
- Simplify schema: use `"required": ["question"]` instead of empty
  required + anyOf (more LLM-friendly)
- Add missing test cases: session=None, single-item questions array,
  duplicate keywords, falsy option values

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-09 18:39:55 +00:00
Zamil Majdy
a0efbbba90 feat(backend/copilot): support multiple questions in ask_question tool
The ask_question tool previously only accepted a single question per
invocation, forcing the LLM to cram multiple queries into one text box
or make multiple sequential tool calls. This adds a `questions` parameter
(list of question objects) so multiple input fields render at once.

Backward-compatible: the existing `question`/`options`/`keyword` params
still work. When `questions` (plural) is provided, they take precedence.
The frontend ClarificationQuestionsCard already supports rendering
multiple questions — no frontend changes needed.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-09 18:21:35 +00:00
Zamil Majdy
8ed959433a fix(frontend/builder): clear stale messages in retrySession so new session starts clean 2026-04-10 00:56:31 +07:00
Zamil Majdy
98f3e09580 fix(frontend/builder): reset hasSentSeedMessageRef in retrySession so seed is sent to new session 2026-04-10 00:39:10 +07:00
Zamil Majdy
9ec44dd109 test(backend): add route-level tests for subscription API endpoints
Tests for GET/POST /credits/subscription covering:
- GET returns current tier (PRO, FREE default when None)
- POST FREE skips Stripe when payment disabled
- POST PRO sets tier directly for beta users (payment disabled)
- POST paid tier rejects missing success_url/cancel_url with 422
- POST paid tier creates Stripe Checkout Session and returns URL
- POST FREE with payment enabled cancels active Stripe subscription
2026-04-10 00:19:06 +07:00
Zamil Majdy
bfb82b6246 fix(platform): address reviewer feedback on subscription endpoint
- Remove useCallback from changeTier (not needed per project guidelines)
- Block self-service tier changes for ENTERPRISE users (admin-managed)
- Preserve current tier on unrecognized Stripe price_id instead of
  defaulting to FREE (prevents accidental downgrades during price migration)
2026-04-10 00:08:54 +07:00
Zamil Majdy
63210770ce test(backend): add tests for get_subscription_price_id to improve coverage 2026-04-09 23:54:02 +07:00
Zamil Majdy
f2b8f81bb1 test(backend/copilot): add unit tests for update_message_content_by_sequence
Cover success, not-found (returns False + warning), and DB-error (returns
False + error log) paths to push patch coverage above the 80% threshold.
2026-04-09 23:52:39 +07:00
Zamil Majdy
68b51ae2d3 test(backend): add coverage for sync_subscription_from_stripe edge cases
Tests for:
- Unknown/mismatched Stripe price_id defaults to FREE (not early return)
- None from LaunchDarkly price flags defaults to FREE
- BUSINESS tier mapping
- StripeError during cancel_stripe_subscription is logged, not raised
2026-04-09 23:52:16 +07:00
Zamil Majdy
63ff214563 fix(backend): default to FREE tier on unknown Stripe price ID in webhook sync
When sync_subscription_from_stripe encounters an unrecognized price_id
(e.g. LD flags unconfigured or price changed), it no longer returns early
leaving the user on a stale tier. Instead it defaults to FREE and logs a
warning, keeping the DB state consistent with Stripe's subscription status.

Also guard against None pro_price/biz_price from LaunchDarkly before
comparison to avoid silent mismatches.
2026-04-09 23:41:51 +07:00
Zamil Majdy
9498daca31 fix(frontend/builder): wrap panel in CopilotChatActionsProvider to prevent crash
EditAgentTool and RunAgentTool call useCopilotChatActions() which throws
if no provider is in the tree. Wrap the panel content with
CopilotChatActionsProvider wired to sendRawMessage so tool components
can send retry prompts without crashing.
2026-04-09 23:41:06 +07:00
Zamil Majdy
ce0cb1e035 fix(backend/copilot): persist user-context prefix to DB in both SDK and baseline paths
The user message was saved to DB before the <user_context> prefix was added
to session.messages. Subsequent upsert_chat_session calls only append new
messages (slicing by existing_message_count), so the prefixed content was
never written to the DB. On page reload or --resume, the unprefixed version
was loaded, losing personalisation.

Fix: add update_message_content_by_sequence to db.py and call it after
injecting the prefix in both sdk/service.py and baseline/service.py.
2026-04-09 23:40:14 +07:00
Zamil Majdy
0d89f7bb33 fix(backend): handle customer.subscription.created webhook event
Add customer.subscription.created to the sync handler so user tier is
upgraded immediately when the subscription is first created (not just on
subsequent updates/deletions).
2026-04-09 23:39:16 +07:00
Zamil Majdy
aef9298be6 test(platform/admin): add cache token and retry cost accumulation tests
Add unit tests for:
- Anthropic cache_read_tokens/cache_creation_tokens in llm_call response
- cache token accumulation in AIStructuredResponseGeneratorBlock stats
- provider_cost persistence on exhausted retry path
- usd_to_microdollars None-safe branch
- explicit start param covering _build_where false branch
- cache token columns in platform_cost integration test
2026-04-09 23:33:21 +07:00
Zamil Majdy
e5ea2e0d5b fix(backend/copilot): fix stale docstring referencing anthropic.omit instead of NOT_GIVEN 2026-04-09 23:24:43 +07:00
Zamil Majdy
4eabc48053 fix(backend): fix migration conflict with dev's SubscriptionTier migration
dev branch already creates SubscriptionTier enum and subscriptionTier column in
20260326200000_add_rate_limit_tier. Remove duplicate DDL from our migration and
only add SUBSCRIPTION to CreditTransactionType using IF NOT EXISTS guard.
2026-04-09 23:24:12 +07:00
Zamil Majdy
101504ce0b fix(platform): cancel Stripe subscription when downgrading to FREE tier
Add cancel_stripe_subscription() which lists and cancels all active Stripe
subscriptions for the customer, preventing continued billing after downgrade.
Call it from update_subscription_tier() when tier == FREE and payment is
enabled. Add two unit tests covering active and empty subscription scenarios.
2026-04-09 23:21:27 +07:00
Zamil Majdy
2f67249d5f test(platform/admin): increase patch coverage for export endpoint and cache token tracking
Add tests for the /logs/export endpoint (success, truncated, filters, auth) and
fix missing import of get_platform_cost_logs_for_export in platform_cost_test.py.
2026-04-09 23:20:37 +07:00
Zamil Majdy
e73b5b3692 fix(backend): validate success_url/cancel_url for paid Stripe checkout
Add upfront 422 validation when upgrading to a paid tier without providing
redirect URLs. Also catch stripe.StripeError alongside ValueError to return
a proper 422 instead of a 500 on Stripe API errors.
2026-04-09 23:18:16 +07:00
Zamil Majdy
57c0c86a10 fix(frontend/builder): skip Escape-to-close when focus is in textarea/input
Pressing Escape while drafting a message was silently discarding the
user's text. Guard the handler so it only closes the panel when focus is
outside an editable element.
2026-04-09 23:15:56 +07:00
Zamil Majdy
77d8362983 docs(blocks): sync misc.md with memory_search/memory_store tools from dev merge 2026-04-09 23:15:02 +07:00
Zamil Majdy
201d88b846 Merge remote-tracking branch 'origin/dev' into spare/3 2026-04-09 23:14:33 +07:00
Zamil Majdy
611a00d930 fix(backend): resolve dev merge conflict and remove credit-based subscription cost
Remove get_subscription_cost (referenced deleted flags SUBSCRIPTION_COST_PRO/BUSINESS).
Subscription pricing is now handled by Stripe. Add GRAPHITI_MEMORY flag from dev.
2026-04-09 23:14:15 +07:00
Zamil Majdy
8d31bdb2dc fix(platform): address remaining review comments on subscription billing
- Remove `# type: ignore[attr-defined]` suppressors from `set_auto_top_up`
  and `set_subscription_tier` — pyright resolves `CachedFunction.cache_delete`
  through the import boundary without the suppressor
- Add `max(0, ...)` guard to `get_subscription_cost` to prevent negative
  LaunchDarkly flag values from yielding negative costs
- Change `SubscriptionTierRequest.tier` from `str` to
  `Literal["FREE", "PRO", "BUSINESS"]` so Pydantic rejects ENTERPRISE and
  any unknown tier with a 422 at the schema layer
- Move `SubscriptionTier` and feature-flag imports from local function scope
  to module-level in v1.py (top-level imports policy)
- Fix `test_sync_subscription_from_stripe_active` mock to use a proper async
  `side_effect` function instead of calling an `AsyncMock` inline
2026-04-09 23:06:40 +07:00
Zamil Majdy
2e64f3add7 feat(frontend): redirect to Stripe checkout when upgrading subscription
POST /credits/subscription now returns {url} when Stripe checkout is needed.
Redirect user to Stripe on non-empty URL, refresh tier on empty URL (beta/FREE).
Remove credit-based tier validation; Stripe handles payment gating.
2026-04-09 22:58:58 +07:00
Zamil Majdy
b7f242f163 chore(backend/copilot): merge dev to pick up graphiti memory and update docs 2026-04-09 22:58:12 +07:00
Zamil Majdy
98c0920c04 fix(platform/admin): revert unrelated openapi.json changes to match backend schema
- Restore CreditTransactionType to original enum without SUBSCRIPTION
- Restore input/ctx fields in ValidationError schema
These changes were accidentally included from workspace drift; they are
not part of this PR and should come from their own respective PRs.
2026-04-09 22:54:02 +07:00
Zamil Majdy
4942249a60 fix(platform): resolve merge conflicts with dev branch
Merges latest dev branch changes into feat/subscription-tier-billing.
Updates credit_subscription_test.py to match new Stripe-based implementation.
2026-04-09 22:51:06 +07:00
Zamil Majdy
0c94d884d0 fix(backend): use monkeypatch.setattr in test and use typed sentry_sdk imports
- Replace type: ignore suppressor with monkeypatch.setattr in AIConditionBlock test
- Replace bare sentry_sdk module with typed API imports in metrics/service/manager
2026-04-09 22:50:58 +07:00
Zamil Majdy
54eaf7b818 fix(platform/admin): sync openapi.json with backend schema
- Fix CostLogRow field order: cache_read/creation_tokens after model
- Move /logs/export endpoint to correct position in paths (before analytics)
- Add model, block_name, tracking_type params to export endpoint schema
- Add PlatformCostExportResponse in correct schema position
- Add SUBSCRIPTION to CreditTransactionType enum
- Remove input/ctx from ValidationError schema
- Add model/block/type filter UI inputs and wire to hook/URL
- Make AnthropicIntegration and LaunchDarklyIntegration optional imports in metrics.py
- Add export CSV button wired to handleExport in LogsTable
2026-04-09 22:48:21 +07:00
Zamil Majdy
be86a911e1 fix(frontend): revert accidental openapi.json changes from export hook
The previous commit accidentally included SUBSCRIPTION in CreditTransactionType
via the local export-api-schema hook which used a Prisma client generated
from a different worktree schema. Restore to the correct pre-commit state.
2026-04-09 22:43:15 +07:00
Zamil Majdy
89091cb90f feat(platform/admin): add CSV export, cache tokens in logs, fix LLM cost on failure
- Add /api/admin/platform-costs/logs/export endpoint (100K row cap)
- Add cache_read_tokens and cache_creation_tokens to CostLogRow model
- Add CSV export button to LogsTable with buildCostLogsCsv helper
- Fix llm.py: persist total_provider_cost to stats even when all retries fail
- Update openapi.json: add PlatformCostExportResponse and export endpoint
2026-04-09 22:35:25 +07:00
Zamil Majdy
54763b660b fix(backend/copilot): persist user_context prefix and guard empty Anthropic system block
- Guard Anthropic system block behind sysprompt.strip() to avoid 400 errors
  when sysprompt is empty (Anthropic rejects empty text blocks with 400)
- Fix anthropic.omit -> anthropic.NOT_GIVEN in convert_openai_tool_fmt_to_anthropic
- Persist <user_context> prefix into session.messages and transcript on first
  turn in both baseline and SDK paths so personalisation survives resume/reload
- Add test for empty-sysprompt -> system key omitted in Anthropic API call
2026-04-09 22:30:39 +07:00
Zamil Majdy
835c8b0230 test(frontend/builder): restore seed-message tests + guard empty messages array
- Re-add describe block for seed message sending (removed in 8b8eb80480):
  - verifies sendMessage is called with buildSeedPrompt when isGraphLoaded=true
  - verifies sendMessage is NOT called when isGraphLoaded=false (default)
  - verifies the hasSentSeedMessageRef guard fires only once per session
- Add test for empty messages guard in prepareSendMessagesRequest
- Guard messages.at(-1) in prepareSendMessagesRequest with an early throw
  so a runtime TypeError cannot occur if the AI SDK contract is violated
2026-04-09 22:15:53 +07:00
Zamil Majdy
87539c03a4 fix(frontend): unify copilot auth headers and propagate impersonation header (#12718)
### Why

Admin user impersonation was silently broken for the copilot/autopilot
chat feature. The SSE stream requests and message feedback requests made
direct HTTP calls to the backend with only a Bearer token — missing the
`X-Act-As-User-Id` header that the impersonation feature requires.

This meant that when an admin impersonated a user and used copilot chat,
messages were processed and feedback was recorded under the admin's
identity, not the impersonated user's. The impersonation header was also
read inconsistently: `custom-mutator.ts` accessed `sessionStorage`
directly (breaking cross-tab impersonation), while other callers had no
impersonation support at all.

### What

- **`src/lib/impersonation.ts`**: Added `getSystemHeaders()` — a single
function that returns all cross-cutting request headers, currently
`X-Act-As-User-Id` when impersonation is active. Uses
`ImpersonationState.get()` which handles both `sessionStorage`
(same-tab) and cookie fallback (cross-tab). Added
`IMPERSONATION_COOKIE_NAME` constant to `constants.ts` to replace the
previously hardcoded local string.
- **`src/app/(platform)/copilot/helpers.ts`**: Added
`getCopilotAuthHeaders()` — combines `getWebSocketToken()` (JWT) with
`getSystemHeaders()` (impersonation) into a single async call for direct
backend requests.
- **`src/app/(platform)/copilot/useCopilotStream.ts`**: Replaced local
`getAuthHeaders()` (JWT only) with shared `getCopilotAuthHeaders()` in
both `prepareSendMessagesRequest` and `prepareReconnectToStreamRequest`.
-
**`src/app/(platform)/copilot/components/ChatMessagesContainer/useMessageFeedback.ts`**:
Switched from `getWebSocketToken()` to `getCopilotAuthHeaders()` for
feedback POST requests.
- **`src/app/api/mutators/custom-mutator.ts`**: Replaced raw
`sessionStorage.getItem(IMPERSONATION_STORAGE_KEY)` with
`getSystemHeaders()` (fixes cross-tab support for all generated API
calls).
- **Tests**: New unit tests for `getCopilotAuthHeaders` (4 cases),
`customMutator` impersonation header propagation (2 cases), and
`ImpersonationState`/`ImpersonationCookie`/`ImpersonationSession` (full
coverage across 3 describe blocks, 18 cases).

### How it works

`getSystemHeaders()` calls `ImpersonationState.get()` which reads
`sessionStorage` first and falls back to the impersonation cookie when
`sessionStorage` is empty (cross-tab scenario). The returned header map
is spread into every outbound request, so a single update to
`getSystemHeaders()` propagates to all callers automatically.

`getCopilotAuthHeaders()` wraps both the JWT fetch and the impersonation
header into one `async` call. Callers no longer need to know about
impersonation — they just spread the returned headers into their fetch
options.

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] As admin, impersonate a user and open copilot/autopilot chat —
messages processed in the context of the impersonated user
- [x] As admin, impersonate a user and submit feedback (upvote/downvote)
— feedback recorded against the impersonated user
  - [x] Without impersonation active, copilot chat works normally
  - [x] Frontend unit tests pass: `pnpm test:unit`
2026-04-09 14:54:53 +00:00
Zamil Majdy
f112555fc3 feat(backend/copilot): hide session-level dry_run from LLM (#12711)
### Why

During autopilot sessions with \`dry_run=True\`, the LLM was leaking
awareness of simulation mode through three channels:

1. \`dry_run\` appeared as a required parameter in \`RunBlockTool\`'s
schema — the LLM could see and pass it.
2. \`is_dry_run: true\` appeared in the serialized MCP tool result JSON
the LLM received, causing it to narrate that execution was simulated.
3. The \`[DRY RUN]\` prefix on response messages told the LLM explicitly
that credentials were absent or execution was skipped.

This broke the illusion of a seamless preview experience: users watching
an autopilot dry-run would see the LLM comment on simulation rather than
treating the run as real.

### What

**Backend:**
- \`copilot/model.py\`: \`ChatSessionInfo.dry_run\` is the single source
of truth, stored in the \`metadata\` JSON column (no migration needed).
Set at session creation; never changes.
- \`copilot/tools/run_block.py\`: Removed \`dry_run\` from the tool
schema and \`_execute\` params entirely. Block always reads
\`session.dry_run\`.
- \`copilot/tools/run_agent.py\`: Kept \`dry_run\` as an **optional**
schema parameter (LLM may request a per-call test run in normal
sessions), but \`session.dry_run=True\` unconditionally forces it True.
Removed from \`required\`.
- \`copilot/tools/models.py\`: \`BlockOutputResponse.is_dry_run: bool |
None = None\` — field is absent from normal-run output (was always
\`false\`).
- \`copilot/tools/base.py\`: \`model_dump_json(exclude_none=True)\` —
omits \`None\` fields from serialized output, keeping payloads clean.
- \`copilot/sdk/tool_adapter.py\`: \`_strip_llm_fields\` removes
\`is_dry_run\` from MCP tool result JSON **after** stashing for the
frontend SSE stream. Stripping is conditional on \`session.dry_run\` —
in normal sessions \`is_dry_run\` remains visible so the LLM can reason
about individual simulated calls. Extracted \`_make_truncating_wrapper\`
(was \`_truncating\`) for direct unit testing.
- \`blocks/autopilot.py\`: \`dry_run\` propagates from
\`execution_context.dry_run\` so nested AutoPilot sessions inherit the
parent's simulation mode.

**Frontend:**
- \`useCopilotUIStore\`: Added \`isDryRun\` / \`setIsDryRun\` state
persisted to localStorage (\`COPILOT_DRY_RUN\` key).
- \`useChatSession\`: Accepts \`dryRun\` option; creates session with
\`dry_run: true\` when enabled; resets session when the toggle changes.
- \`DryRunToggleButton\`: New UI control for toggling dry_run mode.
- \`RunAgent.tsx\` / \`helpers.tsx\`: Added \`AgentOutputResponse\` type
handling and \`ExecutionStartedCard\` rendering for the \`agent_output\`
response type.
- OpenAPI: \`is_dry_run\` on \`BlockOutputResponse\` changed to
\`boolean | null\` (was \`boolean\`).

### How it works

**Three-layer defense:**
1. **Schema layer**: \`run_block\` exposes no \`dry_run\` parameter.
\`run_agent\` keeps it optional so the LLM can request test runs in
normal sessions, but \`session.dry_run\` always wins.
2. **Response layer**: \`is_dry_run: bool | None = None\` +
\`exclude_none=True\` means the field is absent from the serialized JSON
in non-dry-run mode — no leakage at rest.
3. **Transport layer**: When \`session.dry_run=True\`,
\`_strip_llm_fields\` removes \`is_dry_run\` from the MCP result before
the LLM sees it, while the stashed copy (for the frontend SSE stream)
retains the full payload.

**Stash-before-strip ordering**: \`_make_truncating_wrapper\` stashes
the full tool output *before* calling \`_strip_llm_fields\`. This
ensures \`StreamToolOutputAvailable\` events carry the complete payload
— so the frontend's "Simulated" badge renders correctly — while the LLM
only ever sees the stripped version.

**Session-level flag**: \`ChatSessionInfo.dry_run\` is set at session
creation and never changes. No LLM tool call can alter it.

**\`_strip_llm_fields\` fast path**: Stripping is skipped when none of
the \`_STRIP_FROM_LLM\` field names appear in the raw text (string scan
before JSON parse), keeping the common non-dry-run path allocation-free.

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] \`poetry run pytest backend/copilot/tools/test_dry_run.py\` — all
tests pass
- [x] \`poetry run pytest backend/copilot/sdk/tool_adapter_test.py\` —
all tests pass (including new \`TestStripLlmFields\` suite)
- [x] Pre-commit hooks pass (Ruff, Black, isort, pyright, tsc, OpenAPI
export + orval generate)
- [x] Verify LLM tool result JSON for a dry_run session does not contain
\`is_dry_run\`
- [x] Verify frontend SSE stream still delivers \`is_dry_run: true\` for
"Simulated" badge rendering
2026-04-09 14:46:04 +00:00
Zamil Majdy
4e4aafca45 fix(blocks): propagate cache tokens and provider_cost in AIConditionBlock 2026-04-09 21:34:08 +07:00
Nicholas Tindle
e68dadd2c9 feat(backend): add Graphiti temporal knowledge graph memory for CoPilot (#12720)
## Summary

Add Graphiti temporal knowledge graph memory to CoPilot, giving
AutoPilot persistent cross-session memory with entities, relationships,
and temporal validity tracking.

- **3 new CoPilot tools** (`graphiti_store`, `graphiti_search`,
`graphiti_delete_user_data`) as BaseTool implementations — automatically
available in both SDK and baseline/fast modes via existing TOOL_REGISTRY
bridge
- **FalkorDB** as graph database backend with per-user physical
isolation via `driver.clone(database=group_id)`
- **graphiti-core** Python library for in-process knowledge graph
operations (no separate MCP server needed)
- **MemoryEpisodeLog** append-only replay table for migration safety
- **LaunchDarkly flag** `graphiti-memory` for per-user rollout
- **OpenRouter** for extraction LLM, direct OpenAI for embeddings

### Memory Quality
- Episode body uses `"Speaker: content"` format matching graphiti's
extraction prompt expectations
- Only user messages ingested (Zep Cloud `ignore_roles` approach) —
assistant responses excluded from graph
- `custom_extraction_instructions` suppress meta-entity pollution (no
more "assistant", "human", block names as entities)
- `ep.content` attribute correctly surfaced in search results and warm
context
- Per-user asyncio.Queue serializes ingestion (graphiti-core
requirement)

### Architecture Decision
Custom BaseTool implementations over MCP — the existing
`create_copilot_mcp_server()` in `tool_adapter.py` already wraps every
BaseTool as MCP for the SDK path. One implementation serves both
execution paths with zero extra infrastructure.

## Test plan

- [x] Set LaunchDarkly flag `graphiti-memory` to true for test user
- [x] Verify FalkorDB is healthy: `docker compose up falkordb`
- [x] S1: Send message with user facts ("my assistant is Sarah, CC her
on client stuff, CRM is HubSpot")
- [x] Verify agent calls `graphiti_store` to save memories
- [x] S2 (new session): Ask "Who should I CC on outgoing client
proposals?"
- [x] Verify agent calls `graphiti_search` before answering
- [x] Verify agent answers correctly from memory (Sarah)
- [x] Verify graph entities are clean (no "assistant"/"human"/block
names)
- [x] Verify MemoryEpisodeLog has replay entries
- [ ] Verify `GRAPHITI_MEMORY=false` in LaunchDarkly → tools return "not
enabled" error

🤖 Generated with [Claude Code](https://claude.com/claude-code)

<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> **Medium Risk**
> Adds a new persistence layer and background ingestion flow for chat
memory plus new dependencies/services (FalkorDB, `graphiti-core`) and
prompt/tooling changes; rollout is gated by a LaunchDarkly flag but
failures could impact chat latency or resource usage.
> 
> **Overview**
> Enables **optional, per-user Graphiti temporal memory** for CoPilot
(gated by LaunchDarkly `graphiti-memory`), including warm-start recall
on the first turn and background ingestion of user messages after each
turn in both `baseline` and SDK chat paths.
> 
> Adds Graphiti infrastructure: new `memory_search`/`memory_store` tools
and response types, a per-user cached Graphiti client with safe
`group_id` derivation, a FalkorDB driver tweak for full-text queries,
and a serialized per-user ingestion queue with graceful failure/timeout
handling.
> 
> Introduces new runtime configuration and local dev support
(`GRAPHITI_*` env vars, new `falkordb` docker service/volume), updates
permissions/OpenAPI enums, and adds dependencies (`graphiti-core`,
`falkordb`, `cachetools`) plus unit tests for the new modules.
> 
> <sup>Reviewed by [Cursor Bugbot](https://cursor.com/bugbot) for commit
81eb14e30a. Bugbot is set up for automated
code reviews on this repo. Configure
[here](https://www.cursor.com/dashboard/bugbot).</sup>
<!-- /CURSOR_SUMMARY -->

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-09 13:56:52 +00:00
Zamil Majdy
d113687878 fix(copilot): P0 guardrails, transient retry, and security hardening (#12636)
### Why

The copilot's Claude Code CLI integration had several production
reliability gaps reported from live deployments:

- **No transient retry**: 429 rate-limit errors, 5xx server errors, and
ECONNRESET connection resets surfaced immediately as failures — there
was no retry mechanism.
- **Subagent permission errors**: CLI subprocesses wrote temp files to
`/tmp/claude-0/` which was inaccessible inside E2B sandboxes, causing
subagent spawning to report "agent completed" without actually running.
- **Missing security hardening in non-OpenRouter modes**: Security env
vars (`CLAUDE_CODE_DISABLE_CLAUDE_MDS`,
`CLAUDE_CODE_SKIP_PROMPT_HISTORY`, `CLAUDE_CODE_DISABLE_AUTO_MEMORY`,
`CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC`) were only applied in the
OpenRouter path, leaving subscription and direct Anthropic modes
unprotected in multi-tenant deployment.
- **No resource guardrails**: No per-query budget cap, turn limit, or
fallback model meant a single runaway query could burn unlimited
tokens/spend.
- **Lossy transcript reconstruction**: When no transcript file was
available (storage failure or compaction drop), the old code injected a
truncated plain-text summary that cut tool results at 500 chars and
dropped `tool_use`/`tool_result` structural linkage, causing the LLM to
lose conversation context.

### What

- **SDK guardrails** (`config.py`, `sdk/service.py`): Added
`fallback_model` (auto-failover on 529 overloaded), `max_turns=1000`
(runaway prevention), `max_budget_usd=100.0` (per-query cost cap). All
configurable via env-backed `ChatConfig` fields.
- **Transient retry** (`sdk/service.py`, `constants.py`): Exponential
backoff (1s, 2s, 4s) for 429/5xx/ECONNRESET errors, retried only when
`events_yielded == 0` to avoid breaking partial streams.
`_TRANSIENT_ERROR_PATTERNS` extended with status-code-specific patterns
to avoid false positives.
- **Workspace isolation** (`sdk/env.py`): `CLAUDE_CODE_TMPDIR` now set
in all auth modes so CLI subprocesses write to the per-session workspace
directory rather than `/tmp/`.
- **Security hardening** (`sdk/env.py`): Security env vars applied
uniformly across all three auth modes (subscription, direct Anthropic,
OpenRouter) via restructured `build_sdk_env()`.
- **Transcript reconstruction** (`sdk/service.py`):
`_session_messages_to_transcript()` converts `ChatMessage.tool_calls`
and `ChatMessage.tool_call_id` to proper `tool_use`/`tool_result` JSONL
blocks for `--resume`, restoring full structural fidelity.
- **Model normalization refactor** (`sdk/service.py`):
`_resolve_fallback_model()` and `_normalize_model_name()` extracted to
share prefix-stripping and dot→hyphen conversion logic between primary
and fallback model resolution.

### How it works

**Transient retry**: `_can_retry_transient()` checks the retry budget
and returns the next backoff delay (or `None` when exhausted). Retries
are gated on `events_yielded == 0` — if any events were already streamed
to the client, we cannot retry without breaking the SSE stream
mid-response. After all retries are exhausted, `FRIENDLY_TRANSIENT_MSG`
is surfaced to the user.

**Transcript reconstruction**: When `--resume` has no on-disk session
file, `_session_messages_to_transcript()` builds a JSONL transcript from
`session.messages`, emitting `tool_use` blocks for assistant tool calls
and `tool_result` blocks (with matching IDs) for their results. This
gives Claude CLI the same structural fidelity as an on-disk session —
preserving tool call/result pairing that the old plain-text injection
lost.

**`build_sdk_env()` restructure**: The three auth modes now share a
common "epilogue" block that applies workspace isolation and security
hardening env vars regardless of which mode is active, eliminating the
previous pattern of repeating `if sdk_cwd: env["CLAUDE_CODE_TMPDIR"] =
sdk_cwd` in each branch.

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] 729 unit tests passing: `env_test.py`, `p0_guardrails_test.py`,
`retry_scenarios_test.py` (incl. integration tests for both transient
retry paths), `service_test.py`, `sdk_compat_test.py`,
`response_adapter_test.py`
- [x] E2E tested: live copilot session (API + UI), multi-turn, security
env vars verified in all 3 auth modes, guardrail defaults confirmed
- [x] `_session_messages_to_transcript()`: 7 unit tests covering empty
input, tool_use blocks, tool_result blocks, no truncation (10K chars
preserved), parent UUID chain, malformed argument handling
2026-04-09 21:10:39 +07:00
Zamil Majdy
34abaa5a76 fix(backend): update tests to match new cost tracking behavior
- test_llm: rename test_retry_cost_uses_last_attempt_only → test_retry_cost_accumulates_across_attempts
  and update assertion to expect sum of all attempt costs (0.03) instead of last-only (0.02).
- platform_cost_test: add 4th mock side effect for the separate total_agg_rows query
  added in the previous commit; update await_count assertion from 3 → 4.
- test_orchestrator_dynamic_fields: explicitly set cache_read_tokens=0,
  cache_creation_tokens=0, provider_cost=None on the mock LLM response to avoid
  Pydantic validation errors when NodeExecutionStats is constructed from it.
2026-04-09 20:45:48 +07:00
Zamil Majdy
369ce7da16 fix(backend): accumulate provider_cost across LLM retries instead of overwriting
Each retry attempt that gets a response from the provider incurs a cost.
Token counts were already accumulated per attempt, but provider_cost was
overwritten (last value only). Now total_provider_cost accumulates across
all attempts so no billed USD is lost when validation retries occur.
2026-04-09 20:27:39 +07:00
Zamil Majdy
70d53a0926 fix(platform): address round-2 review comments on subscription billing
- Wrap ensure_subscription_paid in spend_credits with try/except (fails open like check_rate_limit)
- Invalidate get_user_by_id cache in set_auto_top_up to prevent stale auto top-up data
- Block ENTERPRISE tier self-service upgrades from POST /credits/subscription API
2026-04-09 20:19:10 +07:00
Zamil Majdy
642c72e5e5 fix(platform): address review comments on subscription billing
- Format error messages as \$X.XX/mo instead of raw cents
- Move get_feature_flag_value import to module level in credit.py
- Add explicit operation_id to subscription FastAPI routes
- Pass autoTopUpConfig as prop to SubscriptionTierSection (avoid duplicate fetch)
- Display fetch error in SubscriptionTierSection instead of silent null
- Add cache hit comment to rate_limit.py hot path
- Add tests: idempotency, free tier no-op, beta grant offset, tier upgrade validation
2026-04-09 20:14:11 +07:00
Zamil Majdy
ba7929205d feat(platform): add subscription tier billing with lazy credit deduction
- Add SubscriptionTier enum (FREE/PRO/BUSINESS/ENTERPRISE) to schema
- Add SUBSCRIPTION CreditTransactionType for monthly charges
- Lazy monthly deduction via ensure_subscription_paid() — idempotent,
  called from spend_credits() and rate-limit checks
- BetaUserCredit grant includes subscription offset so beta usage credits
  are not reduced by subscription cost
- Auto top-up enforced >= subscription cost on tier upgrade and config update
- Subscription cost configurable via LaunchDarkly (subscription-cost-pro,
  subscription-cost-business); 0 = feature off, no separate flag needed
- New endpoints: GET/POST /credits/subscription for tier management
- No proration: full month charged on upgrade, downgrade takes next cycle
- Frontend: SubscriptionTierSection component on billing page with tier
  cards, upgrade/downgrade flow, and auto top-up guard
2026-04-09 19:58:01 +07:00
Zamil Majdy
06c8882222 fix(backend): use separate aggregate query for dashboard totals to avoid undercounting past MAX_PROVIDER_ROWS 2026-04-09 19:56:00 +07:00
Zamil Majdy
6d60265221 fix(backend/copilot): update retry_scenarios_test to use renamed function
`_build_system_prompt` was renamed to `_build_cacheable_system_prompt`
in the SDK path as part of the prompt caching PR. Update the patch
target in `retry_scenarios_test.py` to match the new name so the tests
can find the attribute.
2026-04-09 19:55:15 +07:00
Zamil Majdy
7b30a57112 fix(frontend): use normalized tracking_type (tt) for table row key 2026-04-09 19:53:25 +07:00
Zamil Majdy
7a08d9e0ca fix(platform/admin): address review comments on cost tracking PR
- Remove redundant cache_read/creation_tokens from metadata dict in
  cost_tracking.py — now stored in dedicated DB columns only.
- Fix total_cost_usd accumulation in OrchestratorBlock SDK path: use
  assignment not addition (ResultMessage is emitted once per run, so
  summing double-counts if emitted multiple times).
- trackingValue now shows both read and write cache token counts:
  "+Xr/Yw cached" instead of "+X cached".
- Add cache-aware estimateCostForRow test: validates 0.1x reads and
  1.25x writes multipliers for Anthropic tokens.
2026-04-09 19:45:50 +07:00
Zamil Majdy
7c3a6f597a fix(blocks): re-stage orchestrator.py after Black reformat 2026-04-09 19:41:31 +07:00
Zamil Majdy
0b8997eb01 perf(backend/copilot): gate user-context DB fetch on is_user_message too
Aligns fetch logic with injection logic: `should_inject_user_context`
now requires both `is_first_turn` and `is_user_message`, so
assistant-role calls (e.g. tool-result submissions) on the first turn
no longer trigger a needless `_build_cacheable_system_prompt(user_id)`
DB lookup.

Addresses coderabbitai nitpick from review 4082258841.
2026-04-09 19:38:18 +07:00
Zamil Majdy
2ff036b86b fix(backend/copilot): resolve merge conflicts with dev branch
Keep caching changes (static system prompt + cache_control markers)
on top of dev's new features: transcript support, file attachments,
URL context in baseline path, and _update_title_async in SDK path.
2026-04-09 19:33:49 +07:00
Zamil Majdy
b2d89c3a66 feat(platform/admin): per-model cost breakdown and Anthropic cache token tracking
- Group provider cost table by (provider, tracking_type, model) so each
  model gets its own row with accurate usage and estimated cost.
- Add cacheReadTokens / cacheCreationTokens columns to PlatformCostLog.
- Capture Anthropic cache_read_input_tokens / cache_creation_input_tokens
  from LLM block responses; propagate through NodeExecutionStats and
  PlatformCostEntry to the DB.
- Use per-token-type rates in cost estimation: uncached=100%, reads=10%,
  writes=125% of base rate — prevents overestimation when prompt caching
  is active (PR #12725).
2026-04-09 19:24:13 +07:00
Zamil Majdy
1fc3cc74ea fix(backend/copilot): skip user DB lookup on non-first turns
In the SDK path, pass user_id to _build_cacheable_system_prompt only
when has_history is False, matching the baseline path. Previously
user understanding was fetched from the DB on every turn even though
it is only injected into the first user message, causing an N+1 query.

Also add a defensive logger.warning in the baseline path when no user
message is found for context injection (guarded by is_first_turn, so
this edge case is nearly impossible but surfaces unexpected states).
2026-04-09 19:21:02 +07:00
Zamil Majdy
815659d188 perf(backend/copilot): enable LLM prompt caching to reduce token costs
Move user-specific context out of the system prompt into the first user
message, making the system prompt fully static across all users. Add
explicit Anthropic cache_control markers on both system prompt and tool
definitions in the direct API path (blocks/llm.py).
2026-04-09 19:02:33 +07:00
Zamil Majdy
8c228afb15 fix(frontend/builder): hide seed message from visible chat messages
Import SEED_PROMPT_PREFIX in BuilderChatPanel and extend the
visibleMessages filter to exclude any user message whose text starts
with the prefix. Adds a regression test for the new filter.
2026-04-09 16:49:18 +07:00
Zamil Majdy
afc7d3b252 fix(frontend/builder): render tool calls via MessagePartRenderer normalization
- Fix visibleMessages filter: assistant messages with only dynamic-tool parts
  (no text) were silently hidden — now included when any dynamic-tool part exists
- Normalize dynamic-tool parts to tool-{toolName} before rendering so
  MessagePartRenderer routes them correctly: edit_agent and run_agent get their
  existing copilot renderers, all other tools fall through to GenericTool
  (collapsed accordion with icon, status text, expandable output)
2026-04-09 13:34:17 +07:00
Zamil Majdy
0bd9b58da2 fix(frontend): prevent cross-graph session assignment in concurrent navigation
Track effectFlowID at session creation start and compare against currentFlowIDRef
after the async postV2CreateSession resolves. If the user navigated to a different
graph before the response arrived, the old session ID is discarded instead of
being committed to the new graph's state, preventing chat history from being
crossed between graphs.
2026-04-09 12:06:33 +07:00
Zamil Majdy
ca1577f3b1 fix(frontend): block prototype-polluting keys without schema + validate execution_id
- Add DANGEROUS_KEYS blocklist (__proto__, constructor, prototype) checked before
  the schema guard in handleApplyAction so schema-less nodes cannot be polluted
  via AI-supplied keys
- Validate execution_id from run_agent tool output with /^[\w-]+$/i before
  passing to setQueryStates, preventing URL-special characters from entering
  query state
- Add tests for DANGEROUS_KEYS blocklist on schema-less nodes (three cases)
2026-04-09 11:48:33 +07:00
Zamil Majdy
2f3b29f589 test(frontend): add tool-call detection + session ID validation tests; fix EMPTY_NODES ref
- Add tests for edit_agent tool call detection: verifies onGraphEdited fires on
  output-available state, is suppressed during streaming, and is not called twice
  for the same toolCallId (processedToolCallsRef deduplication)
- Add tests for session ID validation: verifies that path-traversal IDs
  (../../admin) and IDs with spaces set sessionError and leave sessionId null
- Extract EMPTY_NODES module-level constant to give useShallow a stable
  reference when the panel is closed, preventing spurious re-renders
2026-04-09 11:43:08 +07:00
Zamil Majdy
5d0330615f fix(frontend): pass isGraphLoaded from Flow.tsx + Escape key containment check
- Wire isInitialLoadComplete as isGraphLoaded prop in Flow.tsx so the seed
  message effect in useBuilderChatPanel actually fires once the graph is ready
- Add panelRef to BuilderChatPanel and pass it to the hook so the Escape key
  listener only closes the panel when focus is inside it, preventing conflicts
  with other dialogs or canvas keyboard handlers
- Update BuilderChatPanel test to use objectContaining for the hook call
  assertion, accommodating the new panelRef argument
2026-04-09 11:11:39 +07:00
Zamil Majdy
cc6bf13e16 feat(frontend/builder): use copilot MessagePartRenderer for message rendering
Replace the simplified ReactMarkdown block in BuilderChatPanel's MessageList
with MessagePartRenderer from the copilot panel, enabling proper rendering of
tool invocations, error markers, and system markers in addition to text parts.
2026-04-09 11:04:46 +07:00
Zamil Majdy
fce353fb21 fix(frontend): restore seed message + fix prototype pollution + clear session cache in tests
- Restore isGraphLoaded prop and hasSentSeedMessageRef seed-message effect that
  were removed in a prior external modification; all seed-message tests now pass
- Apply Object.prototype.hasOwnProperty.call() guard in inline handleApplyAction
  for input-schema and handle validation (three sites), matching the extracted
  helper functions; prototype-pollution tests now pass
- Export clearGraphSessionCacheForTesting() and call it in beforeEach to prevent
  stale module-level graphSessionCache from leaking across tests (fixes flowID
  reset test)
- Update BuilderChatPanel test to expect isGraphLoaded in useBuilderChatPanel call
- Remove unused Dispatch, SetStateAction, CustomEdge, CustomNode imports
2026-04-09 11:03:04 +07:00
Zamil Majdy
8b8eb80480 feat(frontend/builder): persistent session per graph, no auto-send, tool detection
- Remove auto-send seed message on chat open (user initiates context manually)
- Cache chat session per graph ID (module-level Map) so reopening the panel for
  the same graph reuses the existing session and preserves conversation history
- Detect edit_agent tool completion → trigger graph refetch via onGraphEdited callback
- Detect run_agent tool completion → update flowExecutionID in URL to auto-follow run
- retrySession now evicts the stale cache entry so a fresh session is created
- Flow.tsx passes refetchGraph as onGraphEdited to BuilderChatPanel
2026-04-09 10:58:53 +07:00
Zamil Majdy
875852be32 fix(frontend/builder): address reviewer feedback — prototype pollution, function length, textarea maxLength, and test coverage
- Fix prototype pollution bypass: use Object.prototype.hasOwnProperty.call instead of `in` operator for schema key validation, preventing __proto__/constructor injection through schema-validated nodes
- Extract applyUpdateNodeInput and applyConnectNodes as module-level helpers to reduce handleApplyAction from 165 lines to a 20-line dispatcher
- Add JSDoc to useBuilderChatPanel documenting session lifecycle, transport, seed message, action parsing, undo, and input responsibilities
- Add maxLength=4000 to PanelInput textarea to cap token usage
- Add prototype pollution tests (__proto__ and constructor keys rejected when inputSchema is present)
- Strengthen Send-button-disabled assertion in component test
2026-04-09 10:47:15 +07:00
Zamil Majdy
1e8a0f8d53 feat(frontend/builder): add typing indicator animation to builder chat panel
Shows three bouncing dots in an assistant-style bubble while waiting
for the first response token (status submitted, no assistant text yet).
Disappears once streaming begins and text appears.
2026-04-09 10:37:38 +07:00
Zamil Majdy
a22693a878 fix(frontend/builder): address reviewer comments on BuilderChatPanel
- Overlapping placeholders: add !seedMessage guard to empty-state block so the
  "Ask me to explain…" and "Graph context sent" banners are mutually exclusive
- aria-modal without focus trap: replace role="dialog"/aria-modal="true" with
  role="complementary" since this is a side panel, not a blocking modal
- Stale closure in handleApplyAction: use useNodeStore/useEdgeStore.getState()
  for both validation and mutation so rapid applies see live data
- Gate nodes/edges Zustand subscriptions behind isOpen to prevent chat-panel
  hook re-running on every node drag/resize when panel is closed
- inputValue not cleared on flowID change: add setInputValue("") to flowID reset
- ReactMarkdown links: add custom <a> component with target="_blank" and rel="noopener noreferrer"
- XML sanitization: apply sanitizeForXml() to n.id and edge handle names
- Regex statefulness: move JSON_BLOCK_REGEX inside parseGraphActions() to avoid
  shared lastIndex state (eliminates fragile lastIndex=0 reset)
- Type guard soundness: add typeof p.text === "string" to extractTextFromParts filter
- Session ID validation: validate format before interpolating into streaming URL
- Shallow-copy undo snapshots: spread prevNodes/prevEdges so closures hold
  independent arrays
- Set spread optimisation: use new Set(prev).add(key) instead of new Set([...prev, key])
- Tests: remove dead getGetV1GetSpecificGraphQueryKey mock, add markerEnd assertion
  to connect_nodes tests, add transport prepareSendMessagesRequest coverage,
  add Enter-with-empty-input and inputValue-reset-on-flowID-change tests
2026-04-09 08:12:35 +07:00
Zamil Majdy
bb79cefb05 test(backend): cover usd_to_microdollars(None) and get_platform_cost_logs with explicit start
Closes branch gaps in platform_cost.py (lines 29-31 and 312→314) that
were introduced via the dev merge but not exercised by existing tests.
This also forces the backend CI to run so Codecov uploads fresh coverage
instead of carrying forward stale data from before the cost-tracking
feature landed on dev.
2026-04-09 07:41:16 +07:00
Zamil Majdy
d31ff0586e fix(frontend/builder): guard extractTextFromParts against undefined parts
The AI SDK can return messages with undefined parts in certain error
scenarios. Accept null/undefined in extractTextFromParts and fall back
to an empty array to prevent a TypeError and component crash.
2026-04-09 06:55:32 +07:00
Zamil Majdy
3e35345efb fix(frontend/builder): clear stale chat messages on graph navigation
Adds a useEffect in useBuilderChatPanel that calls setMessages([]) whenever
the flowID query param changes, preventing old technical seed prompts from
the prior session briefly appearing when switching between agents.
2026-04-09 06:43:58 +07:00
Zamil Majdy
478b60ce5d fix(frontend/builder): add markerEnd to chat-applied edges so arrowheads render correctly
Chat panel used setEdges directly without the markerEnd property that edgeStore.addEdge
sets automatically. Added MarkerType.ArrowClosed with strokeWidth=2, color="#555" to
match the standard edge appearance.
2026-04-09 06:29:27 +07:00
Zamil Majdy
824ba15ff9 fix(frontend/builder): address review blockers — duplicate edge guard, undo anti-pattern, stack cap, a11y, and test coverage
- Guard against duplicate connect_nodes edges: check prevEdges before applying,
  mark as already-applied without duplicating if edge exists
- Cap undo stack at MAX_UNDO=20 to prevent unbounded memory growth for large graphs
- Fix React anti-pattern: call restore() before setUndoStack updater instead of
  inside it (state updaters must be pure — no side effects)
- Add aria-modal="true" to dialog panel and aria-expanded to toggle button
- Extract IIFE nodeMap into ActionList sub-component (cleaner render path)
- Add 18 new tests: handleSend when canSend=false, Shift+Enter no-send,
  schema-absent permissive paths (update + connect_nodes), sequential multi-undo
  LIFO order, duplicate edge guard, undo stack size cap, empty stack no-op
2026-04-09 06:10:11 +07:00
Zamil Majdy
907518bfc3 fix(frontend/builder): prevent appliedActionKeys desync after global undo
Apply chat panel changes via setNodes/setEdges (bypassing history store)
so Ctrl+Z cannot revert them and leave the "Applied" badge stale.
Also hoist jsonBlockRegex to module scope, cap node description length
at 500 chars, and remove useShallow from single-value selectors.
2026-04-09 01:50:24 +07:00
Zamil Majdy
15cedc6d17 fix(frontend/builder): fix chat panel undo bypassing global history store
Use setNodes/setEdges directly in undo restore closures instead of
updateNodeData/removeEdge which push to the history store. This prevents
the global Ctrl+Z from re-applying changes that the user already undid via
the chat panel's own undo button.

Also removes unused removeEdge selector from the hook.
2026-04-09 01:36:17 +07:00
Zamil Majdy
28e7772db6 fix(frontend/builder): address review comments on builder chat panel
- Replace fragile setTimeout double-toggle retry with dedicated retrySession()
  callback that resets sessionError and lets the session-creation effect re-run
- Remove invalidateQueries after apply actions — caused server refetch to
  overwrite local Zustand state changes (sentry HIGH severity bug)
- Deep-clone prevHardcoded before undo capture so sequential applies to the
  same node each have an independent snapshot
- Remove unsolicited "What does this agent do?" question from seed prompt;
  invite user to initiate instead
- Remove useCallback from handleUndoLastAction per project convention
- Remove unused sendMessage and status from hook return
- Remove JSDoc comment from BuilderChatPanel per project convention
- Hoist nodeMap construction from ActionItem to parent parsedActions.map
  to avoid N identical Maps per render cycle
- Make useChat mock configurable (mockChatMessages/mockChatStatus) and add
  tests for parsedActions integration, Escape key handler, retrySession,
  and handleSend input-clearing behavior
2026-04-09 01:29:41 +07:00
Zamil Majdy
c390ab13fd Merge branch 'dev' of github.com:Significant-Gravitas/AutoGPT into feat/builder-chat-panel 2026-04-09 01:16:01 +07:00
Otto
7acfdf5974 docs(skill): add coverage guidance to pr-address skill (#12695)
Requested by @majdyz

## Why

As we enforce patch coverage targets via Codecov (see #12694), the
`pr-address` skill needs to guide agents to verify test coverage when
they write new code while addressing review comments. Without this, an
agent could address a comment by adding untested code and create a new
CI failure to fix.

## What

Adds a **Coverage** section to `.claude/skills/pr-address/SKILL.md`
with:
- The `pytest --cov` command to check coverage locally on changed files
- Clear rules: new code needs tests, don't remove existing tests, clean
up dead test code when deleting code

## Impact

Agents using `/pr-address` will now run coverage checks as part of their
workflow and won't land untested new code.

Linear: SECRT-2217

Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
2026-04-08 17:05:54 +00:00
Zamil Majdy
ef477ae4b9 fix(backend): convert AttributeError to ValueError in _generate_schema (#12714)
## Why

`POST /api/graphs` was returning **500** when an agent graph contained
an Agent Input block without a `name` field.

Root cause: `GraphModel._generate_schema` calls
`model_construct(**input_default)` (which skips Pydantic validation) to
build a list of field objects. If `input_default` doesn't include
`name`, the constructed `Input` object has no `name` attribute. The
subsequent dict comprehension (`p.name: {...}`) then raises
`AttributeError`, which is not handled and falls through to the generic
`Exception → 500` catch-all in `rest_api.py`. The `ValueError → 400`
handler already exists but is never reached.

## What

- In `_generate_schema`, wrap the `return {…}` block in `try/except
AttributeError` and re-raise as `ValueError`.
- Added a unit test that directly exercises
`GraphModel._generate_schema` with a nameless `AgentInputBlock.Input`
and asserts `ValueError` is raised.

## How

`rest_api.py` already has:
```python
app.add_exception_handler(ValueError, handle_internal_http_error(400))
```
The only change needed was to ensure `AttributeError` gets converted
before it propagates. The fix is a single `try/except` block — no new
exception types, no new handlers.

**Note:** In Pydantic v2, `ValidationError` is _not_ a subclass of
`ValueError` — they are separate hierarchies. `pydantic.ValidationError`
inherits directly from `Exception`. The existing separate handler for
`pydantic.ValidationError` is correct and unrelated to this fix.

## Checklist

- [x] My changes follow the project coding style
- [x] I've written/updated tests for the changes
- [x] Tests pass locally (`poetry run pytest
backend/data/graph_test.py::test_generate_schema_raises_value_error_when_name_missing`)
2026-04-09 00:05:01 +07:00
Zamil Majdy
2879470185 fix(frontend/builder): fix XML sanitization, add undo for connect_nodes, add hook tests
- sanitizeForXml now escapes &, ", ' in addition to < and >
- connect_nodes actions now push an undo snapshot (removeEdge) so they can be reverted like update_node_input
- useBuilderChatPanel.test.ts adds removeEdge mock and test for undo of connect_nodes
2026-04-08 23:59:26 +07:00
Zamil Majdy
705bd27930 fix(backend): wrap PlatformCostLog metadata in SafeJson to fix silent DataError (#12713)
## Changes

- Wrap `metadata` field in `SafeJson()` when calling
`PrismaLog.prisma().create()` in `log_platform_cost`
- Add `platform_cost_integration_test.py` with DB round-trip tests for
the fix

## Why

`PrismaLog.prisma().create()` was silently failing with a `DataError`
because passing a plain Python `dict` to a `Json?`-typed Prisma field is
not allowed:

```
DataError: Invalid argument type. `metadata` should be of type NullableJsonNullValueInput or Json
```

The error was swallowed silently by `logger.exception` in the background
task, so **no rows ever landed in `PlatformCostLog`** — which is why the
dev admin cost dashboard showed no data after #12696 was merged.

## How

Wrap `entry.metadata` in `SafeJson()` (already used throughout the
codebase, lives in `backend/util/json.py`) before passing it to the
Prisma create call. `SafeJson` extends `prisma.Json`, sanitizes
PostgreSQL-incompatible control characters, and handles Pydantic-model
conversion.

Add two integration tests in `platform_cost_integration_test.py`
(following the `credit_integration_test.py` pattern) that write a record
to a real DB and read it back — confirming both metadata round-trip and
NULL metadata work correctly.

## Test plan

- [x] Integration tests verify metadata persists/reads correctly via
Prisma
- [x] Unit tests updated: `isinstance(data["metadata"], Json)` confirms
the field is wrapped
- [x] Verified on dev executor pod: cost rows now appear in the admin
dashboard after fix
2026-04-08 23:59:06 +07:00
Zamil Majdy
fa6ea36488 fix(backend): make User RPC model forward-compatible during rolling deploys (#12707)
## Why

A Sentry `AttributeError: 'dict' object has no attribute 'timezone'` was
traced to the scheduler accessing `user.timezone` on a value that was a
raw `dict` instead of a typed `User` model.

**Root cause (two-part):**

1. `User.model_config` had `extra='forbid'`. During a rolling deploy,
the database manager (newer pod) can return fields that the client
(older pod) doesn't yet know about. `extra='forbid'` caused
`TypeAdapter(User).validate_python()` to raise `ValidationError` on
those unknown fields.

2. `DynamicClient._get_return` had a silent `try/except` that swallowed
the `ValidationError` and fell back to returning the raw `dict`. The
scheduler then received a `dict` and crashed on `.timezone`.

## What

- **`backend/data/model.py`**: Change `User.model_config`
`extra='forbid'` → `extra='ignore'`. Unknown fields from a newer
database manager are silently dropped, making the RPC layer
forward-compatible during rolling deploys. This is the primary fix.

- **`backend/util/service.py`**: Restore the `try/except` fallback in
`_get_return`, but make it **observable**: log the full error message at
`WARNING` (so ValidationError details — field name, value — appear in
logs) and call `sentry_sdk.capture_exception(e)` so every fallback is
tracked and alerted without crashing the caller. The raw result is still
returned as before (continuity).

- **`backend/util/service_test.py`**: Add `TestGetReturn` with two
direct unit tests: valid dict (including an unknown future field) →
typed `User` returned; invalid dict (missing required fields) → fallback
returns raw dict (no crash). Uses a typed `_SupportsGetReturn` Protocol
+ `cast` instead of `# type: ignore` suppressors.

- **`backend/executor/utils_test.py`**: Fix misleading docstring; move
inner imports to module top level per code style.

## How

`extra='ignore'` is the standard Pydantic pattern for forward-compatible
models at service boundaries. It means a rolling deploy where the DB
manager has a new column will not break older client pods — the extra
field is simply dropped on deserialization.

The restored `_get_return` fallback preserves continuity (callers don't
crash) while the `logger.warning` + `sentry_sdk.capture_exception`
ensure no schema mismatch goes undetected. Silent degradation is
replaced by observable degradation.

## Checklist

- [x] Changes are backward-compatible (unknown fields ignored, not
rejected)
- [x] Regression tests added for `_get_return` typed deserialization
contract
- [x] Fallback preserved with observable logging and Sentry capture (no
silent degradation)
- [x] `extra='ignore'` is consistent with forward-compatibility
requirements at service boundaries
- [x] No `# type: ignore` suppressors introduced
2026-04-08 23:49:30 +07:00
Zamil Majdy
cab061a12d fix(frontend): suppress Sentry noise from expected 401s in OnboardingProvider (#12708)
## Why
`OnboardingProvider` was generating a Sentry alert (BUILDER-7ME:
"Authorization header is missing") on every behave test run. The root
cause: when a user's session expires mid-flow, they get redirected to
`/login`. The provider remounts on the login page, calls
`getV1CheckIfOnboardingIsCompleted()` while unauthenticated, and the 401
falls into the catch block which calls `console.error`. Sentry's
`captureConsole` integration auto-captures all `console.error` calls as
events, triggering the alert.

This is expected behavior — the auth middleware handles the redirect,
there's nothing broken. It was just noisy.

## What
- In `OnboardingProvider`'s `initializeOnboarding` catch block, return
early and silently on `ApiError` with status 401 — no `console.error`,
no toast
- Only unexpected errors (non-401) still surface via `console.error` and
the destructive toast

## How
```ts
} catch (error) {
  if (error instanceof ApiError && error.status === 401) {
    return;
  }
  // ... existing error handling
}
```

## Checklist
- [x] `pnpm format && pnpm lint && pnpm types` pass
- [x] Change is minimal and scoped to the one catch block
- [x] No new test needed — this is a logging/noise fix, not a behavioral
change
2026-04-08 23:40:49 +07:00
Zamil Majdy
6552d9bfdd fix(backend/executor): OrchestratorBlock dry-run credentials + Responses API status field (#12709)
## Why
Two bugs block OrchestratorBlock from working correctly:

1. **Dry-run always fails with "credentials required"** even when
`OPEN_ROUTER_API_KEY` is set on dev. The n8n conversion dry-run hits
this.
2. **Agent-mode OrchestratorBlock fails on the second LLM call** with
`Error code: 400 – Unknown parameter: 'input[2].status'` when using
OpenAI models (Responses API path).

## What
**Bug 1 — manager.py credential null** (`backend/executor/manager.py`):
The dry-run path called `input_data[field_name] = None` to "clear" the
credential slot, but `_execute` in `_base.py` filters out `None` values
before calling `input_schema(**...)`. This drops the required
`credentials` field from the schema constructor, causing a Pydantic
validation error.

Fix: Don't null out the field. If the user already has credential
metadata in `input_data` (normal case), leave it intact. If not (no
credentials configured), synthesise a minimal
`CredentialsMetaInput`-compatible placeholder from the platform
credentials so schema construction passes. The actual
`APIKeyCredentials` (platform key) is still injected via
`extra_exec_kwargs`.

**Bug 2 — Responses API `status` field**
(`backend/blocks/orchestrator.py`):
OpenAI returns output items (function calls, messages) with a `status:
"completed"` field. When `_convert_raw_response_to_dict` serialises
these items and they are stored in `conversation_history`, they are sent
back as input on the next call — but OpenAI rejects `status` as an
input-only field.

Fix: Strip `status` from each output item before it enters the history.

## How
- `manager.py` lines 311-314: removed the `input_data[field_name] =
None` nullification; added a conditional placeholder when no credential
metadata is present.
- `orchestrator.py` `_convert_raw_response_to_dict`: filter `k !=
"status"` when extracting Responses API output items.
- Tests added for both fixes.

## Checklist
- [x] Tests written and passing (94 total, all green)
- [x] Pre-commit hooks passed (Black, Ruff, isort, typecheck)
- [x] No out-of-scope changes
2026-04-08 23:40:08 +07:00
Zamil Majdy
f32a4087df fix(frontend/builder): add hook tests and fix isCreatingSessionRef leak on navigation
- Restore useBuilderChatPanel.test.ts with 28 tests covering session lifecycle
  (create success, failure, non-200), seed message dispatch + only-once guard,
  flowID reset (sessionId, sessionError, appliedActionKeys), cache invalidation
  assertion after handleApplyAction, and undo stack behaviour
- Fix sentry-flagged bug: reset isCreatingSessionRef.current in the flowID
  change effect so navigating mid-session-creation doesn't permanently block
  future session creation on the new graph
2026-04-08 23:31:45 +07:00
Zamil Majdy
eede293e11 fix(frontend/builder): address PR review — move logic to hook, undo, dedup fix, component tests
- Move inputValue, handleSend, handleKeyDown, isStreaming, canSend into
  useBuilderChatPanel (0ubbe: keep render logic out of component)
- Add undo support: snapshot node state before apply, expose undoStack +
  handleUndoLastAction, show undo button in PanelHeader
- Add toast feedback on handleApplyAction validation failures so users
  know why Apply did nothing
- Fix getActionKey for update_node_input to include value so AI corrections
  in later turns are not silently dropped by the dedup Set
- Add getNodeDisplayName shared helper in helpers.ts; use in both
  serializeGraphForChat and ActionItem (removes duplication)
- Use Map<id, node> in serializeGraphForChat for O(1) edge lookups
- Add Retry button to session error state in MessageList
- Add graph context sent banner after seed message so AI response
  does not appear unprompted (addresses confusing auto-response UX)
- Add aria-label to Apply buttons for screen-reader accessibility
- Remove hook-only test file (0ubbe: test component, not hook)
- Expand component tests: undo, retry, seed banner, action label format,
  getNodeDisplayName, getActionKey value-inclusion, edge truncation
- All 1026 tests pass; lint and types clean
2026-04-08 22:41:34 +07:00
Zamil Majdy
31a2371c26 fix(frontend/builder): address PR review — seed filter, validation, tests, session ref guard
- Filter seed message by content prefix (SEED_PROMPT_PREFIX) instead of position
- Add exhaustiveness guard for unhandled GraphAction types
- Guard handleApplyAction against unknown keys/handles via inputSchema/outputSchema
- Add renderHook-based tests: session lifecycle, flowID reset, handleApplyAction, edge cases
- Fix session-creation effect to use isCreatingSessionRef so state-driven re-renders
  don't prematurely cancel the in-flight request via the cancelled flag
- Add empty-input rejection test for BuilderChatPanel send button
2026-04-08 22:07:46 +07:00
Zamil Majdy
21670b20de fix(frontend/builder): require manual action confirmation and prevent prompt injection
- Replace auto-apply with per-action Apply buttons; users must explicitly
  confirm each AI suggestion before the graph is mutated
- Accumulate parsedActions across all assistant messages so multi-turn
  suggestions remain visible rather than disappearing after the next turn
- Escape < and > in node names/descriptions before embedding in XML prompt
  context to prevent AI prompt injection via crafted node labels
- Add MAX_EDGES cap (200) in serializeGraphForChat to mirror the MAX_NODES
  limit and prevent token overruns on dense graphs
- Add Escape key handler in the hook to close the chat panel
- Add helpers.test.ts with unit tests for buildSeedPrompt,
  extractTextFromParts, and XML sanitization
2026-04-08 18:41:58 +07:00
Zamil Majdy
ff8cdda4e8 feat(platform/admin): cost tracking for system credentials (#12696)
## Why

When system-managed credentials are used (AutoGPT pays the API bills),
there was no visibility into which providers were being called, how much
each costs, or which users were driving usage. This makes it impossible
to set appropriate per-user limits or reconcile expenses with actual API
invoices.

## What

End-to-end platform cost tracking for all 22 system-credential providers
+ both copilot modes:

- Every block execution that uses system credentials records a
`PlatformCostLog` row (provider, cost, tokens, user, execution IDs)
- Copilot turns (SDK + baseline) are tracked with model name, token
counts, and actual USD cost
- Admin dashboard at `/admin/platform-costs` shows cost breakdown by
provider and user with date/provider/user filters and paginated raw logs
- Admin API endpoints with 30s TTL cache: `GET
/platform-costs/dashboard` and `GET /platform-costs/logs`

## How

### Core hook

`cost_tracking.py` calls `log_system_credential_cost()` after each block
node execution. It reads `NodeExecutionStats.provider_cost` (set by
`merge_stats()` inside each block) and dispatches a fire-and-forget
`INSERT` via `log_platform_cost_safe()`.

### Per-block tracking

Each block calls `self.merge_stats(NodeExecutionStats(provider_cost=...,
provider_cost_type=...))`:

| Tracking type | Providers | Amount |
|---|---|---|
| `cost_usd` | OpenRouter, Exa | Actual USD from API response |
| `tokens` | OpenAI, Anthropic, Groq, Ollama, Jina | Token count from
response.usage |
| `characters` | Unreal Speech, ElevenLabs, D-ID | Input text length |
| `sandbox_seconds` | E2B | Walltime |
| `walltime_seconds` | FAL, Revid, Replicate | Walltime |
| `per_run` | Google Maps, Apollo, SmartLead, etc. | 1 per execution |

OpenRouter cost: extracted via `with_raw_response.create()` and
`raw.headers.get("x-total-cost")` with `math.isfinite` + `>= 0`
validation (replaces private `_response` access).

### Copilot tracking

`token_tracking.py` writes a `PlatformCostLog` row per copilot LLM turn
via an async fire-and-forget queue bounded by a `Semaphore(50)`. SDK
path uses `sdk_msg.total_cost_usd`; baseline path uses the
`x-total-cost` header from OpenRouter streaming responses.

### Executor drain

`drain_pending_cost_logs()` is called before `executor.shutdown()` using
a module-level loop registry (`_active_node_execution_loops`) so that
pending log tasks from each worker thread's event loop are awaited
before the process exits. Tasks are filtered by `task.get_loop() is
current_loop` to avoid cross-loop `RuntimeError` in Python ≥ 3.10.

### CoPilot executor lifecycle

Worker threads connect Prisma on startup and disconnect on cleanup (even
on failure). If `db.connect()` fails during `@func_retry`, the event
loop is stopped and joined before re-raising so no loop is leaked across
retry attempts.

### Schema

```prisma
model PlatformCostLog {
  id                  String   @id @default(uuid())
  createdAt           DateTime @default(now())
  userId              String?
  graphExecId         String?
  nodeExecId          String?
  blockName           String
  provider            String
  trackingType        String
  costMicrodollars    BigInt   @default(0)
  inputTokens         Int?
  outputTokens        Int?
  duration            Float?
  model               String?
}
```

### Admin dashboard

React page with three tabs (By Provider / By User / Raw Logs) driven by
two generated Orval hooks (`useGetV2GetPlatformCostDashboard`,
`useGetV2GetPlatformCostLogs`). Filters are URL-based (`searchParams`)
for bookmarkability. Pagination for raw logs. Per-provider estimated
totals using configurable cost-per-unit multipliers.

## Test plan
- [x] Migration applies cleanly
- [x] Block execution with system credentials creates PlatformCostLog
row
- [x] Copilot conversation records cost log with tokens + model
- [x] `/admin/platform-costs` dashboard renders with correct data
- [x] Date/provider/user filters work correctly
- [x] Non-admin users get 403 on cost endpoints
- [x] Executor drain completes before process exit (no lost logs)

---------

Co-authored-by: Zamil Majdy <majdyz@users.noreply.github.com>
Co-authored-by: Nicholas Tindle <nicholas.tindle@agpt.co>
2026-04-08 10:05:33 +00:00
Zamil Majdy
c51097d8ac dx(orchestrate): harden agent fleet scripts — idle detection, pagination, fake-resolution guard, parallelism (#12704)
### Why / What / How

**Why:** A series of production failures exposed gaps in the agent fleet
tooling:
1. Agents using `_wait_idle`/`wait_for_claude_idle` would time out
waiting for `❯` while a settings-error dialog blocked progress — because
the dialog can appear above the last 3 captured lines.
2. The run-loop's adaptive backoff used `POLL_CURRENT * 3 / 2` which
stalls at 1 forever in bash integer arithmetic, and printed the interval
*before* recomputing it.
3. `pr-address` agents were silently missing review threads when a PR
had >100 threads across multiple pages — they'd stop at page 1, address
69/111 threads, and falsely report "done".
4. `resolveReviewThread` was being called without a committed fix —
producing false "0 unresolved" signals that bypassed verification.
5. The onboarding bypass in `/pr-test` had no timeout on curl calls, so
the step could hang forever if the backend wasn't ready yet.
6. The orchestrator's own verification query used `first: 1` which can't
reliably count unresolved threads across all pages.

**What:**
- Idle detection hardened in both `spawn-agent.sh` and `run-loop.sh` —
full-pane check for 'Enter to confirm' so the dialog is never missed
- Adaptive backoff arithmetic fixed (`POLL_CURRENT + POLL_CURRENT/2 + 1`
always increments); log ordering corrected; `POLL_IDLE_MAX` made
env-configurable
- `pr-address/SKILL.md`: mandatory cursor-pagination loop collecting ALL
thread IDs before addressing anything; prominent ⚠️ warning with the PR
#12636 incident (142 threads, 2 pages, agent stopped at 69)
- `pr-address/SKILL.md`: new "Parallel thread resolution" section —
batch by file, one commit per file group, concurrent reply subshells
with 3s gaps, sequential resolves
- `pr-address/SKILL.md`: "Verify actual count" section now uses
paginated loop (not single first:100 query)
- `orchestrate/SKILL.md`: verification query fixed to paginate all
pages; new "Thread resolution integrity" section with anti-patterns;
fake-resolution detection query; state-staleness recovery; RUNNING-count
confusion explained
- `/pr-test` onboarding bypass: `--max-time 30` on curl calls; hard-fail
on bypass failure

**How:** All changes are to DX skill files and orchestration scripts —
no production code modified. Each fix is a separate commit so the change
history is readable.

### Changes 🏗️

**Scripts:**
- `run-loop.sh`: `wait_for_claude_idle` — add 'Enter to confirm' dialog
check (reset elapsed on dialog); fix backoff arithmetic stall; fix log
ordering; make `POLL_IDLE_MAX` env-configurable; reset poll interval
when `waiting_approval` agents present
- `spawn-agent.sh`: `_wait_idle` — capture full pane (not just `tail
-3`) for 'Enter to confirm' check; wait-for-idle before sending agent
objective to prevent stuck pasted-text

**SKILL.md files:**
- `pr-address/SKILL.md`:
- ⚠️ WARNING + totalCount step + cursor-pagination loop before
addressing any threads
- "Parallel thread resolution" section: group by file, batch commits,
concurrent replies, sequential resolves
- "Verify actual count" section: full paginated loop instead of single
first:100 query
- "What counts as a valid resolution" with explicit anti-patterns
(Acknowledged, Accepted, no-commit resolves)
  - Rate limits table (403 secondary vs 429 primary), 2-3 min recovery
  - `git rev-parse HEAD` pattern with `${FULL_SHA:0:9}` short SHA
- `orchestrate/SKILL.md`:
- Thread resolution integrity section + fake-resolution detection query
  - Verification query fixed to paginate all pages
- State file staleness recovery (stale `loop_window`, closed windows,
repair recipes)
- RUNNING count confusion: explains `waiting_approval` included in regex
  - Idle check before re-briefing agents
- `pr-test/SKILL.md`:
  - `--max-time 30` on onboarding bypass curl calls
  - Hard-fail (`exit 1`) if bypass verification fails

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] Verified adaptive backoff increments correctly (no longer stalls
at 1)
- [x] Verified 'Enter to confirm' dialog handled in both wait functions
  - [x] Verified pagination loop collects all thread IDs across pages
- [x] Verified PR #12636 onboarding bypass works end-to-end (11/11
scenarios PASS)

---------

Co-authored-by: Zamil Majdy <majdy.zamil@gmail.com>
2026-04-08 17:11:55 +07:00
Zamil Majdy
f3306d9211 Merge branch 'master' of github.com:Significant-Gravitas/AutoGPT into dev 2026-04-08 16:17:09 +07:00
Zamil Majdy
19c8aecb97 fix(frontend/builder): hide seed message from chat UI
The initialization prompt ("I'm building an agent in the AutoGPT flow
builder...") was sent as a visible user message, exposing raw prompt
engineering instructions to end users. Track its ID via seedMessageId
and exclude it from the rendered message list.
2026-04-08 16:15:32 +07:00
Zamil Majdy
d8181e7624 fix(frontend/builder): auto-apply AI graph actions after each streaming turn
handleApplyAction was defined and exported but never called, so the
"AI applied these changes" panel was displaying actions that had no
effect. Wire up a handleApplyActionRef so the status-change effect
can safely apply each parsed action to the local Zustand stores once
per completed AI turn, before the canvas refetch resolves.
2026-04-08 15:52:06 +07:00
Zamil Majdy
a4282d927a fix(frontend/builder): validate key and handle against node schemas in handleApplyAction
Rejects update_node_input keys not present in inputSchema.properties and
connect_nodes handles not present in outputSchema/inputSchema.properties,
preventing AI from writing arbitrary fields that blocks do not support.
Validation is permissive when schema is undefined (backwards-compatible).
2026-04-08 15:44:12 +07:00
Zamil Majdy
1c43d4a81d test(frontend/builder): add hook and component tests for handleApplyAction and session error
- Add useBuilderChatPanel.test.ts with direct tests for handleApplyAction:
  update_node_input (merges hardcodedValues, no-ops for unknown node),
  connect_nodes (calls addEdge with correct args, no-ops if either node missing)
- Add panel open/close state tests for useBuilderChatPanel
- Add session error UI test to BuilderChatPanel.test.tsx
2026-04-08 15:35:30 +07:00
Zamil Majdy
2897550d21 refactor(frontend/builder): extract getActionKey helper, wire textareaRef
- Extract `getActionKey(action)` to helpers.ts, removing duplicated key
  computation from BuilderChatPanel.tsx and useBuilderChatPanel.ts
- Wire `textareaRef` through PanelInputProps so focus-on-open works
- Add `getActionKey` tests covering both action types
2026-04-08 15:08:40 +07:00
Zamil Majdy
e058671325 fix(frontend/builder): escape quotes in welcome state to satisfy react/no-unescaped-entities 2026-04-08 15:00:08 +07:00
Zamil Majdy
a955b017f1 fix(frontend/builder): resolve merge conflicts — keep comprehensive security & UX fixes
Merge resolution keeps:
- buildSeedPrompt helper (prompt injection mitigation with XML tags)
- extractTextFromParts naming (aligned with remote)
- cancelled flag pattern for session creation cleanup
- streamError display and empty/welcome state (new in this branch)
- Static Applied badge (span, no dead toggle logic)
- ARIA roles: role=dialog, role=log
- react-markdown for assistant messages
- Placeholder hint for Enter/Shift+Enter
- All new tests: keyboard, multi-action, customized_name, truncation,
  primitive validation, stream error, ARIA assertions
2026-04-08 14:53:35 +07:00
Zamil Majdy
5f55980669 fix(frontend/builder): address PR review comments — security, UX, quality
Security:
- Wrap graph context in <graph_context> XML tags and label as untrusted to
  mitigate prompt injection from node names/descriptions
- Add comment confirming backend validates session ownership before streaming
- Restrict update_node_input value to string|number|boolean primitives to
  prevent prototype-pollution from crafted AI responses
- Add MAX_NODES=100 cap in serializeGraphForChat to prevent token overruns
- Add source/target node existence check before addEdge in handleApplyAction

Correctness:
- Add `ignore` flag to session-creation effect to prevent state updates after
  unmount or effect re-run
- Add nodes+edges to initialization effect deps (hasSentSeedMessageRef guards
  against re-firing)
- Gate parsedActions useMemo on status==='ready' to avoid hot-path regex
  during streaming

Code quality:
- Rename initializedRef → hasSentSeedMessageRef for clarity
- Extract buildSeedPrompt and getMessageText helpers into helpers.ts
- Remove dead ActionItem handleApply/applied toggle (actions are auto-applied)
- Remove redundant setTimeout scroll in handleSend (useEffect already scrolls)
- Export error from useChat for stream error display

UX / accessibility:
- Add react-markdown rendering for assistant message bubbles
- Add empty/welcome state when no messages
- Add role="dialog" + aria-label to panel, role="log" + aria-live to messages
- Add streaming error display when useChat error is set
- Update placeholder to hint Enter/Shift+Enter behaviour

Tests:
- Add Enter-to-send and Shift+Enter-no-send keyboard tests
- Add multi-action block parsing test
- Add metadata.customized_name preference test
- Add MAX_NODES truncation test
- Add primitive value validation test (number, boolean)
- Add stream error display test
- Add ARIA role assertion tests
2026-04-08 14:46:59 +07:00
Zamil Majdy
7f642f5b64 fix(frontend/builder): address review comments on chat panel
- Validate node existence before connect_nodes in handleApplyAction
- Add cleanup guard to session creation effect to prevent state updates
  after unmount
- Extract extractTextFromParts helper to deduplicate text extraction
- Remove dead code in ActionItem (applied state was always true)
- Remove redundant setTimeout scroll in handleSend (useEffect handles it)
- Update test to match simplified ActionItem
2026-04-08 07:43:22 +00:00
Zamil Majdy
b3f25ecb57 Merge remote-tracking branch 'origin/dev' into feat/builder-chat-panel 2026-04-08 14:37:06 +07:00
Zamil Majdy
f5e2eccda7 dx(orchestrate): fix stale-review gate and add pr-test evaluation rules to SKILL.md (#12701)
## Changes

### verify-complete.sh
- CHANGES_REQUESTED reviews are now compared against the latest commit
timestamp. If the review was submitted **before** the latest commit, it
is treated as stale and does not block verification.
- Added fail-closed guard: if the `gh pr view` fetch fails, the script
exits 1 (rather than treating missing data as "no blocking reviews")
- Fixed edge case: a `CHANGES_REQUESTED` review with a null
`submittedAt` is now counted as fresh/blocking (previously silently
skipped)
- Combined two separate `gh pr view` calls into one (`--json
commits,reviews`) to reduce API calls and ensure consistency

### SKILL.md (orchestrate skill)
- Added `### /pr-test result evaluation` section with explicit
pass/partial/fail handling table
- **PARTIAL on any headline feature scenario = immediate blocker**:
re-brief the agent, fix, and re-run from scratch. Never approve or
output ORCHESTRATOR:DONE with a PARTIAL headline result.
- Concrete incident callout: PR #12699 S5 (Apply suggestions) was
PARTIAL — AI never output JSON action blocks — but was nearly approved.
This rule prevents recurrence.
- Updated `verify-complete.sh` description throughout to include "no
fresh CHANGES_REQUESTED"
- Added staleness rule documentation: a review only blocks if submitted
*after* the latest commit

## Why

Two separate incidents prompted these changes:

1. **verify-complete.sh false positive**: An automated bot
(autogpt-pr-reviewer) submitted a `CHANGES_REQUESTED` review in April.
An agent then pushed fixing commits. The old script still blocked on the
stale review, preventing the PR from being verified as done.

2. **Missed PARTIAL signal**: PR #12699 had a PARTIAL result on its
headline scenario (S5 Apply button) because the AI emitted direct
builder tool calls instead of JSON action blocks. The orchestrator
nearly approved it. The new SKILL.md rule makes PARTIAL = blocker
explicit.

## Checklist

- [x] I have read the contribution guide
- [x] My changes follow the code style of this project  
- [x] Changes are limited to the scope of this PR (< 20% unrelated
changes)
- [x] All new and existing tests pass
2026-04-08 08:58:42 +07:00
Zamil Majdy
8f855e5ea7 fix(frontend/builder): address PR review comments on chat panel
- Feature-flag the BuilderChatPanel behind BUILDER_CHAT_PANEL flag (ntindle)
- Reset sessionId/initializedRef on flowID navigation (sentry x2)
- Block input until session is ready to prevent pre-seed messages (coderabbitai)
- Reset sessionError on panel reopen so retry works (coderabbitai)
- Gate canvas invalidation on actual graph mutations only (coderabbitai)
- Add comment explaining ActionItem applied=true is intentional (sentry)
- Rename test and assert disabled state directly (coderabbitai)
2026-04-08 02:47:47 +07:00
Zamil Majdy
6ed257225f Merge branch 'dev' of github.com:Significant-Gravitas/AutoGPT into feat/builder-chat-panel 2026-04-08 02:39:29 +07:00
Zamil Majdy
109f28d9d1 fix(frontend/builder): auto-scroll to bottom when AI responds in chat panel 2026-04-08 02:07:13 +07:00
Zamil Majdy
ffa955044d fix(frontend/builder): strengthen JSON format instruction in chat seed message 2026-04-08 01:38:34 +07:00
Zamil Majdy
0999739d19 fix(frontend/builder): surface AI graph edits and auto-refresh canvas
- Embed JSON action block instruction in the seed message so the AI
  outputs parseable blocks after edit_agent calls, making the changes
  section visible without a backend system-prompt deploy
- Auto-invalidate the graph React Query after streaming completes so
  useFlow.ts re-fetches and repopulates nodeStore/edgeStore in real-time
- Start ActionItem in pre-applied state; section label reads "AI applied
  these changes" since edit_agent saves immediately server-side
- Update tests to match new label and pre-applied default
2026-04-08 01:01:09 +07:00
Zamil Majdy
58b230ff5a dx: add /orchestrate skill — Claude Code agent fleet supervisor with spare worktree lifecycle (#12691)
### Why

When running multiple Claude Code agents in parallel worktrees, they
frequently get stuck: an agent exits and sits at a shell prompt, freezes
mid-task, or waits on an approval prompt with no human watching. Fixing
this currently requires manually checking each tmux window.

### What

Adds a `/orchestrate` skill — a meta-agent supervisor that manages a
fleet of Claude Code agents across tmux windows and spare worktrees. It
auto-discovers available worktrees, spawns agents, monitors them, kicks
idle/stuck ones, auto-approves safe confirmations, and recycles
worktrees on completion.

### How to use

**Prerequisites:**
- One tmux session already running (the skill adds windows to it; it
does not create a new session)
- Spare worktrees on `spare/N` branches (e.g. `AutoGPT3` on `spare/3`,
`AutoGPT7` on `spare/7`)

**Basic workflow:**

```
/orchestrate capacity     → see how many spare worktrees are free
/orchestrate start        → enter task list, agents spawn automatically
/orchestrate status       → check what's running
/orchestrate add          → add one more task to the next free worktree
/orchestrate stop         → mark inactive (agents finish current work)
/orchestrate poll         → one manual poll cycle (debug / on-demand)
```

**Worktree lifecycle:**
```text
spare/N branch → /orchestrate add → new window + feat/branch + claude running
                                              ↓
                                     ORCHESTRATOR:DONE
                                              ↓
                              kill window + git checkout spare/N
                                              ↓
                                     spare/N (free again)
```

Windows are always capped by worktree count — no creep.

### Changes

- `.claude/skills/orchestrate/SKILL.md` — skill definition with 5
subcommands, state file schema, spawn/recycle helpers, approval policy
- `.claude/skills/orchestrate/scripts/classify-pane.sh` — pane state
classifier: `idle` (shell foreground), `running` (non-shell),
`waiting_approval` (pattern match), `complete` (ORCHESTRATOR:DONE)
- `.claude/skills/orchestrate/scripts/poll-cycle.sh` — poll loop:
reads/updates state file atomically, outputs JSON action list, stuck
detection via output-hash sampling

**State detection:**

| State | Detection method |
|---|---|
| `idle` | `pane_current_command` is a shell (zsh/bash/fish) |
| `running` | `pane_current_command` is non-shell (claude/node) |
| `stuck` | pane hash unchanged for N consecutive polls |
| `waiting_approval` | pattern match on last 40 lines of pane output |
| `complete` | `ORCHESTRATOR:DONE` string present in pane output |

**Safety policy for auto-approvals:** git ops, package installs, tests,
docker compose → approve. `rm -rf` outside worktree, force push, `sudo`,
secrets → escalate to user.

State file lives at `~/.claude/orchestrator-state.json` (outside repo,
never committed).

### Checklist

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] `classify-pane.sh`: idle shell → `idle`, running process →
`running`, `ORCHESTRATOR:DONE` → `complete`, approval prompt →
`waiting_approval`, nonexistent window → `error`
- [x] `poll-cycle.sh`: inactive state → `[]`, empty agents array → `[]`,
spare worktree discovery, stuck detection (3-poll hash cycle)
- [x] Real agent spawn in `autogpt1` tmux session — agent ran, output
`ORCHESTRATOR:DONE`, recycle verified
  - [x] Upfront JSON validation before `set -e`-guarded jq reads
- [x] Idle timer reset only on `idle → running` transition (not stuck),
preventing false stuck-detections
- [x] Classify fallback only triggers when output is empty (no
double-JSON on classify exit 1)
2026-04-08 00:18:32 +07:00
Zamil Majdy
77f41d0cc6 fix(frontend/builder): include handles in connect_nodes dedup key 2026-04-07 23:25:20 +07:00
Zamil Majdy
5e8530b263 fix(frontend/builder): address coderabbitai and sentry review feedback
- Validate required fields in parseGraphActions before emitting actions
  (coderabbitai: reject malformed payloads instead of coercing to "")
- Gate chat seeding on isGraphLoaded to avoid seeding with empty graph
  when panel is opened before graph finishes loading (coderabbitai)
- Deduplicate parsedActions in the hook to prevent duplicate React keys
  when AI suggests the same action twice (sentry)
- Add tests for malformed action field validation
2026-04-07 23:16:52 +07:00
Zamil Majdy
817b80a198 fix(frontend/builder): address chat panel review comments
- Prevent infinite retry loop on session creation failure by tracking
  sessionError state and bailing out on non-200 or thrown errors
- Remove nodes/edges from initialization effect deps (only fire once
  when sessionId+transport become available)
- Show node display name instead of raw ID in action item labels
- Use stable content-based keys for action items instead of array index
2026-04-07 23:09:06 +07:00
Zamil Majdy
fbbd222405 feat(frontend/builder): add chat panel for interactive agent editing
Add a collapsible right-side chat panel to the flow builder that lets
users ask questions about their agent and request modifications via chat.
2026-04-07 22:57:21 +07:00
Krzysztof Czerwinski
67bdef13e7 feat(platform): load copilot messages from newest first with cursor-based pagination (#12328)
Copilot chat sessions with long histories loaded all messages at once,
causing slow initial loads. This PR adds cursor-based pagination so only
the most recent messages load initially, with older messages fetched on
demand as the user scrolls up.

### Changes 🏗️

**Backend:**
- Cursor-based pagination on `GET /sessions/{session_id}` (`limit`,
`before_sequence` params)
- `user_id` relation filter on the paginated query — ownership check and
message fetch now run in parallel
- Backward boundary expansion to keep tool-call / assistant message
pairs intact at page edges
- Unit tests for paginated queries

**Frontend:**
- `useLoadMoreMessages` hook + `LoadMoreSentinel` (IntersectionObserver)
for infinite scroll upward
- `ScrollPreserver` to maintain scroll position when older messages are
prepended
- Session-keyed `Conversation` remount with one-frame opacity hide to
eliminate scroll flash on switch
- Scrollbar moved to the correct scroll container; loading spinner no
longer causes overflow

### Checklist 📋

- [x] Pagination: only recent messages load initially; older pages load
on scroll-up
- [x] Scroll position preserved on prepend; no flash on session switch
- [x] Tool-call boundary pairs stay intact across page edges
- [x] Stream reconnection still works on initial load

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: Nicholas Tindle <nicholas.tindle@agpt.co>
2026-04-07 12:43:47 +00:00
Ubbe
e67dd93ee8 refactor(frontend): remove stale feature flags and stabilize share execution (#12697)
## Why

Stale feature flags add noise to the codebase and make it harder to
understand which flags are actually gating live features. Four flags
were defined but never referenced anywhere in the frontend, and the
"Share Execution Results" flag has been stable long enough to remove its
gate.

## What

- Remove 4 unused flags from the `Flag` enum and `defaultFlags`:
`NEW_BLOCK_MENU`, `GRAPH_SEARCH`, `ENABLE_ENHANCED_OUTPUT_HANDLING`,
`AGENT_FAVORITING`
- Remove the `SHARE_EXECUTION_RESULTS` flag and its conditional — the
`ShareRunButton` now always renders

## How

- Deleted enum entries and default values in `use-get-flag.ts`
- Removed the `useGetFlag` call and conditional wrapper around
`<ShareRunButton />` in `SelectedRunActions.tsx`

## Changes

- `src/services/feature-flags/use-get-flag.ts` — removed 5 flags from
enum + defaults
- `src/app/(platform)/library/.../SelectedRunActions.tsx` — removed flag
import, condition; share button always renders

### Checklist

- [x] My PR is small and focused on one change
- [x] I've tested my changes locally
- [x] `pnpm format && pnpm lint` pass

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-07 19:28:40 +07:00
Otto
3140a60816 fix(frontend/builder): allow horizontal scroll for JSON output data (#12638)
Requested by @Abhi1992002 

## Why

JSON output data in the "Complete Output Data" dialog and node output
panel gets clipped — text overflows and is hidden with no way to scroll
right. Reported by Zamil in #frontend.

## What

The `ContentRenderer` wrapper divs used `overflow-hidden` which
prevented the `JSONRenderer`'s `overflow-x-auto` from working. Changed
both wrapper divs from `overflow-hidden` to `overflow-x-auto`.

```diff
- overflow-hidden [&>*]:rounded-xlarge [&>*]:!text-xs [&_pre]:whitespace-pre-wrap [&_pre]:break-words
+ overflow-x-auto [&>*]:rounded-xlarge [&>*]:!text-xs [&_pre]:whitespace-pre-wrap [&_pre]:break-words

- overflow-hidden [&>*]:rounded-xlarge [&>*]:!text-xs
+ overflow-x-auto [&>*]:rounded-xlarge [&>*]:!text-xs
```

## Scope
- 1 file changed (`ContentRenderer.tsx`)
- 2 lines: `overflow-hidden` → `overflow-x-auto`
- CSS only, no logic changes

Resolves SECRT-2206

Co-authored-by: Abhimanyu Yadav <122007096+Abhi1992002@users.noreply.github.com>
Co-authored-by: Nicholas Tindle <nicholas.tindle@agpt.co>
2026-04-07 19:11:09 +07:00
Nicholas Tindle
41c2ee9f83 feat(platform): add copilot artifact preview panel (#12629)
### Why / What / How

Copilot artifacts were not previewing reliably: PDFs downloaded instead
of rendering, Python code could still render like markdown, JSX/TSX
artifacts were brittle, HTML dashboards/charts could fail to execute,
and users had to manually open artifact panes after generation. The pane
also got stuck at maximized width when trying to drag it smaller.

This PR adds a dedicated copilot artifact panel and preview pipeline
across the backend/frontend boundary. It preserves artifact metadata
needed for classification, adds extension-first preview routing,
introduces dedicated preview/rendering paths for HTML/CSV/code/PDF/React
artifacts, auto-opens new or edited assistant artifacts, and fixes the
maximized-pane resize path so dragging exits maximized mode immediately.

### Changes 🏗️

- add artifact card and artifact panel UI in copilot, including
persisted panel state and resize/maximize/minimize behavior
- add shared artifact extraction/classification helpers and auto-open
behavior for new or edited assistant messages with artifacts
- add preview/rendering support for HTML, CSV, PDF, code, and React
artifact files
- fix code artifacts such as Python to render through the code renderer
with a dark code surface instead of markdown-style output
- improve JSX/TSX preview behavior with provider wrapping, fallback
export selection, and explicit runtime error surfaces
- allow script execution inside HTML previews so embedded chart
dashboards can render
- update workspace artifact/backend API handling and regenerate the
frontend OpenAPI client
- add regression coverage for artifact helpers, React preview runtime,
auto-open behavior, code rendering, and panel store behavior

- post-review hardening: correct download path for cross-origin URLs,
defer scroll restore until content mounts, gate auto-open behind the
ARTIFACTS flag, parse CSVs with RFC 4180-compliant quoted newlines + BOM
handling, distinguish 413 vs 409 on upload, normalize empty session_id,
and keep AnimatePresence mounted so the panel exit animation plays

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  - [x] `pnpm format`
  - [x] `pnpm lint`
  - [x] `pnpm types`
  - [x] `pnpm test:unit`

#### For configuration changes:

- [x] `.env.default` is updated or already compatible with my changes
- [x] `docker-compose.yml` is updated or already compatible with my
changes
- [x] I have included a list of my configuration changes in the PR
description (under **Changes**)

<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> **Medium Risk**
> Adds a new Copilot artifact preview surface that executes
user/AI-generated HTML/React in sandboxed iframes and changes workspace
file upload/listing behavior, so regressions could affect file handling
and client security assumptions despite sandboxing safeguards.
> 
> **Overview**
> Adds an **Artifacts** feature (flagged by `Flag.ARTIFACTS`) to
Copilot: workspace file links/attachments now render as `ArtifactCard`s
and can open a new resizable/minimizable `ArtifactPanel` with history,
auto-open behavior, copy/download actions, and persisted panel width.
> 
> Introduces a richer artifact preview pipeline with type classification
and dedicated renderers for **HTML**, **CSV**, **PDF**, **code
(Shiki-highlighted)**, and **React/TSX** (transpiled and executed in a
sandboxed iframe), plus safer download filename handling and content
caching/scroll restore.
> 
> Extends the workspace backend API by adding `GET /workspace/files`
pagination, standardizing operation IDs in OpenAPI, attaching
`metadata.origin` on uploads/agent-created files, normalizing empty
`session_id`, improving upload error mapping (409 vs 413), and hardening
post-quota soft-delete error handling; updates and expands test coverage
accordingly.
> 
> <sup>Reviewed by [Cursor Bugbot](https://cursor.com/bugbot) for commit
b732d10eca. Bugbot is set up for automated
code reviews on this repo. Configure
[here](https://www.cursor.com/dashboard/bugbot).</sup>
<!-- /CURSOR_SUMMARY -->

---------

Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-07 11:24:22 +00:00
Ubbe
ca748ee12a feat(frontend): refine AutoPilot onboarding — branding, auto-advance, soft cap, polish (#12686)
### Why / What / How

**Why:** The onboarding flow had inconsistent branding ("Autopilot" vs
"AutoPilot"), a heavy progress bar that dominated the header, an extra
click on the role screen, and no guidance on how many pain points to
select — leading to users selecting everything or nothing useful.

**What:** Copy & brand fixes, UX improvements (auto-advance, soft cap),
and visual polish (progress bar, checkmark badges, purple focus inputs).

**How:**
- Replaced all "Autopilot" with "AutoPilot" (capital P) across screens
1-3
- Removed the `?` tooltip on screen 1 (users will learn about AutoPilot
from the access email)
- Changed name label to conversational "What should I call you?"
- Screen 2: auto-advances 350ms after role selection (except "Other"
which still shows input + button)
- Screen 3: soft cap of 3 selections with green confirmation text and
shake animation on overflow attempt
- Thinned progress bar from ~10px to 3px (Linear/Notion style)
- Added purple checkmark badges on selected cards
- Updated Input atom focus state to purple ring

### Changes 🏗️

- **WelcomeStep**: "AutoPilot" branding, removed tooltip, conversational
label
- **RoleStep**: Updated subtitle, auto-advance on non-"Other" role
select, Continue button only for "Other"
- **PainPointsStep**: Soft cap of 3 with dynamic helper text and shake
animation
- **usePainPointsStep**: Added `atLimit`/`shaking` state, wrapped
`togglePainPoint` with cap logic
- **store.ts**: `togglePainPoint` returns early when at 3 and adding
- **ProgressBar**: 3px height, removed glow shadow
- **SelectableCard**: Added purple checkmark badge on selected state
- **Input atom**: Focus ring changed from zinc to purple
- **tailwind.config.ts**: Added `shake` keyframe and `animate-shake`
utility

### Checklist 📋

#### For code changes:
- [ ] I have clearly listed my changes in the PR description
- [ ] I have made a test plan
- [ ] I have tested my changes according to the test plan:
  - [ ] Navigate through full onboarding flow (screens 1→2→3→4)
  - [ ] Verify "AutoPilot" branding on all screens (no "Autopilot")
  - [ ] Verify screen 2 auto-advances after tapping a role (non-"Other")
  - [ ] Verify "Other" role still shows text input and Continue button
  - [ ] Verify Back button works correctly from screen 2 and 3
  - [ ] Select 3 pain points and verify green "3 selected" text
  - [ ] Attempt 4th selection and verify shake animation + swap message
  - [ ] Deselect one and verify can select a different one
  - [ ] Verify checkmark badges appear on selected cards
  - [ ] Verify progress bar is thin (3px) and subtle
  - [ ] Verify input focus state is purple across onboarding inputs
- [ ] Verify "Something else" + other text input still works on screen 3

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-07 17:58:36 +07:00
Zamil Majdy
243b12778f dx: improve pr-test skill — inline screenshots, flow captions, and test evaluation (#12692)
## Changes

### 1. Inline image enforcement (Step 7)
- Added `CRITICAL` warning: never post a bare directory tree link
- Added post-comment verification block that greps for `![` tags and
exits 1 if none found — agents can't silently skip inline embedding

### 2. Structured screenshot captions (Step 6)
- `SCREENSHOT_EXPLANATIONS` now requires **Flow** (which scenario),
**Steps** (exact actions taken), **Evidence** (what this proves)
- Good/bad example included so agents know what format is expected
- A bare "shows the page" caption is explicitly rejected

### 3. Test completeness evaluation (Step 8) — new step
After posting screenshots, the agent must evaluate coverage against the
test plan and post a formal GitHub review:
- **`APPROVE`** — every scenario tested with screenshot + DB/API
evidence, no blockers
- **`REQUEST_CHANGES`** — lists exact gaps: untested scenarios, missing
evidence, confirmed bugs
- Per-scenario checklist (/) required in the review body
- Cannot auto-approve without ticking every item in the test plan

## Why

- Agents were posting `https://github.com/.../tree/test-screenshots/...`
instead of `![name](url)` inline
- Screenshot captions were too vague to be useful ("shows the page")
- No mechanism to catch incomplete test runs — agent could skip
scenarios and still post a passing report

## Checklist

- [x] `.claude/skills/pr-test/SKILL.md` updated
- [x] No production code changes — skill/dx only
- [x] Pre-commit hooks pass
2026-04-07 16:04:08 +07:00
An Vy Le
43c81910ae fix(backend/copilot): skip AI blocks without model property in fix_ai_model_parameter (#12688)
### Why / What / How

**Why:** Some AI-category blocks do not expose a `"model"` input
property in their `inputSchema`. The `fix_ai_model_parameter` fixer was
unconditionally injecting a default model value (e.g. `"gpt-4o"`) into
any node whose block has category `"AI"`, regardless of whether that
block actually accepts a `model` input. This causes the agent JSON to
include an invalid field for those blocks.

**What:** Guard the model-injection logic with a check that `"model"`
exists in the block's `inputSchema.properties` before attempting to set
or validate the field. AI blocks that have no model selector are now
skipped entirely.

**How:** In `fix_ai_model_parameter`, after confirming `is_ai_block`,
extract `input_properties` from the block's `inputSchema.properties` and
`continue` if `"model"` is absent. The subsequent `model_schema` lookup
is also simplified to reuse the already-fetched `input_properties` dict.
A regression test is added to cover this case.

### Changes 🏗️

- `backend/copilot/tools/agent_generator/fixer.py`: In
`fix_ai_model_parameter`, skip AI-category nodes whose block
`inputSchema.properties` does not contain a `"model"` key; reuse
`input_properties` for the subsequent `model_schema` lookup.
- `backend/copilot/tools/agent_generator/fixer_test.py`: Add
`test_ai_block_without_model_property_is_skipped` to
`TestFixAiModelParameter`.

### Checklist 📋

#### For code changes:
- [ ] I have clearly listed my changes in the PR description
- [ ] I have made a test plan
- [ ] I have tested my changes according to the test plan:
- [ ] Run `poetry run pytest
backend/copilot/tools/agent_generator/fixer_test.py` — all 50 tests pass
(49 pre-existing + 1 new)

Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-06 17:14:11 +00:00
Ubbe
a11199aa67 dx(frontend): set up React integration testing with Vitest + RTL + MSW (#12667)
## Summary
- Establish React integration tests (Vitest + RTL + MSW) as the primary
frontend testing strategy (~90% of tests)
- Update all contributor documentation (TESTING.md, CONTRIBUTING.md,
AGENTS.md) to reflect the integration-first convention
- Add `NuqsTestingAdapter` and `TooltipProvider` to the shared test
wrapper so page-level tests work out of the box
- Write 8 integration tests for the library page as a reference example
for the pattern

## Why
We had the testing infrastructure (Vitest, RTL, MSW, Orval-generated
handlers) but no established convention for page-level integration
tests. Most existing tests were for stores or small components. Since
our frontend is client-first, we need a documented, repeatable pattern
for testing full pages with mocked APIs.

## What
- **Docs**: Rewrote `TESTING.md` as a comprehensive guide. Updated
testing sections in `CONTRIBUTING.md`, `frontend/AGENTS.md`,
`platform/AGENTS.md`, and `autogpt_platform/AGENTS.md`
- **Test infra**: Added `NuqsTestingAdapter` (for `nuqs` query state
hooks) and `TooltipProvider` (for Radix tooltips) to `test-utils.tsx`
- **Reference tests**: `library/__tests__/main.test.tsx` with 8 tests
covering agent rendering, tabs, folders, search bar, and Jump Back In

## How
- Convention: tests live in `__tests__/` next to `page.tsx`, named
descriptively (`main.test.tsx`, `search.test.tsx`)
- Pattern: `setupHandlers()` → `render(<Page />)` → `findBy*` assertions
- MSW handlers from
`@/app/api/__generated__/endpoints/{tag}/{tag}.msw.ts` for API mocking
- Custom `render()` from `@/tests/integrations/test-utils` wraps all
required providers

## Test plan
- [x] All 422 unit/integration tests pass (`pnpm test:unit`)
- [x] `pnpm format` clean
- [x] `pnpm lint` clean (no new errors)
- [x] `pnpm types` — pre-existing onboarding type errors only, no new
errors

🤖 Generated with [Claude Code](https://claude.com/claude-code)

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: Nicholas Tindle <nicholas.tindle@agpt.co>
Co-authored-by: Reinier van der Leer <pwuts@agpt.co>
2026-04-06 13:17:08 +00:00
Zamil Majdy
5f82a71d5f feat(copilot): add Fast/Thinking mode toggle with full tool parity (#12623)
### Why / What / How

Users need a way to choose between fast, cheap responses (Sonnet) and
deep reasoning (Opus) in the copilot. Previously only the SDK/Opus path
existed, and the baseline path was a degraded fallback with no tool
calling, no file attachments, no E2B sandbox, and no permission
enforcement.

This PR adds a copilot mode toggle and brings the baseline (fast) path
to full feature parity with the SDK (extended thinking) path.

### Changes 🏗️

#### 1. Mode toggle (UI → full stack)
- Add Fast / Thinking mode toggle to ChatInput footer (Phosphor
`Brain`/`Zap` icons via lucide-react)
- Thread `mode: "fast" | "extended_thinking" | null` from
`StreamChatRequest` → RabbitMQ queue → executor → service selection
- Fast → baseline service (Sonnet 4 via OpenRouter), Thinking → SDK
service (Opus 4.6)
- Toggle gated behind `CHAT_MODE_OPTION` feature flag with server-side
enforcement
- Mode persists in localStorage with SSR-safe init

#### 2. Baseline service full tool parity
- **Tool call persistence**: Store structured `ChatMessage` entries
(assistant + tool results) instead of flat concatenated text — enables
frontend to render tool call details and maintain context across turns
- **E2B sandbox**: Wire up `get_or_create_sandbox()` so `bash_exec`
routes to E2B (image download, Python/PIL compression, filesystem
access)
- **File attachments**: Accept `file_ids`, download workspace files,
embed images as OpenAI vision blocks, save non-images to working dir
- **Permissions**: Filter tool list via `CopilotPermissions`
(whitelist/blacklist)
- **URL context**: Pass `context` dict to user message for URL-shared
content
- **Execution context**: Pass `sandbox`, `sdk_cwd`, `permissions` to
`set_execution_context()`
- **Model**: Changed `fast_model` from `google/gemini-2.5-flash` to
`anthropic/claude-sonnet-4` for reliable function calling
- **Temp dir cleanup**: Lazy `mkdtemp` (only when files attached) +
`shutil.rmtree` in finally

#### 3. Transcript support for Fast mode
- Baseline service now downloads / validates / loads / appends / uploads
transcripts (parity with SDK)
- Enables seamless mode switching mid-conversation via shared transcript
- Upload shielded from cancellation, bounded at 5s timeout

#### 4. Feature-flag infrastructure fixes
- `FORCE_FLAG_*` env-var overrides on both backend and frontend for
local dev / E2E
- LaunchDarkly context parity (frontend mirrors backend user context)
- `CHAT_MODE_OPTION` default flipped to `false` to match backend

#### 5. Other hardening
- Double-submit ref guard in `useChatInput` + reconnect dedup in
`useCopilotStream`
- `copilotModeRef` pattern to read latest mode without recreating
transport
- Shared `CopilotMode` type across frontend files
- File name collision handling with numeric suffix
- Path sanitization in file description hints (`os.path.basename`)

### Test plan
- [x] 30 new unit tests: `_env_flag_override` (12), `envFlagOverride`
(8), `_filter_tools_by_permissions` (4), `_prepare_baseline_attachments`
(6)
- [x] E2E tested on dev: fast mode creates E2B sandbox, calls 7-10
tools, generates and renders images
- [x] Mode switching mid-session works (shared transcript + session
messages)
- [x] Server-side flag gate enforced (crafted `mode=fast` stripped when
flag off)
- [x] All 37 CI checks green
- [x] Verified via agent-browser: workspace images render correctly in
all message positions

🤖 Generated with [Claude Code](https://claude.com/claude-code)

---------

Co-authored-by: Zamil Majdy <majdy.zamil@gmail.com>
2026-04-06 19:54:36 +07:00
Nicholas Tindle
1a305db162 ci(frontend): add Playwright E2E coverage reporting to Codecov (#12665)
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-04 00:55:09 -05:00
Zamil Majdy
48a653dc63 fix(copilot): prevent duplicate side effects from double-submit and stale-cache race (#12660)
## Why

#12604 (intermediate persistence) introduced two bugs on dev:

1. **Duplicate user messages** — `set_turn_duration` calls
`invalidate_session_cache()` which deletes the Redis key. Concurrent
`get_chat_session()` calls re-populate it from DB with stale data. The
executor loads this stale cache, misses the user message, and re-appends
it.

2. **Tool outputs lost on hydration** — Intermediate flushes save
assistant messages to DB before `StreamToolInputAvailable` sets
`tool_calls` on them. Since `_save_session_to_db` is append-only (uses
`start_sequence`), the `tool_calls` update is lost — subsequent flushes
start past that index. On page refresh / SSE reconnect, tool UIs
(SetupRequirementsCard, run_block output, etc.) are invisible.

3. **Sessions stuck running** — If a tool call hangs (e.g. WebSearch
provider not responding), the stream never completes,
`mark_session_completed` never runs, and the `active_stream` flag stays
stale in Redis.

## What

- **In-place cache update** in `set_turn_duration` — replaces
`invalidate_session_cache()` with a read-modify-write that patches the
duration on the cached session, eliminating the stale-cache repopulation
window
- **tool_calls backfill** — tracks the flush watermark and assistant
message index; when `StreamToolInputAvailable` sets `tool_calls` on an
already-flushed assistant, updates the DB record directly via
`update_message_tool_calls()`
- **Improved message dedup** — `is_message_duplicate()` /
`maybe_append_user_message()` scans trailing same-role messages (current
turn) instead of only checking `messages[-1]`
- **Idle timeout** — aborts the stream with a retryable error if no
meaningful SDK message arrives for 10 minutes, preventing hung tool
calls from leaving sessions stuck

## Changes

- `copilot/db.py` — `update_message_tool_calls()`, in-place cache update
in `set_turn_duration`
- `copilot/model.py` — `is_message_duplicate()`,
`maybe_append_user_message()`
- `copilot/sdk/service.py` — flush watermark tracking, tool_calls
backfill, idle timeout
- `copilot/baseline/service.py` — use `maybe_append_user_message()`
- `copilot/model_test.py` — unit tests for dedup
- `copilot/db_test.py` — unit tests for set_turn_duration cache update

## Checklist

- [x] My PR title follows [conventional
commit](https://www.conventionalcommits.org/) format
- [x] Out-of-scope changes are less than 20% of the PR
- [x] Changes to `data/*.py` validated for user ID checks (N/A)
- [x] Protected routes updated in middleware (N/A)
2026-04-04 01:09:42 +07:00
Toran Bruce Richards
f6ddcbc6cb feat(platform): Add all 12 Z.ai GLM models via OpenRouter (#12672)
## Summary

Add Z.ai (Zhipu AI) GLM model family to the platform LLM blocks, routed
through OpenRouter. This enables users to select any of the 12 Z.ai
models across all LLM-powered blocks (AI Text Generator, AI
Conversation, AI Structured Response, AI Text Summarizer, AI List
Generator).

## Gap Analysis

All 12 Z.ai models currently available on OpenRouter's API were missing
from the AutoGPT platform:

| Model | Context Window | Max Output | Price Tier | Cost |
|-------|---------------|------------|------------|------|
| GLM 4 32B | 128K | N/A | Tier 1 | 1 |
| GLM 4.5 | 131K | 98K | Tier 2 | 2 |
| GLM 4.5 Air | 131K | 98K | Tier 1 | 1 |
| GLM 4.5 Air (Free) | 131K | 96K | Tier 1 | 1 |
| GLM 4.5V (vision) | 65K | 16K | Tier 2 | 2 |
| GLM 4.6 | 204K | 204K | Tier 1 | 1 |
| GLM 4.6V (vision) | 131K | 131K | Tier 1 | 1 |
| GLM 4.7 | 202K | 65K | Tier 1 | 1 |
| GLM 4.7 Flash | 202K | N/A | Tier 1 | 1 |
| GLM 5 | 80K | 131K | Tier 2 | 2 |
| GLM 5 Turbo | 202K | 131K | Tier 3 | 4 |
| GLM 5V Turbo (vision) | 202K | 131K | Tier 3 | 4 |

## Changes

- **`autogpt_platform/backend/backend/blocks/llm.py`**: Added 12
`LlmModel` enum entries and corresponding `MODEL_METADATA` with context
windows, max output tokens, display names, and price tiers sourced from
OpenRouter API
- **`autogpt_platform/backend/backend/data/block_cost_config.py`**:
Added `MODEL_COST` entries for all 12 models, with costs scaled to match
pricing (1 for budget, 2 for mid-range, 4 for premium)

## How it works

All Z.ai models route through the existing OpenRouter provider
(`open_router`) — no new provider or API client code needed. Users with
an OpenRouter API key can immediately select any Z.ai model from the
model dropdown in any LLM block.

## Related

- Linear: REQ-83

---------

Co-authored-by: AutoGPT CoPilot <copilot@agpt.co>
2026-04-03 15:48:33 +00:00
Zamil Majdy
98f13a6e5d feat(copilot): add create -> dry-run -> fix loop to agent generation (#12578)
## Summary
- Instructs the copilot LLM to automatically dry-run agents after
creating or editing them, inspect the output for wiring/data-flow
issues, and fix iteratively before presenting the agent as ready to the
user
- Updates tool descriptions (run_agent, get_agent_building_guide),
prompting supplement, and agent generation guide with clear workflow
instructions and error pattern guidance
- Adds Tool Discovery Priority to shared tool notes (find_block ->
run_mcp_tool -> SendAuthenticatedWebRequestBlock -> manual API)
- Adds 37 tests: prompt regression tests + functional tests (tool schema
validation, Pydantic model, guide workflow ordering)
- **Frontend**: Fixes host-scoped credential UX — replaces duplicate
credentials for the same host instead of stacking them, wires up delete
functionality with confirmation modal, updates button text contextually
("Update headers" vs "Add headers")

## Test plan
- [x] All 37 `dry_run_loop_test.py` tests pass (prompt content, tool
schemas, Pydantic model, guide ordering)
- [x] Existing `tool_schema_test.py` passes (110 tests including
character budget gate)
- [x] Ruff lint and format pass
- [x] Pyright type checking passes
- [x] Frontend: `pnpm lint`, `pnpm types` pass
- [x] Manual verification: confirm copilot follows the create -> dry-run
-> fix workflow when asked to build an agent
- [x] Manual verification: confirm host-scoped credentials replace
instead of duplicate
2026-04-03 14:48:57 +00:00
Zamil Majdy
613978a611 ci: add gitleaks secret scanning to pre-commit hooks (#12649)
### Why / What / How

**Why:** We had no local pre-commit protection against accidentally
committing secrets. The existing `detect-secrets` hook only ran on
`pre-push`, which is too late — secrets are already in git history by
that point. GitHub's push protection only covers known provider patterns
and runs server-side.

**What:** Adds a 3-layer defense against secret leaks: local pre-commit
hooks (gitleaks + detect-secrets), and a CI workflow as a safety net.

**How:** 
- Moved `detect-secrets` from `pre-push` to `pre-commit` stage
- Added `gitleaks` as a second pre-commit hook (Go binary, faster and
more comprehensive rule set)
- Added `.gitleaks.toml` config with allowlists for known false
positives (test fixtures, dev docker JWTs, Firebase public keys, lock
files, docs examples)
- Added `repo-secret-scan.yml` CI workflow using `gitleaks-action` on
PRs/pushes to master/dev

### Changes 🏗️

- `.pre-commit-config.yaml`: Moved `detect-secrets` to pre-commit stage,
added baseline arg, added `gitleaks` hook
- `.gitleaks.toml`: New config with tuned allowlists for this repo's
false positives
- `.secrets.baseline`: Empty baseline for detect-secrets to track known
findings
- `.github/workflows/repo-secret-scan.yml`: New CI workflow running
gitleaks on every PR and push

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] Ran `gitleaks detect --no-git` against the full repo — only `.env`
files (gitignored) remain as findings
  - [x] Verified gitleaks catches a test secret file correctly
- [x] Pre-commit hooks pass on commit (both detect-secrets and gitleaks
passed)

#### For configuration changes:

- [x] `.env.default` is updated or already compatible with my changes
- [x] `docker-compose.yml` is updated or already compatible with my
changes
- [x] I have included a list of my configuration changes in the PR
description (under **Changes**)
2026-04-03 14:01:26 +00:00
Zamil Majdy
2b0e8a5a9f feat(platform): add rate-limit tiering system for CoPilot (#12581)
## Summary
- Adds a four-tier subscription system (FREE/PRO/BUSINESS/ENTERPRISE)
for CoPilot with configurable multipliers (1x/5x/20x/60x) applied on top
of the base LaunchDarkly/config limits
- Stores user tier in the database (`User.subscriptionTier` column as a
Prisma enum, defaults to PRO for beta testing) with admin API endpoints
for tier management
- Includes tier info in usage status responses and OTEL/Langfuse trace
metadata for observability

## Tier Structure
| Tier | Multiplier | Daily Tokens | Weekly Tokens | Notes |
|------|-----------|-------------|--------------|-------|
| FREE | 1x | 2.5M | 12.5M | Base tier (unused during beta) |
| PRO | 5x | 12.5M | 62.5M | Default on sign-up (beta) |
| BUSINESS | 20x | 50M | 250M | Manual upgrade for select users |
| ENTERPRISE | 60x | 150M | 750M | Highest tier, custom |

## Changes
- **`rate_limit.py`**: `SubscriptionTier` enum
(FREE/PRO/BUSINESS/ENTERPRISE), `TIER_MULTIPLIERS`, `get_user_tier()`,
`set_user_tier()`, update `get_global_rate_limits()` to apply tier
multiplier and return 3-tuple, add `tier` field to `CoPilotUsageStatus`
- **`rate_limit_admin_routes.py`**: Add `GET/POST
/admin/rate_limit/tier` endpoints, include `tier` in
`UserRateLimitResponse`
- **`routes.py`** (chat): Include tier in `/usage` endpoint response
- **`sdk/service.py`**: Send `subscription_tier` in OTEL/Langfuse trace
metadata
- **`schema.prisma`**: Add `SubscriptionTier` enum and
`subscriptionTier` column to `User` model (default: PRO)
- **`config.py`**: Update docs to reflect tier system
- **Migration**: `20260326200000_add_rate_limit_tier` — creates enum,
migrates STANDARD→PRO, adds BUSINESS, sets default to PRO

## Test plan
- [x] 72 unit tests all passing (43 rate_limit + 11 admin routes + 18
chat routes)
- [ ] Verify FREE tier users get base limits (2.5M daily, 12.5M weekly)
- [ ] Verify PRO tier users get 5x limits (12.5M daily, 62.5M weekly)
- [ ] Verify BUSINESS tier users get 20x limits (50M daily, 250M weekly)
- [ ] Verify ENTERPRISE tier users get 60x limits (150M daily, 750M
weekly)
- [ ] Verify admin can read and set user tiers via API
- [ ] Verify tier info appears in Langfuse traces
- [ ] Verify migration applies cleanly (creates enum, migrates STANDARD
users to PRO, adds BUSINESS, default PRO)

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: Nicholas Tindle <nicholas.tindle@agpt.co>
2026-04-03 13:36:01 +00:00
Zamil Majdy
08bb05141c dx: enhance pr-address skill with detailed codecov coverage guidance (#12662)
Enhanced pr-address skill codecov section with local coverage commands,
priority guide, and troubleshooting steps.
2026-04-03 13:15:46 +00:00
Nicholas Tindle
3ccaa5e103 ci(frontend): make frontend coverage checks informational (non-blocking) (#12663)
### Why / What / How

**Why:** Frontend test coverage is still ramping up. The default
component status checks (project + patch at 80%) would block merges for
insufficient coverage on frontend changes, which isn't practical yet.

**What:** Override the platform-frontend component's coverage statuses
to be `informational: true`, so they report but don't block merges.

**How:** Added explicit `statuses` to the `platform-frontend` component
in `codecov.yml` with `informational: true` on both project and patch
checks, overriding the `default_rules`.

### Changes 🏗️

- **`codecov.yml`**: Added `informational: true` to platform-frontend
component's project and patch status checks

### Checklist 📋

#### For code changes:
- [ ] I have clearly listed my changes in the PR description
- [ ] I have made a test plan
- [ ] I have tested my changes according to the test plan:
- [ ] Verify Codecov frontend status checks show as informational
(non-blocking) on PRs touching frontend code

#### For configuration changes:

- [x] `.env.default` is updated or already compatible with my changes
- [x] `docker-compose.yml` is updated or already compatible with my
changes
- [x] I have included a list of my configuration changes in the PR
description (under **Changes**)

<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> **Low Risk**
> Low risk: Codecov configuration-only change that affects merge gating
for frontend coverage statuses but does not alter runtime code.
> 
> **Overview**
> Updates `codecov.yml` to override the `platform-frontend` component’s
coverage `statuses` so both **project** and **patch** checks are marked
`informational: true` (non-blocking), while leaving the default
component coverage rules unchanged for other components.
> 
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
f8e8426a31. This will update automatically
on new commits. Configure
[here](https://cursor.com/dashboard?tab=bugbot).</sup>
<!-- /CURSOR_SUMMARY -->

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-03 12:22:05 +00:00
Krzysztof Czerwinski
09e42041ce fix(frontend): AutoPilot notification follow-ups — branding, UX, persistence, and cross-tab sync (#12428)
AutoPilot (copilot) notifications had several follow-up issues after
initial implementation: old "Otto" branding, UX quirks, a service-worker
crash, notification state that didn't persist or sync across tabs, a
broken notification sound, and noisy Sentry alerts from SSR.

### Changes 🏗️

- **Rename "Otto" → "AutoPilot"** in all notification surfaces: browser
notifications, document title badge, permission dialog copy, and
notification banner copy
- **Agent Activity icon**: changed from `Bell` to `Pulse` (Phosphor) in
the navbar dropdown
- **Centered dialog buttons**: the "Stay in the loop" permission dialog
buttons are now centered instead of right-aligned
- **Service worker notification fix**: wrapped `new Notification()` in
try-catch so it degrades gracefully in service worker / PWA contexts
instead of throwing `TypeError: Illegal constructor`
- **Persist notification state**: `completedSessionIDs` is now stored in
localStorage (`copilot-completed-sessions`) so it survives page
refreshes and new tabs
- **Cross-tab sync**: a `storage` event listener keeps
`completedSessionIDs` and `document.title` in sync across all open tabs
— clearing a notification in one tab clears it everywhere
- **Fix notification sound**: corrected the sound file path from
`/sounds/notification.mp3` to `/notification.mp3` and added a
`.gitignore` exception (root `.gitignore` has a blanket `*.mp3` ignore
rule from legacy AutoGPT agent days)
- **Fix SSR Sentry noise**: guarded the Copilot Zustand store
initialization with a client-side check so `storage.get()` is never
called during SSR, eliminating spurious Sentry alerts (BUILDER-7CB, 7CC,
7C7) while keeping the Sentry reporting in `local-storage.ts` intact for
genuinely unexpected SSR access

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] Verify "AutoPilot" appears (not "Otto") in browser notification,
document title, permission dialog, and banner
  - [x] Verify Pulse icon in navbar Agent Activity dropdown
  - [x] Verify "Stay in the loop" dialog buttons are centered
- [x] Open two tabs on copilot → trigger completion → both tabs show
badge/checkmark
  - [x] Click completed session in tab 1 → badge clears in both tabs
  - [x] Refresh a tab → completed session state is preserved
  - [x] Verify notification sound plays on completion
  - [x] Verify no Sentry alerts from SSR localStorage access

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-03 11:44:22 +00:00
Zamil Majdy
a50e95f210 feat(backend/copilot): add include_graph option to find_library_agent (#12622)
## Why

The copilot's `edit_agent` tool requires the LLM to provide a complete
agent JSON (all nodes + links), but the LLM had **no way to see the
current graph structure** before editing. It was editing blindly —
guessing/hallucinating the entire node+link structure and replacing the
graph wholesale.

## What

- Add `include_graph` boolean parameter (default `false`) to the
existing `find_library_agent` tool
- When `true`, each returned `AgentInfo` includes a `graph` field with
the full graph JSON (nodes, links, `input_default` values)
- Update the agent generation guide to instruct the LLM to always fetch
the current graph before editing

## How

- Added `graph: dict[str, Any] | None` field to `AgentInfo` model
- Added `_enrich_agents_with_graph()` helper in `agent_search.py` that
calls the existing `get_agent_as_json()` utility to fetch full graph
data
- Threaded `include_graph` parameter through `find_library_agent` →
`search_agents` → `_search_library`
- Updated `agent_generation_guide.md` to add an "if editing" step that
fetches the graph first

No new tools introduced — reuses existing `find_library_agent` with one
optional flag.

## Test plan

- [x] Unit tests: 2 new tests added
(`test_include_graph_fetches_nodes_and_links`,
`test_include_graph_false_does_not_fetch`)
- [x] All 7 `agent_search_test.py` tests pass
- [x] All pre-commit hooks pass (lint, format, typecheck)
- [ ] Verify copilot correctly uses `include_graph=true` before editing
an agent (manual test)
2026-04-03 11:20:57 +00:00
Zamil Majdy
92b395d82a fix(backend): use OpenRouter client for simulator to support non-OpenAI models (#12656)
## Why

Dry-run block simulation is failing in production with `404 - model
gemini-2.5-flash does not exist`. The simulator's default model
(`google/gemini-2.5-flash`) is a non-OpenAI model that requires
OpenRouter routing, but the shared `get_openai_client()` prefers the
direct OpenAI key, creating a client that can't handle non-OpenAI
models. The old code also stripped the provider prefix, sending
`gemini-2.5-flash` to OpenAI's API.

## What

- Added `prefer_openrouter` keyword parameter to `get_openai_client()` —
when True, prefers the OpenRouter key (returns None if unavailable,
rather than falling back to an incompatible direct OpenAI client)
- Simulator now calls `get_openai_client(prefer_openrouter=True)` so
`google/gemini-2.5-flash` routes correctly through OpenRouter
- Removed the redundant `SIMULATION_MODEL` env var override and the
now-unnecessary provider prefix stripping from `_simulator_model()`

## How

`get_openai_client()` is decorated with `@cached(ttl_seconds=3600)`
which keys by args, so `get_openai_client()` and
`get_openai_client(prefer_openrouter=True)` are cached independently.
When `prefer_openrouter=True` and no OpenRouter key exists, returns
`None` instead of falling back — the simulator already handles `None`
with a clear error message.

### Checklist
- [x] All 24 dry-run tests pass
- [x] Test asserts `get_openai_client` is called with
`prefer_openrouter=True`
- [x] Format, lint, and pyright pass
- [x] No changes to user-facing APIs
- [ ] Deploy to staging and verify simulation works

---------

Co-authored-by: Nicholas Tindle <nicholas.tindle@agpt.co>
2026-04-03 11:19:09 +00:00
Ubbe
86abfbd394 feat(frontend): redesign onboarding wizard with Autopilot-first flow (#12640)
### Why / What / How

<img width="800" height="827" alt="Screenshot 2026-04-02 at 15 40 24"
src="https://github.com/user-attachments/assets/69a381c1-2884-434b-9406-4a3f7eec87cf"
/>
<img width="800" height="825" alt="Screenshot 2026-04-02 at 15 40 41"
src="https://github.com/user-attachments/assets/c6191a68-a8ba-482b-ba47-c06c71d69f0c"
/>
<img width="800" height="825" alt="Screenshot 2026-04-02 at 15 40 48"
src="https://github.com/user-attachments/assets/31b632b9-59cb-4bf7-a6a0-6158846fcf9a"
/>
<img width="800" height="812" alt="Screenshot 2026-04-02 at 15 40 54"
src="https://github.com/user-attachments/assets/64e38a15-2e56-4c0e-bd84-987bf6076bf7"
/>



**Why:** The existing onboarding flow was outdated and didn't align with
the new Autopilot-first experience. New users need a streamlined,
visually polished wizard that collects their role and pain points to
personalize Autopilot suggestions.

**What:** Complete redesign of the onboarding wizard as a 4-step flow:
Welcome → Role selection → Pain points → Preparing workspace. Uses the
design system throughout (atoms/molecules), adds animations, and syncs
steps with URL search params.

**How:** 
- Zustand store manages wizard state (name, role, pain points, current
step)
- Steps synced to `?step=N` URL params for browser navigation support
- Pain points reordered based on selected role (e.g. Sales sees "Finding
leads" first)
- Design system components used exclusively (no raw shadcn `ui/`
imports)
- New reusable components: `FadeIn` (atom), `TypingText` (molecule) with
Storybook stories
- `AutoGPTLogo` made sizeable via Tailwind className prop, migrated in
Navbar
- Fixed `SetupAnalytics` crash (client component was rendered inside
`<head>`)

### Changes 🏗️

- **New onboarding wizard** (`steps/WelcomeStep`, `RoleStep`,
`PainPointsStep`, `PreparingStep`)
- **New shared components**: `ProgressBar`, `StepIndicator`,
`SelectableCard`, `CardCarousel`
- **New design system components**: `FadeIn` atom with stories,
`TypingText` molecule with stories
- **`AutoGPTLogo`** — size now controlled via `className` prop instead
of numeric `size`
- **Navbar** — migrated from legacy `IconAutoGPTLogo` to design system
`AutoGPTLogo`
- **Layout fix** — moved `SetupAnalytics` from `<head>` to `<body>` to
fix React hydration crash
- **Role-based pain point ordering** — top picks surfaced first based on
role selection
- **URL-synced steps** — `?step=N` search params for back/forward
navigation
- Removed old onboarding pages (1-welcome through 6-congrats, reset
page)
- Emoji/image assets for role selection cards

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  - [x] Complete onboarding flow from step 1 through 4 as a new user
  - [x] Verify back button navigates to previous step
  - [x] Verify progress bar advances correctly (hidden on step 4)
  - [x] Verify step indicator dots show for steps 1-3
  - [x] Verify role selection reorders pain points on next step
  - [x] Verify "Other" role/pain point shows text input
  - [x] Verify typing animation on PreparingStep title
  - [x] Verify fade-in animations on all steps
  - [x] Verify URL updates with `?step=N` on navigation
  - [x] Verify browser back/forward works with step URLs
  - [x] Verify mobile horizontal scroll on card grids
  - [x] Verify `pnpm types` passes cleanly

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-03 18:06:57 +07:00
Nicholas Tindle
a7f4093424 ci(platform): set up Codecov coverage reporting across platform and classic (#12655)
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-03 03:48:30 -05:00
Nicholas Tindle
e33b1e2105 feat(classic): update classic autogpt a bit to make it more useful for my day to day (#11797)
## Summary

This PR modernizes AutoGPT Classic to make it more useful for day-to-day
autonomous agent development. Major changes include consolidating the
project structure, adding new prompt strategies, modernizing the
benchmark system, and improving the development experience.

**Note: AutoGPT Classic is an experimental, unsupported project
preserved for educational/historical purposes. Dependencies will not be
actively updated.**

## Changes 🏗️

### Project Structure & Build System
- **Consolidated Poetry projects** - Merged `forge/`,
`original_autogpt/`, and benchmark packages into a single
`pyproject.toml` at `classic/` root
- **Removed old benchmark infrastructure** - Deleted the complex
`agbenchmark` package (3000+ lines) in favor of the new
`direct_benchmark` harness
- **Removed frontend** - Deleted `benchmark/frontend/` React app (no
longer needed)
- **Cleaned up CI workflows** - Simplified GitHub Actions workflows for
the consolidated project structure
- **Added CLAUDE.md** - Documentation for working with the codebase
using Claude Code

### New Direct Benchmark System
- **`direct_benchmark` harness** - New streamlined benchmark runner
with:
  - Rich TUI with multi-panel layout showing parallel test execution
  - Incremental resume and selective reset capabilities
  - CI mode for non-interactive environments
  - Step-level logging with colored prefixes
  - "Would have passed" tracking for timed-out challenges
  - Copy-paste completion blocks for sharing results

### Multiple Prompt Strategies
Added pluggable prompt strategy system supporting:
- **one_shot** - Single-prompt completion
- **plan_execute** - Plan first, then execute steps
- **rewoo** - Reasoning without observation (deferred tool execution)
- **react** - Reason + Act iterative loop
- **lats** - Language Agent Tree Search (MCTS-based exploration)
- **sub_agent** - Multi-agent delegation architecture
- **debate** - Multi-agent debate for consensus

### LLM Provider Improvements
- Added support for modern **Anthropic Claude models**
(claude-3.5-sonnet, claude-3-haiku, etc.)
- Added **Groq** provider support
- Improved tool call error feedback for LLM self-correction
- Fixed deprecated API usage

### Web Components
- **Replaced Selenium with Playwright** for web browsing (better async
support, faster)
- Added **lightweight web fetch component** for simple URL fetching
- **Modernized web search** with tiered provider system (Tavily, Serper,
Google)

### Agent Capabilities
- **Workspace permissions system** - Pattern-based allow/deny lists for
agent commands
- **Rich interactive selector** for command approval with scopes
(once/agent/workspace/deny)
- **TodoComponent** with LLM-powered task decomposition
- **Platform blocks integration** - Connect to AutoGPT Platform API for
additional blocks
- **Sub-agent architecture** - Agents can spawn and coordinate
sub-agents

### Developer Experience
- **Python 3.12+ support** with CI testing on 3.12, 3.13, 3.14
- **Current working directory as default workspace** - Run `autogpt`
from any project directory
- Simplified log format (removed timestamps)
- Improved configuration and setup flow
- External benchmark adapters for GAIA, SWE-bench, and AgentBench

### Bug Fixes
- Fixed N/A command loop when using native tool calling
- Fixed auto-advance plan steps in Plan-Execute strategy
- Fixed approve+feedback to execute command then send feedback
- Fixed parallel tool calls in action history
- Always recreate Docker containers for code execution
- Various pyright type errors resolved
- Linting and formatting issues fixed across codebase

## Test Plan

- [x] CI lint, type, and test checks pass
- [x] Run `poetry install` from `classic/` directory
- [x] Run `poetry run autogpt` and verify CLI starts
- [x] Run `poetry run direct-benchmark run --tests ReadFile` to verify
benchmark works

## Notes

- This is a WIP PR for personal use improvements
- The project is marked as **unsupported** - no active maintenance
planned
- Contains known vulnerabilities in dependencies (intentionally not
updated)

<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> **Medium Risk**
> CI/build workflows are substantially reworked (runner matrix removal,
path/layout changes, new benchmark runner), so breakage is most likely
in automation and packaging rather than runtime behavior.
> 
> **Overview**
> **Modernizes the `classic/` project layout and automation around a
single consolidated Poetry project** (root
`classic/pyproject.toml`/`poetry.lock`) and updates docs
(`classic/README.md`, new `classic/CLAUDE.md`) accordingly.
> 
> **Replaces the old `agbenchmark` CI usage with `direct-benchmark` in
GitHub Actions**, including new/updated benchmark smoke and regression
workflows, standardized `working-directory: classic`, and a move to
**Python 3.12** on Ubuntu-only runners (plus updated caching, coverage
flags, and required `ANTHROPIC_API_KEY` wiring).
> 
> Cleans up repo/dev tooling by removing the classic frontend workflow,
deleting the Forge VCR cassette submodule (`.gitmodules`) and associated
CI steps, consolidating `flake8`/`isort`/`pyright` pre-commit hooks to
run from `classic/`, updating ignores for new report/workspace
artifacts, and updating `classic/Dockerfile.autogpt` to build from
Python 3.12 with the consolidated project structure.
> 
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
de67834dac. This will update automatically
on new commits. Configure
[here](https://cursor.com/dashboard?tab=bugbot).</sup>
<!-- /CURSOR_SUMMARY -->

---------

Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
2026-04-03 07:16:36 +00:00
Zamil Majdy
fff101e037 feat(backend): add SQL query block with multi-database support for CoPilot analytics (#12569)
## Summary
- Add a read-only SQL query block for CoPilot/AutoPilot analytics access
- Supports **multiple databases**: PostgreSQL, MySQL, SQLite, MSSQL via
SQLAlchemy
- Enforces read-only queries (SELECT only) with defense-in-depth SQL
validation using sqlparse
- SSRF protection: blocks connections to private/internal IPs
- Credentials stored securely via the platform credential system

## Changes
- New `SQLQueryBlock` in `backend/blocks/sql_query_block.py` with
`DatabaseType` enum
- SQLAlchemy-based execution with dialect-specific read-only and timeout
settings
- Connection URL validation ensuring driver matches selected database
type
- Comprehensive test suite (62 tests) including URL validation,
sanitization, serialization
- Documentation in `docs/integrations/block-integrations/data.md`
- Added `DATABASE` provider to `ProviderName` enum

### Checklist 📋
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan

#### Test plan:
- [x] Unit tests pass for query validation, URL validation, error
sanitization, value serialization
- [x] Read-only enforcement rejects INSERT/UPDATE/DELETE/DROP
- [x] Multi-statement injection blocked
- [x] SSRF protection blocks private IPs
- [x] Connection URL driver validation works for all 4 database types

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-03 06:43:40 +00:00
Zamil Majdy
f1ac05b2e0 fix(backend): propagate dry-run mode to special blocks with LLM-powered simulation (#12575)
## Summary
- **OrchestratorBlock & AgentExecutorBlock** now execute for real in
dry-run mode so the orchestrator can make LLM calls and agent executors
can spawn child graphs. Their downstream tool blocks and child-graph
blocks are still simulated via `simulate_block()`. Credential fields
from node defaults are restored since `validate_exec()` wipes them in
dry-run mode. Agent-mode iterations capped at 1 in dry-run.
- **All blocks** (including MCPToolBlock) are simulated via a single
generic `simulate_block()` path. The LLM prompt is grounded by
`inspect.getsource(block.run)`, giving the simulator access to the exact
implementation of each block's `run()` method. This produces realistic
mock responses for any block type without needing block-specific
simulation logic.
- Updated agent generation guide to document special block dry-run
behavior.
- Minor frontend fixes: exported `formatCents` from
`RateLimitResetDialog` for reuse in `UsagePanelContent`, used `useRef`
for stable callback references in `useResetRateLimit` to avoid stale
closures.
- 74 tests (21 existing dry-run + 53 new simulator tests covering prompt
building, passthrough logic, and special block dry-run).

## Design

The simulator (`backend/executor/simulator.py`) uses a two-tier
approach:

1. **Passthrough blocks** (OrchestratorBlock, AgentExecutorBlock):
`prepare_dry_run()` returns modified input_data so these blocks execute
for real in `manager.py`. OrchestratorBlock gets `max_iterations=1`
(agent mode) or 0 (traditional mode). AgentExecutorBlock spawns real
child graph executions whose blocks inherit `dry_run=True`.

2. **All other blocks**: `simulate_block()` builds an LLM prompt
containing:
   - Block name and description
   - Input/output schemas (JSON Schema)
   - The block's `run()` source code via `inspect.getsource(block.run)`
- The actual input values (with credentials stripped and long values
truncated)

The LLM then role-plays the block's execution, producing realistic
outputs grounded in the actual implementation.

Special handling for input/output blocks: `AgentInputBlock` and
`AgentOutputBlock` are pure passthrough (no LLM call needed).

## Test plan
- [x] All 74 tests pass (`pytest backend/copilot/tools/test_dry_run.py
backend/executor/simulator_test.py`)
- [x] Pre-commit hooks pass (ruff, isort, black, pyright, frontend
typecheck)
- [x] CI: all checks green
- [x] E2E: dry-run execution completes with `is_dry_run=true`, cost=0,
no errors
- [x] E2E: normal (non-dry-run) execution unchanged
- [x] E2E: Create agent with OrchestratorBlock + tool blocks, run with
`dry_run=True`, verify orchestrator makes real LLM calls while tool
blocks are simulated
- [x] E2E: AgentExecutorBlock spawns child graph in dry-run, child
blocks are LLM-simulated
- [x] E2E: Builder simulate button works end-to-end with special blocks

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-02 17:09:55 +00:00
Zamil Majdy
f115607779 fix(copilot): recognize Agent tool name and route CLI state into workspace (#12635)
### Why / What / How

**Why:** The Claude Agent SDK CLI renamed the sub-agent tool from
`"Task"` to `"Agent"` in v2.x. Our security hooks only checked for
`"Task"`, so all sub-agent security controls were silently bypassed on
production: concurrency limiting didn't apply, and slot tracking was
broken. This was discovered via Langfuse trace analysis of session
`62b1b2b9` where background sub-agents ran unchecked.

Additionally, the CLI writes sub-agent output to `/tmp/claude-<uid>/`
and project state to `$HOME/.claude/` — both outside the per-session
workspace (`/tmp/copilot-<session>/`). This caused `PermissionError` in
E2B sandboxes and silently lost sub-agent results.

The frontend also had no rendering for the `Agent` / `TaskOutput` SDK
built-in tools — they fell through to the generic "other" category with
no context-aware display.

**What:**
1. Fix the sub-agent tool name recognition (`"Task"` → `{"Task",
"Agent"}`)
2. Allow `run_in_background` — the SDK handles async lifecycle cleanly
(returns `isAsync:true`, model polls via `TaskOutput`)
3. Route CLI state into the workspace via `CLAUDE_CODE_TMPDIR` and
`HOME` env vars
4. Add lifecycle hooks (`SubagentStart`/`SubagentStop`) for
observability
5. Add frontend `"agent"` tool category with proper UI rendering

**How:**
- Security hooks check `tool_name in _SUBAGENT_TOOLS` (frozenset of
`"Task"` and `"Agent"`)
- Background agents are allowed but still count against `max_subtasks`
concurrency limit
- Frontend detects `isAsync: true` output → shows "Agent started
(background)" not "Agent completed"
- `TaskOutput` tool shows retrieval status and collected results
- Robot icon and agent-specific accordion rendering for both foreground
and background agents

### Changes 🏗️

**Backend:**
- **`security_hooks.py`**: Replace `tool_name == "Task"` with `tool_name
in _SUBAGENT_TOOLS`. Remove `run_in_background` deny block (SDK handles
async lifecycle). Add `SubagentStart`/`SubagentStop` hooks.
- **`tool_adapter.py`**: Add `"Agent"` to `_SDK_BUILTIN_ALWAYS` list
alongside `"Task"`.
- **`service.py`**: Set `CLAUDE_CODE_TMPDIR=sdk_cwd` and `HOME=sdk_cwd`
in SDK subprocess env.
- **`security_hooks_test.py`**: Update background tests (allowed, not
blocked). Add test for background agents counting against concurrency
limit.

**Frontend:**
- **`GenericTool/helpers.ts`**: Add `"agent"` tool category for `Agent`,
`Task`, `TaskOutput`. Agent-specific animation text detecting `isAsync`
output. Input summaries from description/prompt fields.
- **`GenericTool/GenericTool.tsx`**: Add `RobotIcon` for agent category.
Add `getAgentAccordionData()` with async-aware title/content.
`TaskOutput` shows retrieval status.
- **`useChatSession.ts`**: Fix pre-existing TS error (void mutation
body).

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] All security hooks tests pass (background allowed + limit
enforced)
  - [x] Pre-commit hooks (ruff, black, isort, pyright, tsc) all pass
  - [x] E2E test: copilot agent create+run scenario PASS
- [ ] Deploy to dev and test copilot sub-agent spawning with background
mode

#### For configuration changes:
- [x] `.env.default` is updated or already compatible
- [x] `docker-compose.yml` is updated or already compatible
2026-04-03 00:09:19 +07:00
Zamil Majdy
1aef8b7155 fix(backend/copilot): fix tool output file reading between E2B and host (#12646)
### Why / What / How

**Why:** When copilot tools return large outputs (e.g. 3MB+ base64
images from API calls), the agent cannot process them in the E2B
sandbox. Three compounding issues prevent seamless file access:
1. The `<tool-output-truncated path="...">` tag uses a bare `path=`
attribute that the model confuses with a local filesystem path (it's
actually a workspace path)
2. `is_allowed_local_path` rejects `tool-outputs/` directories (only
`tool-results/` was allowed)
3. SDK-internal files read via the `Read` tool are not available in the
E2B sandbox for `bash_exec` processing

**What:** Fixes all three issues so that large tool outputs can be
seamlessly read and processed in both host and E2B contexts.

**How:**
- Changed `path=` → `workspace_path=` in the truncation tag to
disambiguate workspace vs filesystem paths
- Added `save_to_path` guidance in the retrieval instructions for E2B
users
- Extended `is_allowed_local_path` to accept both `tool-results` and
`tool-outputs` directories
- Added automatic bridging: when E2B is active and `Read` accesses an
SDK-internal file, the file is automatically copied to `/tmp/<filename>`
in the sandbox
- Updated system prompting to explain both SDK tool-result bridging and
workspace `<tool-output-truncated>` handling

### Changes 🏗️

- **`tools/base.py`**: `_persist_and_summarize` now uses
`workspace_path=` attribute and includes `save_to_path` example for E2B
processing
- **`context.py`**: `is_allowed_local_path` accepts both `tool-results`
and `tool-outputs` directory names
- **`sdk/e2b_file_tools.py`**: `_handle_read_file` bridges SDK-internal
files to `/tmp/` in E2B sandbox; new `_bridge_to_sandbox` helper
- **`prompting.py`**: Updated "SDK tool-result files" section and added
"Large tool outputs saved to workspace" section
- **Tests**: Added `tool-outputs` path validation tests in
`context_test.py` and `e2b_file_tools_test.py`; updated `base_test.py`
assertion for `workspace_path`

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] `poetry run pytest backend/copilot/tools/base_test.py` — all 9
tests pass (persistence, truncation, binary fields)
  - [x] `poetry run format` and `poetry run lint` pass clean
  - [x] All pre-commit hooks pass
- [ ] `context_test.py`, `e2b_file_tools_test.py`,
`security_hooks_test.py` — blocked by pre-existing DB migration issue on
worktree (missing `User.subscriptionTier` column); CI will validate
these
2026-04-03 00:08:04 +07:00
Nicholas Tindle
0da949ba42 feat(e2b): set git committer identity from user's GitHub profile (#12650)
## Summary

Sets git author/committer identity in E2B sandboxes using the user's
connected GitHub account profile, so commits are properly attributed.

## Changes

### `integration_creds.py`
- Added `get_github_user_git_identity(user_id)` that fetches the user's
name and email from the GitHub `/user` API
- Uses TTL cache (10 min) to avoid repeated API calls
- Falls back to GitHub noreply email
(`{id}+{login}@users.noreply.github.com`) when user has a private email
- Falls back to `login` if `name` is not set

### `bash_exec.py`
- After injecting integration env vars, calls
`get_github_user_git_identity()` and sets `GIT_AUTHOR_NAME`,
`GIT_AUTHOR_EMAIL`, `GIT_COMMITTER_NAME`, `GIT_COMMITTER_EMAIL`
- Only sets these if the user has a connected GitHub account

### `bash_exec_test.py`
- Added tests covering: identity set from GitHub profile, no identity
when GitHub not connected, no injection when no user_id

## Why
Previously, commits made inside E2B sandboxes had no author identity
set, leading to unattributed commits. This dynamically resolves identity
from the user's actual GitHub account rather than hardcoding a default.

<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> **Medium Risk**
> Adds outbound calls to GitHub’s `/user` API during `bash_exec` runs
and injects returned identity into the sandbox environment, which could
impact reliability (network/timeouts) and attribution behavior. Caching
mitigates repeated calls but incorrect/expired tokens or API failures
may lead to missing identity in commits.
> 
> **Overview**
> Sets git author/committer environment variables in the E2B `bash_exec`
path by fetching the connected user’s GitHub profile and injecting
`GIT_AUTHOR_*`/`GIT_COMMITTER_*` into the sandbox env.
> 
> Introduces `get_github_user_git_identity()` with TTL caching
(including a short-lived null cache), fallback to GitHub noreply email
when needed, and ensures `invalidate_user_provider_cache()` also clears
identity caches for the `github` provider. Updates tests to cover
identity injection behavior and the new cache invalidation semantics.
> 
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
955ec81efe. This will update automatically
on new commits. Configure
[here](https://cursor.com/dashboard?tab=bugbot).</sup>
<!-- /CURSOR_SUMMARY -->

---------

Co-authored-by: AutoGPT <autopilot@agpt.co>
2026-04-02 15:07:22 +00:00
Zamil Majdy
6b031085bd feat(platform): add generic ask_question copilot tool (#12647)
### Why / What / How

**Why:** The copilot can ask clarifying questions in plain text, but
that text gets collapsed into hidden "reasoning" UI when the LLM also
calls tools in the same turn. This makes clarification questions
invisible to users. The existing `ClarificationNeededResponse` model and
`ClarificationQuestionsCard` UI component were built for this purpose
but had no tool wiring them up.

**What:** Adds a generic `ask_question` tool that produces a visible,
interactive clarification card instead of collapsible plain text. Unlike
the agent-generation-specific `clarify_agent_request` proposed in
#12601, this tool is workflow-agnostic — usable for agent building,
editing, troubleshooting, or any flow needing user input.

**How:** 
- Backend: New `AskQuestionTool` reuses existing
`ClarificationNeededResponse` model. Registered in `TOOL_REGISTRY` and
`ToolName` permissions.
- Frontend: New `AskQuestion/` renderer reuses
`ClarificationQuestionsCard` from CreateAgent. Registered in
`CUSTOM_TOOL_TYPES` (prevents collapse into reasoning) and
`MessagePartRenderer`.
- Guide: `agent_generation_guide.md` updated to reference `ask_question`
for the clarification step.

### Changes 🏗️

- **`copilot/tools/ask_question.py`** — New generic tool: takes
`question`, optional `options[]` and `keyword`, returns
`ClarificationNeededResponse`
- **`copilot/tools/__init__.py`** — Register `ask_question` in
`TOOL_REGISTRY`
- **`copilot/permissions.py`** — Add `ask_question` to `ToolName`
literal
- **`copilot/sdk/agent_generation_guide.md`** — Reference `ask_question`
tool in clarification step
- **`ChatMessagesContainer/helpers.ts`** — Add `tool-ask_question` to
`CUSTOM_TOOL_TYPES`
- **`MessagePartRenderer.tsx`** — Add switch case for
`tool-ask_question`
- **`AskQuestion/AskQuestion.tsx`** — Renderer reusing
`ClarificationQuestionsCard`
- **`AskQuestion/helpers.ts`** — Output parsing and animation text

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  - [x] Backend format + pyright pass
  - [x] Frontend lint + types pass
  - [x] Pre-commit hooks pass
- [ ] Manual test: copilot uses `ask_question` and card renders visibly
(not collapsed)
2026-04-02 12:56:48 +00:00
Toran Bruce Richards
11b846dd49 fix(blocks): rename placeholder_values to options on AgentDropdownInputBlock (#12595)
## Summary

Resolves [REQ-78](https://linear.app/autogpt/issue/REQ-78): The
`placeholder_values` field on `AgentDropdownInputBlock` is misleadingly
named. In every major UI framework "placeholder" means non-binding hint
text that disappears on focus, but this field actually creates a
dropdown selector that restricts the user to only those values.

## Changes

### Core rename (`autogpt_platform/backend/backend/blocks/io.py`)
- Renamed `placeholder_values` → `options` on
`AgentDropdownInputBlock.Input`
- Added clear field description: *"If provided, renders the input as a
dropdown selector restricted to these values. Leave empty for free-text
input."*
- Updated class docstring to describe actual behavior
- Overrode `model_construct()` to remap legacy `placeholder_values` →
`options` for **backward compatibility** with existing persisted agent
JSON

### Tests (`autogpt_platform/backend/backend/blocks/test/test_block.py`)
- Updated existing tests to use canonical `options` field name
- Added 2 new backward-compat tests verifying legacy
`placeholder_values` still works through both `model_construct()` and
`Graph._generate_schema()` paths

### Documentation
- Updated
`autogpt_platform/backend/backend/copilot/sdk/agent_generation_guide.md`
— changed field name in CoPilot SDK guide
- Updated `docs/integrations/block-integrations/basic.md` — changed
field name and description in public docs

### Load tests
(`autogpt_platform/backend/load-tests/tests/api/graph-execution-test.js`)
- Removed spurious `placeholder_values: {}` from AgentInputBlock node
(this field never existed on AgentInputBlock)
- Fixed execution input to use `value` instead of `placeholder_values`

## Backward Compatibility

Existing agents with `placeholder_values` in their persisted
`input_default` JSON will continue to work — the `model_construct()`
override transparently remaps the old key to `options`. No database
migration needed since the field is stored inside a JSON blob, not as a
dedicated column.

## Testing

- All existing tests updated and passing
- 2 new backward-compat tests added
- No frontend changes needed (frontend reads `enum` from generated JSON
Schema, not the field name directly)

---------

Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
2026-04-02 05:56:17 +00:00
Zamil Majdy
b9e29c96bd fix(backend/copilot): detect prompt-too-long in AssistantMessage content and ResultMessage success subtype (#12642)
## Why

PR #12625 fixed the prompt-too-long retry mechanism for most paths, but
two SDK-specific paths were still broken. The dev session `d2f7cba3`
kept accumulating synthetic "Prompt is too long" error entries on every
turn, growing the transcript from 2.5 MB → 3.2 MB, making recovery
impossible.

Root causes identified from production logs (`[T25]`, `[T28]`):

**Path 1 — AssistantMessage content check:**
When the Claude API rejects a prompt, the SDK surfaces it as
`AssistantMessage(error="invalid_request", content=[TextBlock("Prompt is
too long")])`. Our check only inspected `error_text = str(sdk_error)`
which is `"invalid_request"` — not a prompt-too-long pattern. The
content was then streamed out as `StreamText`, setting `events_yielded =
1`, which blocked retry even when the ResultMessage fired.

**Path 2 — ResultMessage success subtype:**
After the SDK auto-compacts internally (via `PreCompact` hook) and the
compacted transcript is _still_ too long, the SDK returns
`ResultMessage(subtype="success", result="Prompt is too long")`. Our
check only ran for `subtype="error"`. With `subtype="success"`, the
stream "completed normally", appended the synthetic error entry to the
transcript via `transcript_builder`, and uploaded it to GCS — causing
the transcript to grow on each failed turn.

## What

- **AssistantMessage handler**: when `sdk_error` is set, also check the
content text. `sdk_error` being non-`None` confirms this is an API error
message (not user-generated content), so content inspection is safe.
- **ResultMessage handler**: check `result` for prompt-too-long patterns
regardless of `subtype`, covering the SDK auto-compact path where
`subtype="success"` with `result="Prompt is too long"`.

## How

Two targeted one-line condition expansions in `_run_stream_attempt`,
plus two new integration tests in `retry_scenarios_test.py` that
reproduce each broken path and verify retry fires correctly.

## Changes

- `backend/copilot/sdk/service.py`: fix AssistantMessage content check +
ResultMessage subtype-independent check
- `backend/copilot/sdk/retry_scenarios_test.py`: add 2 integration tests
for the new scenarios

## Checklist

- [x] Tests added for both new scenarios (45 total, all pass)
- [x] Formatted (`poetry run format`)
- [x] No false-positive risk: AssistantMessage check gated behind
`sdk_error is not None`
- [x] Root cause verified from production pod logs
2026-04-01 22:32:09 +00:00
Zamil Majdy
4ac0ba570a fix(backend): fix copilot credential loading across event loops (#12628)
## Why

CoPilot autopilot sessions are inconsistently failing to load user
credentials (specifically GitHub OAuth). Some sessions proceed normally,
some show "provide credentials" prompts despite the user having valid
creds, and some are completely blocked.

Production logs confirmed the root cause: `RuntimeError: Task got Future
<Future pending> attached to a different loop` in the credential refresh
path, cascading into null-cache poisoning that blocks credential lookups
for 60 seconds.

## What

Three interrelated bugs in the credential system:

1. **`refresh_if_needed` always acquired Redis locks even with
`lock=False`** — The `lock` parameter only controlled the inner
credential lock, but the outer "refresh" scope lock was always acquired.
The copilot executor uses multiple worker threads with separate event
loops; the `asyncio.Lock` inside `AsyncRedisKeyedMutex` was bound to one
loop and failed on others.

2. **Stale event loop in `locks()` singleton** — Both
`IntegrationCredentialsManager` and `IntegrationCredentialsStore` cached
their `AsyncRedisKeyedMutex` without tracking which event loop created
it. When a different worker thread (with a different loop) reused the
singleton, it got the "Future attached to different loop" error.

3. **Null-cache poisoning on refresh failure** — When OAuth refresh
failed (due to the event loop error), the code fell through to cache "no
credentials found" for 60 seconds via `_null_cache`. This blocked ALL
subsequent credential lookups for that user+provider, even though the
credentials existed and could refresh fine on retry.

## How

- Split `refresh_if_needed` into `_refresh_locked` / `_refresh_unlocked`
so `lock=False` truly skips ALL Redis locking (safe for copilot's
best-effort background injection)
- Added event loop tracking to `locks()` in both
`IntegrationCredentialsManager` and `IntegrationCredentialsStore` —
recreates the mutex when the running loop changes
- Only populate `_null_cache` when the user genuinely has no
credentials; skip caching when OAuth refresh failed transiently
- Updated existing test to verify null-cache is not poisoned on refresh
failure

## Test plan

- [x] All 14 existing `integration_creds_test.py` tests pass
- [x] Updated
`test_oauth2_refresh_failure_returns_none_without_null_cache` verifies
null-cache is not populated on refresh failure
- [x] Format, lint, and typecheck pass
- [ ] Deploy to staging and verify copilot sessions consistently load
GitHub credentials
2026-04-02 00:11:38 +07:00
Zamil Majdy
d61a2c6cd0 Revert "fix(backend/copilot): detect prompt-too-long in AssistantMessage content and ResultMessage success subtype"
This reverts commit 1c301b4b61.
2026-04-01 18:59:38 +02:00
Zamil Majdy
1c301b4b61 fix(backend/copilot): detect prompt-too-long in AssistantMessage content and ResultMessage success subtype
The SDK returns AssistantMessage(error="invalid_request", content=[TextBlock("Prompt is too long")])
followed by ResultMessage(subtype="success", result="Prompt is too long") when the transcript is
rejected after internal auto-compaction. Both paths bypassed the retry mechanism:

- AssistantMessage handler only checked error_text ("invalid_request"), not the content which
  holds the actual error description. The content was then streamed as text, setting events_yielded=1,
  which blocked retry even when ResultMessage fired.
- ResultMessage handler only triggered prompt-too-long detection for subtype="error", not
  subtype="success". The stream "completed normally", stored the synthetic error entry in the
  transcript, and uploaded it — causing the transcript to grow unboundedly on each failed turn.

Fixes:
1. AssistantMessage handler: when sdk_error is set (confirmed error message), also check content
   text. sdk_error being set guarantees this is an API error, not user-generated content, so
   content inspection is safe.
2. ResultMessage handler: check result for prompt-too-long regardless of subtype, covering the
   case where the SDK auto-compacts internally but the result is still too long.

Adds integration tests for both new scenarios.
2026-04-01 18:28:46 +02:00
Zamil Majdy
1750c833ee fix(frontend): upgrade Docker Node.js from v21 (EOL) to v22 LTS (#12561)
## Summary
Upgrade the frontend **Docker image** from **Node.js v21** (EOL since
June 2024) to **Node.js v22 LTS** (supported through April 2027).

> **Scope:** This only affects the **Dockerfile** used for local
development (`docker compose`) and CI. It does **not** affect Vercel
(which manages its own Node.js runtime) or Kubernetes (the frontend Helm
chart was removed in Dec 2025 — the frontend is deployed exclusively via
Vercel).

## Why
- Node v21.7.3 has a **known TransformStream race condition bug**
causing `TypeError: controller[kState].transformAlgorithm is not a
function` — this is
[BUILDER-3KF](https://significant-gravitas.sentry.io/issues/BUILDER-3KF)
with **567,000+ Sentry events**
- The error is entirely in Node.js internals
(`node:internal/webstreams/transformstream`), zero first-party code
- Node 21 is **not an LTS release** and has been EOL since June 2024
- `package.json` already declares `"engines": { "node": "22.x" }` — the
Dockerfile was inconsistent
- Node 22.x LTS (v22.22.1) fixes the TransformStream bug
- Next.js 15.4.x requires Node 18.18+, so Node 22 is fully compatible

## Changes
- `autogpt_platform/frontend/Dockerfile`: `node:21-alpine` →
`node:22.22-alpine3.23` (both `base` and `prod` stages)

## Test plan
- [ ] Verify frontend Docker image builds successfully via `docker
compose`
- [ ] Verify frontend starts and serves pages correctly in local Docker
environment
- [ ] Monitor Sentry for BUILDER-3KF — should drop to zero for
Docker-based runs
2026-03-27 13:11:23 +07:00
3440 changed files with 222422 additions and 835414 deletions

10
.claude/settings.json Normal file
View File

@@ -0,0 +1,10 @@
{
"permissions": {
"allowedTools": [
"Read", "Grep", "Glob",
"Bash(ls:*)", "Bash(cat:*)", "Bash(grep:*)", "Bash(find:*)",
"Bash(git status:*)", "Bash(git diff:*)", "Bash(git log:*)", "Bash(git worktree:*)",
"Bash(tmux:*)", "Bash(sleep:*)", "Bash(branchlet:*)"
]
}
}

View File

@@ -0,0 +1,709 @@
---
name: orchestrate
description: "Meta-agent supervisor that manages a fleet of Claude Code agents running in tmux windows. Auto-discovers spare worktrees, spawns agents, monitors state, kicks idle agents, approves safe confirmations, and recycles worktrees when done. TRIGGER when user asks to supervise agents, run parallel tasks, manage worktrees, check agent status, or orchestrate parallel work."
user-invocable: true
argument-hint: "any free text — e.g. 'start 3 agents on X Y Z', 'show status', 'add task: implement feature A', 'stop', 'how many are free?'"
metadata:
author: autogpt-team
version: "6.0.0"
---
# Orchestrate — Agent Fleet Supervisor
One tmux session, N windows — each window is one agent working in its own worktree. Speak naturally; Claude maps your intent to the right scripts.
## Scripts
```bash
SKILLS_DIR=$(git rev-parse --show-toplevel)/.claude/skills/orchestrate/scripts
STATE_FILE=~/.claude/orchestrator-state.json
```
| Script | Purpose |
|---|---|
| `find-spare.sh [REPO_ROOT]` | List free worktrees — one `PATH BRANCH` per line |
| `spawn-agent.sh SESSION PATH SPARE NEW_BRANCH OBJECTIVE [PR_NUMBER] [STEPS...]` | Create window + checkout branch + launch claude + send task. **Stdout: `SESSION:WIN` only** |
| `recycle-agent.sh WINDOW PATH SPARE_BRANCH` | Kill window + restore spare branch |
| `run-loop.sh` | **Mechanical babysitter** — idle restart + dialog approval + recycle on ORCHESTRATOR:DONE + supervisor health check + all-done notification |
| `verify-complete.sh WINDOW` | Verify PR is done: checkpoints ✓ + 0 unresolved threads + CI green + no fresh CHANGES_REQUESTED. Repo auto-derived from state file `.repo` or git remote. |
| `notify.sh MESSAGE` | Send notification via Discord webhook (env `DISCORD_WEBHOOK_URL` or state `.discord_webhook`), macOS notification center, and stdout |
| `capacity.sh [REPO_ROOT]` | Print available + in-use worktrees |
| `status.sh` | Print fleet status + live pane commands |
| `poll-cycle.sh` | One monitoring cycle — classifies panes, tracks checkpoints, returns JSON action array |
| `classify-pane.sh WINDOW` | Classify one pane state |
## Supervision model
```
Orchestrating Claude (this Claude session — IS the supervisor)
└── Reads pane output, checks CI, intervenes with targeted guidance
run-loop.sh (separate tmux window, every 30s)
└── Mechanical only: idle restart, dialog approval, recycle on ORCHESTRATOR:DONE
```
**You (the orchestrating Claude)** are the supervisor. After spawning agents, stay in this conversation and actively monitor: poll each agent's pane every 2-3 minutes, check CI, nudge stalled agents, and verify completions. Do not spawn a separate supervisor Claude window — it loses context, is hard to observe, and compounds context compression problems.
**run-loop.sh** is the mechanical layer — zero tokens, handles things that need no judgment: restart crashed agents, press Enter on dialogs, recycle completed worktrees (only after `verify-complete.sh` passes).
## Checkpoint protocol
Agents output checkpoints as they complete each required step:
```
CHECKPOINT:<step-name>
```
Required steps are passed as args to `spawn-agent.sh` (e.g. `pr-address pr-test`). `run-loop.sh` will not recycle a window until all required checkpoints are found in the pane output. If `verify-complete.sh` fails, the agent is re-briefed automatically.
## Worktree lifecycle
```text
spare/N branch → spawn-agent.sh (--session-id UUID) → window + feat/branch + claude running
CHECKPOINT:<step> (as steps complete)
ORCHESTRATOR:DONE
verify-complete.sh: checkpoints ✓ + 0 threads + CI green + no fresh CHANGES_REQUESTED
state → "done", notify, window KEPT OPEN
user/orchestrator explicitly requests recycle
recycle-agent.sh → spare/N (free again)
```
**Windows are never auto-killed.** The worktree stays on its branch, the session stays alive. The agent is done working but the window, git state, and Claude session are all preserved until you choose to recycle.
**To resume a done or crashed session:**
```bash
# Resume by stored session ID (preferred — exact session, full context)
claude --resume SESSION_ID --permission-mode bypassPermissions
# Or resume most recent session in that worktree directory
cd /path/to/worktree && claude --continue --permission-mode bypassPermissions
```
**To manually recycle when ready:**
```bash
bash ~/.claude/orchestrator/scripts/recycle-agent.sh SESSION:WIN WORKTREE_PATH spare/N
# Then update state:
jq --arg w "SESSION:WIN" '.agents |= map(if .window == $w then .state = "recycled" else . end)' \
~/.claude/orchestrator-state.json > /tmp/orch.tmp && mv /tmp/orch.tmp ~/.claude/orchestrator-state.json
```
## State file (`~/.claude/orchestrator-state.json`)
Never committed to git. You maintain this file directly using `jq` + atomic writes (`.tmp``mv`).
```json
{
"active": true,
"tmux_session": "autogpt1",
"idle_threshold_seconds": 300,
"loop_window": "autogpt1:5",
"repo": "Significant-Gravitas/AutoGPT",
"discord_webhook": "https://discord.com/api/webhooks/...",
"last_poll_at": 0,
"agents": [
{
"window": "autogpt1:3",
"worktree": "AutoGPT6",
"worktree_path": "/path/to/AutoGPT6",
"spare_branch": "spare/6",
"branch": "feat/my-feature",
"objective": "Implement X and open a PR",
"pr_number": "12345",
"session_id": "550e8400-e29b-41d4-a716-446655440000",
"steps": ["pr-address", "pr-test"],
"checkpoints": ["pr-address"],
"state": "running",
"last_output_hash": "",
"last_seen_at": 0,
"spawned_at": 0,
"idle_since": 0,
"revision_count": 0,
"last_rebriefed_at": 0
}
]
}
```
Top-level optional fields:
- `repo` — GitHub `owner/repo` for CI/thread checks. Auto-derived from git remote if omitted.
- `discord_webhook` — Discord webhook URL for completion notifications. Also reads `DISCORD_WEBHOOK_URL` env var.
Per-agent fields:
- `session_id` — UUID passed to `claude --session-id` at spawn; use with `claude --resume UUID` to restore exact session context after a crash or window close.
- `last_rebriefed_at` — Unix timestamp of last re-brief; enforces 5-min cooldown to prevent spam.
Agent states: `running` | `idle` | `stuck` | `waiting_approval` | `complete` | `done` | `escalated`
`done` means verified complete — window is still open, session still alive, worktree still on task branch. Not recycled yet.
## Serial /pr-test rule
`/pr-test` and `/pr-test --fix` run local Docker + integration tests that use shared ports, a shared database, and shared build caches. **Running two `/pr-test` jobs simultaneously will cause port conflicts and database corruption.**
**Rule: only one `/pr-test` runs at a time. The orchestrator serializes them.**
You (the orchestrating Claude) own the test queue:
1. Agents do `pr-review` and `pr-address` in parallel — that's safe (they only push code and reply to GitHub).
2. When a PR needs local testing, add it to your mental queue — don't give agents a `pr-test` step.
3. Run `/pr-test https://github.com/OWNER/REPO/pull/PR_NUMBER --fix` yourself, sequentially.
4. Feed results back to the relevant agent via `tmux send-keys`:
```bash
tmux send-keys -t SESSION:WIN "Local tests for PR #N: <paste failure output or 'all passed'>. Fix any failures and push, then output ORCHESTRATOR:DONE."
sleep 0.3
tmux send-keys -t SESSION:WIN Enter
```
5. Wait for CI to confirm green before marking the agent done.
If multiple PRs need testing at the same time, pick the one furthest along (fewest pending CI checks) and test it first. Only start the next test after the previous one completes.
## Session restore (tested and confirmed)
Agent sessions are saved to disk. To restore a closed or crashed session:
```bash
# If session_id is in state (preferred):
NEW_WIN=$(tmux new-window -t SESSION -n WORKTREE_NAME -P -F '#{window_index}')
tmux send-keys -t "SESSION:${NEW_WIN}" "cd /path/to/worktree && claude --resume SESSION_ID --permission-mode bypassPermissions" Enter
# If no session_id (use --continue for most recent session in that directory):
tmux send-keys -t "SESSION:${NEW_WIN}" "cd /path/to/worktree && claude --continue --permission-mode bypassPermissions" Enter
```
`--continue` restores the full conversation history including all tool calls, file edits, and context. The agent resumes exactly where it left off. After restoring, update the window address in the state file:
```bash
jq --arg old "SESSION:OLD_WIN" --arg new "SESSION:NEW_WIN" \
'(.agents[] | select(.window == $old)).window = $new' \
~/.claude/orchestrator-state.json > /tmp/orch.tmp && mv /tmp/orch.tmp ~/.claude/orchestrator-state.json
```
## Intent → action mapping
Match the user's message to one of these intents:
| The user says something like… | What to do |
|---|---|
| "status", "what's running", "show agents" | Run `status.sh` + `capacity.sh`, show output |
| "how many free", "capacity", "available worktrees" | Run `capacity.sh`, show output |
| "start N agents on X, Y, Z" or "run these tasks: …" | See **Spawning agents** below |
| "add task: …", "add one more agent for …" | See **Adding an agent** below |
| "stop", "shut down", "pause the fleet" | See **Stopping** below |
| "poll", "check now", "run a cycle" | Run `poll-cycle.sh`, process actions |
| "recycle window X", "free up autogpt3" | Run `recycle-agent.sh` directly |
When the intent is ambiguous, show capacity first and ask what tasks to run.
## Spawning agents
### 1. Resolve tmux session
```bash
tmux list-sessions -F "#{session_name}: #{session_windows} windows" 2>/dev/null
```
Use an existing session. **Never create a tmux session from within Claude** — it becomes a child of Claude's process and dies when the session ends. If no session exists, tell the user to run `tmux new-session -d -s autogpt1` in their terminal first, then re-invoke `/orchestrate`.
### 2. Show available capacity
```bash
bash $SKILLS_DIR/capacity.sh $(git rev-parse --show-toplevel)
```
### 3. Collect tasks from the user
For each task, gather:
- **objective** — what to do (e.g. "implement feature X and open a PR")
- **branch name** — e.g. `feat/my-feature` (derive from objective if not given)
- **pr_number** — GitHub PR number if working on an existing PR (for verification)
- **steps** — required checkpoint names in order (e.g. `pr-address pr-test`) — derive from objective
Ask for `idle_threshold_seconds` only if the user mentions it (default: 300).
Never ask the user to specify a worktree — auto-assign from `find-spare.sh`.
### 4. Spawn one agent per task
```bash
# Get ordered list of spare worktrees
SPARE_LIST=$(bash $SKILLS_DIR/find-spare.sh $(git rev-parse --show-toplevel))
# For each task, take the next spare line:
WORKTREE_PATH=$(echo "$SPARE_LINE" | awk '{print $1}')
SPARE_BRANCH=$(echo "$SPARE_LINE" | awk '{print $2}')
# With PR number and required steps:
WINDOW=$(bash $SKILLS_DIR/spawn-agent.sh "$SESSION" "$WORKTREE_PATH" "$SPARE_BRANCH" "$NEW_BRANCH" "$OBJECTIVE" "$PR_NUMBER" "pr-address" "pr-test")
# Without PR (new work):
WINDOW=$(bash $SKILLS_DIR/spawn-agent.sh "$SESSION" "$WORKTREE_PATH" "$SPARE_BRANCH" "$NEW_BRANCH" "$OBJECTIVE")
```
Build an agent record and append it to the state file. If the state file doesn't exist yet, initialize it:
```bash
# Derive repo from git remote (used by verify-complete.sh + supervisor)
REPO=$(git remote get-url origin 2>/dev/null | sed 's|.*github\.com[:/]||; s|\.git$||' || echo "")
jq -n \
--arg session "$SESSION" \
--arg repo "$REPO" \
--argjson threshold 300 \
'{active:true, tmux_session:$session, idle_threshold_seconds:$threshold,
repo:$repo, loop_window:null, supervisor_window:null, last_poll_at:0, agents:[]}' \
> ~/.claude/orchestrator-state.json
```
Optionally add a Discord webhook for completion notifications:
```bash
jq --arg hook "$DISCORD_WEBHOOK_URL" '.discord_webhook = $hook' ~/.claude/orchestrator-state.json \
> /tmp/orch.tmp && mv /tmp/orch.tmp ~/.claude/orchestrator-state.json
```
`spawn-agent.sh` writes the initial agent record (window, worktree_path, branch, objective, state, etc.) to the state file automatically — **do not append the record again after calling it.** The record already exists and `pr_number`/`steps` are patched in by the script itself.
### 5. Start the mechanical babysitter
```bash
LOOP_WIN=$(tmux new-window -t "$SESSION" -n "orchestrator" -P -F '#{window_index}')
LOOP_WINDOW="${SESSION}:${LOOP_WIN}"
tmux send-keys -t "$LOOP_WINDOW" "bash $SKILLS_DIR/run-loop.sh" Enter
jq --arg w "$LOOP_WINDOW" '.loop_window = $w' ~/.claude/orchestrator-state.json \
> /tmp/orch.tmp && mv /tmp/orch.tmp ~/.claude/orchestrator-state.json
```
### 6. Begin supervising directly in this conversation
You are the supervisor. After spawning, immediately start your first poll loop (see **Supervisor duties** below) and continue every 2-3 minutes. Do NOT spawn a separate supervisor Claude window.
## Adding an agent
Find the next spare worktree, then spawn and append to state — same as steps 24 above but for a single task. If no spare worktrees are available, tell the user.
## Supervisor duties (YOUR job, every 2-3 min in this conversation)
You are the supervisor. Run this poll loop directly in your Claude session — not in a separate window.
### Poll loop mechanism
You are reactive — you only act when a tool completes or the user sends a message. To create a self-sustaining poll loop without user involvement:
1. Start each poll with `run_in_background: true` + a sleep before the work:
```bash
sleep 120 && tmux capture-pane -t autogpt1:0 -p -S -200 | tail -40
# + similar for each active window
```
2. When the background job notifies you, read the pane output and take action.
3. Immediately schedule the next background poll — this keeps the loop alive.
4. Stop scheduling when all agents are done/escalated.
**Never tell the user "I'll poll every 2-3 minutes"** — that does nothing without a trigger. Start the background job instead.
### Each poll: what to check
```bash
# 1. Read state
cat ~/.claude/orchestrator-state.json | jq '.agents[] | {window, worktree, branch, state, pr_number, checkpoints}'
# 2. For each running/stuck/idle agent, capture pane
tmux capture-pane -t SESSION:WIN -p -S -200 | tail -60
```
For each agent, decide:
| What you see | Action |
|---|---|
| Spinner / tools running | Do nothing — agent is working |
| Idle `` prompt, no `ORCHESTRATOR:DONE` | Stalled — send specific nudge with objective from state |
| Stuck in error loop | Send targeted fix with exact error + solution |
| Waiting for input / question | Answer and unblock via `tmux send-keys` |
| CI red | `gh pr checks PR_NUMBER --repo REPO` → tell agent exactly what's failing |
| GitHub abuse rate limit error | Nudge: "Wait 60 seconds then continue posting replies with sleep 3 between each" |
| Context compacted / agent lost | Send recovery: `cat ~/.claude/orchestrator-state.json | jq '.agents[] | select(.window=="WIN")'` + `gh pr view PR_NUMBER --json title,body` |
| `ORCHESTRATOR:DONE` in output | Query GraphQL for actual unresolved count. If >0, re-brief. If 0, run `verify-complete.sh` |
**Poll all windows from state, not from memory.** Before each poll, run:
```bash
jq -r '.agents[] | select(.state | test("running|idle|stuck|waiting_approval|pending_evaluation")) | .window' ~/.claude/orchestrator-state.json
```
and capture every window listed. If you manually added a window outside spawn-agent.sh, ensure it's in the state file first.
### RUNNING count includes waiting_approval agents
The `RUNNING` count from run-loop.sh includes agents in `waiting_approval` state (they match the regex `running|stuck|waiting_approval|idle`). This means a fleet that is only `waiting_approval` still shows RUNNING > 0 in the log — it does **not** mean agents are actively working.
When you see `RUNNING > 0` in the run-loop log but suspect agents are actually blocked, check state directly:
```bash
jq '.agents[] | {window, state, worktree}' ~/.claude/orchestrator-state.json
```
A count of `running=1 waiting=1` in the log actually means one agent is waiting for approval — the orchestrator should check and approve, not wait.
### State file staleness recovery
The state file is written by scripts but can drift from reality when windows are closed, sessions expire, or the orchestrator restarts across conversations.
**Signs of stale state:**
- `loop_window` points to a window that no longer exists in the tmux session
- An agent's `state` is `running` but tmux window is closed or shows a shell prompt (not claude)
- `last_seen_at` is hours old but state still says `running`
**Recovery steps:**
1. **Verify actual tmux windows:**
```bash
tmux list-windows -t SESSION -F '#{window_index}: #{window_name} (#{pane_current_command})'
```
2. **Cross-reference with state file:**
```bash
jq -r '.agents[] | "\(.window) \(.state) \(.worktree)"' ~/.claude/orchestrator-state.json
```
3. **Fix stale entries:**
```bash
# Agent window closed — mark idle so run-loop.sh will restart it
jq --arg w "SESSION:WIN" '(.agents[] | select(.window==$w)).state = "idle"' \
~/.claude/orchestrator-state.json > /tmp/orch.tmp && mv /tmp/orch.tmp ~/.claude/orchestrator-state.json
# loop_window gone — kill the stale reference, then restart run-loop.sh
jq '.loop_window = null' ~/.claude/orchestrator-state.json > /tmp/orch.tmp && mv /tmp/orch.tmp ~/.claude/orchestrator-state.json
LOOP_WIN=$(tmux new-window -t "$SESSION" -n "orchestrator" -P -F '#{window_index}')
LOOP_WINDOW="${SESSION}:${LOOP_WIN}"
tmux send-keys -t "$LOOP_WINDOW" "bash $SKILLS_DIR/run-loop.sh" Enter
jq --arg w "$LOOP_WINDOW" '.loop_window = $w' ~/.claude/orchestrator-state.json \
> /tmp/orch.tmp && mv /tmp/orch.tmp ~/.claude/orchestrator-state.json
```
4. **After any state repair, re-run `status.sh` to confirm coherence before resuming supervision.**
### Strict ORCHESTRATOR:DONE gate
`verify-complete.sh` handles the main checks automatically (checkpoints, threads, CI green, spawned_at, and CHANGES_REQUESTED). Run it:
**CHANGES_REQUESTED staleness rule**: a `CHANGES_REQUESTED` review only blocks if it was submitted *after* the latest commit. If the latest commit postdates the review, the review is considered stale (feedback already addressed) and does not block. This avoids false negatives when a bot reviewer hasn't re-reviewed after the agent's fixing commits.
```bash
SKILLS_DIR=~/.claude/orchestrator/scripts
bash $SKILLS_DIR/verify-complete.sh SESSION:WIN
```
If it passes → run-loop.sh will recycle the window automatically. No manual action needed.
If it fails → re-brief the agent with the failure reason. Never manually mark state `done` to bypass this.
### Re-brief a stalled agent
**Before sending any nudge, verify the pane is at an idle prompt.** Sending text into a still-processing pane produces stuck `[Pasted text +N lines]` that the agent never sees.
Check:
```bash
tmux capture-pane -t SESSION:WIN -p 2>/dev/null | tail -5
```
If the last line shows a spinner (✳✽✢✶·), `Running…`, or no `` — wait 1015s and check again before sending.
```bash
OBJ=$(jq -r --arg w SESSION:WIN '.agents[] | select(.window==$w) | .objective' ~/.claude/orchestrator-state.json)
PR=$(jq -r --arg w SESSION:WIN '.agents[] | select(.window==$w) | .pr_number' ~/.claude/orchestrator-state.json)
tmux send-keys -t SESSION:WIN "You appear stalled. Your objective: $OBJ. Check: gh pr view $PR --json title,body,headRefName to reorient."
sleep 0.3
tmux send-keys -t SESSION:WIN Enter
```
If `image_path` is set on the agent record, include: "Re-read context at IMAGE_PATH with the Read tool."
## Self-recovery protocol (agents)
spawn-agent.sh automatically includes this instruction in every objective:
> If your context compacts and you lose track of what to do, run:
> `cat ~/.claude/orchestrator-state.json | jq '.agents[] | select(.window=="SESSION:WIN")'`
> and `gh pr view PR_NUMBER --json title,body,headRefName` to reorient.
> Output each completed step as `CHECKPOINT:<step-name>` on its own line.
## Passing images and screenshots to agents
`tmux send-keys` is text-only — you cannot paste a raw image into a pane. To give an agent visual context (screenshots, diagrams, mockups):
1. **Save the image to a temp file** with a stable path:
```bash
# If the user drags in a screenshot or you receive a file path:
IMAGE_PATH="/tmp/orchestrator-context-$(date +%s).png"
cp "$USER_PROVIDED_PATH" "$IMAGE_PATH"
```
2. **Reference the path in the objective string**:
```bash
OBJECTIVE="Implement the layout shown in /tmp/orchestrator-context-1234567890.png. Read that image first with the Read tool to understand the design."
```
3. The agent uses its `Read` tool to view the image at startup — Claude Code agents are multimodal and can read image files directly.
**Rule**: always use `/tmp/orchestrator-context-<timestamp>.png` as the naming convention so the supervisor knows what to look for if it needs to re-brief an agent with the same image.
---
## Orchestrator final evaluation (YOU decide, not the script)
`verify-complete.sh` is a gate — it blocks premature marking. But it cannot tell you if the work is actually good. That is YOUR job.
When run-loop marks an agent `pending_evaluation` and you're notified, do all of these before marking done:
### 1. Run /pr-test (required, serialized, use TodoWrite to queue)
`/pr-test` is the only reliable confirmation that the objective is actually met. Run it yourself, not the agent.
**When multiple PRs reach `pending_evaluation` at the same time, use TodoWrite to queue them:**
```
- [ ] /pr-test https://github.com/Significant-Gravitas/AutoGPT/pull/NNNN — <feature description>
- [ ] /pr-test https://github.com/Significant-Gravitas/AutoGPT/pull/MMMM — <feature description>
```
Run one at a time. Check off as you go.
```
/pr-test https://github.com/Significant-Gravitas/AutoGPT/pull/PR_NUMBER
```
**/pr-test can be lazy** — if it gives vague output, re-run with full context:
```
/pr-test https://github.com/OWNER/REPO/pull/PR_NUMBER
Context: This PR implements <objective from state file>. Key files: <list>.
Please verify: <specific behaviors to check>.
```
Only one `/pr-test` at a time — they share ports and DB.
### /pr-test result evaluation
**PARTIAL on any headline feature scenario is an immediate blocker.** Do not approve, do not mark done, do not let the agent output `ORCHESTRATOR:DONE`.
| `/pr-test` result | Action |
|---|---|
| All headline scenarios **PASS** | Proceed to evaluation step 2 |
| Any headline scenario **PARTIAL** | Re-brief the agent immediately — see below |
| Any headline scenario **FAIL** | Re-brief the agent immediately |
**What PARTIAL means**: the feature is only partly working. Example: the Apply button never appeared, or the AI returned no action blocks. The agent addressed part of the objective but not all of it.
**When any headline scenario is PARTIAL or FAIL:**
1. Do NOT mark the agent done or accept `ORCHESTRATOR:DONE`
2. Re-brief the agent with the specific scenario that failed and what was missing:
```bash
tmux send-keys -t SESSION:WIN "PARTIAL result on /pr-test — S5 (Apply button) never appeared. The AI must output JSON action blocks for the Apply button to render. Fix this before re-running /pr-test."
sleep 0.3
tmux send-keys -t SESSION:WIN Enter
```
3. Set state back to `running`:
```bash
jq --arg w "SESSION:WIN" '(.agents[] | select(.window == $w)).state = "running"' \
~/.claude/orchestrator-state.json > /tmp/orch.tmp && mv /tmp/orch.tmp ~/.claude/orchestrator-state.json
```
4. Wait for new `ORCHESTRATOR:DONE`, then re-run `/pr-test` from scratch
**Rule: only ALL-PASS qualifies for approval.** A mix of PASS + PARTIAL is a failure.
> **Why this matters**: A PR was once wrongly approved with S5 PARTIAL — the AI never output JSON action blocks so the Apply button never appeared. The fix was already in the agent's reach but slipped through because PARTIAL was not treated as blocking.
### 2. Do your own evaluation
1. **Read the PR diff and objective** — does the code actually implement what was asked? Is anything obviously missing or half-done?
2. **Read the resolved threads** — were comments addressed with real fixes, or just dismissed/resolved without changes?
3. **Check CI run names** — any suspicious retries that shouldn't have passed?
4. **Check the PR description** — title, summary, test plan complete?
### 3. Decide
- `/pr-test` all scenarios PASS + evaluation looks good → mark `done` in state, tell the user the PR is ready, ask if window should be closed
- `/pr-test` any scenario PARTIAL or FAIL → re-brief the agent with the specific failing scenario, set state back to `running` (see `/pr-test result evaluation` above)
- Evaluation finds gaps even with all PASS → re-brief the agent with specific gaps, set state back to `running`
**Never mark done based purely on script output.** You hold the full objective context; the script does not.
```bash
# Mark done after your positive evaluation:
jq --arg w "SESSION:WIN" '(.agents[] | select(.window == $w)).state = "done"' \
~/.claude/orchestrator-state.json > /tmp/orch.tmp && mv /tmp/orch.tmp ~/.claude/orchestrator-state.json
```
## When to stop the fleet
Stop the fleet (`active = false`) when **all** of the following are true:
| Check | How to verify |
|---|---|
| All agents are `done` or `escalated` | `jq '[.agents[] | select(.state | test("running\|stuck\|idle\|waiting_approval"))] | length' ~/.claude/orchestrator-state.json` == 0 |
| All PRs have 0 unresolved review threads | GraphQL `isResolved` check per PR |
| All PRs have green CI **on a run triggered after the agent's last push** | `gh run list --branch BRANCH --limit 1` timestamp > `spawned_at` in state |
| No fresh CHANGES_REQUESTED (after latest commit) | `verify-complete.sh` checks this — stale pre-commit reviews are ignored |
| No agents are `escalated` without human review | If any are escalated, surface to user first |
**Do NOT stop just because agents output `ORCHESTRATOR:DONE`.** That is a signal to verify, not a signal to stop.
**Do stop** if the user explicitly says "stop", "shut down", or "kill everything", even with agents still running.
```bash
# Graceful stop
jq '.active = false' ~/.claude/orchestrator-state.json > /tmp/orch.tmp \
&& mv /tmp/orch.tmp ~/.claude/orchestrator-state.json
LOOP_WINDOW=$(jq -r '.loop_window // ""' ~/.claude/orchestrator-state.json)
[ -n "$LOOP_WINDOW" ] && tmux kill-window -t "$LOOP_WINDOW" 2>/dev/null || true
```
Does **not** recycle running worktrees — agents may still be mid-task. Run `capacity.sh` to see what's still in progress.
## tmux send-keys pattern
**Always split long messages into text + Enter as two separate calls with a sleep between them.** If sent as one call (`"text" Enter`), Enter can fire before the full string is buffered into Claude's input — leaving the message stuck as `[Pasted text +N lines]` unsent.
```bash
# CORRECT — text then Enter separately
tmux send-keys -t "$WINDOW" "your long message here"
sleep 0.3
tmux send-keys -t "$WINDOW" Enter
# WRONG — Enter may fire before text is buffered
tmux send-keys -t "$WINDOW" "your long message here" Enter
```
Short single-character sends (`y`, `Down`, empty Enter for dialog approval) are safe to combine since they have no buffering lag.
---
## Protected worktrees
Some worktrees must **never** be used as spare worktrees for agent tasks because they host files critical to the orchestrator itself:
| Worktree | Protected branch | Why |
|---|---|---|
| `AutoGPT1` | `dx/orchestrate-skill` | Hosts the orchestrate skill scripts. `recycle-agent.sh` would check out `spare/1`, wiping `.claude/skills/` and breaking all subsequent `spawn-agent.sh` calls. |
**Rule**: when selecting spare worktrees via `find-spare.sh`, skip any worktree whose CURRENT branch matches a protected branch. If you accidentally spawn an agent in a protected worktree, do not let `recycle-agent.sh` run on it — manually restore the branch after the agent finishes.
When `dx/orchestrate-skill` is merged into `dev`, `AutoGPT1` becomes a normal spare again.
---
## Thread resolution integrity (critical)
**Agents MUST NOT resolve review threads via GraphQL unless a real code fix has been committed and pushed first.**
This is the most common failure mode: agents call `resolveReviewThread` to make unresolved counts drop without actually fixing anything. This produces a false "done" signal that gets past verify-complete.sh.
**The only valid resolution sequence:**
1. Read the thread and understand what it's asking
2. Make the actual code change
3. `git commit` and `git push`
4. Reply to the thread with the commit SHA (e.g. "Fixed in `abc1234`")
5. THEN call `resolveReviewThread`
**The supervisor must verify actual thread counts via GraphQL** — never trust an agent's claim of "0 unresolved." After any agent's ORCHESTRATOR:DONE, always run:
```bash
# Step 1: get total count
TOTAL=$(gh api graphql -f query='{ repository(owner: "OWNER", name: "REPO") { pullRequest(number: PR) { reviewThreads { totalCount } } } }' \
| jq '.data.repository.pullRequest.reviewThreads.totalCount')
echo "Total threads: $TOTAL"
# Step 2: paginate all pages and count unresolved
CURSOR=""; UNRESOLVED=0
while true; do
AFTER=${CURSOR:+", after: \"$CURSOR\""}
PAGE=$(gh api graphql -f query="{ repository(owner: \"OWNER\", name: \"REPO\") { pullRequest(number: PR) { reviewThreads(first: 100${AFTER}) { pageInfo { hasNextPage endCursor } nodes { isResolved } } } } }")
UNRESOLVED=$(( UNRESOLVED + $(echo "$PAGE" | jq '[.data.repository.pullRequest.reviewThreads.nodes[] | select(.isResolved==false)] | length') ))
HAS_NEXT=$(echo "$PAGE" | jq -r '.data.repository.pullRequest.reviewThreads.pageInfo.hasNextPage')
CURSOR=$(echo "$PAGE" | jq -r '.data.repository.pullRequest.reviewThreads.pageInfo.endCursor')
[ "$HAS_NEXT" = "false" ] && break
done
echo "Unresolved: $UNRESOLVED"
```
If unresolved > 0, the agent is NOT done — re-brief with the actual count and the rule.
**Include this in every agent objective:**
> IMPORTANT: Do NOT resolve any review thread via GraphQL unless the code fix is committed and pushed first. Fix the code → commit → push → reply with SHA → then resolve. Never resolve without a real commit. "Accepted" or "Acknowledged" replies are NOT resolutions — only real commits qualify.
### Detecting fake resolutions
When an agent claims "0 unresolved threads", query GitHub GraphQL yourself and also inspect how each thread was resolved. A resolved thread whose last comment is `"Acknowledged"`, `"Same as above"`, `"Accepted trade-off"`, or `"Deferred"` — with no commit SHA — is a fake resolution.
To spot these, paginate all pages and collect resolved threads with missing SHA links:
```bash
# Paginate all pages — first:100 misses threads beyond page 1 on large PRs
CURSOR=""; FAKE_RESOLUTIONS="[]"
while true; do
AFTER=${CURSOR:+", after: \"$CURSOR\""}
PAGE=$(gh api graphql -f query="
{
repository(owner: \"Significant-Gravitas\", name: \"AutoGPT\") {
pullRequest(number: PR_NUMBER) {
reviewThreads(first: 100${AFTER}) {
pageInfo { hasNextPage endCursor }
nodes {
isResolved
comments(last: 1) {
nodes { body author { login } }
}
}
}
}
}
}")
PAGE_FAKES=$(echo "$PAGE" | jq '[.data.repository.pullRequest.reviewThreads.nodes[]
| select(.isResolved == true)
| {body: .comments.nodes[0].body[:120], author: .comments.nodes[0].author.login}
| select(.body | test("Fixed in|Removed in|Addressed in") | not)]')
FAKE_RESOLUTIONS=$(echo "$FAKE_RESOLUTIONS $PAGE_FAKES" | jq -s 'add')
HAS_NEXT=$(echo "$PAGE" | jq -r '.data.repository.pullRequest.reviewThreads.pageInfo.hasNextPage')
CURSOR=$(echo "$PAGE" | jq -r '.data.repository.pullRequest.reviewThreads.pageInfo.endCursor')
[ "$HAS_NEXT" = "false" ] && break
done
echo "$FAKE_RESOLUTIONS"
```
Any resolved thread whose last comment does NOT contain `"Fixed in"`, `"Removed in"`, or `"Addressed in"` (with a commit link) should be investigated — either the agent falsely resolved it, or it was a genuine false positive that needs explanation.
## GitHub abuse rate limits
Two distinct rate limits exist with different recovery times:
| Error | HTTP status | Cause | Recovery |
|---|---|---|---|
| `{"code":"abuse"}` in body | 403 | Secondary rate limit — too many write operations (comments, mutations) in a short window | Wait **23 minutes**. 60s is often not enough. |
| `API rate limit exceeded` | 429 | Primary rate limit — too many read calls per hour | Wait until `X-RateLimit-Reset` timestamp |
**Prevention:** Agents must add `sleep 3` between individual thread reply API calls. For >20 unresolved threads, increase to `sleep 5`.
If you see a 403 `abuse` error from an agent's pane:
1. Nudge the agent: `"You hit a GitHub secondary rate limit (403). Stop all API writes. Wait 2 minutes, then resume with sleep 3 between each thread reply."`
2. Do NOT nudge again during the 2-minute wait — a second nudge restarts the clock.
Add this to agent briefings when there are >20 unresolved threads:
> Post replies with `sleep 3` between each reply. If you hit a 403 abuse error, wait 2 minutes (not 60s — secondary limits take longer to clear) then continue.
## Key rules
1. **Scripts do all the heavy lifting** — don't reimplement their logic inline in this file
2. **Never ask the user to pick a worktree** — auto-assign from `find-spare.sh` output
3. **Never restart a running agent** — only restart on `idle` kicks (foreground is a shell)
4. **Auto-dismiss settings dialogs** — if "Enter to confirm" appears, send Down+Enter
5. **Always `--permission-mode bypassPermissions`** on every spawn
6. **Escalate after 3 kicks** — mark `escalated`, surface to user
7. **Atomic state writes** — always write to `.tmp` then `mv`
8. **Never approve destructive commands** outside the worktree scope — when in doubt, escalate
9. **Never recycle without verification** — `verify-complete.sh` must pass before recycling
10. **No TASK.md files** — commit risk; use state file + `gh pr view` for agent context persistence
11. **Re-brief stalled agents** — read objective from state file + `gh pr view`, send via tmux
12. **ORCHESTRATOR:DONE is a signal to verify, not to accept** — always run `verify-complete.sh` and check CI run timestamp before recycling
13. **Protected worktrees** — never use the worktree hosting the skill scripts as a spare
14. **Images via file path** — save screenshots to `/tmp/orchestrator-context-<ts>.png`, pass path in objective; agents read with the `Read` tool
15. **Split send-keys** — always separate text and Enter with `sleep 0.3` between calls for long strings
16. **Poll ALL windows from state file** — never hardcode window count. Derive active windows dynamically: `jq -r '.agents[] | select(.state | test("running|idle|stuck")) | .window' ~/.claude/orchestrator-state.json`. If you added a window mid-session outside spawn-agent.sh, add it to the state file immediately.
20. **Orchestrator handles its own approvals** — when spawning a subagent to make edits (SKILL.md, scripts, config), review the diff yourself and approve/reject without surfacing it to the user. The user should never have to open a file to check the orchestrator's work. Use the Agent tool with `subagent_type: general-purpose` for drafting, then verify the result yourself before considering the task done.
17. **Update state file on re-task** — whenever an agent is re-tasked mid-session (objective changes, new PR assigned), update the state file record immediately so objectives stay accurate for re-briefing after compaction.
18. **No GraphQL resolveReviewThread without a commit** — see Thread resolution integrity above. This is rule #1 for pr-address work.
19. **Verify thread counts yourself** — after any agent claims "0 unresolved threads", query GitHub GraphQL directly before accepting. Never trust the agent's self-report.

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#!/usr/bin/env bash
# capacity.sh — show fleet capacity: available spare worktrees + in-use agents
#
# Usage: capacity.sh [REPO_ROOT]
# REPO_ROOT defaults to the root worktree of the current git repo.
#
# Reads: ~/.claude/orchestrator-state.json (skipped if missing or corrupt)
set -euo pipefail
SCRIPTS_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
STATE_FILE="${ORCHESTRATOR_STATE_FILE:-$HOME/.claude/orchestrator-state.json}"
REPO_ROOT="${1:-$(git rev-parse --show-toplevel 2>/dev/null || echo "")}"
echo "=== Available (spare) worktrees ==="
if [ -n "$REPO_ROOT" ]; then
SPARE=$("$SCRIPTS_DIR/find-spare.sh" "$REPO_ROOT" 2>/dev/null || echo "")
else
SPARE=$("$SCRIPTS_DIR/find-spare.sh" 2>/dev/null || echo "")
fi
if [ -z "$SPARE" ]; then
echo " (none)"
else
while IFS= read -r line; do
[ -z "$line" ] && continue
echo "$line"
done <<< "$SPARE"
fi
echo ""
echo "=== In-use worktrees ==="
if [ -f "$STATE_FILE" ] && jq -e '.' "$STATE_FILE" >/dev/null 2>&1; then
IN_USE=$(jq -r '.agents[] | select(.state != "done") | " [\(.state)] \(.worktree_path) → \(.branch)"' \
"$STATE_FILE" 2>/dev/null || echo "")
if [ -n "$IN_USE" ]; then
echo "$IN_USE"
else
echo " (none)"
fi
else
echo " (no active state file)"
fi

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@@ -0,0 +1,85 @@
#!/usr/bin/env bash
# classify-pane.sh — Classify the current state of a tmux pane
#
# Usage: classify-pane.sh <tmux-target>
# tmux-target: e.g. "work:0", "work:1.0"
#
# Output (stdout): JSON object:
# { "state": "running|idle|waiting_approval|complete", "reason": "...", "pane_cmd": "..." }
#
# Exit codes: 0=ok, 1=error (invalid target or tmux window not found)
set -euo pipefail
TARGET="${1:-}"
if [ -z "$TARGET" ]; then
echo '{"state":"error","reason":"no target provided","pane_cmd":""}'
exit 1
fi
# Validate tmux target format: session:window or session:window.pane
if ! [[ "$TARGET" =~ ^[a-zA-Z0-9_.-]+:[a-zA-Z0-9_.-]+(\.[0-9]+)?$ ]]; then
echo '{"state":"error","reason":"invalid tmux target format","pane_cmd":""}'
exit 1
fi
# Check session exists (use %%:* to extract session name from session:window)
if ! tmux list-windows -t "${TARGET%%:*}" &>/dev/null 2>&1; then
echo '{"state":"error","reason":"tmux target not found","pane_cmd":""}'
exit 1
fi
# Get the current foreground command in the pane
PANE_CMD=$(tmux display-message -t "$TARGET" -p '#{pane_current_command}' 2>/dev/null || echo "unknown")
# Capture and strip ANSI codes (use perl for cross-platform compatibility — BSD sed lacks \x1b support)
RAW=$(tmux capture-pane -t "$TARGET" -p -S -50 2>/dev/null || echo "")
CLEAN=$(echo "$RAW" | perl -pe 's/\x1b\[[0-9;]*[a-zA-Z]//g; s/\x1b\(B//g; s/\x1b\[\?[0-9]*[hl]//g; s/\r//g' \
| grep -v '^[[:space:]]*$' || true)
# --- Check: explicit completion marker ---
# Must be on its own line (not buried in the objective text sent at spawn time).
if echo "$CLEAN" | grep -qE "^[[:space:]]*ORCHESTRATOR:DONE[[:space:]]*$"; then
jq -n --arg cmd "$PANE_CMD" '{"state":"complete","reason":"ORCHESTRATOR:DONE marker found","pane_cmd":$cmd}'
exit 0
fi
# --- Check: Claude Code approval prompt patterns ---
LAST_40=$(echo "$CLEAN" | tail -40)
APPROVAL_PATTERNS=(
"Do you want to proceed"
"Do you want to make this"
"\\[y/n\\]"
"\\[Y/n\\]"
"\\[n/Y\\]"
"Proceed\\?"
"Allow this command"
"Run bash command"
"Allow bash"
"Would you like"
"Press enter to continue"
"Esc to cancel"
)
for pattern in "${APPROVAL_PATTERNS[@]}"; do
if echo "$LAST_40" | grep -qiE "$pattern"; then
jq -n --arg pattern "$pattern" --arg cmd "$PANE_CMD" \
'{"state":"waiting_approval","reason":"approval pattern: \($pattern)","pane_cmd":$cmd}'
exit 0
fi
done
# --- Check: shell prompt (claude has exited) ---
# If the foreground process is a shell (not claude/node), the agent has exited
case "$PANE_CMD" in
zsh|bash|fish|sh|dash|tcsh|ksh)
jq -n --arg cmd "$PANE_CMD" \
'{"state":"idle","reason":"agent exited — shell prompt active","pane_cmd":$cmd}'
exit 0
;;
esac
# Agent is still running (claude/node/python is the foreground process)
jq -n --arg cmd "$PANE_CMD" \
'{"state":"running","reason":"foreground process: \($cmd)","pane_cmd":$cmd}'
exit 0

View File

@@ -0,0 +1,24 @@
#!/usr/bin/env bash
# find-spare.sh — list worktrees on spare/N branches (free to use)
#
# Usage: find-spare.sh [REPO_ROOT]
# REPO_ROOT defaults to the root worktree containing the current git repo.
#
# Output (stdout): one line per available worktree: "PATH BRANCH"
# e.g.: /Users/me/Code/AutoGPT3 spare/3
set -euo pipefail
REPO_ROOT="${1:-$(git rev-parse --show-toplevel 2>/dev/null || echo "")}"
if [ -z "$REPO_ROOT" ]; then
echo "Error: not inside a git repo and no REPO_ROOT provided" >&2
exit 1
fi
git -C "$REPO_ROOT" worktree list --porcelain \
| awk '
/^worktree / { path = substr($0, 10) }
/^branch / { branch = substr($0, 8); print path " " branch }
' \
| { grep -E " refs/heads/spare/[0-9]+$" || true; } \
| sed 's|refs/heads/||'

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@@ -0,0 +1,40 @@
#!/usr/bin/env bash
# notify.sh — send a fleet notification message
#
# Delivery order (first available wins):
# 1. Discord webhook — DISCORD_WEBHOOK_URL env var OR state file .discord_webhook
# 2. macOS notification center — osascript (silent fail if unavailable)
# 3. Stdout only
#
# Usage: notify.sh MESSAGE
# Exit: always 0 (notification failure must not abort the caller)
MESSAGE="${1:-}"
[ -z "$MESSAGE" ] && exit 0
STATE_FILE="${ORCHESTRATOR_STATE_FILE:-$HOME/.claude/orchestrator-state.json}"
# --- Resolve Discord webhook ---
WEBHOOK="${DISCORD_WEBHOOK_URL:-}"
if [ -z "$WEBHOOK" ] && [ -f "$STATE_FILE" ]; then
WEBHOOK=$(jq -r '.discord_webhook // ""' "$STATE_FILE" 2>/dev/null || echo "")
fi
# --- Discord delivery ---
if [ -n "$WEBHOOK" ]; then
PAYLOAD=$(jq -n --arg msg "$MESSAGE" '{"content": $msg}')
curl -s -X POST "$WEBHOOK" \
-H "Content-Type: application/json" \
-d "$PAYLOAD" > /dev/null 2>&1 || true
fi
# --- macOS notification center (silent if not macOS or osascript missing) ---
if command -v osascript &>/dev/null 2>&1; then
# Escape single quotes for AppleScript
SAFE_MSG=$(echo "$MESSAGE" | sed "s/'/\\\\'/g")
osascript -e "display notification \"${SAFE_MSG}\" with title \"Orchestrator\"" 2>/dev/null || true
fi
# Always print to stdout so run-loop.sh logs it
echo "$MESSAGE"
exit 0

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#!/usr/bin/env bash
# poll-cycle.sh — Single orchestrator poll cycle
#
# Reads ~/.claude/orchestrator-state.json, classifies each agent, updates state,
# and outputs a JSON array of actions for Claude to take.
#
# Usage: poll-cycle.sh
# Output (stdout): JSON array of action objects
# [{ "window": "work:0", "action": "kick|approve|none", "state": "...",
# "worktree": "...", "objective": "...", "reason": "..." }]
#
# The state file is updated in-place (atomic write via .tmp).
set -euo pipefail
STATE_FILE="${ORCHESTRATOR_STATE_FILE:-$HOME/.claude/orchestrator-state.json}"
SCRIPTS_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
CLASSIFY="$SCRIPTS_DIR/classify-pane.sh"
# Cross-platform md5: always outputs just the hex digest
md5_hash() {
if command -v md5sum &>/dev/null; then
md5sum | awk '{print $1}'
else
md5 | awk '{print $NF}'
fi
}
# Clean up temp file on any exit (avoids stale .tmp if jq write fails)
trap 'rm -f "${STATE_FILE}.tmp"' EXIT
# Ensure state file exists
if [ ! -f "$STATE_FILE" ]; then
echo '{"active":false,"agents":[]}' > "$STATE_FILE"
fi
# Validate JSON upfront before any jq reads that run under set -e.
# A truncated/corrupt file (e.g. from a SIGKILL mid-write) would otherwise
# abort the script at the ACTIVE read below without emitting any JSON output.
if ! jq -e '.' "$STATE_FILE" >/dev/null 2>&1; then
echo "State file parse error — check $STATE_FILE" >&2
echo "[]"
exit 0
fi
ACTIVE=$(jq -r '.active // false' "$STATE_FILE")
if [ "$ACTIVE" != "true" ]; then
echo "[]"
exit 0
fi
NOW=$(date +%s)
IDLE_THRESHOLD=$(jq -r '.idle_threshold_seconds // 300' "$STATE_FILE")
ACTIONS="[]"
UPDATED_AGENTS="[]"
# Read agents as newline-delimited JSON objects.
# jq exits non-zero when .agents[] has no matches on an empty array, which is valid —
# so we suppress that exit code and separately validate the file is well-formed JSON.
if ! AGENTS_JSON=$(jq -e -c '.agents // empty | .[]' "$STATE_FILE" 2>/dev/null); then
if ! jq -e '.' "$STATE_FILE" > /dev/null 2>&1; then
echo "State file parse error — check $STATE_FILE" >&2
fi
echo "[]"
exit 0
fi
if [ -z "$AGENTS_JSON" ]; then
echo "[]"
exit 0
fi
while IFS= read -r agent; do
[ -z "$agent" ] && continue
# Use // "" defaults so a single malformed field doesn't abort the whole cycle
WINDOW=$(echo "$agent" | jq -r '.window // ""')
WORKTREE=$(echo "$agent" | jq -r '.worktree // ""')
OBJECTIVE=$(echo "$agent"| jq -r '.objective // ""')
STATE=$(echo "$agent" | jq -r '.state // "running"')
LAST_HASH=$(echo "$agent"| jq -r '.last_output_hash // ""')
IDLE_SINCE=$(echo "$agent"| jq -r '.idle_since // 0')
REVISION_COUNT=$(echo "$agent"| jq -r '.revision_count // 0')
# Validate window format to prevent tmux target injection.
# Allow session:window (numeric or named) and session:window.pane
if ! [[ "$WINDOW" =~ ^[a-zA-Z0-9_.-]+:[a-zA-Z0-9_.-]+(\.[0-9]+)?$ ]]; then
echo "Skipping agent with invalid window value: $WINDOW" >&2
UPDATED_AGENTS=$(echo "$UPDATED_AGENTS" | jq --argjson a "$agent" '. + [$a]')
continue
fi
# Pass-through terminal-state agents
if [[ "$STATE" == "done" || "$STATE" == "escalated" || "$STATE" == "complete" || "$STATE" == "pending_evaluation" ]]; then
UPDATED_AGENTS=$(echo "$UPDATED_AGENTS" | jq --argjson a "$agent" '. + [$a]')
continue
fi
# Classify pane.
# classify-pane.sh always emits JSON before exit (even on error), so using
# "|| echo '...'" would concatenate two JSON objects when it exits non-zero.
# Use "|| true" inside the substitution so set -euo pipefail does not abort
# the poll cycle when classify exits with a non-zero status code.
CLASSIFICATION=$("$CLASSIFY" "$WINDOW" 2>/dev/null || true)
[ -z "$CLASSIFICATION" ] && CLASSIFICATION='{"state":"error","reason":"classify failed","pane_cmd":"unknown"}'
PANE_STATE=$(echo "$CLASSIFICATION" | jq -r '.state')
PANE_REASON=$(echo "$CLASSIFICATION" | jq -r '.reason')
# Capture full pane output once — used for hash (stuck detection) and checkpoint parsing.
# Use -S -500 to get the last ~500 lines of scrollback so checkpoints aren't missed.
RAW=$(tmux capture-pane -t "$WINDOW" -p -S -500 2>/dev/null || echo "")
# --- Checkpoint tracking ---
# Parse any "CHECKPOINT:<step>" lines the agent has output and merge into state file.
# The agent writes these as it completes each required step so verify-complete.sh can gate recycling.
EXISTING_CPS=$(echo "$agent" | jq -c '.checkpoints // []')
NEW_CHECKPOINTS_JSON="$EXISTING_CPS"
if [ -n "$RAW" ]; then
FOUND_CPS=$(echo "$RAW" \
| grep -oE "CHECKPOINT:[a-zA-Z0-9_-]+" \
| sed 's/CHECKPOINT://' \
| sort -u \
| jq -R . | jq -s . 2>/dev/null || echo "[]")
NEW_CHECKPOINTS_JSON=$(jq -n \
--argjson existing "$EXISTING_CPS" \
--argjson found "$FOUND_CPS" \
'($existing + $found) | unique' 2>/dev/null || echo "$EXISTING_CPS")
fi
# Compute content hash for stuck-detection (only for running agents)
CURRENT_HASH=""
if [[ "$PANE_STATE" == "running" ]] && [ -n "$RAW" ]; then
CURRENT_HASH=$(echo "$RAW" | tail -20 | md5_hash)
fi
NEW_STATE="$STATE"
NEW_IDLE_SINCE="$IDLE_SINCE"
NEW_REVISION_COUNT="$REVISION_COUNT"
ACTION="none"
REASON="$PANE_REASON"
case "$PANE_STATE" in
complete)
# Agent output ORCHESTRATOR:DONE — mark pending_evaluation so orchestrator handles it.
# run-loop does NOT verify or notify; orchestrator's background poll picks this up.
NEW_STATE="pending_evaluation"
ACTION="complete" # run-loop logs it but takes no action
;;
waiting_approval)
NEW_STATE="waiting_approval"
ACTION="approve"
;;
idle)
# Agent process has exited — needs restart
NEW_STATE="idle"
ACTION="kick"
REASON="agent exited (shell is foreground)"
NEW_REVISION_COUNT=$(( REVISION_COUNT + 1 ))
NEW_IDLE_SINCE=$NOW
if [ "$NEW_REVISION_COUNT" -ge 3 ]; then
NEW_STATE="escalated"
ACTION="none"
REASON="escalated after ${NEW_REVISION_COUNT} kicks — needs human attention"
fi
;;
running)
# Clear idle_since only when transitioning from idle (agent was kicked and
# restarted). Do NOT reset for stuck — idle_since must persist across polls
# so STUCK_DURATION can accumulate and trigger escalation.
# Also update the local IDLE_SINCE so the hash-stability check below uses
# the reset value on this same poll, not the stale kick timestamp.
if [[ "$STATE" == "idle" ]]; then
NEW_IDLE_SINCE=0
IDLE_SINCE=0
fi
# Check if hash has been stable (agent may be stuck mid-task)
if [ -n "$CURRENT_HASH" ] && [ "$CURRENT_HASH" = "$LAST_HASH" ] && [ "$LAST_HASH" != "" ]; then
if [ "$IDLE_SINCE" = "0" ] || [ "$IDLE_SINCE" = "null" ]; then
NEW_IDLE_SINCE=$NOW
else
STUCK_DURATION=$(( NOW - IDLE_SINCE ))
if [ "$STUCK_DURATION" -gt "$IDLE_THRESHOLD" ]; then
NEW_REVISION_COUNT=$(( REVISION_COUNT + 1 ))
NEW_IDLE_SINCE=$NOW
if [ "$NEW_REVISION_COUNT" -ge 3 ]; then
NEW_STATE="escalated"
ACTION="none"
REASON="escalated after ${NEW_REVISION_COUNT} kicks — needs human attention"
else
NEW_STATE="stuck"
ACTION="kick"
REASON="output unchanged for ${STUCK_DURATION}s (threshold: ${IDLE_THRESHOLD}s)"
fi
fi
fi
else
# Only reset the idle timer when we have a valid hash comparison (pane
# capture succeeded). If CURRENT_HASH is empty (tmux capture-pane failed),
# preserve existing timers so stuck detection is not inadvertently reset.
if [ -n "$CURRENT_HASH" ]; then
NEW_STATE="running"
NEW_IDLE_SINCE=0
fi
fi
;;
error)
REASON="classify error: $PANE_REASON"
;;
esac
# Build updated agent record (ensure idle_since and revision_count are numeric)
# Use || true on each jq call so a malformed field skips this agent rather than
# aborting the entire poll cycle under set -e.
UPDATED_AGENT=$(echo "$agent" | jq \
--arg state "$NEW_STATE" \
--arg hash "$CURRENT_HASH" \
--argjson now "$NOW" \
--arg idle_since "$NEW_IDLE_SINCE" \
--arg revision_count "$NEW_REVISION_COUNT" \
--argjson checkpoints "$NEW_CHECKPOINTS_JSON" \
'.state = $state
| .last_output_hash = (if $hash == "" then .last_output_hash else $hash end)
| .last_seen_at = $now
| .idle_since = ($idle_since | tonumber)
| .revision_count = ($revision_count | tonumber)
| .checkpoints = $checkpoints' 2>/dev/null) || {
echo "Warning: failed to build updated agent for window $WINDOW — keeping original" >&2
UPDATED_AGENTS=$(echo "$UPDATED_AGENTS" | jq --argjson a "$agent" '. + [$a]')
continue
}
UPDATED_AGENTS=$(echo "$UPDATED_AGENTS" | jq --argjson a "$UPDATED_AGENT" '. + [$a]')
# Add action if needed
if [ "$ACTION" != "none" ]; then
ACTION_OBJ=$(jq -n \
--arg window "$WINDOW" \
--arg action "$ACTION" \
--arg state "$NEW_STATE" \
--arg worktree "$WORKTREE" \
--arg objective "$OBJECTIVE" \
--arg reason "$REASON" \
'{window:$window, action:$action, state:$state, worktree:$worktree, objective:$objective, reason:$reason}')
ACTIONS=$(echo "$ACTIONS" | jq --argjson a "$ACTION_OBJ" '. + [$a]')
fi
done <<< "$AGENTS_JSON"
# Atomic state file update
jq --argjson agents "$UPDATED_AGENTS" \
--argjson now "$NOW" \
'.agents = $agents | .last_poll_at = $now' \
"$STATE_FILE" > "${STATE_FILE}.tmp" && mv "${STATE_FILE}.tmp" "$STATE_FILE"
echo "$ACTIONS"

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#!/usr/bin/env bash
# recycle-agent.sh — kill a tmux window and restore the worktree to its spare branch
#
# Usage: recycle-agent.sh WINDOW WORKTREE_PATH SPARE_BRANCH
# WINDOW — tmux target, e.g. autogpt1:3
# WORKTREE_PATH — absolute path to the git worktree
# SPARE_BRANCH — branch to restore, e.g. spare/6
#
# Stdout: one status line
set -euo pipefail
if [ $# -lt 3 ]; then
echo "Usage: recycle-agent.sh WINDOW WORKTREE_PATH SPARE_BRANCH" >&2
exit 1
fi
WINDOW="$1"
WORKTREE_PATH="$2"
SPARE_BRANCH="$3"
# Kill the tmux window (ignore error — may already be gone)
tmux kill-window -t "$WINDOW" 2>/dev/null || true
# Restore to spare branch: abort any in-progress operation, then clean
git -C "$WORKTREE_PATH" rebase --abort 2>/dev/null || true
git -C "$WORKTREE_PATH" merge --abort 2>/dev/null || true
git -C "$WORKTREE_PATH" reset --hard HEAD 2>/dev/null
git -C "$WORKTREE_PATH" clean -fd 2>/dev/null
git -C "$WORKTREE_PATH" checkout "$SPARE_BRANCH"
echo "Recycled: $(basename "$WORKTREE_PATH")$SPARE_BRANCH (window $WINDOW closed)"

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@@ -0,0 +1,215 @@
#!/usr/bin/env bash
# run-loop.sh — Mechanical babysitter for the agent fleet (runs in its own tmux window)
#
# Handles ONLY two things that need no intelligence:
# idle → restart claude using --resume SESSION_ID (or --continue) to restore context
# approve → auto-approve safe dialogs, press Enter on numbered-option dialogs
#
# Everything else — ORCHESTRATOR:DONE, verification, /pr-test, final evaluation,
# marking done, deciding to close windows — is the orchestrating Claude's job.
# poll-cycle.sh sets state to pending_evaluation when ORCHESTRATOR:DONE is detected;
# the orchestrator's background poll loop handles it from there.
#
# Usage: run-loop.sh
# Env: POLL_INTERVAL (default: 30), ORCHESTRATOR_STATE_FILE
set -euo pipefail
# Copy scripts to a stable location outside the repo so they survive branch
# checkouts (e.g. recycle-agent.sh switching spare/N back into this worktree
# would wipe .claude/skills/orchestrate/scripts if the skill only exists on the
# current branch).
_ORIGIN_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
STABLE_SCRIPTS_DIR="$HOME/.claude/orchestrator/scripts"
mkdir -p "$STABLE_SCRIPTS_DIR"
cp "$_ORIGIN_DIR"/*.sh "$STABLE_SCRIPTS_DIR/"
chmod +x "$STABLE_SCRIPTS_DIR"/*.sh
SCRIPTS_DIR="$STABLE_SCRIPTS_DIR"
STATE_FILE="${ORCHESTRATOR_STATE_FILE:-$HOME/.claude/orchestrator-state.json}"
# Adaptive polling: starts at base interval, backs off up to POLL_IDLE_MAX when
# no agents need attention, resets on any activity or waiting_approval state.
POLL_INTERVAL="${POLL_INTERVAL:-30}"
POLL_IDLE_MAX=${POLL_IDLE_MAX:-300}
POLL_CURRENT=$POLL_INTERVAL
# ---------------------------------------------------------------------------
# update_state WINDOW FIELD VALUE
# ---------------------------------------------------------------------------
update_state() {
local window="$1" field="$2" value="$3"
jq --arg w "$window" --arg f "$field" --arg v "$value" \
'.agents |= map(if .window == $w then .[$f] = $v else . end)' \
"$STATE_FILE" > "${STATE_FILE}.tmp" && mv "${STATE_FILE}.tmp" "$STATE_FILE"
}
update_state_int() {
local window="$1" field="$2" value="$3"
jq --arg w "$window" --arg f "$field" --argjson v "$value" \
'.agents |= map(if .window == $w then .[$f] = $v else . end)' \
"$STATE_FILE" > "${STATE_FILE}.tmp" && mv "${STATE_FILE}.tmp" "$STATE_FILE"
}
agent_field() {
jq -r --arg w "$1" --arg f "$2" \
'.agents[] | select(.window == $w) | .[$f] // ""' \
"$STATE_FILE" 2>/dev/null
}
# ---------------------------------------------------------------------------
# wait_for_prompt WINDOW — wait up to 60s for Claude's prompt
# ---------------------------------------------------------------------------
wait_for_prompt() {
local window="$1"
for i in $(seq 1 60); do
local cmd pane
cmd=$(tmux display-message -t "$window" -p '#{pane_current_command}' 2>/dev/null || echo "")
pane=$(tmux capture-pane -t "$window" -p 2>/dev/null || echo "")
if echo "$pane" | grep -q "Enter to confirm"; then
tmux send-keys -t "$window" Down Enter; sleep 2; continue
fi
[[ "$cmd" == "node" ]] && echo "$pane" | grep -q "" && return 0
sleep 1
done
return 1 # timed out
}
# ---------------------------------------------------------------------------
# wait_for_claude_idle WINDOW — wait up to 30s for Claude to reach idle prompt
# (no spinner or busy indicator visible in the last 3 lines of pane output)
# Returns 0 when idle, 1 on timeout.
# ---------------------------------------------------------------------------
wait_for_claude_idle() {
local window="$1"
local timeout="${2:-30}"
local elapsed=0
while (( elapsed < timeout )); do
local cmd pane pane_tail
cmd=$(tmux display-message -t "$window" -p '#{pane_current_command}' 2>/dev/null || echo "")
pane=$(tmux capture-pane -t "$window" -p 2>/dev/null || echo "")
pane_tail=$(echo "$pane" | tail -3)
# Check full pane (not just tail) — 'Enter to confirm' dialog can scroll above last 3 lines.
# Do NOT reset elapsed — resetting allows an infinite loop if the dialog never clears.
if echo "$pane" | grep -q "Enter to confirm"; then
tmux send-keys -t "$window" Down Enter
sleep 2; (( elapsed += 2 )); continue
fi
# Must be running under node (Claude is live)
if [[ "$cmd" == "node" ]]; then
# Idle: prompt visible AND no spinner/busy text in last 3 lines
if echo "$pane_tail" | grep -q "" && \
! echo "$pane_tail" | grep -qE '[✳✽✢✶·✻✼✿❋✤]|Running…|Compacting'; then
return 0
fi
fi
sleep 2
(( elapsed += 2 ))
done
return 1 # timed out
}
# ---------------------------------------------------------------------------
# handle_kick WINDOW STATE — only for idle (crashed) agents, not stuck
# ---------------------------------------------------------------------------
handle_kick() {
local window="$1" state="$2"
[[ "$state" != "idle" ]] && return # stuck agents handled by supervisor
local worktree_path session_id
worktree_path=$(agent_field "$window" "worktree_path")
session_id=$(agent_field "$window" "session_id")
echo "[$(date +%H:%M:%S)] KICK restart $window — agent exited, resuming session"
# Wait for the shell prompt before typing — avoids sending into a still-draining pane
wait_for_claude_idle "$window" 30 \
|| echo "[$(date +%H:%M:%S)] KICK WARNING $window — pane still busy before resume, sending anyway"
# Resume the exact session so the agent retains full context — no need to re-send objective
if [ -n "$session_id" ]; then
tmux send-keys -t "$window" "cd '${worktree_path}' && claude --resume '${session_id}' --permission-mode bypassPermissions" Enter
else
tmux send-keys -t "$window" "cd '${worktree_path}' && claude --continue --permission-mode bypassPermissions" Enter
fi
wait_for_prompt "$window" || echo "[$(date +%H:%M:%S)] KICK WARNING $window — timed out waiting for "
}
# ---------------------------------------------------------------------------
# handle_approve WINDOW — auto-approve dialogs that need no judgment
# ---------------------------------------------------------------------------
handle_approve() {
local window="$1"
local pane_tail
pane_tail=$(tmux capture-pane -t "$window" -p 2>/dev/null | tail -3 || echo "")
# Settings error dialog at startup
if echo "$pane_tail" | grep -q "Enter to confirm"; then
echo "[$(date +%H:%M:%S)] APPROVE dialog $window — settings error"
tmux send-keys -t "$window" Down Enter
return
fi
# Numbered-option dialog (e.g. "Do you want to make this edit?")
# is already on option 1 (Yes) — Enter confirms it
if echo "$pane_tail" | grep -qE "\s*1\." || echo "$pane_tail" | grep -q "Esc to cancel"; then
echo "[$(date +%H:%M:%S)] APPROVE edit $window"
tmux send-keys -t "$window" "" Enter
return
fi
# y/n prompt for safe operations
if echo "$pane_tail" | grep -qiE "(^git |^npm |^pnpm |^poetry |^pytest|^docker |^make |^cargo |^pip |^yarn |curl .*(localhost|127\.0\.0\.1))"; then
echo "[$(date +%H:%M:%S)] APPROVE safe $window"
tmux send-keys -t "$window" "y" Enter
return
fi
# Anything else — supervisor handles it, just log
echo "[$(date +%H:%M:%S)] APPROVE skip $window — unknown dialog, supervisor will handle"
}
# ---------------------------------------------------------------------------
# Main loop
# ---------------------------------------------------------------------------
echo "[$(date +%H:%M:%S)] run-loop started (mechanical only, poll ${POLL_INTERVAL}s→${POLL_IDLE_MAX}s adaptive)"
echo "[$(date +%H:%M:%S)] Supervisor: orchestrating Claude session (not a separate window)"
echo "---"
while true; do
if ! jq -e '.active == true' "$STATE_FILE" >/dev/null 2>&1; then
echo "[$(date +%H:%M:%S)] active=false — exiting."
exit 0
fi
ACTIONS=$("$SCRIPTS_DIR/poll-cycle.sh" 2>/dev/null || echo "[]")
KICKED=0; DONE=0
while IFS= read -r action; do
[ -z "$action" ] && continue
WINDOW=$(echo "$action" | jq -r '.window // ""')
ACTION=$(echo "$action" | jq -r '.action // ""')
STATE=$(echo "$action" | jq -r '.state // ""')
case "$ACTION" in
kick) handle_kick "$WINDOW" "$STATE" || true; KICKED=$(( KICKED + 1 )) ;;
approve) handle_approve "$WINDOW" || true ;;
complete) DONE=$(( DONE + 1 )) ;; # poll-cycle already set state=pending_evaluation; orchestrator handles
esac
done < <(echo "$ACTIONS" | jq -c '.[]' 2>/dev/null || true)
RUNNING=$(jq '[.agents[] | select(.state | test("running|stuck|waiting_approval|idle"))] | length' \
"$STATE_FILE" 2>/dev/null || echo 0)
# Adaptive backoff: reset to base on activity or waiting_approval agents; back off when truly idle
WAITING=$(jq '[.agents[] | select(.state == "waiting_approval")] | length' "$STATE_FILE" 2>/dev/null || echo 0)
if (( KICKED > 0 || DONE > 0 || WAITING > 0 )); then
POLL_CURRENT=$POLL_INTERVAL
else
POLL_CURRENT=$(( POLL_CURRENT + POLL_CURRENT / 2 + 1 ))
(( POLL_CURRENT > POLL_IDLE_MAX )) && POLL_CURRENT=$POLL_IDLE_MAX
fi
echo "[$(date +%H:%M:%S)] Poll — ${RUNNING} running ${KICKED} kicked ${DONE} recycled (next in ${POLL_CURRENT}s)"
sleep "$POLL_CURRENT"
done

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#!/usr/bin/env bash
# spawn-agent.sh — create tmux window, checkout branch, launch claude, send task
#
# Usage: spawn-agent.sh SESSION WORKTREE_PATH SPARE_BRANCH NEW_BRANCH OBJECTIVE [PR_NUMBER] [STEPS...]
# SESSION — tmux session name, e.g. autogpt1
# WORKTREE_PATH — absolute path to the git worktree
# SPARE_BRANCH — spare branch being replaced, e.g. spare/6 (saved for recycle)
# NEW_BRANCH — task branch to create, e.g. feat/my-feature
# OBJECTIVE — task description sent to the agent
# PR_NUMBER — (optional) GitHub PR number for completion verification
# STEPS... — (optional) required checkpoint names, e.g. pr-address pr-test
#
# Stdout: SESSION:WINDOW_INDEX (nothing else — callers rely on this)
# Exit non-zero on failure.
set -euo pipefail
if [ $# -lt 5 ]; then
echo "Usage: spawn-agent.sh SESSION WORKTREE_PATH SPARE_BRANCH NEW_BRANCH OBJECTIVE [PR_NUMBER] [STEPS...]" >&2
exit 1
fi
SESSION="$1"
WORKTREE_PATH="$2"
SPARE_BRANCH="$3"
NEW_BRANCH="$4"
OBJECTIVE="$5"
PR_NUMBER="${6:-}"
STEPS=("${@:7}")
WORKTREE_NAME=$(basename "$WORKTREE_PATH")
STATE_FILE="${ORCHESTRATOR_STATE_FILE:-$HOME/.claude/orchestrator-state.json}"
# Generate a stable session ID so this agent's Claude session can always be resumed:
# claude --resume $SESSION_ID --permission-mode bypassPermissions
SESSION_ID=$(uuidgen 2>/dev/null || python3 -c "import uuid; print(uuid.uuid4())")
# Create (or switch to) the task branch
git -C "$WORKTREE_PATH" checkout -b "$NEW_BRANCH" 2>/dev/null \
|| git -C "$WORKTREE_PATH" checkout "$NEW_BRANCH"
# Open a new named tmux window; capture its numeric index
WIN_IDX=$(tmux new-window -t "$SESSION" -n "$WORKTREE_NAME" -P -F '#{window_index}')
WINDOW="${SESSION}:${WIN_IDX}"
# Append the initial agent record to the state file so subsequent jq updates find it.
# This must happen before the pr_number/steps update below.
if [ -f "$STATE_FILE" ]; then
NOW=$(date +%s)
jq --arg window "$WINDOW" \
--arg worktree "$WORKTREE_NAME" \
--arg worktree_path "$WORKTREE_PATH" \
--arg spare_branch "$SPARE_BRANCH" \
--arg branch "$NEW_BRANCH" \
--arg objective "$OBJECTIVE" \
--arg session_id "$SESSION_ID" \
--argjson now "$NOW" \
'.agents += [{
"window": $window,
"worktree": $worktree,
"worktree_path": $worktree_path,
"spare_branch": $spare_branch,
"branch": $branch,
"objective": $objective,
"session_id": $session_id,
"state": "running",
"checkpoints": [],
"last_output_hash": "",
"last_seen_at": $now,
"spawned_at": $now,
"idle_since": 0,
"revision_count": 0,
"last_rebriefed_at": 0
}]' "$STATE_FILE" > "${STATE_FILE}.tmp" && mv "${STATE_FILE}.tmp" "$STATE_FILE"
fi
# Store pr_number + steps in state file if provided (enables verify-complete.sh).
# The agent record was appended above so the jq select now finds it.
if [ -n "$PR_NUMBER" ] && [ -f "$STATE_FILE" ]; then
if [ "${#STEPS[@]}" -gt 0 ]; then
STEPS_JSON=$(printf '%s\n' "${STEPS[@]}" | jq -R . | jq -s .)
else
STEPS_JSON='[]'
fi
jq --arg w "$WINDOW" --arg pr "$PR_NUMBER" --argjson steps "$STEPS_JSON" \
'.agents |= map(if .window == $w then . + {pr_number: $pr, steps: $steps, checkpoints: []} else . end)' \
"$STATE_FILE" > "${STATE_FILE}.tmp" && mv "${STATE_FILE}.tmp" "$STATE_FILE"
fi
# Launch claude with a stable session ID so it can always be resumed after a crash:
# claude --resume SESSION_ID --permission-mode bypassPermissions
tmux send-keys -t "$WINDOW" "cd '${WORKTREE_PATH}' && claude --permission-mode bypassPermissions --session-id '${SESSION_ID}'" Enter
# wait_for_claude_idle — poll until the pane shows idle with no spinner in the last 3 lines.
# Returns 0 when idle, 1 on timeout.
_wait_idle() {
local window="$1" timeout="${2:-60}" elapsed=0
while (( elapsed < timeout )); do
local cmd pane_tail
cmd=$(tmux display-message -t "$window" -p '#{pane_current_command}' 2>/dev/null || echo "")
pane=$(tmux capture-pane -t "$window" -p 2>/dev/null || echo "")
pane_tail=$(echo "$pane" | tail -3)
# Check full pane (not just tail) — 'Enter to confirm' dialog can appear above the last 3 lines
if echo "$pane" | grep -q "Enter to confirm"; then
tmux send-keys -t "$window" Down Enter
sleep 2; (( elapsed += 2 )); continue
fi
if [[ "$cmd" == "node" ]] && \
echo "$pane_tail" | grep -q "" && \
! echo "$pane_tail" | grep -qE '[✳✽✢✶·✻✼✿❋✤]|Running…|Compacting'; then
return 0
fi
sleep 2; (( elapsed += 2 ))
done
return 1
}
# Wait up to 60s for claude to be fully interactive and idle ( visible, no spinner).
if ! _wait_idle "$WINDOW" 60; then
echo "[spawn-agent] WARNING: timed out waiting for idle prompt on $WINDOW — sending objective anyway" >&2
fi
# Send the task. Split text and Enter — if combined, Enter can fire before the string
# is fully buffered, leaving the message stuck as "[Pasted text +N lines]" unsent.
tmux send-keys -t "$WINDOW" "${OBJECTIVE} Output each completed step as CHECKPOINT:<step-name>. When ALL steps are done, output ORCHESTRATOR:DONE on its own line."
sleep 0.3
tmux send-keys -t "$WINDOW" Enter
# Only output the window address — nothing else (callers parse this)
echo "$WINDOW"

View File

@@ -0,0 +1,43 @@
#!/usr/bin/env bash
# status.sh — print orchestrator status: state file summary + live tmux pane commands
#
# Usage: status.sh
# Reads: ~/.claude/orchestrator-state.json
set -euo pipefail
STATE_FILE="${ORCHESTRATOR_STATE_FILE:-$HOME/.claude/orchestrator-state.json}"
if [ ! -f "$STATE_FILE" ] || ! jq -e '.' "$STATE_FILE" >/dev/null 2>&1; then
echo "No orchestrator state found at $STATE_FILE"
exit 0
fi
# Header: active status, session, thresholds, last poll
jq -r '
"=== Orchestrator [\(if .active then "RUNNING" else "STOPPED" end)] ===",
"Session: \(.tmux_session // "unknown") | Idle threshold: \(.idle_threshold_seconds // 300)s",
"Last poll: \(if (.last_poll_at // 0) == 0 then "never" else (.last_poll_at | strftime("%H:%M:%S")) end)",
""
' "$STATE_FILE"
# Each agent: state, window, worktree/branch, truncated objective
AGENT_COUNT=$(jq '.agents | length' "$STATE_FILE")
if [ "$AGENT_COUNT" -eq 0 ]; then
echo " (no agents registered)"
else
jq -r '
.agents[] |
" [\(.state | ascii_upcase)] \(.window) \(.worktree)/\(.branch)",
" \(.objective // "" | .[0:70])"
' "$STATE_FILE"
fi
echo ""
# Live pane_current_command for non-done agents
while IFS= read -r WINDOW; do
[ -z "$WINDOW" ] && continue
CMD=$(tmux display-message -t "$WINDOW" -p '#{pane_current_command}' 2>/dev/null || echo "unreachable")
echo " $WINDOW live: $CMD"
done < <(jq -r '.agents[] | select(.state != "done") | .window' "$STATE_FILE" 2>/dev/null || true)

View File

@@ -0,0 +1,180 @@
#!/usr/bin/env bash
# verify-complete.sh — verify a PR task is truly done before marking the agent done
#
# Check order matters:
# 1. Checkpoints — did the agent do all required steps?
# 2. CI complete — no pending (bots post comments AFTER their check runs, must wait)
# 3. CI passing — no failures (agent must fix before done)
# 4. spawned_at — a new CI run was triggered after agent spawned (proves real work)
# 5. Unresolved threads — checked AFTER CI so bot-posted comments are included
# 6. CHANGES_REQUESTED — checked AFTER CI so bot reviews are included
#
# Usage: verify-complete.sh WINDOW
# Exit 0 = verified complete; exit 1 = not complete (stderr has reason)
set -euo pipefail
WINDOW="$1"
STATE_FILE="${ORCHESTRATOR_STATE_FILE:-$HOME/.claude/orchestrator-state.json}"
PR_NUMBER=$(jq -r --arg w "$WINDOW" '.agents[] | select(.window == $w) | .pr_number // ""' "$STATE_FILE" 2>/dev/null)
STEPS=$(jq -r --arg w "$WINDOW" '.agents[] | select(.window == $w) | .steps // [] | .[]' "$STATE_FILE" 2>/dev/null || true)
CHECKPOINTS=$(jq -r --arg w "$WINDOW" '.agents[] | select(.window == $w) | .checkpoints // [] | .[]' "$STATE_FILE" 2>/dev/null || true)
WORKTREE_PATH=$(jq -r --arg w "$WINDOW" '.agents[] | select(.window == $w) | .worktree_path // ""' "$STATE_FILE" 2>/dev/null)
BRANCH=$(jq -r --arg w "$WINDOW" '.agents[] | select(.window == $w) | .branch // ""' "$STATE_FILE" 2>/dev/null)
SPAWNED_AT=$(jq -r --arg w "$WINDOW" '.agents[] | select(.window == $w) | .spawned_at // "0"' "$STATE_FILE" 2>/dev/null || echo "0")
# No PR number = cannot verify
if [ -z "$PR_NUMBER" ]; then
echo "NOT COMPLETE: no pr_number in state — set pr_number or mark done manually" >&2
exit 1
fi
# --- Check 1: all required steps are checkpointed ---
MISSING=""
while IFS= read -r step; do
[ -z "$step" ] && continue
if ! echo "$CHECKPOINTS" | grep -qFx "$step"; then
MISSING="$MISSING $step"
fi
done <<< "$STEPS"
if [ -n "$MISSING" ]; then
echo "NOT COMPLETE: missing checkpoints:$MISSING on PR #$PR_NUMBER" >&2
exit 1
fi
# Resolve repo for all GitHub checks below
REPO=$(jq -r '.repo // ""' "$STATE_FILE" 2>/dev/null || echo "")
if [ -z "$REPO" ] && [ -n "$WORKTREE_PATH" ] && [ -d "$WORKTREE_PATH" ]; then
REPO=$(git -C "$WORKTREE_PATH" remote get-url origin 2>/dev/null \
| sed 's|.*github\.com[:/]||; s|\.git$||' || echo "")
fi
if [ -z "$REPO" ]; then
echo "Warning: cannot resolve repo — skipping CI/thread checks" >&2
echo "VERIFIED: PR #$PR_NUMBER — checkpoints ✓ (CI/thread checks skipped — no repo)"
exit 0
fi
CI_BUCKETS=$(gh pr checks "$PR_NUMBER" --repo "$REPO" --json bucket 2>/dev/null || echo "[]")
# --- Check 2: CI fully complete — no pending checks ---
# Pending checks MUST finish before we check threads/reviews:
# bots (Seer, Check PR Status, etc.) post comments and CHANGES_REQUESTED AFTER their CI check runs.
PENDING=$(echo "$CI_BUCKETS" | jq '[.[] | select(.bucket == "pending")] | length' 2>/dev/null || echo "0")
if [ "$PENDING" -gt 0 ]; then
PENDING_NAMES=$(gh pr checks "$PR_NUMBER" --repo "$REPO" --json bucket,name 2>/dev/null \
| jq -r '[.[] | select(.bucket == "pending") | .name] | join(", ")' 2>/dev/null || echo "unknown")
echo "NOT COMPLETE: $PENDING CI checks still pending on PR #$PR_NUMBER ($PENDING_NAMES)" >&2
exit 1
fi
# --- Check 3: CI passing — no failures ---
FAILING=$(echo "$CI_BUCKETS" | jq '[.[] | select(.bucket == "fail")] | length' 2>/dev/null || echo "0")
if [ "$FAILING" -gt 0 ]; then
FAILING_NAMES=$(gh pr checks "$PR_NUMBER" --repo "$REPO" --json bucket,name 2>/dev/null \
| jq -r '[.[] | select(.bucket == "fail") | .name] | join(", ")' 2>/dev/null || echo "unknown")
echo "NOT COMPLETE: $FAILING failing CI checks on PR #$PR_NUMBER ($FAILING_NAMES)" >&2
exit 1
fi
# --- Check 4: a new CI run was triggered AFTER the agent spawned ---
if [ -n "$BRANCH" ] && [ "${SPAWNED_AT:-0}" -gt 0 ]; then
LATEST_RUN_AT=$(gh run list --repo "$REPO" --branch "$BRANCH" \
--json createdAt --limit 1 2>/dev/null | jq -r '.[0].createdAt // ""')
if [ -n "$LATEST_RUN_AT" ]; then
if date --version >/dev/null 2>&1; then
LATEST_RUN_EPOCH=$(date -d "$LATEST_RUN_AT" "+%s" 2>/dev/null || echo "0")
else
LATEST_RUN_EPOCH=$(TZ=UTC date -j -f "%Y-%m-%dT%H:%M:%SZ" "$LATEST_RUN_AT" "+%s" 2>/dev/null || echo "0")
fi
if [ "$LATEST_RUN_EPOCH" -le "$SPAWNED_AT" ]; then
echo "NOT COMPLETE: latest CI run on $BRANCH predates agent spawn — agent may not have pushed yet" >&2
exit 1
fi
fi
fi
OWNER=$(echo "$REPO" | cut -d/ -f1)
REPONAME=$(echo "$REPO" | cut -d/ -f2)
# --- Check 5: no unresolved review threads (checked AFTER CI — bots post after their check) ---
UNRESOLVED=$(gh api graphql -f query="
{ repository(owner: \"${OWNER}\", name: \"${REPONAME}\") {
pullRequest(number: ${PR_NUMBER}) {
reviewThreads(first: 50) { nodes { isResolved } }
}
}
}
" --jq '[.data.repository.pullRequest.reviewThreads.nodes[] | select(.isResolved == false)] | length' 2>/dev/null || echo "0")
if [ "$UNRESOLVED" -gt 0 ]; then
echo "NOT COMPLETE: $UNRESOLVED unresolved review threads on PR #$PR_NUMBER" >&2
exit 1
fi
# --- Check 6: no CHANGES_REQUESTED (checked AFTER CI — bots post reviews after their check) ---
# A CHANGES_REQUESTED review is stale if the latest commit was pushed AFTER the review was submitted.
# Stale reviews (pre-dating the fixing commits) should not block verification.
#
# Fetch commits and latestReviews in a single call and fail closed — if gh fails,
# treat that as NOT COMPLETE rather than silently passing.
# Use latestReviews (not reviews) so each reviewer's latest state is used — superseded
# CHANGES_REQUESTED entries are automatically excluded when the reviewer later approved.
# Note: we intentionally use committedDate (not PR updatedAt) because updatedAt changes on any
# PR activity (bot comments, label changes) which would create false negatives.
PR_REVIEW_METADATA=$(gh pr view "$PR_NUMBER" --repo "$REPO" \
--json commits,latestReviews 2>/dev/null) || {
echo "NOT COMPLETE: unable to fetch PR review metadata for PR #$PR_NUMBER" >&2
exit 1
}
LATEST_COMMIT_DATE=$(jq -r '.commits[-1].committedDate // ""' <<< "$PR_REVIEW_METADATA")
CHANGES_REQUESTED_REVIEWS=$(jq '[.latestReviews[]? | select(.state == "CHANGES_REQUESTED")]' <<< "$PR_REVIEW_METADATA")
BLOCKING_CHANGES_REQUESTED=0
BLOCKING_REQUESTERS=""
if [ -n "$LATEST_COMMIT_DATE" ] && [ "$(echo "$CHANGES_REQUESTED_REVIEWS" | jq length)" -gt 0 ]; then
if date --version >/dev/null 2>&1; then
LATEST_COMMIT_EPOCH=$(date -d "$LATEST_COMMIT_DATE" "+%s" 2>/dev/null || echo "0")
else
LATEST_COMMIT_EPOCH=$(TZ=UTC date -j -f "%Y-%m-%dT%H:%M:%SZ" "$LATEST_COMMIT_DATE" "+%s" 2>/dev/null || echo "0")
fi
while IFS= read -r review; do
[ -z "$review" ] && continue
REVIEW_DATE=$(echo "$review" | jq -r '.submittedAt // ""')
REVIEWER=$(echo "$review" | jq -r '.author.login // "unknown"')
if [ -z "$REVIEW_DATE" ]; then
# No submission date — treat as fresh (conservative: blocks verification)
BLOCKING_CHANGES_REQUESTED=$(( BLOCKING_CHANGES_REQUESTED + 1 ))
BLOCKING_REQUESTERS="${BLOCKING_REQUESTERS:+$BLOCKING_REQUESTERS, }${REVIEWER}"
else
if date --version >/dev/null 2>&1; then
REVIEW_EPOCH=$(date -d "$REVIEW_DATE" "+%s" 2>/dev/null || echo "0")
else
REVIEW_EPOCH=$(TZ=UTC date -j -f "%Y-%m-%dT%H:%M:%SZ" "$REVIEW_DATE" "+%s" 2>/dev/null || echo "0")
fi
if [ "$REVIEW_EPOCH" -gt "$LATEST_COMMIT_EPOCH" ]; then
# Review was submitted AFTER latest commit — still fresh, blocks verification
BLOCKING_CHANGES_REQUESTED=$(( BLOCKING_CHANGES_REQUESTED + 1 ))
BLOCKING_REQUESTERS="${BLOCKING_REQUESTERS:+$BLOCKING_REQUESTERS, }${REVIEWER}"
fi
# Review submitted BEFORE latest commit — stale, skip
fi
done <<< "$(echo "$CHANGES_REQUESTED_REVIEWS" | jq -c '.[]')"
else
# No commit date or no changes_requested — check raw count as fallback
BLOCKING_CHANGES_REQUESTED=$(echo "$CHANGES_REQUESTED_REVIEWS" | jq length 2>/dev/null || echo "0")
BLOCKING_REQUESTERS=$(echo "$CHANGES_REQUESTED_REVIEWS" | jq -r '[.[].author.login] | join(", ")' 2>/dev/null || echo "unknown")
fi
if [ "$BLOCKING_CHANGES_REQUESTED" -gt 0 ]; then
echo "NOT COMPLETE: CHANGES_REQUESTED (after latest commit) from ${BLOCKING_REQUESTERS} on PR #$PR_NUMBER" >&2
exit 1
fi
echo "VERIFIED: PR #$PR_NUMBER — checkpoints ✓, CI complete + green, 0 unresolved threads, no CHANGES_REQUESTED"
exit 0

View File

@@ -25,43 +25,102 @@ Understand the **Why / What / How** before addressing comments — you need cont
gh pr view {N} --json body --jq '.body'
```
> If GraphQL is rate-limited, `gh pr view` fails. See [GitHub rate limits](#github-rate-limits) for REST fallbacks.
## Fetch comments (all sources)
### 1. Inline review threads — GraphQL (primary source of actionable items)
Use GraphQL to fetch inline threads. It natively exposes `isResolved`, returns threads already grouped with all replies, and paginates via cursor — no manual thread reconstruction needed.
> ⚠️ **WARNING — PAGINATE ALL PAGES BEFORE ADDRESSING ANYTHING**
>
> `reviewThreads(first: 100)` returns at most 100 threads per page AND returns threads **oldest-first**. On a PR with many review cycles (e.g. 373 threads), the oldest 100200 threads are from past cycles and are **all already resolved**. Filtering client-side with `select(.isResolved == false)` on page 1 therefore yields **0 results** — even though pages 24 contain many unresolved threads from recent review cycles.
>
> **This is the most common failure mode:** agent fetches page 1, sees 0 unresolved after filtering, stops pagination, reports "done" — while hundreds of unresolved threads sit on later pages.
>
> One observed PR had 142 total threads: page 1 returned 0 unresolved (all old/resolved), while pages 23 had 111 unresolved. Another with 373 threads across 4 pages also had page 1 entirely resolved.
>
> **The rule: ALWAYS paginate to `hasNextPage == false` regardless of the per-page unresolved count. Never stop early because a page returns 0 unresolved.**
**Step 1 — Fetch total count and sanity-check the newest threads:**
```bash
# Get total count and the newest 100 threads (last: 100 returns newest-first)
gh api graphql -f query='
{
repository(owner: "Significant-Gravitas", name: "AutoGPT") {
pullRequest(number: {N}) {
reviewThreads(first: 100) {
pageInfo { hasNextPage endCursor }
nodes {
id
isResolved
path
comments(last: 1) {
nodes { databaseId body author { login } createdAt }
reviewThreads { totalCount }
newest: reviewThreads(last: 100) {
nodes { isResolved }
}
}
}
}' | jq '{ total: .data.repository.pullRequest.reviewThreads.totalCount, newest_unresolved: [.data.repository.pullRequest.newest.nodes[] | select(.isResolved == false)] | length }'
```
If `total > 100`, you have multiple pages — you **must** paginate all of them regardless of what `newest_unresolved` shows. The `last: 100` check is a sanity signal only; the full loop below is mandatory.
**Step 2 — Collect all unresolved thread IDs across all pages:**
```bash
# Accumulate all unresolved threads — loop until hasNextPage == false
CURSOR=""
ALL_THREADS="[]"
while true; do
AFTER=${CURSOR:+", after: \"$CURSOR\""}
PAGE=$(gh api graphql -f query="
{
repository(owner: \"Significant-Gravitas\", name: \"AutoGPT\") {
pullRequest(number: {N}) {
reviewThreads(first: 100${AFTER}) {
pageInfo { hasNextPage endCursor }
nodes {
id
isResolved
path
line
comments(last: 1) {
nodes { databaseId body author { login } }
}
}
}
}
}
}
}'
}")
# Append unresolved nodes from this page
PAGE_THREADS=$(echo "$PAGE" | jq '[.data.repository.pullRequest.reviewThreads.nodes[] | select(.isResolved == false)]')
ALL_THREADS=$(echo "$ALL_THREADS $PAGE_THREADS" | jq -s 'add')
HAS_NEXT=$(echo "$PAGE" | jq -r '.data.repository.pullRequest.reviewThreads.pageInfo.hasNextPage')
CURSOR=$(echo "$PAGE" | jq -r '.data.repository.pullRequest.reviewThreads.pageInfo.endCursor')
[ "$HAS_NEXT" = "false" ] && break
done
# Reverse so newest threads (last pages) are addressed first — GitHub returns oldest-first
# and the most recent review cycle's comments are the ones blocking approval.
ALL_THREADS=$(echo "$ALL_THREADS" | jq 'reverse')
echo "Total unresolved threads: $(echo "$ALL_THREADS" | jq 'length')"
echo "$ALL_THREADS" | jq '[.[] | {id, path, line, body: .comments.nodes[0].body[:200]}]'
```
If `pageInfo.hasNextPage` is true, fetch subsequent pages by adding `after: "<endCursor>"` to `reviewThreads(first: 100, after: "...")` and repeat until `hasNextPage` is false.
**Step 3 — Address every thread in `ALL_THREADS`, then resolve.**
Only after this loop completes (all pages fetched, count confirmed) should you begin making fixes.
> **Why reverse?** GraphQL returns threads oldest-first and exposes no `orderBy` option. A PR with 373 threads has ~4 pages; threads from the latest review cycle land on the last pages. Processing in reverse ensures the newest, most blocking comments are addressed first — the earlier pages mostly contain outdated threads from prior cycles.
**Filter to unresolved threads only** — skip any thread where `isResolved: true`. `comments(last: 1)` returns the most recent comment in the thread — act on that; it reflects the reviewer's final ask. Use the thread `id` (Relay global ID) to track threads across polls.
> If GraphQL is rate-limited, see [GitHub rate limits](#github-rate-limits) for the REST fallback (flat comment list — no thread grouping or `isResolved`).
### 2. Top-level reviews — REST (MUST paginate)
```bash
gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews --paginate
```
> **Already REST — unaffected by GraphQL rate limits or outages. Continue polling reviews normally even when GraphQL is exhausted.**
**CRITICAL — always `--paginate`.** Reviews default to 30 per page. PRs can have 80170+ reviews (mostly empty resolution events). Without pagination you miss reviews past position 30 — including `autogpt-reviewer`'s structured review which is typically posted after several CI runs and sits well beyond the first page.
Two things to extract:
@@ -80,20 +139,71 @@ Two things to extract:
gh api repos/Significant-Gravitas/AutoGPT/issues/{N}/comments --paginate
```
> **Already REST — unaffected by GraphQL rate limits.**
Mostly contains: bot summaries (`coderabbitai[bot]`), CI/conflict detection (`github-actions[bot]`), and author status updates. Scan for non-empty messages from non-bot human reviewers that aren't the PR author — those are the ones that need a response.
## For each unaddressed comment
Address comments **one at a time**: fix → commit → push → inline reply → next.
**CRITICAL: The only valid sequence is fix → commit → push → reply → resolve. Never resolve a thread without a real code commit.**
Resolving a thread via `resolveReviewThread` without an actual fix is the most common failure mode — it makes unresolved counts drop without any real change, producing a false "done" signal. If the issue was genuinely a false positive (no code change needed), reply explaining why and then resolve. Otherwise:
Address comments **one at a time**: fix → commit → push → inline reply → resolve.
1. Read the referenced code, make the fix (or reply explaining why it's not needed)
2. Commit and push the fix
3. Reply **inline** (not as a new top-level comment) referencing the fixing commit — this is what resolves the conversation for bot reviewers (coderabbitai, sentry):
Use a **markdown commit link** so GitHub renders it as a clickable reference. Always get the full SHA with `git rev-parse HEAD` **after** committing — never copy a SHA from a previous commit or hardcode one:
```bash
FULL_SHA=$(git rev-parse HEAD)
gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments/{ID}/replies \
-f body="🤖 Fixed in [${FULL_SHA:0:9}](https://github.com/Significant-Gravitas/AutoGPT/commit/${FULL_SHA}): <description>"
```
| Comment type | How to reply |
|---|---|
| Inline review (`pulls/{N}/comments`) | `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments/{ID}/replies -f body="🤖 Fixed in <commit-sha>: <description>"` |
| Conversation (`issues/{N}/comments`) | `gh api repos/Significant-Gravitas/AutoGPT/issues/{N}/comments -f body="🤖 Fixed in <commit-sha>: <description>"` |
| Inline review (`pulls/{N}/comments`) | `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments/{ID}/replies -f body="🤖 Fixed in [abc1234](https://github.com/Significant-Gravitas/AutoGPT/commit/FULL_SHA): <description>"` |
| Conversation (`issues/{N}/comments`) | `gh api repos/Significant-Gravitas/AutoGPT/issues/{N}/comments -f body="🤖 Fixed in [abc1234](https://github.com/Significant-Gravitas/AutoGPT/commit/FULL_SHA): <description>"` |
### What counts as a valid resolution
Only two situations justify calling `resolveReviewThread`:
1. **Real code fix**: you changed the code, committed + pushed, and replied with the SHA. The commit diff must actually address the concern — not just touch the same file.
2. **Genuine false positive**: the reviewer's concern does not apply to this code, and you can give a specific technical reason (e.g. "Not applicable — `sdk_cwd` is pre-validated by `_make_sdk_cwd()` which applies normpath + prefix assertion before reaching this point").
**Anti-patterns that look resolved but aren't — never do these:**
- `"Accepted, tracked as follow-up"` — a deferral, not a fix. The concern is still open. Do not resolve.
- `"Acknowledged"` or `"Same as above"` — these are acknowledgements, not fixes. Do not resolve.
- `"Fixed in abc1234"` where `abc1234` is a commit that doesn't actually change the flagged line/logic — dishonest. Verify `git show abc1234 -- path/to/file` changes the right thing before posting.
- Resolving without replying — the reviewer never sees what happened.
When in doubt: if a code change is needed, make it. A deferred issue means the thread stays open until the follow-up PR is merged.
## Codecov coverage
Codecov patch target is **80%** on changed lines. Checks are **informational** (not blocking) but should be green.
### Running coverage locally
**Backend** (from `autogpt_platform/backend/`):
```bash
poetry run pytest -s -vv --cov=backend --cov-branch --cov-report term-missing
```
**Frontend** (from `autogpt_platform/frontend/`):
```bash
pnpm vitest run --coverage
```
### When codecov/patch fails
1. Find uncovered files: `git diff --name-only $(gh pr view --json baseRefName --jq '.baseRefName')...HEAD`
2. For each uncovered file — extract inline logic to `helpers.ts`/`helpers.py` and test those (highest ROI). Colocate tests as `*_test.py` (backend) or `__tests__/*.test.ts` (frontend).
3. Run coverage locally to verify, commit, push.
## Format and commit
@@ -119,6 +229,22 @@ Then commit and **push immediately** — never batch commits without pushing. Ea
For backend commits in worktrees: `poetry run git commit` (pre-commit hooks).
## Coverage
Codecov enforces patch coverage on new/changed lines — new code you write must be tested. Before pushing, verify you haven't left new lines uncovered:
```bash
cd autogpt_platform/backend
poetry run pytest --cov=. --cov-report=term-missing {path/to/changed/module}
```
Look for lines marked `miss` — those are uncovered. Add tests for any new code you wrote as part of addressing comments.
**Rules:**
- New code you add should have tests
- Don't remove existing tests when fixing comments
- If a reviewer asks you to delete code, also delete its tests, but verify coverage hasn't dropped on remaining lines
## The loop
```text
@@ -208,3 +334,162 @@ git push
```
5. Restart the polling loop from the top — new commits reset CI status.
## GitHub rate limits
Three distinct rate limits exist — they have different causes, error shapes, and recovery times:
| Error | HTTP code | Cause | Recovery |
|---|---|---|---|
| `{"code":"abuse"}` | 403 | Secondary rate limit — too many write operations (comments, mutations) in a short window | Wait **23 minutes**. 60s is often not enough. |
| `{"message":"API rate limit exceeded"}` | 429 | Primary REST rate limit — 5000 calls/hr per user | Wait until `X-RateLimit-Reset` header timestamp |
| `GraphQL: API rate limit already exceeded for user ID ...` | 403 on stderr, `gh` exits 1 | **GraphQL-specific** per-user limit — distinct from REST's 5000/hr and from the abuse secondary limit. Trips faster than REST because point costs per query. | Wait until the GraphQL window resets (typically ~1 hour from the first call in the window). REST still works — use fallbacks below. |
**Prevention:** Add `sleep 3` between individual thread reply API calls. When posting >20 replies, increase to `sleep 5`.
### Detection
The `gh` CLI surfaces the GraphQL limit on stderr with the exact string `GraphQL: API rate limit already exceeded for user ID <id>` and exits 1 — any `gh api graphql ...` **or** `gh pr view ...` call fails. Check current quota and reset time via the REST endpoint that reports GraphQL quota (this call is REST and still works whether GraphQL is rate-limited OR fully down):
```bash
gh api rate_limit --jq '.resources.graphql' # { "limit": 5000, "used": 5000, "remaining": 0, "reset": 1729...}
# Human-readable reset:
gh api rate_limit --jq '.resources.graphql.reset' | xargs -I{} date -r {}
```
Retry when `remaining > 0`. If you need to proceed sooner, sleep 25 min and probe again — the limit is per user, not per machine, so other concurrent agents under the same token also consume it.
### What keeps working
When GraphQL is unavailable (rate-limited or outage):
- **Keeps working (REST):** top-level reviews fetch, conversation comments fetch, all inline-comment replies, CI status (`gh pr checks`), and the `gh api rate_limit` probe.
- **Degraded:** inline thread list — fall back to flat `/pulls/{N}/comments` REST, which drops thread grouping, `isResolved`, and Relay thread IDs. You still get comment bodies and the `databaseId` as `id`, enough to read and reply.
- **Blocked:** `gh pr view`, the `resolveReviewThread` mutation, and any new `gh api graphql` queries — wait for the quota to reset.
### Fall back to REST
**PR metadata reads** — `gh pr view` uses GraphQL under the hood; use the REST pulls endpoint instead, which returns the full PR object:
```bash
gh api repos/Significant-Gravitas/AutoGPT/pulls/{N} --jq '.body' # == --json body
gh api repos/Significant-Gravitas/AutoGPT/pulls/{N} --jq '.base.ref' # == --json baseRefName
gh api repos/Significant-Gravitas/AutoGPT/pulls/{N} --jq '.mergeable' # == --json mergeable
```
Note: REST `mergeable` returns `true|false|null`; GraphQL returns `MERGEABLE|CONFLICTING|UNKNOWN`. The `null` case maps to `UNKNOWN` — treat it the same (still computing; poll again).
**Inline comments (flat list)** — no thread grouping or `isResolved`, but enough to read and reply:
```bash
gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments --paginate \
| jq '[.[] | {id, path, line, user: .user.login, body: .body[:200], in_reply_to_id}]'
```
Use this degraded mode to make progress on the fix → reply loop, then return to GraphQL for `resolveReviewThread` once the rate limit resets.
**Replies** — already REST-native (`/pulls/{N}/comments/{ID}/replies`); no change needed, use the same command as the main flow.
**`resolveReviewThread`** — **no REST equivalent**; GitHub does not expose a REST endpoint for thread resolution. Queue the thread IDs needing resolution, wait for the GraphQL limit to reset, then run the resolve mutations in a batch (with `sleep 3` between calls, per the secondary-limit guidance).
### Recovery from secondary rate limit (403 abuse)
1. Stop all API writes immediately
2. Wait **2 minutes minimum** (not 60s — secondary limits are stricter)
3. Resume with `sleep 3` between each call
4. If 403 persists after 2 min, wait another 2 min before retrying
Never batch all replies in a tight loop — always space them out.
## Parallel thread resolution
When a PR has more than 10 unresolved threads, addressing one commit per thread is slow. Use this strategy instead:
### Group by file, batch per commit
1. Sort `ALL_THREADS` by `path` — threads in the same file can share a single commit.
2. Fix all threads in one file → `git commit` → `git push` → reply to **all** those threads with the same SHA → resolve them all.
3. Move to the next file group and repeat.
This reduces N commits to (number of files touched), which is usually 35 instead of 1530.
### Posting replies concurrently (for large batches)
For truly independent thread groups (different files, no shared logic), you can post replies in parallel using background subshells — but always space out API writes:
```bash
# Post replies to a batch of threads concurrently, 3s apart
(
sleep 3
gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments/{ID1}/replies \
-f body="🤖 Fixed in [${FULL_SHA:0:9}](https://github.com/Significant-Gravitas/AutoGPT/commit/${FULL_SHA}): ..."
) &
(
sleep 6
gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments/{ID2}/replies \
-f body="🤖 Fixed in [${FULL_SHA:0:9}](https://github.com/Significant-Gravitas/AutoGPT/commit/${FULL_SHA}): ..."
) &
wait # wait for all background replies before resolving
```
Then resolve sequentially (GraphQL mutations):
```bash
for THREAD_ID in "$THREAD1" "$THREAD2" "$THREAD3"; do
gh api graphql -f query="mutation { resolveReviewThread(input: {threadId: \"${THREAD_ID}\"}) { thread { isResolved } } }"
sleep 3
done
```
**Always sleep 3s between individual API writes** — GitHub's secondary rate limit (403) triggers on bursts of >20 writes. Increase to `sleep 5` when posting more than 20 replies in a batch.
## Resolving threads via GraphQL
Use `resolveReviewThread` **only after** the commit is pushed and the reply is posted:
```bash
gh api graphql -f query='mutation { resolveReviewThread(input: {threadId: "THREAD_ID"}) { thread { isResolved } } }'
```
**Never call this mutation before committing the fix.** The orchestrator will verify actual unresolved counts via GraphQL after you output `ORCHESTRATOR:DONE` — false resolutions will be caught and you will be re-briefed.
> `resolveReviewThread` is GraphQL-only — no REST equivalent. If GraphQL is rate-limited, see [GitHub rate limits](#github-rate-limits) for the queue-and-retry flow.
### Verify actual count before outputting ORCHESTRATOR:DONE
Before claiming "0 unresolved threads", always query GitHub directly — don't rely on your own bookkeeping. Paginate all pages — a single `first: 100` query misses threads beyond page 1:
```bash
# Step 1: get total thread count
gh api graphql -f query='
{
repository(owner: "Significant-Gravitas", name: "AutoGPT") {
pullRequest(number: {N}) {
reviewThreads { totalCount }
}
}
}' | jq '.data.repository.pullRequest.reviewThreads.totalCount'
# Step 2: paginate all pages, count truly unresolved
CURSOR=""; UNRESOLVED=0
while true; do
AFTER=${CURSOR:+", after: \"$CURSOR\""}
PAGE=$(gh api graphql -f query="
{
repository(owner: \"Significant-Gravitas\", name: \"AutoGPT\") {
pullRequest(number: {N}) {
reviewThreads(first: 100${AFTER}) {
pageInfo { hasNextPage endCursor }
nodes { isResolved }
}
}
}
}")
UNRESOLVED=$(( UNRESOLVED + $(echo "$PAGE" | jq '[.data.repository.pullRequest.reviewThreads.nodes[] | select(.isResolved==false)] | length') ))
HAS_NEXT=$(echo "$PAGE" | jq -r '.data.repository.pullRequest.reviewThreads.pageInfo.hasNextPage')
CURSOR=$(echo "$PAGE" | jq -r '.data.repository.pullRequest.reviewThreads.pageInfo.endCursor')
[ "$HAS_NEXT" = "false" ] && break
done
echo "Unresolved threads: $UNRESOLVED"
```
Only output `ORCHESTRATOR:DONE` after this loop reports 0.

View File

@@ -0,0 +1,275 @@
---
name: pr-polish
description: Alternate /pr-review and /pr-address on a PR until the PR is truly mergeable — no new review findings, zero unresolved inline threads, zero unaddressed top-level reviews or issue comments, all CI checks green, and two consecutive quiet polls after CI settles. Use when the user wants a PR polished to merge-ready without setting a fixed number of rounds.
user-invocable: true
argument-hint: "[PR number or URL] — if omitted, finds PR for current branch."
metadata:
author: autogpt-team
version: "1.0.0"
---
# PR Polish
**Goal.** Drive a PR to merge-ready by alternating `/pr-review` and `/pr-address` until **all** of the following hold:
1. The most recent `/pr-review` produces **zero new findings** (no new inline comments, no new top-level reviews with a non-empty body).
2. Every inline review thread reachable via GraphQL reports `isResolved: true`.
3. Every non-bot, non-author top-level review has been acknowledged (replied-to) OR resolved via a thread it spawned.
4. Every non-bot, non-author issue comment has been acknowledged (replied-to).
5. Every CI check is `conclusion: "success"` or `"skipped"` / `"neutral"` — none `"failure"` or still pending.
6. **Two consecutive post-CI polls** (≥60s apart) stay clean — no new threads, no new non-empty reviews, no new issue comments. Bots (coderabbitai, sentry, autogpt-reviewer) frequently post late after CI settles; a single green snapshot is not sufficient.
**Do not stop at a fixed number of rounds.** If round N introduces new comments, round N+1 is required. Cap at `_MAX_ROUNDS = 10` as a safety valve, but expect 25 in practice.
## TodoWrite
Before starting, write two todos so the user can see the loop progression:
- `Round {current}: /pr-review + /pr-address on PR #{N}` — current iteration.
- `Final polish polling: 2 consecutive clean polls, CI green, 0 unresolved` — runs after the last non-empty review round.
Update the `current` round counter at the start of each iteration; mark `completed` only when the round's address step finishes (all new threads addressed + resolved).
## Find the PR
```bash
ARG_PR="${ARG:-}"
# Normalize URL → numeric ID if the skill arg is a pull-request URL.
if [[ "$ARG_PR" =~ ^https?://github\.com/[^/]+/[^/]+/pull/([0-9]+) ]]; then
ARG_PR="${BASH_REMATCH[1]}"
fi
PR="${ARG_PR:-$(gh pr list --head "$(git branch --show-current)" --repo Significant-Gravitas/AutoGPT --json number --jq '.[0].number')}"
if [ -z "$PR" ] || [ "$PR" = "null" ]; then
echo "No PR found for current branch. Provide a PR number or URL as the skill arg."
exit 1
fi
echo "Polishing PR #$PR"
```
## The outer loop
```text
round = 0
while round < _MAX_ROUNDS:
round += 1
baseline = snapshot_state(PR) # see "Snapshotting state" below
invoke_skill("pr-review", PR) # posts findings as inline comments / top-level review
findings = diff_state(PR, baseline)
if findings.total == 0:
break # no new findings → go to polish polling
invoke_skill("pr-address", PR) # resolves every unresolved thread + CI failure
# Post-loop: polish polling (see below).
polish_polling(PR)
```
### Snapshotting state
Before each `/pr-review`, capture a baseline so the diff after the review reflects **only** what the review just added (not pre-existing threads):
```bash
# Inline threads — total count + latest databaseId per thread
gh api graphql -f query="
{
repository(owner: \"Significant-Gravitas\", name: \"AutoGPT\") {
pullRequest(number: ${PR}) {
reviewThreads(first: 100) {
totalCount
nodes {
id
isResolved
comments(last: 1) { nodes { databaseId } }
}
}
}
}
}" > /tmp/baseline_threads.json
# Top-level reviews — count + latest id per non-empty review
gh api "repos/Significant-Gravitas/AutoGPT/pulls/${PR}/reviews" --paginate \
--jq '[.[] | select((.body // "") != "") | {id, user: .user.login, state, submitted_at}]' \
> /tmp/baseline_reviews.json
# Issue comments — count + latest id per non-bot, non-author comment.
# Bots are filtered by User.type == "Bot" (GitHub sets this for app/bot
# accounts like coderabbitai, github-actions, sentry-io). The author is
# filtered by comparing login to the PR author — export it so jq can see it.
AUTHOR=$(gh api "repos/Significant-Gravitas/AutoGPT/pulls/${PR}" --jq '.user.login')
gh api "repos/Significant-Gravitas/AutoGPT/issues/${PR}/comments" --paginate \
--jq --arg author "$AUTHOR" \
'[.[] | select(.user.type != "Bot" and .user.login != $author)
| {id, user: .user.login, created_at}]' \
> /tmp/baseline_issue_comments.json
```
### Diffing after a review
After `/pr-review` runs, any of these counting as "new findings" means another address round is needed:
- New inline thread `id` not in the baseline.
- An existing thread whose latest comment `databaseId` is higher than the baseline's (new reply on an old thread).
- A new top-level review `id` with a non-empty body.
- A new issue comment `id` from a non-bot, non-author user.
If any of the four buckets is non-empty → not done; invoke `/pr-address` and loop.
## Polish polling
Once `/pr-review` produces zero new findings, do **not** exit yet. Bots (coderabbitai, sentry, autogpt-reviewer) commonly post late reviews after CI settles — 3090 seconds after the final push. Poll at 60-second intervals:
```text
NON_SUCCESS_TERMINAL = {"failure", "cancelled", "timed_out", "action_required", "startup_failure"}
clean_polls = 0
required_clean = 2
while clean_polls < required_clean:
# 1. CI gate — any terminal non-success conclusion (not just "failure")
# must trigger /pr-address. "success", "skipped", "neutral" are clean;
# anything else (including cancelled, timed_out, action_required) is a
# blocker that won't self-resolve.
ci = fetch_check_runs(PR)
if any ci.conclusion in NON_SUCCESS_TERMINAL:
invoke_skill("pr-address", PR) # address failures + any new comments
baseline = snapshot_state(PR) # reset — push during address invalidates old baseline
clean_polls = 0
continue
if any ci.conclusion is None (still in_progress):
sleep 60; continue # wait without counting this as clean
# 2. Comment / thread gate
threads = fetch_unresolved_threads(PR)
new_issue_comments = diff_against_baseline(issue_comments)
new_reviews = diff_against_baseline(reviews)
if threads or new_issue_comments or new_reviews:
invoke_skill("pr-address", PR)
baseline = snapshot_state(PR) # reset — the address loop just dealt with these,
# otherwise they stay "new" relative to the old baseline forever
clean_polls = 0
continue
# 3. Mergeability gate
mergeable = gh api repos/.../pulls/${PR} --jq '.mergeable'
if mergeable == false (CONFLICTING):
resolve_conflicts(PR) # see pr-address skill
clean_polls = 0
continue
if mergeable is null (UNKNOWN):
sleep 60; continue
clean_polls += 1
sleep 60
```
Only after `clean_polls == 2` do you report `ORCHESTRATOR:DONE`.
### Concrete CI fetch (don't parse `gh pr checks` text columns)
The `fetch_check_runs(PR)` step above must use `--json`, not the default text output. Job names can contain spaces and parentheses (e.g. `test (3.11)`, `Analyze (python)`), so `gh pr checks $PR | awk '{print $2}'` extracts `(3.11)` instead of the status — leading to a clean-poll firing while jobs are still pending.
```bash
# Reliable: use --json so columns are unambiguous.
ci_json=$(gh pr checks $PR --repo Significant-Gravitas/AutoGPT --json name,state,bucket)
pending=$(echo "$ci_json" | jq '[.[] | select(.bucket == "pending")] | length')
failed=$(echo "$ci_json" | jq '[.[] | select(.bucket == "fail" or .bucket == "cancel")] | length')
# Buckets are: pass | fail | pending | cancel | skipping
# (NOTE: gh pr checks does NOT expose `conclusion` as a JSON field —
# only `bucket`. Don't confuse with the GitHub REST API's check_runs
# endpoint, which DOES use conclusion.)
```
Map back to the pseudocode above: `bucket == "pending"` is `ci.conclusion is None (still in_progress)`; `bucket in {"fail", "cancel"}` is `ci.conclusion in NON_SUCCESS_TERMINAL`; `bucket in {"pass", "skipping"}` is clean.
### Why 2 clean polls, not 1
A single green snapshot can be misleading — the final CI check often completes ~30s before a bot posts its delayed review. One quiet cycle does not prove the PR is stable; two consecutive cycles with no new threads, reviews, or issue comments arriving gives high confidence nothing else is incoming.
### Why checking every source each poll
`/pr-address` polling inside a single round already re-checks its own comments, but `/pr-polish` sits a level above and must also catch:
- New top-level reviews (autogpt-reviewer sometimes posts structured feedback only after several CI green cycles).
- Issue comments from human reviewers (not caught by inline thread polling).
- Sentry bug predictions that land on new line numbers post-push.
- Merge conflicts introduced by a race between your push and a merge to `dev`.
## Invocation pattern
Delegate to existing skills with the `Skill` tool; do not re-implement the review or address logic inline. This keeps the polish loop focused on orchestration and lets the child skills evolve independently.
```python
Skill(skill="pr-review", args=pr_url)
Skill(skill="pr-address", args=pr_url)
```
After each child invocation, re-query GitHub state directly — never trust a summary for the stop condition. The orchestrator's `ORCHESTRATOR:DONE` is verified against actual GraphQL / REST responses per the rules in `pr-address`'s "Verify actual count before outputting ORCHESTRATOR:DONE" section.
### **Auto-continue: do NOT end your response between child skills**
`/pr-polish` is a single orchestration task — one invocation drives the PR all the way to merge-ready. When a child `Skill()` call returns control to you:
- Do NOT summarize and stop.
- Do NOT wait for user confirmation to continue.
- Immediately, in the same response, perform the next loop step: state diff → decide next action → next `Skill()` call or polling sleep.
The child skill returning is a **loop iteration boundary**, not a conversation turn boundary. You are expected to keep going until one of the exit conditions in the opening section is met (2 consecutive clean polls, `_MAX_ROUNDS` hit, or an unrecoverable error).
If the user needs to approve a risky action mid-loop (e.g., a force-push or a destructive git operation), pause there — but not at the routine "round N finished, round N+1 needed" boundary. Those are silent transitions.
### **Run /pr-polish in the foreground — never in a background agent**
Spawning `/pr-polish` inside an `Agent(subagent_type="general-purpose")` background task **does not work**. Background agents don't inherit the parent's slash-command registry, so `Skill(skill="pr-review")` and `Skill(skill="pr-address")` calls aren't available — the agent has to manually replicate the child skills' logic, which is fragile and tends to stall on the first network or rate-limit hiccup. Symptom: the background task reports `stalled: no progress for 600s` mid-review.
Run `/pr-polish` inline in the foreground conversation. If the user asks for "/pr-polish + /pr-test in parallel", split them: foreground `/pr-polish`, and ONLY then can the test step go to a background agent (because `/pr-test` doesn't itself need to invoke skills).
### **You MUST invoke `Skill(pr-review)` every round — even when bot reviews already exist**
A common failure mode: CodeRabbit / autogpt-reviewer / Sentry have already posted findings on the PR, and the orchestrator skips the `Skill(pr-review)` step on the assumption that "review has been done." That's wrong — the outer loop's purpose is to layer **the agent's own review** on top of the bot reviews, catching issues the bots miss (architecture, naming, cross-file invariants, hidden coupling). If the orchestrator only addresses bot findings without ever running its own review, the loop converges to "bot-clean" but not "agent-reviewed-clean," and the user reasonably asks "did /pr-polish even read the diff?"
**Self-check before reporting `ORCHESTRATOR:DONE`:** confirm at least one `Skill(skill="pr-review")` call appears in the current orchestration. If none, the loop is incomplete — go back and run one round.
## GitHub rate limits
This skill issues many GraphQL calls (one review-thread query per outer iteration plus per-poll queries inside polish polling). Expect the GraphQL budget to be tight on large PRs. When `gh api rate_limit --jq .resources.graphql.remaining` drops below ~200, back off:
- Fall back to REST for reads (flat `/pulls/{N}/comments`, `/pulls/{N}/reviews`, `/issues/{N}/comments`) per the `pr-address` skill's GraphQL-fallback section.
- Queue thread resolutions (GraphQL-only) until the budget resets; keep making progress on fixes + REST replies meanwhile.
- `sleep 5` between any batch of ≥20 writes to avoid secondary rate limits.
## Safety valves
- `_MAX_ROUNDS = 10` — if review+address rounds exceed this, stop and escalate to the user with a summary of what's still unresolved. A PR that cannot converge in 10 rounds has systemic issues that need human judgment.
- After each commit, run `poetry run format` / `pnpm format && pnpm lint && pnpm types` per the target codebase's conventions. A failing format check is CI `failure` that will never self-resolve.
- Every `/pr-review` round checks for **duplicate** concerns first (via `pr-review`'s own "Fetch existing review comments" step) so the loop does not re-post the same finding that a prior round already resolved.
## Reporting
When the skill finishes (either via two clean polls or hitting `_MAX_ROUNDS`), produce a compact summary:
```
PR #{N} polish complete ({rounds_completed} rounds):
- {X} inline threads opened and resolved
- {Y} CI failures fixed
- {Z} new commits pushed
Final state: CI green, {total} threads all resolved, mergeable.
```
If exiting via `_MAX_ROUNDS`, flag explicitly:
```
PR #{N} polish stopped at {_MAX_ROUNDS} rounds — NOT merge-ready:
- {N} threads still unresolved: {titles}
- CI status: {summary}
Needs human review.
```
## When to use this skill
Use when the user says any of:
- "polish this PR"
- "keep reviewing and addressing until it's mergeable"
- "loop /pr-review + /pr-address until done"
- "make sure the PR is actually merge-ready"
Do **not** use when:
- User wants just one review pass (→ `/pr-review`).
- User wants to address already-posted comments without further self-review (→ `/pr-address`).
- A fixed round count is explicitly requested (e.g., "do 3 rounds") — honour the count instead of converging.

View File

@@ -5,7 +5,7 @@ user-invocable: true
argument-hint: "[worktree path or PR number] — tests the PR in the given worktree. Optional flags: --fix (auto-fix issues found)"
metadata:
author: autogpt-team
version: "2.0.0"
version: "2.1.0"
---
# Manual E2E Test
@@ -180,6 +180,120 @@ Based on the PR analysis, write a test plan to `$RESULTS_DIR/test-plan.md`:
**Be critical** — include edge cases, error paths, and security checks. Every scenario MUST specify what screenshots to take and what state to verify.
## Step 3.0: Claim the testing lock (coordinate parallel agents)
Multiple worktrees share the same host — Docker infra (postgres, redis, clamav), app ports (3000/8006/…), and the test user. Two agents running `/pr-test` concurrently will corrupt each other's state (connection-pool exhaustion, port binds failing silently, cross-test assertions). Use the root-worktree lock file to take turns.
### Lock file contract
Path (**always** the root worktree so all siblings see it): `$REPO_ROOT/.ign.testing.lock`
Body (one `key=value` per line):
```
holder=<pr-XXXXX-purpose>
pid=<pid-or-"self">
started=<iso8601>
heartbeat=<iso8601, updated every ~2 min>
worktree=<full path>
branch=<branch name>
intent=<one-line description + rough duration>
```
### Claim
```bash
LOCK=$REPO_ROOT/.ign.testing.lock
NOW=$(date -u +%Y-%m-%dT%H:%MZ)
STALE_AFTER_MIN=5
if [ -f "$LOCK" ]; then
HB=$(grep '^heartbeat=' "$LOCK" | cut -d= -f2)
HB_EPOCH=$(date -j -f '%Y-%m-%dT%H:%MZ' "$HB" +%s 2>/dev/null || date -d "$HB" +%s 2>/dev/null || echo 0)
AGE_MIN=$(( ( $(date -u +%s) - HB_EPOCH ) / 60 ))
if [ "$AGE_MIN" -gt "$STALE_AFTER_MIN" ]; then
echo "WARN: stale lock (${AGE_MIN}m old) — reclaiming"
cat "$LOCK" | sed 's/^/ stale: /'
else
echo "Another agent holds the lock:"; cat "$LOCK"
echo "Wait until released or resume after $((STALE_AFTER_MIN - AGE_MIN))m."
exit 1
fi
fi
cat > "$LOCK" <<EOF
holder=pr-${PR_NUMBER}-e2e
pid=self
started=$NOW
heartbeat=$NOW
worktree=$WORKTREE_PATH
branch=$(cd $WORKTREE_PATH && git branch --show-current)
intent=E2E test PR #${PR_NUMBER}, native mode, ~60min
EOF
echo "Lock claimed"
```
### Heartbeat (MUST run in background during the whole test)
Without a heartbeat a crashed agent keeps the lock forever. Run this as a background process right after claim:
```bash
(while true; do
sleep 120
[ -f "$LOCK" ] || exit 0 # lock released → exit heartbeat
perl -i -pe "s/^heartbeat=.*/heartbeat=$(date -u +%Y-%m-%dT%H:%MZ)/" "$LOCK"
done) &
HEARTBEAT_PID=$!
echo "$HEARTBEAT_PID" > /tmp/pr-test-heartbeat.pid
```
### Release (always — even on failure)
```bash
kill "$HEARTBEAT_PID" 2>/dev/null
rm -f "$LOCK" /tmp/pr-test-heartbeat.pid
echo "$(date -u +%Y-%m-%dT%H:%MZ) [pr-${PR_NUMBER}] released lock" \
>> $REPO_ROOT/.ign.testing.log
```
Use a `trap` so release runs even on `exit 1`:
```bash
trap 'kill "$HEARTBEAT_PID" 2>/dev/null; rm -f "$LOCK"' EXIT INT TERM
```
### **Release the lock AS SOON AS the test run is done**
The lock guards **test execution**, not **app lifecycle**. Once Step 5 (record results) and Step 6 (post PR comment) are complete, release the lock IMMEDIATELY — even if:
- The native `poetry run app` / `pnpm dev` processes are still running so the user can keep poking at the app manually.
- You're leaving docker containers up.
- You're tailing logs for a minute or two.
Keeping the lock held past the test run is the single most common way `/pr-test` stalls other agents. **The app staying up is orthogonal to the lock; don't conflate them.** Sibling worktrees running their own `/pr-test` will kill the stray processes and free the ports themselves (Step 3c/3e-native handle that) — they just need the lock file gone.
Concretely, the sequence at the end of every `/pr-test` run (success or failure) is:
```bash
# 1. Write the final report + post PR comment — done above in Step 5/6.
# 2. Release the lock right now, even if the app is still up.
kill "$HEARTBEAT_PID" 2>/dev/null
rm -f "$LOCK" /tmp/pr-test-heartbeat.pid
echo "$(date -u +%Y-%m-%dT%H:%MZ) [pr-${PR_NUMBER}] released lock (app may still be running)" \
>> $REPO_ROOT/.ign.testing.log
# 3. Optionally leave the app running and note it so the user knows:
echo "Native stack still running on :3000 / :8006 for manual poking. Kill with:"
echo " pkill -9 -f 'poetry run app'; pkill -9 -f 'next-server|next dev'"
```
If a sibling agent's `/pr-test` needs to take over, it'll do the kill+rebuild dance from Step 3c/3e-native on its own — your only job is to not hold the lock file past the end of your test.
### Shared status log
`$REPO_ROOT/.ign.testing.log` is an append-only channel any agent can read/write. Use it for "I'm waiting", "I'm done, resources free", or post-run notes:
```bash
echo "$(date -u +%Y-%m-%dT%H:%MZ) [pr-${PR_NUMBER}] <message>" \
>> $REPO_ROOT/.ign.testing.log
```
## Step 3: Environment setup
### 3a. Copy .env files from the root worktree
@@ -248,7 +362,87 @@ docker ps --format "{{.Names}}" | grep -E "rest_server|executor|copilot|websocke
done
```
### 3e. Build and start
**Native mode also:** when running the app natively (see 3e-native), kill any stray host processes and free the app ports before starting — otherwise `poetry run app` and `pnpm dev` will fail to bind.
```bash
# Kill stray native app processes from prior runs
pkill -9 -f "python.*backend" 2>/dev/null || true
pkill -9 -f "poetry run app" 2>/dev/null || true
pkill -9 -f "next-server|next dev" 2>/dev/null || true
# Free app ports (errors per port are ignored — port may simply be unused)
for port in 3000 8006 8001 8002 8005 8008; do
lsof -ti :$port -sTCP:LISTEN | xargs -r kill -9 2>/dev/null || true
done
```
### 3e-native. Run the app natively (PREFERRED for iterative dev)
Native mode runs infra (postgres, supabase, redis, rabbitmq, clamav) in docker but runs the backend and frontend directly on the host. This avoids the 3-8 minute `docker compose build` cycle on every backend change — code edits are picked up on process restart (seconds) instead of a full image rebuild.
**When to prefer native mode (default for this skill):**
- Iterative dev/debug loops where you're editing backend or frontend code between test runs
- Any PR that touches Python/TS source but not Dockerfiles, compose config, or infra images
- Fast repro of a failing scenario — restart `poetry run app` in a couple of seconds
**When to prefer docker mode (3e fallback):**
- Testing changes to `Dockerfile`, `docker-compose.yml`, or base images
- Production-parity smoke tests (exact container env, networking, volumes)
- CI-equivalent runs where you need the exact image that'll ship
**Note on 3b (copilot auth):** no npm install anywhere. `poetry install` pulls in `claude_agent_sdk`, which ships its own Claude CLI binary — available on `PATH` whenever you run commands via `poetry run` (native) OR whenever the copilot_executor container is built from its Poetry lockfile (docker). The OAuth token extraction still applies (same `refresh_claude_token.sh` call).
**Preamble:** before starting native, run the kill-stray + free-ports block from 3c's "Native mode also" subsection.
**1. Start infra only (one-time per session):**
```bash
cd $PLATFORM_DIR && docker compose --profile local up deps --detach --remove-orphans --build
```
This brings up postgres/supabase/redis/rabbitmq/clamav and skips all app services.
**2. Start the backend natively:**
```bash
cd $BACKEND_DIR && (poetry run app 2>&1 | tee .ign.application.logs) &
```
`poetry run app` spawns **all** app subprocesses — `rest_server`, `executor`, `copilot_executor`, `websocket`, `scheduler`, `notification_server`, `database_manager` — inside ONE parent process. No separate containers, no separate terminals. The `.ign.application.logs` prefix is already gitignored.
**3. Wait for the backend on :8006 BEFORE starting the frontend.** This ordering matters — the frontend's `pnpm dev` startup invokes `generate-api-queries`, which fetches `/openapi.json` from the backend. If the backend isn't listening yet, `pnpm dev` fails immediately.
```bash
for i in $(seq 1 60); do
if [ "$(curl -s -o /dev/null -w '%{http_code}' http://localhost:8006/docs 2>/dev/null)" = "200" ]; then
echo "Backend ready"
break
fi
sleep 2
done
```
**4. Start the frontend natively:**
```bash
cd $FRONTEND_DIR && (pnpm dev 2>&1 | tee .ign.frontend.logs) &
```
**5. Wait for the frontend on :3000:**
```bash
for i in $(seq 1 60); do
if [ "$(curl -s -o /dev/null -w '%{http_code}' http://localhost:3000 2>/dev/null)" = "200" ]; then
echo "Frontend ready"
break
fi
sleep 2
done
```
Once both are up, skip 3e/3f and go straight to **3g/3h** (feature flags / test user creation).
### 3e. Build and start (docker — fallback)
```bash
cd $PLATFORM_DIR && docker compose build --no-cache 2>&1 | tail -20
@@ -310,6 +504,28 @@ TOKEN=$(curl -s -X POST 'http://localhost:8000/auth/v1/token?grant_type=password
curl -H "Authorization: Bearer $TOKEN" http://localhost:8006/api/...
```
### 3i. Disable onboarding for test user
The frontend redirects to `/onboarding` when the `VISIT_COPILOT` step is not in `completedSteps`.
Mark it complete via the backend API so every browser test lands on the real feature UI:
```bash
ONBOARDING_RESULT=$(curl -s --max-time 30 -X POST \
"http://localhost:8006/api/onboarding/step?step=VISIT_COPILOT" \
-H "Authorization: Bearer $TOKEN")
echo "Onboarding bypass: $ONBOARDING_RESULT"
# Verify it took effect
ONBOARDING_STATUS=$(curl -s --max-time 30 \
"http://localhost:8006/api/onboarding/completed" \
-H "Authorization: Bearer $TOKEN" | jq -r '.is_completed')
echo "Onboarding completed: $ONBOARDING_STATUS"
if [ "$ONBOARDING_STATUS" != "true" ]; then
echo "ERROR: onboarding bypass failed — browser tests will hit /onboarding instead of the target feature. Investigate before proceeding."
exit 1
fi
```
## Step 4: Run tests
### Service ports reference
@@ -420,6 +636,22 @@ agent-browser --session-name pr-test snapshot | grep "text:"
### Checking logs
**Native mode:** when running via `poetry run app` + `pnpm dev`, all app logs stream to the `.ign.*.logs` files written by the `tee` pipes in 3e-native. `rest_server`, `executor`, `copilot_executor`, `websocket`, `scheduler`, `notification_server`, and `database_manager` are all subprocesses of the single `poetry run app` parent, so their output is interleaved in `.ign.application.logs`.
```bash
# Backend (all app subprocesses interleaved)
tail -f $BACKEND_DIR/.ign.application.logs
# Frontend (Next.js dev server)
tail -f $FRONTEND_DIR/.ign.frontend.logs
# Filter for errors across either log
grep -iE "error|exception|traceback" $BACKEND_DIR/.ign.application.logs | tail -20
grep -iE "error|exception|traceback" $FRONTEND_DIR/.ign.frontend.logs | tail -20
```
**Docker mode:**
```bash
# Backend REST server
docker logs autogpt_platform-rest_server-1 2>&1 | tail -30
@@ -547,6 +779,21 @@ Upload screenshots to the PR using the GitHub Git API (no local git operations
**This step is MANDATORY. Every test run MUST post a PR comment with screenshots. No exceptions.**
**CRITICAL — NEVER post a bare directory link like `https://github.com/.../tree/...`.** Every screenshot MUST appear as `![name](raw_url)` inline in the PR comment so reviewers can see them without clicking any links. After posting, the verification step below greps the comment for `![` tags and exits 1 if none are found — the test run is considered incomplete until this passes.
**CRITICAL — NEVER paste absolute local paths into the PR comment.** Strings like `/Users/…`, `/home/…`, `C:\…` are useless to every reviewer except you. Before posting, grep the final body for `/Users/`, `/home/`, `/tmp/`, `/private/`, `C:\`, `~/` and either drop those lines entirely or rewrite them as repo-relative paths (`autogpt_platform/backend/…`). The PR comment is an artifact reviewers on GitHub read — it must be self-contained on github.com. Keep local paths in `$RESULTS_DIR/test-report.md` for yourself; only copy the *content* they reference (excerpts, test names, log lines) into the PR comment, not the path.
**Pre-post sanity check** (paste after building the comment body, before `gh api ... comments`):
```bash
# Reject any local-looking absolute path or home-dir shortcut in the body
if grep -nE '(^|[^A-Za-z])(/Users/|/home/|/tmp/|/private/|C:\\|~/)[A-Za-z0-9]' "$COMMENT_FILE" ; then
echo "ABORT: local filesystem paths detected in PR comment body."
echo "Remove or rewrite as repo-relative (autogpt_platform/...) before posting."
exit 1
fi
```
```bash
# Upload screenshots via GitHub Git API (creates blobs, tree, commit, and ref remotely)
REPO="Significant-Gravitas/AutoGPT"
@@ -584,15 +831,27 @@ TREE_JSON+=']'
# Step 2: Create tree, commit, and branch ref
TREE_SHA=$(echo "$TREE_JSON" | jq -c '{tree: .}' | gh api "repos/${REPO}/git/trees" --input - --jq '.sha')
COMMIT_SHA=$(gh api "repos/${REPO}/git/commits" \
-f message="test: add E2E test screenshots for PR #${PR_NUMBER}" \
-f tree="$TREE_SHA" \
--jq '.sha')
# Resolve parent commit so screenshots are chained, not orphan root commits
PARENT_SHA=$(gh api "repos/${REPO}/git/refs/heads/${SCREENSHOTS_BRANCH}" --jq '.object.sha' 2>/dev/null || echo "")
if [ -n "$PARENT_SHA" ]; then
COMMIT_SHA=$(gh api "repos/${REPO}/git/commits" \
-f message="test: add E2E test screenshots for PR #${PR_NUMBER}" \
-f tree="$TREE_SHA" \
-f "parents[]=$PARENT_SHA" \
--jq '.sha')
else
COMMIT_SHA=$(gh api "repos/${REPO}/git/commits" \
-f message="test: add E2E test screenshots for PR #${PR_NUMBER}" \
-f tree="$TREE_SHA" \
--jq '.sha')
fi
gh api "repos/${REPO}/git/refs" \
-f ref="refs/heads/${SCREENSHOTS_BRANCH}" \
-f sha="$COMMIT_SHA" 2>/dev/null \
|| gh api "repos/${REPO}/git/refs/heads/${SCREENSHOTS_BRANCH}" \
-X PATCH -f sha="$COMMIT_SHA" -f force=true
-X PATCH -f sha="$COMMIT_SHA" -F force=true
```
Then post the comment with **inline images AND explanations for each screenshot**:
@@ -658,6 +917,15 @@ INNEREOF
gh api "repos/${REPO}/issues/$PR_NUMBER/comments" -F body=@"$COMMENT_FILE"
rm -f "$COMMENT_FILE"
# Verify the posted comment contains inline images — exit 1 if none found
# Use separate --paginate + jq pipe: --jq applies per-page, not to the full list
LAST_COMMENT=$(gh api "repos/${REPO}/issues/$PR_NUMBER/comments" --paginate 2>/dev/null | jq -r '.[-1].body // ""')
if ! echo "$LAST_COMMENT" | grep -q '!\['; then
echo "ERROR: Posted comment contains no inline images (![). Bare directory links are not acceptable." >&2
exit 1
fi
echo "✓ Inline images verified in posted comment"
```
**The PR comment MUST include:**
@@ -667,6 +935,103 @@ rm -f "$COMMENT_FILE"
This approach uses the GitHub Git API to create blobs, trees, commits, and refs entirely server-side. No local `git checkout` or `git push` — safe for worktrees and won't interfere with the PR branch.
## Step 8: Evaluate and post a formal PR review
After the test comment is posted, evaluate whether the run was thorough enough to make a merge decision, then post a formal GitHub review (approve or request changes). **This step is mandatory — every test run MUST end with a formal review decision.**
### Evaluation criteria
Re-read the PR description:
```bash
gh pr view "$PR_NUMBER" --json body --jq '.body' --repo "$REPO"
```
Score the run against each criterion:
| Criterion | Pass condition |
|-----------|---------------|
| **Coverage** | Every feature/change described in the PR has at least one test scenario |
| **All scenarios pass** | No FAIL rows in the results table |
| **Negative tests** | At least one failure-path test per feature (invalid input, unauthorized, edge case) |
| **Before/after evidence** | Every state-changing API call has before/after values logged |
| **Screenshots are meaningful** | Screenshots show the actual state change, not just a loading spinner or blank page |
| **No regressions** | Existing core flows (login, agent create/run) still work |
### Decision logic
```
ALL criteria pass → APPROVE
Any scenario FAIL or missing PR feature → REQUEST_CHANGES (list gaps)
Evidence weak (no before/after, vague shots) → REQUEST_CHANGES (list what's missing)
```
### Post the review
```bash
REVIEW_FILE=$(mktemp)
# Count results
PASS_COUNT=$(echo "$TEST_RESULTS_TABLE" | grep -c "PASS" || true)
FAIL_COUNT=$(echo "$TEST_RESULTS_TABLE" | grep -c "FAIL" || true)
TOTAL=$(( PASS_COUNT + FAIL_COUNT ))
# List any coverage gaps found during evaluation (populate this array as you assess)
# e.g. COVERAGE_GAPS=("PR claims to add X but no test covers it")
COVERAGE_GAPS=()
```
**If APPROVING** — all criteria met, zero failures, full coverage:
```bash
cat > "$REVIEW_FILE" <<REVIEWEOF
## E2E Test Evaluation — APPROVED
**Results:** ${PASS_COUNT}/${TOTAL} scenarios passed.
**Coverage:** All features described in the PR were exercised.
**Evidence:** Before/after API values logged for all state-changing operations; screenshots show meaningful state transitions.
**Negative tests:** Failure paths tested for each feature.
No regressions observed on core flows.
REVIEWEOF
gh pr review "$PR_NUMBER" --repo "$REPO" --approve --body "$(cat "$REVIEW_FILE")"
echo "✅ PR approved"
```
**If REQUESTING CHANGES** — any failure, coverage gap, or missing evidence:
```bash
FAIL_LIST=$(echo "$TEST_RESULTS_TABLE" | grep "FAIL" | awk -F'|' '{print "- Scenario" $2 "failed"}' || true)
cat > "$REVIEW_FILE" <<REVIEWEOF
## E2E Test Evaluation — Changes Requested
**Results:** ${PASS_COUNT}/${TOTAL} scenarios passed, ${FAIL_COUNT} failed.
### Required before merge
${FAIL_LIST}
$(for gap in "${COVERAGE_GAPS[@]}"; do echo "- $gap"; done)
Please fix the above and re-run the E2E tests.
REVIEWEOF
gh pr review "$PR_NUMBER" --repo "$REPO" --request-changes --body "$(cat "$REVIEW_FILE")"
echo "❌ Changes requested"
```
```bash
rm -f "$REVIEW_FILE"
```
**Rules:**
- In `--fix` mode, fix all failures before posting the review — the review reflects the final state after fixes
- Never approve if any scenario failed, even if it seems like a flake — rerun that scenario first
- Never request changes for issues already fixed in this run
## Fix mode (--fix flag)
When `--fix` is present, the standard is HIGHER. Do not just note issues — FIX them immediately.
@@ -734,9 +1099,15 @@ test scenario → find issue (bug OR UX problem) → screenshot broken state
### Problem: Frontend shows cookie banner blocking interaction
**Fix:** `agent-browser click 'text=Accept All'` before other interactions.
### Problem: Container loses npm packages after rebuild
**Cause:** `docker compose up --build` rebuilds the image, losing runtime installs.
**Fix:** Add packages to the Dockerfile instead of installing at runtime.
### Problem: Claude CLI not found in copilot_executor container
**Symptom:** Copilot logs say `claude: command not found` or similar when starting an SDK turn.
**Cause:** Image was built without `poetry install` (stale base layer, or Dockerfile bypass). The SDK CLI ships inside the `claude_agent_sdk` Poetry dep — it is NOT an npm package.
**Fix:** Rebuild the image cleanly: `docker compose build --no-cache copilot_executor && docker compose up -d copilot_executor`. Do NOT `docker exec ... npm install -g @anthropic-ai/claude-code` — that is outdated guidance and will pollute the container with a second CLI that the SDK won't use.
### Problem: agent-browser screenshot hangs / times out
**Symptom:** `agent-browser screenshot` exits with code 124 even on `about:blank`.
**Cause:** Stuck CDP connection or Chromium process tree. Seen on macOS when a prior `/pr-test` left a zombie Chrome for Testing.
**Fix:** `pkill -9 -f "agent-browser|chromium|Chrome for Testing" && sleep 2`, then reopen the browser with a fresh `--session-name`. If still failing, verify via `agent-browser eval` + `agent-browser snapshot` (DOM state) instead of relying on PNGs — the feature under test is the same.
### Problem: Services not starting after `docker compose up`
**Fix:** Wait and check health: `docker compose ps`. Common cause: migration hasn't finished. Check: `docker logs autogpt_platform-migrate-1 2>&1 | tail -5`. If supabase-db isn't healthy: `docker restart supabase-db && sleep 10`.

View File

@@ -0,0 +1,225 @@
---
name: write-frontend-tests
description: "Analyze the current branch diff against dev, plan integration tests for changed frontend pages/components, and write them. TRIGGER when user asks to write frontend tests, add test coverage, or 'write tests for my changes'."
user-invocable: true
args: "[base branch] — defaults to dev. Optionally pass a specific base branch to diff against."
metadata:
author: autogpt-team
version: "1.0.0"
---
# Write Frontend Tests
Analyze the current branch's frontend changes, plan integration tests, and write them.
## References
Before writing any tests, read the testing rules and conventions:
- `autogpt_platform/frontend/TESTING.md` — testing strategy, file locations, examples
- `autogpt_platform/frontend/src/tests/AGENTS.md` — detailed testing rules, MSW patterns, decision flowchart
- `autogpt_platform/frontend/src/tests/integrations/test-utils.tsx` — custom render with providers
- `autogpt_platform/frontend/src/tests/integrations/vitest.setup.tsx` — MSW server setup
## Step 1: Identify changed frontend files
```bash
BASE_BRANCH="${ARGUMENTS:-dev}"
cd autogpt_platform/frontend
# Get changed frontend files (excluding generated, config, and test files)
git diff "$BASE_BRANCH"...HEAD --name-only -- src/ \
| grep -v '__generated__' \
| grep -v '__tests__' \
| grep -v '\.test\.' \
| grep -v '\.stories\.' \
| grep -v '\.spec\.'
```
Also read the diff to understand what changed:
```bash
git diff "$BASE_BRANCH"...HEAD --stat -- src/
git diff "$BASE_BRANCH"...HEAD -- src/ | head -500
```
## Step 2: Categorize changes and find test targets
For each changed file, determine:
1. **Is it a page?** (`page.tsx`) — these are the primary test targets
2. **Is it a hook?** (`use*.ts`) — test via the page/component that uses it; avoid direct `renderHook()` tests unless it is a shared reusable hook with standalone business logic
3. **Is it a component?** (`.tsx` in `components/`) — test via the parent page unless it's complex enough to warrant isolation
4. **Is it a helper?** (`helpers.ts`, `utils.ts`) — unit test directly if pure logic
**Priority order:**
1. Pages with new/changed data fetching or user interactions
2. Components with complex internal logic (modals, forms, wizards)
3. Shared hooks with standalone business logic when UI-level coverage is impractical
4. Pure helper functions
Skip: styling-only changes, type-only changes, config changes.
## Step 3: Check for existing tests
For each test target, check if tests already exist:
```bash
# For a page at src/app/(platform)/library/page.tsx
ls src/app/\(platform\)/library/__tests__/ 2>/dev/null
# For a component at src/app/(platform)/library/components/AgentCard/AgentCard.tsx
ls src/app/\(platform\)/library/components/AgentCard/__tests__/ 2>/dev/null
```
Note which targets have no tests (need new files) vs which have tests that need updating.
## Step 4: Identify API endpoints used
For each test target, find which API hooks are used:
```bash
# Find generated API hook imports in the changed files
grep -rn 'from.*__generated__/endpoints' src/app/\(platform\)/library/
grep -rn 'use[A-Z].*V[12]' src/app/\(platform\)/library/
```
For each API hook found, locate the corresponding MSW handler:
```bash
# If the page uses useGetV2ListLibraryAgents, find its MSW handlers
grep -rn 'getGetV2ListLibraryAgents.*Handler' src/app/api/__generated__/endpoints/library/library.msw.ts
```
List every MSW handler you will need (200 for happy path, 4xx for error paths).
## Step 5: Write the test plan
Before writing code, output a plan as a numbered list:
```
Test plan for [branch name]:
1. src/app/(platform)/library/__tests__/main.test.tsx (NEW)
- Renders page with agent list (MSW 200)
- Shows loading state
- Shows error state (MSW 422)
- Handles empty agent list
2. src/app/(platform)/library/__tests__/search.test.tsx (NEW)
- Filters agents by search query
- Shows no results message
- Clears search
3. src/app/(platform)/library/components/AgentCard/__tests__/AgentCard.test.tsx (UPDATE)
- Add test for new "duplicate" action
```
Present this plan to the user. Wait for confirmation before proceeding. If the user has feedback, adjust the plan.
## Step 6: Write the tests
For each test file in the plan, follow these conventions:
### File structure
```tsx
import { render, screen, waitFor } from "@/tests/integrations/test-utils";
import { server } from "@/mocks/mock-server";
// Import MSW handlers for endpoints the page uses
import {
getGetV2ListLibraryAgentsMockHandler200,
getGetV2ListLibraryAgentsMockHandler422,
} from "@/app/api/__generated__/endpoints/library/library.msw";
// Import the component under test
import LibraryPage from "../page";
describe("LibraryPage", () => {
test("renders agent list from API", async () => {
server.use(getGetV2ListLibraryAgentsMockHandler200());
render(<LibraryPage />);
expect(await screen.findByText(/my agents/i)).toBeDefined();
});
test("shows error state on API failure", async () => {
server.use(getGetV2ListLibraryAgentsMockHandler422());
render(<LibraryPage />);
expect(await screen.findByText(/error/i)).toBeDefined();
});
});
```
### Rules
- Use `render()` from `@/tests/integrations/test-utils` (NOT from `@testing-library/react` directly)
- Use `server.use()` to set up MSW handlers BEFORE rendering
- Use `findBy*` (async) for elements that appear after data fetching — NOT `getBy*`
- Use `getBy*` only for elements that are immediately present in the DOM
- Use `screen` queries — do NOT destructure from `render()`
- Use `waitFor` when asserting side effects or state changes after interactions
- Import `fireEvent` or `userEvent` from the test-utils for interactions
- Do NOT mock internal hooks or functions — mock at the API boundary via MSW
- Prefer Orval-generated MSW handlers and response builders over hand-built API response objects
- Do NOT use `act()` manually — `render` and `fireEvent` handle it
- Keep tests focused: one behavior per test
- Use descriptive test names that read like sentences
### Test location
```
# For pages: __tests__/ next to page.tsx
src/app/(platform)/library/__tests__/main.test.tsx
# For complex standalone components: __tests__/ inside component folder
src/app/(platform)/library/components/AgentCard/__tests__/AgentCard.test.tsx
# For pure helpers: co-located .test.ts
src/app/(platform)/library/helpers.test.ts
```
### Custom MSW overrides
When the auto-generated faker data is not enough, override with specific data:
```tsx
import { http, HttpResponse } from "msw";
server.use(
http.get("http://localhost:3000/api/proxy/api/v2/library/agents", () => {
return HttpResponse.json({
agents: [{ id: "1", name: "Test Agent", description: "A test agent" }],
pagination: { total_items: 1, total_pages: 1, page: 1, page_size: 10 },
});
}),
);
```
Use the proxy URL pattern: `http://localhost:3000/api/proxy/api/v{version}/{path}` — this matches the MSW base URL configured in `orval.config.ts`.
## Step 7: Run and verify
After writing all tests:
```bash
cd autogpt_platform/frontend
pnpm test:unit --reporter=verbose
```
If tests fail:
1. Read the error output carefully
2. Fix the test (not the source code, unless there is a genuine bug)
3. Re-run until all pass
Then run the full checks:
```bash
pnpm format
pnpm lint
pnpm types
```

View File

@@ -6,11 +6,19 @@ on:
paths:
- '.github/workflows/classic-autogpt-ci.yml'
- 'classic/original_autogpt/**'
- 'classic/direct_benchmark/**'
- 'classic/forge/**'
- 'classic/pyproject.toml'
- 'classic/poetry.lock'
pull_request:
branches: [ master, dev, release-* ]
paths:
- '.github/workflows/classic-autogpt-ci.yml'
- 'classic/original_autogpt/**'
- 'classic/direct_benchmark/**'
- 'classic/forge/**'
- 'classic/pyproject.toml'
- 'classic/poetry.lock'
concurrency:
group: ${{ format('classic-autogpt-ci-{0}', github.head_ref && format('{0}-{1}', github.event_name, github.event.pull_request.number) || github.sha) }}
@@ -19,47 +27,22 @@ concurrency:
defaults:
run:
shell: bash
working-directory: classic/original_autogpt
working-directory: classic
jobs:
test:
permissions:
contents: read
timeout-minutes: 30
strategy:
fail-fast: false
matrix:
python-version: ["3.10"]
platform-os: [ubuntu, macos, macos-arm64, windows]
runs-on: ${{ matrix.platform-os != 'macos-arm64' && format('{0}-latest', matrix.platform-os) || 'macos-14' }}
runs-on: ubuntu-latest
steps:
# Quite slow on macOS (2~4 minutes to set up Docker)
# - name: Set up Docker (macOS)
# if: runner.os == 'macOS'
# uses: crazy-max/ghaction-setup-docker@v3
- name: Start MinIO service (Linux)
if: runner.os == 'Linux'
- name: Start MinIO service
working-directory: '.'
run: |
docker pull minio/minio:edge-cicd
docker run -d -p 9000:9000 minio/minio:edge-cicd
- name: Start MinIO service (macOS)
if: runner.os == 'macOS'
working-directory: ${{ runner.temp }}
run: |
brew install minio/stable/minio
mkdir data
minio server ./data &
# No MinIO on Windows:
# - Windows doesn't support running Linux Docker containers
# - It doesn't seem possible to start background processes on Windows. They are
# killed after the step returns.
# See: https://github.com/actions/runner/issues/598#issuecomment-2011890429
- name: Checkout repository
uses: actions/checkout@v4
with:
@@ -71,41 +54,23 @@ jobs:
git config --global user.name "Auto-GPT-Bot"
git config --global user.email "github-bot@agpt.co"
- name: Set up Python ${{ matrix.python-version }}
- name: Set up Python 3.12
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
python-version: "3.12"
- id: get_date
name: Get date
run: echo "date=$(date +'%Y-%m-%d')" >> $GITHUB_OUTPUT
- name: Set up Python dependency cache
# On Windows, unpacking cached dependencies takes longer than just installing them
if: runner.os != 'Windows'
uses: actions/cache@v4
with:
path: ${{ runner.os == 'macOS' && '~/Library/Caches/pypoetry' || '~/.cache/pypoetry' }}
key: poetry-${{ runner.os }}-${{ hashFiles('classic/original_autogpt/poetry.lock') }}
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('classic/poetry.lock') }}
- name: Install Poetry (Unix)
if: runner.os != 'Windows'
run: |
curl -sSL https://install.python-poetry.org | python3 -
if [ "${{ runner.os }}" = "macOS" ]; then
PATH="$HOME/.local/bin:$PATH"
echo "$HOME/.local/bin" >> $GITHUB_PATH
fi
- name: Install Poetry (Windows)
if: runner.os == 'Windows'
shell: pwsh
run: |
(Invoke-WebRequest -Uri https://install.python-poetry.org -UseBasicParsing).Content | python -
$env:PATH += ";$env:APPDATA\Python\Scripts"
echo "$env:APPDATA\Python\Scripts" >> $env:GITHUB_PATH
- name: Install Poetry
run: curl -sSL https://install.python-poetry.org | python3 -
- name: Install Python dependencies
run: poetry install
@@ -116,12 +81,13 @@ jobs:
--cov=autogpt --cov-branch --cov-report term-missing --cov-report xml \
--numprocesses=logical --durations=10 \
--junitxml=junit.xml -o junit_family=legacy \
tests/unit tests/integration
original_autogpt/tests/unit original_autogpt/tests/integration
env:
CI: true
PLAIN_OUTPUT: True
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
S3_ENDPOINT_URL: ${{ runner.os != 'Windows' && 'http://127.0.0.1:9000' || '' }}
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
S3_ENDPOINT_URL: http://127.0.0.1:9000
AWS_ACCESS_KEY_ID: minioadmin
AWS_SECRET_ACCESS_KEY: minioadmin
@@ -135,11 +101,11 @@ jobs:
uses: codecov/codecov-action@v5
with:
token: ${{ secrets.CODECOV_TOKEN }}
flags: autogpt-agent,${{ runner.os }}
flags: autogpt-agent
- name: Upload logs to artifact
if: always()
uses: actions/upload-artifact@v4
with:
name: test-logs
path: classic/original_autogpt/logs/
path: classic/logs/

View File

@@ -148,7 +148,7 @@ jobs:
--entrypoint poetry ${{ env.IMAGE_NAME }} run \
pytest -v --cov=autogpt --cov-branch --cov-report term-missing \
--numprocesses=4 --durations=10 \
tests/unit tests/integration 2>&1 | tee test_output.txt
original_autogpt/tests/unit original_autogpt/tests/integration 2>&1 | tee test_output.txt
test_failure=${PIPESTATUS[0]}

View File

@@ -10,10 +10,9 @@ on:
- '.github/workflows/classic-autogpts-ci.yml'
- 'classic/original_autogpt/**'
- 'classic/forge/**'
- 'classic/benchmark/**'
- 'classic/run'
- 'classic/cli.py'
- 'classic/setup.py'
- 'classic/direct_benchmark/**'
- 'classic/pyproject.toml'
- 'classic/poetry.lock'
- '!**/*.md'
pull_request:
branches: [ master, dev, release-* ]
@@ -21,10 +20,9 @@ on:
- '.github/workflows/classic-autogpts-ci.yml'
- 'classic/original_autogpt/**'
- 'classic/forge/**'
- 'classic/benchmark/**'
- 'classic/run'
- 'classic/cli.py'
- 'classic/setup.py'
- 'classic/direct_benchmark/**'
- 'classic/pyproject.toml'
- 'classic/poetry.lock'
- '!**/*.md'
defaults:
@@ -35,13 +33,9 @@ defaults:
jobs:
serve-agent-protocol:
runs-on: ubuntu-latest
strategy:
matrix:
agent-name: [ original_autogpt ]
fail-fast: false
timeout-minutes: 20
env:
min-python-version: '3.10'
min-python-version: '3.12'
steps:
- name: Checkout repository
uses: actions/checkout@v4
@@ -55,22 +49,22 @@ jobs:
python-version: ${{ env.min-python-version }}
- name: Install Poetry
working-directory: ./classic/${{ matrix.agent-name }}/
run: |
curl -sSL https://install.python-poetry.org | python -
- name: Run regression tests
- name: Install dependencies
run: poetry install
- name: Run smoke tests with direct-benchmark
run: |
./run agent start ${{ matrix.agent-name }}
cd ${{ matrix.agent-name }}
poetry run agbenchmark --mock --test=BasicRetrieval --test=Battleship --test=WebArenaTask_0
poetry run agbenchmark --test=WriteFile
poetry run direct-benchmark run \
--strategies one_shot \
--models claude \
--tests ReadFile,WriteFile \
--json
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
AGENT_NAME: ${{ matrix.agent-name }}
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
REQUESTS_CA_BUNDLE: /etc/ssl/certs/ca-certificates.crt
HELICONE_CACHE_ENABLED: false
HELICONE_PROPERTY_AGENT: ${{ matrix.agent-name }}
REPORTS_FOLDER: ${{ format('../../reports/{0}', matrix.agent-name) }}
TELEMETRY_ENVIRONMENT: autogpt-ci
TELEMETRY_OPT_IN: ${{ github.ref_name == 'master' }}
NONINTERACTIVE_MODE: "true"
CI: true

View File

@@ -1,18 +1,24 @@
name: Classic - AGBenchmark CI
name: Classic - Direct Benchmark CI
on:
push:
branches: [ master, dev, ci-test* ]
paths:
- 'classic/benchmark/**'
- '!classic/benchmark/reports/**'
- 'classic/direct_benchmark/**'
- 'classic/original_autogpt/**'
- 'classic/forge/**'
- .github/workflows/classic-benchmark-ci.yml
- 'classic/pyproject.toml'
- 'classic/poetry.lock'
pull_request:
branches: [ master, dev, release-* ]
paths:
- 'classic/benchmark/**'
- '!classic/benchmark/reports/**'
- 'classic/direct_benchmark/**'
- 'classic/original_autogpt/**'
- 'classic/forge/**'
- .github/workflows/classic-benchmark-ci.yml
- 'classic/pyproject.toml'
- 'classic/poetry.lock'
concurrency:
group: ${{ format('benchmark-ci-{0}', github.head_ref && format('{0}-{1}', github.event_name, github.event.pull_request.number) || github.sha) }}
@@ -23,95 +29,16 @@ defaults:
shell: bash
env:
min-python-version: '3.10'
min-python-version: '3.12'
jobs:
test:
permissions:
contents: read
benchmark-tests:
runs-on: ubuntu-latest
timeout-minutes: 30
strategy:
fail-fast: false
matrix:
python-version: ["3.10"]
platform-os: [ubuntu, macos, macos-arm64, windows]
runs-on: ${{ matrix.platform-os != 'macos-arm64' && format('{0}-latest', matrix.platform-os) || 'macos-14' }}
defaults:
run:
shell: bash
working-directory: classic/benchmark
steps:
- name: Checkout repository
uses: actions/checkout@v4
with:
fetch-depth: 0
submodules: true
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
- name: Set up Python dependency cache
# On Windows, unpacking cached dependencies takes longer than just installing them
if: runner.os != 'Windows'
uses: actions/cache@v4
with:
path: ${{ runner.os == 'macOS' && '~/Library/Caches/pypoetry' || '~/.cache/pypoetry' }}
key: poetry-${{ runner.os }}-${{ hashFiles('classic/benchmark/poetry.lock') }}
- name: Install Poetry (Unix)
if: runner.os != 'Windows'
run: |
curl -sSL https://install.python-poetry.org | python3 -
if [ "${{ runner.os }}" = "macOS" ]; then
PATH="$HOME/.local/bin:$PATH"
echo "$HOME/.local/bin" >> $GITHUB_PATH
fi
- name: Install Poetry (Windows)
if: runner.os == 'Windows'
shell: pwsh
run: |
(Invoke-WebRequest -Uri https://install.python-poetry.org -UseBasicParsing).Content | python -
$env:PATH += ";$env:APPDATA\Python\Scripts"
echo "$env:APPDATA\Python\Scripts" >> $env:GITHUB_PATH
- name: Install Python dependencies
run: poetry install
- name: Run pytest with coverage
run: |
poetry run pytest -vv \
--cov=agbenchmark --cov-branch --cov-report term-missing --cov-report xml \
--durations=10 \
--junitxml=junit.xml -o junit_family=legacy \
tests
env:
CI: true
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
- name: Upload test results to Codecov
if: ${{ !cancelled() }} # Run even if tests fail
uses: codecov/test-results-action@v1
with:
token: ${{ secrets.CODECOV_TOKEN }}
- name: Upload coverage reports to Codecov
uses: codecov/codecov-action@v5
with:
token: ${{ secrets.CODECOV_TOKEN }}
flags: agbenchmark,${{ runner.os }}
self-test-with-agent:
runs-on: ubuntu-latest
strategy:
matrix:
agent-name: [forge]
fail-fast: false
timeout-minutes: 20
working-directory: classic
steps:
- name: Checkout repository
uses: actions/checkout@v4
@@ -124,53 +51,120 @@ jobs:
with:
python-version: ${{ env.min-python-version }}
- name: Set up Python dependency cache
uses: actions/cache@v4
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('classic/poetry.lock') }}
- name: Install Poetry
run: |
curl -sSL https://install.python-poetry.org | python -
curl -sSL https://install.python-poetry.org | python3 -
- name: Install dependencies
run: poetry install
- name: Run basic benchmark tests
run: |
echo "Testing ReadFile challenge with one_shot strategy..."
poetry run direct-benchmark run \
--fresh \
--strategies one_shot \
--models claude \
--tests ReadFile \
--json
echo "Testing WriteFile challenge..."
poetry run direct-benchmark run \
--fresh \
--strategies one_shot \
--models claude \
--tests WriteFile \
--json
env:
CI: true
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
NONINTERACTIVE_MODE: "true"
- name: Test category filtering
run: |
echo "Testing coding category..."
poetry run direct-benchmark run \
--fresh \
--strategies one_shot \
--models claude \
--categories coding \
--tests ReadFile,WriteFile \
--json
env:
CI: true
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
NONINTERACTIVE_MODE: "true"
- name: Test multiple strategies
run: |
echo "Testing multiple strategies..."
poetry run direct-benchmark run \
--fresh \
--strategies one_shot,plan_execute \
--models claude \
--tests ReadFile \
--parallel 2 \
--json
env:
CI: true
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
NONINTERACTIVE_MODE: "true"
# Run regression tests on maintain challenges
regression-tests:
runs-on: ubuntu-latest
timeout-minutes: 45
if: github.ref == 'refs/heads/master' || github.ref == 'refs/heads/dev'
defaults:
run:
shell: bash
working-directory: classic
steps:
- name: Checkout repository
uses: actions/checkout@v4
with:
fetch-depth: 0
submodules: true
- name: Set up Python ${{ env.min-python-version }}
uses: actions/setup-python@v5
with:
python-version: ${{ env.min-python-version }}
- name: Set up Python dependency cache
uses: actions/cache@v4
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('classic/poetry.lock') }}
- name: Install Poetry
run: |
curl -sSL https://install.python-poetry.org | python3 -
- name: Install dependencies
run: poetry install
- name: Run regression tests
working-directory: classic
run: |
./run agent start ${{ matrix.agent-name }}
cd ${{ matrix.agent-name }}
set +e # Ignore non-zero exit codes and continue execution
echo "Running the following command: poetry run agbenchmark --maintain --mock"
poetry run agbenchmark --maintain --mock
EXIT_CODE=$?
set -e # Stop ignoring non-zero exit codes
# Check if the exit code was 5, and if so, exit with 0 instead
if [ $EXIT_CODE -eq 5 ]; then
echo "regression_tests.json is empty."
fi
echo "Running the following command: poetry run agbenchmark --mock"
poetry run agbenchmark --mock
echo "Running the following command: poetry run agbenchmark --mock --category=data"
poetry run agbenchmark --mock --category=data
echo "Running the following command: poetry run agbenchmark --mock --category=coding"
poetry run agbenchmark --mock --category=coding
# echo "Running the following command: poetry run agbenchmark --test=WriteFile"
# poetry run agbenchmark --test=WriteFile
cd ../benchmark
poetry install
echo "Adding the BUILD_SKILL_TREE environment variable. This will attempt to add new elements in the skill tree. If new elements are added, the CI fails because they should have been pushed"
export BUILD_SKILL_TREE=true
# poetry run agbenchmark --mock
# CHANGED=$(git diff --name-only | grep -E '(agbenchmark/challenges)|(../classic/frontend/assets)') || echo "No diffs"
# if [ ! -z "$CHANGED" ]; then
# echo "There are unstaged changes please run agbenchmark and commit those changes since they are needed."
# echo "$CHANGED"
# exit 1
# else
# echo "No unstaged changes."
# fi
echo "Running regression tests (previously beaten challenges)..."
poetry run direct-benchmark run \
--fresh \
--strategies one_shot \
--models claude \
--maintain \
--parallel 4 \
--json
env:
CI: true
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
TELEMETRY_ENVIRONMENT: autogpt-benchmark-ci
TELEMETRY_OPT_IN: ${{ github.ref_name == 'master' }}
NONINTERACTIVE_MODE: "true"

View File

@@ -6,13 +6,15 @@ on:
paths:
- '.github/workflows/classic-forge-ci.yml'
- 'classic/forge/**'
- '!classic/forge/tests/vcr_cassettes'
- 'classic/pyproject.toml'
- 'classic/poetry.lock'
pull_request:
branches: [ master, dev, release-* ]
paths:
- '.github/workflows/classic-forge-ci.yml'
- 'classic/forge/**'
- '!classic/forge/tests/vcr_cassettes'
- 'classic/pyproject.toml'
- 'classic/poetry.lock'
concurrency:
group: ${{ format('forge-ci-{0}', github.head_ref && format('{0}-{1}', github.event_name, github.event.pull_request.number) || github.sha) }}
@@ -21,131 +23,60 @@ concurrency:
defaults:
run:
shell: bash
working-directory: classic/forge
working-directory: classic
jobs:
test:
permissions:
contents: read
timeout-minutes: 30
strategy:
fail-fast: false
matrix:
python-version: ["3.10"]
platform-os: [ubuntu, macos, macos-arm64, windows]
runs-on: ${{ matrix.platform-os != 'macos-arm64' && format('{0}-latest', matrix.platform-os) || 'macos-14' }}
runs-on: ubuntu-latest
steps:
# Quite slow on macOS (2~4 minutes to set up Docker)
# - name: Set up Docker (macOS)
# if: runner.os == 'macOS'
# uses: crazy-max/ghaction-setup-docker@v3
- name: Start MinIO service (Linux)
if: runner.os == 'Linux'
- name: Start MinIO service
working-directory: '.'
run: |
docker pull minio/minio:edge-cicd
docker run -d -p 9000:9000 minio/minio:edge-cicd
- name: Start MinIO service (macOS)
if: runner.os == 'macOS'
working-directory: ${{ runner.temp }}
run: |
brew install minio/stable/minio
mkdir data
minio server ./data &
# No MinIO on Windows:
# - Windows doesn't support running Linux Docker containers
# - It doesn't seem possible to start background processes on Windows. They are
# killed after the step returns.
# See: https://github.com/actions/runner/issues/598#issuecomment-2011890429
- name: Checkout repository
uses: actions/checkout@v4
with:
fetch-depth: 0
submodules: true
- name: Checkout cassettes
if: ${{ startsWith(github.event_name, 'pull_request') }}
env:
PR_BASE: ${{ github.event.pull_request.base.ref }}
PR_BRANCH: ${{ github.event.pull_request.head.ref }}
PR_AUTHOR: ${{ github.event.pull_request.user.login }}
run: |
cassette_branch="${PR_AUTHOR}-${PR_BRANCH}"
cassette_base_branch="${PR_BASE}"
cd tests/vcr_cassettes
if ! git ls-remote --exit-code --heads origin $cassette_base_branch ; then
cassette_base_branch="master"
fi
if git ls-remote --exit-code --heads origin $cassette_branch ; then
git fetch origin $cassette_branch
git fetch origin $cassette_base_branch
git checkout $cassette_branch
# Pick non-conflicting cassette updates from the base branch
git merge --no-commit --strategy-option=ours origin/$cassette_base_branch
echo "Using cassettes from mirror branch '$cassette_branch'," \
"synced to upstream branch '$cassette_base_branch'."
else
git checkout -b $cassette_branch
echo "Branch '$cassette_branch' does not exist in cassette submodule." \
"Using cassettes from '$cassette_base_branch'."
fi
- name: Set up Python ${{ matrix.python-version }}
- name: Set up Python 3.12
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
python-version: "3.12"
- name: Set up Python dependency cache
# On Windows, unpacking cached dependencies takes longer than just installing them
if: runner.os != 'Windows'
uses: actions/cache@v4
with:
path: ${{ runner.os == 'macOS' && '~/Library/Caches/pypoetry' || '~/.cache/pypoetry' }}
key: poetry-${{ runner.os }}-${{ hashFiles('classic/forge/poetry.lock') }}
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('classic/poetry.lock') }}
- name: Install Poetry (Unix)
if: runner.os != 'Windows'
run: |
curl -sSL https://install.python-poetry.org | python3 -
if [ "${{ runner.os }}" = "macOS" ]; then
PATH="$HOME/.local/bin:$PATH"
echo "$HOME/.local/bin" >> $GITHUB_PATH
fi
- name: Install Poetry (Windows)
if: runner.os == 'Windows'
shell: pwsh
run: |
(Invoke-WebRequest -Uri https://install.python-poetry.org -UseBasicParsing).Content | python -
$env:PATH += ";$env:APPDATA\Python\Scripts"
echo "$env:APPDATA\Python\Scripts" >> $env:GITHUB_PATH
- name: Install Poetry
run: curl -sSL https://install.python-poetry.org | python3 -
- name: Install Python dependencies
run: poetry install
- name: Install Playwright browsers
run: poetry run playwright install chromium
- name: Run pytest with coverage
run: |
poetry run pytest -vv \
--cov=forge --cov-branch --cov-report term-missing --cov-report xml \
--durations=10 \
--junitxml=junit.xml -o junit_family=legacy \
forge
forge/forge forge/tests
env:
CI: true
PLAIN_OUTPUT: True
# API keys - tests that need these will skip if not available
# Secrets are not available to fork PRs (GitHub security feature)
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
S3_ENDPOINT_URL: ${{ runner.os != 'Windows' && 'http://127.0.0.1:9000' || '' }}
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
S3_ENDPOINT_URL: http://127.0.0.1:9000
AWS_ACCESS_KEY_ID: minioadmin
AWS_SECRET_ACCESS_KEY: minioadmin
@@ -159,85 +90,11 @@ jobs:
uses: codecov/codecov-action@v5
with:
token: ${{ secrets.CODECOV_TOKEN }}
flags: forge,${{ runner.os }}
- id: setup_git_auth
name: Set up git token authentication
# Cassettes may be pushed even when tests fail
if: success() || failure()
run: |
config_key="http.${{ github.server_url }}/.extraheader"
if [ "${{ runner.os }}" = 'macOS' ]; then
base64_pat=$(echo -n "pat:${{ secrets.PAT_REVIEW }}" | base64)
else
base64_pat=$(echo -n "pat:${{ secrets.PAT_REVIEW }}" | base64 -w0)
fi
git config "$config_key" \
"Authorization: Basic $base64_pat"
cd tests/vcr_cassettes
git config "$config_key" \
"Authorization: Basic $base64_pat"
echo "config_key=$config_key" >> $GITHUB_OUTPUT
- id: push_cassettes
name: Push updated cassettes
# For pull requests, push updated cassettes even when tests fail
if: github.event_name == 'push' || (! github.event.pull_request.head.repo.fork && (success() || failure()))
env:
PR_BRANCH: ${{ github.event.pull_request.head.ref }}
PR_AUTHOR: ${{ github.event.pull_request.user.login }}
run: |
if [ "${{ startsWith(github.event_name, 'pull_request') }}" = "true" ]; then
is_pull_request=true
cassette_branch="${PR_AUTHOR}-${PR_BRANCH}"
else
cassette_branch="${{ github.ref_name }}"
fi
cd tests/vcr_cassettes
# Commit & push changes to cassettes if any
if ! git diff --quiet; then
git add .
git commit -m "Auto-update cassettes"
git push origin HEAD:$cassette_branch
if [ ! $is_pull_request ]; then
cd ../..
git add tests/vcr_cassettes
git commit -m "Update cassette submodule"
git push origin HEAD:$cassette_branch
fi
echo "updated=true" >> $GITHUB_OUTPUT
else
echo "updated=false" >> $GITHUB_OUTPUT
echo "No cassette changes to commit"
fi
- name: Post Set up git token auth
if: steps.setup_git_auth.outcome == 'success'
run: |
git config --unset-all '${{ steps.setup_git_auth.outputs.config_key }}'
git submodule foreach git config --unset-all '${{ steps.setup_git_auth.outputs.config_key }}'
- name: Apply "behaviour change" label and comment on PR
if: ${{ startsWith(github.event_name, 'pull_request') }}
run: |
PR_NUMBER="${{ github.event.pull_request.number }}"
TOKEN="${{ secrets.PAT_REVIEW }}"
REPO="${{ github.repository }}"
if [[ "${{ steps.push_cassettes.outputs.updated }}" == "true" ]]; then
echo "Adding label and comment..."
echo $TOKEN | gh auth login --with-token
gh issue edit $PR_NUMBER --add-label "behaviour change"
gh issue comment $PR_NUMBER --body "You changed AutoGPT's behaviour on ${{ runner.os }}. The cassettes have been updated and will be merged to the submodule when this Pull Request gets merged."
fi
flags: forge
- name: Upload logs to artifact
if: always()
uses: actions/upload-artifact@v4
with:
name: test-logs
path: classic/forge/logs/
path: classic/logs/

View File

@@ -1,60 +0,0 @@
name: Classic - Frontend CI/CD
on:
push:
branches:
- master
- dev
- 'ci-test*' # This will match any branch that starts with "ci-test"
paths:
- 'classic/frontend/**'
- '.github/workflows/classic-frontend-ci.yml'
pull_request:
paths:
- 'classic/frontend/**'
- '.github/workflows/classic-frontend-ci.yml'
jobs:
build:
permissions:
contents: write
pull-requests: write
runs-on: ubuntu-latest
env:
BUILD_BRANCH: ${{ format('classic-frontend-build/{0}', github.ref_name) }}
steps:
- name: Checkout Repo
uses: actions/checkout@v4
- name: Setup Flutter
uses: subosito/flutter-action@v2
with:
flutter-version: '3.13.2'
- name: Build Flutter to Web
run: |
cd classic/frontend
flutter build web --base-href /app/
# - name: Commit and Push to ${{ env.BUILD_BRANCH }}
# if: github.event_name == 'push'
# run: |
# git config --local user.email "action@github.com"
# git config --local user.name "GitHub Action"
# git add classic/frontend/build/web
# git checkout -B ${{ env.BUILD_BRANCH }}
# git commit -m "Update frontend build to ${GITHUB_SHA:0:7}" -a
# git push -f origin ${{ env.BUILD_BRANCH }}
- name: Create PR ${{ env.BUILD_BRANCH }} -> ${{ github.ref_name }}
if: github.event_name == 'push'
uses: peter-evans/create-pull-request@v8
with:
add-paths: classic/frontend/build/web
base: ${{ github.ref_name }}
branch: ${{ env.BUILD_BRANCH }}
delete-branch: true
title: "Update frontend build in `${{ github.ref_name }}`"
body: "This PR updates the frontend build based on commit ${{ github.sha }}."
commit-message: "Update frontend build based on commit ${{ github.sha }}"

View File

@@ -7,7 +7,9 @@ on:
- '.github/workflows/classic-python-checks-ci.yml'
- 'classic/original_autogpt/**'
- 'classic/forge/**'
- 'classic/benchmark/**'
- 'classic/direct_benchmark/**'
- 'classic/pyproject.toml'
- 'classic/poetry.lock'
- '**.py'
- '!classic/forge/tests/vcr_cassettes'
pull_request:
@@ -16,7 +18,9 @@ on:
- '.github/workflows/classic-python-checks-ci.yml'
- 'classic/original_autogpt/**'
- 'classic/forge/**'
- 'classic/benchmark/**'
- 'classic/direct_benchmark/**'
- 'classic/pyproject.toml'
- 'classic/poetry.lock'
- '**.py'
- '!classic/forge/tests/vcr_cassettes'
@@ -27,44 +31,13 @@ concurrency:
defaults:
run:
shell: bash
working-directory: classic
jobs:
get-changed-parts:
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v4
- id: changes-in
name: Determine affected subprojects
uses: dorny/paths-filter@v3
with:
filters: |
original_autogpt:
- classic/original_autogpt/autogpt/**
- classic/original_autogpt/tests/**
- classic/original_autogpt/poetry.lock
forge:
- classic/forge/forge/**
- classic/forge/tests/**
- classic/forge/poetry.lock
benchmark:
- classic/benchmark/agbenchmark/**
- classic/benchmark/tests/**
- classic/benchmark/poetry.lock
outputs:
changed-parts: ${{ steps.changes-in.outputs.changes }}
lint:
needs: get-changed-parts
runs-on: ubuntu-latest
env:
min-python-version: "3.10"
strategy:
matrix:
sub-package: ${{ fromJson(needs.get-changed-parts.outputs.changed-parts) }}
fail-fast: false
min-python-version: "3.12"
steps:
- name: Checkout repository
@@ -81,42 +54,31 @@ jobs:
uses: actions/cache@v4
with:
path: ~/.cache/pypoetry
key: ${{ runner.os }}-poetry-${{ hashFiles(format('{0}/poetry.lock', matrix.sub-package)) }}
key: ${{ runner.os }}-poetry-${{ hashFiles('classic/poetry.lock') }}
- name: Install Poetry
run: curl -sSL https://install.python-poetry.org | python3 -
# Install dependencies
- name: Install Python dependencies
run: poetry -C classic/${{ matrix.sub-package }} install
run: poetry install
# Lint
- name: Lint (isort)
run: poetry run isort --check .
working-directory: classic/${{ matrix.sub-package }}
- name: Lint (Black)
if: success() || failure()
run: poetry run black --check .
working-directory: classic/${{ matrix.sub-package }}
- name: Lint (Flake8)
if: success() || failure()
run: poetry run flake8 .
working-directory: classic/${{ matrix.sub-package }}
types:
needs: get-changed-parts
runs-on: ubuntu-latest
env:
min-python-version: "3.10"
strategy:
matrix:
sub-package: ${{ fromJson(needs.get-changed-parts.outputs.changed-parts) }}
fail-fast: false
min-python-version: "3.12"
steps:
- name: Checkout repository
@@ -133,19 +95,16 @@ jobs:
uses: actions/cache@v4
with:
path: ~/.cache/pypoetry
key: ${{ runner.os }}-poetry-${{ hashFiles(format('{0}/poetry.lock', matrix.sub-package)) }}
key: ${{ runner.os }}-poetry-${{ hashFiles('classic/poetry.lock') }}
- name: Install Poetry
run: curl -sSL https://install.python-poetry.org | python3 -
# Install dependencies
- name: Install Python dependencies
run: poetry -C classic/${{ matrix.sub-package }} install
run: poetry install
# Typecheck
- name: Typecheck
if: success() || failure()
run: poetry run pyright
working-directory: classic/${{ matrix.sub-package }}

View File

@@ -119,10 +119,12 @@ jobs:
runs-on: ubuntu-latest
services:
redis:
image: redis:latest
ports:
- 6379:6379
# Redis is provisioned as a real 3-shard cluster below via docker
# run (see the "Start Redis Cluster" step). GHA services can't
# override the image CMD or stand up multi-container clusters, so
# that setup is inlined — it mirrors the topology of the local dev
# compose stack (autogpt_platform/docker-compose.platform.yml) and
# prod helm chart.
rabbitmq:
image: rabbitmq:4.1.4
ports:
@@ -166,6 +168,68 @@ jobs:
with:
python-version: ${{ matrix.python-version }}
- name: Start Redis Cluster (3 shards)
run: |
# 3-master Redis Cluster matching the local compose stack
# (autogpt_platform/docker-compose.platform.yml) and prod. Each
# shard runs in its own container on a dedicated bridge network,
# announces its compose-style hostname for intra-network clients,
# and publishes 1700N on the GHA host so tests can reach every
# shard via localhost. The backend's ``_address_remap`` rewrites
# every CLUSTER SLOTS reply to localhost:<announced-port>, which
# picks the right published port per shard.
#
# Not reusing docker-compose.platform.yml directly because compose
# validates the full file even when only some services are ``up``,
# and that file references services (db/kong/...) defined in a
# sibling compose file — pulling both in would needlessly couple
# CI to the full local-dev stack.
docker network create redis-cluster-ci
for i in 0 1 2; do
port=$((17000 + i))
bus=$((27000 + i))
docker run -d --name redis-$i --network redis-cluster-ci \
--network-alias redis-$i \
-p $port:$port \
redis:7 \
redis-server --port $port \
--cluster-enabled yes \
--cluster-config-file nodes.conf \
--cluster-node-timeout 5000 \
--cluster-require-full-coverage no \
--cluster-announce-hostname redis-$i \
--cluster-announce-port $port \
--cluster-announce-bus-port $bus \
--cluster-preferred-endpoint-type hostname
done
# Wait for each shard to accept commands.
for i in 0 1 2; do
port=$((17000 + i))
for _ in $(seq 1 30); do
docker exec redis-$i redis-cli -p $port ping 2>/dev/null | grep -q PONG && break
sleep 1
done
done
# Form the cluster from an init container on the same network so
# --cluster-preferred-endpoint-type hostname resolves redis-0/1/2.
docker run --rm --network redis-cluster-ci redis:7 \
redis-cli --cluster create \
redis-0:17000 redis-1:17001 redis-2:17002 \
--cluster-replicas 0 --cluster-yes
# Confirm convergence.
for _ in $(seq 1 30); do
state=$(docker exec redis-0 redis-cli -p 17000 cluster info | awk -F: '/^cluster_state:/ {print $2}' | tr -d '[:cntrl:]')
if [ "$state" = "ok" ]; then
echo "Redis Cluster ready (3 shards, state=ok)"
docker exec redis-0 redis-cli -p 17000 cluster nodes
exit 0
fi
sleep 1
done
echo "Redis Cluster failed to reach ok state" >&2
docker exec redis-0 redis-cli -p 17000 cluster info >&2 || true
exit 1
- name: Setup Supabase
uses: supabase/setup-cli@v1
with:
@@ -269,12 +333,14 @@ jobs:
DATABASE_URL: ${{ steps.supabase.outputs.DB_URL }}
DIRECT_URL: ${{ steps.supabase.outputs.DB_URL }}
- name: Run pytest
- name: Run pytest with coverage
run: |
if [[ "${{ runner.debug }}" == "1" ]]; then
poetry run pytest -s -vv -o log_cli=true -o log_cli_level=DEBUG
poetry run pytest -s -vv -o log_cli=true -o log_cli_level=DEBUG \
--cov=backend --cov-branch --cov-report term-missing --cov-report xml
else
poetry run pytest -s -vv
poetry run pytest -s -vv \
--cov=backend --cov-branch --cov-report term-missing --cov-report xml
fi
env:
LOG_LEVEL: ${{ runner.debug && 'DEBUG' || 'INFO' }}
@@ -284,14 +350,21 @@ jobs:
SUPABASE_SERVICE_ROLE_KEY: ${{ steps.supabase.outputs.SERVICE_ROLE_KEY }}
JWT_VERIFY_KEY: ${{ steps.supabase.outputs.JWT_SECRET }}
REDIS_HOST: "localhost"
REDIS_PORT: "6379"
REDIS_PORT: "17000"
ENCRYPTION_KEY: "dvziYgz0KSK8FENhju0ZYi8-fRTfAdlz6YLhdB_jhNw=" # DO NOT USE IN PRODUCTION!!
# Opt-in: lets backend/data/e2e_redis_restart_test.py spin up its
# own isolated 3-shard cluster (ports 2711027112) and exercise
# ``docker restart <shard>`` mid-stream. Off locally so a
# contributor's ``poetry run test`` doesn't pay the ~15s cost.
E2E_RESTART_ISOLATED: "1"
# - name: Upload coverage reports to Codecov
# uses: codecov/codecov-action@v4
# with:
# token: ${{ secrets.CODECOV_TOKEN }}
# flags: backend,${{ runner.os }}
- name: Upload coverage reports to Codecov
if: ${{ !cancelled() }}
uses: codecov/codecov-action@v5
with:
token: ${{ secrets.CODECOV_TOKEN }}
flags: platform-backend
files: ./autogpt_platform/backend/coverage.xml
env:
CI: true

View File

@@ -148,3 +148,11 @@ jobs:
- name: Run Integration Tests
run: pnpm test:unit
- name: Upload coverage reports to Codecov
if: ${{ !cancelled() }}
uses: codecov/codecov-action@v5
with:
token: ${{ secrets.CODECOV_TOKEN }}
flags: platform-frontend
files: ./autogpt_platform/frontend/coverage/cobertura-coverage.xml

View File

@@ -160,6 +160,7 @@ jobs:
run: |
cp ../backend/.env.default ../backend/.env
echo "OPENAI_INTERNAL_API_KEY=${{ secrets.OPENAI_API_KEY }}" >> ../backend/.env
echo "SCHEDULER_STARTUP_EMBEDDING_BACKFILL=false" >> ../backend/.env
env:
# Used by E2E test data script to generate embeddings for approved store agents
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
@@ -179,21 +180,30 @@ jobs:
pip install pyyaml
# Resolve extends and generate a flat compose file that bake can understand
export NEXT_PUBLIC_SOURCEMAPS NEXT_PUBLIC_PW_TEST
docker compose -f docker-compose.yml config > docker-compose.resolved.yml
# Ensure NEXT_PUBLIC_SOURCEMAPS is in resolved compose
# (docker compose config on some versions drops this arg)
if ! grep -q "NEXT_PUBLIC_SOURCEMAPS" docker-compose.resolved.yml; then
echo "Injecting NEXT_PUBLIC_SOURCEMAPS into resolved compose (docker compose config dropped it)"
sed -i '/NEXT_PUBLIC_PW_TEST/a\ NEXT_PUBLIC_SOURCEMAPS: "true"' docker-compose.resolved.yml
fi
# Add cache configuration to the resolved compose file
python ../.github/workflows/scripts/docker-ci-fix-compose-build-cache.py \
--source docker-compose.resolved.yml \
--cache-from "type=gha" \
--cache-to "type=gha,mode=max" \
--backend-hash "${{ hashFiles('autogpt_platform/backend/Dockerfile', 'autogpt_platform/backend/poetry.lock', 'autogpt_platform/backend/backend/**') }}" \
--frontend-hash "${{ hashFiles('autogpt_platform/frontend/Dockerfile', 'autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/src/**') }}" \
--frontend-hash "${{ hashFiles('autogpt_platform/frontend/Dockerfile', 'autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/src/**') }}-sourcemaps" \
--git-ref "${{ github.ref }}"
# Build with bake using the resolved compose file (now includes cache config)
docker buildx bake --allow=fs.read=.. -f docker-compose.resolved.yml --load
env:
NEXT_PUBLIC_PW_TEST: true
NEXT_PUBLIC_SOURCEMAPS: true
- name: Set up tests - Cache E2E test data
id: e2e-data-cache
@@ -279,16 +289,38 @@ jobs:
cache: "pnpm"
cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
- name: Set up tests - Cache Playwright browsers
uses: actions/cache@v5
with:
path: ~/.cache/ms-playwright
key: playwright-${{ runner.os }}-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml') }}
restore-keys: |
playwright-${{ runner.os }}-
- name: Copy source maps from Docker for E2E coverage
run: |
FRONTEND_CONTAINER=$(docker compose -f ../docker-compose.resolved.yml ps -q frontend)
docker cp "$FRONTEND_CONTAINER":/app/.next/static .next-static-coverage
- name: Set up tests - Install dependencies
run: pnpm install --frozen-lockfile
- name: Set up tests - Install browser 'chromium'
run: pnpm playwright install --with-deps chromium
- name: Run Playwright tests
run: pnpm test:no-build
- name: Run Playwright E2E suite
run: pnpm test:e2e:no-build
continue-on-error: false
- name: Upload E2E coverage to Codecov
if: ${{ !cancelled() }}
uses: codecov/codecov-action@v5
with:
token: ${{ secrets.CODECOV_TOKEN }}
flags: platform-frontend-e2e
files: ./autogpt_platform/frontend/coverage/e2e/cobertura-coverage.xml
disable_search: true
- name: Upload Playwright report
if: always()
uses: actions/upload-artifact@v4

17
.gitignore vendored
View File

@@ -3,6 +3,7 @@
classic/original_autogpt/keys.py
classic/original_autogpt/*.json
auto_gpt_workspace/*
.autogpt/
*.mpeg
.env
# Root .env files
@@ -16,6 +17,7 @@ log-ingestion.txt
/logs
*.log
*.mp3
!autogpt_platform/frontend/public/notification.mp3
mem.sqlite3
venvAutoGPT
@@ -159,6 +161,10 @@ CURRENT_BULLETIN.md
# AgBenchmark
classic/benchmark/agbenchmark/reports/
classic/reports/
classic/direct_benchmark/reports/
classic/.benchmark_workspaces/
classic/direct_benchmark/.benchmark_workspaces/
# Nodejs
package-lock.json
@@ -177,9 +183,20 @@ autogpt_platform/backend/settings.py
*.ign.*
.test-contents
**/.claude/settings.local.json
.claude/settings.local.json
CLAUDE.local.md
/autogpt_platform/backend/logs
/autogpt_platform/backend/poetry.toml
# Test database
test.db
.next
# Implementation plans (generated by AI agents)
plans/
.claude/worktrees/
test-results/
# Playwright MCP / local browser-testing artifacts
.playwright-mcp/
copilot-session-switch-qa/

36
.gitleaks.toml Normal file
View File

@@ -0,0 +1,36 @@
title = "AutoGPT Gitleaks Config"
[extend]
useDefault = true
[allowlist]
description = "Global allowlist"
paths = [
# Template/example env files (no real secrets)
'''\.env\.(default|example|template)$''',
# Lock files
'''pnpm-lock\.yaml$''',
'''poetry\.lock$''',
# Secrets baseline
'''\.secrets\.baseline$''',
# Build artifacts and caches (should not be committed)
'''__pycache__/''',
'''classic/frontend/build/''',
# Docker dev setup (local dev JWTs/keys only)
'''autogpt_platform/db/docker/''',
# Load test configs (dev JWTs)
'''load-tests/configs/''',
# Test files with fake/fixture keys (_test.py, test_*.py, conftest.py)
'''(_test|test_.*|conftest)\.py$''',
# Documentation (only contains placeholder keys in curl/API examples)
'''docs/.*\.md$''',
# Firebase config (public API keys by design)
'''google-services\.json$''',
'''classic/frontend/(lib|web)/''',
]
# CI test-only encryption key (marked DO NOT USE IN PRODUCTION)
regexes = [
'''dvziYgz0KSK8FENhju0ZYi8''',
# LLM model name enum values falsely flagged as API keys
'''Llama-\d.*Instruct''',
]

3
.gitmodules vendored
View File

@@ -1,3 +0,0 @@
[submodule "classic/forge/tests/vcr_cassettes"]
path = classic/forge/tests/vcr_cassettes
url = https://github.com/Significant-Gravitas/Auto-GPT-test-cassettes

View File

@@ -23,9 +23,15 @@ repos:
- id: detect-secrets
name: Detect secrets
description: Detects high entropy strings that are likely to be passwords.
args: ["--baseline", ".secrets.baseline"]
files: ^autogpt_platform/
exclude: pnpm-lock\.yaml$
stages: [pre-push]
exclude: (pnpm-lock\.yaml|\.env\.(default|example|template))$
- repo: https://github.com/gitleaks/gitleaks
rev: v8.24.3
hooks:
- id: gitleaks
name: Detect secrets (gitleaks)
- repo: local
# For proper type checking, all dependencies need to be up-to-date.
@@ -84,51 +90,16 @@ repos:
stages: [pre-commit, post-checkout]
- id: poetry-install
name: Check & Install dependencies - Classic - AutoGPT
alias: poetry-install-classic-autogpt
name: Check & Install dependencies - Classic
alias: poetry-install-classic
entry: >
bash -c '
if [ -n "$PRE_COMMIT_FROM_REF" ]; then
git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
else
git diff --cached --name-only
fi | grep -qE "^classic/(original_autogpt|forge)/poetry\.lock$" || exit 0;
poetry -C classic/original_autogpt install
'
# include forge source (since it's a path dependency)
always_run: true
language: system
pass_filenames: false
stages: [pre-commit, post-checkout]
- id: poetry-install
name: Check & Install dependencies - Classic - Forge
alias: poetry-install-classic-forge
entry: >
bash -c '
if [ -n "$PRE_COMMIT_FROM_REF" ]; then
git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
else
git diff --cached --name-only
fi | grep -qE "^classic/forge/poetry\.lock$" || exit 0;
poetry -C classic/forge install
'
always_run: true
language: system
pass_filenames: false
stages: [pre-commit, post-checkout]
- id: poetry-install
name: Check & Install dependencies - Classic - Benchmark
alias: poetry-install-classic-benchmark
entry: >
bash -c '
if [ -n "$PRE_COMMIT_FROM_REF" ]; then
git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
else
git diff --cached --name-only
fi | grep -qE "^classic/benchmark/poetry\.lock$" || exit 0;
poetry -C classic/benchmark install
fi | grep -qE "^classic/poetry\.lock$" || exit 0;
poetry -C classic install
'
always_run: true
language: system
@@ -223,26 +194,10 @@ repos:
language: system
- id: isort
name: Lint (isort) - Classic - AutoGPT
alias: isort-classic-autogpt
entry: poetry -P classic/original_autogpt run isort -p autogpt
files: ^classic/original_autogpt/
types: [file, python]
language: system
- id: isort
name: Lint (isort) - Classic - Forge
alias: isort-classic-forge
entry: poetry -P classic/forge run isort -p forge
files: ^classic/forge/
types: [file, python]
language: system
- id: isort
name: Lint (isort) - Classic - Benchmark
alias: isort-classic-benchmark
entry: poetry -P classic/benchmark run isort -p agbenchmark
files: ^classic/benchmark/
name: Lint (isort) - Classic
alias: isort-classic
entry: bash -c 'cd classic && poetry run isort $(echo "$@" | sed "s|classic/||g")' --
files: ^classic/(original_autogpt|forge|direct_benchmark)/
types: [file, python]
language: system
@@ -256,26 +211,13 @@ repos:
- repo: https://github.com/PyCQA/flake8
rev: 7.0.0
# To have flake8 load the config of the individual subprojects, we have to call
# them separately.
# Use consolidated flake8 config at classic/.flake8
hooks:
- id: flake8
name: Lint (Flake8) - Classic - AutoGPT
alias: flake8-classic-autogpt
files: ^classic/original_autogpt/(autogpt|scripts|tests)/
args: [--config=classic/original_autogpt/.flake8]
- id: flake8
name: Lint (Flake8) - Classic - Forge
alias: flake8-classic-forge
files: ^classic/forge/(forge|tests)/
args: [--config=classic/forge/.flake8]
- id: flake8
name: Lint (Flake8) - Classic - Benchmark
alias: flake8-classic-benchmark
files: ^classic/benchmark/(agbenchmark|tests)/((?!reports).)*[/.]
args: [--config=classic/benchmark/.flake8]
name: Lint (Flake8) - Classic
alias: flake8-classic
files: ^classic/(original_autogpt|forge|direct_benchmark)/
args: [--config=classic/.flake8]
- repo: local
hooks:
@@ -311,29 +253,10 @@ repos:
pass_filenames: false
- id: pyright
name: Typecheck - Classic - AutoGPT
alias: pyright-classic-autogpt
entry: poetry -C classic/original_autogpt run pyright
# include forge source (since it's a path dependency) but exclude *_test.py files:
files: ^(classic/original_autogpt/((autogpt|scripts|tests)/|poetry\.lock$)|classic/forge/(forge/.*(?<!_test)\.py|poetry\.lock)$)
types: [file]
language: system
pass_filenames: false
- id: pyright
name: Typecheck - Classic - Forge
alias: pyright-classic-forge
entry: poetry -C classic/forge run pyright
files: ^classic/forge/(forge/|poetry\.lock$)
types: [file]
language: system
pass_filenames: false
- id: pyright
name: Typecheck - Classic - Benchmark
alias: pyright-classic-benchmark
entry: poetry -C classic/benchmark run pyright
files: ^classic/benchmark/(agbenchmark/|tests/|poetry\.lock$)
name: Typecheck - Classic
alias: pyright-classic
entry: poetry -C classic run pyright
files: ^classic/(original_autogpt|forge|direct_benchmark)/.*\.py$|^classic/poetry\.lock$
types: [file]
language: system
pass_filenames: false
@@ -360,26 +283,9 @@ repos:
# pass_filenames: false
# - id: pytest
# name: Run tests - Classic - AutoGPT (excl. slow tests)
# alias: pytest-classic-autogpt
# entry: bash -c 'cd classic/original_autogpt && poetry run pytest --cov=autogpt -m "not slow" tests/unit tests/integration'
# # include forge source (since it's a path dependency) but exclude *_test.py files:
# files: ^(classic/original_autogpt/((autogpt|tests)/|poetry\.lock$)|classic/forge/(forge/.*(?<!_test)\.py|poetry\.lock)$)
# language: system
# pass_filenames: false
# - id: pytest
# name: Run tests - Classic - Forge (excl. slow tests)
# alias: pytest-classic-forge
# entry: bash -c 'cd classic/forge && poetry run pytest --cov=forge -m "not slow"'
# files: ^classic/forge/(forge/|tests/|poetry\.lock$)
# language: system
# pass_filenames: false
# - id: pytest
# name: Run tests - Classic - Benchmark
# alias: pytest-classic-benchmark
# entry: bash -c 'cd classic/benchmark && poetry run pytest --cov=benchmark'
# files: ^classic/benchmark/(agbenchmark/|tests/|poetry\.lock$)
# name: Run tests - Classic (excl. slow tests)
# alias: pytest-classic
# entry: bash -c 'cd classic && poetry run pytest -m "not slow"'
# files: ^classic/(original_autogpt|forge|direct_benchmark)/
# language: system
# pass_filenames: false

471
.secrets.baseline Normal file
View File

@@ -0,0 +1,471 @@
{
"version": "1.5.0",
"plugins_used": [
{
"name": "ArtifactoryDetector"
},
{
"name": "AWSKeyDetector"
},
{
"name": "AzureStorageKeyDetector"
},
{
"name": "Base64HighEntropyString",
"limit": 4.5
},
{
"name": "BasicAuthDetector"
},
{
"name": "CloudantDetector"
},
{
"name": "DiscordBotTokenDetector"
},
{
"name": "GitHubTokenDetector"
},
{
"name": "GitLabTokenDetector"
},
{
"name": "HexHighEntropyString",
"limit": 3.0
},
{
"name": "IbmCloudIamDetector"
},
{
"name": "IbmCosHmacDetector"
},
{
"name": "IPPublicDetector"
},
{
"name": "JwtTokenDetector"
},
{
"name": "KeywordDetector",
"keyword_exclude": ""
},
{
"name": "MailchimpDetector"
},
{
"name": "NpmDetector"
},
{
"name": "OpenAIDetector"
},
{
"name": "PrivateKeyDetector"
},
{
"name": "PypiTokenDetector"
},
{
"name": "SendGridDetector"
},
{
"name": "SlackDetector"
},
{
"name": "SoftlayerDetector"
},
{
"name": "SquareOAuthDetector"
},
{
"name": "StripeDetector"
},
{
"name": "TelegramBotTokenDetector"
},
{
"name": "TwilioKeyDetector"
}
],
"filters_used": [
{
"path": "detect_secrets.filters.allowlist.is_line_allowlisted"
},
{
"path": "detect_secrets.filters.common.is_baseline_file",
"filename": ".secrets.baseline"
},
{
"path": "detect_secrets.filters.common.is_ignored_due_to_verification_policies",
"min_level": 2
},
{
"path": "detect_secrets.filters.heuristic.is_indirect_reference"
},
{
"path": "detect_secrets.filters.heuristic.is_likely_id_string"
},
{
"path": "detect_secrets.filters.heuristic.is_lock_file"
},
{
"path": "detect_secrets.filters.heuristic.is_not_alphanumeric_string"
},
{
"path": "detect_secrets.filters.heuristic.is_potential_uuid"
},
{
"path": "detect_secrets.filters.heuristic.is_prefixed_with_dollar_sign"
},
{
"path": "detect_secrets.filters.heuristic.is_sequential_string"
},
{
"path": "detect_secrets.filters.heuristic.is_swagger_file"
},
{
"path": "detect_secrets.filters.heuristic.is_templated_secret"
},
{
"path": "detect_secrets.filters.regex.should_exclude_file",
"pattern": [
"\\.env$",
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}

View File

@@ -30,7 +30,7 @@ See `/frontend/CONTRIBUTING.md` for complete patterns. Quick reference:
- Regenerate with `pnpm generate:api`
- Pattern: `use{Method}{Version}{OperationName}`
4. **Styling**: Tailwind CSS only, use design tokens, Phosphor Icons only
5. **Testing**: Add Storybook stories for new components, Playwright for E2E
5. **Testing**: Integration tests (Vitest + RTL + MSW) are the default (~90%, page-level). Playwright for E2E critical flows. Storybook for design system components. See `autogpt_platform/frontend/TESTING.md`
6. **Code conventions**: Function declarations (not arrow functions) for components/handlers
- Component props should be `interface Props { ... }` (not exported) unless the interface needs to be used outside the component
@@ -47,7 +47,9 @@ See `/frontend/CONTRIBUTING.md` for complete patterns. Quick reference:
## Testing
- Backend: `poetry run test` (runs pytest with a docker based postgres + prisma).
- Frontend: `pnpm test` or `pnpm test-ui` for Playwright tests. See `docs/content/platform/contributing/tests.md` for tips.
- Frontend integration tests: `pnpm test:unit` (Vitest + RTL + MSW, primary testing approach).
- Frontend E2E tests: `pnpm test` or `pnpm test-ui` for Playwright tests.
- See `autogpt_platform/frontend/TESTING.md` for the full testing strategy.
Always run the relevant linters and tests before committing.
Use conventional commit messages for all commits (e.g. `feat(backend): add API`).

View File

@@ -1,3 +1,6 @@
*.ignore.*
*.ign.*
.application.logs
# Claude Code local settings only — the rest of .claude/ is shared (skills etc.)
.claude/settings.local.json

View File

@@ -0,0 +1,100 @@
-- =============================================================
-- View: analytics.platform_cost_log
-- Looker source alias: ds115 | Charts: 0
-- =============================================================
-- DESCRIPTION
-- One row per platform cost log entry (last 90 days).
-- Tracks real API spend at the call level: provider, model,
-- token counts (including Anthropic cache tokens), cost in
-- microdollars, and the block/execution that incurred the cost.
-- Joins the User table to provide email for per-user breakdowns.
--
-- SOURCE TABLES
-- platform.PlatformCostLog — Per-call cost records
-- platform.User — User email
--
-- OUTPUT COLUMNS
-- id TEXT Log entry UUID
-- createdAt TIMESTAMPTZ When the cost was recorded
-- userId TEXT User who incurred the cost (nullable)
-- email TEXT User email (nullable)
-- graphExecId TEXT Graph execution UUID (nullable)
-- nodeExecId TEXT Node execution UUID (nullable)
-- blockName TEXT Block that made the API call (nullable)
-- provider TEXT API provider, lowercase (e.g. 'openai', 'anthropic')
-- model TEXT Model name (nullable)
-- trackingType TEXT Cost unit: 'tokens' | 'cost_usd' | 'characters' | etc.
-- costMicrodollars BIGINT Cost in microdollars (divide by 1,000,000 for USD)
-- costUsd FLOAT Cost in USD (costMicrodollars / 1,000,000)
-- inputTokens INT Prompt/input tokens (nullable)
-- outputTokens INT Completion/output tokens (nullable)
-- cacheReadTokens INT Anthropic cache-read tokens billed at 10% (nullable)
-- cacheCreationTokens INT Anthropic cache-write tokens billed at 125% (nullable)
-- totalTokens INT inputTokens + outputTokens (nullable if either is null)
-- duration FLOAT API call duration in seconds (nullable)
--
-- WINDOW
-- Rolling 90 days (createdAt > CURRENT_DATE - 90 days)
--
-- EXAMPLE QUERIES
-- -- Total spend by provider (last 90 days)
-- SELECT provider, SUM("costUsd") AS total_usd, COUNT(*) AS calls
-- FROM analytics.platform_cost_log
-- GROUP BY 1 ORDER BY total_usd DESC;
--
-- -- Spend by model
-- SELECT provider, model, SUM("costUsd") AS total_usd,
-- SUM("inputTokens") AS input_tokens,
-- SUM("outputTokens") AS output_tokens
-- FROM analytics.platform_cost_log
-- WHERE model IS NOT NULL
-- GROUP BY 1, 2 ORDER BY total_usd DESC;
--
-- -- Top 20 users by spend
-- SELECT "userId", email, SUM("costUsd") AS total_usd, COUNT(*) AS calls
-- FROM analytics.platform_cost_log
-- WHERE "userId" IS NOT NULL
-- GROUP BY 1, 2 ORDER BY total_usd DESC LIMIT 20;
--
-- -- Daily spend trend
-- SELECT DATE_TRUNC('day', "createdAt") AS day,
-- SUM("costUsd") AS daily_usd,
-- COUNT(*) AS calls
-- FROM analytics.platform_cost_log
-- GROUP BY 1 ORDER BY 1;
--
-- -- Cache hit rate for Anthropic (cache reads vs total reads)
-- SELECT DATE_TRUNC('day', "createdAt") AS day,
-- SUM("cacheReadTokens")::float /
-- NULLIF(SUM("inputTokens" + COALESCE("cacheReadTokens", 0)), 0) AS cache_hit_rate
-- FROM analytics.platform_cost_log
-- WHERE provider = 'anthropic'
-- GROUP BY 1 ORDER BY 1;
-- =============================================================
SELECT
p."id" AS id,
p."createdAt" AS createdAt,
p."userId" AS userId,
u."email" AS email,
p."graphExecId" AS graphExecId,
p."nodeExecId" AS nodeExecId,
p."blockName" AS blockName,
p."provider" AS provider,
p."model" AS model,
p."trackingType" AS trackingType,
p."costMicrodollars" AS costMicrodollars,
p."costMicrodollars"::float / 1000000.0 AS costUsd,
p."inputTokens" AS inputTokens,
p."outputTokens" AS outputTokens,
p."cacheReadTokens" AS cacheReadTokens,
p."cacheCreationTokens" AS cacheCreationTokens,
CASE
WHEN p."inputTokens" IS NOT NULL AND p."outputTokens" IS NOT NULL
THEN p."inputTokens" + p."outputTokens"
ELSE NULL
END AS totalTokens,
p."duration" AS duration
FROM platform."PlatformCostLog" p
LEFT JOIN platform."User" u ON u."id" = p."userId"
WHERE p."createdAt" > CURRENT_DATE - INTERVAL '90 days'

View File

@@ -1,33 +0,0 @@
from typing import Optional
from pydantic import Field
from pydantic_settings import BaseSettings, SettingsConfigDict
class RateLimitSettings(BaseSettings):
redis_host: str = Field(
default="redis://localhost:6379",
description="Redis host",
validation_alias="REDIS_HOST",
)
redis_port: str = Field(
default="6379", description="Redis port", validation_alias="REDIS_PORT"
)
redis_password: Optional[str] = Field(
default=None,
description="Redis password",
validation_alias="REDIS_PASSWORD",
)
requests_per_minute: int = Field(
default=60,
description="Maximum number of requests allowed per minute per API key",
validation_alias="RATE_LIMIT_REQUESTS_PER_MINUTE",
)
model_config = SettingsConfigDict(case_sensitive=True, extra="ignore")
RATE_LIMIT_SETTINGS = RateLimitSettings()

View File

@@ -1,51 +0,0 @@
import time
from typing import Tuple
from redis import Redis
from .config import RATE_LIMIT_SETTINGS
class RateLimiter:
def __init__(
self,
redis_host: str = RATE_LIMIT_SETTINGS.redis_host,
redis_port: str = RATE_LIMIT_SETTINGS.redis_port,
redis_password: str | None = RATE_LIMIT_SETTINGS.redis_password,
requests_per_minute: int = RATE_LIMIT_SETTINGS.requests_per_minute,
):
self.redis = Redis(
host=redis_host,
port=int(redis_port),
password=redis_password,
decode_responses=True,
)
self.window = 60
self.max_requests = requests_per_minute
async def check_rate_limit(self, api_key_id: str) -> Tuple[bool, int, int]:
"""
Check if request is within rate limits.
Args:
api_key_id: The API key identifier to check
Returns:
Tuple of (is_allowed, remaining_requests, reset_time)
"""
now = time.time()
window_start = now - self.window
key = f"ratelimit:{api_key_id}:1min"
pipe = self.redis.pipeline()
pipe.zremrangebyscore(key, 0, window_start)
pipe.zadd(key, {str(now): now})
pipe.zcount(key, window_start, now)
pipe.expire(key, self.window)
_, _, request_count, _ = pipe.execute()
remaining = max(0, self.max_requests - request_count)
reset_time = int(now + self.window)
return request_count <= self.max_requests, remaining, reset_time

View File

@@ -1,32 +0,0 @@
from fastapi import HTTPException, Request
from starlette.middleware.base import RequestResponseEndpoint
from .limiter import RateLimiter
async def rate_limit_middleware(request: Request, call_next: RequestResponseEndpoint):
"""FastAPI middleware for rate limiting API requests."""
limiter = RateLimiter()
if not request.url.path.startswith("/api"):
return await call_next(request)
api_key = request.headers.get("Authorization")
if not api_key:
return await call_next(request)
api_key = api_key.replace("Bearer ", "")
is_allowed, remaining, reset_time = await limiter.check_rate_limit(api_key)
if not is_allowed:
raise HTTPException(
status_code=429, detail="Rate limit exceeded. Please try again later."
)
response = await call_next(request)
response.headers["X-RateLimit-Limit"] = str(limiter.max_requests)
response.headers["X-RateLimit-Remaining"] = str(remaining)
response.headers["X-RateLimit-Reset"] = str(reset_time)
return response

View File

@@ -59,6 +59,8 @@ class OAuthState(BaseModel):
code_verifier: Optional[str] = None
scopes: list[str]
"""Unix timestamp (seconds) indicating when this OAuth state expires"""
credential_id: Optional[str] = None
"""If set, this OAuth flow upgrades an existing credential's scopes."""
class UserMetadata(BaseModel):

View File

@@ -1,13 +1,16 @@
import asyncio
from contextlib import asynccontextmanager
from typing import TYPE_CHECKING, Any
from typing import TYPE_CHECKING, Any, Union
from expiringdict import ExpiringDict
if TYPE_CHECKING:
from redis.asyncio import Redis as AsyncRedis
from redis.asyncio.cluster import RedisCluster as AsyncRedisCluster
from redis.asyncio.lock import Lock as AsyncRedisLock
AsyncRedisLike = Union[AsyncRedis, AsyncRedisCluster]
class AsyncRedisKeyedMutex:
"""
@@ -17,7 +20,7 @@ class AsyncRedisKeyedMutex:
in case the key is not unlocked for a specified duration, to prevent memory leaks.
"""
def __init__(self, redis: "AsyncRedis", timeout: int | None = 60):
def __init__(self, redis: "AsyncRedisLike", timeout: int | None = 60):
self.redis = redis
self.timeout = timeout
self.locks: dict[Any, "AsyncRedisLock"] = ExpiringDict(

View File

@@ -37,6 +37,23 @@ JWT_VERIFY_KEY=your-super-secret-jwt-token-with-at-least-32-characters-long
ENCRYPTION_KEY=dvziYgz0KSK8FENhju0ZYi8-fRTfAdlz6YLhdB_jhNw=
UNSUBSCRIBE_SECRET_KEY=HlP8ivStJjmbf6NKi78m_3FnOogut0t5ckzjsIqeaio=
# Web Push (VAPID) — generate with: poetry run python -c "
# from py_vapid import Vapid; import base64
# from cryptography.hazmat.primitives.serialization import Encoding, PublicFormat
# v = Vapid(); v.generate_keys()
# raw_priv = v.private_key.private_numbers().private_value.to_bytes(32, 'big')
# print('VAPID_PRIVATE_KEY=' + base64.urlsafe_b64encode(raw_priv).rstrip(b'=').decode())
# raw_pub = v.public_key.public_bytes(Encoding.X962, PublicFormat.UncompressedPoint)
# print('VAPID_PUBLIC_KEY=' + base64.urlsafe_b64encode(raw_pub).rstrip(b'=').decode())
# "
# Dev-only keypair below — DO NOT use in staging/production. Regenerate
# your own with the snippet above before any non-local deployment.
VAPID_PRIVATE_KEY=17hBPdSdn6TR_yAgQxA0TjTcvRj3Lf6znHnASZ4rOKc
VAPID_PUBLIC_KEY=BBg49iVTWthVbRYphwmZNvZyiSJDqtSO4nmLxDzLKe3Oo9jbtu0Usa14xX4HQQNLUeiEfzD42zWSlrvY1PR12bs
# Per RFC 8292 push services use this in 410 Gone reports; set to a real
# mailbox in production. Defaults to a placeholder for local dev.
VAPID_CLAIM_EMAIL=mailto:dev@example.com
## ===== IMPORTANT OPTIONAL CONFIGURATION ===== ##
# Platform URLs (set these for webhooks and OAuth to work)
PLATFORM_BASE_URL=http://localhost:8000
@@ -58,6 +75,17 @@ V0_API_KEY=
OPEN_ROUTER_API_KEY=
NVIDIA_API_KEY=
# Graphiti Temporal Knowledge Graph Memory
# Rollout controlled by LaunchDarkly flag "graphiti-memory"
# LLM key falls back to CHAT_API_KEY (AutoPilot), then OPEN_ROUTER_API_KEY.
# Embedder key falls back to CHAT_OPENAI_API_KEY (AutoPilot), then OPENAI_API_KEY.
GRAPHITI_FALKORDB_HOST=localhost
GRAPHITI_FALKORDB_PORT=6380
GRAPHITI_FALKORDB_PASSWORD=
GRAPHITI_LLM_MODEL=gpt-4.1-mini
GRAPHITI_EMBEDDER_MODEL=text-embedding-3-small
GRAPHITI_SEMAPHORE_LIMIT=5
# Langfuse Prompt Management
# Used for managing the CoPilot system prompt externally
# Get credentials from https://cloud.langfuse.com or your self-hosted instance
@@ -168,6 +196,13 @@ MEM0_API_KEY=
OPENWEATHERMAP_API_KEY=
GOOGLE_MAPS_API_KEY=
# Platform Bot Linking
PLATFORM_LINK_BASE_URL=http://localhost:3000/link
# CoPilot chat-platform bridge (Discord/Telegram/Slack)
# Uses FRONTEND_BASE_URL (above) for link confirmation pages.
AUTOPILOT_BOT_DISCORD_TOKEN=
# Communication Services
DISCORD_BOT_TOKEN=
MEDIUM_API_KEY=

View File

@@ -0,0 +1,166 @@
{
"id": "858e2226-e047-4d19-a832-3be4a134d155",
"version": 2,
"is_active": true,
"name": "Calculator agent",
"description": "",
"instructions": null,
"recommended_schedule_cron": null,
"forked_from_id": null,
"forked_from_version": null,
"user_id": "",
"created_at": "2026-04-13T03:45:11.241Z",
"nodes": [
{
"id": "6762da5d-6915-4836-a431-6dcd7d36a54a",
"block_id": "c0a8e994-ebf1-4a9c-a4d8-89d09c86741b",
"input_default": {
"name": "Input",
"secret": false,
"advanced": false
},
"metadata": {
"position": {
"x": -188.2244873046875,
"y": 95
}
},
"input_links": [],
"output_links": [
{
"id": "432c7caa-49b9-4b70-bd21-2fa33a569601",
"source_id": "6762da5d-6915-4836-a431-6dcd7d36a54a",
"sink_id": "bf4a15ff-b0c4-4032-a21b-5880224af690",
"source_name": "result",
"sink_name": "a",
"is_static": true
}
],
"graph_id": "858e2226-e047-4d19-a832-3be4a134d155",
"graph_version": 2,
"webhook_id": null
},
{
"id": "65429c9e-a0c6-4032-a421-6899c394fa74",
"block_id": "363ae599-353e-4804-937e-b2ee3cef3da4",
"input_default": {
"name": "Output",
"secret": false,
"advanced": false,
"escape_html": false
},
"metadata": {
"position": {
"x": 825.198974609375,
"y": 123.75
}
},
"input_links": [
{
"id": "8cdb2f33-5b10-4cc2-8839-f8ccb70083a3",
"source_id": "bf4a15ff-b0c4-4032-a21b-5880224af690",
"sink_id": "65429c9e-a0c6-4032-a421-6899c394fa74",
"source_name": "result",
"sink_name": "value",
"is_static": false
}
],
"output_links": [],
"graph_id": "858e2226-e047-4d19-a832-3be4a134d155",
"graph_version": 2,
"webhook_id": null
},
{
"id": "bf4a15ff-b0c4-4032-a21b-5880224af690",
"block_id": "b1ab9b19-67a6-406d-abf5-2dba76d00c79",
"input_default": {
"b": 34,
"operation": "Add",
"round_result": false
},
"metadata": {
"position": {
"x": 323.0255126953125,
"y": 121.25
}
},
"input_links": [
{
"id": "432c7caa-49b9-4b70-bd21-2fa33a569601",
"source_id": "6762da5d-6915-4836-a431-6dcd7d36a54a",
"sink_id": "bf4a15ff-b0c4-4032-a21b-5880224af690",
"source_name": "result",
"sink_name": "a",
"is_static": true
}
],
"output_links": [
{
"id": "8cdb2f33-5b10-4cc2-8839-f8ccb70083a3",
"source_id": "bf4a15ff-b0c4-4032-a21b-5880224af690",
"sink_id": "65429c9e-a0c6-4032-a421-6899c394fa74",
"source_name": "result",
"sink_name": "value",
"is_static": false
}
],
"graph_id": "858e2226-e047-4d19-a832-3be4a134d155",
"graph_version": 2,
"webhook_id": null
}
],
"links": [
{
"id": "8cdb2f33-5b10-4cc2-8839-f8ccb70083a3",
"source_id": "bf4a15ff-b0c4-4032-a21b-5880224af690",
"sink_id": "65429c9e-a0c6-4032-a421-6899c394fa74",
"source_name": "result",
"sink_name": "value",
"is_static": false
},
{
"id": "432c7caa-49b9-4b70-bd21-2fa33a569601",
"source_id": "6762da5d-6915-4836-a431-6dcd7d36a54a",
"sink_id": "bf4a15ff-b0c4-4032-a21b-5880224af690",
"source_name": "result",
"sink_name": "a",
"is_static": true
}
],
"sub_graphs": [],
"input_schema": {
"type": "object",
"properties": {
"Input": {
"advanced": false,
"secret": false,
"title": "Input"
}
},
"required": [
"Input"
]
},
"output_schema": {
"type": "object",
"properties": {
"Output": {
"advanced": false,
"secret": false,
"title": "Output"
}
},
"required": [
"Output"
]
},
"has_external_trigger": false,
"has_human_in_the_loop": false,
"has_sensitive_action": false,
"trigger_setup_info": null,
"credentials_input_schema": {
"type": "object",
"properties": {},
"required": []
}
}

View File

@@ -1,14 +1,44 @@
import asyncio
from typing import Dict, Set
import json
import logging
import time
from typing import Awaitable, Callable, Dict, Optional, Set
from fastapi import WebSocket
from fastapi import WebSocket, WebSocketDisconnect
from redis.asyncio import Redis as AsyncRedis
from redis.asyncio.client import PubSub as AsyncPubSub
from redis.exceptions import MovedError, RedisError, ResponseError
from starlette.websockets import WebSocketState
from backend.api.model import NotificationPayload, WSMessage, WSMethod
from backend.api.model import WSMessage, WSMethod
from backend.data import redis_client as redis
from backend.data.event_bus import _assert_no_wildcard
from backend.data.execution import (
ExecutionEventType,
GraphExecutionEvent,
NodeExecutionEvent,
exec_channel,
get_graph_execution_meta,
graph_all_channel,
)
from backend.data.notification_bus import NotificationEvent
from backend.util.settings import Settings
logger = logging.getLogger(__name__)
_settings = Settings()
def _is_ws_close_race(exc: BaseException, websocket: WebSocket) -> bool:
"""A SPUBLISH→WS send racing with WS close — benign, drop quietly."""
if isinstance(exc, WebSocketDisconnect):
return True
if (
getattr(websocket, "application_state", None) == WebSocketState.DISCONNECTED
or getattr(websocket, "client_state", None) == WebSocketState.DISCONNECTED
):
return True
if isinstance(exc, RuntimeError) and "close message has been sent" in str(exc):
return True
return False
_EVENT_TYPE_TO_METHOD_MAP: dict[ExecutionEventType, WSMethod] = {
ExecutionEventType.GRAPH_EXEC_UPDATE: WSMethod.GRAPH_EXECUTION_EVENT,
@@ -16,128 +46,379 @@ _EVENT_TYPE_TO_METHOD_MAP: dict[ExecutionEventType, WSMethod] = {
}
def event_bus_channel(channel_key: str) -> str:
"""Prefix a channel key with the execution event bus name."""
return f"{_settings.config.execution_event_bus_name}/{channel_key}"
def _notification_bus_channel(user_id: str) -> str:
"""Return the full sharded channel name for a user's notifications."""
return f"{_settings.config.notification_event_bus_name}/{user_id}"
MessageHandler = Callable[[Optional[bytes | str]], Awaitable[None]]
def _is_moved_error(exc: BaseException) -> bool:
"""A MOVED redirect — slot migration mid-stream; pump should reconnect."""
if isinstance(exc, MovedError):
return True
if isinstance(exc, ResponseError) and str(exc).startswith("MOVED "):
return True
return False
# Reconnect tunables for shard-failover during pubsub.listen().
_PUMP_RECONNECT_DEADLINE_S = 60.0
_PUMP_RECONNECT_BACKOFF_INITIAL_S = 0.5
_PUMP_RECONNECT_BACKOFF_MAX_S = 8.0
class _Subscription:
"""One SSUBSCRIBE lifecycle bound to a WebSocket, pinned to the owning shard."""
def __init__(self, full_channel: str) -> None:
_assert_no_wildcard(full_channel)
self.full_channel = full_channel
self._client: AsyncRedis | None = None
self._pubsub: AsyncPubSub | None = None
self._task: asyncio.Task | None = None
async def start(self, on_message: MessageHandler) -> None:
await self._open_pubsub()
self._task = asyncio.create_task(self._pump(on_message))
async def _open_pubsub(self) -> None:
"""(Re)establish the sharded pubsub connection + SSUBSCRIBE."""
self._client = await redis.connect_sharded_pubsub_async(self.full_channel)
self._pubsub = self._client.pubsub()
await self._pubsub.execute_command("SSUBSCRIBE", self.full_channel)
# redis-py 6.x async PubSub.listen() exits when ``channels`` is
# empty; raw SSUBSCRIBE doesn't populate it, so do it ourselves.
self._pubsub.channels[self.full_channel] = None # type: ignore[index]
async def _close_pubsub_quietly(self) -> None:
"""Best-effort teardown before reconnect — never raises."""
if self._pubsub is not None:
try:
await self._pubsub.aclose()
except Exception:
pass
self._pubsub = None
if self._client is not None:
try:
await self._client.aclose()
except Exception:
pass
self._client = None
async def _pump(self, on_message: MessageHandler) -> None:
if self._pubsub is None:
return
backoff = _PUMP_RECONNECT_BACKOFF_INITIAL_S
deadline = time.monotonic() + _PUMP_RECONNECT_DEADLINE_S
while True:
pubsub = self._pubsub
if pubsub is None:
return
needs_reconnect = False
try:
async for message in pubsub.listen():
msg_type = message.get("type")
# Server-pushed sunsubscribe: slot ownership changed and
# Redis revoked our SSUBSCRIBE without dropping the TCP.
# Treat as a reconnect trigger so we re-resolve the shard.
if msg_type == "sunsubscribe":
needs_reconnect = True
break
if msg_type not in ("smessage", "message", "pmessage"):
continue
# Successful read resets the reconnect budget.
backoff = _PUMP_RECONNECT_BACKOFF_INITIAL_S
deadline = time.monotonic() + _PUMP_RECONNECT_DEADLINE_S
try:
await on_message(message.get("data"))
except Exception:
logger.exception(
"Websocket message-handler failed for channel %s",
self.full_channel,
)
if not needs_reconnect:
# listen() exited cleanly (channels emptied) — pump is done.
return
except asyncio.CancelledError:
raise
except (ConnectionError, RedisError) as exc:
if isinstance(exc, ResponseError) and not _is_moved_error(exc):
logger.exception(
"Pubsub pump crashed on non-retryable ResponseError for %s",
self.full_channel,
)
return
if time.monotonic() > deadline:
logger.exception(
"Pubsub pump giving up after reconnect deadline for %s",
self.full_channel,
)
return
logger.warning(
"Pubsub pump reconnecting for %s after %s: %s",
self.full_channel,
type(exc).__name__,
exc,
)
except Exception:
logger.exception("Pubsub pump crashed for %s", self.full_channel)
return
# Either a retryable error was raised, or the server pushed a
# sunsubscribe — close the stale pubsub and reopen against the
# (possibly migrated) shard.
await self._close_pubsub_quietly()
await asyncio.sleep(backoff)
backoff = min(backoff * 2, _PUMP_RECONNECT_BACKOFF_MAX_S)
try:
await self._open_pubsub()
except (ConnectionError, RedisError) as reopen_exc:
logger.warning(
"Pubsub pump reopen failed for %s: %s",
self.full_channel,
reopen_exc,
)
# Loop again — deadline check will eventually exit.
continue
async def stop(self) -> None:
if self._task is not None:
self._task.cancel()
try:
await self._task
except (asyncio.CancelledError, Exception):
pass
self._task = None
if self._pubsub is not None:
try:
await self._pubsub.execute_command("SUNSUBSCRIBE", self.full_channel)
except Exception:
logger.warning(
"SUNSUBSCRIBE failed for %s", self.full_channel, exc_info=True
)
try:
await self._pubsub.aclose()
except Exception:
pass
self._pubsub = None
if self._client is not None:
try:
await self._client.aclose()
except Exception:
pass
self._client = None
class ConnectionManager:
def __init__(self):
self.active_connections: Set[WebSocket] = set()
# channel_key → sockets subscribed (public channel keys, not raw Redis channels)
self.subscriptions: Dict[str, Set[WebSocket]] = {}
self.user_connections: Dict[str, Set[WebSocket]] = {}
# websocket → {channel_key: _Subscription}
self._ws_subs: Dict[WebSocket, Dict[str, _Subscription]] = {}
# websocket → notification subscription
self._ws_notifications: Dict[WebSocket, _Subscription] = {}
async def connect_socket(self, websocket: WebSocket, *, user_id: str):
await websocket.accept()
self.active_connections.add(websocket)
if user_id not in self.user_connections:
self.user_connections[user_id] = set()
self.user_connections[user_id].add(websocket)
self._ws_subs.setdefault(websocket, {})
await self._start_notification_subscription(websocket, user_id=user_id)
def disconnect_socket(self, websocket: WebSocket, *, user_id: str):
async def disconnect_socket(self, websocket: WebSocket, *, user_id: str):
self.active_connections.discard(websocket)
for subscribers in self.subscriptions.values():
# Stop SSUBSCRIBE pumps before dropping bookkeeping to avoid leaks.
subs = self._ws_subs.pop(websocket, {})
for sub in subs.values():
await sub.stop()
notif_sub = self._ws_notifications.pop(websocket, None)
if notif_sub is not None:
await notif_sub.stop()
for channel_key, subscribers in list(self.subscriptions.items()):
subscribers.discard(websocket)
user_conns = self.user_connections.get(user_id)
if user_conns is not None:
user_conns.discard(websocket)
if not user_conns:
self.user_connections.pop(user_id, None)
if not subscribers:
self.subscriptions.pop(channel_key, None)
async def subscribe_graph_exec(
self, *, user_id: str, graph_exec_id: str, websocket: WebSocket
) -> str:
return await self._subscribe(
_graph_exec_channel_key(user_id, graph_exec_id=graph_exec_id), websocket
# Hash-tagged channel needs graph_id; resolve once per subscribe.
meta = await get_graph_execution_meta(user_id, graph_exec_id)
if meta is None:
raise ValueError(
f"graph_exec #{graph_exec_id} not found for user #{user_id}"
)
channel_key = graph_exec_channel_key(user_id, graph_exec_id=graph_exec_id)
full_channel = event_bus_channel(
exec_channel(user_id, meta.graph_id, graph_exec_id)
)
await self._open_subscription(websocket, channel_key, full_channel)
return channel_key
async def subscribe_graph_execs(
self, *, user_id: str, graph_id: str, websocket: WebSocket
) -> str:
return await self._subscribe(
_graph_execs_channel_key(user_id, graph_id=graph_id), websocket
)
channel_key = _graph_execs_channel_key(user_id, graph_id=graph_id)
full_channel = event_bus_channel(graph_all_channel(user_id, graph_id))
await self._open_subscription(websocket, channel_key, full_channel)
return channel_key
async def unsubscribe_graph_exec(
self, *, user_id: str, graph_exec_id: str, websocket: WebSocket
) -> str | None:
return await self._unsubscribe(
_graph_exec_channel_key(user_id, graph_exec_id=graph_exec_id), websocket
)
channel_key = graph_exec_channel_key(user_id, graph_exec_id=graph_exec_id)
return await self._close_subscription(websocket, channel_key)
async def unsubscribe_graph_execs(
self, *, user_id: str, graph_id: str, websocket: WebSocket
) -> str | None:
return await self._unsubscribe(
_graph_execs_channel_key(user_id, graph_id=graph_id), websocket
)
channel_key = _graph_execs_channel_key(user_id, graph_id=graph_id)
return await self._close_subscription(websocket, channel_key)
async def send_execution_update(
self, exec_event: GraphExecutionEvent | NodeExecutionEvent
) -> int:
graph_exec_id = (
exec_event.id
if isinstance(exec_event, GraphExecutionEvent)
else exec_event.graph_exec_id
)
async def _open_subscription(
self, websocket: WebSocket, channel_key: str, full_channel: str
) -> None:
self.subscriptions.setdefault(channel_key, set()).add(websocket)
per_ws = self._ws_subs.setdefault(websocket, {})
if channel_key in per_ws:
return
sub = _Subscription(full_channel)
n_sent = 0
async def on_message(data: Optional[bytes | str]) -> None:
await self._forward_exec_event(websocket, channel_key, data)
channels: set[str] = {
# Send update to listeners for this graph execution
_graph_exec_channel_key(exec_event.user_id, graph_exec_id=graph_exec_id)
}
if isinstance(exec_event, GraphExecutionEvent):
# Send update to listeners for all executions of this graph
channels.add(
_graph_execs_channel_key(
exec_event.user_id, graph_id=exec_event.graph_id
)
)
await sub.start(on_message)
per_ws[channel_key] = sub
for channel in channels.intersection(self.subscriptions.keys()):
message = WSMessage(
method=_EVENT_TYPE_TO_METHOD_MAP[exec_event.event_type],
channel=channel,
data=exec_event.model_dump(),
).model_dump_json()
for connection in self.subscriptions[channel]:
await connection.send_text(message)
n_sent += 1
return n_sent
async def send_notification(
self, *, user_id: str, payload: NotificationPayload
) -> int:
"""Send a notification to all websocket connections belonging to a user."""
message = WSMessage(
method=WSMethod.NOTIFICATION,
data=payload.model_dump(),
).model_dump_json()
connections = tuple(self.user_connections.get(user_id, set()))
if not connections:
return 0
await asyncio.gather(
*(connection.send_text(message) for connection in connections),
return_exceptions=True,
)
return len(connections)
async def _subscribe(self, channel_key: str, websocket: WebSocket) -> str:
if channel_key not in self.subscriptions:
self.subscriptions[channel_key] = set()
self.subscriptions[channel_key].add(websocket)
async def _close_subscription(
self, websocket: WebSocket, channel_key: str
) -> str | None:
subscribers = self.subscriptions.get(channel_key)
if subscribers is None:
return None
subscribers.discard(websocket)
if not subscribers:
self.subscriptions.pop(channel_key, None)
per_ws = self._ws_subs.get(websocket)
if per_ws and channel_key in per_ws:
sub = per_ws.pop(channel_key)
await sub.stop()
return channel_key
async def _unsubscribe(self, channel_key: str, websocket: WebSocket) -> str | None:
if channel_key in self.subscriptions:
self.subscriptions[channel_key].discard(websocket)
if not self.subscriptions[channel_key]:
del self.subscriptions[channel_key]
return channel_key
return None
async def _forward_exec_event(
self,
websocket: WebSocket,
channel_key: str,
raw_payload: Optional[bytes | str],
) -> None:
if raw_payload is None:
return
# Unwrap the `_EventPayloadWrapper` envelope, then re-wrap as a WS message.
try:
wrapper = (
raw_payload.decode()
if isinstance(raw_payload, (bytes, bytearray))
else raw_payload
)
except Exception:
logger.warning(
"Failed to decode pubsub payload on %s", channel_key, exc_info=True
)
return
try:
parsed = json.loads(wrapper)
event_data = parsed.get("payload")
if not isinstance(event_data, dict):
return
event_type = event_data.get("event_type")
method = _EVENT_TYPE_TO_METHOD_MAP.get(ExecutionEventType(event_type))
if method is None:
return
message = WSMessage(
method=method,
channel=channel_key,
data=event_data,
).model_dump_json()
await websocket.send_text(message)
except Exception as e:
if _is_ws_close_race(e, websocket):
logger.debug("Dropped exec event on closed WS for %s", channel_key)
return
logger.exception("Failed to forward exec event on %s", channel_key)
async def _start_notification_subscription(
self, websocket: WebSocket, *, user_id: str
) -> None:
full_channel = _notification_bus_channel(user_id)
sub = _Subscription(full_channel)
async def on_message(data: Optional[bytes | str]) -> None:
await self._forward_notification(websocket, user_id, data)
try:
await sub.start(on_message)
except Exception:
logger.exception(
"Failed to open notification SSUBSCRIBE for user=%s", user_id
)
return
self._ws_notifications[websocket] = sub
async def _forward_notification(
self,
websocket: WebSocket,
user_id: str,
raw_payload: Optional[bytes | str],
) -> None:
if raw_payload is None:
return
try:
wrapper_json = (
raw_payload.decode()
if isinstance(raw_payload, (bytes, bytearray))
else raw_payload
)
parsed = json.loads(wrapper_json)
inner = parsed.get("payload") if isinstance(parsed, dict) else None
if not isinstance(inner, dict):
return
event = NotificationEvent.model_validate(inner)
except Exception:
logger.warning(
"Failed to parse notification payload for user=%s",
user_id,
exc_info=True,
)
return
# Defense in depth against cross-user payloads.
if event.user_id != user_id:
return
message = WSMessage(
method=WSMethod.NOTIFICATION,
data=event.payload.model_dump(),
).model_dump_json()
try:
await websocket.send_text(message)
except Exception as e:
if _is_ws_close_race(e, websocket):
logger.debug("Dropped notification on closed WS for user=%s", user_id)
return
logger.warning(
"Failed to deliver notification to WS for user=%s",
user_id,
exc_info=True,
)
def _graph_exec_channel_key(user_id: str, *, graph_exec_id: str) -> str:
def graph_exec_channel_key(user_id: str, *, graph_exec_id: str) -> str:
return f"{user_id}|graph_exec#{graph_exec_id}"

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@@ -0,0 +1,386 @@
"""ConnectionManager integration over the live 3-shard Redis cluster:
SSUBSCRIBE → SPUBLISH → WebSocket forwarding with no Redis mocks. Skips
when the cluster is unreachable."""
import asyncio
import json
from datetime import datetime, timezone
from unittest.mock import AsyncMock
from uuid import uuid4
import pytest
from fastapi import WebSocket
import backend.data.redis_client as redis_client
from backend.api.conn_manager import (
ConnectionManager,
_graph_execs_channel_key,
event_bus_channel,
graph_exec_channel_key,
)
from backend.api.model import WSMethod
from backend.data.execution import (
ExecutionStatus,
GraphExecutionEvent,
GraphExecutionMeta,
NodeExecutionEvent,
exec_channel,
graph_all_channel,
)
def _has_live_cluster() -> bool:
try:
c = redis_client.connect()
except Exception: # noqa: BLE001 — any connect failure → skip
return False
try:
c.close()
except Exception:
pass
return True
pytestmark = pytest.mark.skipif(
not _has_live_cluster(),
reason="local redis cluster not reachable; skip conn_manager integration",
)
def _meta(user_id: str, graph_id: str, graph_exec_id: str) -> GraphExecutionMeta:
"""Build a minimal GraphExecutionMeta for ``subscribe_graph_exec`` to use."""
return GraphExecutionMeta(
id=graph_exec_id,
user_id=user_id,
graph_id=graph_id,
graph_version=1,
inputs=None,
credential_inputs=None,
nodes_input_masks=None,
preset_id=None,
status=ExecutionStatus.RUNNING,
started_at=datetime.now(tz=timezone.utc),
ended_at=None,
stats=GraphExecutionMeta.Stats(),
)
def _node_event_payload(
*, user_id: str, graph_id: str, graph_exec_id: str, marker: str
) -> bytes:
"""Wire-format a NodeExecutionEvent the way RedisExecutionEventBus would."""
inner = NodeExecutionEvent(
user_id=user_id,
graph_id=graph_id,
graph_version=1,
graph_exec_id=graph_exec_id,
node_exec_id=f"node-exec-{marker}",
node_id="node-1",
block_id="block-1",
status=ExecutionStatus.COMPLETED,
input_data={"in": marker},
output_data={"out": [marker]},
add_time=datetime.now(tz=timezone.utc),
queue_time=None,
start_time=datetime.now(tz=timezone.utc),
end_time=datetime.now(tz=timezone.utc),
).model_dump(mode="json")
return json.dumps({"payload": inner}).encode()
def _graph_event_payload(
*, user_id: str, graph_id: str, graph_exec_id: str, marker: str
) -> bytes:
inner = GraphExecutionEvent(
id=graph_exec_id,
user_id=user_id,
graph_id=graph_id,
graph_version=1,
preset_id=None,
status=ExecutionStatus.COMPLETED,
started_at=datetime.now(tz=timezone.utc),
ended_at=datetime.now(tz=timezone.utc),
stats=GraphExecutionEvent.Stats(
cost=0,
duration=1.0,
node_exec_time=0.5,
node_exec_count=1,
),
inputs={"x": marker},
credential_inputs=None,
nodes_input_masks=None,
outputs={"y": [marker]},
).model_dump(mode="json")
return json.dumps({"payload": inner}).encode()
async def _wait_until(predicate, timeout: float = 5.0, interval: float = 0.05) -> bool:
"""Poll ``predicate()`` until truthy or timeout — used to wait for pubsub."""
deadline = asyncio.get_event_loop().time() + timeout
while asyncio.get_event_loop().time() < deadline:
if predicate():
return True
await asyncio.sleep(interval)
return False
@pytest.mark.asyncio
async def test_two_clients_get_independent_ssubscribes_on_right_shards(
monkeypatch,
) -> None:
"""Two WS clients on different graph_exec_ids each receive ONLY their
own publish, even when the channels land on different shards."""
user_id = "user-conn-int-1"
graph_a = f"graph-a-{uuid4().hex[:8]}"
graph_b = f"graph-b-{uuid4().hex[:8]}"
exec_a = f"exec-a-{uuid4().hex[:8]}"
exec_b = f"exec-b-{uuid4().hex[:8]}"
# Stub Prisma lookup so tests don't need a DB.
async def _fake_meta(_uid, gex_id):
return _meta(user_id, graph_a if gex_id == exec_a else graph_b, gex_id)
monkeypatch.setattr("backend.api.conn_manager.get_graph_execution_meta", _fake_meta)
cm = ConnectionManager()
ws_a: AsyncMock = AsyncMock(spec=WebSocket)
ws_b: AsyncMock = AsyncMock(spec=WebSocket)
sent_a: list[str] = []
sent_b: list[str] = []
ws_a.send_text = AsyncMock(side_effect=lambda m: sent_a.append(m))
ws_b.send_text = AsyncMock(side_effect=lambda m: sent_b.append(m))
redis_client.get_redis.cache_clear()
cluster = redis_client.get_redis()
try:
await cm.subscribe_graph_exec(
user_id=user_id, graph_exec_id=exec_a, websocket=ws_a
)
await cm.subscribe_graph_exec(
user_id=user_id, graph_exec_id=exec_b, websocket=ws_b
)
# Let SSUBSCRIBE settle on each shard.
await asyncio.sleep(0.2)
# Publish to each per-exec channel.
chan_a = event_bus_channel(exec_channel(user_id, graph_a, exec_a))
chan_b = event_bus_channel(exec_channel(user_id, graph_b, exec_b))
cluster.spublish(
chan_a,
_node_event_payload(
user_id=user_id,
graph_id=graph_a,
graph_exec_id=exec_a,
marker="A",
).decode(),
)
cluster.spublish(
chan_b,
_node_event_payload(
user_id=user_id,
graph_id=graph_b,
graph_exec_id=exec_b,
marker="B",
).decode(),
)
delivered = await _wait_until(lambda: sent_a and sent_b, timeout=5.0)
assert delivered, f"timeout: sent_a={sent_a!r} sent_b={sent_b!r}"
msg_a = json.loads(sent_a[0])
msg_b = json.loads(sent_b[0])
assert msg_a["channel"] == graph_exec_channel_key(user_id, graph_exec_id=exec_a)
assert msg_b["channel"] == graph_exec_channel_key(user_id, graph_exec_id=exec_b)
assert msg_a["data"]["graph_exec_id"] == exec_a
assert msg_b["data"]["graph_exec_id"] == exec_b
# No cross-talk: each socket got exactly one message.
assert len(sent_a) == 1 and len(sent_b) == 1
finally:
await cm.disconnect_socket(ws_a, user_id=user_id)
await cm.disconnect_socket(ws_b, user_id=user_id)
redis_client.disconnect()
@pytest.mark.asyncio
async def test_aggregate_channel_receives_per_exec_publishes(monkeypatch) -> None:
"""A subscriber on the ``graph_execs`` aggregate channel must receive the
GraphExecutionEvent published to the ``/all`` channel — even though
per-exec events go to a different channel."""
user_id = "user-conn-int-2"
graph_id = f"graph-{uuid4().hex[:8]}"
exec_id = f"exec-{uuid4().hex[:8]}"
async def _fake_meta(_uid, gex_id):
return _meta(user_id, graph_id, gex_id)
monkeypatch.setattr("backend.api.conn_manager.get_graph_execution_meta", _fake_meta)
cm = ConnectionManager()
ws_agg: AsyncMock = AsyncMock(spec=WebSocket)
ws_per: AsyncMock = AsyncMock(spec=WebSocket)
sent_agg: list[str] = []
sent_per: list[str] = []
ws_agg.send_text = AsyncMock(side_effect=lambda m: sent_agg.append(m))
ws_per.send_text = AsyncMock(side_effect=lambda m: sent_per.append(m))
redis_client.get_redis.cache_clear()
cluster = redis_client.get_redis()
try:
await cm.subscribe_graph_execs(
user_id=user_id, graph_id=graph_id, websocket=ws_agg
)
await cm.subscribe_graph_exec(
user_id=user_id, graph_exec_id=exec_id, websocket=ws_per
)
await asyncio.sleep(0.2)
# The eventbus publishes the same event to both channels — replicate.
chan_per = event_bus_channel(exec_channel(user_id, graph_id, exec_id))
chan_all = event_bus_channel(graph_all_channel(user_id, graph_id))
payload = _graph_event_payload(
user_id=user_id,
graph_id=graph_id,
graph_exec_id=exec_id,
marker="agg",
).decode()
cluster.spublish(chan_per, payload)
cluster.spublish(chan_all, payload)
delivered = await _wait_until(lambda: sent_agg and sent_per, timeout=5.0)
assert delivered, f"sent_agg={sent_agg!r} sent_per={sent_per!r}"
agg_msg = json.loads(sent_agg[0])
per_msg = json.loads(sent_per[0])
# Aggregate subscriber's channel key is the per-graph executions key.
assert agg_msg["channel"] == _graph_execs_channel_key(
user_id, graph_id=graph_id
)
assert per_msg["channel"] == graph_exec_channel_key(
user_id, graph_exec_id=exec_id
)
assert agg_msg["method"] == WSMethod.GRAPH_EXECUTION_EVENT.value
finally:
await cm.disconnect_socket(ws_agg, user_id=user_id)
await cm.disconnect_socket(ws_per, user_id=user_id)
redis_client.disconnect()
@pytest.mark.asyncio
async def test_disconnect_unsubscribes_and_drops_future_publishes(monkeypatch) -> None:
"""After ``disconnect_socket`` runs, a subsequent SPUBLISH must NOT reach
the dead websocket — exercises the SUNSUBSCRIBE + bookkeeping cleanup."""
user_id = "user-conn-int-3"
graph_id = f"graph-{uuid4().hex[:8]}"
exec_id = f"exec-{uuid4().hex[:8]}"
async def _fake_meta(_uid, gex_id):
return _meta(user_id, graph_id, gex_id)
monkeypatch.setattr("backend.api.conn_manager.get_graph_execution_meta", _fake_meta)
cm = ConnectionManager()
ws: AsyncMock = AsyncMock(spec=WebSocket)
sent: list[str] = []
ws.send_text = AsyncMock(side_effect=lambda m: sent.append(m))
redis_client.get_redis.cache_clear()
cluster = redis_client.get_redis()
chan = event_bus_channel(exec_channel(user_id, graph_id, exec_id))
payload = _node_event_payload(
user_id=user_id, graph_id=graph_id, graph_exec_id=exec_id, marker="live"
).decode()
try:
await cm.subscribe_graph_exec(
user_id=user_id, graph_exec_id=exec_id, websocket=ws
)
await asyncio.sleep(0.15)
# First publish — must reach the socket.
cluster.spublish(chan, payload)
delivered = await _wait_until(lambda: bool(sent), timeout=5.0)
assert delivered
assert len(sent) == 1
# Disconnect → SUNSUBSCRIBE + bookkeeping cleared.
await cm.disconnect_socket(ws, user_id=user_id)
# Pump cancellation may drain in-flight messages; wait for it.
await asyncio.sleep(0.2)
# Channel bookkeeping must be gone.
assert (
graph_exec_channel_key(user_id, graph_exec_id=exec_id)
not in cm.subscriptions
)
assert ws not in cm._ws_subs
# Second publish — must NOT reach the (already-disconnected) socket.
cluster.spublish(
chan,
_node_event_payload(
user_id=user_id,
graph_id=graph_id,
graph_exec_id=exec_id,
marker="post-disconnect",
).decode(),
)
await asyncio.sleep(0.5)
# Still only the one pre-disconnect message.
assert len(sent) == 1
finally:
redis_client.disconnect()
@pytest.mark.asyncio
async def test_slow_consumer_receives_all_events_without_loss(monkeypatch) -> None:
"""Burst-publish many SPUBLISHes; assert every one reaches the subscriber
in order — guards against drops/reorderings in the pubsub pump."""
user_id = "user-conn-int-4"
graph_id = f"graph-{uuid4().hex[:8]}"
exec_id = f"exec-{uuid4().hex[:8]}"
n_events = 100
async def _fake_meta(_uid, gex_id):
return _meta(user_id, graph_id, gex_id)
monkeypatch.setattr("backend.api.conn_manager.get_graph_execution_meta", _fake_meta)
cm = ConnectionManager()
ws: AsyncMock = AsyncMock(spec=WebSocket)
sent: list[str] = []
ws.send_text = AsyncMock(side_effect=lambda m: sent.append(m))
redis_client.get_redis.cache_clear()
cluster = redis_client.get_redis()
chan = event_bus_channel(exec_channel(user_id, graph_id, exec_id))
try:
await cm.subscribe_graph_exec(
user_id=user_id, graph_exec_id=exec_id, websocket=ws
)
await asyncio.sleep(0.2)
# Burst-publish n_events without yielding to the pump.
for i in range(n_events):
cluster.spublish(
chan,
_node_event_payload(
user_id=user_id,
graph_id=graph_id,
graph_exec_id=exec_id,
marker=f"m{i}",
).decode(),
)
delivered = await _wait_until(
lambda: len(sent) >= n_events, timeout=15.0, interval=0.1
)
assert delivered, f"only delivered {len(sent)}/{n_events}"
# Validate ordering — Redis pub/sub is FIFO per channel.
markers = [json.loads(m)["data"]["input_data"]["in"] for m in sent[:n_events]]
assert markers == [f"m{i}" for i in range(n_events)]
finally:
await cm.disconnect_socket(ws, user_id=user_id)
redis_client.disconnect()

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import asyncio
import logging
from typing import List
from autogpt_libs.auth import requires_admin_user
from autogpt_libs.auth.models import User as AuthUser
from fastapi import APIRouter, HTTPException, Security
from prisma.enums import AgentExecutionStatus
from pydantic import BaseModel
from backend.api.features.admin.model import (
AgentDiagnosticsResponse,
ExecutionDiagnosticsResponse,
)
from backend.data.diagnostics import (
FailedExecutionDetail,
OrphanedScheduleDetail,
RunningExecutionDetail,
ScheduleDetail,
ScheduleHealthMetrics,
cleanup_all_stuck_queued_executions,
cleanup_orphaned_executions_bulk,
cleanup_orphaned_schedules_bulk,
get_agent_diagnostics,
get_all_orphaned_execution_ids,
get_all_schedules_details,
get_all_stuck_queued_execution_ids,
get_execution_diagnostics,
get_failed_executions_count,
get_failed_executions_details,
get_invalid_executions_details,
get_long_running_executions_details,
get_orphaned_executions_details,
get_orphaned_schedules_details,
get_running_executions_details,
get_schedule_health_metrics,
get_stuck_queued_executions_details,
stop_all_long_running_executions,
)
from backend.data.execution import get_graph_executions
from backend.executor.utils import add_graph_execution, stop_graph_execution
logger = logging.getLogger(__name__)
router = APIRouter(
prefix="/admin",
tags=["diagnostics", "admin"],
dependencies=[Security(requires_admin_user)],
)
class RunningExecutionsListResponse(BaseModel):
"""Response model for list of running executions"""
executions: List[RunningExecutionDetail]
total: int
class FailedExecutionsListResponse(BaseModel):
"""Response model for list of failed executions"""
executions: List[FailedExecutionDetail]
total: int
class StopExecutionRequest(BaseModel):
"""Request model for stopping a single execution"""
execution_id: str
class StopExecutionsRequest(BaseModel):
"""Request model for stopping multiple executions"""
execution_ids: List[str]
class StopExecutionResponse(BaseModel):
"""Response model for stop execution operations"""
success: bool
stopped_count: int = 0
message: str
class RequeueExecutionResponse(BaseModel):
"""Response model for requeue execution operations"""
success: bool
requeued_count: int = 0
message: str
@router.get(
"/diagnostics/executions",
response_model=ExecutionDiagnosticsResponse,
summary="Get Execution Diagnostics",
)
async def get_execution_diagnostics_endpoint():
"""
Get comprehensive diagnostic information about execution status.
Returns all execution metrics including:
- Current state (running, queued)
- Orphaned executions (>24h old, likely not in executor)
- Failure metrics (1h, 24h, rate)
- Long-running detection (stuck >1h, >24h)
- Stuck queued detection
- Throughput metrics (completions/hour)
- RabbitMQ queue depths
"""
logger.info("Getting execution diagnostics")
diagnostics = await get_execution_diagnostics()
response = ExecutionDiagnosticsResponse(
running_executions=diagnostics.running_count,
queued_executions_db=diagnostics.queued_db_count,
queued_executions_rabbitmq=diagnostics.rabbitmq_queue_depth,
cancel_queue_depth=diagnostics.cancel_queue_depth,
orphaned_running=diagnostics.orphaned_running,
orphaned_queued=diagnostics.orphaned_queued,
failed_count_1h=diagnostics.failed_count_1h,
failed_count_24h=diagnostics.failed_count_24h,
failure_rate_24h=diagnostics.failure_rate_24h,
stuck_running_24h=diagnostics.stuck_running_24h,
stuck_running_1h=diagnostics.stuck_running_1h,
oldest_running_hours=diagnostics.oldest_running_hours,
stuck_queued_1h=diagnostics.stuck_queued_1h,
queued_never_started=diagnostics.queued_never_started,
invalid_queued_with_start=diagnostics.invalid_queued_with_start,
invalid_running_without_start=diagnostics.invalid_running_without_start,
completed_1h=diagnostics.completed_1h,
completed_24h=diagnostics.completed_24h,
throughput_per_hour=diagnostics.throughput_per_hour,
timestamp=diagnostics.timestamp,
)
logger.info(
f"Execution diagnostics: running={diagnostics.running_count}, "
f"queued_db={diagnostics.queued_db_count}, "
f"orphaned={diagnostics.orphaned_running + diagnostics.orphaned_queued}, "
f"failed_24h={diagnostics.failed_count_24h}"
)
return response
@router.get(
"/diagnostics/agents",
response_model=AgentDiagnosticsResponse,
summary="Get Agent Diagnostics",
)
async def get_agent_diagnostics_endpoint():
"""
Get diagnostic information about agents.
Returns:
- agents_with_active_executions: Number of unique agents with running/queued executions
- timestamp: Current timestamp
"""
logger.info("Getting agent diagnostics")
diagnostics = await get_agent_diagnostics()
response = AgentDiagnosticsResponse(
agents_with_active_executions=diagnostics.agents_with_active_executions,
timestamp=diagnostics.timestamp,
)
logger.info(
f"Agent diagnostics: with_active_executions={diagnostics.agents_with_active_executions}"
)
return response
@router.get(
"/diagnostics/executions/running",
response_model=RunningExecutionsListResponse,
summary="List Running Executions",
)
async def list_running_executions(
limit: int = 100,
offset: int = 0,
):
"""
Get detailed list of running and queued executions (recent, likely active).
Args:
limit: Maximum number of executions to return (default 100)
offset: Number of executions to skip (default 0)
Returns:
List of running executions with details
"""
logger.info(f"Listing running executions (limit={limit}, offset={offset})")
executions = await get_running_executions_details(limit=limit, offset=offset)
# Get total count for pagination
diagnostics = await get_execution_diagnostics()
total = diagnostics.running_count + diagnostics.queued_db_count
return RunningExecutionsListResponse(executions=executions, total=total)
@router.get(
"/diagnostics/executions/orphaned",
response_model=RunningExecutionsListResponse,
summary="List Orphaned Executions",
)
async def list_orphaned_executions(
limit: int = 100,
offset: int = 0,
):
"""
Get detailed list of orphaned executions (>24h old, likely not in executor).
Args:
limit: Maximum number of executions to return (default 100)
offset: Number of executions to skip (default 0)
Returns:
List of orphaned executions with details
"""
logger.info(f"Listing orphaned executions (limit={limit}, offset={offset})")
executions = await get_orphaned_executions_details(limit=limit, offset=offset)
# Get total count for pagination
diagnostics = await get_execution_diagnostics()
total = diagnostics.orphaned_running + diagnostics.orphaned_queued
return RunningExecutionsListResponse(executions=executions, total=total)
@router.get(
"/diagnostics/executions/failed",
response_model=FailedExecutionsListResponse,
summary="List Failed Executions",
)
async def list_failed_executions(
limit: int = 100,
offset: int = 0,
hours: int = 24,
):
"""
Get detailed list of failed executions.
Args:
limit: Maximum number of executions to return (default 100)
offset: Number of executions to skip (default 0)
hours: Number of hours to look back (default 24)
Returns:
List of failed executions with error details
"""
logger.info(
f"Listing failed executions (limit={limit}, offset={offset}, hours={hours})"
)
executions = await get_failed_executions_details(
limit=limit, offset=offset, hours=hours
)
# Get total count for pagination
# Always count actual total for given hours parameter
total = await get_failed_executions_count(hours=hours)
return FailedExecutionsListResponse(executions=executions, total=total)
@router.get(
"/diagnostics/executions/long-running",
response_model=RunningExecutionsListResponse,
summary="List Long-Running Executions",
)
async def list_long_running_executions(
limit: int = 100,
offset: int = 0,
):
"""
Get detailed list of long-running executions (RUNNING status >24h).
Args:
limit: Maximum number of executions to return (default 100)
offset: Number of executions to skip (default 0)
Returns:
List of long-running executions with details
"""
logger.info(f"Listing long-running executions (limit={limit}, offset={offset})")
executions = await get_long_running_executions_details(limit=limit, offset=offset)
# Get total count for pagination
diagnostics = await get_execution_diagnostics()
total = diagnostics.stuck_running_24h
return RunningExecutionsListResponse(executions=executions, total=total)
@router.get(
"/diagnostics/executions/stuck-queued",
response_model=RunningExecutionsListResponse,
summary="List Stuck Queued Executions",
)
async def list_stuck_queued_executions(
limit: int = 100,
offset: int = 0,
):
"""
Get detailed list of stuck queued executions (QUEUED >1h, never started).
Args:
limit: Maximum number of executions to return (default 100)
offset: Number of executions to skip (default 0)
Returns:
List of stuck queued executions with details
"""
logger.info(f"Listing stuck queued executions (limit={limit}, offset={offset})")
executions = await get_stuck_queued_executions_details(limit=limit, offset=offset)
# Get total count for pagination
diagnostics = await get_execution_diagnostics()
total = diagnostics.stuck_queued_1h
return RunningExecutionsListResponse(executions=executions, total=total)
@router.get(
"/diagnostics/executions/invalid",
response_model=RunningExecutionsListResponse,
summary="List Invalid Executions",
)
async def list_invalid_executions(
limit: int = 100,
offset: int = 0,
):
"""
Get detailed list of executions in invalid states (READ-ONLY).
Invalid states indicate data corruption and require manual investigation:
- QUEUED but has startedAt (impossible - can't start while queued)
- RUNNING but no startedAt (impossible - can't run without starting)
⚠️ NO BULK ACTIONS PROVIDED - These need case-by-case investigation.
Each invalid execution likely has a different root cause (crashes, race conditions,
DB corruption). Investigate the execution history and logs to determine appropriate
action (manual cleanup, status fix, or leave as-is if system recovered).
Args:
limit: Maximum number of executions to return (default 100)
offset: Number of executions to skip (default 0)
Returns:
List of invalid state executions with details
"""
logger.info(f"Listing invalid state executions (limit={limit}, offset={offset})")
executions = await get_invalid_executions_details(limit=limit, offset=offset)
# Get total count for pagination
diagnostics = await get_execution_diagnostics()
total = (
diagnostics.invalid_queued_with_start
+ diagnostics.invalid_running_without_start
)
return RunningExecutionsListResponse(executions=executions, total=total)
@router.post(
"/diagnostics/executions/requeue",
response_model=RequeueExecutionResponse,
summary="Requeue Stuck Execution",
)
async def requeue_single_execution(
request: StopExecutionRequest, # Reuse same request model (has execution_id)
user: AuthUser = Security(requires_admin_user),
):
"""
Requeue a stuck QUEUED execution (admin only).
Uses add_graph_execution with existing graph_exec_id to requeue.
⚠️ WARNING: Only use for stuck executions. This will re-execute and may cost credits.
Args:
request: Contains execution_id to requeue
Returns:
Success status and message
"""
logger.info(f"Admin {user.user_id} requeueing execution {request.execution_id}")
# Get the execution (validation - must be QUEUED)
executions = await get_graph_executions(
graph_exec_id=request.execution_id,
statuses=[AgentExecutionStatus.QUEUED],
)
if not executions:
raise HTTPException(
status_code=404,
detail="Execution not found or not in QUEUED status",
)
execution = executions[0]
# Use add_graph_execution in requeue mode
await add_graph_execution(
graph_id=execution.graph_id,
user_id=execution.user_id,
graph_version=execution.graph_version,
graph_exec_id=request.execution_id, # Requeue existing execution
)
return RequeueExecutionResponse(
success=True,
requeued_count=1,
message="Execution requeued successfully",
)
@router.post(
"/diagnostics/executions/requeue-bulk",
response_model=RequeueExecutionResponse,
summary="Requeue Multiple Stuck Executions",
)
async def requeue_multiple_executions(
request: StopExecutionsRequest, # Reuse same request model (has execution_ids)
user: AuthUser = Security(requires_admin_user),
):
"""
Requeue multiple stuck QUEUED executions (admin only).
Uses add_graph_execution with existing graph_exec_id to requeue.
⚠️ WARNING: Only use for stuck executions. This will re-execute and may cost credits.
Args:
request: Contains list of execution_ids to requeue
Returns:
Number of executions requeued and success message
"""
logger.info(
f"Admin {user.user_id} requeueing {len(request.execution_ids)} executions"
)
# Get executions by ID list (must be QUEUED)
executions = await get_graph_executions(
execution_ids=request.execution_ids,
statuses=[AgentExecutionStatus.QUEUED],
)
if not executions:
return RequeueExecutionResponse(
success=False,
requeued_count=0,
message="No QUEUED executions found to requeue",
)
# Requeue all executions in parallel using add_graph_execution
async def requeue_one(exec) -> bool:
try:
await add_graph_execution(
graph_id=exec.graph_id,
user_id=exec.user_id,
graph_version=exec.graph_version,
graph_exec_id=exec.id, # Requeue existing
)
return True
except Exception as e:
logger.error(f"Failed to requeue {exec.id}: {e}")
return False
results = await asyncio.gather(
*[requeue_one(exec) for exec in executions], return_exceptions=False
)
requeued_count = sum(1 for success in results if success)
return RequeueExecutionResponse(
success=requeued_count > 0,
requeued_count=requeued_count,
message=f"Requeued {requeued_count} of {len(request.execution_ids)} executions",
)
@router.post(
"/diagnostics/executions/stop",
response_model=StopExecutionResponse,
summary="Stop Single Execution",
)
async def stop_single_execution(
request: StopExecutionRequest,
user: AuthUser = Security(requires_admin_user),
):
"""
Stop a single execution (admin only).
Uses robust stop_graph_execution which cascades to children and waits for termination.
Args:
request: Contains execution_id to stop
Returns:
Success status and message
"""
logger.info(f"Admin {user.user_id} stopping execution {request.execution_id}")
# Get the execution to find its owner user_id (required by stop_graph_execution)
executions = await get_graph_executions(
graph_exec_id=request.execution_id,
)
if not executions:
raise HTTPException(status_code=404, detail="Execution not found")
execution = executions[0]
# Use robust stop_graph_execution (cascades to children, waits for termination)
await stop_graph_execution(
user_id=execution.user_id,
graph_exec_id=request.execution_id,
wait_timeout=15.0,
cascade=True,
)
return StopExecutionResponse(
success=True,
stopped_count=1,
message="Execution stopped successfully",
)
@router.post(
"/diagnostics/executions/stop-bulk",
response_model=StopExecutionResponse,
summary="Stop Multiple Executions",
)
async def stop_multiple_executions(
request: StopExecutionsRequest,
user: AuthUser = Security(requires_admin_user),
):
"""
Stop multiple active executions (admin only).
Uses robust stop_graph_execution which cascades to children and waits for termination.
Args:
request: Contains list of execution_ids to stop
Returns:
Number of executions stopped and success message
"""
logger.info(
f"Admin {user.user_id} stopping {len(request.execution_ids)} executions"
)
# Get executions by ID list
executions = await get_graph_executions(
execution_ids=request.execution_ids,
)
if not executions:
return StopExecutionResponse(
success=False,
stopped_count=0,
message="No executions found",
)
# Stop all executions in parallel using robust stop_graph_execution
async def stop_one(exec) -> bool:
try:
await stop_graph_execution(
user_id=exec.user_id,
graph_exec_id=exec.id,
wait_timeout=15.0,
cascade=True,
)
return True
except Exception as e:
logger.error(f"Failed to stop execution {exec.id}: {e}")
return False
results = await asyncio.gather(
*[stop_one(exec) for exec in executions], return_exceptions=False
)
stopped_count = sum(1 for success in results if success)
return StopExecutionResponse(
success=stopped_count > 0,
stopped_count=stopped_count,
message=f"Stopped {stopped_count} of {len(request.execution_ids)} executions",
)
@router.post(
"/diagnostics/executions/cleanup-orphaned",
response_model=StopExecutionResponse,
summary="Cleanup Orphaned Executions",
)
async def cleanup_orphaned_executions(
request: StopExecutionsRequest,
user: AuthUser = Security(requires_admin_user),
):
"""
Cleanup orphaned executions by directly updating DB status (admin only).
For executions in DB but not actually running in executor (old/stale records).
Args:
request: Contains list of execution_ids to cleanup
Returns:
Number of executions cleaned up and success message
"""
logger.info(
f"Admin {user.user_id} cleaning up {len(request.execution_ids)} orphaned executions"
)
cleaned_count = await cleanup_orphaned_executions_bulk(
request.execution_ids, user.user_id
)
return StopExecutionResponse(
success=cleaned_count > 0,
stopped_count=cleaned_count,
message=f"Cleaned up {cleaned_count} of {len(request.execution_ids)} orphaned executions",
)
# ============================================================================
# SCHEDULE DIAGNOSTICS ENDPOINTS
# ============================================================================
class SchedulesListResponse(BaseModel):
"""Response model for list of schedules"""
schedules: List[ScheduleDetail]
total: int
class OrphanedSchedulesListResponse(BaseModel):
"""Response model for list of orphaned schedules"""
schedules: List[OrphanedScheduleDetail]
total: int
class ScheduleCleanupRequest(BaseModel):
"""Request model for cleaning up schedules"""
schedule_ids: List[str]
class ScheduleCleanupResponse(BaseModel):
"""Response model for schedule cleanup operations"""
success: bool
deleted_count: int = 0
message: str
@router.get(
"/diagnostics/schedules",
response_model=ScheduleHealthMetrics,
summary="Get Schedule Diagnostics",
)
async def get_schedule_diagnostics_endpoint():
"""
Get comprehensive diagnostic information about schedule health.
Returns schedule metrics including:
- Total schedules (user vs system)
- Orphaned schedules by category
- Upcoming executions
"""
logger.info("Getting schedule diagnostics")
diagnostics = await get_schedule_health_metrics()
logger.info(
f"Schedule diagnostics: total={diagnostics.total_schedules}, "
f"user={diagnostics.user_schedules}, "
f"orphaned={diagnostics.total_orphaned}"
)
return diagnostics
@router.get(
"/diagnostics/schedules/all",
response_model=SchedulesListResponse,
summary="List All User Schedules",
)
async def list_all_schedules(
limit: int = 100,
offset: int = 0,
):
"""
Get detailed list of all user schedules (excludes system monitoring jobs).
Args:
limit: Maximum number of schedules to return (default 100)
offset: Number of schedules to skip (default 0)
Returns:
List of schedules with details
"""
logger.info(f"Listing all schedules (limit={limit}, offset={offset})")
schedules = await get_all_schedules_details(limit=limit, offset=offset)
# Get total count
diagnostics = await get_schedule_health_metrics()
total = diagnostics.user_schedules
return SchedulesListResponse(schedules=schedules, total=total)
@router.get(
"/diagnostics/schedules/orphaned",
response_model=OrphanedSchedulesListResponse,
summary="List Orphaned Schedules",
)
async def list_orphaned_schedules():
"""
Get detailed list of orphaned schedules with orphan reasons.
Returns:
List of orphaned schedules categorized by orphan type
"""
logger.info("Listing orphaned schedules")
schedules = await get_orphaned_schedules_details()
return OrphanedSchedulesListResponse(schedules=schedules, total=len(schedules))
@router.post(
"/diagnostics/schedules/cleanup-orphaned",
response_model=ScheduleCleanupResponse,
summary="Cleanup Orphaned Schedules",
)
async def cleanup_orphaned_schedules(
request: ScheduleCleanupRequest,
user: AuthUser = Security(requires_admin_user),
):
"""
Cleanup orphaned schedules by deleting from scheduler (admin only).
Args:
request: Contains list of schedule_ids to delete
Returns:
Number of schedules deleted and success message
"""
logger.info(
f"Admin {user.user_id} cleaning up {len(request.schedule_ids)} orphaned schedules"
)
deleted_count = await cleanup_orphaned_schedules_bulk(
request.schedule_ids, user.user_id
)
return ScheduleCleanupResponse(
success=deleted_count > 0,
deleted_count=deleted_count,
message=f"Deleted {deleted_count} of {len(request.schedule_ids)} orphaned schedules",
)
@router.post(
"/diagnostics/executions/stop-all-long-running",
response_model=StopExecutionResponse,
summary="Stop ALL Long-Running Executions",
)
async def stop_all_long_running_executions_endpoint(
user: AuthUser = Security(requires_admin_user),
):
"""
Stop ALL long-running executions (RUNNING >24h) by sending cancel signals (admin only).
Operates on entire dataset, not limited to pagination.
Returns:
Number of executions stopped and success message
"""
logger.info(f"Admin {user.user_id} stopping ALL long-running executions")
stopped_count = await stop_all_long_running_executions(user.user_id)
return StopExecutionResponse(
success=stopped_count > 0,
stopped_count=stopped_count,
message=f"Stopped {stopped_count} long-running executions",
)
@router.post(
"/diagnostics/executions/cleanup-all-orphaned",
response_model=StopExecutionResponse,
summary="Cleanup ALL Orphaned Executions",
)
async def cleanup_all_orphaned_executions(
user: AuthUser = Security(requires_admin_user),
):
"""
Cleanup ALL orphaned executions (>24h old) by directly updating DB status.
Operates on all executions, not just paginated results.
Returns:
Number of executions cleaned up and success message
"""
logger.info(f"Admin {user.user_id} cleaning up ALL orphaned executions")
# Fetch all orphaned execution IDs
execution_ids = await get_all_orphaned_execution_ids()
if not execution_ids:
return StopExecutionResponse(
success=True,
stopped_count=0,
message="No orphaned executions to cleanup",
)
cleaned_count = await cleanup_orphaned_executions_bulk(execution_ids, user.user_id)
return StopExecutionResponse(
success=cleaned_count > 0,
stopped_count=cleaned_count,
message=f"Cleaned up {cleaned_count} orphaned executions",
)
@router.post(
"/diagnostics/executions/cleanup-all-stuck-queued",
response_model=StopExecutionResponse,
summary="Cleanup ALL Stuck Queued Executions",
)
async def cleanup_all_stuck_queued_executions_endpoint(
user: AuthUser = Security(requires_admin_user),
):
"""
Cleanup ALL stuck queued executions (QUEUED >1h) by updating DB status (admin only).
Operates on entire dataset, not limited to pagination.
Returns:
Number of executions cleaned up and success message
"""
logger.info(f"Admin {user.user_id} cleaning up ALL stuck queued executions")
cleaned_count = await cleanup_all_stuck_queued_executions(user.user_id)
return StopExecutionResponse(
success=cleaned_count > 0,
stopped_count=cleaned_count,
message=f"Cleaned up {cleaned_count} stuck queued executions",
)
@router.post(
"/diagnostics/executions/requeue-all-stuck",
response_model=RequeueExecutionResponse,
summary="Requeue ALL Stuck Queued Executions",
)
async def requeue_all_stuck_executions(
user: AuthUser = Security(requires_admin_user),
):
"""
Requeue ALL stuck queued executions (QUEUED >1h) by publishing to RabbitMQ.
Operates on all executions, not just paginated results.
Uses add_graph_execution with existing graph_exec_id to requeue.
⚠️ WARNING: This will re-execute ALL stuck executions and may cost significant credits.
Returns:
Number of executions requeued and success message
"""
logger.info(f"Admin {user.user_id} requeueing ALL stuck queued executions")
# Fetch all stuck queued execution IDs
execution_ids = await get_all_stuck_queued_execution_ids()
if not execution_ids:
return RequeueExecutionResponse(
success=True,
requeued_count=0,
message="No stuck queued executions to requeue",
)
# Get stuck executions by ID list (must be QUEUED)
executions = await get_graph_executions(
execution_ids=execution_ids,
statuses=[AgentExecutionStatus.QUEUED],
)
# Requeue all in parallel using add_graph_execution
async def requeue_one(exec) -> bool:
try:
await add_graph_execution(
graph_id=exec.graph_id,
user_id=exec.user_id,
graph_version=exec.graph_version,
graph_exec_id=exec.id, # Requeue existing
)
return True
except Exception as e:
logger.error(f"Failed to requeue {exec.id}: {e}")
return False
results = await asyncio.gather(
*[requeue_one(exec) for exec in executions], return_exceptions=False
)
requeued_count = sum(1 for success in results if success)
return RequeueExecutionResponse(
success=requeued_count > 0,
requeued_count=requeued_count,
message=f"Requeued {requeued_count} stuck executions",
)

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from datetime import datetime, timezone
from unittest.mock import AsyncMock
import fastapi
import fastapi.testclient
import pytest
import pytest_mock
from autogpt_libs.auth.jwt_utils import get_jwt_payload
from prisma.enums import AgentExecutionStatus
import backend.api.features.admin.diagnostics_admin_routes as diagnostics_admin_routes
from backend.data.diagnostics import (
AgentDiagnosticsSummary,
ExecutionDiagnosticsSummary,
FailedExecutionDetail,
OrphanedScheduleDetail,
RunningExecutionDetail,
ScheduleDetail,
ScheduleHealthMetrics,
)
from backend.data.execution import GraphExecutionMeta
app = fastapi.FastAPI()
app.include_router(diagnostics_admin_routes.router)
client = fastapi.testclient.TestClient(app)
@pytest.fixture(autouse=True)
def setup_app_admin_auth(mock_jwt_admin):
"""Setup admin auth overrides for all tests in this module"""
app.dependency_overrides[get_jwt_payload] = mock_jwt_admin["get_jwt_payload"]
yield
app.dependency_overrides.clear()
def test_get_execution_diagnostics_success(
mocker: pytest_mock.MockFixture,
):
"""Test fetching execution diagnostics with invalid state detection"""
mock_diagnostics = ExecutionDiagnosticsSummary(
running_count=10,
queued_db_count=5,
rabbitmq_queue_depth=3,
cancel_queue_depth=0,
orphaned_running=2,
orphaned_queued=1,
failed_count_1h=5,
failed_count_24h=20,
failure_rate_24h=0.83,
stuck_running_24h=1,
stuck_running_1h=3,
oldest_running_hours=26.5,
stuck_queued_1h=2,
queued_never_started=1,
invalid_queued_with_start=1, # New invalid state
invalid_running_without_start=1, # New invalid state
completed_1h=50,
completed_24h=1200,
throughput_per_hour=50.0,
timestamp=datetime.now(timezone.utc).isoformat(),
)
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_execution_diagnostics",
return_value=mock_diagnostics,
)
response = client.get("/admin/diagnostics/executions")
assert response.status_code == 200
data = response.json()
# Verify new invalid state fields are included
assert data["invalid_queued_with_start"] == 1
assert data["invalid_running_without_start"] == 1
# Verify all expected fields present
assert "running_executions" in data
assert "orphaned_running" in data
assert "failed_count_24h" in data
def test_list_invalid_executions(
mocker: pytest_mock.MockFixture,
):
"""Test listing executions in invalid states (read-only endpoint)"""
mock_invalid_executions = [
RunningExecutionDetail(
execution_id="exec-invalid-1",
graph_id="graph-123",
graph_name="Test Graph",
graph_version=1,
user_id="user-123",
user_email="test@example.com",
status="QUEUED",
created_at=datetime.now(timezone.utc),
started_at=datetime.now(
timezone.utc
), # QUEUED but has startedAt - INVALID!
queue_status=None,
),
RunningExecutionDetail(
execution_id="exec-invalid-2",
graph_id="graph-456",
graph_name="Another Graph",
graph_version=2,
user_id="user-456",
user_email="user@example.com",
status="RUNNING",
created_at=datetime.now(timezone.utc),
started_at=None, # RUNNING but no startedAt - INVALID!
queue_status=None,
),
]
mock_diagnostics = ExecutionDiagnosticsSummary(
running_count=10,
queued_db_count=5,
rabbitmq_queue_depth=3,
cancel_queue_depth=0,
orphaned_running=0,
orphaned_queued=0,
failed_count_1h=0,
failed_count_24h=0,
failure_rate_24h=0.0,
stuck_running_24h=0,
stuck_running_1h=0,
oldest_running_hours=None,
stuck_queued_1h=0,
queued_never_started=0,
invalid_queued_with_start=1,
invalid_running_without_start=1,
completed_1h=0,
completed_24h=0,
throughput_per_hour=0.0,
timestamp=datetime.now(timezone.utc).isoformat(),
)
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_invalid_executions_details",
return_value=mock_invalid_executions,
)
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_execution_diagnostics",
return_value=mock_diagnostics,
)
response = client.get("/admin/diagnostics/executions/invalid?limit=100&offset=0")
assert response.status_code == 200
data = response.json()
assert data["total"] == 2 # Sum of both invalid state types
assert len(data["executions"]) == 2
# Verify both types of invalid states are returned
assert data["executions"][0]["execution_id"] in [
"exec-invalid-1",
"exec-invalid-2",
]
assert data["executions"][1]["execution_id"] in [
"exec-invalid-1",
"exec-invalid-2",
]
def test_requeue_single_execution_with_add_graph_execution(
mocker: pytest_mock.MockFixture,
admin_user_id: str,
):
"""Test requeueing uses add_graph_execution in requeue mode"""
mock_exec_meta = GraphExecutionMeta(
id="exec-stuck-123",
user_id="user-123",
graph_id="graph-456",
graph_version=1,
inputs=None,
credential_inputs=None,
nodes_input_masks=None,
preset_id=None,
status=AgentExecutionStatus.QUEUED,
started_at=datetime.now(timezone.utc),
ended_at=datetime.now(timezone.utc),
stats=None,
)
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_graph_executions",
return_value=[mock_exec_meta],
)
mock_add_graph_execution = mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.add_graph_execution",
return_value=AsyncMock(),
)
response = client.post(
"/admin/diagnostics/executions/requeue",
json={"execution_id": "exec-stuck-123"},
)
assert response.status_code == 200
data = response.json()
assert data["success"] is True
assert data["requeued_count"] == 1
# Verify it used add_graph_execution in requeue mode
mock_add_graph_execution.assert_called_once()
call_kwargs = mock_add_graph_execution.call_args.kwargs
assert call_kwargs["graph_exec_id"] == "exec-stuck-123" # Requeue mode!
assert call_kwargs["graph_id"] == "graph-456"
assert call_kwargs["user_id"] == "user-123"
def test_stop_single_execution_with_stop_graph_execution(
mocker: pytest_mock.MockFixture,
admin_user_id: str,
):
"""Test stopping uses robust stop_graph_execution"""
mock_exec_meta = GraphExecutionMeta(
id="exec-running-123",
user_id="user-789",
graph_id="graph-999",
graph_version=2,
inputs=None,
credential_inputs=None,
nodes_input_masks=None,
preset_id=None,
status=AgentExecutionStatus.RUNNING,
started_at=datetime.now(timezone.utc),
ended_at=datetime.now(timezone.utc),
stats=None,
)
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_graph_executions",
return_value=[mock_exec_meta],
)
mock_stop_graph_execution = mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.stop_graph_execution",
return_value=AsyncMock(),
)
response = client.post(
"/admin/diagnostics/executions/stop",
json={"execution_id": "exec-running-123"},
)
assert response.status_code == 200
data = response.json()
assert data["success"] is True
assert data["stopped_count"] == 1
# Verify it used stop_graph_execution with cascade
mock_stop_graph_execution.assert_called_once()
call_kwargs = mock_stop_graph_execution.call_args.kwargs
assert call_kwargs["graph_exec_id"] == "exec-running-123"
assert call_kwargs["user_id"] == "user-789"
assert call_kwargs["cascade"] is True # Stops children too!
assert call_kwargs["wait_timeout"] == 15.0
def test_requeue_not_queued_execution_fails(
mocker: pytest_mock.MockFixture,
):
"""Test that requeue fails if execution is not in QUEUED status"""
# Mock an execution that's RUNNING (not QUEUED)
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_graph_executions",
return_value=[], # No QUEUED executions found
)
response = client.post(
"/admin/diagnostics/executions/requeue",
json={"execution_id": "exec-running-123"},
)
assert response.status_code == 404
assert "not found or not in QUEUED status" in response.json()["detail"]
def test_list_invalid_executions_no_bulk_actions(
mocker: pytest_mock.MockFixture,
):
"""Verify invalid executions endpoint is read-only (no bulk actions)"""
# This is a documentation test - the endpoint exists but should not
# have corresponding cleanup/stop/requeue endpoints
# These endpoints should NOT exist for invalid states:
invalid_bulk_endpoints = [
"/admin/diagnostics/executions/cleanup-invalid",
"/admin/diagnostics/executions/stop-invalid",
"/admin/diagnostics/executions/requeue-invalid",
]
for endpoint in invalid_bulk_endpoints:
response = client.post(endpoint, json={"execution_ids": ["test"]})
assert response.status_code == 404, f"{endpoint} should not exist (read-only)"
def test_execution_ids_filter_efficiency(
mocker: pytest_mock.MockFixture,
):
"""Test that bulk operations use efficient execution_ids filter"""
mock_exec_metas = [
GraphExecutionMeta(
id=f"exec-{i}",
user_id=f"user-{i}",
graph_id="graph-123",
graph_version=1,
inputs=None,
credential_inputs=None,
nodes_input_masks=None,
preset_id=None,
status=AgentExecutionStatus.QUEUED,
started_at=datetime.now(timezone.utc),
ended_at=datetime.now(timezone.utc),
stats=None,
)
for i in range(3)
]
mock_get_graph_executions = mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_graph_executions",
return_value=mock_exec_metas,
)
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.add_graph_execution",
return_value=AsyncMock(),
)
response = client.post(
"/admin/diagnostics/executions/requeue-bulk",
json={"execution_ids": ["exec-0", "exec-1", "exec-2"]},
)
assert response.status_code == 200
# Verify it used execution_ids filter (not fetching all queued)
mock_get_graph_executions.assert_called_once()
call_kwargs = mock_get_graph_executions.call_args.kwargs
assert "execution_ids" in call_kwargs
assert call_kwargs["execution_ids"] == ["exec-0", "exec-1", "exec-2"]
assert call_kwargs["statuses"] == [AgentExecutionStatus.QUEUED]
# ---------------------------------------------------------------------------
# Helper: reusable mock diagnostics summary
# ---------------------------------------------------------------------------
def _make_mock_diagnostics(**overrides) -> ExecutionDiagnosticsSummary:
defaults = dict(
running_count=10,
queued_db_count=5,
rabbitmq_queue_depth=3,
cancel_queue_depth=0,
orphaned_running=2,
orphaned_queued=1,
failed_count_1h=5,
failed_count_24h=20,
failure_rate_24h=0.83,
stuck_running_24h=3,
stuck_running_1h=5,
oldest_running_hours=26.5,
stuck_queued_1h=2,
queued_never_started=1,
invalid_queued_with_start=1,
invalid_running_without_start=1,
completed_1h=50,
completed_24h=1200,
throughput_per_hour=50.0,
timestamp=datetime.now(timezone.utc).isoformat(),
)
defaults.update(overrides)
return ExecutionDiagnosticsSummary(**defaults)
_SENTINEL = object()
def _make_mock_execution(
exec_id: str = "exec-1",
status: str = "RUNNING",
started_at: datetime | None | object = _SENTINEL,
) -> RunningExecutionDetail:
return RunningExecutionDetail(
execution_id=exec_id,
graph_id="graph-123",
graph_name="Test Graph",
graph_version=1,
user_id="user-123",
user_email="test@example.com",
status=status,
created_at=datetime.now(timezone.utc),
started_at=(
datetime.now(timezone.utc) if started_at is _SENTINEL else started_at
),
queue_status=None,
)
def _make_mock_failed_execution(
exec_id: str = "exec-fail-1",
) -> FailedExecutionDetail:
return FailedExecutionDetail(
execution_id=exec_id,
graph_id="graph-123",
graph_name="Test Graph",
graph_version=1,
user_id="user-123",
user_email="test@example.com",
status="FAILED",
created_at=datetime.now(timezone.utc),
started_at=datetime.now(timezone.utc),
failed_at=datetime.now(timezone.utc),
error_message="Something went wrong",
)
def _make_mock_schedule_health(**overrides) -> ScheduleHealthMetrics:
defaults = dict(
total_schedules=15,
user_schedules=10,
system_schedules=5,
orphaned_deleted_graph=2,
orphaned_no_library_access=1,
orphaned_invalid_credentials=0,
orphaned_validation_failed=0,
total_orphaned=3,
schedules_next_hour=4,
schedules_next_24h=8,
total_runs_next_hour=12,
total_runs_next_24h=48,
timestamp=datetime.now(timezone.utc).isoformat(),
)
defaults.update(overrides)
return ScheduleHealthMetrics(**defaults)
# ---------------------------------------------------------------------------
# GET endpoints: execution list variants
# ---------------------------------------------------------------------------
def test_list_running_executions(mocker: pytest_mock.MockFixture):
mock_execs = [
_make_mock_execution("exec-run-1"),
_make_mock_execution("exec-run-2"),
]
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_running_executions_details",
return_value=mock_execs,
)
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_execution_diagnostics",
return_value=_make_mock_diagnostics(),
)
response = client.get("/admin/diagnostics/executions/running?limit=50&offset=0")
assert response.status_code == 200
data = response.json()
assert data["total"] == 15 # running_count(10) + queued_db_count(5)
assert len(data["executions"]) == 2
assert data["executions"][0]["execution_id"] == "exec-run-1"
def test_list_orphaned_executions(mocker: pytest_mock.MockFixture):
mock_execs = [_make_mock_execution("exec-orphan-1", status="RUNNING")]
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_orphaned_executions_details",
return_value=mock_execs,
)
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_execution_diagnostics",
return_value=_make_mock_diagnostics(),
)
response = client.get("/admin/diagnostics/executions/orphaned?limit=50&offset=0")
assert response.status_code == 200
data = response.json()
assert data["total"] == 3 # orphaned_running(2) + orphaned_queued(1)
assert len(data["executions"]) == 1
def test_list_failed_executions(mocker: pytest_mock.MockFixture):
mock_execs = [_make_mock_failed_execution("exec-fail-1")]
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_failed_executions_details",
return_value=mock_execs,
)
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_failed_executions_count",
return_value=42,
)
response = client.get(
"/admin/diagnostics/executions/failed?limit=50&offset=0&hours=24"
)
assert response.status_code == 200
data = response.json()
assert data["total"] == 42
assert len(data["executions"]) == 1
assert data["executions"][0]["error_message"] == "Something went wrong"
def test_list_long_running_executions(mocker: pytest_mock.MockFixture):
mock_execs = [_make_mock_execution("exec-long-1")]
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_long_running_executions_details",
return_value=mock_execs,
)
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_execution_diagnostics",
return_value=_make_mock_diagnostics(),
)
response = client.get(
"/admin/diagnostics/executions/long-running?limit=50&offset=0"
)
assert response.status_code == 200
data = response.json()
assert data["total"] == 3 # stuck_running_24h
assert len(data["executions"]) == 1
def test_list_stuck_queued_executions(mocker: pytest_mock.MockFixture):
mock_execs = [
_make_mock_execution("exec-stuck-1", status="QUEUED", started_at=None)
]
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_stuck_queued_executions_details",
return_value=mock_execs,
)
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_execution_diagnostics",
return_value=_make_mock_diagnostics(),
)
response = client.get(
"/admin/diagnostics/executions/stuck-queued?limit=50&offset=0"
)
assert response.status_code == 200
data = response.json()
assert data["total"] == 2 # stuck_queued_1h
assert len(data["executions"]) == 1
# ---------------------------------------------------------------------------
# GET endpoints: agent + schedule diagnostics
# ---------------------------------------------------------------------------
def test_get_agent_diagnostics(mocker: pytest_mock.MockFixture):
mock_diag = AgentDiagnosticsSummary(
agents_with_active_executions=7,
timestamp=datetime.now(timezone.utc).isoformat(),
)
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_agent_diagnostics",
return_value=mock_diag,
)
response = client.get("/admin/diagnostics/agents")
assert response.status_code == 200
data = response.json()
assert data["agents_with_active_executions"] == 7
def test_get_schedule_diagnostics(mocker: pytest_mock.MockFixture):
mock_metrics = _make_mock_schedule_health()
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_schedule_health_metrics",
return_value=mock_metrics,
)
response = client.get("/admin/diagnostics/schedules")
assert response.status_code == 200
data = response.json()
assert data["user_schedules"] == 10
assert data["total_orphaned"] == 3
assert data["total_runs_next_hour"] == 12
def test_list_all_schedules(mocker: pytest_mock.MockFixture):
mock_schedules = [
ScheduleDetail(
schedule_id="sched-1",
schedule_name="Daily Run",
graph_id="graph-1",
graph_name="My Agent",
graph_version=1,
user_id="user-1",
user_email="alice@example.com",
cron="0 9 * * *",
timezone="UTC",
next_run_time=datetime.now(timezone.utc).isoformat(),
),
]
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_all_schedules_details",
return_value=mock_schedules,
)
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_schedule_health_metrics",
return_value=_make_mock_schedule_health(),
)
response = client.get("/admin/diagnostics/schedules/all?limit=50&offset=0")
assert response.status_code == 200
data = response.json()
assert data["total"] == 10
assert len(data["schedules"]) == 1
assert data["schedules"][0]["schedule_name"] == "Daily Run"
def test_list_orphaned_schedules(mocker: pytest_mock.MockFixture):
mock_orphans = [
OrphanedScheduleDetail(
schedule_id="sched-orphan-1",
schedule_name="Ghost Schedule",
graph_id="graph-deleted",
graph_version=1,
user_id="user-1",
orphan_reason="deleted_graph",
error_detail=None,
next_run_time=datetime.now(timezone.utc).isoformat(),
),
]
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_orphaned_schedules_details",
return_value=mock_orphans,
)
response = client.get("/admin/diagnostics/schedules/orphaned")
assert response.status_code == 200
data = response.json()
assert data["total"] == 1
assert data["schedules"][0]["orphan_reason"] == "deleted_graph"
# ---------------------------------------------------------------------------
# POST endpoints: bulk stop, cleanup, requeue
# ---------------------------------------------------------------------------
def test_stop_multiple_executions(mocker: pytest_mock.MockFixture):
mock_exec_metas = [
GraphExecutionMeta(
id=f"exec-{i}",
user_id=f"user-{i}",
graph_id="graph-123",
graph_version=1,
inputs=None,
credential_inputs=None,
nodes_input_masks=None,
preset_id=None,
status=AgentExecutionStatus.RUNNING,
started_at=datetime.now(timezone.utc),
ended_at=None,
stats=None,
)
for i in range(2)
]
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_graph_executions",
return_value=mock_exec_metas,
)
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.stop_graph_execution",
return_value=AsyncMock(),
)
response = client.post(
"/admin/diagnostics/executions/stop-bulk",
json={"execution_ids": ["exec-0", "exec-1"]},
)
assert response.status_code == 200
data = response.json()
assert data["success"] is True
assert data["stopped_count"] == 2
def test_stop_multiple_executions_none_found(mocker: pytest_mock.MockFixture):
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_graph_executions",
return_value=[],
)
response = client.post(
"/admin/diagnostics/executions/stop-bulk",
json={"execution_ids": ["nonexistent"]},
)
assert response.status_code == 200
data = response.json()
assert data["success"] is False
assert data["stopped_count"] == 0
def test_cleanup_orphaned_executions(mocker: pytest_mock.MockFixture):
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.cleanup_orphaned_executions_bulk",
return_value=3,
)
response = client.post(
"/admin/diagnostics/executions/cleanup-orphaned",
json={"execution_ids": ["exec-1", "exec-2", "exec-3"]},
)
assert response.status_code == 200
data = response.json()
assert data["success"] is True
assert data["stopped_count"] == 3
def test_cleanup_orphaned_schedules(mocker: pytest_mock.MockFixture):
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.cleanup_orphaned_schedules_bulk",
return_value=2,
)
response = client.post(
"/admin/diagnostics/schedules/cleanup-orphaned",
json={"schedule_ids": ["sched-1", "sched-2"]},
)
assert response.status_code == 200
data = response.json()
assert data["success"] is True
assert data["deleted_count"] == 2
def test_stop_all_long_running_executions(mocker: pytest_mock.MockFixture):
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.stop_all_long_running_executions",
return_value=5,
)
response = client.post("/admin/diagnostics/executions/stop-all-long-running")
assert response.status_code == 200
data = response.json()
assert data["success"] is True
assert data["stopped_count"] == 5
def test_cleanup_all_orphaned_executions(mocker: pytest_mock.MockFixture):
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_all_orphaned_execution_ids",
return_value=["exec-1", "exec-2"],
)
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.cleanup_orphaned_executions_bulk",
return_value=2,
)
response = client.post("/admin/diagnostics/executions/cleanup-all-orphaned")
assert response.status_code == 200
data = response.json()
assert data["success"] is True
assert data["stopped_count"] == 2
def test_cleanup_all_orphaned_executions_none(mocker: pytest_mock.MockFixture):
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_all_orphaned_execution_ids",
return_value=[],
)
response = client.post("/admin/diagnostics/executions/cleanup-all-orphaned")
assert response.status_code == 200
data = response.json()
assert data["success"] is True
assert data["stopped_count"] == 0
assert "No orphaned" in data["message"]
def test_cleanup_all_stuck_queued_executions(mocker: pytest_mock.MockFixture):
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.cleanup_all_stuck_queued_executions",
return_value=4,
)
response = client.post("/admin/diagnostics/executions/cleanup-all-stuck-queued")
assert response.status_code == 200
data = response.json()
assert data["success"] is True
assert data["stopped_count"] == 4
def test_requeue_all_stuck_executions(mocker: pytest_mock.MockFixture):
mock_exec_metas = [
GraphExecutionMeta(
id=f"exec-stuck-{i}",
user_id=f"user-{i}",
graph_id="graph-123",
graph_version=1,
inputs=None,
credential_inputs=None,
nodes_input_masks=None,
preset_id=None,
status=AgentExecutionStatus.QUEUED,
started_at=None,
ended_at=None,
stats=None,
)
for i in range(3)
]
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_all_stuck_queued_execution_ids",
return_value=["exec-stuck-0", "exec-stuck-1", "exec-stuck-2"],
)
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_graph_executions",
return_value=mock_exec_metas,
)
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.add_graph_execution",
return_value=AsyncMock(),
)
response = client.post("/admin/diagnostics/executions/requeue-all-stuck")
assert response.status_code == 200
data = response.json()
assert data["success"] is True
assert data["requeued_count"] == 3
def test_requeue_all_stuck_executions_none(mocker: pytest_mock.MockFixture):
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_all_stuck_queued_execution_ids",
return_value=[],
)
response = client.post("/admin/diagnostics/executions/requeue-all-stuck")
assert response.status_code == 200
data = response.json()
assert data["success"] is True
assert data["requeued_count"] == 0
assert "No stuck" in data["message"]
def test_requeue_bulk_none_found(mocker: pytest_mock.MockFixture):
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_graph_executions",
return_value=[],
)
response = client.post(
"/admin/diagnostics/executions/requeue-bulk",
json={"execution_ids": ["nonexistent"]},
)
assert response.status_code == 200
data = response.json()
assert data["success"] is False
assert data["requeued_count"] == 0
def test_stop_single_execution_not_found(mocker: pytest_mock.MockFixture):
mocker.patch(
"backend.api.features.admin.diagnostics_admin_routes.get_graph_executions",
return_value=[],
)
response = client.post(
"/admin/diagnostics/executions/stop",
json={"execution_id": "nonexistent"},
)
assert response.status_code == 404
assert "not found" in response.json()["detail"]

View File

@@ -14,3 +14,70 @@ class UserHistoryResponse(BaseModel):
class AddUserCreditsResponse(BaseModel):
new_balance: int
transaction_key: str
class ExecutionDiagnosticsResponse(BaseModel):
"""Response model for execution diagnostics"""
# Current execution state
running_executions: int
queued_executions_db: int
queued_executions_rabbitmq: int
cancel_queue_depth: int
# Orphaned execution detection
orphaned_running: int
orphaned_queued: int
# Failure metrics
failed_count_1h: int
failed_count_24h: int
failure_rate_24h: float
# Long-running detection
stuck_running_24h: int
stuck_running_1h: int
oldest_running_hours: float | None
# Stuck queued detection
stuck_queued_1h: int
queued_never_started: int
# Invalid state detection (data corruption - no auto-actions)
invalid_queued_with_start: int
invalid_running_without_start: int
# Throughput metrics
completed_1h: int
completed_24h: int
throughput_per_hour: float
timestamp: str
class AgentDiagnosticsResponse(BaseModel):
"""Response model for agent diagnostics"""
agents_with_active_executions: int
timestamp: str
class ScheduleHealthMetrics(BaseModel):
"""Response model for schedule diagnostics"""
total_schedules: int
user_schedules: int
system_schedules: int
# Orphan detection
orphaned_deleted_graph: int
orphaned_no_library_access: int
orphaned_invalid_credentials: int
orphaned_validation_failed: int
total_orphaned: int
# Upcoming
schedules_next_hour: int
schedules_next_24h: int
timestamp: str

View File

@@ -0,0 +1,141 @@
import logging
from datetime import datetime
from autogpt_libs.auth import get_user_id, requires_admin_user
from fastapi import APIRouter, Query, Security
from pydantic import BaseModel
from backend.data.platform_cost import (
CostLogRow,
PlatformCostDashboard,
get_platform_cost_dashboard,
get_platform_cost_logs,
get_platform_cost_logs_for_export,
)
from backend.util.models import Pagination
logger = logging.getLogger(__name__)
router = APIRouter(
prefix="/platform-costs",
tags=["platform-cost", "admin"],
dependencies=[Security(requires_admin_user)],
)
class PlatformCostLogsResponse(BaseModel):
logs: list[CostLogRow]
pagination: Pagination
@router.get(
"/dashboard",
response_model=PlatformCostDashboard,
summary="Get Platform Cost Dashboard",
)
async def get_cost_dashboard(
admin_user_id: str = Security(get_user_id),
start: datetime | None = Query(None),
end: datetime | None = Query(None),
provider: str | None = Query(None),
user_id: str | None = Query(None),
model: str | None = Query(None),
block_name: str | None = Query(None),
tracking_type: str | None = Query(None),
graph_exec_id: str | None = Query(None),
):
logger.info("Admin %s fetching platform cost dashboard", admin_user_id)
return await get_platform_cost_dashboard(
start=start,
end=end,
provider=provider,
user_id=user_id,
model=model,
block_name=block_name,
tracking_type=tracking_type,
graph_exec_id=graph_exec_id,
)
@router.get(
"/logs",
response_model=PlatformCostLogsResponse,
summary="Get Platform Cost Logs",
)
async def get_cost_logs(
admin_user_id: str = Security(get_user_id),
start: datetime | None = Query(None),
end: datetime | None = Query(None),
provider: str | None = Query(None),
user_id: str | None = Query(None),
page: int = Query(1, ge=1),
page_size: int = Query(50, ge=1, le=200),
model: str | None = Query(None),
block_name: str | None = Query(None),
tracking_type: str | None = Query(None),
graph_exec_id: str | None = Query(None),
):
logger.info("Admin %s fetching platform cost logs", admin_user_id)
logs, total = await get_platform_cost_logs(
start=start,
end=end,
provider=provider,
user_id=user_id,
page=page,
page_size=page_size,
model=model,
block_name=block_name,
tracking_type=tracking_type,
graph_exec_id=graph_exec_id,
)
total_pages = (total + page_size - 1) // page_size
return PlatformCostLogsResponse(
logs=logs,
pagination=Pagination(
total_items=total,
total_pages=total_pages,
current_page=page,
page_size=page_size,
),
)
class PlatformCostExportResponse(BaseModel):
logs: list[CostLogRow]
total_rows: int
truncated: bool
@router.get(
"/logs/export",
response_model=PlatformCostExportResponse,
summary="Export Platform Cost Logs",
)
async def export_cost_logs(
admin_user_id: str = Security(get_user_id),
start: datetime | None = Query(None),
end: datetime | None = Query(None),
provider: str | None = Query(None),
user_id: str | None = Query(None),
model: str | None = Query(None),
block_name: str | None = Query(None),
tracking_type: str | None = Query(None),
graph_exec_id: str | None = Query(None),
):
logger.info("Admin %s exporting platform cost logs", admin_user_id)
logs, truncated = await get_platform_cost_logs_for_export(
start=start,
end=end,
provider=provider,
user_id=user_id,
model=model,
block_name=block_name,
tracking_type=tracking_type,
graph_exec_id=graph_exec_id,
)
return PlatformCostExportResponse(
logs=logs,
total_rows=len(logs),
truncated=truncated,
)

View File

@@ -0,0 +1,291 @@
from datetime import datetime, timezone
from unittest.mock import AsyncMock
import fastapi
import fastapi.testclient
import pytest
import pytest_mock
from autogpt_libs.auth.jwt_utils import get_jwt_payload
from backend.data.platform_cost import CostLogRow, PlatformCostDashboard
from .platform_cost_routes import router as platform_cost_router
app = fastapi.FastAPI()
app.include_router(platform_cost_router)
client = fastapi.testclient.TestClient(app)
@pytest.fixture(autouse=True)
def setup_app_admin_auth(mock_jwt_admin):
"""Setup admin auth overrides for all tests in this module"""
app.dependency_overrides[get_jwt_payload] = mock_jwt_admin["get_jwt_payload"]
yield
app.dependency_overrides.clear()
def test_get_dashboard_success(
mocker: pytest_mock.MockerFixture,
) -> None:
real_dashboard = PlatformCostDashboard(
by_provider=[],
by_user=[],
total_cost_microdollars=0,
total_requests=0,
total_users=0,
)
mocker.patch(
"backend.api.features.admin.platform_cost_routes.get_platform_cost_dashboard",
AsyncMock(return_value=real_dashboard),
)
response = client.get("/platform-costs/dashboard")
assert response.status_code == 200
data = response.json()
assert "by_provider" in data
assert "by_user" in data
assert data["total_cost_microdollars"] == 0
def test_get_logs_success(
mocker: pytest_mock.MockerFixture,
) -> None:
mocker.patch(
"backend.api.features.admin.platform_cost_routes.get_platform_cost_logs",
AsyncMock(return_value=([], 0)),
)
response = client.get("/platform-costs/logs")
assert response.status_code == 200
data = response.json()
assert data["logs"] == []
assert data["pagination"]["total_items"] == 0
def test_get_dashboard_with_filters(
mocker: pytest_mock.MockerFixture,
) -> None:
real_dashboard = PlatformCostDashboard(
by_provider=[],
by_user=[],
total_cost_microdollars=0,
total_requests=0,
total_users=0,
)
mock_dashboard = AsyncMock(return_value=real_dashboard)
mocker.patch(
"backend.api.features.admin.platform_cost_routes.get_platform_cost_dashboard",
mock_dashboard,
)
response = client.get(
"/platform-costs/dashboard",
params={
"start": "2026-01-01T00:00:00",
"end": "2026-04-01T00:00:00",
"provider": "openai",
"user_id": "test-user-123",
},
)
assert response.status_code == 200
mock_dashboard.assert_called_once()
call_kwargs = mock_dashboard.call_args.kwargs
assert call_kwargs["provider"] == "openai"
assert call_kwargs["user_id"] == "test-user-123"
assert call_kwargs["start"] is not None
assert call_kwargs["end"] is not None
def test_get_logs_with_pagination(
mocker: pytest_mock.MockerFixture,
) -> None:
mocker.patch(
"backend.api.features.admin.platform_cost_routes.get_platform_cost_logs",
AsyncMock(return_value=([], 0)),
)
response = client.get(
"/platform-costs/logs",
params={"page": 2, "page_size": 25, "provider": "anthropic"},
)
assert response.status_code == 200
data = response.json()
assert data["pagination"]["current_page"] == 2
assert data["pagination"]["page_size"] == 25
def test_get_dashboard_requires_admin() -> None:
import fastapi
from fastapi import HTTPException
def reject_jwt(request: fastapi.Request):
raise HTTPException(status_code=401, detail="Not authenticated")
app.dependency_overrides[get_jwt_payload] = reject_jwt
try:
response = client.get("/platform-costs/dashboard")
assert response.status_code == 401
response = client.get("/platform-costs/logs")
assert response.status_code == 401
finally:
app.dependency_overrides.clear()
def test_get_dashboard_rejects_non_admin(mock_jwt_user, mock_jwt_admin) -> None:
"""Non-admin JWT must be rejected with 403 by requires_admin_user."""
app.dependency_overrides[get_jwt_payload] = mock_jwt_user["get_jwt_payload"]
try:
response = client.get("/platform-costs/dashboard")
assert response.status_code == 403
response = client.get("/platform-costs/logs")
assert response.status_code == 403
finally:
app.dependency_overrides[get_jwt_payload] = mock_jwt_admin["get_jwt_payload"]
def test_get_logs_invalid_page_size_too_large() -> None:
"""page_size > 200 must be rejected with 422."""
response = client.get("/platform-costs/logs", params={"page_size": 201})
assert response.status_code == 422
def test_get_logs_invalid_page_size_zero() -> None:
"""page_size = 0 (below ge=1) must be rejected with 422."""
response = client.get("/platform-costs/logs", params={"page_size": 0})
assert response.status_code == 422
def test_get_logs_invalid_page_negative() -> None:
"""page < 1 must be rejected with 422."""
response = client.get("/platform-costs/logs", params={"page": 0})
assert response.status_code == 422
def test_get_dashboard_invalid_date_format() -> None:
"""Malformed start date must be rejected with 422."""
response = client.get("/platform-costs/dashboard", params={"start": "not-a-date"})
assert response.status_code == 422
def test_get_dashboard_repeated_requests(
mocker: pytest_mock.MockerFixture,
) -> None:
"""Repeated requests to the dashboard route both return 200."""
real_dashboard = PlatformCostDashboard(
by_provider=[],
by_user=[],
total_cost_microdollars=42,
total_requests=1,
total_users=1,
)
mocker.patch(
"backend.api.features.admin.platform_cost_routes.get_platform_cost_dashboard",
AsyncMock(return_value=real_dashboard),
)
r1 = client.get("/platform-costs/dashboard")
r2 = client.get("/platform-costs/dashboard")
assert r1.status_code == 200
assert r2.status_code == 200
assert r1.json()["total_cost_microdollars"] == 42
assert r2.json()["total_cost_microdollars"] == 42
def _make_cost_log_row() -> CostLogRow:
return CostLogRow(
id="log-1",
created_at=datetime(2026, 1, 1, tzinfo=timezone.utc),
user_id="user-1",
email="u***@example.com",
graph_exec_id="graph-1",
node_exec_id="node-1",
block_name="LlmCallBlock",
provider="anthropic",
tracking_type="token",
cost_microdollars=500,
input_tokens=100,
output_tokens=50,
cache_read_tokens=10,
cache_creation_tokens=5,
duration=1.5,
model="claude-3-5-sonnet-20241022",
)
def test_export_logs_success(
mocker: pytest_mock.MockerFixture,
) -> None:
row = _make_cost_log_row()
mocker.patch(
"backend.api.features.admin.platform_cost_routes.get_platform_cost_logs_for_export",
AsyncMock(return_value=([row], False)),
)
response = client.get("/platform-costs/logs/export")
assert response.status_code == 200
data = response.json()
assert data["total_rows"] == 1
assert data["truncated"] is False
assert len(data["logs"]) == 1
assert data["logs"][0]["cache_read_tokens"] == 10
assert data["logs"][0]["cache_creation_tokens"] == 5
def test_export_logs_truncated(
mocker: pytest_mock.MockerFixture,
) -> None:
rows = [_make_cost_log_row() for _ in range(3)]
mocker.patch(
"backend.api.features.admin.platform_cost_routes.get_platform_cost_logs_for_export",
AsyncMock(return_value=(rows, True)),
)
response = client.get("/platform-costs/logs/export")
assert response.status_code == 200
data = response.json()
assert data["total_rows"] == 3
assert data["truncated"] is True
def test_export_logs_with_filters(
mocker: pytest_mock.MockerFixture,
) -> None:
mock_export = AsyncMock(return_value=([], False))
mocker.patch(
"backend.api.features.admin.platform_cost_routes.get_platform_cost_logs_for_export",
mock_export,
)
response = client.get(
"/platform-costs/logs/export",
params={
"provider": "anthropic",
"model": "claude-3-5-sonnet-20241022",
"block_name": "LlmCallBlock",
"tracking_type": "token",
},
)
assert response.status_code == 200
mock_export.assert_called_once()
call_kwargs = mock_export.call_args.kwargs
assert call_kwargs["provider"] == "anthropic"
assert call_kwargs["model"] == "claude-3-5-sonnet-20241022"
assert call_kwargs["block_name"] == "LlmCallBlock"
assert call_kwargs["tracking_type"] == "token"
def test_export_logs_requires_admin() -> None:
import fastapi
from fastapi import HTTPException
def reject_jwt(request: fastapi.Request):
raise HTTPException(status_code=401, detail="Not authenticated")
app.dependency_overrides[get_jwt_payload] = reject_jwt
try:
response = client.get("/platform-costs/logs/export")
assert response.status_code == 401
finally:
app.dependency_overrides.clear()

View File

@@ -9,11 +9,14 @@ from pydantic import BaseModel
from backend.copilot.config import ChatConfig
from backend.copilot.rate_limit import (
SubscriptionTier,
get_global_rate_limits,
get_usage_status,
get_user_tier,
reset_user_usage,
set_user_tier,
)
from backend.data.user import get_user_by_email, get_user_email_by_id
from backend.data.user import get_user_by_email, get_user_email_by_id, search_users
logger = logging.getLogger(__name__)
@@ -29,10 +32,21 @@ router = APIRouter(
class UserRateLimitResponse(BaseModel):
user_id: str
user_email: Optional[str] = None
daily_token_limit: int
weekly_token_limit: int
daily_tokens_used: int
weekly_tokens_used: int
daily_cost_limit_microdollars: int
weekly_cost_limit_microdollars: int
daily_cost_used_microdollars: int
weekly_cost_used_microdollars: int
tier: SubscriptionTier
class UserTierResponse(BaseModel):
user_id: str
tier: SubscriptionTier
class SetUserTierRequest(BaseModel):
user_id: str
tier: SubscriptionTier
async def _resolve_user_id(
@@ -86,18 +100,21 @@ async def get_user_rate_limit(
logger.info("Admin %s checking rate limit for user %s", admin_user_id, resolved_id)
daily_limit, weekly_limit = await get_global_rate_limits(
resolved_id, config.daily_token_limit, config.weekly_token_limit
daily_limit, weekly_limit, tier = await get_global_rate_limits(
resolved_id,
config.daily_cost_limit_microdollars,
config.weekly_cost_limit_microdollars,
)
usage = await get_usage_status(resolved_id, daily_limit, weekly_limit)
usage = await get_usage_status(resolved_id, daily_limit, weekly_limit, tier=tier)
return UserRateLimitResponse(
user_id=resolved_id,
user_email=resolved_email,
daily_token_limit=daily_limit,
weekly_token_limit=weekly_limit,
daily_tokens_used=usage.daily.used,
weekly_tokens_used=usage.weekly.used,
daily_cost_limit_microdollars=daily_limit,
weekly_cost_limit_microdollars=weekly_limit,
daily_cost_used_microdollars=usage.daily.used,
weekly_cost_used_microdollars=usage.weekly.used,
tier=tier,
)
@@ -125,10 +142,12 @@ async def reset_user_rate_limit(
logger.exception("Failed to reset user usage")
raise HTTPException(status_code=500, detail="Failed to reset usage") from e
daily_limit, weekly_limit = await get_global_rate_limits(
user_id, config.daily_token_limit, config.weekly_token_limit
daily_limit, weekly_limit, tier = await get_global_rate_limits(
user_id,
config.daily_cost_limit_microdollars,
config.weekly_cost_limit_microdollars,
)
usage = await get_usage_status(user_id, daily_limit, weekly_limit)
usage = await get_usage_status(user_id, daily_limit, weekly_limit, tier=tier)
try:
resolved_email = await get_user_email_by_id(user_id)
@@ -139,8 +158,106 @@ async def reset_user_rate_limit(
return UserRateLimitResponse(
user_id=user_id,
user_email=resolved_email,
daily_token_limit=daily_limit,
weekly_token_limit=weekly_limit,
daily_tokens_used=usage.daily.used,
weekly_tokens_used=usage.weekly.used,
daily_cost_limit_microdollars=daily_limit,
weekly_cost_limit_microdollars=weekly_limit,
daily_cost_used_microdollars=usage.daily.used,
weekly_cost_used_microdollars=usage.weekly.used,
tier=tier,
)
@router.get(
"/rate_limit/tier",
response_model=UserTierResponse,
summary="Get User Rate Limit Tier",
)
async def get_user_rate_limit_tier(
user_id: str,
admin_user_id: str = Security(get_user_id),
) -> UserTierResponse:
"""Get a user's current rate-limit tier. Admin-only.
Returns 404 if the user does not exist in the database.
"""
logger.info("Admin %s checking tier for user %s", admin_user_id, user_id)
resolved_email = await get_user_email_by_id(user_id)
if resolved_email is None:
raise HTTPException(status_code=404, detail=f"User {user_id} not found")
tier = await get_user_tier(user_id)
return UserTierResponse(user_id=user_id, tier=tier)
@router.post(
"/rate_limit/tier",
response_model=UserTierResponse,
summary="Set User Rate Limit Tier",
)
async def set_user_rate_limit_tier(
request: SetUserTierRequest,
admin_user_id: str = Security(get_user_id),
) -> UserTierResponse:
"""Set a user's rate-limit tier. Admin-only.
Returns 404 if the user does not exist in the database.
"""
try:
resolved_email = await get_user_email_by_id(request.user_id)
except Exception:
logger.warning(
"Failed to resolve email for user %s",
request.user_id,
exc_info=True,
)
resolved_email = None
if resolved_email is None:
raise HTTPException(status_code=404, detail=f"User {request.user_id} not found")
old_tier = await get_user_tier(request.user_id)
logger.info(
"Admin %s changing tier for user %s (%s): %s -> %s",
admin_user_id,
request.user_id,
resolved_email,
old_tier.value,
request.tier.value,
)
try:
await set_user_tier(request.user_id, request.tier)
except Exception as e:
logger.exception("Failed to set user tier")
raise HTTPException(status_code=500, detail="Failed to set tier") from e
return UserTierResponse(user_id=request.user_id, tier=request.tier)
class UserSearchResult(BaseModel):
user_id: str
user_email: Optional[str] = None
@router.get(
"/rate_limit/search_users",
response_model=list[UserSearchResult],
summary="Search Users by Name or Email",
)
async def admin_search_users(
query: str,
limit: int = 20,
admin_user_id: str = Security(get_user_id),
) -> list[UserSearchResult]:
"""Search users by partial email or name. Admin-only.
Queries the User table directly — returns results even for users
without credit transaction history.
"""
if len(query.strip()) < 3:
raise HTTPException(
status_code=400,
detail="Search query must be at least 3 characters.",
)
logger.info("Admin %s searching users with query=%r", admin_user_id, query)
results = await search_users(query, limit=max(1, min(limit, 50)))
return [UserSearchResult(user_id=uid, user_email=email) for uid, email in results]

View File

@@ -9,7 +9,7 @@ import pytest_mock
from autogpt_libs.auth.jwt_utils import get_jwt_payload
from pytest_snapshot.plugin import Snapshot
from backend.copilot.rate_limit import CoPilotUsageStatus, UsageWindow
from backend.copilot.rate_limit import CoPilotUsageStatus, SubscriptionTier, UsageWindow
from .rate_limit_admin_routes import router as rate_limit_admin_router
@@ -57,7 +57,7 @@ def _patch_rate_limit_deps(
mocker.patch(
f"{_MOCK_MODULE}.get_global_rate_limits",
new_callable=AsyncMock,
return_value=(2_500_000, 12_500_000),
return_value=(2_500_000, 12_500_000, SubscriptionTier.BASIC),
)
mocker.patch(
f"{_MOCK_MODULE}.get_usage_status",
@@ -85,10 +85,11 @@ def test_get_rate_limit(
data = response.json()
assert data["user_id"] == target_user_id
assert data["user_email"] == _TARGET_EMAIL
assert data["daily_token_limit"] == 2_500_000
assert data["weekly_token_limit"] == 12_500_000
assert data["daily_tokens_used"] == 500_000
assert data["weekly_tokens_used"] == 3_000_000
assert data["daily_cost_limit_microdollars"] == 2_500_000
assert data["weekly_cost_limit_microdollars"] == 12_500_000
assert data["daily_cost_used_microdollars"] == 500_000
assert data["weekly_cost_used_microdollars"] == 3_000_000
assert data["tier"] == "BASIC"
configured_snapshot.assert_match(
json.dumps(data, indent=2, sort_keys=True) + "\n",
@@ -116,7 +117,7 @@ def test_get_rate_limit_by_email(
data = response.json()
assert data["user_id"] == target_user_id
assert data["user_email"] == _TARGET_EMAIL
assert data["daily_token_limit"] == 2_500_000
assert data["daily_cost_limit_microdollars"] == 2_500_000
def test_get_rate_limit_by_email_not_found(
@@ -159,9 +160,10 @@ def test_reset_user_usage_daily_only(
assert response.status_code == 200
data = response.json()
assert data["daily_tokens_used"] == 0
assert data["daily_cost_used_microdollars"] == 0
# Weekly is untouched
assert data["weekly_tokens_used"] == 3_000_000
assert data["weekly_cost_used_microdollars"] == 3_000_000
assert data["tier"] == "BASIC"
mock_reset.assert_awaited_once_with(target_user_id, reset_weekly=False)
@@ -190,8 +192,9 @@ def test_reset_user_usage_daily_and_weekly(
assert response.status_code == 200
data = response.json()
assert data["daily_tokens_used"] == 0
assert data["weekly_tokens_used"] == 0
assert data["daily_cost_used_microdollars"] == 0
assert data["weekly_cost_used_microdollars"] == 0
assert data["tier"] == "BASIC"
mock_reset.assert_awaited_once_with(target_user_id, reset_weekly=True)
@@ -228,7 +231,7 @@ def test_get_rate_limit_email_lookup_failure(
mocker.patch(
f"{_MOCK_MODULE}.get_global_rate_limits",
new_callable=AsyncMock,
return_value=(2_500_000, 12_500_000),
return_value=(2_500_000, 12_500_000, SubscriptionTier.BASIC),
)
mocker.patch(
f"{_MOCK_MODULE}.get_usage_status",
@@ -261,3 +264,303 @@ def test_admin_endpoints_require_admin_role(mock_jwt_user) -> None:
json={"user_id": "test"},
)
assert response.status_code == 403
# ---------------------------------------------------------------------------
# Tier management endpoints
# ---------------------------------------------------------------------------
def test_get_user_tier(
mocker: pytest_mock.MockerFixture,
target_user_id: str,
) -> None:
"""Test getting a user's rate-limit tier."""
mocker.patch(
f"{_MOCK_MODULE}.get_user_email_by_id",
new_callable=AsyncMock,
return_value=_TARGET_EMAIL,
)
mocker.patch(
f"{_MOCK_MODULE}.get_user_tier",
new_callable=AsyncMock,
return_value=SubscriptionTier.PRO,
)
response = client.get("/admin/rate_limit/tier", params={"user_id": target_user_id})
assert response.status_code == 200
data = response.json()
assert data["user_id"] == target_user_id
assert data["tier"] == "PRO"
def test_get_user_tier_user_not_found(
mocker: pytest_mock.MockerFixture,
target_user_id: str,
) -> None:
"""Test that getting tier for a non-existent user returns 404."""
mocker.patch(
f"{_MOCK_MODULE}.get_user_email_by_id",
new_callable=AsyncMock,
return_value=None,
)
response = client.get("/admin/rate_limit/tier", params={"user_id": target_user_id})
assert response.status_code == 404
def test_set_user_tier(
mocker: pytest_mock.MockerFixture,
target_user_id: str,
) -> None:
"""Test setting a user's rate-limit tier (upgrade)."""
mocker.patch(
f"{_MOCK_MODULE}.get_user_email_by_id",
new_callable=AsyncMock,
return_value=_TARGET_EMAIL,
)
mocker.patch(
f"{_MOCK_MODULE}.get_user_tier",
new_callable=AsyncMock,
return_value=SubscriptionTier.BASIC,
)
mock_set = mocker.patch(
f"{_MOCK_MODULE}.set_user_tier",
new_callable=AsyncMock,
)
response = client.post(
"/admin/rate_limit/tier",
json={"user_id": target_user_id, "tier": "ENTERPRISE"},
)
assert response.status_code == 200
data = response.json()
assert data["user_id"] == target_user_id
assert data["tier"] == "ENTERPRISE"
mock_set.assert_awaited_once_with(target_user_id, SubscriptionTier.ENTERPRISE)
def test_set_user_tier_downgrade(
mocker: pytest_mock.MockerFixture,
target_user_id: str,
) -> None:
"""Test downgrading a user's tier from PRO to BASIC."""
mocker.patch(
f"{_MOCK_MODULE}.get_user_email_by_id",
new_callable=AsyncMock,
return_value=_TARGET_EMAIL,
)
mocker.patch(
f"{_MOCK_MODULE}.get_user_tier",
new_callable=AsyncMock,
return_value=SubscriptionTier.PRO,
)
mock_set = mocker.patch(
f"{_MOCK_MODULE}.set_user_tier",
new_callable=AsyncMock,
)
response = client.post(
"/admin/rate_limit/tier",
json={"user_id": target_user_id, "tier": "BASIC"},
)
assert response.status_code == 200
data = response.json()
assert data["user_id"] == target_user_id
assert data["tier"] == "BASIC"
mock_set.assert_awaited_once_with(target_user_id, SubscriptionTier.BASIC)
def test_set_user_tier_invalid_tier(
target_user_id: str,
) -> None:
"""Test that setting an invalid tier returns 422."""
response = client.post(
"/admin/rate_limit/tier",
json={"user_id": target_user_id, "tier": "invalid"},
)
assert response.status_code == 422
def test_set_user_tier_invalid_tier_uppercase(
target_user_id: str,
) -> None:
"""Test that setting an unrecognised uppercase tier (e.g. 'INVALID') returns 422.
Regression: ensures Pydantic enum validation rejects values that are not
members of SubscriptionTier, even when they look like valid enum names.
"""
response = client.post(
"/admin/rate_limit/tier",
json={"user_id": target_user_id, "tier": "INVALID"},
)
assert response.status_code == 422
body = response.json()
assert "detail" in body
def test_set_user_tier_email_lookup_failure_returns_404(
mocker: pytest_mock.MockerFixture,
target_user_id: str,
) -> None:
"""Test that email lookup failure returns 404 (user unverifiable)."""
mocker.patch(
f"{_MOCK_MODULE}.get_user_email_by_id",
new_callable=AsyncMock,
side_effect=Exception("DB connection failed"),
)
response = client.post(
"/admin/rate_limit/tier",
json={"user_id": target_user_id, "tier": "PRO"},
)
assert response.status_code == 404
def test_set_user_tier_user_not_found(
mocker: pytest_mock.MockerFixture,
target_user_id: str,
) -> None:
"""Test that setting tier for a non-existent user returns 404."""
mocker.patch(
f"{_MOCK_MODULE}.get_user_email_by_id",
new_callable=AsyncMock,
return_value=None,
)
response = client.post(
"/admin/rate_limit/tier",
json={"user_id": target_user_id, "tier": "PRO"},
)
assert response.status_code == 404
def test_set_user_tier_db_failure(
mocker: pytest_mock.MockerFixture,
target_user_id: str,
) -> None:
"""Test that DB failure on set tier returns 500."""
mocker.patch(
f"{_MOCK_MODULE}.get_user_email_by_id",
new_callable=AsyncMock,
return_value=_TARGET_EMAIL,
)
mocker.patch(
f"{_MOCK_MODULE}.get_user_tier",
new_callable=AsyncMock,
return_value=SubscriptionTier.BASIC,
)
mocker.patch(
f"{_MOCK_MODULE}.set_user_tier",
new_callable=AsyncMock,
side_effect=Exception("DB connection refused"),
)
response = client.post(
"/admin/rate_limit/tier",
json={"user_id": target_user_id, "tier": "PRO"},
)
assert response.status_code == 500
def test_tier_endpoints_require_admin_role(mock_jwt_user) -> None:
"""Test that tier admin endpoints require admin role."""
app.dependency_overrides[get_jwt_payload] = mock_jwt_user["get_jwt_payload"]
response = client.get("/admin/rate_limit/tier", params={"user_id": "test"})
assert response.status_code == 403
response = client.post(
"/admin/rate_limit/tier",
json={"user_id": "test", "tier": "PRO"},
)
assert response.status_code == 403
# ─── search_users endpoint ──────────────────────────────────────────
def test_search_users_returns_matching_users(
mocker: pytest_mock.MockerFixture,
admin_user_id: str,
) -> None:
"""Partial search should return all matching users from the User table."""
mocker.patch(
_MOCK_MODULE + ".search_users",
new_callable=AsyncMock,
return_value=[
("user-1", "zamil.majdy@gmail.com"),
("user-2", "zamil.majdy@agpt.co"),
],
)
response = client.get("/admin/rate_limit/search_users", params={"query": "zamil"})
assert response.status_code == 200
results = response.json()
assert len(results) == 2
assert results[0]["user_email"] == "zamil.majdy@gmail.com"
assert results[1]["user_email"] == "zamil.majdy@agpt.co"
def test_search_users_empty_results(
mocker: pytest_mock.MockerFixture,
admin_user_id: str,
) -> None:
"""Search with no matches returns empty list."""
mocker.patch(
_MOCK_MODULE + ".search_users",
new_callable=AsyncMock,
return_value=[],
)
response = client.get(
"/admin/rate_limit/search_users", params={"query": "nonexistent"}
)
assert response.status_code == 200
assert response.json() == []
def test_search_users_short_query_rejected(
admin_user_id: str,
) -> None:
"""Query shorter than 3 characters should return 400."""
response = client.get("/admin/rate_limit/search_users", params={"query": "ab"})
assert response.status_code == 400
def test_search_users_negative_limit_clamped(
mocker: pytest_mock.MockerFixture,
admin_user_id: str,
) -> None:
"""Negative limit should be clamped to 1, not passed through."""
mock_search = mocker.patch(
_MOCK_MODULE + ".search_users",
new_callable=AsyncMock,
return_value=[],
)
response = client.get(
"/admin/rate_limit/search_users", params={"query": "test", "limit": -1}
)
assert response.status_code == 200
mock_search.assert_awaited_once_with("test", limit=1)
def test_search_users_requires_admin_role(mock_jwt_user) -> None:
"""Test that the search_users endpoint requires admin role."""
app.dependency_overrides[get_jwt_payload] = mock_jwt_user["get_jwt_payload"]
response = client.get("/admin/rate_limit/search_users", params={"query": "test"})
assert response.status_code == 403

View File

@@ -2,7 +2,6 @@
import asyncio
import logging
import re
from collections.abc import AsyncGenerator
from typing import Annotated
from uuid import uuid4
@@ -10,12 +9,13 @@ from uuid import uuid4
from autogpt_libs import auth
from fastapi import APIRouter, HTTPException, Query, Response, Security
from fastapi.responses import StreamingResponse
from prisma.models import UserWorkspaceFile
from pydantic import BaseModel, ConfigDict, Field, field_validator
from backend.copilot import service as chat_service
from backend.copilot import stream_registry
from backend.copilot.config import ChatConfig
from backend.copilot.builder_context import resolve_session_permissions
from backend.copilot.config import ChatConfig, CopilotLlmModel, CopilotMode
from backend.copilot.db import get_chat_messages_paginated
from backend.copilot.executor.utils import enqueue_cancel_task, enqueue_copilot_turn
from backend.copilot.model import (
ChatMessage,
@@ -25,11 +25,18 @@ from backend.copilot.model import (
create_chat_session,
delete_chat_session,
get_chat_session,
get_or_create_builder_session,
get_user_sessions,
update_session_title,
)
from backend.copilot.pending_message_helpers import (
QueuePendingMessageResponse,
is_turn_in_flight,
queue_pending_for_http,
)
from backend.copilot.pending_messages import peek_pending_messages
from backend.copilot.rate_limit import (
CoPilotUsageStatus,
CoPilotUsagePublic,
RateLimitExceeded,
acquire_reset_lock,
check_rate_limit,
@@ -40,7 +47,15 @@ from backend.copilot.rate_limit import (
release_reset_lock,
reset_daily_usage,
)
from backend.copilot.response_model import StreamError, StreamFinish, StreamHeartbeat
from backend.copilot.response_model import (
StreamError,
StreamFinish,
StreamFinishStep,
StreamHeartbeat,
StreamStart,
StreamStartStep,
)
from backend.copilot.service import strip_injected_context_for_display
from backend.copilot.tools.e2b_sandbox import kill_sandbox
from backend.copilot.tools.models import (
AgentDetailsResponse,
@@ -59,17 +74,22 @@ from backend.copilot.tools.models import (
InputValidationErrorResponse,
MCPToolOutputResponse,
MCPToolsDiscoveredResponse,
MemoryForgetCandidatesResponse,
MemoryForgetConfirmResponse,
MemorySearchResponse,
MemoryStoreResponse,
NeedLoginResponse,
NoResultsResponse,
SetupRequirementsResponse,
SuggestedGoalResponse,
TodoWriteResponse,
UnderstandingUpdatedResponse,
)
from backend.copilot.tracking import track_user_message
from backend.data.credit import UsageTransactionMetadata, get_user_credit_model
from backend.data.redis_client import get_redis_async
from backend.data.understanding import get_business_understanding
from backend.data.workspace import get_or_create_workspace
from backend.data.workspace import build_files_block, resolve_workspace_files
from backend.util.exceptions import InsufficientBalanceError, NotFoundError
from backend.util.settings import Settings
@@ -79,10 +99,6 @@ logger = logging.getLogger(__name__)
config = ChatConfig()
_UUID_RE = re.compile(
r"^[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}$", re.I
)
async def _validate_and_get_session(
session_id: str,
@@ -99,30 +115,99 @@ router = APIRouter(
tags=["chat"],
)
def _strip_injected_context(message: dict) -> dict:
"""Hide server-injected context blocks from the API response.
Returns a **shallow copy** of *message* with all server-injected XML
blocks removed from ``content`` (if applicable). The original dict is
never mutated, so callers can safely pass live session dicts without
risking side-effects.
Handles all three injected block types — ``<memory_context>``,
``<env_context>``, and ``<user_context>`` — regardless of the order they
appear at the start of the message. Only ``user``-role messages with
string content are touched; assistant / multimodal blocks pass through
unchanged.
"""
if message.get("role") == "user" and isinstance(message.get("content"), str):
result = message.copy()
result["content"] = strip_injected_context_for_display(message["content"])
return result
return message
# ========== Request/Response Models ==========
class StreamChatRequest(BaseModel):
"""Request model for streaming chat with optional context."""
message: str
message: str = Field(max_length=64_000)
is_user_message: bool = True
context: dict[str, str] | None = None # {url: str, content: str}
file_ids: list[str] | None = Field(
default=None, max_length=20
) # Workspace file IDs attached to this message
mode: CopilotMode | None = Field(
default=None,
description="Autopilot mode: 'fast' for baseline LLM, 'extended_thinking' for Claude Agent SDK. "
"If None, uses the server default (extended_thinking).",
)
model: CopilotLlmModel | None = Field(
default=None,
description="Model tier: 'standard' for the default model, 'advanced' for the highest-capability model. "
"If None, the server applies per-user LD targeting then falls back to config.",
)
class QueuePendingMessageRequest(BaseModel):
"""Request model for queueing a follow-up while a turn is running."""
message: str = Field(max_length=64_000)
context: dict[str, str] | None = None
file_ids: list[str] | None = Field(default=None, max_length=20)
class PeekPendingMessagesResponse(BaseModel):
"""Response for the pending-message peek (GET) endpoint.
Returns a read-only view of the pending buffer — messages are NOT
consumed. The frontend uses this to restore the queued-message
indicator after a page refresh and to decide when to clear it once
a turn has ended.
"""
messages: list[str]
count: int
class CreateSessionRequest(BaseModel):
"""Request model for creating a new chat session.
"""Request model for creating (or get-or-creating) a chat session.
Two modes, selected by the body:
- Default: create a fresh session. ``dry_run`` is a **top-level**
field — do not nest it inside ``metadata``.
- Builder-bound: when ``builder_graph_id`` is set, the endpoint
switches to **get-or-create** keyed on
``(user_id, builder_graph_id)``. The builder panel calls this on
mount so the chat persists across refreshes. Graph ownership is
validated inside :func:`get_or_create_builder_session`. Write-side
scope is enforced per-tool (``edit_agent`` / ``run_agent`` reject
any ``agent_id`` other than the bound graph) and a small blacklist
hides tools that conflict with the panel's scope
(``create_agent`` / ``customize_agent`` / ``get_agent_building_guide``
— see :data:`BUILDER_BLOCKED_TOOLS`). Read-side lookups
(``find_block``, ``find_agent``, ``search_docs``, …) stay open.
``dry_run`` is a **top-level** field — do not nest it inside ``metadata``.
Extra/unknown fields are rejected (422) to prevent silent mis-use.
"""
model_config = ConfigDict(extra="forbid")
dry_run: bool = False
builder_graph_id: str | None = Field(default=None, max_length=128)
class CreateSessionResponse(BaseModel):
@@ -139,6 +224,11 @@ class ActiveStreamInfo(BaseModel):
turn_id: str
last_message_id: str # Redis Stream message ID for resumption
# ISO-8601 timestamp (UTC) marking when the backend registered the turn
# as running. Lets the frontend seed its elapsed-time counter so restored
# turns show honest "time since turn started" instead of the misleading
# "time since this mount resumed the SSE".
started_at: str | None = None
class SessionDetailResponse(BaseModel):
@@ -150,6 +240,8 @@ class SessionDetailResponse(BaseModel):
user_id: str | None
messages: list[dict]
active_stream: ActiveStreamInfo | None = None # Present if stream is still active
has_more_messages: bool = False
oldest_sequence: int | None = None
total_prompt_tokens: int = 0
total_completion_tokens: int = 0
metadata: ChatSessionMetadata = ChatSessionMetadata()
@@ -228,8 +320,11 @@ async def list_sessions(
redis = await get_redis_async()
pipe = redis.pipeline(transaction=False)
for session in sessions:
# Use the canonical helper so the hash-tag braces match every
# other writer; building the key inline drops the braces and
# silently misses every running session on cluster mode.
pipe.hget(
f"{config.session_meta_prefix}{session.session_id}",
stream_registry.get_session_meta_key(session.session_id),
"status",
)
statuses = await pipe.execute()
@@ -265,29 +360,43 @@ async def create_session(
user_id: Annotated[str, Security(auth.get_user_id)],
request: CreateSessionRequest | None = None,
) -> CreateSessionResponse:
"""
Create a new chat session.
"""Create (or get-or-create) a chat session.
Initiates a new chat session for the authenticated user.
Two modes, selected by the request body:
- Default: create a fresh session for the user. ``dry_run=True`` forces
run_block and run_agent calls to use dry-run simulation.
- Builder-bound: when ``builder_graph_id`` is set, get-or-create keyed
on ``(user_id, builder_graph_id)``. Returns the existing session for
that graph or creates one locked to it. Graph ownership is validated
inside :func:`get_or_create_builder_session`; raises 404 on
unauthorized access. Write-side scope is enforced per-tool
(``edit_agent`` / ``run_agent`` reject any ``agent_id`` other than
the bound graph) and a small blacklist hides tools that conflict
with the panel's scope (see :data:`BUILDER_BLOCKED_TOOLS`).
Args:
user_id: The authenticated user ID parsed from the JWT (required).
request: Optional request body. When provided, ``dry_run=True``
forces run_block and run_agent calls to use dry-run simulation.
request: Optional request body with ``dry_run`` and/or
``builder_graph_id``.
Returns:
CreateSessionResponse: Details of the created session.
CreateSessionResponse: Details of the resulting session.
"""
dry_run = request.dry_run if request else False
builder_graph_id = request.builder_graph_id if request else None
logger.info(
f"Creating session with user_id: "
f"...{user_id[-8:] if len(user_id) > 8 else '<redacted>'}"
f"{', dry_run=True' if dry_run else ''}"
f"{f', builder_graph_id={builder_graph_id}' if builder_graph_id else ''}"
)
session = await create_chat_session(user_id, dry_run=dry_run)
if builder_graph_id:
session = await get_or_create_builder_session(user_id, builder_graph_id)
else:
session = await create_chat_session(user_id, dry_run=dry_run)
return CreateSessionResponse(
id=session.session_id,
@@ -346,6 +455,31 @@ async def delete_session(
return Response(status_code=204)
@router.delete(
"/sessions/{session_id}/stream",
dependencies=[Security(auth.requires_user)],
status_code=204,
)
async def disconnect_session_stream(
session_id: str,
user_id: Annotated[str, Security(auth.get_user_id)],
) -> Response:
"""Disconnect all active SSE listeners for a session.
Called by the frontend when the user switches away from a chat so the
backend releases XREAD listeners immediately rather than waiting for
the 5-10 s timeout.
"""
session = await get_chat_session(session_id, user_id)
if not session:
raise HTTPException(
status_code=404,
detail=f"Session {session_id} not found or access denied",
)
await stream_registry.disconnect_all_listeners(session_id)
return Response(status_code=204)
@router.patch(
"/sessions/{session_id}/title",
summary="Update session title",
@@ -389,60 +523,68 @@ async def update_session_title_route(
async def get_session(
session_id: str,
user_id: Annotated[str, Security(auth.get_user_id)],
limit: int = Query(default=50, ge=1, le=200),
before_sequence: int | None = Query(default=None, ge=0),
) -> SessionDetailResponse:
"""
Retrieve the details of a specific chat session.
Looks up a chat session by ID for the given user (if authenticated) and returns all session data including messages.
If there's an active stream for this session, returns active_stream info for reconnection.
Args:
session_id: The unique identifier for the desired chat session.
user_id: The optional authenticated user ID, or None for anonymous access.
Returns:
SessionDetailResponse: Details for the requested session, including active_stream info if applicable.
Supports cursor-based pagination via ``limit`` and ``before_sequence``.
When no pagination params are provided, returns the most recent messages.
"""
session = await get_chat_session(session_id, user_id)
if not session:
page = await get_chat_messages_paginated(
session_id, limit, before_sequence, user_id=user_id
)
if page is None:
raise NotFoundError(f"Session {session_id} not found.")
messages = [message.model_dump() for message in session.messages]
messages = [
_strip_injected_context(message.model_dump()) for message in page.messages
]
# Check if there's an active stream for this session
# Only check active stream on initial load (not on "load more" requests)
active_stream_info = None
active_session, last_message_id = await stream_registry.get_active_session(
session_id, user_id
)
logger.info(
f"[GET_SESSION] session={session_id}, active_session={active_session is not None}, "
f"msg_count={len(messages)}, last_role={messages[-1].get('role') if messages else 'none'}"
)
if active_session:
# Keep the assistant message (including tool_calls) so the frontend can
# render the correct tool UI (e.g. CreateAgent with mini game).
# convertChatSessionToUiMessages handles isComplete=false by setting
# tool parts without output to state "input-available".
active_stream_info = ActiveStreamInfo(
turn_id=active_session.turn_id,
last_message_id=last_message_id,
if before_sequence is None:
active_session, last_message_id = await stream_registry.get_active_session(
session_id, user_id
)
if active_session:
active_stream_info = ActiveStreamInfo(
turn_id=active_session.turn_id,
last_message_id=last_message_id,
started_at=active_session.created_at.isoformat(),
)
# Skip session metadata on "load more" — frontend only needs messages
if before_sequence is not None:
return SessionDetailResponse(
id=page.session.session_id,
created_at=page.session.started_at.isoformat(),
updated_at=page.session.updated_at.isoformat(),
user_id=page.session.user_id or None,
messages=messages,
active_stream=None,
has_more_messages=page.has_more,
oldest_sequence=page.oldest_sequence,
total_prompt_tokens=0,
total_completion_tokens=0,
)
# Sum token usage from session
total_prompt = sum(u.prompt_tokens for u in session.usage)
total_completion = sum(u.completion_tokens for u in session.usage)
total_prompt = sum(u.prompt_tokens for u in page.session.usage)
total_completion = sum(u.completion_tokens for u in page.session.usage)
return SessionDetailResponse(
id=session.session_id,
created_at=session.started_at.isoformat(),
updated_at=session.updated_at.isoformat(),
user_id=session.user_id or None,
id=page.session.session_id,
created_at=page.session.started_at.isoformat(),
updated_at=page.session.updated_at.isoformat(),
user_id=page.session.user_id or None,
messages=messages,
active_stream=active_stream_info,
has_more_messages=page.has_more,
oldest_sequence=page.oldest_sequence,
total_prompt_tokens=total_prompt,
total_completion_tokens=total_completion,
metadata=session.metadata,
metadata=page.session.metadata,
)
@@ -451,21 +593,27 @@ async def get_session(
)
async def get_copilot_usage(
user_id: Annotated[str, Security(auth.get_user_id)],
) -> CoPilotUsageStatus:
) -> CoPilotUsagePublic:
"""Get CoPilot usage status for the authenticated user.
Returns current token usage vs limits for daily and weekly windows.
Global defaults sourced from LaunchDarkly (falling back to config).
Returns the percentage of the daily/weekly allowance used — not the
raw spend or cap — so clients cannot derive per-turn cost or platform
margins. Global defaults sourced from LaunchDarkly (falling back to
config). Includes the user's rate-limit tier.
"""
daily_limit, weekly_limit = await get_global_rate_limits(
user_id, config.daily_token_limit, config.weekly_token_limit
daily_limit, weekly_limit, tier = await get_global_rate_limits(
user_id,
config.daily_cost_limit_microdollars,
config.weekly_cost_limit_microdollars,
)
return await get_usage_status(
status = await get_usage_status(
user_id=user_id,
daily_token_limit=daily_limit,
weekly_token_limit=weekly_limit,
daily_cost_limit=daily_limit,
weekly_cost_limit=weekly_limit,
rate_limit_reset_cost=config.rate_limit_reset_cost,
tier=tier,
)
return CoPilotUsagePublic.from_status(status)
class RateLimitResetResponse(BaseModel):
@@ -474,7 +622,9 @@ class RateLimitResetResponse(BaseModel):
success: bool
credits_charged: int = Field(description="Credits charged (in cents)")
remaining_balance: int = Field(description="Credit balance after charge (in cents)")
usage: CoPilotUsageStatus = Field(description="Updated usage status after reset")
usage: CoPilotUsagePublic = Field(
description="Updated usage status after reset (percentages only)"
)
@router.post(
@@ -498,7 +648,7 @@ async def reset_copilot_usage(
) -> RateLimitResetResponse:
"""Reset the daily CoPilot rate limit by spending credits.
Allows users who have hit their daily token limit to spend credits
Allows users who have hit their daily cost limit to spend credits
to reset their daily usage counter and continue working.
Returns 400 if the feature is disabled or the user is not over the limit.
Returns 402 if the user has insufficient credits.
@@ -516,8 +666,10 @@ async def reset_copilot_usage(
detail="Rate limit reset is not available (credit system is disabled).",
)
daily_limit, weekly_limit = await get_global_rate_limits(
user_id, config.daily_token_limit, config.weekly_token_limit
daily_limit, weekly_limit, tier = await get_global_rate_limits(
user_id,
config.daily_cost_limit_microdollars,
config.weekly_cost_limit_microdollars,
)
if daily_limit <= 0:
@@ -550,10 +702,13 @@ async def reset_copilot_usage(
try:
# Verify the user is actually at or over their daily limit.
# (rate_limit_reset_cost intentionally omitted — this object is only
# used for limit checks, not returned to the client.)
usage_status = await get_usage_status(
user_id=user_id,
daily_token_limit=daily_limit,
weekly_token_limit=weekly_limit,
daily_cost_limit=daily_limit,
weekly_cost_limit=weekly_limit,
tier=tier,
)
if daily_limit > 0 and usage_status.daily.used < daily_limit:
raise HTTPException(
@@ -587,7 +742,7 @@ async def reset_copilot_usage(
# Reset daily usage in Redis. If this fails, refund the credits
# so the user is not charged for a service they did not receive.
if not await reset_daily_usage(user_id, daily_token_limit=daily_limit):
if not await reset_daily_usage(user_id, daily_cost_limit=daily_limit):
# Compensate: refund the charged credits.
refunded = False
try:
@@ -623,19 +778,20 @@ async def reset_copilot_usage(
finally:
await release_reset_lock(user_id)
# Return updated usage status.
# Return updated usage status (public schema — percentages only).
updated_usage = await get_usage_status(
user_id=user_id,
daily_token_limit=daily_limit,
weekly_token_limit=weekly_limit,
daily_cost_limit=daily_limit,
weekly_cost_limit=weekly_limit,
rate_limit_reset_cost=config.rate_limit_reset_cost,
tier=tier,
)
return RateLimitResetResponse(
success=True,
credits_charged=cost,
remaining_balance=remaining,
usage=updated_usage,
usage=CoPilotUsagePublic.from_status(updated_usage),
)
@@ -684,38 +840,81 @@ async def cancel_session_task(
return CancelSessionResponse(cancelled=True)
def _ui_message_stream_headers() -> dict[str, str]:
return {
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"X-Accel-Buffering": "no",
"x-vercel-ai-ui-message-stream": "v1",
}
def _empty_ui_message_stream_response() -> StreamingResponse:
# Stable placeholder messageId for the empty queued-mid-turn stream.
# Real turns generate per-message UUIDs via the executor; this stream
# has no message to attach to, but the AI SDK parser still requires a
# non-empty ``messageId`` field on ``StreamStart``.
message_id = uuid4().hex
async def event_generator() -> AsyncGenerator[str, None]:
# Vercel AI SDK's UI-message-stream parser expects symmetric
# start/finish framing at both stream and step level — every
# non-empty turn emits the pair. Without an opener, today's parser
# tolerates the closer (no active parts to flush) but a future SDK
# tightening would silently break the queue-mid-turn UX. Emit the
# full empty pair so the contract stays correct.
yield StreamStart(messageId=message_id).to_sse()
yield StreamStartStep().to_sse()
yield StreamFinishStep().to_sse()
yield StreamFinish().to_sse()
yield "data: [DONE]\n\n"
return StreamingResponse(
event_generator(),
media_type="text/event-stream",
headers=_ui_message_stream_headers(),
)
@router.post(
"/sessions/{session_id}/stream",
responses={
404: {"description": "Session not found or access denied"},
429: {"description": "Cost rate-limit or call-frequency cap exceeded"},
},
)
async def stream_chat_post(
session_id: str,
request: StreamChatRequest,
user_id: str = Security(auth.get_user_id),
):
"""
Stream chat responses for a session (POST with context support).
"""Start a new turn and return an AI SDK UI message stream.
Streams the AI/completion responses in real time over Server-Sent Events (SSE), including:
- Text fragments as they are generated
- Tool call UI elements (if invoked)
- Tool execution results
Returns an SSE stream (``text/event-stream``) with Vercel AI SDK chunks
(text fragments, tool-call UI, tool results). The generation runs in a
background task that survives client disconnects; reconnect via
``GET /sessions/{session_id}/stream`` to resume.
The AI generation runs in a background task that continues even if the client disconnects.
All chunks are written to a per-turn Redis stream for reconnection support. If the client
disconnects, they can reconnect using GET /sessions/{session_id}/stream to resume.
Follow-up messages typed while a turn is already running should use
``POST /sessions/{session_id}/messages/pending``. If an older client still
posts that follow-up here, we queue it defensively but still return a valid
empty UI-message stream so AI SDK transports never receive a JSON body from
the stream endpoint.
Args:
session_id: The chat session identifier to associate with the streamed messages.
request: Request body containing message, is_user_message, and optional context.
session_id: The chat session identifier.
request: Request body with message, is_user_message, and optional context.
user_id: Authenticated user ID.
Returns:
StreamingResponse: SSE-formatted response chunks.
"""
import asyncio
import time
stream_start_time = time.perf_counter()
# Wall-clock arrival time, propagated to the executor so the turn-start
# drain can order pending messages relative to this request (pending
# pushed BEFORE this instant were typed earlier; pending pushed AFTER
# are race-path follow-ups typed while /stream was still processing).
request_arrival_at = time.time()
log_meta = {"component": "ChatStream", "session_id": session_id, "user_id": user_id}
logger.info(
@@ -723,7 +922,31 @@ async def stream_chat_post(
f"user={user_id}, message_len={len(request.message)}",
extra={"json_fields": log_meta},
)
await _validate_and_get_session(session_id, user_id)
session = await _validate_and_get_session(session_id, user_id)
if (
request.is_user_message
and request.message
and await is_turn_in_flight(session_id)
):
try:
await queue_pending_for_http(
session_id=session_id,
user_id=user_id,
message=request.message,
context=request.context,
file_ids=request.file_ids,
)
return _empty_ui_message_stream_response()
except HTTPException as exc:
if exc.status_code != 409:
raise
# Permission resolution is only needed below for the actual turn — keep
# it after the queue-fall-through so a queued mid-turn request returns
# without paying the work.
builder_permissions = resolve_session_permissions(session)
logger.info(
f"[TIMING] session validated in {(time.perf_counter() - stream_start_time) * 1000:.1f}ms",
extra={
@@ -734,18 +957,20 @@ async def stream_chat_post(
},
)
# Pre-turn rate limit check (token-based).
# Pre-turn rate limit check (cost-based, microdollars).
# check_rate_limit short-circuits internally when both limits are 0.
# Global defaults sourced from LaunchDarkly, falling back to config.
if user_id:
try:
daily_limit, weekly_limit = await get_global_rate_limits(
user_id, config.daily_token_limit, config.weekly_token_limit
daily_limit, weekly_limit, _ = await get_global_rate_limits(
user_id,
config.daily_cost_limit_microdollars,
config.weekly_cost_limit_microdollars,
)
await check_rate_limit(
user_id=user_id,
daily_token_limit=daily_limit,
weekly_token_limit=weekly_limit,
daily_cost_limit=daily_limit,
weekly_cost_limit=weekly_limit,
)
except RateLimitExceeded as e:
raise HTTPException(status_code=429, detail=str(e)) from e
@@ -754,87 +979,75 @@ async def stream_chat_post(
# Also sanitise file_ids so only validated, workspace-scoped IDs are
# forwarded downstream (e.g. to the executor via enqueue_copilot_turn).
sanitized_file_ids: list[str] | None = None
if request.file_ids and user_id:
# Filter to valid UUIDs only to prevent DB abuse
valid_ids = [fid for fid in request.file_ids if _UUID_RE.match(fid)]
if valid_ids:
workspace = await get_or_create_workspace(user_id)
# Batch query instead of N+1
files = await UserWorkspaceFile.prisma().find_many(
where={
"id": {"in": valid_ids},
"workspaceId": workspace.id,
"isDeleted": False,
}
)
# Only keep IDs that actually exist in the user's workspace
sanitized_file_ids = [wf.id for wf in files] or None
file_lines: list[str] = [
f"- {wf.name} ({wf.mimeType}, {round(wf.sizeBytes / 1024, 1)} KB), file_id={wf.id}"
for wf in files
]
if file_lines:
files_block = (
"\n\n[Attached files]\n"
+ "\n".join(file_lines)
+ "\nUse read_workspace_file with the file_id to access file contents."
)
request.message += files_block
if request.file_ids:
files = await resolve_workspace_files(user_id, request.file_ids)
sanitized_file_ids = [wf.id for wf in files] or None
request.message += build_files_block(files)
# Atomically append user message to session BEFORE creating task to avoid
# race condition where GET_SESSION sees task as "running" but message isn't
# saved yet. append_and_save_message re-fetches inside a lock to prevent
# message loss from concurrent requests.
# saved yet. append_and_save_message returns None when a duplicate is
# detected — in that case skip enqueue to avoid processing the message twice.
is_duplicate_message = False
if request.message:
message = ChatMessage(
role="user" if request.is_user_message else "assistant",
content=request.message,
)
if request.is_user_message:
logger.info(f"[STREAM] Saving user message to session {session_id}")
is_duplicate_message = (
await append_and_save_message(session_id, message)
) is None
logger.info(f"[STREAM] User message saved for session {session_id}")
if not is_duplicate_message and request.is_user_message:
track_user_message(
user_id=user_id,
session_id=session_id,
message_length=len(request.message),
)
logger.info(f"[STREAM] Saving user message to session {session_id}")
await append_and_save_message(session_id, message)
logger.info(f"[STREAM] User message saved for session {session_id}")
# Create a task in the stream registry for reconnection support
turn_id = str(uuid4())
log_meta["turn_id"] = turn_id
session_create_start = time.perf_counter()
await stream_registry.create_session(
session_id=session_id,
user_id=user_id,
tool_call_id="chat_stream",
tool_name="chat",
turn_id=turn_id,
)
logger.info(
f"[TIMING] create_session completed in {(time.perf_counter() - session_create_start) * 1000:.1f}ms",
extra={
"json_fields": {
**log_meta,
"duration_ms": (time.perf_counter() - session_create_start) * 1000,
}
},
)
# Per-turn stream is always fresh (unique turn_id), subscribe from beginning
subscribe_from_id = "0-0"
await enqueue_copilot_turn(
session_id=session_id,
user_id=user_id,
message=request.message,
turn_id=turn_id,
is_user_message=request.is_user_message,
context=request.context,
file_ids=sanitized_file_ids,
)
# Create a task in the stream registry for reconnection support.
# For duplicate messages, skip create_session entirely so the infra-retry
# client subscribes to the *existing* turn's Redis stream and receives the
# in-progress executor output rather than an empty stream.
turn_id = ""
if not is_duplicate_message:
turn_id = str(uuid4())
log_meta["turn_id"] = turn_id
session_create_start = time.perf_counter()
await stream_registry.create_session(
session_id=session_id,
user_id=user_id,
tool_call_id="chat_stream",
tool_name="chat",
turn_id=turn_id,
)
logger.info(
f"[TIMING] create_session completed in {(time.perf_counter() - session_create_start) * 1000:.1f}ms",
extra={
"json_fields": {
**log_meta,
"duration_ms": (time.perf_counter() - session_create_start) * 1000,
}
},
)
await enqueue_copilot_turn(
session_id=session_id,
user_id=user_id,
message=request.message,
turn_id=turn_id,
is_user_message=request.is_user_message,
context=request.context,
file_ids=sanitized_file_ids,
mode=request.mode,
model=request.model,
permissions=builder_permissions,
request_arrival_at=request_arrival_at,
)
else:
logger.info(
f"[STREAM] Duplicate message detected for session {session_id}, skipping enqueue"
)
setup_time = (time.perf_counter() - stream_start_time) * 1000
logger.info(
@@ -842,6 +1055,9 @@ async def stream_chat_post(
extra={"json_fields": {**log_meta, "setup_time_ms": setup_time}},
)
# Per-turn stream is always fresh (unique turn_id), subscribe from beginning
subscribe_from_id = "0-0"
# SSE endpoint that subscribes to the task's stream
async def event_generator() -> AsyncGenerator[str, None]:
import time as time_module
@@ -866,7 +1082,6 @@ async def stream_chat_post(
if subscriber_queue is None:
yield StreamFinish().to_sse()
yield "data: [DONE]\n\n"
return
# Read from the subscriber queue and yield to SSE
@@ -896,7 +1111,6 @@ async def stream_chat_post(
yield chunk.to_sse()
# Check for finish signal
if isinstance(chunk, StreamFinish):
total_time = time_module.perf_counter() - event_gen_start
logger.info(
@@ -911,6 +1125,7 @@ async def stream_chat_post(
},
)
break
except asyncio.TimeoutError:
yield StreamHeartbeat().to_sse()
@@ -925,7 +1140,6 @@ async def stream_chat_post(
}
},
)
pass # Client disconnected - background task continues
except Exception as e:
elapsed = (time_module.perf_counter() - event_gen_start) * 1000
logger.error(
@@ -970,12 +1184,62 @@ async def stream_chat_post(
return StreamingResponse(
event_generator(),
media_type="text/event-stream",
headers={
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"X-Accel-Buffering": "no", # Disable nginx buffering
"x-vercel-ai-ui-message-stream": "v1", # AI SDK protocol header
},
headers=_ui_message_stream_headers(),
)
@router.post(
"/sessions/{session_id}/messages/pending",
response_model=QueuePendingMessageResponse,
responses={
404: {"description": "Session not found or access denied"},
409: {"description": "Session has no active turn to receive pending messages"},
429: {"description": "Call-frequency cap exceeded"},
},
)
async def queue_pending_message(
session_id: str,
request: QueuePendingMessageRequest,
user_id: str = Security(auth.get_user_id),
):
"""Queue a follow-up message while the session has an active turn."""
await _validate_and_get_session(session_id, user_id)
if not await is_turn_in_flight(session_id):
raise HTTPException(
status_code=409,
detail="Session has no active turn. Start a new turn with POST /stream.",
)
return await queue_pending_for_http(
session_id=session_id,
user_id=user_id,
message=request.message,
context=request.context,
file_ids=request.file_ids,
)
@router.get(
"/sessions/{session_id}/messages/pending",
response_model=PeekPendingMessagesResponse,
responses={
404: {"description": "Session not found or access denied"},
},
)
async def get_pending_messages(
session_id: str,
user_id: str = Security(auth.get_user_id),
):
"""Peek at the pending-message buffer without consuming it.
Returns the current contents of the session's pending message buffer
so the frontend can restore the queued-message indicator after a page
refresh and clear it correctly once a turn drains the buffer.
"""
await _validate_and_get_session(session_id, user_id)
pending = await peek_pending_messages(session_id)
return PeekPendingMessagesResponse(
messages=[m.content for m in pending],
count=len(pending),
)
@@ -984,6 +1248,7 @@ async def stream_chat_post(
)
async def resume_session_stream(
session_id: str,
last_chunk_id: str | None = Query(default=None, include_in_schema=False),
user_id: str = Security(auth.get_user_id),
):
"""
@@ -993,27 +1258,26 @@ async def resume_session_stream(
Checks for an active (in-progress) task on the session and either replays
the full SSE stream or returns 204 No Content if nothing is running.
Args:
session_id: The chat session identifier.
user_id: Optional authenticated user ID.
Returns:
StreamingResponse (SSE) when an active stream exists,
or 204 No Content when there is nothing to resume.
Always replays the active turn from ``0-0``. The AI SDK UI-message parser
keeps text/reasoning part state inside a single parser instance; resuming
from a Redis cursor can skip the ``*-start`` events required by later
``*-delta`` chunks.
"""
import asyncio
active_session, last_message_id = await stream_registry.get_active_session(
active_session, _latest_backend_id = await stream_registry.get_active_session(
session_id, user_id
)
if not active_session:
return Response(status_code=204)
# Always replay from the beginning ("0-0") on resume.
# We can't use last_message_id because it's the latest ID in the backend
# stream, not the latest the frontend received — the gap causes lost
# messages. The frontend deduplicates replayed content.
if last_chunk_id:
logger.info(
"Ignoring deprecated last_chunk_id on stream resume",
extra={"session_id": session_id, "last_chunk_id": last_chunk_id},
)
subscriber_queue = await stream_registry.subscribe_to_session(
session_id=session_id,
user_id=user_id,
@@ -1074,12 +1338,7 @@ async def resume_session_stream(
return StreamingResponse(
event_generator(),
media_type="text/event-stream",
headers={
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"X-Accel-Buffering": "no",
"x-vercel-ai-ui-message-stream": "v1",
},
headers=_ui_message_stream_headers(),
)
@@ -1231,6 +1490,11 @@ ToolResponseUnion = (
| DocPageResponse
| MCPToolsDiscoveredResponse
| MCPToolOutputResponse
| MemoryStoreResponse
| MemorySearchResponse
| MemoryForgetCandidatesResponse
| MemoryForgetConfirmResponse
| TodoWriteResponse
)

View File

@@ -7,6 +7,7 @@ allowing frontend code generators like Orval to create corresponding TypeScript
from pydantic import BaseModel, Field
from backend.data.model import CredentialsType
from backend.integrations.providers import ProviderName
from backend.sdk.registry import AutoRegistry
@@ -47,6 +48,57 @@ class ProviderNamesResponse(BaseModel):
)
class ProviderMetadata(BaseModel):
"""Display metadata for a provider, shown in the settings integrations UI."""
name: str = Field(description="Provider slug (e.g. ``github``)")
description: str | None = Field(
default=None,
description=(
"One-line human-readable summary of what the provider does. "
"Declared via ``ProviderBuilder.with_description(...)`` in the "
"provider's ``_config.py``. ``None`` if not set."
),
)
supported_auth_types: list[CredentialsType] = Field(
default_factory=list,
description=(
"Credential types this provider accepts. Drives which connection "
"tabs the settings UI renders for the provider. Empty list means "
"no auth types declared."
),
)
def get_supported_auth_types(name: str) -> list[CredentialsType]:
"""Return the provider's supported credential types from :class:`AutoRegistry`.
Populated by :meth:`ProviderBuilder.with_supported_auth_types` (or by
``with_oauth`` / ``with_api_key`` / ``with_user_password`` when the provider
uses the full builder chain). Returns an empty list for providers with no
auth types declared.
"""
provider = AutoRegistry.get_provider(name)
if provider is None:
return []
return sorted(provider.supported_auth_types)
def get_provider_description(name: str) -> str | None:
"""Return the provider's description from :class:`AutoRegistry`.
Descriptions are declared via ``ProviderBuilder.with_description(...)`` in
the provider's ``_config.py`` (SDK path) or in
``blocks/_static_provider_configs.py`` (for providers that don't yet have
their own directory). Returns ``None`` for providers with no registered
description.
"""
provider = AutoRegistry.get_provider(name)
if provider is None:
return None
return provider.description
class ProviderConstants(BaseModel):
"""
Model that exposes all provider names as a constant in the OpenAPI schema.

View File

@@ -14,7 +14,7 @@ from fastapi import (
Security,
status,
)
from pydantic import BaseModel, Field, SecretStr, model_validator
from pydantic import BaseModel, Field, model_validator
from starlette.status import HTTP_500_INTERNAL_SERVER_ERROR, HTTP_502_BAD_GATEWAY
from backend.api.features.library.db import set_preset_webhook, update_preset
@@ -29,15 +29,14 @@ from backend.data.integrations import (
wait_for_webhook_event,
)
from backend.data.model import (
APIKeyCredentials,
Credentials,
CredentialsType,
HostScopedCredentials,
OAuth2Credentials,
UserIntegrations,
is_sdk_default,
)
from backend.data.onboarding import OnboardingStep, complete_onboarding_step
from backend.data.user import get_user_integrations
from backend.executor.utils import add_graph_execution
from backend.integrations.ayrshare import AyrshareClient, SocialPlatform
from backend.integrations.credentials_store import (
@@ -48,7 +47,14 @@ from backend.integrations.creds_manager import (
IntegrationCredentialsManager,
create_mcp_oauth_handler,
)
from backend.integrations.managed_credentials import ensure_managed_credentials
from backend.integrations.managed_credentials import (
ensure_managed_credential,
ensure_managed_credentials,
)
from backend.integrations.managed_providers.ayrshare import AyrshareManagedProvider
from backend.integrations.managed_providers.ayrshare import (
settings_available as ayrshare_settings_available,
)
from backend.integrations.oauth import CREDENTIALS_BY_PROVIDER, HANDLERS_BY_NAME
from backend.integrations.providers import ProviderName
from backend.integrations.webhooks import get_webhook_manager
@@ -60,7 +66,14 @@ from backend.util.exceptions import (
)
from backend.util.settings import Settings
from .models import ProviderConstants, ProviderNamesResponse, get_all_provider_names
from .models import (
ProviderConstants,
ProviderMetadata,
ProviderNamesResponse,
get_all_provider_names,
get_provider_description,
get_supported_auth_types,
)
if TYPE_CHECKING:
from backend.integrations.oauth import BaseOAuthHandler
@@ -87,14 +100,23 @@ async def login(
scopes: Annotated[
str, Query(title="Comma-separated list of authorization scopes")
] = "",
credential_id: Annotated[
str | None,
Query(title="ID of existing credential to upgrade scopes for"),
] = None,
) -> LoginResponse:
handler = _get_provider_oauth_handler(request, provider)
requested_scopes = scopes.split(",") if scopes else []
if credential_id:
requested_scopes = await _prepare_scope_upgrade(
user_id, provider, credential_id, requested_scopes
)
# Generate and store a secure random state token along with the scopes
state_token, code_challenge = await creds_manager.store.store_state_token(
user_id, provider, requested_scopes
user_id, provider, requested_scopes, credential_id=credential_id
)
login_url = handler.get_login_url(
requested_scopes, state_token, code_challenge=code_challenge
@@ -216,7 +238,9 @@ async def callback(
)
# TODO: Allow specifying `title` to set on `credentials`
await creds_manager.create(user_id, credentials)
credentials = await _merge_or_create_credential(
user_id, provider, credentials, valid_state.credential_id
)
logger.debug(
f"Successfully processed OAuth callback for user {user_id} "
@@ -226,13 +250,38 @@ async def callback(
return to_meta_response(credentials)
# Bound the first-time sweep so a slow upstream (e.g. Ayrshare) can't hang
# the credential-list endpoint. On timeout we still kick off a fire-and-
# forget sweep so provisioning eventually completes; the user just won't
# see the managed cred until the next refresh.
_MANAGED_PROVISION_TIMEOUT_S = 10.0
async def _ensure_managed_credentials_bounded(user_id: str) -> None:
try:
await asyncio.wait_for(
ensure_managed_credentials(user_id, creds_manager.store),
timeout=_MANAGED_PROVISION_TIMEOUT_S,
)
except asyncio.TimeoutError:
logger.warning(
"Managed credential sweep exceeded %.1fs for user=%s; "
"continuing without it — provisioning will complete in background",
_MANAGED_PROVISION_TIMEOUT_S,
user_id,
)
asyncio.create_task(ensure_managed_credentials(user_id, creds_manager.store))
@router.get("/credentials", summary="List Credentials")
async def list_credentials(
user_id: Annotated[str, Security(get_user_id)],
) -> list[CredentialsMetaResponse]:
# Fire-and-forget: provision missing managed credentials in the background.
# The credential appears on the next page load; listing is never blocked.
asyncio.create_task(ensure_managed_credentials(user_id, creds_manager.store))
# Block on provisioning so managed credentials appear on the first load
# instead of after a refresh, but with a timeout so a slow upstream
# can't hang the endpoint. `_provisioned_users` short-circuits on
# repeat calls.
await _ensure_managed_credentials_bounded(user_id)
credentials = await creds_manager.store.get_all_creds(user_id)
return [
@@ -247,7 +296,7 @@ async def list_credentials_by_provider(
],
user_id: Annotated[str, Security(get_user_id)],
) -> list[CredentialsMetaResponse]:
asyncio.create_task(ensure_managed_credentials(user_id, creds_manager.store))
await _ensure_managed_credentials_bounded(user_id)
credentials = await creds_manager.store.get_creds_by_provider(user_id, provider)
return [
@@ -281,6 +330,115 @@ async def get_credential(
return to_meta_response(credential)
class PickerTokenResponse(BaseModel):
"""Short-lived OAuth access token shipped to the browser for rendering a
provider-hosted picker UI (e.g. Google Drive Picker). Deliberately narrow:
only the fields the client needs to initialize the picker widget. Issued
from the user's own stored credential so ownership and scope gating are
enforced by the credential lookup."""
access_token: str = Field(
description="OAuth access token suitable for the picker SDK call."
)
access_token_expires_at: int | None = Field(
default=None,
description="Unix timestamp at which the access token expires, if known.",
)
# Allowlist of (provider, scopes) tuples that may mint picker tokens. Only
# Drive-picker-capable scopes qualify so a caller can't use this endpoint to
# extract a GitHub / other-provider OAuth token for unrelated purposes. If a
# future provider integrates a hosted picker that needs a raw access token,
# add its specific picker-relevant scopes here.
_PICKER_TOKEN_ALLOWED_SCOPES: dict[ProviderName, frozenset[str]] = {
ProviderName.GOOGLE: frozenset(
[
"https://www.googleapis.com/auth/drive.file",
"https://www.googleapis.com/auth/drive.readonly",
"https://www.googleapis.com/auth/drive",
]
),
}
@router.post(
"/{provider}/credentials/{cred_id}/picker-token",
summary="Issue a short-lived access token for a provider-hosted picker",
operation_id="postV1GetPickerToken",
)
async def get_picker_token(
provider: Annotated[
ProviderName, Path(title="The provider that owns the credentials")
],
cred_id: Annotated[
str, Path(title="The ID of the OAuth2 credentials to mint a token from")
],
user_id: Annotated[str, Security(get_user_id)],
) -> PickerTokenResponse:
"""Return the raw access token for an OAuth2 credential so the frontend
can initialize a provider-hosted picker (e.g. Google Drive Picker).
`GET /{provider}/credentials/{cred_id}` deliberately strips secrets (see
`CredentialsMetaResponse` + `TestGetCredentialReturnsMetaOnly` in
`router_test.py`). That hardening broke the Drive picker, which needs the
raw access token to call `google.picker.Builder.setOAuthToken(...)`. This
endpoint carves a narrow, explicit hole: the caller must own the
credential, it must be OAuth2, and the endpoint returns only the access
token + its expiry — nothing else about the credential. SDK-default
credentials are excluded for the same reason as `get_credential`.
"""
if is_sdk_default(cred_id):
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND, detail="Credentials not found"
)
credential = await creds_manager.get(user_id, cred_id)
if not credential:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND, detail="Credentials not found"
)
if not provider_matches(credential.provider, provider):
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND, detail="Credentials not found"
)
if not isinstance(credential, OAuth2Credentials):
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="Picker tokens are only available for OAuth2 credentials",
)
if not credential.access_token:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="Credential has no access token; reconnect the account",
)
# Gate on provider+scope: only credentials that actually grant access to
# a provider-hosted picker flow may mint a token through this endpoint.
# Prevents using this path to extract bearer tokens for unrelated OAuth
# integrations (e.g. GitHub) that happen to be stored under the same user.
allowed_scopes = _PICKER_TOKEN_ALLOWED_SCOPES.get(provider)
if not allowed_scopes:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=(f"Picker tokens are not available for provider '{provider.value}'"),
)
cred_scopes = set(credential.scopes or [])
if cred_scopes.isdisjoint(allowed_scopes):
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=(
"Credential does not grant any scope eligible for the picker. "
"Reconnect with the appropriate scope."
),
)
return PickerTokenResponse(
access_token=credential.access_token.get_secret_value(),
access_token_expires_at=credential.access_token_expires_at,
)
@router.post("/{provider}/credentials", status_code=201, summary="Create Credentials")
async def create_credentials(
user_id: Annotated[str, Security(get_user_id)],
@@ -574,6 +732,186 @@ async def _execute_webhook_preset_trigger(
# Continue processing - webhook should be resilient to individual failures
# -------------------- INCREMENTAL AUTH HELPERS -------------------- #
async def _prepare_scope_upgrade(
user_id: str,
provider: ProviderName,
credential_id: str,
requested_scopes: list[str],
) -> list[str]:
"""Validate an existing credential for scope upgrade and compute scopes.
For providers without native incremental auth (e.g. GitHub), returns the
union of existing + requested scopes. For providers that handle merging
server-side (e.g. Google with ``include_granted_scopes``), returns the
requested scopes unchanged.
Raises HTTPException on validation failure.
"""
# Platform-owned system credentials must never be upgraded — scope
# changes here would leak across every user that shares them.
if is_system_credential(credential_id):
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="System credentials cannot be upgraded",
)
existing = await creds_manager.store.get_creds_by_id(user_id, credential_id)
if not existing:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Credential to upgrade not found",
)
if not isinstance(existing, OAuth2Credentials):
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="Only OAuth2 credentials can be upgraded",
)
if not provider_matches(existing.provider, provider.value):
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="Credential provider does not match the requested provider",
)
if existing.is_managed:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="Managed credentials cannot be upgraded",
)
# Google handles scope merging via include_granted_scopes; others need
# the union of existing + new scopes in the login URL.
if provider != ProviderName.GOOGLE:
requested_scopes = list(set(requested_scopes) | set(existing.scopes))
return requested_scopes
async def _merge_or_create_credential(
user_id: str,
provider: ProviderName,
credentials: OAuth2Credentials,
credential_id: str | None,
) -> OAuth2Credentials:
"""Either upgrade an existing credential or create a new one.
When *credential_id* is set (explicit upgrade), merges scopes and updates
the existing credential. Otherwise, checks for an implicit merge (same
provider + username) before falling back to creating a new credential.
"""
if credential_id:
return await _upgrade_existing_credential(user_id, credential_id, credentials)
# Implicit merge: check for existing credential with same provider+username.
# Skip managed/system credentials and require a non-None username on both
# sides so we never accidentally merge unrelated credentials.
if credentials.username is None:
await creds_manager.create(user_id, credentials)
return credentials
existing_creds = await creds_manager.store.get_creds_by_provider(user_id, provider)
matching = next(
(
c
for c in existing_creds
if isinstance(c, OAuth2Credentials)
and not c.is_managed
and not is_system_credential(c.id)
and c.username is not None
and c.username == credentials.username
),
None,
)
if matching:
# Only merge into the existing credential when the new token
# already covers every scope we're about to advertise on it.
# Without this guard we'd overwrite ``matching.access_token`` with
# a narrower token while storing a wider ``scopes`` list — the
# record would claim authorizations the token does not grant, and
# blocks using the lost scopes would fail with opaque 401/403s
# until the user hits re-auth. On a narrowing login, keep the
# two credentials separate instead.
if set(credentials.scopes).issuperset(set(matching.scopes)):
return await _upgrade_existing_credential(user_id, matching.id, credentials)
await creds_manager.create(user_id, credentials)
return credentials
async def _upgrade_existing_credential(
user_id: str,
existing_cred_id: str,
new_credentials: OAuth2Credentials,
) -> OAuth2Credentials:
"""Merge scopes from *new_credentials* into an existing credential."""
# Defense-in-depth: re-check system and provider invariants right before
# the write. The login-time check in `_prepare_scope_upgrade` can go stale
# by the time the callback runs, and the implicit-merge path bypasses
# login-time validation entirely, so every write-path must enforce these
# on its own.
if is_system_credential(existing_cred_id):
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="System credentials cannot be upgraded",
)
existing = await creds_manager.store.get_creds_by_id(user_id, existing_cred_id)
if not existing or not isinstance(existing, OAuth2Credentials):
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="Credential to upgrade not found",
)
if existing.is_managed:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="Managed credentials cannot be upgraded",
)
if not provider_matches(existing.provider, new_credentials.provider):
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="Credential provider does not match the requested provider",
)
if (
existing.username
and new_credentials.username
and existing.username != new_credentials.username
):
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="Username mismatch: authenticated as a different user",
)
# Operate on a copy so the caller's ``new_credentials`` object is not
# mutated out from under them. Every caller today immediately discards
# or replaces its reference, but the implicit-merge path in
# ``_merge_or_create_credential`` reads ``credentials.scopes`` before
# calling into us — a future reader after the call would otherwise
# silently see the overwritten values.
merged = new_credentials.model_copy(deep=True)
merged.id = existing.id
merged.title = existing.title
merged.scopes = list(set(existing.scopes) | set(new_credentials.scopes))
merged.metadata = {
**(existing.metadata or {}),
**(new_credentials.metadata or {}),
}
# Preserve the existing refresh_token and username if the incremental
# response doesn't carry them. Providers like Google only return a
# refresh_token on first authorization — dropping it here would orphan
# the credential on the next access-token expiry, forcing the user to
# re-auth from scratch. Username is similarly sticky: if we've already
# resolved it for this credential, keep it rather than silently
# blanking it on an incremental upgrade.
if not merged.refresh_token and existing.refresh_token:
merged.refresh_token = existing.refresh_token
merged.refresh_token_expires_at = existing.refresh_token_expires_at
if not merged.username and existing.username:
merged.username = existing.username
await creds_manager.update(user_id, merged)
return merged
# --------------------------- UTILITIES ---------------------------- #
@@ -784,12 +1122,21 @@ def _get_provider_oauth_handler(
async def get_ayrshare_sso_url(
user_id: Annotated[str, Security(get_user_id)],
) -> AyrshareSSOResponse:
"""
Generate an SSO URL for Ayrshare social media integration.
"""Generate a JWT SSO URL so the user can link their social accounts.
Returns:
dict: Contains the SSO URL for Ayrshare integration
The per-user Ayrshare profile key is provisioned and persisted as a
standard ``is_managed=True`` credential by
:class:`~backend.integrations.managed_providers.ayrshare.AyrshareManagedProvider`.
This endpoint only signs a short-lived JWT pointing at the Ayrshare-
hosted social-linking page; all profile lifecycle logic lives with the
managed provider.
"""
if not ayrshare_settings_available():
raise HTTPException(
status_code=HTTP_500_INTERNAL_SERVER_ERROR,
detail="Ayrshare integration is not configured",
)
try:
client = AyrshareClient()
except MissingConfigError:
@@ -798,66 +1145,63 @@ async def get_ayrshare_sso_url(
detail="Ayrshare integration is not configured",
)
# Ayrshare profile key is stored in the credentials store
# It is generated when creating a new profile, if there is no profile key,
# we create a new profile and store the profile key in the credentials store
user_integrations: UserIntegrations = await get_user_integrations(user_id)
profile_key = user_integrations.managed_credentials.ayrshare_profile_key
if not profile_key:
logger.debug(f"Creating new Ayrshare profile for user {user_id}")
try:
profile = await client.create_profile(
title=f"User {user_id}", messaging_active=True
)
profile_key = profile.profileKey
await creds_manager.store.set_ayrshare_profile_key(user_id, profile_key)
except Exception as e:
logger.error(f"Error creating Ayrshare profile for user {user_id}: {e}")
raise HTTPException(
status_code=HTTP_502_BAD_GATEWAY,
detail="Failed to create Ayrshare profile",
)
else:
logger.debug(f"Using existing Ayrshare profile for user {user_id}")
profile_key_str = (
profile_key.get_secret_value()
if isinstance(profile_key, SecretStr)
else str(profile_key)
# On-demand provisioning: AyrshareManagedProvider opts out of the
# credentials sweep (profile quota is per-user subscription-bound). This
# endpoint is the only trigger that provisions a profile — one Ayrshare
# profile per user who actually opens the connect flow, not one per
# every authenticated user.
provisioned = await ensure_managed_credential(
user_id, creds_manager.store, AyrshareManagedProvider()
)
if not provisioned:
raise HTTPException(
status_code=HTTP_502_BAD_GATEWAY,
detail="Failed to provision Ayrshare profile",
)
ayrshare_creds = [
c
for c in await creds_manager.store.get_creds_by_provider(user_id, "ayrshare")
if c.is_managed and isinstance(c, APIKeyCredentials)
]
if not ayrshare_creds:
logger.error(
"Ayrshare credential provisioning did not produce a credential "
"for user %s",
user_id,
)
raise HTTPException(
status_code=HTTP_502_BAD_GATEWAY,
detail="Failed to provision Ayrshare profile",
)
profile_key_str = ayrshare_creds[0].api_key.get_secret_value()
private_key = settings.secrets.ayrshare_jwt_key
# Ayrshare JWT expiry is 2880 minutes (48 hours)
# Ayrshare JWT max lifetime is 2880 minutes (48 h).
max_expiry_minutes = 2880
try:
logger.debug(f"Generating Ayrshare JWT for user {user_id}")
jwt_response = await client.generate_jwt(
private_key=private_key,
profile_key=profile_key_str,
# `allowed_social` is the set of networks the Ayrshare-hosted
# social-linking page will *offer* the user to connect. Blocks
# exist for more platforms than are listed here; the list is
# deliberately narrower so the rollout can verify each network
# end-to-end before widening the user-visible surface. Keep
# in sync with tested platforms — extend as each is verified
# against the block + Ayrshare's network-specific quirks.
allowed_social=[
# NOTE: We are enabling platforms one at a time
# to speed up the development process
# SocialPlatform.FACEBOOK,
SocialPlatform.TWITTER,
SocialPlatform.LINKEDIN,
SocialPlatform.INSTAGRAM,
SocialPlatform.YOUTUBE,
# SocialPlatform.REDDIT,
# SocialPlatform.TELEGRAM,
# SocialPlatform.GOOGLE_MY_BUSINESS,
# SocialPlatform.PINTEREST,
SocialPlatform.TIKTOK,
# SocialPlatform.BLUESKY,
# SocialPlatform.SNAPCHAT,
# SocialPlatform.THREADS,
],
expires_in=max_expiry_minutes,
verify=True,
)
except Exception as e:
logger.error(f"Error generating Ayrshare JWT for user {user_id}: {e}")
except Exception as exc:
logger.error("Error generating Ayrshare JWT for user %s: %s", user_id, exc)
raise HTTPException(
status_code=HTTP_502_BAD_GATEWAY, detail="Failed to generate JWT"
)
@@ -867,20 +1211,37 @@ async def get_ayrshare_sso_url(
# === PROVIDER DISCOVERY ENDPOINTS ===
@router.get("/providers", response_model=List[str])
async def list_providers() -> List[str]:
@router.get("/providers", response_model=List[ProviderMetadata])
async def list_providers() -> List[ProviderMetadata]:
"""
Get a list of all available provider names.
Get metadata for every available provider.
Returns both statically defined providers (from ProviderName enum)
and dynamically registered providers (from SDK decorators).
Returns both statically defined providers (from ``ProviderName`` enum) and
dynamically registered providers (from SDK decorators). Each entry includes
a ``description`` declared via ``ProviderBuilder.with_description(...)`` in
the provider's ``_config.py``.
Note: The complete list of provider names is also available as a constant
in the generated TypeScript client via PROVIDER_NAMES.
"""
# Get all providers at runtime
# Ensure all block modules (and therefore every provider's _config.py) are
# imported before we read from AutoRegistry. Cached on first call.
try:
from backend.blocks import load_all_blocks
load_all_blocks()
except Exception as e:
logger.warning(f"Failed to load blocks for provider metadata: {e}")
all_providers = get_all_provider_names()
return all_providers
return [
ProviderMetadata(
name=name,
description=get_provider_description(name),
supported_auth_types=get_supported_auth_types(name),
)
for name in all_providers
]
@router.get("/providers/system", response_model=List[str])

View File

@@ -393,7 +393,7 @@ class TestEnsureManagedCredentials:
_PROVIDERS.update(saved)
_provisioned_users.pop("user-1", None)
provider.provision.assert_awaited_once_with("user-1")
provider.provision.assert_awaited_once_with("user-1", store)
store.add_managed_credential.assert_awaited_once_with("user-1", cred)
@pytest.mark.asyncio
@@ -568,3 +568,181 @@ class TestCleanupManagedCredentials:
_PROVIDERS.update(saved)
# No exception raised — cleanup failure is swallowed.
class TestGetPickerToken:
"""POST /{provider}/credentials/{cred_id}/picker-token must:
1. Return the access token for OAuth2 creds the caller owns.
2. 404 for non-owned, non-existent, or wrong-provider creds.
3. 400 for non-OAuth2 creds (API key, host-scoped, user/password).
4. 404 for SDK default creds (same hardening as get_credential).
5. Preserve the `TestGetCredentialReturnsMetaOnly` contract — the
existing meta-only endpoint must still strip secrets even after
this picker-token endpoint exists."""
def test_oauth2_owner_gets_access_token(self):
# Use a Google cred with a drive.file scope — only picker-eligible
# (provider, scope) pairs can mint a token. GitHub-style creds are
# explicitly rejected; see `test_non_picker_provider_rejected_as_400`.
cred = _make_oauth2_cred(
cred_id="cred-gdrive",
provider="google",
)
cred.scopes = ["https://www.googleapis.com/auth/drive.file"]
with patch(
"backend.api.features.integrations.router.creds_manager"
) as mock_mgr:
mock_mgr.get = AsyncMock(return_value=cred)
resp = client.post("/google/credentials/cred-gdrive/picker-token")
assert resp.status_code == 200
data = resp.json()
# The whole point of this endpoint: the access token IS returned here.
assert data["access_token"] == "ghp_secret_token"
# Only the two declared fields come back — nothing else leaks.
assert set(data.keys()) <= {"access_token", "access_token_expires_at"}
def test_non_picker_provider_rejected_as_400(self):
"""Provider allowlist: even with a valid OAuth2 credential, a
non-picker provider (GitHub, etc.) cannot mint a picker token.
Stops this endpoint from being used as a generic bearer-token
extraction path for any stored OAuth cred under the same user."""
cred = _make_oauth2_cred(provider="github")
with patch(
"backend.api.features.integrations.router.creds_manager"
) as mock_mgr:
mock_mgr.get = AsyncMock(return_value=cred)
resp = client.post("/github/credentials/cred-456/picker-token")
assert resp.status_code == 400
assert "not available for provider" in resp.json()["detail"]
assert "ghp_secret_token" not in str(resp.json())
def test_google_oauth_without_drive_scope_rejected(self):
"""Scope allowlist: a Google OAuth2 cred that only carries non-picker
scopes (e.g. gmail.readonly, calendar) cannot mint a picker token.
Forces the frontend to reconnect with a Drive scope before the
picker is available."""
cred = _make_oauth2_cred(provider="google")
cred.scopes = [
"https://www.googleapis.com/auth/gmail.readonly",
"https://www.googleapis.com/auth/calendar",
]
with patch(
"backend.api.features.integrations.router.creds_manager"
) as mock_mgr:
mock_mgr.get = AsyncMock(return_value=cred)
resp = client.post("/google/credentials/cred-456/picker-token")
assert resp.status_code == 400
assert "picker" in resp.json()["detail"].lower()
def test_api_key_credential_rejected_as_400(self):
cred = _make_api_key_cred()
with patch(
"backend.api.features.integrations.router.creds_manager"
) as mock_mgr:
mock_mgr.get = AsyncMock(return_value=cred)
resp = client.post("/openai/credentials/cred-123/picker-token")
assert resp.status_code == 400
# API keys must not silently fall through to a 200 response of some
# other shape — the client should see a clear shape rejection.
body = str(resp.json())
assert "sk-secret-key-value" not in body
def test_user_password_credential_rejected_as_400(self):
cred = _make_user_password_cred()
with patch(
"backend.api.features.integrations.router.creds_manager"
) as mock_mgr:
mock_mgr.get = AsyncMock(return_value=cred)
resp = client.post("/openai/credentials/cred-789/picker-token")
assert resp.status_code == 400
body = str(resp.json())
assert "s3cret-pass" not in body
assert "admin" not in body
def test_host_scoped_credential_rejected_as_400(self):
cred = _make_host_scoped_cred()
with patch(
"backend.api.features.integrations.router.creds_manager"
) as mock_mgr:
mock_mgr.get = AsyncMock(return_value=cred)
resp = client.post("/openai/credentials/cred-host/picker-token")
assert resp.status_code == 400
assert "top-secret" not in str(resp.json())
def test_missing_credential_returns_404(self):
with patch(
"backend.api.features.integrations.router.creds_manager"
) as mock_mgr:
mock_mgr.get = AsyncMock(return_value=None)
resp = client.post("/github/credentials/nonexistent/picker-token")
assert resp.status_code == 404
assert resp.json()["detail"] == "Credentials not found"
def test_wrong_provider_returns_404(self):
"""Symmetric with get_credential: provider mismatch is a generic
404, not a 400, so we don't leak existence of a credential the
caller doesn't own on that provider."""
cred = _make_oauth2_cred(provider="github")
with patch(
"backend.api.features.integrations.router.creds_manager"
) as mock_mgr:
mock_mgr.get = AsyncMock(return_value=cred)
resp = client.post("/google/credentials/cred-456/picker-token")
assert resp.status_code == 404
assert resp.json()["detail"] == "Credentials not found"
def test_sdk_default_returns_404(self):
"""SDK defaults are invisible to the user-facing API — picker-token
must not mint a token for them either."""
with patch(
"backend.api.features.integrations.router.creds_manager"
) as mock_mgr:
mock_mgr.get = AsyncMock()
resp = client.post("/openai/credentials/openai-default/picker-token")
assert resp.status_code == 404
mock_mgr.get.assert_not_called()
def test_oauth2_without_access_token_returns_400(self):
"""A stored OAuth2 cred whose access_token is missing can't satisfy
a picker init. Surface a clear reconnect instruction rather than
returning an empty string."""
cred = _make_oauth2_cred()
# Simulate a cred that lost its access token
object.__setattr__(cred, "access_token", None)
with patch(
"backend.api.features.integrations.router.creds_manager"
) as mock_mgr:
mock_mgr.get = AsyncMock(return_value=cred)
resp = client.post("/github/credentials/cred-456/picker-token")
assert resp.status_code == 400
assert "reconnect" in resp.json()["detail"].lower()
def test_meta_only_endpoint_still_strips_access_token(self):
"""Regression guard for the coexistence contract: the new
picker-token endpoint must NOT accidentally leak the token through
the meta-only GET endpoint. TestGetCredentialReturnsMetaOnly
covers this more broadly; this is a fast sanity check co-located
with the new endpoint's tests."""
cred = _make_oauth2_cred()
with patch(
"backend.api.features.integrations.router.creds_manager"
) as mock_mgr:
mock_mgr.get = AsyncMock(return_value=cred)
resp = client.get("/github/credentials/cred-456")
assert resp.status_code == 200
body = resp.json()
assert "access_token" not in body
assert "refresh_token" not in body
assert "ghp_secret_token" not in str(body)

View File

@@ -12,6 +12,7 @@ import prisma.models
import backend.api.features.library.model as library_model
import backend.data.graph as graph_db
from backend.api.features.library.db import _fetch_schedule_info
from backend.data.graph import GraphModel, GraphSettings
from backend.data.includes import library_agent_include
from backend.util.exceptions import NotFoundError
@@ -117,4 +118,5 @@ async def add_graph_to_library(
f"for store listing version #{store_listing_version_id} "
f"to library for user #{user_id}"
)
return library_model.LibraryAgent.from_db(added_agent)
schedule_info = await _fetch_schedule_info(user_id, graph_id=graph_model.id)
return library_model.LibraryAgent.from_db(added_agent, schedule_info=schedule_info)

View File

@@ -21,13 +21,17 @@ async def test_add_graph_to_library_create_new_agent() -> None:
"backend.api.features.library._add_to_library.library_model.LibraryAgent.from_db",
return_value=converted_agent,
) as mock_from_db,
patch(
"backend.api.features.library._add_to_library._fetch_schedule_info",
new=AsyncMock(return_value={}),
),
):
mock_prisma.return_value.create = AsyncMock(return_value=created_agent)
result = await add_graph_to_library("slv-id", graph_model, "user-id")
assert result is converted_agent
mock_from_db.assert_called_once_with(created_agent)
mock_from_db.assert_called_once_with(created_agent, schedule_info={})
# Verify create was called with correct data
create_call = mock_prisma.return_value.create.call_args
create_data = create_call.kwargs["data"]
@@ -54,6 +58,10 @@ async def test_add_graph_to_library_unique_violation_updates_existing() -> None:
"backend.api.features.library._add_to_library.library_model.LibraryAgent.from_db",
return_value=converted_agent,
) as mock_from_db,
patch(
"backend.api.features.library._add_to_library._fetch_schedule_info",
new=AsyncMock(return_value={}),
),
):
mock_prisma.return_value.create = AsyncMock(
side_effect=prisma.errors.UniqueViolationError(
@@ -65,7 +73,7 @@ async def test_add_graph_to_library_unique_violation_updates_existing() -> None:
result = await add_graph_to_library("slv-id", graph_model, "user-id")
assert result is converted_agent
mock_from_db.assert_called_once_with(updated_agent)
mock_from_db.assert_called_once_with(updated_agent, schedule_info={})
# Verify update was called with correct where and data
update_call = mock_prisma.return_value.update.call_args
assert update_call.kwargs["where"] == {

View File

@@ -1,6 +1,7 @@
import asyncio
import itertools
import logging
from datetime import datetime, timezone
from typing import Literal, Optional
import fastapi
@@ -43,6 +44,65 @@ config = Config()
integration_creds_manager = IntegrationCredentialsManager()
async def _fetch_execution_counts(user_id: str, graph_ids: list[str]) -> dict[str, int]:
"""Fetch execution counts per graph in a single batched query."""
if not graph_ids:
return {}
rows = await prisma.models.AgentGraphExecution.prisma().group_by(
by=["agentGraphId"],
where={
"userId": user_id,
"agentGraphId": {"in": graph_ids},
"isDeleted": False,
},
count=True,
)
return {
row["agentGraphId"]: int((row.get("_count") or {}).get("_all") or 0)
for row in rows
}
async def _fetch_schedule_info(
user_id: str, graph_id: Optional[str] = None
) -> dict[str, str]:
"""Fetch a map of graph_id → earliest next_run_time ISO string.
When `graph_id` is provided, the scheduler query is narrowed to that graph,
which is cheaper for single-agent lookups (detail page, post-update, etc.).
"""
try:
scheduler_client = get_scheduler_client()
schedules = await scheduler_client.get_execution_schedules(
graph_id=graph_id,
user_id=user_id,
)
earliest: dict[str, tuple[datetime, str]] = {}
for s in schedules:
parsed = _parse_iso_datetime(s.next_run_time)
if parsed is None:
continue
current = earliest.get(s.graph_id)
if current is None or parsed < current[0]:
earliest[s.graph_id] = (parsed, s.next_run_time)
return {graph_id: iso for graph_id, (_, iso) in earliest.items()}
except Exception:
logger.warning("Failed to fetch schedules for library agents", exc_info=True)
return {}
def _parse_iso_datetime(value: str) -> Optional[datetime]:
"""Parse an ISO 8601 datetime, tolerating `Z` and naive forms (assumed UTC)."""
try:
parsed = datetime.fromisoformat(value.replace("Z", "+00:00"))
except ValueError:
logger.warning("Failed to parse schedule next_run_time: %s", value)
return None
if parsed.tzinfo is None:
parsed = parsed.replace(tzinfo=timezone.utc)
return parsed
async def list_library_agents(
user_id: str,
search_term: Optional[str] = None,
@@ -137,12 +197,22 @@ async def list_library_agents(
logger.debug(f"Retrieved {len(library_agents)} library agents for user #{user_id}")
graph_ids = [a.agentGraphId for a in library_agents if a.agentGraphId]
execution_counts, schedule_info = await asyncio.gather(
_fetch_execution_counts(user_id, graph_ids),
_fetch_schedule_info(user_id),
)
# Only pass valid agents to the response
valid_library_agents: list[library_model.LibraryAgent] = []
for agent in library_agents:
try:
library_agent = library_model.LibraryAgent.from_db(agent)
library_agent = library_model.LibraryAgent.from_db(
agent,
execution_count_override=execution_counts.get(agent.agentGraphId),
schedule_info=schedule_info,
)
valid_library_agents.append(library_agent)
except Exception as e:
# Skip this agent if there was an error
@@ -214,12 +284,22 @@ async def list_favorite_library_agents(
f"Retrieved {len(library_agents)} favorite library agents for user #{user_id}"
)
graph_ids = [a.agentGraphId for a in library_agents if a.agentGraphId]
execution_counts, schedule_info = await asyncio.gather(
_fetch_execution_counts(user_id, graph_ids),
_fetch_schedule_info(user_id),
)
# Only pass valid agents to the response
valid_library_agents: list[library_model.LibraryAgent] = []
for agent in library_agents:
try:
library_agent = library_model.LibraryAgent.from_db(agent)
library_agent = library_model.LibraryAgent.from_db(
agent,
execution_count_override=execution_counts.get(agent.agentGraphId),
schedule_info=schedule_info,
)
valid_library_agents.append(library_agent)
except Exception as e:
# Skip this agent if there was an error
@@ -285,6 +365,12 @@ async def get_library_agent(id: str, user_id: str) -> library_model.LibraryAgent
where={"userId": store_listing.owningUserId}
)
schedule_info = (
await _fetch_schedule_info(user_id, graph_id=library_agent.AgentGraph.id)
if library_agent.AgentGraph
else {}
)
return library_model.LibraryAgent.from_db(
library_agent,
sub_graphs=(
@@ -294,6 +380,7 @@ async def get_library_agent(id: str, user_id: str) -> library_model.LibraryAgent
),
store_listing=store_listing,
profile=profile,
schedule_info=schedule_info,
)
@@ -329,7 +416,10 @@ async def get_library_agent_by_store_version_id(
},
include=library_agent_include(user_id),
)
return library_model.LibraryAgent.from_db(agent) if agent else None
if not agent:
return None
schedule_info = await _fetch_schedule_info(user_id, graph_id=agent.agentGraphId)
return library_model.LibraryAgent.from_db(agent, schedule_info=schedule_info)
async def get_library_agent_by_graph_id(
@@ -358,7 +448,10 @@ async def get_library_agent_by_graph_id(
assert agent.AgentGraph # make type checker happy
# Include sub-graphs so we can make a full credentials input schema
sub_graphs = await graph_db.get_sub_graphs(agent.AgentGraph)
return library_model.LibraryAgent.from_db(agent, sub_graphs=sub_graphs)
schedule_info = await _fetch_schedule_info(user_id, graph_id=agent.agentGraphId)
return library_model.LibraryAgent.from_db(
agent, sub_graphs=sub_graphs, schedule_info=schedule_info
)
async def add_generated_agent_image(
@@ -481,6 +574,11 @@ async def create_library_agent(
sensitive_action_safe_mode=sensitive_action_safe_mode,
).model_dump()
),
**(
{"Folder": {"connect": {"id": folder_id}}}
if folder_id and graph_entry is graph
else {}
),
},
},
include=library_agent_include(
@@ -495,7 +593,11 @@ async def create_library_agent(
for agent, graph in zip(library_agents, graph_entries):
asyncio.create_task(add_generated_agent_image(graph, user_id, agent.id))
return [library_model.LibraryAgent.from_db(agent) for agent in library_agents]
schedule_info = await _fetch_schedule_info(user_id)
return [
library_model.LibraryAgent.from_db(agent, schedule_info=schedule_info)
for agent in library_agents
]
async def update_agent_version_in_library(
@@ -557,7 +659,8 @@ async def update_agent_version_in_library(
f"Failed to update library agent for {agent_graph_id} v{agent_graph_version}"
)
return library_model.LibraryAgent.from_db(lib)
schedule_info = await _fetch_schedule_info(user_id, graph_id=agent_graph_id)
return library_model.LibraryAgent.from_db(lib, schedule_info=schedule_info)
async def create_graph_in_library(
@@ -640,6 +743,7 @@ async def update_library_agent_version_and_settings(
graph=agent_graph,
hitl_safe_mode=library.settings.human_in_the_loop_safe_mode,
sensitive_action_safe_mode=library.settings.sensitive_action_safe_mode,
builder_chat_session_id=library.settings.builder_chat_session_id,
)
if updated_settings != library.settings:
library = await update_library_agent(
@@ -1462,7 +1566,11 @@ async def bulk_move_agents_to_folder(
),
)
return [library_model.LibraryAgent.from_db(agent) for agent in agents]
schedule_info = await _fetch_schedule_info(user_id)
return [
library_model.LibraryAgent.from_db(agent, schedule_info=schedule_info)
for agent in agents
]
def collect_tree_ids(
@@ -1696,7 +1804,7 @@ async def create_preset_from_graph_execution(
raise NotFoundError(
f"Graph #{graph_execution.graph_id} not found or accessible"
)
elif len(graph.aggregate_credentials_inputs()) > 0:
elif len(graph.regular_credentials_inputs) > 0:
raise ValueError(
f"Graph execution #{graph_exec_id} can't be turned into a preset "
"because it was run before this feature existed "

View File

@@ -65,6 +65,11 @@ async def test_get_library_agents(mocker):
)
mock_library_agent.return_value.count = mocker.AsyncMock(return_value=1)
mocker.patch(
"backend.api.features.library.db._fetch_execution_counts",
new=mocker.AsyncMock(return_value={}),
)
# Call function
result = await db.list_library_agents("test-user")
@@ -353,3 +358,136 @@ async def test_create_library_agent_uses_upsert():
# Verify update branch restores soft-deleted/archived agents
assert data["update"]["isDeleted"] is False
assert data["update"]["isArchived"] is False
@pytest.mark.asyncio
async def test_list_favorite_library_agents(mocker):
mock_library_agents = [
prisma.models.LibraryAgent(
id="fav1",
userId="test-user",
agentGraphId="agent-fav",
settings="{}", # type: ignore
agentGraphVersion=1,
isCreatedByUser=False,
isDeleted=False,
isArchived=False,
createdAt=datetime.now(),
updatedAt=datetime.now(),
isFavorite=True,
useGraphIsActiveVersion=True,
AgentGraph=prisma.models.AgentGraph(
id="agent-fav",
version=1,
name="Favorite Agent",
description="My Favorite",
userId="other-user",
isActive=True,
createdAt=datetime.now(),
),
)
]
mock_library_agent = mocker.patch("prisma.models.LibraryAgent.prisma")
mock_library_agent.return_value.find_many = mocker.AsyncMock(
return_value=mock_library_agents
)
mock_library_agent.return_value.count = mocker.AsyncMock(return_value=1)
mocker.patch(
"backend.api.features.library.db._fetch_execution_counts",
new=mocker.AsyncMock(return_value={"agent-fav": 7}),
)
result = await db.list_favorite_library_agents("test-user")
assert len(result.agents) == 1
assert result.agents[0].id == "fav1"
assert result.agents[0].name == "Favorite Agent"
assert result.agents[0].graph_id == "agent-fav"
assert result.pagination.total_items == 1
assert result.pagination.total_pages == 1
assert result.pagination.current_page == 1
assert result.pagination.page_size == 50
@pytest.mark.asyncio
async def test_list_library_agents_skips_failed_agent(mocker):
"""Agents that fail parsing should be skipped — covers the except branch."""
mock_library_agents = [
prisma.models.LibraryAgent(
id="ua-bad",
userId="test-user",
agentGraphId="agent-bad",
settings="{}", # type: ignore
agentGraphVersion=1,
isCreatedByUser=False,
isDeleted=False,
isArchived=False,
createdAt=datetime.now(),
updatedAt=datetime.now(),
isFavorite=False,
useGraphIsActiveVersion=True,
AgentGraph=prisma.models.AgentGraph(
id="agent-bad",
version=1,
name="Bad Agent",
description="",
userId="other-user",
isActive=True,
createdAt=datetime.now(),
),
)
]
mock_library_agent = mocker.patch("prisma.models.LibraryAgent.prisma")
mock_library_agent.return_value.find_many = mocker.AsyncMock(
return_value=mock_library_agents
)
mock_library_agent.return_value.count = mocker.AsyncMock(return_value=1)
mocker.patch(
"backend.api.features.library.db._fetch_execution_counts",
new=mocker.AsyncMock(return_value={}),
)
mocker.patch(
"backend.api.features.library.model.LibraryAgent.from_db",
side_effect=Exception("parse error"),
)
result = await db.list_library_agents("test-user")
assert len(result.agents) == 0
assert result.pagination.total_items == 1
@pytest.mark.asyncio
async def test_fetch_execution_counts_empty_graph_ids():
result = await db._fetch_execution_counts("user-1", [])
assert result == {}
@pytest.mark.asyncio
async def test_fetch_execution_counts_uses_group_by(mocker):
mock_prisma = mocker.patch("prisma.models.AgentGraphExecution.prisma")
mock_prisma.return_value.group_by = mocker.AsyncMock(
return_value=[
{"agentGraphId": "graph-1", "_count": {"_all": 5}},
{"agentGraphId": "graph-2", "_count": {"_all": 2}},
]
)
result = await db._fetch_execution_counts(
"user-1", ["graph-1", "graph-2", "graph-3"]
)
assert result == {"graph-1": 5, "graph-2": 2}
mock_prisma.return_value.group_by.assert_called_once_with(
by=["agentGraphId"],
where={
"userId": "user-1",
"agentGraphId": {"in": ["graph-1", "graph-2", "graph-3"]},
"isDeleted": False,
},
count=True,
)

View File

@@ -214,6 +214,14 @@ class LibraryAgent(pydantic.BaseModel):
folder_name: str | None = None # Denormalized for display
recommended_schedule_cron: str | None = None
is_scheduled: bool = pydantic.Field(
default=False,
description="Whether this agent has active execution schedules",
)
next_scheduled_run: str | None = pydantic.Field(
default=None,
description="ISO 8601 timestamp of the next scheduled run, if any",
)
settings: GraphSettings = pydantic.Field(default_factory=GraphSettings)
marketplace_listing: Optional["MarketplaceListing"] = None
@@ -223,6 +231,8 @@ class LibraryAgent(pydantic.BaseModel):
sub_graphs: Optional[list[prisma.models.AgentGraph]] = None,
store_listing: Optional[prisma.models.StoreListing] = None,
profile: Optional[prisma.models.Profile] = None,
execution_count_override: Optional[int] = None,
schedule_info: Optional[dict[str, str]] = None,
) -> "LibraryAgent":
"""
Factory method that constructs a LibraryAgent from a Prisma LibraryAgent
@@ -258,10 +268,14 @@ class LibraryAgent(pydantic.BaseModel):
status = status_result.status
new_output = status_result.new_output
execution_count = len(executions)
execution_count = (
execution_count_override
if execution_count_override is not None
else len(executions)
)
success_rate: float | None = None
avg_correctness_score: float | None = None
if execution_count > 0:
if executions and execution_count > 0:
success_count = sum(
1
for e in executions
@@ -354,6 +368,10 @@ class LibraryAgent(pydantic.BaseModel):
folder_id=agent.folderId,
folder_name=agent.Folder.name if agent.Folder else None,
recommended_schedule_cron=agent.AgentGraph.recommendedScheduleCron,
is_scheduled=bool(schedule_info and agent.agentGraphId in schedule_info),
next_scheduled_run=(
schedule_info.get(agent.agentGraphId) if schedule_info else None
),
settings=_parse_settings(agent.settings),
marketplace_listing=marketplace_listing_data,
)

View File

@@ -1,11 +1,66 @@
import datetime
import prisma.enums
import prisma.models
import pytest
from . import model as library_model
def _make_library_agent(
*,
graph_id: str = "g1",
executions: list | None = None,
) -> prisma.models.LibraryAgent:
return prisma.models.LibraryAgent(
id="la1",
userId="u1",
agentGraphId=graph_id,
settings="{}", # type: ignore
agentGraphVersion=1,
isCreatedByUser=True,
isDeleted=False,
isArchived=False,
createdAt=datetime.datetime.now(),
updatedAt=datetime.datetime.now(),
isFavorite=False,
useGraphIsActiveVersion=True,
AgentGraph=prisma.models.AgentGraph(
id=graph_id,
version=1,
name="Agent",
description="Desc",
userId="u1",
isActive=True,
createdAt=datetime.datetime.now(),
Executions=executions,
),
)
def test_from_db_execution_count_override_covers_success_rate():
"""Covers execution_count_override is not None branch and executions/count > 0 block."""
now = datetime.datetime.now(datetime.timezone.utc)
exec1 = prisma.models.AgentGraphExecution(
id="exec-1",
agentGraphId="g1",
agentGraphVersion=1,
userId="u1",
executionStatus=prisma.enums.AgentExecutionStatus.COMPLETED,
createdAt=now,
updatedAt=now,
isDeleted=False,
isShared=False,
)
agent = _make_library_agent(executions=[exec1])
result = library_model.LibraryAgent.from_db(agent, execution_count_override=1)
assert result.execution_count == 1
assert result.success_rate is not None
assert result.success_rate == 100.0
@pytest.mark.asyncio
async def test_agent_preset_from_db(test_user_id: str):
# Create mock DB agent

View File

@@ -0,0 +1,61 @@
from unittest.mock import AsyncMock
import fastapi
import fastapi.testclient
import pytest
from backend.api.features.v1 import v1_router
app = fastapi.FastAPI()
app.include_router(v1_router)
client = fastapi.testclient.TestClient(app)
@pytest.fixture(autouse=True)
def setup_app_auth(mock_jwt_user):
from autogpt_libs.auth.jwt_utils import get_jwt_payload
app.dependency_overrides[get_jwt_payload] = mock_jwt_user["get_jwt_payload"]
yield
app.dependency_overrides.clear()
def test_onboarding_profile_success(mocker):
mock_extract = mocker.patch(
"backend.api.features.v1.extract_business_understanding",
new_callable=AsyncMock,
)
mock_upsert = mocker.patch(
"backend.api.features.v1.upsert_business_understanding",
new_callable=AsyncMock,
)
from backend.data.understanding import BusinessUnderstandingInput
mock_extract.return_value = BusinessUnderstandingInput.model_construct(
user_name="John",
user_role="Founder/CEO",
pain_points=["Finding leads"],
suggested_prompts={"Learn": ["How do I automate lead gen?"]},
)
mock_upsert.return_value = AsyncMock()
response = client.post(
"/onboarding/profile",
json={
"user_name": "John",
"user_role": "Founder/CEO",
"pain_points": ["Finding leads", "Email & outreach"],
},
)
assert response.status_code == 200
mock_extract.assert_awaited_once()
mock_upsert.assert_awaited_once()
def test_onboarding_profile_missing_fields():
response = client.post(
"/onboarding/profile",
json={"user_name": "John"},
)
assert response.status_code == 422

View File

@@ -0,0 +1 @@
"""Platform bot linking — user-facing REST routes."""

View File

@@ -0,0 +1,158 @@
"""User-facing platform_linking REST routes (JWT auth)."""
import logging
from typing import Annotated
from autogpt_libs import auth
from fastapi import APIRouter, HTTPException, Path, Security
from backend.data.db_accessors import platform_linking_db
from backend.platform_linking.models import (
ConfirmLinkResponse,
ConfirmUserLinkResponse,
DeleteLinkResponse,
LinkTokenInfoResponse,
PlatformLinkInfo,
PlatformUserLinkInfo,
)
from backend.util.exceptions import (
LinkAlreadyExistsError,
LinkFlowMismatchError,
LinkTokenExpiredError,
NotAuthorizedError,
NotFoundError,
)
logger = logging.getLogger(__name__)
router = APIRouter()
TokenPath = Annotated[
str,
Path(max_length=64, pattern=r"^[A-Za-z0-9_-]+$"),
]
def _translate(exc: Exception) -> HTTPException:
if isinstance(exc, NotFoundError):
return HTTPException(status_code=404, detail=str(exc))
if isinstance(exc, NotAuthorizedError):
return HTTPException(status_code=403, detail=str(exc))
if isinstance(exc, LinkAlreadyExistsError):
return HTTPException(status_code=409, detail=str(exc))
if isinstance(exc, LinkTokenExpiredError):
return HTTPException(status_code=410, detail=str(exc))
if isinstance(exc, LinkFlowMismatchError):
return HTTPException(status_code=400, detail=str(exc))
return HTTPException(status_code=500, detail="Internal error.")
@router.get(
"/tokens/{token}/info",
response_model=LinkTokenInfoResponse,
dependencies=[Security(auth.requires_user)],
summary="Get display info for a link token",
)
async def get_link_token_info_route(token: TokenPath) -> LinkTokenInfoResponse:
try:
return await platform_linking_db().get_link_token_info(token)
except (NotFoundError, LinkTokenExpiredError) as exc:
raise _translate(exc) from exc
@router.post(
"/tokens/{token}/confirm",
response_model=ConfirmLinkResponse,
dependencies=[Security(auth.requires_user)],
summary="Confirm a SERVER link token (user must be authenticated)",
)
async def confirm_link_token(
token: TokenPath,
user_id: Annotated[str, Security(auth.get_user_id)],
) -> ConfirmLinkResponse:
try:
return await platform_linking_db().confirm_server_link(token, user_id)
except (
NotFoundError,
LinkFlowMismatchError,
LinkTokenExpiredError,
LinkAlreadyExistsError,
) as exc:
raise _translate(exc) from exc
@router.post(
"/user-tokens/{token}/confirm",
response_model=ConfirmUserLinkResponse,
dependencies=[Security(auth.requires_user)],
summary="Confirm a USER link token (user must be authenticated)",
)
async def confirm_user_link_token(
token: TokenPath,
user_id: Annotated[str, Security(auth.get_user_id)],
) -> ConfirmUserLinkResponse:
try:
return await platform_linking_db().confirm_user_link(token, user_id)
except (
NotFoundError,
LinkFlowMismatchError,
LinkTokenExpiredError,
LinkAlreadyExistsError,
) as exc:
raise _translate(exc) from exc
@router.get(
"/links",
response_model=list[PlatformLinkInfo],
dependencies=[Security(auth.requires_user)],
summary="List all platform servers linked to the authenticated user",
)
async def list_my_links(
user_id: Annotated[str, Security(auth.get_user_id)],
) -> list[PlatformLinkInfo]:
return await platform_linking_db().list_server_links(user_id)
@router.get(
"/user-links",
response_model=list[PlatformUserLinkInfo],
dependencies=[Security(auth.requires_user)],
summary="List all DM links for the authenticated user",
)
async def list_my_user_links(
user_id: Annotated[str, Security(auth.get_user_id)],
) -> list[PlatformUserLinkInfo]:
return await platform_linking_db().list_user_links(user_id)
@router.delete(
"/links/{link_id}",
response_model=DeleteLinkResponse,
dependencies=[Security(auth.requires_user)],
summary="Unlink a platform server",
)
async def delete_link(
link_id: str,
user_id: Annotated[str, Security(auth.get_user_id)],
) -> DeleteLinkResponse:
try:
return await platform_linking_db().delete_server_link(link_id, user_id)
except (NotFoundError, NotAuthorizedError) as exc:
raise _translate(exc) from exc
@router.delete(
"/user-links/{link_id}",
response_model=DeleteLinkResponse,
dependencies=[Security(auth.requires_user)],
summary="Unlink a DM / user link",
)
async def delete_user_link_route(
link_id: str,
user_id: Annotated[str, Security(auth.get_user_id)],
) -> DeleteLinkResponse:
try:
return await platform_linking_db().delete_user_link(link_id, user_id)
except (NotFoundError, NotAuthorizedError) as exc:
raise _translate(exc) from exc

View File

@@ -0,0 +1,264 @@
"""Route tests: domain exceptions → HTTPException status codes."""
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from fastapi import HTTPException
from backend.util.exceptions import (
LinkAlreadyExistsError,
LinkFlowMismatchError,
LinkTokenExpiredError,
NotAuthorizedError,
NotFoundError,
)
def _db_mock(**method_configs):
"""Return a mock of the accessor's return value with the given AsyncMocks."""
db = MagicMock()
for name, mock in method_configs.items():
setattr(db, name, mock)
return db
class TestTokenInfoRouteTranslation:
@pytest.mark.asyncio
async def test_not_found_maps_to_404(self):
from backend.api.features.platform_linking.routes import (
get_link_token_info_route,
)
db = _db_mock(
get_link_token_info=AsyncMock(side_effect=NotFoundError("missing"))
)
with patch(
"backend.api.features.platform_linking.routes.platform_linking_db",
return_value=db,
):
with pytest.raises(HTTPException) as exc:
await get_link_token_info_route(token="abc")
assert exc.value.status_code == 404
@pytest.mark.asyncio
async def test_expired_maps_to_410(self):
from backend.api.features.platform_linking.routes import (
get_link_token_info_route,
)
db = _db_mock(
get_link_token_info=AsyncMock(side_effect=LinkTokenExpiredError("expired"))
)
with patch(
"backend.api.features.platform_linking.routes.platform_linking_db",
return_value=db,
):
with pytest.raises(HTTPException) as exc:
await get_link_token_info_route(token="abc")
assert exc.value.status_code == 410
class TestConfirmLinkRouteTranslation:
@pytest.mark.asyncio
@pytest.mark.parametrize(
"exc,expected_status",
[
(NotFoundError("missing"), 404),
(LinkFlowMismatchError("wrong flow"), 400),
(LinkTokenExpiredError("expired"), 410),
(LinkAlreadyExistsError("already"), 409),
],
)
async def test_translation(self, exc: Exception, expected_status: int):
from backend.api.features.platform_linking.routes import confirm_link_token
db = _db_mock(confirm_server_link=AsyncMock(side_effect=exc))
with patch(
"backend.api.features.platform_linking.routes.platform_linking_db",
return_value=db,
):
with pytest.raises(HTTPException) as ctx:
await confirm_link_token(token="abc", user_id="u1")
assert ctx.value.status_code == expected_status
class TestConfirmUserLinkRouteTranslation:
@pytest.mark.asyncio
@pytest.mark.parametrize(
"exc,expected_status",
[
(NotFoundError("missing"), 404),
(LinkFlowMismatchError("wrong flow"), 400),
(LinkTokenExpiredError("expired"), 410),
(LinkAlreadyExistsError("already"), 409),
],
)
async def test_translation(self, exc: Exception, expected_status: int):
from backend.api.features.platform_linking.routes import confirm_user_link_token
db = _db_mock(confirm_user_link=AsyncMock(side_effect=exc))
with patch(
"backend.api.features.platform_linking.routes.platform_linking_db",
return_value=db,
):
with pytest.raises(HTTPException) as ctx:
await confirm_user_link_token(token="abc", user_id="u1")
assert ctx.value.status_code == expected_status
class TestDeleteLinkRouteTranslation:
@pytest.mark.asyncio
async def test_not_found_maps_to_404(self):
from backend.api.features.platform_linking.routes import delete_link
db = _db_mock(
delete_server_link=AsyncMock(side_effect=NotFoundError("missing"))
)
with patch(
"backend.api.features.platform_linking.routes.platform_linking_db",
return_value=db,
):
with pytest.raises(HTTPException) as exc:
await delete_link(link_id="x", user_id="u1")
assert exc.value.status_code == 404
@pytest.mark.asyncio
async def test_not_owned_maps_to_403(self):
from backend.api.features.platform_linking.routes import delete_link
db = _db_mock(
delete_server_link=AsyncMock(side_effect=NotAuthorizedError("nope"))
)
with patch(
"backend.api.features.platform_linking.routes.platform_linking_db",
return_value=db,
):
with pytest.raises(HTTPException) as exc:
await delete_link(link_id="x", user_id="u1")
assert exc.value.status_code == 403
class TestDeleteUserLinkRouteTranslation:
@pytest.mark.asyncio
async def test_not_found_maps_to_404(self):
from backend.api.features.platform_linking.routes import delete_user_link_route
db = _db_mock(delete_user_link=AsyncMock(side_effect=NotFoundError("missing")))
with patch(
"backend.api.features.platform_linking.routes.platform_linking_db",
return_value=db,
):
with pytest.raises(HTTPException) as exc:
await delete_user_link_route(link_id="x", user_id="u1")
assert exc.value.status_code == 404
@pytest.mark.asyncio
async def test_not_owned_maps_to_403(self):
from backend.api.features.platform_linking.routes import delete_user_link_route
db = _db_mock(
delete_user_link=AsyncMock(side_effect=NotAuthorizedError("nope"))
)
with patch(
"backend.api.features.platform_linking.routes.platform_linking_db",
return_value=db,
):
with pytest.raises(HTTPException) as exc:
await delete_user_link_route(link_id="x", user_id="u1")
assert exc.value.status_code == 403
# ── Adversarial: malformed token path params ──────────────────────────
class TestAdversarialTokenPath:
# TokenPath enforces `^[A-Za-z0-9_-]+$` + max_length=64.
@pytest.fixture
def client(self):
import fastapi
from autogpt_libs.auth import get_user_id, requires_user
from fastapi.testclient import TestClient
import backend.api.features.platform_linking.routes as routes_mod
app = fastapi.FastAPI()
app.dependency_overrides[requires_user] = lambda: None
app.dependency_overrides[get_user_id] = lambda: "caller-user"
app.include_router(routes_mod.router, prefix="/api/platform-linking")
return TestClient(app)
def test_rejects_token_with_special_chars(self, client):
response = client.get("/api/platform-linking/tokens/bad%24token/info")
assert response.status_code == 422
def test_rejects_token_with_path_traversal(self, client):
for probe in ("..%2F..", "foo..bar", "foo%2Fbar"):
response = client.get(f"/api/platform-linking/tokens/{probe}/info")
assert response.status_code in (
404,
422,
), f"path-traversal probe {probe!r} returned {response.status_code}"
def test_rejects_token_too_long(self, client):
long_token = "a" * 65
response = client.get(f"/api/platform-linking/tokens/{long_token}/info")
assert response.status_code == 422
def test_accepts_token_at_max_length(self, client):
token = "a" * 64
db = _db_mock(
get_link_token_info=AsyncMock(side_effect=NotFoundError("missing"))
)
with patch(
"backend.api.features.platform_linking.routes.platform_linking_db",
return_value=db,
):
response = client.get(f"/api/platform-linking/tokens/{token}/info")
assert response.status_code == 404
def test_accepts_urlsafe_b64_token_shape(self, client):
db = _db_mock(
get_link_token_info=AsyncMock(side_effect=NotFoundError("missing"))
)
with patch(
"backend.api.features.platform_linking.routes.platform_linking_db",
return_value=db,
):
response = client.get("/api/platform-linking/tokens/abc-_XYZ123-_abc/info")
assert response.status_code == 404
def test_confirm_rejects_malformed_token(self, client):
response = client.post("/api/platform-linking/tokens/bad%24token/confirm")
assert response.status_code == 422
class TestAdversarialDeleteLinkId:
"""DELETE link_id has no regex — ensure weird values are handled via
NotFoundError (no crash, no cross-user leak)."""
@pytest.fixture
def client(self):
import fastapi
from autogpt_libs.auth import get_user_id, requires_user
from fastapi.testclient import TestClient
import backend.api.features.platform_linking.routes as routes_mod
app = fastapi.FastAPI()
app.dependency_overrides[requires_user] = lambda: None
app.dependency_overrides[get_user_id] = lambda: "caller-user"
app.include_router(routes_mod.router, prefix="/api/platform-linking")
return TestClient(app)
def test_weird_link_id_returns_404(self, client):
db = _db_mock(
delete_server_link=AsyncMock(side_effect=NotFoundError("missing"))
)
with patch(
"backend.api.features.platform_linking.routes.platform_linking_db",
return_value=db,
):
for link_id in ("'; DROP TABLE links;--", "../../etc/passwd", ""):
response = client.delete(f"/api/platform-linking/links/{link_id}")
assert response.status_code in (404, 405)

View File

@@ -0,0 +1,20 @@
import pydantic
class PushSubscriptionKeys(pydantic.BaseModel):
p256dh: str = pydantic.Field(min_length=1, max_length=512)
auth: str = pydantic.Field(min_length=1, max_length=512)
class PushSubscribeRequest(pydantic.BaseModel):
endpoint: str = pydantic.Field(min_length=1, max_length=2048)
keys: PushSubscriptionKeys
user_agent: str | None = pydantic.Field(default=None, max_length=512)
class PushUnsubscribeRequest(pydantic.BaseModel):
endpoint: str = pydantic.Field(min_length=1, max_length=2048)
class VapidPublicKeyResponse(pydantic.BaseModel):
public_key: str

View File

@@ -0,0 +1,64 @@
from typing import Annotated
from autogpt_libs.auth import get_user_id, requires_user
from fastapi import APIRouter, HTTPException, Security
from starlette.status import HTTP_204_NO_CONTENT, HTTP_400_BAD_REQUEST
from backend.api.features.push.model import (
PushSubscribeRequest,
PushUnsubscribeRequest,
VapidPublicKeyResponse,
)
from backend.data.push_subscription import (
delete_push_subscription,
upsert_push_subscription,
validate_push_endpoint,
)
from backend.util.settings import Settings
router = APIRouter()
_settings = Settings()
@router.get(
"/vapid-key",
summary="Get VAPID public key for push subscription",
)
async def get_vapid_public_key() -> VapidPublicKeyResponse:
return VapidPublicKeyResponse(public_key=_settings.secrets.vapid_public_key)
@router.post(
"/subscribe",
summary="Register a push subscription for the current user",
status_code=HTTP_204_NO_CONTENT,
dependencies=[Security(requires_user)],
)
async def subscribe_push(
user_id: Annotated[str, Security(get_user_id)],
body: PushSubscribeRequest,
) -> None:
try:
await validate_push_endpoint(body.endpoint)
await upsert_push_subscription(
user_id=user_id,
endpoint=body.endpoint,
p256dh=body.keys.p256dh,
auth=body.keys.auth,
user_agent=body.user_agent,
)
except ValueError as e:
raise HTTPException(status_code=HTTP_400_BAD_REQUEST, detail=str(e))
@router.post(
"/unsubscribe",
summary="Remove a push subscription",
status_code=HTTP_204_NO_CONTENT,
dependencies=[Security(requires_user)],
)
async def unsubscribe_push(
user_id: Annotated[str, Security(get_user_id)],
body: PushUnsubscribeRequest,
) -> None:
await delete_push_subscription(user_id, body.endpoint)

View File

@@ -0,0 +1,240 @@
"""Tests for push notification routes."""
from unittest.mock import AsyncMock, MagicMock
import fastapi
import fastapi.testclient
import pytest
from backend.api.features.push.routes import router
app = fastapi.FastAPI()
app.include_router(router)
client = fastapi.testclient.TestClient(app)
@pytest.fixture(autouse=True)
def setup_app_auth(mock_jwt_user):
from autogpt_libs.auth.jwt_utils import get_jwt_payload
app.dependency_overrides[get_jwt_payload] = mock_jwt_user["get_jwt_payload"]
yield
app.dependency_overrides.clear()
def test_get_vapid_public_key(mocker):
mock_settings = MagicMock()
mock_settings.secrets.vapid_public_key = "test-vapid-public-key-base64url"
mocker.patch(
"backend.api.features.push.routes._settings",
mock_settings,
)
response = client.get("/vapid-key")
assert response.status_code == 200
data = response.json()
assert data["public_key"] == "test-vapid-public-key-base64url"
def test_get_vapid_public_key_empty(mocker):
mock_settings = MagicMock()
mock_settings.secrets.vapid_public_key = ""
mocker.patch(
"backend.api.features.push.routes._settings",
mock_settings,
)
response = client.get("/vapid-key")
assert response.status_code == 200
data = response.json()
assert data["public_key"] == ""
def test_subscribe_push(mocker, test_user_id):
mock_upsert = mocker.patch(
"backend.api.features.push.routes.upsert_push_subscription",
new_callable=AsyncMock,
)
response = client.post(
"/subscribe",
json={
"endpoint": "https://fcm.googleapis.com/fcm/send/abc123",
"keys": {
"p256dh": "test-p256dh-key",
"auth": "test-auth-key",
},
"user_agent": "Mozilla/5.0 Test",
},
)
assert response.status_code == 204
mock_upsert.assert_awaited_once_with(
user_id=test_user_id,
endpoint="https://fcm.googleapis.com/fcm/send/abc123",
p256dh="test-p256dh-key",
auth="test-auth-key",
user_agent="Mozilla/5.0 Test",
)
def test_subscribe_push_without_user_agent(mocker, test_user_id):
mock_upsert = mocker.patch(
"backend.api.features.push.routes.upsert_push_subscription",
new_callable=AsyncMock,
)
response = client.post(
"/subscribe",
json={
"endpoint": "https://fcm.googleapis.com/fcm/send/abc123",
"keys": {
"p256dh": "test-p256dh-key",
"auth": "test-auth-key",
},
},
)
assert response.status_code == 204
mock_upsert.assert_awaited_once_with(
user_id=test_user_id,
endpoint="https://fcm.googleapis.com/fcm/send/abc123",
p256dh="test-p256dh-key",
auth="test-auth-key",
user_agent=None,
)
def test_subscribe_push_missing_keys():
response = client.post(
"/subscribe",
json={
"endpoint": "https://fcm.googleapis.com/fcm/send/abc123",
},
)
assert response.status_code == 422
def test_subscribe_push_missing_endpoint():
response = client.post(
"/subscribe",
json={
"keys": {
"p256dh": "test-p256dh-key",
"auth": "test-auth-key",
},
},
)
assert response.status_code == 422
def test_subscribe_push_rejects_empty_crypto_keys():
response = client.post(
"/subscribe",
json={
"endpoint": "https://fcm.googleapis.com/fcm/send/abc123",
"keys": {"p256dh": "", "auth": ""},
},
)
assert response.status_code == 422
def test_subscribe_push_rejects_oversized_endpoint():
response = client.post(
"/subscribe",
json={
"endpoint": "https://fcm.googleapis.com/fcm/send/" + "x" * 3000,
"keys": {"p256dh": "k", "auth": "a"},
},
)
assert response.status_code == 422
def test_unsubscribe_push(mocker, test_user_id):
mock_delete = mocker.patch(
"backend.api.features.push.routes.delete_push_subscription",
new_callable=AsyncMock,
)
response = client.post(
"/unsubscribe",
json={
"endpoint": "https://fcm.googleapis.com/fcm/send/abc123",
},
)
assert response.status_code == 204
mock_delete.assert_awaited_once_with(
test_user_id,
"https://fcm.googleapis.com/fcm/send/abc123",
)
def test_unsubscribe_push_missing_endpoint():
response = client.post(
"/unsubscribe",
json={},
)
assert response.status_code == 422
@pytest.mark.parametrize(
"untrusted_endpoint",
[
"https://localhost/evil",
"https://127.0.0.1/evil",
"https://169.254.169.254/latest/meta-data/",
"https://internal-service.local/api",
"https://attacker.example.com/push",
"http://fcm.googleapis.com/fcm/send/abc",
"file:///etc/passwd",
],
)
def test_subscribe_push_rejects_untrusted_endpoints(mocker, untrusted_endpoint):
mock_upsert = mocker.patch(
"backend.api.features.push.routes.upsert_push_subscription",
new_callable=AsyncMock,
)
response = client.post(
"/subscribe",
json={
"endpoint": untrusted_endpoint,
"keys": {
"p256dh": "test-p256dh-key",
"auth": "test-auth-key",
},
},
)
assert response.status_code == 400
mock_upsert.assert_not_awaited()
def test_subscribe_push_surfaces_cap_as_400(mocker):
mocker.patch(
"backend.api.features.push.routes.upsert_push_subscription",
new_callable=AsyncMock,
side_effect=ValueError("Subscription limit of 20 per user reached"),
)
response = client.post(
"/subscribe",
json={
"endpoint": "https://fcm.googleapis.com/fcm/send/abc123",
"keys": {
"p256dh": "test-p256dh-key",
"auth": "test-auth-key",
},
},
)
assert response.status_code == 400
assert "Subscription limit" in response.json()["detail"]

View File

@@ -490,6 +490,9 @@ async def get_store_creators(
# Build where clause with sanitized inputs
where = {}
# Only return creators with approved agents
where["num_agents"] = {"gt": 0}
if featured:
where["is_featured"] = featured

View File

@@ -1,4 +1,5 @@
from datetime import datetime
from unittest.mock import AsyncMock
import prisma.enums
import prisma.errors
@@ -50,8 +51,8 @@ async def test_get_store_agents(mocker):
# Mock prisma calls
mock_store_agent = mocker.patch("prisma.models.StoreAgent.prisma")
mock_store_agent.return_value.find_many = mocker.AsyncMock(return_value=mock_agents)
mock_store_agent.return_value.count = mocker.AsyncMock(return_value=1)
mock_store_agent.return_value.find_many = AsyncMock(return_value=mock_agents)
mock_store_agent.return_value.count = AsyncMock(return_value=1)
# Call function
result = await db.get_store_agents()
@@ -94,7 +95,7 @@ async def test_get_store_agent_details(mocker):
# Mock StoreAgent prisma call
mock_store_agent = mocker.patch("prisma.models.StoreAgent.prisma")
mock_store_agent.return_value.find_first = mocker.AsyncMock(return_value=mock_agent)
mock_store_agent.return_value.find_first = AsyncMock(return_value=mock_agent)
# Call function
result = await db.get_store_agent_details("creator", "test-agent")
@@ -133,7 +134,7 @@ async def test_get_store_creator(mocker):
# Mock prisma call
mock_creator = mocker.patch("prisma.models.Creator.prisma")
mock_creator.return_value.find_unique = mocker.AsyncMock()
mock_creator.return_value.find_unique = AsyncMock()
# Configure the mock to return values that will pass validation
mock_creator.return_value.find_unique.return_value = mock_creator_data
@@ -189,6 +190,7 @@ async def test_create_store_submission(mocker):
notifyOnAgentApproved=True,
notifyOnAgentRejected=True,
timezone="Europe/Delft",
subscriptionTier=prisma.enums.SubscriptionTier.BASIC, # type: ignore[reportCallIssue,reportAttributeAccessIssue]
)
mock_agent = prisma.models.AgentGraph(
id="agent-id",
@@ -235,23 +237,23 @@ async def test_create_store_submission(mocker):
# Mock prisma calls
mock_agent_graph = mocker.patch("prisma.models.AgentGraph.prisma")
mock_agent_graph.return_value.find_first = mocker.AsyncMock(return_value=mock_agent)
mock_agent_graph.return_value.find_first = AsyncMock(return_value=mock_agent)
# Mock transaction context manager
mock_tx = mocker.MagicMock()
mocker.patch(
"backend.api.features.store.db.transaction",
return_value=mocker.AsyncMock(
__aenter__=mocker.AsyncMock(return_value=mock_tx),
__aexit__=mocker.AsyncMock(return_value=False),
return_value=AsyncMock(
__aenter__=AsyncMock(return_value=mock_tx),
__aexit__=AsyncMock(return_value=False),
),
)
mock_sl = mocker.patch("prisma.models.StoreListing.prisma")
mock_sl.return_value.find_unique = mocker.AsyncMock(return_value=None)
mock_sl.return_value.find_unique = AsyncMock(return_value=None)
mock_slv = mocker.patch("prisma.models.StoreListingVersion.prisma")
mock_slv.return_value.create = mocker.AsyncMock(return_value=mock_version)
mock_slv.return_value.create = AsyncMock(return_value=mock_version)
# Call function
result = await db.create_store_submission(
@@ -291,10 +293,8 @@ async def test_update_profile(mocker):
# Mock prisma calls
mock_profile_db = mocker.patch("prisma.models.Profile.prisma")
mock_profile_db.return_value.find_first = mocker.AsyncMock(
return_value=mock_profile
)
mock_profile_db.return_value.update = mocker.AsyncMock(return_value=mock_profile)
mock_profile_db.return_value.find_first = AsyncMock(return_value=mock_profile)
mock_profile_db.return_value.update = AsyncMock(return_value=mock_profile)
# Test data
profile = Profile(
@@ -335,9 +335,7 @@ async def test_get_user_profile(mocker):
# Mock prisma calls
mock_profile_db = mocker.patch("prisma.models.Profile.prisma")
mock_profile_db.return_value.find_first = mocker.AsyncMock(
return_value=mock_profile
)
mock_profile_db.return_value.find_first = AsyncMock(return_value=mock_profile)
# Call function
result = await db.get_user_profile("user-id")
@@ -395,3 +393,38 @@ async def test_get_store_agents_search_category_array_injection():
# Verify the query executed without error
# Category should be parameterized, preventing SQL injection
assert isinstance(result.agents, list)
@pytest.mark.asyncio(loop_scope="session")
async def test_get_store_creators_only_returns_approved(mocker):
mock_creators = [
prisma.models.Creator(
name="Creator One",
username="creator1",
description="desc",
links=["link1"],
avatar_url="avatar.jpg",
num_agents=1,
agent_rating=4.5,
agent_runs=10,
top_categories=["test"],
is_featured=False,
)
]
mock_creator = mocker.patch("prisma.models.Creator.prisma")
mock_creator.return_value.find_many = AsyncMock(return_value=mock_creators)
mock_creator.return_value.count = AsyncMock(return_value=1)
result = await db.get_store_creators()
assert len(result.creators) == 1
assert result.creators[0].username == "creator1"
mock_creator.return_value.find_many.assert_called_once()
mock_creator.return_value.count.assert_called_once()
_, find_kwargs = mock_creator.return_value.find_many.call_args
_, count_kwargs = mock_creator.return_value.count.call_args
assert find_kwargs["where"]["num_agents"] == {"gt": 0}
assert count_kwargs["where"]["num_agents"] == {"gt": 0}

File diff suppressed because it is too large Load Diff

View File

@@ -5,7 +5,8 @@ import time
import uuid
from collections import defaultdict
from datetime import datetime, timezone
from typing import Annotated, Any, Sequence, get_args
from typing import Annotated, Any, Literal, Sequence, cast, get_args
from urllib.parse import urlparse
import pydantic
import stripe
@@ -24,10 +25,12 @@ from fastapi import (
UploadFile,
)
from fastapi.concurrency import run_in_threadpool
from pydantic import BaseModel
from prisma.enums import SubscriptionTier
from pydantic import BaseModel, Field
from starlette.status import HTTP_204_NO_CONTENT, HTTP_404_NOT_FOUND
from typing_extensions import Optional, TypedDict
from backend.api.features.workspace.routes import create_file_download_response
from backend.api.model import (
CreateAPIKeyRequest,
CreateAPIKeyResponse,
@@ -41,18 +44,33 @@ from backend.api.model import (
UploadFileResponse,
)
from backend.blocks import get_block, get_blocks
from backend.copilot.rate_limit import get_tier_multipliers
from backend.data import execution as execution_db
from backend.data import graph as graph_db
from backend.data.auth import api_key as api_key_db
from backend.data.block import BlockInput, CompletedBlockOutput
from backend.data.credit import (
AutoTopUpConfig,
PendingChangeUnknown,
RefundRequest,
TransactionHistory,
UserCredit,
cancel_stripe_subscription,
create_subscription_checkout,
get_active_subscription_period_end,
get_auto_top_up,
get_pending_subscription_change,
get_proration_credit_cents,
get_subscription_price_id,
get_user_credit_model,
handle_subscription_payment_failure,
handle_subscription_payment_success,
modify_stripe_subscription_for_tier,
release_pending_subscription_schedule,
set_auto_top_up,
set_subscription_tier,
sync_subscription_from_stripe,
sync_subscription_schedule_from_stripe,
)
from backend.data.graph import GraphSettings
from backend.data.model import CredentialsMetaInput, UserOnboarding
@@ -63,12 +81,17 @@ from backend.data.onboarding import (
UserOnboardingUpdate,
complete_onboarding_step,
complete_re_run_agent,
format_onboarding_for_extraction,
get_recommended_agents,
get_user_onboarding,
onboarding_enabled,
reset_user_onboarding,
update_user_onboarding,
)
from backend.data.tally import extract_business_understanding
from backend.data.understanding import (
BusinessUnderstandingInput,
upsert_business_understanding,
)
from backend.data.user import (
get_or_create_user,
get_user_by_id,
@@ -77,6 +100,7 @@ from backend.data.user import (
update_user_notification_preference,
update_user_timezone,
)
from backend.data.workspace import get_workspace_file_by_id
from backend.executor import scheduler
from backend.executor import utils as execution_utils
from backend.integrations.webhooks.graph_lifecycle_hooks import (
@@ -282,35 +306,33 @@ async def get_onboarding_agents(
return await get_recommended_agents(user_id)
class OnboardingStatusResponse(pydantic.BaseModel):
"""Response for onboarding status check."""
class OnboardingProfileRequest(pydantic.BaseModel):
"""Request body for onboarding profile submission."""
is_onboarding_enabled: bool
is_chat_enabled: bool
user_name: str = pydantic.Field(min_length=1, max_length=100)
user_role: str = pydantic.Field(min_length=1, max_length=100)
pain_points: list[str] = pydantic.Field(default_factory=list, max_length=20)
class OnboardingStatusResponse(pydantic.BaseModel):
"""Response for onboarding completion check."""
is_completed: bool
@v1_router.get(
"/onboarding/enabled",
summary="Is onboarding enabled",
"/onboarding/completed",
summary="Check if onboarding is completed",
tags=["onboarding", "public"],
response_model=OnboardingStatusResponse,
dependencies=[Security(requires_user)],
)
async def is_onboarding_enabled(
async def is_onboarding_completed(
user_id: Annotated[str, Security(get_user_id)],
) -> OnboardingStatusResponse:
# Check if chat is enabled for user
is_chat_enabled = await is_feature_enabled(Flag.CHAT, user_id, False)
# If chat is enabled, skip legacy onboarding
if is_chat_enabled:
return OnboardingStatusResponse(
is_onboarding_enabled=False,
is_chat_enabled=True,
)
user_onboarding = await get_user_onboarding(user_id)
return OnboardingStatusResponse(
is_onboarding_enabled=await onboarding_enabled(),
is_chat_enabled=False,
is_completed=OnboardingStep.VISIT_COPILOT in user_onboarding.completedSteps,
)
@@ -325,6 +347,38 @@ async def reset_onboarding(user_id: Annotated[str, Security(get_user_id)]):
return await reset_user_onboarding(user_id)
@v1_router.post(
"/onboarding/profile",
summary="Submit onboarding profile",
tags=["onboarding"],
dependencies=[Security(requires_user)],
)
async def submit_onboarding_profile(
data: OnboardingProfileRequest,
user_id: Annotated[str, Security(get_user_id)],
):
formatted = format_onboarding_for_extraction(
user_name=data.user_name,
user_role=data.user_role,
pain_points=data.pain_points,
)
try:
understanding_input = await extract_business_understanding(formatted)
except Exception:
understanding_input = BusinessUnderstandingInput.model_construct()
# Ensure the direct fields are set even if LLM missed them
understanding_input.user_name = data.user_name
understanding_input.user_role = data.user_role
if not understanding_input.pain_points:
understanding_input.pain_points = data.pain_points
await upsert_business_understanding(user_id, understanding_input)
return {"status": "ok"}
########################################################
##################### Blocks ###########################
########################################################
@@ -626,9 +680,12 @@ async def configure_user_auto_top_up(
raise HTTPException(status_code=422, detail=str(e))
raise
await set_auto_top_up(
user_id, AutoTopUpConfig(threshold=request.threshold, amount=request.amount)
)
try:
await set_auto_top_up(
user_id, AutoTopUpConfig(threshold=request.threshold, amount=request.amount)
)
except ValueError as e:
raise HTTPException(status_code=422, detail=str(e))
return "Auto top-up settings updated"
@@ -644,41 +701,500 @@ async def get_user_auto_top_up(
return await get_auto_top_up(user_id)
class SubscriptionTierRequest(BaseModel):
tier: Literal["NO_TIER", "BASIC", "PRO", "MAX", "BUSINESS"]
success_url: str = ""
cancel_url: str = ""
class SubscriptionStatusResponse(BaseModel):
tier: Literal["NO_TIER", "BASIC", "PRO", "MAX", "BUSINESS", "ENTERPRISE"]
monthly_cost: int # amount in cents (Stripe convention)
tier_costs: dict[str, int] # tier name -> amount in cents
tier_multipliers: dict[str, float] = Field(
default_factory=dict,
description=(
"Tier → rate-limit multiplier. Covers the same tiers listed in"
" ``tier_costs`` so the frontend can render rate-limit badges"
" relative to the lowest visible tier without knowing backend"
" defaults."
),
)
proration_credit_cents: int # unused portion of current sub to convert on upgrade
has_active_stripe_subscription: bool = Field(
default=False,
description=(
"True when the user has an active/trialing Stripe subscription. The"
" frontend uses this to branch upgrade UX: modify-in-place + saved-card"
" auto-charge when True, redirect to Stripe Checkout when False."
),
)
current_period_end: Optional[int] = Field(
default=None,
description=(
"Unix timestamp of the active subscription's current_period_end. Used"
" to show the date Stripe will issue the next invoice (with prorated"
" upgrade charges, if any). None when no active sub."
),
)
pending_tier: Optional[Literal["NO_TIER", "BASIC", "PRO", "MAX", "BUSINESS"]] = None
pending_tier_effective_at: Optional[datetime] = None
url: str = Field(
default="",
description=(
"Populated only when POST /credits/subscription starts a Stripe Checkout"
" Session (BASIC → paid upgrade). Empty string in all other branches —"
" the client redirects to this URL when non-empty."
),
)
def _validate_checkout_redirect_url(url: str) -> bool:
"""Return True if `url` matches the configured frontend origin.
Prevents open-redirect: attackers must not be able to supply arbitrary
success_url/cancel_url that Stripe will redirect users to after checkout.
Pre-parse rejection rules (applied before urlparse):
- Backslashes (``\\``) are normalised differently across parsers/browsers.
- Control characters (U+0000U+001F) are not valid in URLs and may confuse
some URL-parsing implementations.
"""
# Reject characters that can confuse URL parsers before any parsing.
if "\\" in url:
return False
if any(ord(c) < 0x20 for c in url):
return False
allowed = settings.config.frontend_base_url or settings.config.platform_base_url
if not allowed:
# No configured origin — refuse to validate rather than allow arbitrary URLs.
return False
try:
parsed = urlparse(url)
allowed_parsed = urlparse(allowed)
except ValueError:
return False
if parsed.scheme not in ("http", "https"):
return False
# Reject ``user:pass@host`` authority tricks — ``@`` in the netloc component
# can trick browsers into connecting to a different host than displayed.
# ``@`` in query/fragment is harmless and must be allowed.
if "@" in parsed.netloc:
return False
return (
parsed.scheme == allowed_parsed.scheme
and parsed.netloc == allowed_parsed.netloc
)
@cached(ttl_seconds=300, maxsize=32, cache_none=False)
async def _get_stripe_price_amount(price_id: str) -> int | None:
"""Return the unit_amount (cents) for a Stripe Price ID, cached for 5 minutes.
Returns ``None`` on transient Stripe errors. ``cache_none=False`` opts out
of caching the ``None`` sentinel so the next request retries Stripe instead
of being served a stale "no price" for the rest of the TTL window. Callers
should treat ``None`` as an unknown price and fall back to 0.
Stripe prices rarely change; caching avoids a ~200-600 ms Stripe round-trip on
every GET /credits/subscription page load and reduces quota consumption.
"""
try:
price = await run_in_threadpool(stripe.Price.retrieve, price_id)
return price.unit_amount or 0
except stripe.StripeError:
logger.warning(
"Failed to retrieve Stripe price %s — returning None (not cached)",
price_id,
)
return None
@v1_router.get(
path="/credits/subscription",
summary="Get subscription tier, current cost, and all tier costs",
operation_id="getSubscriptionStatus",
tags=["credits"],
dependencies=[Security(requires_user)],
)
async def get_subscription_status(
user_id: Annotated[str, Security(get_user_id)],
) -> SubscriptionStatusResponse:
user = await get_user_by_id(user_id)
tier = user.subscription_tier or SubscriptionTier.NO_TIER
# Tiers that *can* have a Stripe price configured (and therefore appear
# in the tier picker if the LD flag exposes a price-id). NO_TIER is not
# priceable — it's the implicit "no active subscription" state.
priceable_tiers = [
SubscriptionTier.BASIC,
SubscriptionTier.PRO,
SubscriptionTier.MAX,
SubscriptionTier.BUSINESS,
]
price_ids = await asyncio.gather(
*[get_subscription_price_id(t) for t in priceable_tiers]
)
async def _cost(pid: str | None) -> int:
return (await _get_stripe_price_amount(pid) or 0) if pid else 0
costs = await asyncio.gather(*[_cost(pid) for pid in price_ids])
tier_costs: dict[str, int] = {}
for t, pid, cost in zip(priceable_tiers, price_ids, costs):
if pid:
tier_costs[t.value] = cost
# Expose the effective rate-limit multipliers alongside prices so the
# frontend can render "Nx rate limits" relative to the lowest visible
# tier without hard-coding backend defaults. Only emit entries for tiers
# that land in ``tier_costs`` — rows hidden at the price layer must stay
# hidden in the multiplier layer too.
multipliers = await get_tier_multipliers()
tier_multipliers: dict[str, float] = {
t.value: multipliers.get(t, 1.0)
for t in priceable_tiers
if t.value in tier_costs
}
current_monthly_cost = tier_costs.get(tier.value, 0)
proration_credit, current_period_end = await asyncio.gather(
get_proration_credit_cents(user_id, current_monthly_cost),
get_active_subscription_period_end(user_id),
)
try:
pending = await get_pending_subscription_change(user_id)
except (stripe.StripeError, PendingChangeUnknown):
# Swallow Stripe-side failures (rate limits, transient network) AND
# PendingChangeUnknown (LaunchDarkly price-id lookup failed). Both
# propagate past the cache so the next request retries fresh instead
# of serving a stale None for the TTL window. Let real bugs (KeyError,
# AttributeError, etc.) propagate so they surface in Sentry.
logger.exception(
"get_subscription_status: failed to resolve pending change for user %s",
user_id,
)
pending = None
response = SubscriptionStatusResponse(
tier=tier.value,
monthly_cost=current_monthly_cost,
tier_costs=tier_costs,
tier_multipliers=tier_multipliers,
proration_credit_cents=proration_credit,
has_active_stripe_subscription=current_period_end is not None,
current_period_end=current_period_end,
)
if pending is not None:
pending_tier_enum, pending_effective_at = pending
if pending_tier_enum in (
SubscriptionTier.NO_TIER,
SubscriptionTier.BASIC,
SubscriptionTier.PRO,
SubscriptionTier.MAX,
SubscriptionTier.BUSINESS,
):
response.pending_tier = pending_tier_enum.value
response.pending_tier_effective_at = pending_effective_at
return response
@v1_router.post(
path="/credits/subscription",
summary="Update subscription tier or start a Stripe Checkout session",
operation_id="updateSubscriptionTier",
tags=["credits"],
dependencies=[Security(requires_user)],
)
async def update_subscription_tier(
request: SubscriptionTierRequest,
user_id: Annotated[str, Security(get_user_id)],
) -> SubscriptionStatusResponse:
# Pydantic validates tier is one of BASIC/PRO/MAX/BUSINESS via Literal type.
tier = SubscriptionTier(request.tier)
# ENTERPRISE tier is admin-managed — block self-service changes from ENTERPRISE users.
user = await get_user_by_id(user_id)
if (
user.subscription_tier or SubscriptionTier.NO_TIER
) == SubscriptionTier.ENTERPRISE:
raise HTTPException(
status_code=403,
detail="ENTERPRISE subscription changes must be managed by an administrator",
)
# Same-tier request = "stay on my current tier" = cancel any pending
# scheduled change (paid→paid downgrade or paid→BASIC cancel). This is the
# collapsed behaviour that replaces the old /credits/subscription/cancel-pending
# route. Safe when no pending change exists: release_pending_subscription_schedule
# returns False and we simply return the current status.
if (user.subscription_tier or SubscriptionTier.NO_TIER) == tier:
try:
await release_pending_subscription_schedule(user_id)
except stripe.StripeError as e:
logger.exception(
"Stripe error releasing pending subscription change for user %s: %s",
user_id,
e,
)
raise HTTPException(
status_code=502,
detail=(
"Unable to cancel the pending subscription change right now. "
"Please try again or contact support."
),
)
return await get_subscription_status(user_id)
payment_enabled = await is_feature_enabled(
Flag.ENABLE_PLATFORM_PAYMENT, user_id, default=False
)
target_price_id = await get_subscription_price_id(tier)
# Cancel: target NO_TIER. Schedule Stripe cancellation at period end;
# cancel_at_period_end=True lets the webhook flip the DB tier. No active
# sub (admin-granted or never-paid) or payment disabled → DB flip.
# NO_TIER is never priceable, so this branch always fires for cancel
# requests regardless of LD config.
if tier == SubscriptionTier.NO_TIER:
if payment_enabled:
try:
had_subscription = await cancel_stripe_subscription(user_id)
except stripe.StripeError as e:
logger.exception(
"Stripe error cancelling subscription for user %s: %s",
user_id,
e,
)
raise HTTPException(
status_code=502,
detail=(
"Unable to cancel your subscription right now. "
"Please try again or contact support."
),
)
if not had_subscription:
await set_subscription_tier(user_id, tier)
return await get_subscription_status(user_id)
await set_subscription_tier(user_id, tier)
return await get_subscription_status(user_id)
if not payment_enabled:
raise HTTPException(
status_code=422,
detail=f"Subscription not available for tier {tier.value}",
)
# Target has no LD price — not provisionable (matches the GET hiding).
if target_price_id is None:
raise HTTPException(
status_code=422,
detail=f"Subscription not available for tier {tier.value}",
)
# Modify in place if there's a sub; else fall through to Checkout below.
try:
modified = await modify_stripe_subscription_for_tier(user_id, tier)
if modified:
return await get_subscription_status(user_id)
except ValueError as e:
raise HTTPException(status_code=422, detail=str(e))
except stripe.InvalidRequestError as e:
# Stripe rejects schedule modify when phases mix currencies, e.g. the
# active sub was checked out in GBP but the target tier's Price is
# USD-only. 502 reads as outage; surface a 422 with a specific message
# so the user/admin can see what to fix in Stripe.
msg = str(e)
if "currency" in msg.lower():
logger.warning(
"Currency mismatch on tier change for user %s: %s", user_id, msg
)
raise HTTPException(
status_code=422,
detail=(
"Tier change unavailable for your current billing currency."
" Please contact support — the target tier needs to be"
" configured for your currency in Stripe before this"
" change can go through."
),
)
logger.exception(
"Stripe error modifying subscription for user %s: %s", user_id, e
)
raise HTTPException(
status_code=502,
detail=(
"Unable to update your subscription right now. "
"Please try again or contact support."
),
)
except stripe.StripeError as e:
logger.exception(
"Stripe error modifying subscription for user %s: %s", user_id, e
)
raise HTTPException(
status_code=502,
detail=(
"Unable to update your subscription right now. "
"Please try again or contact support."
),
)
# No active Stripe subscription → create Stripe Checkout Session.
if not request.success_url or not request.cancel_url:
raise HTTPException(
status_code=422,
detail="success_url and cancel_url are required for paid tier upgrades",
)
# Open-redirect protection: both URLs must point to the configured frontend
# origin, otherwise an attacker could use our Stripe integration as a
# redirector to arbitrary phishing sites.
#
# Fail early with a clear 503 if the server is misconfigured (neither
# frontend_base_url nor platform_base_url set), so operators get an
# actionable error instead of the misleading "must match the platform
# frontend origin" 422 that _validate_checkout_redirect_url would otherwise
# produce when `allowed` is empty.
if not (settings.config.frontend_base_url or settings.config.platform_base_url):
logger.error(
"update_subscription_tier: neither frontend_base_url nor "
"platform_base_url is configured; cannot validate checkout redirect URLs"
)
raise HTTPException(
status_code=503,
detail=(
"Payment redirect URLs cannot be validated: "
"frontend_base_url or platform_base_url must be set on the server."
),
)
if not _validate_checkout_redirect_url(
request.success_url
) or not _validate_checkout_redirect_url(request.cancel_url):
raise HTTPException(
status_code=422,
detail="success_url and cancel_url must match the platform frontend origin",
)
try:
url = await create_subscription_checkout(
user_id=user_id,
tier=tier,
success_url=request.success_url,
cancel_url=request.cancel_url,
)
except ValueError as e:
raise HTTPException(status_code=422, detail=str(e))
except stripe.StripeError as e:
logger.exception(
"Stripe error creating checkout session for user %s: %s", user_id, e
)
raise HTTPException(
status_code=502,
detail=(
"Unable to start checkout right now. "
"Please try again or contact support."
),
)
status = await get_subscription_status(user_id)
status.url = url
return status
@v1_router.post(
path="/credits/stripe_webhook", summary="Handle Stripe webhooks", tags=["credits"]
)
async def stripe_webhook(request: Request):
webhook_secret = settings.secrets.stripe_webhook_secret
if not webhook_secret:
# Guard: an empty secret allows HMAC forgery (attacker can compute a valid
# signature over the same empty key). Reject all webhook calls when unconfigured.
logger.error(
"stripe_webhook: STRIPE_WEBHOOK_SECRET is not configured — "
"rejecting request to prevent signature bypass"
)
raise HTTPException(status_code=503, detail="Webhook not configured")
# Get the raw request body
payload = await request.body()
# Get the signature header
sig_header = request.headers.get("stripe-signature")
try:
event = stripe.Webhook.construct_event(
payload, sig_header, settings.secrets.stripe_webhook_secret
)
except ValueError as e:
event = stripe.Webhook.construct_event(payload, sig_header, webhook_secret)
except ValueError:
# Invalid payload
raise HTTPException(
status_code=400, detail=f"Invalid payload: {str(e) or type(e).__name__}"
)
except stripe.SignatureVerificationError as e:
raise HTTPException(status_code=400, detail="Invalid payload")
except stripe.SignatureVerificationError:
# Invalid signature
raise HTTPException(
status_code=400, detail=f"Invalid signature: {str(e) or type(e).__name__}"
raise HTTPException(status_code=400, detail="Invalid signature")
# Defensive payload extraction. A malformed payload (missing/non-dict
# `data.object`, missing `id`) would otherwise raise KeyError/TypeError
# AFTER signature verification — which Stripe interprets as a delivery
# failure and retries forever, while spamming Sentry with no useful info.
# Acknowledge with 200 and a warning so Stripe stops retrying.
event_type = event.get("type", "")
event_data = event.get("data") or {}
data_object = event_data.get("object") if isinstance(event_data, dict) else None
if not isinstance(data_object, dict):
logger.warning(
"stripe_webhook: %s missing or non-dict data.object; ignoring",
event_type,
)
return Response(status_code=200)
if (
event["type"] == "checkout.session.completed"
or event["type"] == "checkout.session.async_payment_succeeded"
if event_type in (
"checkout.session.completed",
"checkout.session.async_payment_succeeded",
):
await UserCredit().fulfill_checkout(session_id=event["data"]["object"]["id"])
session_id = data_object.get("id")
if not session_id:
logger.warning(
"stripe_webhook: %s missing data.object.id; ignoring", event_type
)
return Response(status_code=200)
await UserCredit().fulfill_checkout(session_id=session_id)
if event["type"] == "charge.dispute.created":
await UserCredit().handle_dispute(event["data"]["object"])
if event_type in (
"customer.subscription.created",
"customer.subscription.updated",
"customer.subscription.deleted",
):
await sync_subscription_from_stripe(data_object)
if event["type"] == "refund.created" or event["type"] == "charge.dispute.closed":
await UserCredit().deduct_credits(event["data"]["object"])
# `subscription_schedule.updated` is deliberately omitted: our own
# `SubscriptionSchedule.create` + `.modify` calls in
# `_schedule_downgrade_at_period_end` would fire that event right back at us
# and loop redundant traffic through this handler. We only care about state
# transitions (released / completed); phase advance to the new price is
# already covered by `customer.subscription.updated`.
if event_type in (
"subscription_schedule.released",
"subscription_schedule.completed",
):
await sync_subscription_schedule_from_stripe(data_object)
if event_type == "invoice.payment_succeeded":
await handle_subscription_payment_success(data_object)
if event_type == "invoice.payment_failed":
await handle_subscription_payment_failure(data_object)
# `handle_dispute` and `deduct_credits` expect Stripe SDK typed objects
# (Dispute/Refund). The Stripe webhook payload's `data.object` is a
# StripeObject (a dict subclass) carrying that runtime shape, so we cast
# to satisfy the type checker without changing runtime behaviour.
if event_type == "charge.dispute.created":
await UserCredit().handle_dispute(cast(stripe.Dispute, data_object))
if event_type == "refund.created" or event_type == "charge.dispute.closed":
await UserCredit().deduct_credits(
cast("stripe.Refund | stripe.Dispute", data_object)
)
return Response(status_code=200)
@@ -1262,6 +1778,10 @@ async def enable_execution_sharing(
# Generate a unique share token
share_token = str(uuid.uuid4())
# Remove stale allowlist records before updating the token — prevents a
# window where old records + new token could coexist.
await execution_db.delete_shared_execution_files(execution_id=graph_exec_id)
# Update the execution with share info
await execution_db.update_graph_execution_share_status(
execution_id=graph_exec_id,
@@ -1271,6 +1791,14 @@ async def enable_execution_sharing(
shared_at=datetime.now(timezone.utc),
)
# Create allowlist of workspace files referenced in outputs
await execution_db.create_shared_execution_files(
execution_id=graph_exec_id,
share_token=share_token,
user_id=user_id,
outputs=execution.outputs,
)
# Return the share URL
frontend_url = settings.config.frontend_base_url or "http://localhost:3000"
share_url = f"{frontend_url}/share/{share_token}"
@@ -1296,6 +1824,9 @@ async def disable_execution_sharing(
if not execution:
raise HTTPException(status_code=404, detail="Execution not found")
# Remove shared file allowlist records
await execution_db.delete_shared_execution_files(execution_id=graph_exec_id)
# Remove share info
await execution_db.update_graph_execution_share_status(
execution_id=graph_exec_id,
@@ -1321,6 +1852,43 @@ async def get_shared_execution(
return execution
@v1_router.get(
"/public/shared/{share_token}/files/{file_id}/download",
summary="Download a file from a shared execution",
operation_id="download_shared_file",
tags=["graphs"],
)
async def download_shared_file(
share_token: Annotated[
str,
Path(pattern=r"^[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}$"),
],
file_id: Annotated[
str,
Path(pattern=r"^[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}$"),
],
) -> Response:
"""Download a workspace file from a shared execution (no auth required).
Validates that the file was explicitly exposed when sharing was enabled.
Returns a uniform 404 for all failure modes to prevent enumeration attacks.
"""
# Single-query validation against the allowlist
execution_id = await execution_db.get_shared_execution_file(
share_token=share_token, file_id=file_id
)
if not execution_id:
raise HTTPException(status_code=404, detail="Not found")
# Look up the actual file (no workspace scoping needed — the allowlist
# already validated that this file belongs to the shared execution)
file = await get_workspace_file_by_id(file_id)
if not file:
raise HTTPException(status_code=404, detail="Not found")
return await create_file_download_response(file, inline=True)
########################################################
##################### Schedules ########################
########################################################

View File

@@ -0,0 +1,157 @@
"""Tests for the public shared file download endpoint."""
from datetime import datetime, timezone
from unittest.mock import AsyncMock, patch
import pytest
from fastapi import FastAPI
from fastapi.testclient import TestClient
from starlette.responses import Response
from backend.api.features.v1 import v1_router
from backend.data.workspace import WorkspaceFile
app = FastAPI()
app.include_router(v1_router, prefix="/api")
VALID_TOKEN = "550e8400-e29b-41d4-a716-446655440000"
VALID_FILE_ID = "6ba7b810-9dad-11d1-80b4-00c04fd430c8"
def _make_workspace_file(**overrides) -> WorkspaceFile:
defaults = {
"id": VALID_FILE_ID,
"workspace_id": "ws-001",
"created_at": datetime(2026, 1, 1, tzinfo=timezone.utc),
"updated_at": datetime(2026, 1, 1, tzinfo=timezone.utc),
"name": "image.png",
"path": "/image.png",
"storage_path": "local://uploads/image.png",
"mime_type": "image/png",
"size_bytes": 4,
"checksum": None,
"is_deleted": False,
"deleted_at": None,
"metadata": {},
}
defaults.update(overrides)
return WorkspaceFile(**defaults)
def _mock_download_response(**kwargs):
"""Return an AsyncMock that resolves to a Response with inline disposition."""
async def _handler(file, *, inline=False):
return Response(
content=b"\x89PNG",
media_type="image/png",
headers={
"Content-Disposition": (
'inline; filename="image.png"'
if inline
else 'attachment; filename="image.png"'
),
"Content-Length": "4",
},
)
return _handler
class TestDownloadSharedFile:
"""Tests for GET /api/public/shared/{token}/files/{id}/download."""
@pytest.fixture(autouse=True)
def _client(self):
self.client = TestClient(app, raise_server_exceptions=False)
def test_valid_token_and_file_returns_inline_content(self):
with (
patch(
"backend.api.features.v1.execution_db.get_shared_execution_file",
new_callable=AsyncMock,
return_value="exec-123",
),
patch(
"backend.api.features.v1.get_workspace_file_by_id",
new_callable=AsyncMock,
return_value=_make_workspace_file(),
),
patch(
"backend.api.features.v1.create_file_download_response",
side_effect=_mock_download_response(),
),
):
response = self.client.get(
f"/api/public/shared/{VALID_TOKEN}/files/{VALID_FILE_ID}/download"
)
assert response.status_code == 200
assert response.content == b"\x89PNG"
assert "inline" in response.headers["Content-Disposition"]
def test_invalid_token_format_returns_422(self):
response = self.client.get(
f"/api/public/shared/not-a-uuid/files/{VALID_FILE_ID}/download"
)
assert response.status_code == 422
def test_token_not_in_allowlist_returns_404(self):
with patch(
"backend.api.features.v1.execution_db.get_shared_execution_file",
new_callable=AsyncMock,
return_value=None,
):
response = self.client.get(
f"/api/public/shared/{VALID_TOKEN}/files/{VALID_FILE_ID}/download"
)
assert response.status_code == 404
def test_file_missing_from_workspace_returns_404(self):
with (
patch(
"backend.api.features.v1.execution_db.get_shared_execution_file",
new_callable=AsyncMock,
return_value="exec-123",
),
patch(
"backend.api.features.v1.get_workspace_file_by_id",
new_callable=AsyncMock,
return_value=None,
),
):
response = self.client.get(
f"/api/public/shared/{VALID_TOKEN}/files/{VALID_FILE_ID}/download"
)
assert response.status_code == 404
def test_uniform_404_prevents_enumeration(self):
"""Both failure modes produce identical 404 — no information leak."""
with patch(
"backend.api.features.v1.execution_db.get_shared_execution_file",
new_callable=AsyncMock,
return_value=None,
):
resp_no_allow = self.client.get(
f"/api/public/shared/{VALID_TOKEN}/files/{VALID_FILE_ID}/download"
)
with (
patch(
"backend.api.features.v1.execution_db.get_shared_execution_file",
new_callable=AsyncMock,
return_value="exec-123",
),
patch(
"backend.api.features.v1.get_workspace_file_by_id",
new_callable=AsyncMock,
return_value=None,
),
):
resp_no_file = self.client.get(
f"/api/public/shared/{VALID_TOKEN}/files/{VALID_FILE_ID}/download"
)
assert resp_no_allow.status_code == 404
assert resp_no_file.status_code == 404
assert resp_no_allow.json() == resp_no_file.json()

View File

@@ -12,7 +12,7 @@ import fastapi
from autogpt_libs.auth.dependencies import get_user_id, requires_user
from fastapi import Query, UploadFile
from fastapi.responses import Response
from pydantic import BaseModel
from pydantic import BaseModel, Field
from backend.data.workspace import (
WorkspaceFile,
@@ -29,7 +29,9 @@ from backend.util.workspace import WorkspaceManager
from backend.util.workspace_storage import get_workspace_storage
def _sanitize_filename_for_header(filename: str) -> str:
def _sanitize_filename_for_header(
filename: str, disposition: str = "attachment"
) -> str:
"""
Sanitize filename for Content-Disposition header to prevent header injection.
@@ -44,11 +46,11 @@ def _sanitize_filename_for_header(filename: str) -> str:
# Check if filename has non-ASCII characters
try:
sanitized.encode("ascii")
return f'attachment; filename="{sanitized}"'
return f'{disposition}; filename="{sanitized}"'
except UnicodeEncodeError:
# Use RFC5987 encoding for UTF-8 filenames
encoded = quote(sanitized, safe="")
return f"attachment; filename*=UTF-8''{encoded}"
return f"{disposition}; filename*=UTF-8''{encoded}"
logger = logging.getLogger(__name__)
@@ -58,19 +60,26 @@ router = fastapi.APIRouter(
)
def _create_streaming_response(content: bytes, file: WorkspaceFile) -> Response:
def _create_streaming_response(
content: bytes, file: WorkspaceFile, *, inline: bool = False
) -> Response:
"""Create a streaming response for file content."""
disposition = _sanitize_filename_for_header(
file.name, disposition="inline" if inline else "attachment"
)
return Response(
content=content,
media_type=file.mime_type,
headers={
"Content-Disposition": _sanitize_filename_for_header(file.name),
"Content-Disposition": disposition,
"Content-Length": str(len(content)),
},
)
async def _create_file_download_response(file: WorkspaceFile) -> Response:
async def create_file_download_response(
file: WorkspaceFile, *, inline: bool = False
) -> Response:
"""
Create a download response for a workspace file.
@@ -82,7 +91,7 @@ async def _create_file_download_response(file: WorkspaceFile) -> Response:
# For local storage, stream the file directly
if file.storage_path.startswith("local://"):
content = await storage.retrieve(file.storage_path)
return _create_streaming_response(content, file)
return _create_streaming_response(content, file, inline=inline)
# For GCS, try to redirect to signed URL, fall back to streaming
try:
@@ -90,7 +99,7 @@ async def _create_file_download_response(file: WorkspaceFile) -> Response:
# If we got back an API path (fallback), stream directly instead
if url.startswith("/api/"):
content = await storage.retrieve(file.storage_path)
return _create_streaming_response(content, file)
return _create_streaming_response(content, file, inline=inline)
return fastapi.responses.RedirectResponse(url=url, status_code=302)
except Exception as e:
# Log the signed URL failure with context
@@ -102,7 +111,7 @@ async def _create_file_download_response(file: WorkspaceFile) -> Response:
# Fall back to streaming directly from GCS
try:
content = await storage.retrieve(file.storage_path)
return _create_streaming_response(content, file)
return _create_streaming_response(content, file, inline=inline)
except Exception as fallback_error:
logger.error(
f"Fallback streaming also failed for file {file.id} "
@@ -131,9 +140,26 @@ class StorageUsageResponse(BaseModel):
file_count: int
class WorkspaceFileItem(BaseModel):
id: str
name: str
path: str
mime_type: str
size_bytes: int
metadata: dict = Field(default_factory=dict)
created_at: str
class ListFilesResponse(BaseModel):
files: list[WorkspaceFileItem]
offset: int = 0
has_more: bool = False
@router.get(
"/files/{file_id}/download",
summary="Download file by ID",
operation_id="getWorkspaceDownloadFileById",
)
async def download_file(
user_id: Annotated[str, fastapi.Security(get_user_id)],
@@ -152,12 +178,13 @@ async def download_file(
if file is None:
raise fastapi.HTTPException(status_code=404, detail="File not found")
return await _create_file_download_response(file)
return await create_file_download_response(file)
@router.delete(
"/files/{file_id}",
summary="Delete a workspace file",
operation_id="deleteWorkspaceFile",
)
async def delete_workspace_file(
user_id: Annotated[str, fastapi.Security(get_user_id)],
@@ -183,6 +210,7 @@ async def delete_workspace_file(
@router.post(
"/files/upload",
summary="Upload file to workspace",
operation_id="uploadWorkspaceFile",
)
async def upload_file(
user_id: Annotated[str, fastapi.Security(get_user_id)],
@@ -196,6 +224,9 @@ async def upload_file(
Files are stored in session-scoped paths when session_id is provided,
so the agent's session-scoped tools can discover them automatically.
"""
# Empty-string session_id drops session scoping; normalize to None.
session_id = session_id or None
config = Config()
# Sanitize filename — strip any directory components
@@ -250,16 +281,27 @@ async def upload_file(
manager = WorkspaceManager(user_id, workspace.id, session_id)
try:
workspace_file = await manager.write_file(
content, filename, overwrite=overwrite
content, filename, overwrite=overwrite, metadata={"origin": "user-upload"}
)
except ValueError as e:
raise fastapi.HTTPException(status_code=409, detail=str(e)) from e
# write_file raises ValueError for both path-conflict and size-limit
# cases; map each to its correct HTTP status.
message = str(e)
if message.startswith("File too large"):
raise fastapi.HTTPException(status_code=413, detail=message) from e
raise fastapi.HTTPException(status_code=409, detail=message) from e
# Post-write storage check — eliminates TOCTOU race on the quota.
# If a concurrent upload pushed us over the limit, undo this write.
new_total = await get_workspace_total_size(workspace.id)
if storage_limit_bytes and new_total > storage_limit_bytes:
await soft_delete_workspace_file(workspace_file.id, workspace.id)
try:
await soft_delete_workspace_file(workspace_file.id, workspace.id)
except Exception as e:
logger.warning(
f"Failed to soft-delete over-quota file {workspace_file.id} "
f"in workspace {workspace.id}: {e}"
)
raise fastapi.HTTPException(
status_code=413,
detail={
@@ -281,6 +323,7 @@ async def upload_file(
@router.get(
"/storage/usage",
summary="Get workspace storage usage",
operation_id="getWorkspaceStorageUsage",
)
async def get_storage_usage(
user_id: Annotated[str, fastapi.Security(get_user_id)],
@@ -301,3 +344,57 @@ async def get_storage_usage(
used_percent=round((used_bytes / limit_bytes) * 100, 1) if limit_bytes else 0,
file_count=file_count,
)
@router.get(
"/files",
summary="List workspace files",
operation_id="listWorkspaceFiles",
)
async def list_workspace_files(
user_id: Annotated[str, fastapi.Security(get_user_id)],
session_id: str | None = Query(default=None),
limit: int = Query(default=200, ge=1, le=1000),
offset: int = Query(default=0, ge=0),
) -> ListFilesResponse:
"""
List files in the user's workspace.
When session_id is provided, only files for that session are returned.
Otherwise, all files across sessions are listed. Results are paginated
via `limit`/`offset`; `has_more` indicates whether additional pages exist.
"""
workspace = await get_or_create_workspace(user_id)
# Treat empty-string session_id the same as omitted — an empty value
# would otherwise silently list files across every session instead of
# scoping to one.
session_id = session_id or None
manager = WorkspaceManager(user_id, workspace.id, session_id)
include_all = session_id is None
# Fetch one extra to compute has_more without a separate count query.
files = await manager.list_files(
limit=limit + 1,
offset=offset,
include_all_sessions=include_all,
)
has_more = len(files) > limit
page = files[:limit]
return ListFilesResponse(
files=[
WorkspaceFileItem(
id=f.id,
name=f.name,
path=f.path,
mime_type=f.mime_type,
size_bytes=f.size_bytes,
metadata=f.metadata or {},
created_at=f.created_at.isoformat(),
)
for f in page
],
offset=offset,
has_more=has_more,
)

View File

@@ -1,48 +1,28 @@
"""Tests for workspace file upload and download routes."""
import io
from datetime import datetime, timezone
from unittest.mock import AsyncMock, MagicMock, patch
import fastapi
import fastapi.testclient
import pytest
import pytest_mock
from backend.api.features.workspace import routes as workspace_routes
from backend.data.workspace import WorkspaceFile
from backend.api.features.workspace.routes import router
from backend.data.workspace import Workspace, WorkspaceFile
app = fastapi.FastAPI()
app.include_router(workspace_routes.router)
app.include_router(router)
@app.exception_handler(ValueError)
async def _value_error_handler(
request: fastapi.Request, exc: ValueError
) -> fastapi.responses.JSONResponse:
"""Mirror the production ValueError → 400 mapping from rest_api.py."""
"""Mirror the production ValueError → 400 mapping from the REST app."""
return fastapi.responses.JSONResponse(status_code=400, content={"detail": str(exc)})
client = fastapi.testclient.TestClient(app)
TEST_USER_ID = "3e53486c-cf57-477e-ba2a-cb02dc828e1a"
MOCK_WORKSPACE = type("W", (), {"id": "ws-1"})()
_NOW = datetime(2023, 1, 1, tzinfo=timezone.utc)
MOCK_FILE = WorkspaceFile(
id="file-aaa-bbb",
workspace_id="ws-1",
created_at=_NOW,
updated_at=_NOW,
name="hello.txt",
path="/session/hello.txt",
mime_type="text/plain",
size_bytes=13,
storage_path="local://hello.txt",
)
@pytest.fixture(autouse=True)
def setup_app_auth(mock_jwt_user):
@@ -53,25 +33,201 @@ def setup_app_auth(mock_jwt_user):
app.dependency_overrides.clear()
def _make_workspace(user_id: str = "test-user-id") -> Workspace:
return Workspace(
id="ws-001",
user_id=user_id,
created_at=datetime(2026, 1, 1, tzinfo=timezone.utc),
updated_at=datetime(2026, 1, 1, tzinfo=timezone.utc),
)
def _make_file(**overrides) -> WorkspaceFile:
defaults = {
"id": "file-001",
"workspace_id": "ws-001",
"created_at": datetime(2026, 1, 1, tzinfo=timezone.utc),
"updated_at": datetime(2026, 1, 1, tzinfo=timezone.utc),
"name": "test.txt",
"path": "/test.txt",
"storage_path": "local://test.txt",
"mime_type": "text/plain",
"size_bytes": 100,
"checksum": None,
"is_deleted": False,
"deleted_at": None,
"metadata": {},
}
defaults.update(overrides)
return WorkspaceFile(**defaults)
def _make_file_mock(**overrides) -> MagicMock:
"""Create a mock WorkspaceFile to simulate DB records with null fields."""
defaults = {
"id": "file-001",
"name": "test.txt",
"path": "/test.txt",
"mime_type": "text/plain",
"size_bytes": 100,
"metadata": {},
"created_at": datetime(2026, 1, 1, tzinfo=timezone.utc),
}
defaults.update(overrides)
mock = MagicMock(spec=WorkspaceFile)
for k, v in defaults.items():
setattr(mock, k, v)
return mock
# -- list_workspace_files tests --
@patch("backend.api.features.workspace.routes.get_or_create_workspace")
@patch("backend.api.features.workspace.routes.WorkspaceManager")
def test_list_files_returns_all_when_no_session(mock_manager_cls, mock_get_workspace):
mock_get_workspace.return_value = _make_workspace()
files = [
_make_file(id="f1", name="a.txt", metadata={"origin": "user-upload"}),
_make_file(id="f2", name="b.csv", metadata={"origin": "agent-created"}),
]
mock_instance = AsyncMock()
mock_instance.list_files.return_value = files
mock_manager_cls.return_value = mock_instance
response = client.get("/files")
assert response.status_code == 200
data = response.json()
assert len(data["files"]) == 2
assert data["has_more"] is False
assert data["offset"] == 0
assert data["files"][0]["id"] == "f1"
assert data["files"][0]["metadata"] == {"origin": "user-upload"}
assert data["files"][1]["id"] == "f2"
mock_instance.list_files.assert_called_once_with(
limit=201, offset=0, include_all_sessions=True
)
@patch("backend.api.features.workspace.routes.get_or_create_workspace")
@patch("backend.api.features.workspace.routes.WorkspaceManager")
def test_list_files_scopes_to_session_when_provided(
mock_manager_cls, mock_get_workspace, test_user_id
):
mock_get_workspace.return_value = _make_workspace(user_id=test_user_id)
mock_instance = AsyncMock()
mock_instance.list_files.return_value = []
mock_manager_cls.return_value = mock_instance
response = client.get("/files?session_id=sess-123")
assert response.status_code == 200
data = response.json()
assert data["files"] == []
assert data["has_more"] is False
mock_manager_cls.assert_called_once_with(test_user_id, "ws-001", "sess-123")
mock_instance.list_files.assert_called_once_with(
limit=201, offset=0, include_all_sessions=False
)
@patch("backend.api.features.workspace.routes.get_or_create_workspace")
@patch("backend.api.features.workspace.routes.WorkspaceManager")
def test_list_files_null_metadata_coerced_to_empty_dict(
mock_manager_cls, mock_get_workspace
):
"""Route uses `f.metadata or {}` for pre-existing files with null metadata."""
mock_get_workspace.return_value = _make_workspace()
mock_instance = AsyncMock()
mock_instance.list_files.return_value = [_make_file_mock(metadata=None)]
mock_manager_cls.return_value = mock_instance
response = client.get("/files")
assert response.status_code == 200
assert response.json()["files"][0]["metadata"] == {}
# -- upload_file metadata tests --
@patch("backend.api.features.workspace.routes.get_or_create_workspace")
@patch("backend.api.features.workspace.routes.get_workspace_total_size")
@patch("backend.api.features.workspace.routes.scan_content_safe")
@patch("backend.api.features.workspace.routes.WorkspaceManager")
def test_upload_passes_user_upload_origin_metadata(
mock_manager_cls, mock_scan, mock_total_size, mock_get_workspace
):
mock_get_workspace.return_value = _make_workspace()
mock_total_size.return_value = 100
written = _make_file(id="new-file", name="doc.pdf")
mock_instance = AsyncMock()
mock_instance.write_file.return_value = written
mock_manager_cls.return_value = mock_instance
response = client.post(
"/files/upload",
files={"file": ("doc.pdf", b"fake-pdf-content", "application/pdf")},
)
assert response.status_code == 200
mock_instance.write_file.assert_called_once()
call_kwargs = mock_instance.write_file.call_args
assert call_kwargs.kwargs.get("metadata") == {"origin": "user-upload"}
@patch("backend.api.features.workspace.routes.get_or_create_workspace")
@patch("backend.api.features.workspace.routes.get_workspace_total_size")
@patch("backend.api.features.workspace.routes.scan_content_safe")
@patch("backend.api.features.workspace.routes.WorkspaceManager")
def test_upload_returns_409_on_file_conflict(
mock_manager_cls, mock_scan, mock_total_size, mock_get_workspace
):
mock_get_workspace.return_value = _make_workspace()
mock_total_size.return_value = 100
mock_instance = AsyncMock()
mock_instance.write_file.side_effect = ValueError("File already exists at path")
mock_manager_cls.return_value = mock_instance
response = client.post(
"/files/upload",
files={"file": ("dup.txt", b"content", "text/plain")},
)
assert response.status_code == 409
assert "already exists" in response.json()["detail"]
# -- Restored upload/download/delete security + invariant tests --
def _upload(
filename: str = "hello.txt",
content: bytes = b"Hello, world!",
content_type: str = "text/plain",
):
"""Helper to POST a file upload."""
return client.post(
"/files/upload?session_id=sess-1",
files={"file": (filename, io.BytesIO(content), content_type)},
)
# ---- Happy path ----
_MOCK_FILE = WorkspaceFile(
id="file-aaa-bbb",
workspace_id="ws-001",
created_at=datetime(2026, 1, 1, tzinfo=timezone.utc),
updated_at=datetime(2026, 1, 1, tzinfo=timezone.utc),
name="hello.txt",
path="/sessions/sess-1/hello.txt",
mime_type="text/plain",
size_bytes=13,
storage_path="local://hello.txt",
)
def test_upload_happy_path(mocker: pytest_mock.MockFixture):
def test_upload_happy_path(mocker):
mocker.patch(
"backend.api.features.workspace.routes.get_or_create_workspace",
return_value=MOCK_WORKSPACE,
return_value=_make_workspace(),
)
mocker.patch(
"backend.api.features.workspace.routes.get_workspace_total_size",
@@ -82,7 +238,7 @@ def test_upload_happy_path(mocker: pytest_mock.MockFixture):
return_value=None,
)
mock_manager = mocker.MagicMock()
mock_manager.write_file = mocker.AsyncMock(return_value=MOCK_FILE)
mock_manager.write_file = mocker.AsyncMock(return_value=_MOCK_FILE)
mocker.patch(
"backend.api.features.workspace.routes.WorkspaceManager",
return_value=mock_manager,
@@ -96,10 +252,7 @@ def test_upload_happy_path(mocker: pytest_mock.MockFixture):
assert data["size_bytes"] == 13
# ---- Per-file size limit ----
def test_upload_exceeds_max_file_size(mocker: pytest_mock.MockFixture):
def test_upload_exceeds_max_file_size(mocker):
"""Files larger than max_file_size_mb should be rejected with 413."""
cfg = mocker.patch("backend.api.features.workspace.routes.Config")
cfg.return_value.max_file_size_mb = 0 # 0 MB → any content is too big
@@ -109,15 +262,11 @@ def test_upload_exceeds_max_file_size(mocker: pytest_mock.MockFixture):
assert response.status_code == 413
# ---- Storage quota exceeded ----
def test_upload_storage_quota_exceeded(mocker: pytest_mock.MockFixture):
def test_upload_storage_quota_exceeded(mocker):
mocker.patch(
"backend.api.features.workspace.routes.get_or_create_workspace",
return_value=MOCK_WORKSPACE,
return_value=_make_workspace(),
)
# Current usage already at limit
mocker.patch(
"backend.api.features.workspace.routes.get_workspace_total_size",
return_value=500 * 1024 * 1024,
@@ -128,27 +277,22 @@ def test_upload_storage_quota_exceeded(mocker: pytest_mock.MockFixture):
assert "Storage limit exceeded" in response.text
# ---- Post-write quota race (B2) ----
def test_upload_post_write_quota_race(mocker: pytest_mock.MockFixture):
"""If a concurrent upload tips the total over the limit after write,
the file should be soft-deleted and 413 returned."""
def test_upload_post_write_quota_race(mocker):
"""Concurrent upload tipping over limit after write should soft-delete + 413."""
mocker.patch(
"backend.api.features.workspace.routes.get_or_create_workspace",
return_value=MOCK_WORKSPACE,
return_value=_make_workspace(),
)
# Pre-write check passes (under limit), but post-write check fails
mocker.patch(
"backend.api.features.workspace.routes.get_workspace_total_size",
side_effect=[0, 600 * 1024 * 1024], # first call OK, second over limit
side_effect=[0, 600 * 1024 * 1024],
)
mocker.patch(
"backend.api.features.workspace.routes.scan_content_safe",
return_value=None,
)
mock_manager = mocker.MagicMock()
mock_manager.write_file = mocker.AsyncMock(return_value=MOCK_FILE)
mock_manager.write_file = mocker.AsyncMock(return_value=_MOCK_FILE)
mocker.patch(
"backend.api.features.workspace.routes.WorkspaceManager",
return_value=mock_manager,
@@ -160,17 +304,14 @@ def test_upload_post_write_quota_race(mocker: pytest_mock.MockFixture):
response = _upload()
assert response.status_code == 413
mock_delete.assert_called_once_with("file-aaa-bbb", "ws-1")
mock_delete.assert_called_once_with("file-aaa-bbb", "ws-001")
# ---- Any extension accepted (no allowlist) ----
def test_upload_any_extension(mocker: pytest_mock.MockFixture):
def test_upload_any_extension(mocker):
"""Any file extension should be accepted — ClamAV is the security layer."""
mocker.patch(
"backend.api.features.workspace.routes.get_or_create_workspace",
return_value=MOCK_WORKSPACE,
return_value=_make_workspace(),
)
mocker.patch(
"backend.api.features.workspace.routes.get_workspace_total_size",
@@ -181,7 +322,7 @@ def test_upload_any_extension(mocker: pytest_mock.MockFixture):
return_value=None,
)
mock_manager = mocker.MagicMock()
mock_manager.write_file = mocker.AsyncMock(return_value=MOCK_FILE)
mock_manager.write_file = mocker.AsyncMock(return_value=_MOCK_FILE)
mocker.patch(
"backend.api.features.workspace.routes.WorkspaceManager",
return_value=mock_manager,
@@ -191,16 +332,13 @@ def test_upload_any_extension(mocker: pytest_mock.MockFixture):
assert response.status_code == 200
# ---- Virus scan rejection ----
def test_upload_blocked_by_virus_scan(mocker: pytest_mock.MockFixture):
def test_upload_blocked_by_virus_scan(mocker):
"""Files flagged by ClamAV should be rejected and never written to storage."""
from backend.api.features.store.exceptions import VirusDetectedError
mocker.patch(
"backend.api.features.workspace.routes.get_or_create_workspace",
return_value=MOCK_WORKSPACE,
return_value=_make_workspace(),
)
mocker.patch(
"backend.api.features.workspace.routes.get_workspace_total_size",
@@ -211,7 +349,7 @@ def test_upload_blocked_by_virus_scan(mocker: pytest_mock.MockFixture):
side_effect=VirusDetectedError("Eicar-Test-Signature"),
)
mock_manager = mocker.MagicMock()
mock_manager.write_file = mocker.AsyncMock(return_value=MOCK_FILE)
mock_manager.write_file = mocker.AsyncMock(return_value=_MOCK_FILE)
mocker.patch(
"backend.api.features.workspace.routes.WorkspaceManager",
return_value=mock_manager,
@@ -219,18 +357,14 @@ def test_upload_blocked_by_virus_scan(mocker: pytest_mock.MockFixture):
response = _upload(filename="evil.exe", content=b"X5O!P%@AP...")
assert response.status_code == 400
assert "Virus detected" in response.text
mock_manager.write_file.assert_not_called()
# ---- No file extension ----
def test_upload_file_without_extension(mocker: pytest_mock.MockFixture):
def test_upload_file_without_extension(mocker):
"""Files without an extension should be accepted and stored as-is."""
mocker.patch(
"backend.api.features.workspace.routes.get_or_create_workspace",
return_value=MOCK_WORKSPACE,
return_value=_make_workspace(),
)
mocker.patch(
"backend.api.features.workspace.routes.get_workspace_total_size",
@@ -241,7 +375,7 @@ def test_upload_file_without_extension(mocker: pytest_mock.MockFixture):
return_value=None,
)
mock_manager = mocker.MagicMock()
mock_manager.write_file = mocker.AsyncMock(return_value=MOCK_FILE)
mock_manager.write_file = mocker.AsyncMock(return_value=_MOCK_FILE)
mocker.patch(
"backend.api.features.workspace.routes.WorkspaceManager",
return_value=mock_manager,
@@ -257,14 +391,11 @@ def test_upload_file_without_extension(mocker: pytest_mock.MockFixture):
assert mock_manager.write_file.call_args[0][1] == "Makefile"
# ---- Filename sanitization (SF5) ----
def test_upload_strips_path_components(mocker: pytest_mock.MockFixture):
def test_upload_strips_path_components(mocker):
"""Path-traversal filenames should be reduced to their basename."""
mocker.patch(
"backend.api.features.workspace.routes.get_or_create_workspace",
return_value=MOCK_WORKSPACE,
return_value=_make_workspace(),
)
mocker.patch(
"backend.api.features.workspace.routes.get_workspace_total_size",
@@ -275,28 +406,23 @@ def test_upload_strips_path_components(mocker: pytest_mock.MockFixture):
return_value=None,
)
mock_manager = mocker.MagicMock()
mock_manager.write_file = mocker.AsyncMock(return_value=MOCK_FILE)
mock_manager.write_file = mocker.AsyncMock(return_value=_MOCK_FILE)
mocker.patch(
"backend.api.features.workspace.routes.WorkspaceManager",
return_value=mock_manager,
)
# Filename with traversal
_upload(filename="../../etc/passwd.txt")
# write_file should have been called with just the basename
mock_manager.write_file.assert_called_once()
call_args = mock_manager.write_file.call_args
assert call_args[0][1] == "passwd.txt"
# ---- Download ----
def test_download_file_not_found(mocker: pytest_mock.MockFixture):
def test_download_file_not_found(mocker):
mocker.patch(
"backend.api.features.workspace.routes.get_workspace",
return_value=MOCK_WORKSPACE,
return_value=_make_workspace(),
)
mocker.patch(
"backend.api.features.workspace.routes.get_workspace_file",
@@ -307,14 +433,11 @@ def test_download_file_not_found(mocker: pytest_mock.MockFixture):
assert response.status_code == 404
# ---- Delete ----
def test_delete_file_success(mocker: pytest_mock.MockFixture):
def test_delete_file_success(mocker):
"""Deleting an existing file should return {"deleted": true}."""
mocker.patch(
"backend.api.features.workspace.routes.get_workspace",
return_value=MOCK_WORKSPACE,
return_value=_make_workspace(),
)
mock_manager = mocker.MagicMock()
mock_manager.delete_file = mocker.AsyncMock(return_value=True)
@@ -329,11 +452,11 @@ def test_delete_file_success(mocker: pytest_mock.MockFixture):
mock_manager.delete_file.assert_called_once_with("file-aaa-bbb")
def test_delete_file_not_found(mocker: pytest_mock.MockFixture):
def test_delete_file_not_found(mocker):
"""Deleting a non-existent file should return 404."""
mocker.patch(
"backend.api.features.workspace.routes.get_workspace",
return_value=MOCK_WORKSPACE,
return_value=_make_workspace(),
)
mock_manager = mocker.MagicMock()
mock_manager.delete_file = mocker.AsyncMock(return_value=False)
@@ -347,7 +470,7 @@ def test_delete_file_not_found(mocker: pytest_mock.MockFixture):
assert "File not found" in response.text
def test_delete_file_no_workspace(mocker: pytest_mock.MockFixture):
def test_delete_file_no_workspace(mocker):
"""Deleting when user has no workspace should return 404."""
mocker.patch(
"backend.api.features.workspace.routes.get_workspace",
@@ -357,3 +480,341 @@ def test_delete_file_no_workspace(mocker: pytest_mock.MockFixture):
response = client.delete("/files/file-aaa-bbb")
assert response.status_code == 404
assert "Workspace not found" in response.text
def test_upload_write_file_too_large_returns_413(mocker):
"""write_file raises ValueError("File too large: …") → must map to 413."""
mocker.patch(
"backend.api.features.workspace.routes.get_or_create_workspace",
return_value=_make_workspace(),
)
mocker.patch(
"backend.api.features.workspace.routes.get_workspace_total_size",
return_value=0,
)
mocker.patch(
"backend.api.features.workspace.routes.scan_content_safe",
return_value=None,
)
mock_manager = mocker.MagicMock()
mock_manager.write_file = mocker.AsyncMock(
side_effect=ValueError("File too large: 900 bytes exceeds 1MB limit")
)
mocker.patch(
"backend.api.features.workspace.routes.WorkspaceManager",
return_value=mock_manager,
)
response = _upload()
assert response.status_code == 413
assert "File too large" in response.text
def test_upload_write_file_conflict_returns_409(mocker):
"""Non-'File too large' ValueErrors from write_file stay as 409."""
mocker.patch(
"backend.api.features.workspace.routes.get_or_create_workspace",
return_value=_make_workspace(),
)
mocker.patch(
"backend.api.features.workspace.routes.get_workspace_total_size",
return_value=0,
)
mocker.patch(
"backend.api.features.workspace.routes.scan_content_safe",
return_value=None,
)
mock_manager = mocker.MagicMock()
mock_manager.write_file = mocker.AsyncMock(
side_effect=ValueError("File already exists at path: /sessions/x/a.txt")
)
mocker.patch(
"backend.api.features.workspace.routes.WorkspaceManager",
return_value=mock_manager,
)
response = _upload()
assert response.status_code == 409
assert "already exists" in response.text
@patch("backend.api.features.workspace.routes.get_or_create_workspace")
@patch("backend.api.features.workspace.routes.WorkspaceManager")
def test_list_files_has_more_true_when_limit_exceeded(
mock_manager_cls, mock_get_workspace
):
"""The limit+1 fetch trick must flip has_more=True and trim the page."""
mock_get_workspace.return_value = _make_workspace()
# Backend was asked for limit+1=3, and returned exactly 3 items.
files = [
_make_file(id="f1", name="a.txt"),
_make_file(id="f2", name="b.txt"),
_make_file(id="f3", name="c.txt"),
]
mock_instance = AsyncMock()
mock_instance.list_files.return_value = files
mock_manager_cls.return_value = mock_instance
response = client.get("/files?limit=2")
assert response.status_code == 200
data = response.json()
assert data["has_more"] is True
assert len(data["files"]) == 2
assert data["files"][0]["id"] == "f1"
assert data["files"][1]["id"] == "f2"
mock_instance.list_files.assert_called_once_with(
limit=3, offset=0, include_all_sessions=True
)
@patch("backend.api.features.workspace.routes.get_or_create_workspace")
@patch("backend.api.features.workspace.routes.WorkspaceManager")
def test_list_files_has_more_false_when_exactly_page_size(
mock_manager_cls, mock_get_workspace
):
"""Exactly `limit` rows means we're on the last page — has_more=False."""
mock_get_workspace.return_value = _make_workspace()
files = [_make_file(id="f1", name="a.txt"), _make_file(id="f2", name="b.txt")]
mock_instance = AsyncMock()
mock_instance.list_files.return_value = files
mock_manager_cls.return_value = mock_instance
response = client.get("/files?limit=2")
assert response.status_code == 200
data = response.json()
assert data["has_more"] is False
assert len(data["files"]) == 2
@patch("backend.api.features.workspace.routes.get_or_create_workspace")
@patch("backend.api.features.workspace.routes.WorkspaceManager")
def test_list_files_offset_is_echoed_back(mock_manager_cls, mock_get_workspace):
mock_get_workspace.return_value = _make_workspace()
mock_instance = AsyncMock()
mock_instance.list_files.return_value = []
mock_manager_cls.return_value = mock_instance
response = client.get("/files?offset=50&limit=10")
assert response.status_code == 200
assert response.json()["offset"] == 50
mock_instance.list_files.assert_called_once_with(
limit=11, offset=50, include_all_sessions=True
)
# -- _sanitize_filename_for_header tests --
class TestSanitizeFilenameForHeader:
def test_simple_ascii_attachment(self):
from backend.api.features.workspace.routes import _sanitize_filename_for_header
assert _sanitize_filename_for_header("report.pdf") == (
'attachment; filename="report.pdf"'
)
def test_inline_disposition(self):
from backend.api.features.workspace.routes import _sanitize_filename_for_header
assert _sanitize_filename_for_header("image.png", disposition="inline") == (
'inline; filename="image.png"'
)
def test_strips_cr_lf_null(self):
from backend.api.features.workspace.routes import _sanitize_filename_for_header
result = _sanitize_filename_for_header("a\rb\nc\x00d.txt")
assert "\r" not in result
assert "\n" not in result
assert "\x00" not in result
assert 'filename="abcd.txt"' in result
def test_escapes_quotes(self):
from backend.api.features.workspace.routes import _sanitize_filename_for_header
result = _sanitize_filename_for_header('file"name.txt')
assert 'filename="file\\"name.txt"' in result
def test_header_injection_blocked(self):
from backend.api.features.workspace.routes import _sanitize_filename_for_header
result = _sanitize_filename_for_header("evil.txt\r\nX-Injected: true")
# CR/LF stripped — the remaining text is safely inside the quoted value
assert "\r" not in result
assert "\n" not in result
assert result == 'attachment; filename="evil.txtX-Injected: true"'
def test_unicode_uses_rfc5987(self):
from backend.api.features.workspace.routes import _sanitize_filename_for_header
result = _sanitize_filename_for_header("日本語.pdf")
assert "filename*=UTF-8''" in result
assert "attachment" in result
def test_unicode_inline(self):
from backend.api.features.workspace.routes import _sanitize_filename_for_header
result = _sanitize_filename_for_header("图片.png", disposition="inline")
assert result.startswith("inline; filename*=UTF-8''")
def test_empty_filename(self):
from backend.api.features.workspace.routes import _sanitize_filename_for_header
result = _sanitize_filename_for_header("")
assert result == 'attachment; filename=""'
# -- _create_streaming_response tests --
class TestCreateStreamingResponse:
def test_attachment_disposition_by_default(self):
from backend.api.features.workspace.routes import _create_streaming_response
file = _make_file(name="data.bin", mime_type="application/octet-stream")
response = _create_streaming_response(b"binary-data", file)
assert (
response.headers["Content-Disposition"] == 'attachment; filename="data.bin"'
)
assert response.headers["Content-Type"] == "application/octet-stream"
assert response.headers["Content-Length"] == "11"
assert response.body == b"binary-data"
def test_inline_disposition(self):
from backend.api.features.workspace.routes import _create_streaming_response
file = _make_file(name="photo.png", mime_type="image/png")
response = _create_streaming_response(b"\x89PNG", file, inline=True)
assert response.headers["Content-Disposition"] == 'inline; filename="photo.png"'
assert response.headers["Content-Type"] == "image/png"
def test_inline_sanitizes_filename(self):
from backend.api.features.workspace.routes import _create_streaming_response
file = _make_file(name='evil"\r\n.txt', mime_type="text/plain")
response = _create_streaming_response(b"data", file, inline=True)
assert "\r" not in response.headers["Content-Disposition"]
assert "\n" not in response.headers["Content-Disposition"]
assert "inline" in response.headers["Content-Disposition"]
def test_content_length_matches_body(self):
from backend.api.features.workspace.routes import _create_streaming_response
content = b"x" * 1000
file = _make_file(name="big.bin", mime_type="application/octet-stream")
response = _create_streaming_response(content, file)
assert response.headers["Content-Length"] == "1000"
# -- create_file_download_response tests --
class TestCreateFileDownloadResponse:
@pytest.mark.asyncio
async def test_local_storage_returns_streaming_response(self, mocker):
from backend.api.features.workspace.routes import create_file_download_response
mock_storage = AsyncMock()
mock_storage.retrieve.return_value = b"file contents"
mocker.patch(
"backend.api.features.workspace.routes.get_workspace_storage",
return_value=mock_storage,
)
file = _make_file(
storage_path="local://uploads/test.txt",
mime_type="text/plain",
)
response = await create_file_download_response(file)
assert response.status_code == 200
assert response.body == b"file contents"
assert "attachment" in response.headers["Content-Disposition"]
@pytest.mark.asyncio
async def test_local_storage_inline(self, mocker):
from backend.api.features.workspace.routes import create_file_download_response
mock_storage = AsyncMock()
mock_storage.retrieve.return_value = b"\x89PNG"
mocker.patch(
"backend.api.features.workspace.routes.get_workspace_storage",
return_value=mock_storage,
)
file = _make_file(
storage_path="local://uploads/photo.png",
mime_type="image/png",
name="photo.png",
)
response = await create_file_download_response(file, inline=True)
assert "inline" in response.headers["Content-Disposition"]
@pytest.mark.asyncio
async def test_gcs_redirect(self, mocker):
from backend.api.features.workspace.routes import create_file_download_response
mock_storage = AsyncMock()
mock_storage.get_download_url.return_value = (
"https://storage.googleapis.com/signed-url"
)
mocker.patch(
"backend.api.features.workspace.routes.get_workspace_storage",
return_value=mock_storage,
)
file = _make_file(storage_path="gcs://bucket/file.pdf")
response = await create_file_download_response(file)
assert response.status_code == 302
assert (
response.headers["location"] == "https://storage.googleapis.com/signed-url"
)
@pytest.mark.asyncio
async def test_gcs_api_fallback_streams_directly(self, mocker):
from backend.api.features.workspace.routes import create_file_download_response
mock_storage = AsyncMock()
mock_storage.get_download_url.return_value = "/api/fallback"
mock_storage.retrieve.return_value = b"fallback content"
mocker.patch(
"backend.api.features.workspace.routes.get_workspace_storage",
return_value=mock_storage,
)
file = _make_file(storage_path="gcs://bucket/file.txt")
response = await create_file_download_response(file)
assert response.status_code == 200
assert response.body == b"fallback content"
@pytest.mark.asyncio
async def test_gcs_signed_url_failure_falls_back_to_streaming(self, mocker):
from backend.api.features.workspace.routes import create_file_download_response
mock_storage = AsyncMock()
mock_storage.get_download_url.side_effect = RuntimeError("GCS error")
mock_storage.retrieve.return_value = b"streamed"
mocker.patch(
"backend.api.features.workspace.routes.get_workspace_storage",
return_value=mock_storage,
)
file = _make_file(storage_path="gcs://bucket/file.txt")
response = await create_file_download_response(file)
assert response.status_code == 200
assert response.body == b"streamed"
@pytest.mark.asyncio
async def test_gcs_total_failure_raises(self, mocker):
from backend.api.features.workspace.routes import create_file_download_response
mock_storage = AsyncMock()
mock_storage.get_download_url.side_effect = RuntimeError("GCS error")
mock_storage.retrieve.side_effect = RuntimeError("Also failed")
mocker.patch(
"backend.api.features.workspace.routes.get_workspace_storage",
return_value=mock_storage,
)
file = _make_file(storage_path="gcs://bucket/file.txt")
with pytest.raises(RuntimeError, match="Also failed"):
await create_file_download_response(file)

View File

@@ -17,7 +17,9 @@ from fastapi.routing import APIRoute
from prisma.errors import PrismaError
import backend.api.features.admin.credit_admin_routes
import backend.api.features.admin.diagnostics_admin_routes
import backend.api.features.admin.execution_analytics_routes
import backend.api.features.admin.platform_cost_routes
import backend.api.features.admin.rate_limit_admin_routes
import backend.api.features.admin.store_admin_routes
import backend.api.features.builder
@@ -30,7 +32,9 @@ import backend.api.features.library.routes
import backend.api.features.mcp.routes as mcp_routes
import backend.api.features.oauth
import backend.api.features.otto.routes
import backend.api.features.platform_linking.routes
import backend.api.features.postmark.postmark
import backend.api.features.push.routes as push_routes
import backend.api.features.store.model
import backend.api.features.store.routes
import backend.api.features.v1
@@ -38,6 +42,7 @@ import backend.api.features.workspace.routes as workspace_routes
import backend.data.block
import backend.data.db
import backend.data.graph
import backend.data.redis_client
import backend.data.user
import backend.integrations.webhooks.utils
import backend.util.service
@@ -92,6 +97,8 @@ async def lifespan_context(app: fastapi.FastAPI):
verify_auth_settings()
await backend.data.db.connect()
# Eager connect to fail-fast if Redis is unreachable.
await backend.data.redis_client.get_redis_async()
# Configure thread pool for FastAPI sync operation performance
# CRITICAL: FastAPI automatically runs ALL sync functions in this thread pool:
@@ -143,7 +150,18 @@ async def lifespan_context(app: fastapi.FastAPI):
except Exception as e:
logger.warning(f"Error shutting down workspace storage: {e}")
await backend.data.db.disconnect()
# Each cleanup is wrapped so one failure doesn't block the rest. The
# Redis close in particular silences asyncio's "Unclosed ClusterNode"
# GC warning at interpreter shutdown.
try:
await backend.data.redis_client.disconnect_async()
except Exception:
logger.warning("redis_client.disconnect_async failed", exc_info=True)
try:
await backend.data.db.disconnect()
except Exception:
logger.warning("db.disconnect failed", exc_info=True)
def custom_generate_unique_id(route: APIRoute):
@@ -319,6 +337,11 @@ app.include_router(
tags=["v2", "admin"],
prefix="/api/credits",
)
app.include_router(
backend.api.features.admin.diagnostics_admin_routes.router,
tags=["v2", "admin"],
prefix="/api",
)
app.include_router(
backend.api.features.admin.execution_analytics_routes.router,
tags=["v2", "admin"],
@@ -329,6 +352,11 @@ app.include_router(
tags=["v2", "admin"],
prefix="/api/copilot",
)
app.include_router(
backend.api.features.admin.platform_cost_routes.router,
tags=["v2", "admin"],
prefix="/api/admin",
)
app.include_router(
backend.api.features.executions.review.routes.router,
tags=["v2", "executions", "review"],
@@ -366,6 +394,16 @@ app.include_router(
tags=["oauth"],
prefix="/api/oauth",
)
app.include_router(
push_routes.router,
tags=["push"],
prefix="/api/push",
)
app.include_router(
backend.api.features.platform_linking.routes.router,
tags=["platform-linking"],
prefix="/api/platform-linking",
)
app.mount("/external-api", external_api)

View File

@@ -1,4 +1,3 @@
import asyncio
import logging
from contextlib import asynccontextmanager
from typing import Protocol
@@ -17,14 +16,12 @@ from backend.api.model import (
WSSubscribeGraphExecutionsRequest,
)
from backend.api.utils.cors import build_cors_params
from backend.data.execution import AsyncRedisExecutionEventBus
from backend.data.notification_bus import AsyncRedisNotificationEventBus
from backend.data import db, redis_client
from backend.data.user import DEFAULT_USER_ID
from backend.monitoring.instrumentation import (
instrument_fastapi,
update_websocket_connections,
)
from backend.util.retry import continuous_retry
from backend.util.service import AppProcess
from backend.util.settings import AppEnvironment, Config, Settings
@@ -34,10 +31,24 @@ settings = Settings()
@asynccontextmanager
async def lifespan(app: FastAPI):
manager = get_connection_manager()
fut = asyncio.create_task(event_broadcaster(manager))
fut.add_done_callback(lambda _: logger.info("Event broadcaster stopped"))
yield
# Prisma is needed to resolve graph_id from graph_exec_id on subscribe.
await db.connect()
# Eager connect to fail-fast if Redis is unreachable.
await redis_client.get_redis_async()
try:
yield
finally:
# Each cleanup is wrapped so one failure doesn't block the rest. The
# Redis close silences asyncio's "Unclosed ClusterNode" GC warning at
# interpreter shutdown.
try:
await redis_client.disconnect_async()
except Exception:
logger.warning("redis_client.disconnect_async failed", exc_info=True)
try:
await db.disconnect()
except Exception:
logger.warning("db.disconnect failed", exc_info=True)
docs_url = "/docs" if settings.config.app_env == AppEnvironment.LOCAL else None
@@ -61,31 +72,6 @@ def get_connection_manager():
return _connection_manager
@continuous_retry()
async def event_broadcaster(manager: ConnectionManager):
execution_bus = AsyncRedisExecutionEventBus()
notification_bus = AsyncRedisNotificationEventBus()
try:
async def execution_worker():
async for event in execution_bus.listen("*"):
await manager.send_execution_update(event)
async def notification_worker():
async for notification in notification_bus.listen("*"):
await manager.send_notification(
user_id=notification.user_id,
payload=notification.payload,
)
await asyncio.gather(execution_worker(), notification_worker())
finally:
# Ensure PubSub connections are closed on any exit to prevent leaks
await execution_bus.close()
await notification_bus.close()
async def authenticate_websocket(websocket: WebSocket) -> str:
if not settings.config.enable_auth:
return DEFAULT_USER_ID
@@ -297,6 +283,21 @@ async def websocket_router(
).model_dump_json()
)
continue
except ValueError as e:
logger.warning(
"Subscription rejected for user #%s on '%s': %s",
user_id,
message.method.value,
e,
)
await websocket.send_text(
WSMessage(
method=WSMethod.ERROR,
success=False,
error=str(e),
).model_dump_json()
)
continue
except Exception as e:
logger.error(
f"Error while handling '{message.method.value}' message "
@@ -321,9 +322,13 @@ async def websocket_router(
)
except WebSocketDisconnect:
manager.disconnect_socket(websocket, user_id=user_id)
logger.debug("WebSocket client disconnected")
except Exception:
logger.exception(f"Unexpected error in websocket_router for user #{user_id}")
finally:
# Always release subscription pumps + Redis connections, regardless of how
# the loop exited — otherwise non-WebSocketDisconnect failures leak both.
await manager.disconnect_socket(websocket, user_id=user_id)
update_websocket_connections(user_id, -1)

View File

@@ -44,9 +44,12 @@ def test_websocket_server_uses_cors_helper(mocker) -> None:
"backend.api.ws_api.build_cors_params", return_value=cors_params
)
with override_config(
settings, "backend_cors_allow_origins", cors_params["allow_origins"]
), override_config(settings, "app_env", AppEnvironment.LOCAL):
with (
override_config(
settings, "backend_cors_allow_origins", cors_params["allow_origins"]
),
override_config(settings, "app_env", AppEnvironment.LOCAL),
):
WebsocketServer().run()
build_cors.assert_called_once_with(
@@ -65,9 +68,12 @@ def test_websocket_server_uses_cors_helper(mocker) -> None:
def test_websocket_server_blocks_localhost_in_production(mocker) -> None:
mocker.patch("backend.api.ws_api.uvicorn.run")
with override_config(
settings, "backend_cors_allow_origins", ["http://localhost:3000"]
), override_config(settings, "app_env", AppEnvironment.PRODUCTION):
with (
override_config(
settings, "backend_cors_allow_origins", ["http://localhost:3000"]
),
override_config(settings, "app_env", AppEnvironment.PRODUCTION),
):
with pytest.raises(ValueError):
WebsocketServer().run()
@@ -290,7 +296,232 @@ async def test_handle_unsubscribe_missing_data(
message=message,
)
mock_manager._unsubscribe.assert_not_called()
mock_manager.unsubscribe_graph_exec.assert_not_called()
mock_websocket.send_text.assert_called_once()
assert '"method":"error"' in mock_websocket.send_text.call_args[0][0]
assert '"success":false' in mock_websocket.send_text.call_args[0][0]
# ---------- Per-graph subscribe branch ----------
@pytest.mark.asyncio
async def test_handle_subscribe_graph_execs_branch(
mock_websocket: AsyncMock, mock_manager: AsyncMock
) -> None:
"""The SUBSCRIBE_GRAPH_EXECS branch must route to subscribe_graph_execs,
not subscribe_graph_exec — regression guard for the aggregate channel."""
message = WSMessage(
method=WSMethod.SUBSCRIBE_GRAPH_EXECS,
data={"graph_id": "graph-abc"},
)
mock_manager.subscribe_graph_execs.return_value = (
"user-1|graph#graph-abc|executions"
)
await handle_subscribe(
connection_manager=cast(ConnectionManager, mock_manager),
websocket=cast(WebSocket, mock_websocket),
user_id="user-1",
message=message,
)
mock_manager.subscribe_graph_execs.assert_called_once_with(
user_id="user-1",
graph_id="graph-abc",
websocket=mock_websocket,
)
mock_manager.subscribe_graph_exec.assert_not_called()
mock_websocket.send_text.assert_called_once()
assert (
'"method":"subscribe_graph_executions"'
in mock_websocket.send_text.call_args[0][0]
)
assert '"success":true' in mock_websocket.send_text.call_args[0][0]
@pytest.mark.asyncio
async def test_handle_subscribe_rejects_unrelated_method(
mock_websocket: AsyncMock, mock_manager: AsyncMock
) -> None:
"""handle_subscribe must raise for methods that aren't SUBSCRIBE_*."""
import pytest as _pytest
message = WSMessage(
method=WSMethod.HEARTBEAT,
data={"graph_exec_id": "x"},
)
with _pytest.raises(ValueError):
await handle_subscribe(
connection_manager=cast(ConnectionManager, mock_manager),
websocket=cast(WebSocket, mock_websocket),
user_id="user-1",
message=message,
)
# ---------- authenticate_websocket branches ----------
@pytest.mark.asyncio
async def test_authenticate_websocket_missing_token_closes_4001(mocker) -> None:
from backend.api.ws_api import authenticate_websocket
mocker.patch.object(settings.config, "enable_auth", True)
ws = AsyncMock(spec=WebSocket)
ws.query_params = {}
user_id = await authenticate_websocket(ws)
ws.close.assert_awaited_once()
assert ws.close.call_args.kwargs["code"] == 4001
assert user_id == ""
@pytest.mark.asyncio
async def test_authenticate_websocket_invalid_token_closes_4003(mocker) -> None:
from backend.api.ws_api import authenticate_websocket
mocker.patch.object(settings.config, "enable_auth", True)
mocker.patch(
"backend.api.ws_api.parse_jwt_token", side_effect=ValueError("bad token")
)
ws = AsyncMock(spec=WebSocket)
ws.query_params = {"token": "abc"}
user_id = await authenticate_websocket(ws)
ws.close.assert_awaited_once()
assert ws.close.call_args.kwargs["code"] == 4003
assert user_id == ""
@pytest.mark.asyncio
async def test_authenticate_websocket_missing_sub_closes_4002(mocker) -> None:
from backend.api.ws_api import authenticate_websocket
mocker.patch.object(settings.config, "enable_auth", True)
mocker.patch("backend.api.ws_api.parse_jwt_token", return_value={"not_sub": "x"})
ws = AsyncMock(spec=WebSocket)
ws.query_params = {"token": "abc"}
user_id = await authenticate_websocket(ws)
ws.close.assert_awaited_once()
assert ws.close.call_args.kwargs["code"] == 4002
assert user_id == ""
@pytest.mark.asyncio
async def test_authenticate_websocket_happy_path_returns_sub(mocker) -> None:
from backend.api.ws_api import authenticate_websocket
mocker.patch.object(settings.config, "enable_auth", True)
mocker.patch("backend.api.ws_api.parse_jwt_token", return_value={"sub": "user-X"})
ws = AsyncMock(spec=WebSocket)
ws.query_params = {"token": "abc"}
user_id = await authenticate_websocket(ws)
assert user_id == "user-X"
@pytest.mark.asyncio
async def test_authenticate_websocket_auth_disabled_returns_default(mocker) -> None:
from backend.api.ws_api import authenticate_websocket
mocker.patch.object(settings.config, "enable_auth", False)
ws = AsyncMock(spec=WebSocket)
ws.query_params = {}
user_id = await authenticate_websocket(ws)
assert user_id == DEFAULT_USER_ID
# ---------- get_connection_manager singleton ----------
def test_get_connection_manager_singleton() -> None:
"""Repeated calls must return the same ConnectionManager — the WS router
depends on a single process-wide subscription table."""
import backend.api.ws_api as ws_api
ws_api._connection_manager = None
a = ws_api.get_connection_manager()
b = ws_api.get_connection_manager()
assert a is b
assert isinstance(a, ConnectionManager)
# ---------- Lifespan: Prisma connect/disconnect ----------
@pytest.mark.asyncio
async def test_lifespan_connects_and_disconnects_prisma(mocker) -> None:
"""Lifespan must both connect() and disconnect() db — the subscribe path
resolves graph_id via Prisma so a missing connect() is the regression bug."""
from fastapi import FastAPI
from backend.api.ws_api import lifespan
mock_db = mocker.patch("backend.api.ws_api.db")
mock_db.connect = AsyncMock()
mock_db.disconnect = AsyncMock()
dummy_app = FastAPI()
async with lifespan(dummy_app):
mock_db.connect.assert_awaited_once()
mock_db.disconnect.assert_not_called()
mock_db.disconnect.assert_awaited_once()
@pytest.mark.asyncio
async def test_lifespan_still_disconnects_on_exception(mocker) -> None:
"""If the app raises inside the yield, Prisma must still disconnect."""
from fastapi import FastAPI
from backend.api.ws_api import lifespan
mock_db = mocker.patch("backend.api.ws_api.db")
mock_db.connect = AsyncMock()
mock_db.disconnect = AsyncMock()
dummy_app = FastAPI()
class _Boom(Exception):
pass
with pytest.raises(_Boom):
async with lifespan(dummy_app):
raise _Boom()
mock_db.disconnect.assert_awaited_once()
# ---------- Health endpoint ----------
def test_health_endpoint_returns_ok() -> None:
# TestClient triggers lifespan — stub it out so Prisma isn't hit.
from contextlib import asynccontextmanager
from fastapi.testclient import TestClient
import backend.api.ws_api as ws_api
@asynccontextmanager
async def _noop_lifespan(app):
yield
# Replace the app-level lifespan temporarily.
real_router_lifespan = ws_api.app.router.lifespan_context
ws_api.app.router.lifespan_context = _noop_lifespan
try:
with TestClient(ws_api.app) as client:
r = client.get("/")
assert r.status_code == 200
assert r.json() == {"status": "healthy"}
finally:
ws_api.app.router.lifespan_context = real_router_lifespan

View File

@@ -38,19 +38,23 @@ def main(**kwargs):
from backend.api.rest_api import AgentServer
from backend.api.ws_api import WebsocketServer
from backend.copilot.bot.app import CoPilotChatBridge
from backend.copilot.executor.manager import CoPilotExecutor
from backend.data.db_manager import DatabaseManager
from backend.executor import ExecutionManager, Scheduler
from backend.notifications import NotificationManager
from backend.platform_linking.manager import PlatformLinkingManager
run_processes(
DatabaseManager().set_log_level("warning"),
Scheduler(),
NotificationManager(),
PlatformLinkingManager(),
WebsocketServer(),
AgentServer(),
ExecutionManager(),
CoPilotExecutor(),
CoPilotChatBridge(),
**kwargs,
)

View File

@@ -25,6 +25,7 @@ from backend.data.model import (
Credentials,
CredentialsFieldInfo,
CredentialsMetaInput,
NodeExecutionStats,
SchemaField,
is_credentials_field_name,
)
@@ -43,7 +44,7 @@ logger = logging.getLogger(__name__)
if TYPE_CHECKING:
from backend.data.execution import ExecutionContext
from backend.data.model import ContributorDetails, NodeExecutionStats
from backend.data.model import ContributorDetails
from ..data.graph import Link
@@ -95,27 +96,64 @@ class BlockCategory(Enum):
class BlockCostType(str, Enum):
RUN = "run" # cost X credits per run
BYTE = "byte" # cost X credits per byte
SECOND = "second" # cost X credits per second
# RUN : cost_amount credits per run.
# BYTE : cost_amount credits per byte of input data.
# SECOND : cost_amount credits per cost_divisor walltime seconds.
# ITEMS : cost_amount credits per cost_divisor items (from stats).
# COST_USD : cost_amount credits per USD of stats.provider_cost.
# TOKENS : per-(model, provider) rate table lookup; see TOKEN_COST.
RUN = "run"
BYTE = "byte"
SECOND = "second"
ITEMS = "items"
COST_USD = "cost_usd"
TOKENS = "tokens"
@property
def is_dynamic(self) -> bool:
"""Real charge is computed post-flight from stats.
Dynamic types (SECOND/ITEMS/COST_USD/TOKENS) return 0 pre-flight and
settle against stats via charge_reconciled_usage once the block runs.
"""
return self in _DYNAMIC_COST_TYPES
_DYNAMIC_COST_TYPES: frozenset[BlockCostType] = frozenset(
{
BlockCostType.SECOND,
BlockCostType.ITEMS,
BlockCostType.COST_USD,
BlockCostType.TOKENS,
}
)
class BlockCost(BaseModel):
cost_amount: int
cost_filter: BlockInput
cost_type: BlockCostType
# cost_divisor: interpret cost_amount as "credits per cost_divisor units".
# Only meaningful for SECOND / ITEMS. TOKENS routes through TOKEN_COST
# rate tables (per-model input/output/cache pricing) and ignores
# cost_divisor entirely. Defaults to 1 so existing RUN/BYTE entries stay
# point-wise. Example: cost_amount=1, cost_divisor=10 under SECOND means
# "1 credit per 10 seconds of walltime".
cost_divisor: int = 1
def __init__(
self,
cost_amount: int,
cost_type: BlockCostType = BlockCostType.RUN,
cost_filter: Optional[BlockInput] = None,
cost_divisor: int = 1,
**data: Any,
) -> None:
super().__init__(
cost_amount=cost_amount,
cost_filter=cost_filter or {},
cost_type=cost_type,
cost_divisor=max(1, cost_divisor),
**data,
)
@@ -167,9 +205,31 @@ class BlockSchema(BaseModel):
return cls.cached_jsonschema
@classmethod
def validate_data(cls, data: BlockInput) -> str | None:
def validate_data(
cls,
data: BlockInput,
exclude_fields: set[str] | None = None,
) -> str | None:
schema = cls.jsonschema()
if exclude_fields:
# Drop the excluded fields from both the properties and the
# ``required`` list so jsonschema doesn't flag them as missing.
# Used by the dry-run path to skip credentials validation while
# still validating the remaining block inputs.
schema = {
**schema,
"properties": {
k: v
for k, v in schema.get("properties", {}).items()
if k not in exclude_fields
},
"required": [
r for r in schema.get("required", []) if r not in exclude_fields
],
}
data = {k: v for k, v in data.items() if k not in exclude_fields}
return json.validate_with_jsonschema(
schema=cls.jsonschema(),
schema=schema,
data={k: v for k, v in data.items() if v is not None},
)
@@ -310,6 +370,8 @@ class BlockSchema(BaseModel):
"credentials_provider": [config.get("provider", "google")],
"credentials_types": [config.get("type", "oauth2")],
"credentials_scopes": config.get("scopes"),
"is_auto_credential": True,
"input_field_name": info["field_name"],
}
result[kwarg_name] = CredentialsFieldInfo.model_validate(
auto_schema, by_alias=True
@@ -455,8 +517,6 @@ class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
disabled: If the block is disabled, it will not be available for execution.
static_output: Whether the output links of the block are static by default.
"""
from backend.data.model import NodeExecutionStats
self.id = id
self.input_schema = input_schema
self.output_schema = output_schema
@@ -474,7 +534,7 @@ class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
self.is_sensitive_action = is_sensitive_action
# Read from ClassVar set by initialize_blocks()
self.optimized_description: str | None = type(self)._optimized_description
self.execution_stats: "NodeExecutionStats" = NodeExecutionStats()
self.execution_stats: NodeExecutionStats = NodeExecutionStats()
if self.webhook_config:
if isinstance(self.webhook_config, BlockWebhookConfig):
@@ -554,7 +614,7 @@ class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
return data
raise ValueError(f"{self.name} did not produce any output for {output}")
def merge_stats(self, stats: "NodeExecutionStats") -> "NodeExecutionStats":
def merge_stats(self, stats: NodeExecutionStats) -> NodeExecutionStats:
self.execution_stats += stats
return self.execution_stats
@@ -698,13 +758,90 @@ class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
if should_pause:
return
# Validate the input data (original or reviewer-modified) once
if error := self.input_schema.validate_data(input_data):
raise BlockInputError(
message=f"Unable to execute block with invalid input data: {error}",
block_name=self.name,
block_id=self.id,
)
# Validate the input data (original or reviewer-modified) once.
# In dry-run mode, credential fields may contain sentinel None values
# that would fail JSON schema required checks. We still validate the
# non-credential fields so blocks that execute for real during dry-run
# (e.g. AgentExecutorBlock) get proper input validation.
is_dry_run = getattr(kwargs.get("execution_context"), "dry_run", False)
if is_dry_run:
# Credential fields may be absent (LLM-built agents often skip
# wiring them) or nullified earlier in the pipeline. Validate
# the non-credential inputs against a schema with those fields
# excluded — stripping only the data while keeping them in the
# ``required`` list would falsely report ``'credentials' is a
# required property``.
cred_field_names = set(self.input_schema.get_credentials_fields().keys())
if error := self.input_schema.validate_data(
input_data, exclude_fields=cred_field_names
):
raise BlockInputError(
message=f"Unable to execute block with invalid input data: {error}",
block_name=self.name,
block_id=self.id,
)
else:
if error := self.input_schema.validate_data(input_data):
raise BlockInputError(
message=f"Unable to execute block with invalid input data: {error}",
block_name=self.name,
block_id=self.id,
)
# Ensure auto-credential kwargs are present before we hand off to
# run(). A missing auto-credential means the upstream field (e.g.
# a Google Drive picker) didn't embed a _credentials_id, or the
# executor couldn't resolve it. Without this guard, run() would
# crash with a TypeError (missing required kwarg) or an opaque
# AttributeError deep inside the provider SDK.
#
# Only raise when the field is ALSO not populated in input_data.
# ``_acquire_auto_credentials`` intentionally skips setting the
# kwarg in two legitimate cases — ``_credentials_id`` is ``None``
# (chained from upstream) or the field is missing from
# ``input_data`` at prep time (connected from upstream block).
# In both cases the upstream block is expected to populate the
# field value by execute time; raising here would break the
# documented ``AgentGoogleDriveFileInputBlock`` chaining pattern.
# Dry-run skips because the executor intentionally runs blocks
# without resolved creds for schema validation.
if not is_dry_run:
for (
kwarg_name,
info,
) in self.input_schema.get_auto_credentials_fields().items():
kwargs.setdefault(kwarg_name, None)
if kwargs[kwarg_name] is not None:
continue
# Upstream-chained pattern: the field was populated by a
# prior node (e.g. AgentGoogleDriveFileInputBlock) whose
# output carries a resolved ``_credentials_id``.
# ``_acquire_auto_credentials`` deliberately doesn't set
# the kwarg in that case because the value isn't available
# at prep time; the executor fills it in before we reach
# ``_execute``. Trust it if the ``_credentials_id`` KEY
# is present — its value may be explicitly ``None`` in
# the chained case (see sentry thread
# PRRT_kwDOJKSTjM58sJfA). Checking truthiness here would
# falsely preempt run() for every valid chained graph
# that ships ``_credentials_id=None`` in the picker
# object. Mirror ``_acquire_auto_credentials``'s own
# skip rule, which treats ``cred_id is None`` as a
# chained-skip signal.
field_name = info["field_name"]
field_value = input_data.get(field_name)
if isinstance(field_value, dict) and "_credentials_id" in field_value:
continue
raise BlockExecutionError(
message=(
f"Missing credentials for '{kwarg_name}'. "
"Select a file via the picker (which carries "
"its credentials), or connect credentials for "
"this block."
),
block_name=self.name,
block_id=self.id,
)
# Use the validated input data
async for output_name, output_data in self.run(

View File

@@ -0,0 +1,56 @@
"""Provider descriptions for services that don't yet have their own ``_config.py``.
Every provider in ``_STATIC_PROVIDER_CONFIGS`` below is declared here because
its block code currently lives either in a single shared file (e.g. the 8 LLM
providers in ``blocks/llm.py``) or in a single-file block that has no dedicated
directory (e.g. ``blocks/reddit.py``).
This file gets loaded by the block auto-loader in ``blocks/__init__.py``
(``rglob("*.py")`` picks it up) so the ``ProviderBuilder(...).build()`` calls
run at startup and populate ``AutoRegistry`` before the first API request.
**Migration path:** when a provider graduates into its own directory with a
proper ``_config.py`` (following the SDK pattern, e.g. ``blocks/linear/_config.py``),
delete its entry here. The metadata will still be served by
``GET /integrations/providers`` — it just moves to live next to the provider's
auth and webhook config.
"""
from backend.data.model import CredentialsType
from backend.sdk import ProviderBuilder
_STATIC_PROVIDER_CONFIGS: dict[str, tuple[str, tuple[CredentialsType, ...]]] = {
# LLM providers that share blocks/llm.py
"aiml_api": ("Unified access to 100+ AI models", ("api_key",)),
"anthropic": ("Claude language models", ("api_key",)),
"groq": ("Fast LLM inference", ("api_key",)),
"llama_api": ("Llama model hosting", ("api_key",)),
"ollama": ("Run open-source LLMs locally", ("api_key",)),
"open_router": ("One API for every LLM", ("api_key",)),
"openai": ("GPT models and embeddings", ("api_key",)),
"v0": ("AI-generated UI components", ("api_key",)),
# Single-file providers (one provider per standalone blocks/*.py file)
"d_id": ("AI avatar and video generation", ("api_key",)),
"e2b": ("Sandboxed code execution", ("api_key",)),
"google_maps": ("Places, directions, geocoding", ("api_key",)),
"http": ("Generic HTTP requests", ("api_key", "host_scoped")),
"ideogram": ("Text-to-image generation", ("api_key",)),
"medium": ("Publish stories and posts", ("api_key",)),
"mem0": ("Long-term memory for agents", ("api_key",)),
"openweathermap": ("Weather data and forecasts", ("api_key",)),
"pinecone": ("Managed vector database", ("api_key",)),
"reddit": ("Subreddits, posts, and comments", ("oauth2",)),
"revid": ("AI-generated short-form video", ("api_key",)),
"screenshotone": ("Automated website screenshots", ("api_key",)),
"smtp": ("Send email via SMTP", ("user_password",)),
"unreal_speech": ("Low-cost text-to-speech", ("api_key",)),
"webshare_proxy": ("Rotating proxies for scraping", ("api_key",)),
}
for _name, (_description, _auth_types) in _STATIC_PROVIDER_CONFIGS.items():
(
ProviderBuilder(_name)
.with_description(_description)
.with_supported_auth_types(*_auth_types)
.build()
)

View File

@@ -49,11 +49,17 @@ class AgentExecutorBlock(Block):
@classmethod
def get_missing_input(cls, data: BlockInput) -> set[str]:
required_fields = cls.get_input_schema(data).get("required", [])
return set(required_fields) - set(data)
# Check against the nested `inputs` dict, not the top-level node
# data — required fields like "topic" live inside data["inputs"],
# not at data["topic"].
provided = data.get("inputs", {})
return set(required_fields) - set(provided)
@classmethod
def get_mismatch_error(cls, data: BlockInput) -> str | None:
return validate_with_jsonschema(cls.get_input_schema(data), data)
return validate_with_jsonschema(
cls.get_input_schema(data), data.get("inputs", {})
)
class Output(BlockSchema):
# Use BlockSchema to avoid automatic error field that could clash with graph outputs
@@ -88,6 +94,7 @@ class AgentExecutorBlock(Block):
execution_context=execution_context.model_copy(
update={"parent_execution_id": graph_exec_id},
),
dry_run=execution_context.dry_run,
)
logger = execution_utils.LogMetadata(
@@ -149,17 +156,25 @@ class AgentExecutorBlock(Block):
ExecutionStatus.TERMINATED,
ExecutionStatus.FAILED,
]:
logger.debug(
f"Execution {log_id} received event {event.event_type} with status {event.status}"
logger.info(
f"Execution {log_id} skipping event {event.event_type} status={event.status} "
f"node={getattr(event, 'node_exec_id', '?')}"
)
continue
if event.event_type == ExecutionEventType.GRAPH_EXEC_UPDATE:
# If the graph execution is COMPLETED, TERMINATED, or FAILED,
# we can stop listening for further events.
logger.info(
f"Execution {log_id} graph completed with status {event.status}, "
f"yielded {len(yielded_node_exec_ids)} outputs"
)
self.merge_stats(
NodeExecutionStats(
extra_cost=event.stats.cost if event.stats else 0,
# Sub-graph already debited each of its own nodes; we
# roll up its total so graph_stats.cost reflects the
# full sub-graph spend.
reconciled_cost_delta=(event.stats.cost if event.stats else 0),
extra_steps=event.stats.node_exec_count if event.stats else 0,
)
)

View File

@@ -4,11 +4,17 @@ Shared configuration for all AgentMail blocks.
from agentmail import AsyncAgentMail
from backend.sdk import APIKeyCredentials, ProviderBuilder, SecretStr
from backend.sdk import APIKeyCredentials, BlockCostType, ProviderBuilder, SecretStr
# AgentMail is in beta with no published paid tier yet, but ~37 blocks
# without any BLOCK_COSTS entry means they currently execute wallet-free.
# 1 cr/call is a conservative interim floor so no AgentMail work leaks
# past billing. Revisit once AgentMail publishes usage-based pricing.
agent_mail = (
ProviderBuilder("agent_mail")
.with_description("Managed email accounts for agents")
.with_api_key("AGENTMAIL_API_KEY", "AgentMail API Key")
.with_base_cost(1, BlockCostType.RUN)
.build()
)

View File

@@ -207,6 +207,9 @@ class AIConditionBlock(AIBlockBase):
NodeExecutionStats(
input_token_count=response.prompt_tokens,
output_token_count=response.completion_tokens,
cache_read_token_count=response.cache_read_tokens,
cache_creation_token_count=response.cache_creation_tokens,
provider_cost=response.provider_cost,
)
)
self.prompt = response.prompt

View File

@@ -47,7 +47,13 @@ def _make_input(**overrides) -> AIConditionBlock.Input:
return AIConditionBlock.Input(**defaults)
def _mock_llm_response(response_text: str) -> LLMResponse:
def _mock_llm_response(
response_text: str,
*,
cache_read_tokens: int = 0,
cache_creation_tokens: int = 0,
provider_cost: float | None = None,
) -> LLMResponse:
return LLMResponse(
raw_response="",
prompt=[],
@@ -56,6 +62,9 @@ def _mock_llm_response(response_text: str) -> LLMResponse:
prompt_tokens=10,
completion_tokens=5,
reasoning=None,
cache_read_tokens=cache_read_tokens,
cache_creation_tokens=cache_creation_tokens,
provider_cost=provider_cost,
)
@@ -145,3 +154,35 @@ class TestExceptionPropagation:
input_data = _make_input()
with pytest.raises(RuntimeError, match="LLM provider error"):
await _collect_outputs(block, input_data, credentials=TEST_CREDENTIALS)
# ---------------------------------------------------------------------------
# Regression: cache tokens and provider_cost must be propagated to stats
# ---------------------------------------------------------------------------
class TestCacheTokenPropagation:
@pytest.mark.asyncio
async def test_cache_tokens_propagated_to_stats(
self, monkeypatch: pytest.MonkeyPatch
):
"""cache_read_tokens and cache_creation_tokens must be forwarded to
NodeExecutionStats so that usage dashboards count cached tokens."""
block = AIConditionBlock()
async def spy_llm(**kwargs):
return _mock_llm_response(
"true",
cache_read_tokens=7,
cache_creation_tokens=3,
provider_cost=0.0012,
)
monkeypatch.setattr(block, "llm_call", spy_llm)
input_data = _make_input()
await _collect_outputs(block, input_data, credentials=TEST_CREDENTIALS)
assert block.execution_stats.cache_read_token_count == 7
assert block.execution_stats.cache_creation_token_count == 3
assert block.execution_stats.provider_cost == 0.0012

View File

@@ -10,6 +10,7 @@ from ._webhook import AirtableWebhookManager
# Configure the Airtable provider with API key authentication
airtable = (
ProviderBuilder("airtable")
.with_description("Bases, tables, and records")
.with_api_key("AIRTABLE_API_KEY", "Airtable Personal Access Token")
.with_webhook_manager(AirtableWebhookManager)
.with_base_cost(1, BlockCostType.RUN)

View File

@@ -0,0 +1,15 @@
"""Provider registration for Apollo.
Registers the provider description shown in the settings integrations UI.
Apollo doesn't use a full :class:`ProviderBuilder` chain (auth is set up in
``_auth.py``), so this file only declares metadata.
"""
from backend.sdk import ProviderBuilder
apollo = (
ProviderBuilder("apollo")
.with_description("Sales intelligence and prospecting")
.with_supported_auth_types("api_key")
.build()
)

View File

@@ -17,7 +17,7 @@ from backend.blocks.apollo.models import (
PrimaryPhone,
SearchOrganizationsRequest,
)
from backend.data.model import CredentialsField, SchemaField
from backend.data.model import CredentialsField, NodeExecutionStats, SchemaField
class SearchOrganizationsBlock(Block):
@@ -218,6 +218,11 @@ To find IDs, identify the values for organization_id when you call this endpoint
) -> BlockOutput:
query = SearchOrganizationsRequest(**input_data.model_dump())
organizations = await self.search_organizations(query, credentials)
self.merge_stats(
NodeExecutionStats(
provider_cost=float(len(organizations)), provider_cost_type="items"
)
)
for organization in organizations:
yield "organization", organization
yield "organizations", organizations

View File

@@ -21,7 +21,7 @@ from backend.blocks.apollo.models import (
SearchPeopleRequest,
SenorityLevels,
)
from backend.data.model import CredentialsField, SchemaField
from backend.data.model import CredentialsField, NodeExecutionStats, SchemaField
class SearchPeopleBlock(Block):
@@ -366,4 +366,9 @@ class SearchPeopleBlock(Block):
*(enrich_or_fallback(person) for person in people)
)
self.merge_stats(
NodeExecutionStats(
provider_cost=float(len(people)), provider_cost_type="items"
)
)
yield "people", people

View File

@@ -4,8 +4,10 @@ import asyncio
import contextvars
import json
import logging
import uuid
from typing import TYPE_CHECKING, Any
from pydantic import field_validator
from typing_extensions import TypedDict # Needed for Python <3.12 compatibility
from backend.blocks._base import (
@@ -16,12 +18,14 @@ from backend.blocks._base import (
BlockSchemaOutput,
)
from backend.copilot.permissions import (
DISABLED_LEGACY_TOOL_NAMES,
CopilotPermissions,
ToolName,
all_known_tool_names,
validate_block_identifiers,
)
from backend.data.model import SchemaField
from backend.util.exceptions import BlockExecutionError
if TYPE_CHECKING:
from backend.data.execution import ExecutionContext
@@ -31,6 +35,37 @@ logger = logging.getLogger(__name__)
# Block ID shared between autopilot.py and copilot prompting.py.
AUTOPILOT_BLOCK_ID = "c069dc6b-c3ed-4c12-b6e5-d47361e64ce6"
# Identifiers used when registering an AutoPilotBlock turn with the
# stream registry — distinguishes block-originated turns from sub-session
# or HTTP SSE turns in logs / observability.
_AUTOPILOT_TOOL_CALL_ID = "autopilot_block"
_AUTOPILOT_TOOL_NAME = "autopilot_block"
# Ceiling on how long AutoPilotBlock.execute_copilot will wait for the
# enqueued turn's terminal event. Graph blocks run synchronously from
# the caller's perspective so we wait effectively as long as needed; 6h
# matches the previous abandoned-task cap and is much longer than any
# legitimate AutoPilot turn.
_AUTOPILOT_BLOCK_MAX_WAIT_SECONDS = 6 * 60 * 60 # 6 hours
class SubAgentRecursionError(BlockExecutionError):
"""Raised when the AutoPilot sub-agent nesting depth limit is exceeded.
Inherits :class:`BlockExecutionError` — this is a known, handled
runtime failure at the block level (caller nested AutoPilotBlocks
beyond the configured limit). Surfaces with the block_name /
block_id the block framework expects, instead of being wrapped in
``BlockUnknownError``.
"""
def __init__(self, message: str) -> None:
super().__init__(
message=message,
block_name="AutoPilotBlock",
block_id=AUTOPILOT_BLOCK_ID,
)
class ToolCallEntry(TypedDict):
"""A single tool invocation record from an autopilot execution."""
@@ -165,6 +200,13 @@ class AutoPilotBlock(Block):
# timeouts internally; wrapping with asyncio.timeout corrupts the
# SDK's internal stream (see service.py CRITICAL comment).
@field_validator("tools", mode="before")
@classmethod
def strip_disabled_legacy_tools(cls, tools: Any) -> Any:
if not isinstance(tools, list):
return tools
return [tool for tool in tools if tool not in DISABLED_LEGACY_TOOL_NAMES]
class Output(BlockSchemaOutput):
"""Output schema for the AutoPilot block."""
@@ -263,11 +305,15 @@ class AutoPilotBlock(Block):
user_id: str,
permissions: "CopilotPermissions | None" = None,
) -> tuple[str, list[ToolCallEntry], str, str, TokenUsage]:
"""Invoke the copilot and collect all stream results.
"""Invoke the copilot on the copilot_executor queue and aggregate the
result.
Delegates to :func:`collect_copilot_response` — the shared helper that
consumes ``stream_chat_completion_sdk`` without wrapping it in an
``asyncio.timeout`` (the SDK manages its own heartbeat-based timeouts).
Delegates to :func:`run_copilot_turn_via_queue` — the shared
primitive used by ``run_sub_session`` too — which creates the
stream_registry meta record, enqueues the job, and waits on the
Redis stream for the terminal event. Any available
copilot_executor worker picks up the job, so this call survives
the graph-executor worker dying mid-turn (RabbitMQ redelivers).
Args:
prompt: The user task/instruction.
@@ -280,8 +326,8 @@ class AutoPilotBlock(Block):
Returns:
A tuple of (response_text, tool_calls, history_json, session_id, usage).
"""
from backend.copilot.sdk.collect import (
collect_copilot_response, # avoid circular import
from backend.copilot.sdk.session_waiter import (
run_copilot_turn_via_queue, # avoid circular import
)
tokens = _check_recursion(max_recursion_depth)
@@ -294,14 +340,35 @@ class AutoPilotBlock(Block):
if system_context:
effective_prompt = f"[System Context: {system_context}]\n\n{prompt}"
result = await collect_copilot_response(
outcome, result = await run_copilot_turn_via_queue(
session_id=session_id,
message=effective_prompt,
user_id=user_id,
message=effective_prompt,
# Graph block execution is synchronous from the caller's
# perspective — wait effectively as long as needed. The
# SDK enforces its own idle-based timeout inside the
# stream_registry pipeline.
timeout=_AUTOPILOT_BLOCK_MAX_WAIT_SECONDS,
permissions=effective_permissions,
tool_call_id=_AUTOPILOT_TOOL_CALL_ID,
tool_name=_AUTOPILOT_TOOL_NAME,
)
if outcome == "failed":
raise RuntimeError(
"AutoPilot turn failed — see the session's transcript"
)
if outcome == "running":
raise RuntimeError(
"AutoPilot turn did not complete within "
f"{_AUTOPILOT_BLOCK_MAX_WAIT_SECONDS}s — session "
f"{session_id}"
)
# Build a lightweight conversation summary from streamed data.
# Build a lightweight conversation summary from the aggregated data.
# When ``result.queued`` is True the prompt rode on an already-
# in-flight turn (``run_copilot_turn_via_queue`` queued it and
# waited on the existing turn's stream); the aggregated result
# is still valid, so the same rendering path applies.
turn_messages: list[dict[str, Any]] = [
{"role": "user", "content": effective_prompt},
]
@@ -310,7 +377,7 @@ class AutoPilotBlock(Block):
{
"role": "assistant",
"content": result.response_text,
"tool_calls": result.tool_calls,
"tool_calls": [tc.model_dump() for tc in result.tool_calls],
}
)
else:
@@ -321,11 +388,11 @@ class AutoPilotBlock(Block):
tool_calls: list[ToolCallEntry] = [
{
"tool_call_id": tc["tool_call_id"],
"tool_name": tc["tool_name"],
"input": tc["input"],
"output": tc["output"],
"success": tc["success"],
"tool_call_id": tc.tool_call_id,
"tool_name": tc.tool_name,
"input": tc.input,
"output": tc.output,
"success": tc.success,
}
for tc in result.tool_calls
]
@@ -383,7 +450,8 @@ class AutoPilotBlock(Block):
sid = input_data.session_id
if not sid:
sid = await self.create_session(
execution_context.user_id, dry_run=input_data.dry_run
execution_context.user_id,
dry_run=input_data.dry_run or execution_context.dry_run,
)
# NOTE: No asyncio.timeout() here — the SDK manages its own
@@ -409,8 +477,41 @@ class AutoPilotBlock(Block):
yield "session_id", sid
yield "error", "AutoPilot execution was cancelled."
raise
except SubAgentRecursionError as exc:
# Deliberate block — re-enqueueing would immediately hit the limit
# again, so skip recovery and just surface the error.
yield "session_id", sid
yield "error", str(exc)
except Exception as exc:
yield "session_id", sid
# Recovery enqueue must happen BEFORE yielding "error": the block
# framework (_base.execute) raises BlockExecutionError immediately
# when it sees ("error", ...) and stops consuming the generator,
# so any code after that yield is dead code in production.
effective_prompt = input_data.prompt
if input_data.system_context:
effective_prompt = (
f"[System Context: {input_data.system_context}]\n\n"
f"{input_data.prompt}"
)
try:
await _enqueue_for_recovery(
sid,
execution_context.user_id,
effective_prompt,
input_data.dry_run or execution_context.dry_run,
)
except asyncio.CancelledError:
# Task cancelled during recovery — still yield the error
# so the session_id + error pair is visible before re-raising.
yield "error", str(exc)
raise
except Exception:
logger.warning(
"AutoPilot session %s: recovery enqueue raised unexpectedly",
sid[:12],
exc_info=True,
)
yield "error", str(exc)
@@ -438,13 +539,13 @@ def _check_recursion(
when the caller exits to restore the previous depth.
Raises:
RuntimeError: If the current depth already meets or exceeds the limit.
SubAgentRecursionError: If the current depth already meets or exceeds the limit.
"""
current = _autopilot_recursion_depth.get()
inherited = _autopilot_recursion_limit.get()
limit = max_depth if inherited is None else min(inherited, max_depth)
if current >= limit:
raise RuntimeError(
raise SubAgentRecursionError(
f"AutoPilot recursion depth limit reached ({limit}). "
"The autopilot has called itself too many times."
)
@@ -535,3 +636,51 @@ def _merge_inherited_permissions(
# Return the token so the caller can restore the previous value in finally.
token = _inherited_permissions.set(merged)
return merged, token
# ---------------------------------------------------------------------------
# Recovery helpers
# ---------------------------------------------------------------------------
async def _enqueue_for_recovery(
session_id: str,
user_id: str,
message: str,
dry_run: bool,
) -> None:
"""Re-enqueue an orphaned sub-agent session so a fresh executor picks it up.
When ``execute_copilot`` raises an unexpected exception the sub-agent
session is left with ``last_role=user`` and no active consumer — identical
to the state that caused Toran's reports of silent sub-agents. Publishing
the original prompt back to the copilot queue lets the executor service
resume the session without manual intervention.
Skipped for dry-run sessions (no real consumers listen to the queue for
simulated sessions). Any failure to publish is logged and swallowed so
it never masks the original exception.
"""
if dry_run:
return
try:
from backend.copilot.executor.utils import ( # avoid circular import
enqueue_copilot_turn,
)
await asyncio.wait_for(
enqueue_copilot_turn(
session_id=session_id,
user_id=user_id,
message=message,
turn_id=str(uuid.uuid4()),
),
timeout=10,
)
logger.info("AutoPilot session %s enqueued for recovery", session_id[:12])
except Exception:
logger.warning(
"AutoPilot session %s: failed to enqueue for recovery",
session_id[:12],
exc_info=True,
)

View File

@@ -62,6 +62,14 @@ class TestBuildAndValidatePermissions:
with pytest.raises(ValidationError, match="not_a_real_tool"):
_make_input(tools=["not_a_real_tool"])
async def test_disabled_legacy_tool_is_accepted_and_removed(self):
inp = _make_input(tools=["ask_question", "run_block"])
result = await _build_and_validate_permissions(inp)
assert inp.tools == ["run_block"]
assert isinstance(result, CopilotPermissions)
assert result.tools == ["run_block"]
async def test_valid_block_name_accepted(self):
mock_block_cls = MagicMock()
mock_block_cls.return_value.name = "HTTP Request"

View File

@@ -0,0 +1,26 @@
"""Shared provider config for Ayrshare social-media blocks.
The "credential" exposed to blocks is the **per-user Ayrshare profile key**,
not the org-level ``AYRSHARE_API_KEY``. Profile keys are provisioned per
user by :class:`~backend.integrations.managed_providers.ayrshare.AyrshareManagedProvider`
and stored in the normal credentials list with ``is_managed=True``, so every
Ayrshare block fits the standard credential flow:
credentials: CredentialsMetaInput = ayrshare.credentials_field(...)
``run_block`` / ``resolve_block_credentials`` take care of the rest.
``with_managed_api_key()`` registers ``api_key`` as a supported auth type
without the env-var-backed default credential that ``with_api_key()`` would
create — the org-level ``AYRSHARE_API_KEY`` is the admin key and must never
reach a block as a "profile key".
"""
from backend.sdk import ProviderBuilder
ayrshare = (
ProviderBuilder("ayrshare")
.with_description("Post to every social network")
.with_managed_api_key()
.build()
)

View File

@@ -0,0 +1,18 @@
from backend.sdk import BlockCost, BlockCostType
# Ayrshare is a subscription proxy ($149/mo Business). Per-post credit charges
# prevent a single heavy user from absorbing the fixed cost and align with the
# upload cost of each post variant.
# cost_filter matches on input_data.is_video BEFORE run() executes, so the flag
# has to be correct at input-eval time. Video-only platforms (YouTube, Snapchat)
# override the base default to True; platforms that accept both (TikTok, etc.)
# rely on the caller setting is_video explicitly for accurate billing.
# First match wins in block_usage_cost, so list the video tier first.
AYRSHARE_POST_COSTS = (
BlockCost(
cost_amount=5, cost_type=BlockCostType.RUN, cost_filter={"is_video": True}
),
BlockCost(
cost_amount=2, cost_type=BlockCostType.RUN, cost_filter={"is_video": False}
),
)

View File

@@ -4,22 +4,25 @@ from typing import Optional
from pydantic import BaseModel, Field
from backend.blocks._base import BlockSchemaInput
from backend.data.model import SchemaField, UserIntegrations
from backend.data.model import CredentialsMetaInput, SchemaField
from backend.integrations.ayrshare import AyrshareClient
from backend.util.clients import get_database_manager_async_client
from backend.util.exceptions import MissingConfigError
async def get_profile_key(user_id: str):
user_integrations: UserIntegrations = (
await get_database_manager_async_client().get_user_integrations(user_id)
)
return user_integrations.managed_credentials.ayrshare_profile_key
from ._config import ayrshare
class BaseAyrshareInput(BlockSchemaInput):
"""Base input model for Ayrshare social media posts with common fields."""
credentials: CredentialsMetaInput = ayrshare.credentials_field(
description=(
"Ayrshare profile credential. AutoGPT provisions this managed "
"credential automatically — the user does not create it. After "
"it's in place, the user links each social account via the "
"Ayrshare SSO popup in the Builder."
),
)
post: str = SchemaField(
description="The post text to be published", default="", advanced=False
)
@@ -29,7 +32,9 @@ class BaseAyrshareInput(BlockSchemaInput):
advanced=False,
)
is_video: bool = SchemaField(
description="Whether the media is a video", default=False, advanced=True
description="Whether the media is a video. Set to True when uploading a video so billing applies the video tier.",
default=False,
advanced=True,
)
schedule_date: Optional[datetime] = SchemaField(
description="UTC datetime for scheduling (YYYY-MM-DDThh:mm:ssZ)",

View File

@@ -1,16 +1,20 @@
from backend.integrations.ayrshare import PostIds, PostResponse, SocialPlatform
from backend.sdk import (
APIKeyCredentials,
Block,
BlockCategory,
BlockOutput,
BlockSchemaOutput,
BlockType,
SchemaField,
cost,
)
from ._util import BaseAyrshareInput, create_ayrshare_client, get_profile_key
from ._cost import AYRSHARE_POST_COSTS
from ._util import BaseAyrshareInput, create_ayrshare_client
@cost(*AYRSHARE_POST_COSTS)
class PostToBlueskyBlock(Block):
"""Block for posting to Bluesky with Bluesky-specific options."""
@@ -57,16 +61,10 @@ class PostToBlueskyBlock(Block):
self,
input_data: "PostToBlueskyBlock.Input",
*,
user_id: str,
credentials: APIKeyCredentials,
**kwargs,
) -> BlockOutput:
"""Post to Bluesky with Bluesky-specific options."""
profile_key = await get_profile_key(user_id)
if not profile_key:
yield "error", "Please link a social account via Ayrshare"
return
client = create_ayrshare_client()
if not client:
yield "error", "Ayrshare integration is not configured. Please set up the AYRSHARE_API_KEY."
@@ -106,7 +104,7 @@ class PostToBlueskyBlock(Block):
random_media_url=input_data.random_media_url,
notes=input_data.notes,
bluesky_options=bluesky_options if bluesky_options else None,
profile_key=profile_key.get_secret_value(),
profile_key=credentials.api_key.get_secret_value(),
)
yield "post_result", response
if response.postIds:

View File

@@ -1,21 +1,20 @@
from backend.integrations.ayrshare import PostIds, PostResponse, SocialPlatform
from backend.sdk import (
APIKeyCredentials,
Block,
BlockCategory,
BlockOutput,
BlockSchemaOutput,
BlockType,
SchemaField,
cost,
)
from ._util import (
BaseAyrshareInput,
CarouselItem,
create_ayrshare_client,
get_profile_key,
)
from ._cost import AYRSHARE_POST_COSTS
from ._util import BaseAyrshareInput, CarouselItem, create_ayrshare_client
@cost(*AYRSHARE_POST_COSTS)
class PostToFacebookBlock(Block):
"""Block for posting to Facebook with Facebook-specific options."""
@@ -120,15 +119,10 @@ class PostToFacebookBlock(Block):
self,
input_data: "PostToFacebookBlock.Input",
*,
user_id: str,
credentials: APIKeyCredentials,
**kwargs,
) -> BlockOutput:
"""Post to Facebook with Facebook-specific options."""
profile_key = await get_profile_key(user_id)
if not profile_key:
yield "error", "Please link a social account via Ayrshare"
return
client = create_ayrshare_client()
if not client:
yield "error", "Ayrshare integration is not configured. Please set up the AYRSHARE_API_KEY."
@@ -204,7 +198,7 @@ class PostToFacebookBlock(Block):
random_media_url=input_data.random_media_url,
notes=input_data.notes,
facebook_options=facebook_options if facebook_options else None,
profile_key=profile_key.get_secret_value(),
profile_key=credentials.api_key.get_secret_value(),
)
yield "post_result", response
if response.postIds:

View File

@@ -1,16 +1,20 @@
from backend.integrations.ayrshare import PostIds, PostResponse, SocialPlatform
from backend.sdk import (
APIKeyCredentials,
Block,
BlockCategory,
BlockOutput,
BlockSchemaOutput,
BlockType,
SchemaField,
cost,
)
from ._util import BaseAyrshareInput, create_ayrshare_client, get_profile_key
from ._cost import AYRSHARE_POST_COSTS
from ._util import BaseAyrshareInput, create_ayrshare_client
@cost(*AYRSHARE_POST_COSTS)
class PostToGMBBlock(Block):
"""Block for posting to Google My Business with GMB-specific options."""
@@ -110,14 +114,13 @@ class PostToGMBBlock(Block):
)
async def run(
self, input_data: "PostToGMBBlock.Input", *, user_id: str, **kwargs
self,
input_data: "PostToGMBBlock.Input",
*,
credentials: APIKeyCredentials,
**kwargs
) -> BlockOutput:
"""Post to Google My Business with GMB-specific options."""
profile_key = await get_profile_key(user_id)
if not profile_key:
yield "error", "Please link a social account via Ayrshare"
return
client = create_ayrshare_client()
if not client:
yield "error", "Ayrshare integration is not configured. Please set up the AYRSHARE_API_KEY."
@@ -202,7 +205,7 @@ class PostToGMBBlock(Block):
random_media_url=input_data.random_media_url,
notes=input_data.notes,
gmb_options=gmb_options if gmb_options else None,
profile_key=profile_key.get_secret_value(),
profile_key=credentials.api_key.get_secret_value(),
)
yield "post_result", response
if response.postIds:

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