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347 Commits

Author SHA1 Message Date
Zamil Majdy
5cc72e7608 fix(backend): validate non-finite float in extract_openrouter_cost, restore UTILITIES comment
- Add math.isfinite() guard in extract_openrouter_cost so inf/nan header
  values are rejected instead of stored (Sentry finding)
- Add test cases for inf, -inf, and nan header values
- Restore the '# ------- UTILITIES ------- #' section separator in
  manager.py that was accidentally dropped during the drain-on-shutdown commit
2026-04-08 10:26:41 +07:00
Zamil Majdy
fa0650214d refactor(backend): extract shared _update_title_async to copilot/service.py
The function was duplicated in both baseline/service.py and sdk/service.py
with identical logic. Consolidate into the shared service module alongside
_generate_session_title which it wraps.
2026-04-08 10:14:29 +07:00
Zamil Majdy
3e016508d4 fix(backend): replace getattr/hasattr duck-typing with try/except in baseline cost extraction
Consistent with the pattern used in llm.extract_openrouter_cost():
use try/except (AttributeError, ValueError) instead of getattr(response, '_response', None)
+ hasattr(raw_resp, 'headers') so there is only one attribute-access pattern in the codebase.
2026-04-08 10:08:52 +07:00
Zamil Majdy
b80d7abda9 fix(backend): remove per-worker Prisma connect, route DB via DatabaseManagerAsyncClient
- Remove local import + db.connect()/disconnect() from CoPilotProcessor.on_executor_start
  DB calls already route through db_accessors (chat_db, user_db) which fall back to
  DatabaseManagerAsyncClient RPC when db.is_connected() is False
- Fix rate_limit._fetch_user_tier to use user_db().get_user_by_id() instead of
  PrismaUser.prisma() directly — avoids requiring Prisma connected on worker event loop
- Add subscription_tier field to User Pydantic model, mapped in User.from_db() so
  the RPC path returns the tier value without a direct Prisma connection
2026-04-08 10:05:18 +07:00
Zamil Majdy
0e310c788a fix(backend): fix TestGetPlatformCostDashboard mocks to match 3-query implementation
get_platform_cost_dashboard runs 3 concurrent queries (by_provider,
by_user, COUNT DISTINCT userId) but the unit tests only provided 2
side_effect values, causing StopAsyncIteration on the third call.
Updated all three test cases to supply a third mock return value and
corrected await_count assertion from 2 to 3.
2026-04-07 23:15:42 +07:00
Zamil Majdy
91af007c18 fix(backend): guard against non-finite cost_usd in persist_and_record_usage
float('inf') and float('nan') do not raise ValueError/TypeError so they
bypass the existing try/except. Passing them to usd_to_microdollars causes
OverflowError at round(inf * 1_000_000). Add math.isfinite(val) and val >= 0
check (matching the same pattern used in baseline/service.py and llm.py)
before assigning cost_float.
2026-04-07 22:56:20 +07:00
Zamil Majdy
e7ca81ed89 fix(backend): address coderabbitai nitpicks in cost tracking files
- token_tracking.py: convert logger.info %s calls to f-strings per style guide
- cost_tracking.py: simplify metadata=meta (was redundantly `meta or None`);
  move token_tracking imports to module level to remove # noqa: PLC0415 suppressors
- baseline/service.py: remove dead UnboundLocalError from except tuple since
  response is initialized to None before the try block
2026-04-07 22:54:52 +07:00
Zamil Majdy
5164fa878f fix(backend): fix race condition on _copilot_tasks concurrent iteration during drain
Add _pending_log_tasks_lock to token_tracking.py so that add/discard
operations on _pending_log_tasks are always lock-protected. Update
drain_pending_cost_logs in cost_tracking.py to acquire the copilot
tasks lock (not its own lock) when taking a snapshot of the copilot
set, preventing RuntimeError: Set changed size during iteration during
graceful shutdown when done callbacks fire concurrently.
2026-04-07 22:48:51 +07:00
Zamil Majdy
cf605ef5a3 fix(backend): fix race condition on _pending_log_tasks and uncapped total_users
- cost_tracking.py: add threading.Lock (_pending_log_tasks_lock) around all
  add/discard/iterate access to _pending_log_tasks; worker thread done callbacks
  and drain_pending_cost_logs() run concurrently across loops, causing
  RuntimeError: Set changed size during iteration without a lock

- platform_cost.py: add a separate COUNT(DISTINCT userId) query so total_users
  is accurate for >100 active users; previously it was silently capped at
  MAX_USER_ROWS=100 because it was derived from len(by_user_rows)
2026-04-07 22:25:25 +07:00
Zamil Majdy
e7bd05c6f1 fix(backend): filter drain tasks by current event loop to prevent cross-loop asyncio.wait() crash 2026-04-07 21:42:17 +07:00
Zamil Majdy
22fb3549e3 test(frontend): fix null-user dash assertion using getAllByText to handle multiple matches 2026-04-07 21:31:43 +07:00
Zamil Majdy
1c3fe1444e fix(backend): address 4 unresolved review threads on cost tracking
1. cost_tracking.py: replace shared _log_semaphore with per-loop dict
   (_log_semaphores + _get_log_semaphore()) — asyncio.Semaphore is not
   thread-safe and must not be shared across executor worker threads/loops

2. cost_tracking.py: only honor provider_cost_type when provider_cost is
   also present (not None); use tracking_amount (not raw stats.provider_cost)
   in usd_to_microdollars() to avoid unit mismatches

3. token_tracking.py: add semaphore to _schedule_cost_log (same pattern
   as cost_tracking.py) to bound concurrent DB inserts under load; fix
   forward-reference string in _pending_log_tasks type annotation

4. baseline/service.py: validate x-total-cost header with math.isfinite
   and max(0.0, cost) guard before accumulating — rejects nan/inf values
   that float() accepts but that should never reach the persistence path
2026-04-07 21:25:56 +07:00
Zamil Majdy
b89321a688 Merge remote-tracking branch 'origin/dev' into codex/platform-cost-tracking 2026-04-07 21:16:02 +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
Zamil Majdy
630d6d4705 fix(backend): add semaphore to executor cost log tasks; fix type annotation
- Add `_log_semaphore = asyncio.Semaphore(50)` to cost_tracking.py to bound
  concurrent DB inserts (mirrors platform_cost.py's existing semaphore)
- Narrow `_extract_model_name` param type from `Any` to `str | dict | None`
- Add `test_get_dashboard_cache_hit` to verify TTL cache deduplicates DB calls
- Add `scope="col"` to all table `<th>` elements for screen-reader accessibility
- Add `(local time)` labels to date filter inputs to clarify timezone behaviour
2026-04-07 18:15:57 +07:00
Zamil Majdy
7c685c6677 fix(backend): update platform_cost_test to expect masked email in dashboard
_mask_email() is applied to by_user emails in get_platform_cost_dashboard().
Test now asserts 'a***@b.com' instead of 'a@b.com'.
2026-04-07 18:02:00 +07:00
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
bbdf13c7a8 test(backend): add missing cost-tracking tests for Exa research, Apollo people, and copilot baseline
- ExaCreateResearchBlock, ExaGetResearchBlock, ExaWaitForResearchBlock: verify
  merge_stats is called with provider_cost=cost_dollars.total when completed, and
  not called when costDollars is absent
- SearchPeopleBlock: verify provider_cost=len(people) with type='items'
- Copilot baseline: 4 tests for x-total-cost header extraction in
  _baseline_llm_caller — including accumulation across turns and extraction in
  the finally block when the stream raises
2026-04-07 17:44:15 +07:00
Zamil Majdy
e1ea4cf326 test(frontend): rewrite PlatformCostContent tests to mock Orval hooks
Component now uses React Query hooks (useGetV2GetPlatformCostDashboard,
useGetV2GetPlatformCostLogs) instead of server actions, so tests must
mock @/app/api/__generated__/endpoints/admin/admin rather than ../actions.

Adds 16 test cases covering loading state, empty/data renders, tabs,
filters, pagination, null email/user handling, and tracking type badges.
2026-04-07 17:34:15 +07:00
Zamil Majdy
db6b4444e0 fix(platform): address autogpt-reviewer should-fix items
- Remove dead _pending_log_tasks/schedule_cost_log/drain_pending_cost_logs
  from platform_cost.py (only cost_tracking.py and token_tracking.py have
  active task registries; drain comment updated to match)
- Replace vars(other) iteration in NodeExecutionStats.__iadd__ with
  type(other).model_fields to avoid any potential __pydantic_extra__ leakage
- Fix rate-override clear: onRateOverride(key, null) deletes the key so
  defaultRateFor() takes effect instead of pinning estimated cost to $0
- Type extract_openrouter_cost parameter as OpenAIChatCompletion
- Fix early-return guard in persist_and_record_usage: allow through when
  all token counts are 0 but cost_usd is provided (fully-cached responses)
- Add missing tests: LLM retry cost (only last attempt merged), zero-token
  copilot cost, Exa search + similar merge_stats coverage
2026-04-07 17:23:42 +07:00
Zamil Majdy
9b1175473b fix(backend/copilot): update stale comment in processor.py after cost log routing change
token_tracking.py now routes cost logs through DatabaseManagerAsyncClient
(platform_cost_db()), so the Prisma connect in on_executor_start() is for
copilot/db.py and rate_limit.py direct Prisma usage.
2026-04-07 17:11:56 +07:00
Zamil Majdy
752a238166 refactor(frontend): replace server actions with React Query hooks for cost dashboard
usePlatformCostContent.ts now calls useGetV2GetPlatformCostDashboard and
useGetV2GetPlatformCostLogs directly (with okData selector) so the browser
gets proper caching, deduplication, and background refetch.

actions.ts is retained as a plain helper module (no 'use server') because
the co-located test file imports from it; the functions are no longer called
by the hook.
2026-04-07 17:08:42 +07:00
Zamil Majdy
2a73d1baa9 fix(backend/copilot): route copilot cost logging through DatabaseManagerAsyncClient
The copilot executor's token_tracking.py was using schedule_cost_log()
which calls execute_raw_with_schema() directly on the Prisma singleton.
In the copilot_executor process, Prisma is not reliably connected due to
event-loop binding issues, causing ClientNotConnectedError on every turn.

Fix: route cost logging through platform_cost_db() -> DatabaseManagerAsyncClient
RPC (same approach already used by the block executor). Also fix
_copilot_block_name() to extract only the service tag from the log prefix
(e.g. "[SDK][session-id][T1]" -> "copilot:SDK") instead of the full suffix.

Update cost_tracking.py drain to drain token_tracking._pending_log_tasks,
and update token_tracking_test.py mocks to match new call site.
2026-04-07 16:58:41 +07:00
Zamil Majdy
254e6057f4 fix(backend/copilot): connect Prisma in copilot executor for cost log writes
schedule_cost_log() in token_tracking.py writes PlatformCostLog rows via
execute_raw_with_schema(), which requires an active Prisma connection.
Connect Prisma at on_executor_start() so cost tracking is not silently dropped
in the copilot executor process.
2026-04-07 16:54:00 +07:00
Zamil Majdy
a616e5a060 fix(backend): address PR review — email masking, semaphore, openrouter cost style
- Mask user emails in admin API responses (dashboard + logs) to reduce
  PII exposure in proxy/CDN logs; _mask_email() shows first 2 chars only
- Add _log_semaphore(50) in platform_cost.py to bound concurrent DB inserts
  and provide back-pressure under high load
- Refactor extract_openrouter_cost() to use try/except AttributeError
  instead of getattr/hasattr, and log a WARNING when _response is missing
  so SDK changes are detectable
- Add comment to usePlatformCostContent.ts explaining why server actions
  are used instead of React Query (server-side withRoleAccess constraint)
2026-04-07 16:38:07 +07:00
Zamil Majdy
c9461836c6 fix(backend): address all open review comments on platform cost tracking
- Normalize provider to lowercase at write time; drop LOWER() in filter so
  the (provider, createdAt) index is used without function overhead
- Drop COALESCE(trackingType, metadata->>'tracking_type') fallback — new rows
  always have trackingType set at write time
- Derive total_users from len(by_user_rows) instead of a separate
  COUNT(DISTINCT userId) query (saves one aggregation per dashboard load)
- Add 30-second TTLCache for dashboard endpoint (cachetools, maxsize=256)
- Add backpressure/bounds comment to _pending_log_tasks in platform_cost.py
- Convert f-string logger calls in token_tracking.py to lazy %s formatting
- Add 6 block-level tests for ExaCodeContextBlock and ExaContentsBlock cost
  paths: valid/invalid/zero cost_dollars strings and None cost_dollars
- Update existing tests to match provider-lowercasing and 2-query dashboard
2026-04-07 16:23:10 +07:00
Zamil Majdy
50a8df3d67 Merge branch 'dev' of github.com:Significant-Gravitas/AutoGPT into codex/platform-cost-tracking 2026-04-07 16:12:47 +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
Zamil Majdy
3f7a8dc44d fix(backend/copilot): use active_model instead of config.model for cost attribution
When fast mode is selected, the baseline copilot uses a different model
(active_model from _resolve_baseline_model) than the config default. Using
config.model for cost attribution would misattribute costs to the wrong model.
2026-04-07 15:54:36 +07:00
Zamil Majdy
1c15d6a6cc fix(frontend): update platform-costs tests for Skeleton loading state and removed duration_seconds
- Update loading state test to check for absent Skeleton elements (animate-pulse)
  rather than absent 'Loading...' text (which was removed in previous commit)
- Update helpers.test.ts to test sandbox_seconds instead of the removed duration_seconds
2026-04-07 15:52:38 +07:00
Zamil Majdy
a31be77408 fix(platform): address additional reviewer feedback on platform cost dashboard
- Extract _extract_model_name() helper in cost_tracking.py to replace nested isinstance checks
- Replace Lucide icons with Phosphor equivalents in admin/layout.tsx
- Replace Loading... text with Skeleton components in PlatformCostContent
- Switch Promise.all to Promise.allSettled in usePlatformCostContent for partial data resilience
- Fix hardcoded border-blue-600/text-blue-600 with design token border-primary/text-primary
- Remove dead duration_seconds case from helpers.ts and TrackingBadge (backend never emits it)
2026-04-07 15:46:39 +07:00
Zamil Majdy
1d45f2f18c fix(platform): fix baseline copilot OpenRouter cost extraction and credit_cost check
- Fix wrong attribute: baseline/service.py used getattr(response, 'response')
  but AsyncStream exposes the raw httpx response via '_response' (with
  underscore), matching the pattern in llm.py:extract_openrouter_cost().
  OpenRouter cost tracking in baseline copilot was silently failing.
- Fix falsy zero-cost guard: change `if credit_cost:` to `if credit_cost is
  not None:` so free-tier blocks (credit_cost=0) include the field in metadata.
2026-04-07 15:25:02 +07:00
Zamil Majdy
27e34e9514 fix(platform): drain pending cost logs on shutdown, remove dark: badges
- Wire drain_pending_cost_logs() into ExecutionManager.cleanup() so
  in-flight INSERT tasks are awaited before process exit during rolling
  deployments (uses the existing node_execution_loop; no-op if the loop
  was never started, e.g. in tests)
- Remove prohibited dark: Tailwind classes from TrackingBadge badges;
  light tokens (text-green-700, text-blue-700, …) now apply in all
  themes — design system handles dark mode via CSS variables
2026-04-07 15:07:41 +07:00
Zamil Majdy
16d696edcc fix(platform): address autogpt-reviewer blockers and should-fix items
- Fix LLM retry double-counting: track tokens per attempt but only merge
  provider_cost on the successful attempt, not across all retries
- Add drain_pending_cost_logs() to platform_cost.py; update cost_tracking
  to drain both executor and copilot task sets on shutdown
- Remove prohibited dark: Tailwind classes from PlatformCostContent error
  div, replace with Alert component (design system error variant)
- Add block-level cost tracking tests for: JinaEmbeddingBlock (with/without
  usage), UnrealTextToSpeechBlock (character count), GoogleMapsSearchBlock
  (place count), AddLeadToCampaignBlock (lead count)
- Add __iadd__ edge case tests: provider_cost_type first-write-to-None and
  None does not overwrite existing value
- Rename metadata key provider_cost_usd to provider_cost_raw (value unit
  varies by tracking type; only cost_usd uses USD)
- Add test verifying per_run providers have no provider_cost_raw in metadata
2026-04-07 15:05:44 +07:00
Zamil Majdy
f87bbd5966 fix(backend): route platform cost logging through DatabaseManagerAsyncClient
Fixes ClientNotConnectedError in the executor process by routing
log_platform_cost through the DatabaseManagerAsyncClient RPC proxy
instead of calling execute_raw_with_schema directly on the unconnected
module-level prisma instance.
2026-04-07 14:53:46 +07:00
Nicholas Tindle
b64d1ed9fa Merge branch 'dev' into codex/platform-cost-tracking 2026-04-06 14:31:13 -05:00
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
Zamil Majdy
3895d95826 fix(platform): address reviewer comments — tests, a11y, and frontend polish
Backend:
- Add block cost tracking tests for ExaCodeContext, ExaContents, and
  SearchOrganizations blocks (high-severity reviewer ask)
- Add test verifying FAILED status skips cost log in manager
- Add test for empty org list tracking zero items cost

Frontend:
- Rename trackingBadge() → TrackingBadge component (PascalCase convention)
- Move toLocalInput/toUtcIso helpers from usePlatformCostContent.ts to helpers.ts
- Add aria-label to ProviderTable rate override inputs
- Add role="alert" to error state div in PlatformCostContent
- Add Clear Filters button next to Apply
- Fix text-gray-500 → text-muted-foreground in page.tsx (dark mode)
- Dark-mode-compatible error div styling
- Strengthen PlatformCostContent test assertion (exact count instead of >= 1)
- Add tab panel visibility tests and toLocalInput/toUtcIso unit tests
2026-04-06 21:49:23 +07:00
Zamil Majdy
181208528f fix(backend): update token_tracking_test mock targets after _schedule_log refactor
After extracting _schedule_log into schedule_cost_log() in platform_cost.py,
token_tracking no longer has log_platform_cost_safe as an attribute.
Update patch targets to backend.data.platform_cost.log_platform_cost_safe.
2026-04-06 21:37:38 +07:00
Zamil Majdy
0365a26c85 refactor(backend): add clarifying comment to NodeExecutionStats.__iadd__ vars() usage 2026-04-06 21:25:00 +07:00
Zamil Majdy
fb63ae54f0 refactor(platform): address review comments on platform cost tracking
Backend:
- Extract shared _schedule_log into schedule_cost_log() in platform_cost.py
  so both cost_tracking and token_tracking drain a single task set
- Add DEFAULT_DASHBOARD_DAYS=30 default for dashboard queries to avoid
  full-table scans when no date filter is provided
- Add MAX_PROVIDER_ROWS=500 / MAX_USER_ROWS=100 named constants
- Fix typing.Optional -> X | None union syntax in routes
- Fix logger f-strings to lazy %s format in platform_cost_routes
- Fix token_tracking condition to allow logging when cost_usd is set
  even if total_tokens is 0 (fully-cached responses)
- Fix test_get_dashboard_success to use real PlatformCostDashboard instance
- Add invalid input tests (422 for bad dates, page_size=0/201, page=0)
- Add test_does_not_raise_when_block_usage_cost_raises
- Add test_provider_cost_zero_is_not_none

Frontend:
- Fix TrackingBadge dark mode colors using design tokens
- Fix UserTable null key for deleted users (use unknown-{idx} fallback)
- Fix ProviderTable rate input from uncontrolled to controlled
- Fix "use server" directive on page component (not a server action)
- Add ARIA label and tabpanel roles to tab UI
- Fix LogsTable fragile cast with safe formatLogDate helper
2026-04-06 21:19:49 +07:00
Zamil Majdy
6de79fb73f fix: resolve merge conflicts with dev branch
Keep cost_usd field alongside new thinking_stripper and session_messages
fields added in dev for baseline copilot state.
2026-04-06 21:00:23 +07:00
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
Zamil Majdy
d57da6c078 refactor(platform): extract usePlatformCostContent hook
PlatformCostContent.tsx was 248 lines mixing data fetching, URL state,
filter inputs, rate overrides, and rendering. Per frontend convention,
extract the stateful/effectful logic into a dedicated hook:

- usePlatformCostContent.ts (new, 142 lines) — owns:
  - dashboard/logs/pagination fetching via effect
  - URL ↔ filter input sync (startInput, endInput, providerInput, userInput)
  - rateOverrides state + handleRateOverride
  - toLocalInput/toUtcIso datetime helpers
  - updateUrl + handleFilter actions
  - totalEstimatedCost reducer
- PlatformCostContent.tsx (now 182 lines) — pure rendering only.
2026-04-05 15:56:32 +02:00
Zamil Majdy
689cd67a13 refactor(platform): address autogpt-reviewer feedback (batch 2)
- resolve_tracking: replace hardcoded provider string literals with
  ProviderName enum values + _CHARACTER_BILLED_PROVIDERS /
  _WALLTIME_BILLED_PROVIDERS frozensets (nice-to-have #2).
- NodeExecutionStats.__iadd__: replace double model_dump() with
  vars()-based iteration for ~10-50x speedup on each merge_stats() call
  (hot path — runs once per block per yield across 20+ blocks).
- Add 3 accumulation tests for provider_cost semantics:
  - Multiple provider_cost values sum (not last-write-wins)
  - None never overwrites a set value
  - provider_cost_type is last-write-wins (documented semantics)
2026-04-05 15:54:12 +02:00
Zamil Majdy
dca89d1586 refactor(platform): address autogpt-reviewer feedback (batch 1)
- cost_tracking.py: replace `Any` types with NodeExecutionEntry + Block
- Extract usd_to_microdollars utility in platform_cost.py, used by
  cost_tracking.py and copilot/token_tracking.py.
- llm.py: extract x-total-cost header parsing to extract_openrouter_cost()
  helper + 8 unit tests covering present/absent/empty/non-numeric/zero
  cases. Previously untested blocker.
- token_tracking.py: extract COPILOT_BLOCK_ID, COPILOT_CREDENTIAL_ID
  constants + _copilot_block_name() helper (clearer than inline
  f"copilot:{log_prefix.strip(' []')}".rstrip(":")).
- platform_cost.py: cap by_provider query at LIMIT 500 (defensive bound).
- TrackingBadge.tsx: drop dark: classes per frontend convention, add
  "items" badge color.
- PlatformCostContent.tsx: drop dark: classes from error banner,
  add role="tablist"/role="tab"/aria-selected to tabs, add htmlFor
  to filter input labels.
- admin/layout.tsx: Receipt icon moved from lucide-react to phosphor.
- ProviderTable.tsx: add "(unsaved)" label to Rate column header to
  signal per-session only.
2026-04-05 15:46:50 +02:00
Zamil Majdy
2f63fcd383 test(frontend): update platform-costs helpers tests for per-type rate estimation
Updates the test suite to match the new per-type rate estimation logic:
- rateOverrides now use composite keys (provider:tracking_type)
- trackingValue appends unit suffixes (tokens, chars, items)
- characters/items tracking reads from total_tracking_amount
- adds coverage for default rates across characters, items, duration types
2026-04-05 15:30:32 +02:00
Zamil Majdy
f04cd08e40 feat(platform): add trackingAmount column + per-type rate estimation
Problem
- cost_tracking.py was multiplying stats.provider_cost by 1M to get
  cost_microdollars regardless of tracking_type. When provider_cost_type
  was "items" or "characters", 5.0 items got stored as $5 USD.
- The dashboard had no way to aggregate item/character counts since
  they aren't naturally carried by inputTokens/outputTokens/duration.
- Dashboard estimation only handled cost_usd/tokens/per_run; characters,
  items, sandbox_seconds, walltime_seconds showed "-" always.

Fix
- Add PlatformCostLog.trackingAmount (Float?) column + migration.
- cost_tracking.py: only treat provider_cost as USD when tracking_type
  is "cost_usd"; always populate trackingAmount with resolve_tracking's
  amount so the dashboard can aggregate it.
- Dashboard query: SUM(trackingAmount) as total_tracking_amount.
- ProviderCostSummary (backend + regenerated TS): add total_tracking_amount.
- Frontend helpers: DEFAULT_COST_PER_1K_CHARS, DEFAULT_COST_PER_ITEM,
  DEFAULT_COST_PER_SECOND tables for characters/items/duration rates.
  estimateCostForRow dispatches per tracking_type and multiplies the
  correct amount by the correct rate.
- ProviderTable: show editable rate input for every tracking_type
  (not only per_run), with unit label ($/1K tokens, $/1K chars, $/item,
  $/second, $/run). Rate overrides keyed on "provider:tracking_type".
2026-04-05 15:23:31 +02:00
Zamil Majdy
44714f1b25 refactor(platform): use provider_cost_type Literal instead of output_size misuse
Blocks previously called merge_stats(NodeExecutionStats(output_size=...))
to signal "per-request" billing or "N items returned", but `output_size`
is semantically the output payload byte count and is always overridden
by the executor wrapper (manager.py:440 = len(json.dumps(output_data))).
Those calls were silently dead code.

Changes:
- Add ProviderCostType Literal enum on NodeExecutionStats with the
  canonical set of tracking types: cost_usd, tokens, characters,
  sandbox_seconds, walltime_seconds, per_run, items.
- Add provider_cost_type field to NodeExecutionStats so blocks can
  declare their billing model explicitly instead of resolve_tracking
  guessing from provider name.
- resolve_tracking honors provider_cost_type first, falling back to
  heuristics only when not set.
- Remove 26 dead merge_stats(output_size=1) calls across 15 blocks.
- Replace 5 merge_stats(output_size=len(X)) calls with explicit
  provider_cost+provider_cost_type (items/characters) so the count
  is preserved through the wrapper's output_size override.
- Clean up unused NodeExecutionStats imports in 14 files.
- Add tests for block-declared provider_cost_type pathway.
2026-04-05 14:56:44 +02:00
Zamil Majdy
78b95f8a76 fix(platform): add provider_cost tracking to Exa code_context block 2026-04-05 14:44:30 +02:00
Zamil Majdy
6f0c1dfa11 fix(platform): close tracking gaps found during audit
- resolve_tracking: read `script` field for elevenlabs in addition to
  `script_input`/`text` — VideoNarrationBlock uses `script`, was
  producing tracking_amount=0 characters before.
- exa/similar.py + exa/research.py (3 blocks): extract provider_cost
  from response.cost_dollars.total via merge_stats so tracking_type
  ends up as "cost_usd" with real dollar amounts instead of
  falling through to per_run.
- Add test for script field resolution.

Audit finding: `output_size` set via merge_stats in blocks is
always overridden by the executor wrapper (manager.py:440 computes
byte count of serialized output), and `walltime` is also set by
the wrapper (manager.py:667). So the existing merge_stats(output_size=1)
calls in ~15 blocks are dead code for cost tracking purposes; they
don't hurt but don't add data either. The real tracking data sources
are: (1) input/output_token_count from LLM blocks, (2) provider_cost
from APIs that return USD, (3) input_data for per-character TTS,
(4) auto-populated walltime for wall-clock billing.
2026-04-05 14:38:24 +02:00
Zamil Majdy
5e595231da test(platform): align actions tests with string date passthrough
The actions intentionally pass raw ISO strings (cast to Date) to the
generated client to avoid Date.toString() producing non-ISO output
that FastAPI rejects. Update the tests to match this behavior rather
than expecting Date instances.
2026-04-05 12:54:42 +02:00
Zamil Majdy
7b36bed8a5 fix(platform): address autogpt-reviewer feedback on cost tracking
- cost_tracking.py + token_tracking.py: switch back to asyncio.create_task
  for true fire-and-forget on hot path, but hold strong references in a
  module-level set (with done-callback discard) so tasks can't be GC'd
  mid-flight. Addresses both the "await blocks executor" concern and the
  "task may vanish before completion" concern.
- cost_tracking.py: `> 0` checks instead of truthy for output_size/walltime
  so legitimate zero values aren't stored as NULL.
- platform_cost_routes_test.py: add explicit 403 test for non-admin JWT
  and extend 401 test to cover /logs endpoint.
- actions.ts: forward raw ISO strings to generated client instead of Date
  objects — the client calls .toString() which produces human-readable
  format that FastAPI rejects with 422. Fixes timezone filter on the
  admin dashboard.
2026-04-05 12:50:03 +02:00
Zamil Majdy
372900c141 fix(platform): address 5 self-review items on cost tracking
- cost_tracking.py: drop asyncio.create_task fire-and-forget (risked task
  GC mid-flight per Python docs); await log_platform_cost_safe directly.
  Wrap body in try/except so logging never disrupts executor.
- token_tracking.py: same create_task fix; await directly.
- platform_cost.py: document that by_provider rows are keyed on
  (provider, tracking_type) so the same provider can appear multiple times.
- PlatformCostContent.tsx: convert datetime-local (naive local time) to
  UTC ISO before URL serialization so filter windows match admin's wall
  clock regardless of backend timezone. Convert back to local for input
  display.
2026-04-05 11:55:00 +02:00
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
7afd2b249d fix(platform): address 9 should-fix items from PR review
1. Fix route path double-nesting: /api/admin/platform-costs/{dashboard,logs}
2. Fix falsy zero suppression: pass raw token counts instead of `or None`
3. Split 546-line PlatformCostContent into SummaryCard, ProviderTable,
   UserTable, LogsTable, TrackingBadge sub-components
4. Add merge_stats accumulation tests and integration test for
   on_node_execution -> log_system_credential_cost wiring
5. Add source citations for DEFAULT_COST_PER_RUN values
6. Extract MICRODOLLARS_PER_USD constant, use in all conversion sites
7. Parallelize COUNT + SELECT in get_platform_cost_logs with asyncio.gather
8. Remove dead block_name parameter from resolve_tracking()
9. Remove unrelated store.test.ts (added by this PR, not on dev)
2026-04-03 23:14:38 +02:00
Zamil Majdy
8d22653810 fix(platform): address 4 review blockers on cost tracking
- Fire-and-forget cost logging via asyncio.create_task() instead of await
  to avoid blocking executor and copilot streaming paths on DB INSERT
- Add trackingType column to PlatformCostLog schema, migration, and INSERT;
  update dashboard/logs queries to use COALESCE(column, JSONB) for backward
  compat and index-friendly GROUP BY
- Admin auth test now explicitly mocks get_jwt_payload to raise 401 instead
  of relying on bare FastAPI app behavior
- Blocker 3 (nullable user_id) was already addressed in prior commit
2026-04-03 22:43:57 +02:00
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
b00e16b438 fix(platform): fix model_test to use Optional fields for None-skip test
Use provider_cost (Optional) and error (Optional) instead of
walltime (non-nullable float) to test __iadd__ None-skip behavior.
2026-04-03 17:25:15 +02:00
Zamil Majdy
b5acfb7855 fix: resolve merge conflict with dev in helpers.test.ts 2026-04-03 17:12:07 +02:00
Zamil Majdy
1ee0bd6619 fix(platform): use round() for microdollar conversion and add cost tracking tests
- Fix float->int truncation bug in token_tracking.py and cost_tracking.py
  where int(cost * 1_000_000) would under-count (e.g. 0.0015 -> 1499
  instead of 1500). Now uses round() for correct rounding.
- Extract _resolve_tracking and _log_system_credential_cost from
  manager.py into dedicated cost_tracking.py module for testability.
- Add unit tests for all 8+ provider branches in resolve_tracking,
  log_system_credential_cost happy/skip paths, and model conversion.
- Add NodeExecutionStats.__iadd__ regression tests for None-skip behavior.
- Add frontend component tests for PlatformCostContent (14 tests) and
  actions.ts server actions (7 tests) to improve codecov patch coverage.
2026-04-03 17:04:07 +02:00
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
Zamil Majdy
4190f75b0b test: additional coverage for platform cost and token tracking 2026-04-03 15:09:54 +02:00
Zamil Majdy
71315aa982 fix(backend): use actual provider in persist_and_record_usage cost logging
The provider field was hardcoded to "open_router" for all PlatformCostLog
entries, even when the SDK (Anthropic) path was the caller. Add a provider
parameter that defaults to "open_router" for backward compatibility and
pass "anthropic" from the SDK service layer.
2026-04-03 14:37:47 +02:00
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
Zamil Majdy
960f893295 test(platform): add unit tests for platform cost helpers and data layer
Extract pure helper functions (formatMicrodollars, formatTokens,
formatDuration, estimateCostForRow, trackingValue, toDateOrUndefined)
from PlatformCostContent.tsx into helpers.ts for testability. Add 26
vitest cases covering all formatting and cost-estimation branches.

Add backend tests for _build_where and _json_or_none in
platform_cost.py (11 pytest cases covering filter combinations).
2026-04-03 14:15:28 +02:00
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
759effab60 test(frontend): add unit tests for onboarding store and GenericTool helpers
Improve frontend patch coverage with comprehensive tests for the
onboarding wizard zustand store and GenericTool helper functions.
2026-04-03 13:25:52 +02:00
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
Zamil Majdy
45b6ada739 Merge branch 'dev' of github.com:Significant-Gravitas/AutoGPT into codex/platform-cost-tracking 2026-04-03 13:07:06 +02:00
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
da544d3411 fix(platform): fix CI - regenerate API schema + fix Date type mismatch
- Regenerate openapi.json using export-api-schema command (CI-compatible)
- Convert string date params to Date objects before passing to generated
  API functions (orval generates Date | null for datetime fields)
- pnpm types passes cleanly
2026-04-02 20:56:08 +02:00
Zamil Majdy
54e5059d7c fix(platform): use generated Pagination type + estimate token costs
- Import Pagination from generated client instead of hand-written types
- Add DEFAULT_COST_PER_1K_TOKENS for OpenAI/Anthropic/Groq/Ollama
- estimateCostForRow now computes cost from token count when provider
  doesn't report actual USD (tokens * rate_per_1k / 1000)
- Added date comment for when default rates were checked
2026-04-02 20:43:23 +02:00
Zamil Majdy
1d7d2f77f3 feat(platform): tracking-aware dashboard with generated API client
Backend:
- ProviderCostSummary now includes tracking_type and total_duration_seconds
- CostLogRow includes tracking_type and duration
- SQL queries extract tracking_type from metadata JSON

Frontend:
- Replaced hand-written types/client with generated API client (orval)
- Actions use getV2GetPlatformCostDashboard/getV2GetPlatformCostLogs
- Provider table shows: Type badge, Usage metric, Known Cost, Estimated Cost
- Per-run providers have editable $/run input with defaults
- Summary cards show "Known Cost" vs "Estimated Total"
- Logs table shows tracking_type badge + duration column
- Color-coded badges: cost_usd(green), tokens(blue), duration(orange),
  characters(purple), per_run(gray)
2026-04-02 20:27:58 +02:00
Zamil Majdy
567bc73ec4 fix(blocks): regenerate block docs after merge with dev 2026-04-02 19:32:15 +02:00
Zamil Majdy
61ef54af05 Merge branch 'dev' of github.com:Significant-Gravitas/AutoGPT into codex/platform-cost-tracking 2026-04-02 19:28:37 +02:00
Zamil Majdy
405403e6b7 fix(backend): initialize response before try block to satisfy pyright 2026-04-02 19:21:22 +02:00
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
Zamil Majdy
ab16e63b0a fix(platform): pass model name to copilot cost tracking
Both SDK and Baseline paths now pass config.model to
persist_and_record_usage so PlatformCostLog records the actual
model (e.g. anthropic/claude-sonnet-4) for filtering/grouping.
2026-04-02 19:03:47 +02:00
Zamil Majdy
45d3193727 fix(platform): move baseline cost extraction to finally + accumulate multi-round costs
- Move x-total-cost header extraction to finally block so cost is
  captured even when stream errors mid-way (we already paid)
- Accumulate cost across multi-round tool-calling turns instead of
  overwriting with last round only
- Handle UnboundLocalError if response was never assigned
2026-04-02 19:00:44 +02:00
Zamil Majdy
9a08011d7d fix(platform): move opentelemetry import to top-level in both copilot paths 2026-04-02 18:57:36 +02:00
Zamil Majdy
6fa66ac7da feat(platform): add cost/token OTEL attributes to both copilot paths
Both SDK and Baseline copilot paths now set OpenTelemetry span
attributes for cost tracking before the trace context closes:
- gen_ai.usage.prompt_tokens
- gen_ai.usage.completion_tokens
- gen_ai.usage.cost_usd (when available)
- gen_ai.usage.cache_read_tokens (SDK only)
- gen_ai.usage.cache_creation_tokens (SDK only)

Also extracts x-total-cost from OpenRouter response headers in the
Baseline streaming path, giving actual USD cost for both modes.

These attributes flow to Langfuse/any OTEL backend for cost dashboards.
2026-04-02 18:55:12 +02:00
Zamil Majdy
4bad08394c feat(platform): extract OpenRouter cost from baseline copilot path
The baseline copilot path uses the same OpenRouter API but wasn't
extracting the x-total-cost header. Now extracts cost from the
streaming response headers and passes it to persist_and_record_usage,
giving us actual USD cost for both copilot modes.
2026-04-02 18:39:55 +02:00
Zamil Majdy
993c43b623 feat(platform): add merge_stats to remaining blocks (FAL, Revid, D-ID, E2B, YouTube, Weather, TTS, Enrichlayer)
Every system credential block now has explicit merge_stats tracking.
No block relies on the generic fallback anymore.
2026-04-02 18:22:02 +02:00
Zamil Majdy
a8a62eeefc feat(platform): add merge_stats tracking to all system credential blocks
Every block that uses system credentials now calls merge_stats with
meaningful data after the API response:
- Google Maps: output_size = number of places returned (= detail API calls)
- Apollo people/org: output_size = results count
- Apollo person: output_size = 1 per enrichment
- SmartLead: output_size = leads added or 1 per operation
- Ideogram: output_size = 1 per image
- Replicate: output_size = 1 per prediction
- Nvidia: output_size = 1 per inference
- ScreenshotOne: output_size = 1 per screenshot
- ZeroBounce: output_size = 1 per email validated
- Mem0: output_size = 1 per memory operation
2026-04-02 18:13:15 +02:00
Zamil Majdy
173614bcc5 fix(platform): audit and fix per-provider tracking accuracy
- Fix ElevenLabs/D-ID field name: script -> script_input
- Remove incorrect Google Maps api_calls formula, use per_run instead
- Remove D-ID from generation_seconds (walltime includes polling)
- Jina embeddings: extract total_tokens from response.usage
- Simplify tracking types: cost_usd, tokens, characters,
  sandbox_seconds, walltime_seconds, per_run
2026-04-02 17:58:24 +02:00
Zamil Majdy
fbe634fb19 fix(platform): handle null user_id in cost logs and fix 0.0 cost stored as NULL
- Add null-safe optional chaining for user_id.slice() in LogsTable, displaying
  "Deleted user" when user_id is null to prevent frontend crash
- Change `if cost_float` to `if cost_float is not None` in token_tracking.py
  so that a legitimate $0.00 cost is stored as 0 instead of NULL
2026-04-02 17:38:59 +02:00
Zamil Majdy
a338c72c42 Merge branch 'dev' of github.com:Significant-Gravitas/AutoGPT into codex/platform-cost-tracking 2026-04-02 17:36:14 +02:00
Zamil Majdy
7f4398efa3 feat(platform): provider-specific tracking types for accurate cost metrics
Replace one-size-fits-all tracking cascade with provider-aware logic:
- cost_usd: OpenRouter (x-total-cost header), Exa (cost_dollars)
- tokens: OpenAI, Anthropic, Groq, Ollama (token counts)
- characters: Unreal Speech, ElevenLabs (input text length)
- api_calls: Google Maps (1 nearby + N detail calls)
- sandbox_seconds: E2B (sandbox execution time)
- generation_seconds: FAL, Revid, D-ID, Replicate (video/image gen time)
- per_run: Apollo, SmartLead, ZeroBounce, Jina, etc.
2026-04-02 17:30:15 +02:00
Zamil Majdy
c2a054c511 fix(backend): prevent provider_cost loss on stats merge and widen costMicrodollars to BigInt
- NodeExecutionStats.__iadd__ was overwriting accumulated provider_cost
  with None when merging stats that lacked provider_cost (e.g. the final
  llm_call_count/llm_retry_count merge). Skip None values in __iadd__
  so existing data is never erased.
- Widen PlatformCostLog.costMicrodollars from Int (max ~$2,147) to
  BigInt to prevent theoretical overflow for high-cost aggregated
  node executions.
2026-04-02 17:28:27 +02:00
Zamil Majdy
83b00f4789 feat(platform): add copilot/autopilot cost tracking via token_tracking.py
Copilot uses OpenRouter via a separate code path (not through the block
executor). This integrates PlatformCostLog into the shared
persist_and_record_usage() function which is called by both SDK and
baseline copilot paths, capturing:
- Every LLM turn (main conversation, title gen, context compression)
- Tokens (prompt + completion + cache)
- Actual USD cost when available (SDK path provides cost_usd)
- Session ID for correlation
2026-04-02 17:17:53 +02:00
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
95524e94b3 feat(platform): add tracking_type and tracking_amount to cost log metadata
Standardize cost tracking across providers:
- cost_usd: actual dollar cost (OpenRouter, Exa)
- tokens: total token count (LLM blocks)
- duration_seconds: execution time (video gen, sandboxes)
- per_run: flat per-request (all others)
2026-04-02 17:04:50 +02:00
Zamil Majdy
2c517ff9a1 feat(platform): add per-provider cost extraction
- OpenRouter: Extract actual USD cost from x-total-cost response header
- Exa (search, contents): Write cost_dollars.total to execution_stats
- LLM blocks: Store provider_cost in stats when available
- Add provider_cost field to NodeExecutionStats
- Hook now converts provider_cost to costMicrodollars in PlatformCostLog
- Metadata includes both credit_cost and provider_cost_usd when available
2026-04-02 16:57:34 +02:00
Zamil Majdy
7020ae2189 fix(backend): handle NULL userId in platform cost models and queries
Make user_id Optional[str] in UserCostSummary and CostLogRow to handle
cases where the referenced user has been deleted. Use .get() for safe
access to user_id from query result rows. Regenerate OpenAPI schema.
2026-04-02 16:54:09 +02:00
Zamil Majdy
b9336984be fix(platform): re-add credit_cost to platform cost log metadata
Include the block's credit cost (from block_cost_config) in the log
metadata so every entry has a known cost proxy even when the provider
doesn't expose actual dollar costs.
2026-04-02 16:37:28 +02:00
Zamil Majdy
9924dedddc fix(platform): address bot review comments (sentry + coderabbit)
- CRITICAL: Use execute_raw_with_schema for INSERT (not query_raw)
- Remove accidentally committed transcripts/
- Add dry_run guard to skip cost logging for simulated executions
- Change onDelete: Cascade → SetNull to preserve cost history
- Add standalone createdAt index for date-only queries
- Add deterministic tiebreaker (id) to pagination ORDER BY
- Update migration SQL to match schema changes
2026-04-02 16:26:01 +02:00
Zamil Majdy
c054799b4f fix: regenerate API schema and block docs 2026-04-02 16:23:12 +02:00
Zamil Majdy
f3b5d584a3 fix(platform): address PR review round 5
- Replace ServerCrash icon with Receipt for Platform Costs sidebar
2026-04-02 16:02:00 +02:00
Zamil Majdy
476d9dcf80 fix(platform): address PR review round 4
- Add tests for query parameter forwarding and pagination
2026-04-02 16:00:08 +02:00
Zamil Majdy
072b623f8b fix(platform): address PR review round 3
- Remove duplicate block_usage_cost call from cost logging
- Add case-insensitive provider filter using LOWER()
- Add platform_cost_routes_test.py with basic endpoint tests
2026-04-02 15:58:00 +02:00
Zamil Majdy
26b0c95936 fix(platform): address PR review round 2
- Parallelize dashboard queries with asyncio.gather for ~3x speedup
- Move json import to top-level
- Use consistent p. table alias across all dashboard queries
2026-04-02 15:55:03 +02:00
Zamil Majdy
308357de84 fix(platform): address PR review round 1
- Parameterize LIMIT/OFFSET in SQL queries to prevent injection
- Only log platform cost on successful block execution
- Convert model enum values to strings for proper logging
- Add error handling with try/catch/finally in frontend useEffect
- Drive filter state from URL params to prevent desync
- Add dark mode support using design tokens
- Return total_users count in dashboard for accurate reporting
- Add credit_cost to metadata as cost proxy until per-token pricing
2026-04-02 15:51:28 +02:00
Zamil Majdy
1a6c50c6cc feat(platform): add platform cost tracking for system credentials
Track real API costs incurred when users consume system-managed credentials.
Captures provider, tokens, duration, and model per block execution and
surfaces an admin dashboard with provider/user aggregation and raw logs.
2026-04-02 15:42:18 +02:00
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
24d0c35ed3 fix(backend/copilot): prompt-too-long retry, compaction churn, model-aware compression, and truncated tool call recovery (#12625)
## Why

CoPilot has several context management issues that degrade long
sessions:
1. "Prompt is too long" errors crash the session instead of triggering
retry/compaction
2. Stale thinking blocks bloat transcripts, causing unnecessary
compaction every turn
3. Compression target is hardcoded regardless of model context window
size
4. Truncated tool calls (empty `{}` args from max_tokens) kill the
session instead of guiding the model to self-correct

## What

**Fix 1: Prompt-too-long retry bypass (SENTRY-1207)**
The SDK surfaces "prompt too long" via `AssistantMessage.error` and
`ResultMessage.result` — neither triggered the retry/compaction loop
(only Python exceptions did). Now both paths are intercepted and
re-raised.

**Fix 2: Strip stale thinking blocks before upload**
Thinking/redacted_thinking blocks in non-last assistant entries are
10-50K tokens each but only needed for API signature verification in the
*last* message. Stripping before upload reduces transcript size and
prevents per-turn compaction.

**Fix 3: Model-aware compression target**
`compress_context()` now computes `target_tokens` from the model's
context window (e.g. 140K for Opus 200K) instead of a hardcoded 120K
default. Larger models retain more history; smaller models compress more
aggressively.

**Fix 4: Self-correcting truncated tool calls**
When the model's response exceeds max_tokens, tool call inputs get
silently truncated to `{}`. Previously this tripped a circuit breaker
after 3 attempts. Now the MCP wrapper detects empty args and returns
guidance: "write in chunks with `cat >>`, pass via
`@@agptfile:filename`". The model can self-correct instead of the
session dying.

## How

- **service.py**: `_is_prompt_too_long` checks in both
`AssistantMessage.error` and `ResultMessage` error handlers. Circuit
breaker limit raised from 3→5.
- **transcript.py**: `strip_stale_thinking_blocks()` reverse-scans for
last assistant `message.id`, strips thinking blocks from all others.
Called in `upload_transcript()`.
- **prompt.py**: `get_compression_target(model)` computes
`context_window - 60K overhead`. `compress_context()` uses it when
`target_tokens` is None.
- **tool_adapter.py**: `_truncating` wrapper intercepts empty args on
tools with required params, returns actionable guidance instead of
failing.

## Related

- Fixes SENTRY-1207
- Sessions: `d2f7cba3` (repeated compaction), `08b807d4` (prompt too
long), `130d527c` (truncated tool calls)
- Extends #12413, consolidates #12626

## Test plan

- [x] 6 unit tests for `strip_stale_thinking_blocks`
- [x] 1 integration test for ResultMessage prompt-too-long → compaction
retry
- [x] Pyright clean (0 errors), all pre-commit hooks pass
- [ ] E2E: Load transcripts from affected sessions and verify behavior
2026-04-01 15:10:57 +00:00
Zamil Majdy
8aae7751dc fix(backend/copilot): prevent duplicate block execution from pre-launch arg mismatch (#12632)
## Why

CoPilot sessions are duplicating Linear tickets and GitHub PRs.
Investigation of 5 production sessions (March 31st) found that 3/5
created duplicate Linear issues — each with consecutive IDs at the exact
same timestamp, but only one visible in Langfuse traces.

Production gcloud logs confirm: **279 arg mismatch warnings per day**,
**37 duplicate block execution pairs**, and all LinearCreateIssueBlock
failures in pairs.

Related: SECRT-2204

## What

Replace the speculative pre-launch mechanism with the SDK's native
parallel dispatch via `readOnlyHint` tool annotations. Remove ~580 lines
of pre-launch infrastructure code.

## How

### Root cause
The pre-launch mechanism had three compounding bugs:
1. **Arg mismatch**: The SDK CLI normalises args between the
`AssistantMessage` (used for pre-launch) and the MCP `tools/call`
dispatch, causing frequent mismatches (279/day in prod)
2. **FIFO desync on denial**: Security hooks can deny tool calls,
causing the CLI to skip the MCP dispatch — but the pre-launched task
stays in the FIFO queue, misaligning all subsequent matches
3. **Cancel race**: `task.cancel()` is best-effort in asyncio — if the
HTTP call to Linear/GitHub already completed, the side effect is
irreversible

### Fix
- **Removed** `pre_launch_tool_call()`, `cancel_pending_tool_tasks()`,
`_tool_task_queues` ContextVar, all FIFO queue logic, and all 4
`cancel_pending_tool_tasks()` calls in `service.py`
- **Added** `readOnlyHint=True` annotations on 15+ read-only tools
(`find_block`, `search_docs`, `list_workspace_files`, etc.) — the SDK
CLI natively dispatches these in parallel ([ref:
anthropics/claude-code#14353](https://github.com/anthropics/claude-code/issues/14353))
- Side-effect tools (`run_block`, `bash_exec`, `create_agent`, etc.)
have no annotation → CLI runs them sequentially → no duplicate execution
risk

### Net change: -578 lines, +105 lines
2026-04-01 13:42:54 +00:00
An Vy Le
725da7e887 dx(backend/copilot): clarify ambiguous agent goals using find_block before generation (#12601)
### Why / What / How

**Why:** When a user asks CoPilot to build an agent with an ambiguous
goal (output format, delivery channel, data source, or trigger
unspecified), the agent generator previously made assumptions and jumped
straight into JSON generation. This produced agents that didn't match
what the user actually wanted, requiring multiple correction cycles.

**What:** Adds a "Clarifying Before Building" section to the agent
generation guide. When the goal is ambiguous, CoPilot first calls
`find_block` to discover what the platform actually supports for the
ambiguous dimension, then asks the user one concrete question grounded
in real platform options (e.g. "The platform supports Gmail, Slack, and
Google Docs — which should the agent use for delivery?"). Only after the
user answers does the full agent generation workflow proceed.

**How:** The clarification instruction is added to
`agent_generation_guide.md` — the guide loaded on-demand via
`get_agent_building_guide` when the LLM is about to build an agent. This
avoids polluting the system prompt supplement (which loads for every
CoPilot conversation, not just agent building). No dedicated tool is
needed — the LLM asks naturally in conversation text after discovering
real platform options via `find_block`.

### Changes 🏗️

- `backend/copilot/sdk/agent_generation_guide.md`: Adds "Clarifying
Before Building" section before the workflow steps. Instructs the model
to call `find_block` for the ambiguous dimension, ask the user one
grounded question, wait for the answer, then proceed to generation.
- `backend/copilot/prompting_test.py`: New test file verifying the guide
contains the clarification section and references `find_block`.

### 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:
- [ ] Ask CoPilot to "build an agent to send a report" (ambiguous
output) — verify it calls `find_block` for delivery options and asks one
grounded question before generating JSON
- [ ] Ask CoPilot to "build an agent to scrape prices from Amazon and
email me daily" (specific goal) — verify it skips clarification and
proceeds directly to agent generation
- [ ] Verify the clarification question lists real block options (e.g.
Gmail, Slack, Google Docs) rather than abstract options

---------

Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
2026-04-01 13:32:12 +00:00
seer-by-sentry[bot]
bd9e9ec614 fix(frontend): remove LaunchDarkly local storage bootstrapping (#12606)
### Why / What / How

<!-- Why: Why does this PR exist? What problem does it solve, or what's
broken/missing without it? -->
This PR fixes
[BUILDER-7HD](https://sentry.io/organizations/significant-gravitas/issues/7374387984/).
The issue was that: LaunchDarkly SDK fails to construct streaming URL
due to non-string `_url` from malformed `localStorage` bootstrap data.
<!-- What: What does this PR change? Summarize the changes at a high
level. -->
Removed the `bootstrap: "localStorage"` option from the LaunchDarkly
provider configuration.
<!-- How: How does it work? Describe the approach, key implementation
details, or architecture decisions. -->
This change ensures that LaunchDarkly no longer attempts to load initial
feature flag values from local storage. Flag values will now always be
fetched directly from the LaunchDarkly service, preventing potential
issues with stale local storage data.

### Changes 🏗️

<!-- List the key changes. Keep it higher level than the diff but
specific enough to highlight what's new/modified. -->
- Removed the `bootstrap: "localStorage"` option from the LaunchDarkly
provider configuration.
- LaunchDarkly will now always fetch flag values directly from its
service, bypassing local storage.

### Checklist 📋

#### For code changes:
- [x] 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:
  <!-- Put your test plan here: -->
- [ ] Verify that LaunchDarkly flags are loaded correctly without
issues.
- [ ] Ensure no errors related to `localStorage` or streaming URL
construction appear in the console.

<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:

- [ ] `.env.default` is updated or already compatible with my changes
- [ ] `docker-compose.yml` is updated or already compatible with my
changes
- [ ] 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>

---------

Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
Co-authored-by: seer-by-sentry[bot] <157164994+seer-by-sentry[bot]@users.noreply.github.com>
2026-04-01 19:12:54 +07:00
Nicholas Tindle
88589764b5 dx(platform): normalize agent instructions for Claude and Codex (#12592)
### Why / What / How

Why: repo guidance was split between Claude-specific `CLAUDE.md` files
and Codex-specific `AGENTS.md` files, which duplicated instruction
content and made the same repository behave differently across agents.
The repo also had Claude skills under `.claude/skills` but no
Codex-visible repo skill path.

What: this PR bridges the repo's Claude skills into Codex and normalizes
shared instruction files so `AGENTS.md` becomes the canonical source
while each `CLAUDE.md` imports its sibling `AGENTS.md`.

How: add a repo-local `.agents/skills` symlink pointing to
`../.claude/skills`; move nested `CLAUDE.md` content into sibling
`AGENTS.md` files; replace each repo `CLAUDE.md` with a one-line
`@AGENTS.md` shim so Claude and Codex read the same scoped guidance
without duplicating text. The root `CLAUDE.md` now imports the root
`AGENTS.md` rather than symlinking to it.

Note: the instruction-file normalization commit was created with
`--no-verify` because the repo's frontend pre-commit `tsc` hook
currently fails on unrelated existing errors, largely missing
`autogpt_platform/frontend/src/app/api/__generated__/*` modules.

### Changes 🏗️

- Add `.agents/skills` as a repo-local symlink to `../.claude/skills` so
Codex discovers the existing Claude repo skills.
- Add a real root `CLAUDE.md` shim that imports the canonical root
`AGENTS.md`.
- Promote nested scoped instruction content into sibling `AGENTS.md`
files under `autogpt_platform/`, `autogpt_platform/backend/`,
`autogpt_platform/frontend/`, `autogpt_platform/frontend/src/tests/`,
and `docs/`.
- Replace the corresponding nested `CLAUDE.md` files with one-line
`@AGENTS.md` shims.
- Preserve the existing scoped instruction hierarchy while making the
shared content cross-compatible between Claude and Codex.

### 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 `.agents/skills` resolves to `../.claude/skills`
  - [x] Verified each repo `CLAUDE.md` now contains only `@AGENTS.md`
- [x] Verified the expected `AGENTS.md` files exist at the root and
nested scoped directories
- [x] Verified the branch contains only the intended agent-guidance
commits relative to `dev` and the working tree is clean

#### 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 runtime configuration changes are included in this PR.

<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> **Low Risk**
> Low risk: documentation/instruction-file reshuffle plus an
`.agents/skills` pointer; no runtime code paths are modified.
> 
> **Overview**
> Unifies agent guidance so **`AGENTS.md` becomes canonical** and all
corresponding `CLAUDE.md` files become 1-line shims (`@AGENTS.md`) at
the repo root, `autogpt_platform/`, backend, frontend, frontend tests,
and `docs/`.
> 
> Adds `.agents/skills` pointing to `../.claude/skills` so non-Claude
agents discover the same shared skills/instructions, eliminating
duplicated/agent-specific guidance content.
> 
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
839483c3b6. This will update automatically
on new commits. Configure
[here](https://cursor.com/dashboard?tab=bugbot).</sup>
<!-- /CURSOR_SUMMARY -->
2026-04-01 09:08:51 +00:00
Zamil Majdy
c659f3b058 fix(copilot): fix dry-run simulation showing INCOMPLETE/error status (#12580)
## Summary
- **Backend**: Strip empty `error` pins from dry-run simulation outputs
that the simulator always includes (set to `""` meaning "no error").
This was causing the LLM to misinterpret successful simulations as
failures and report "INCOMPLETE" status to users
- **Backend**: Add explicit "Status: COMPLETED" to dry-run response
message to prevent LLM misinterpretation
- **Backend**: Update simulation prompt to exclude `error` from the
"MUST include" keys list, and instruct LLM to omit error unless
simulating a logical failure
- **Frontend**: Fix `isRunBlockErrorOutput()` type guard that was too
broad (`"error" in output` matched BlockOutputResponse objects, not just
ErrorResponse), causing dry-run results to be displayed as errors
- **Frontend**: Fix `parseOutput()` fallback matching to not classify
BlockOutputResponse as ErrorResponse
- **Frontend**: Filter out empty error pins from `BlockOutputCard`
display and accordion metadata output key counting
- **Frontend**: Clear stale execution results before dry-run/no-input
runs so the UI shows fresh output
- **Frontend**: Fix first-click simulate race condition by invalidating
execution details query after WebSocket subscription confirms

## Test plan
- [x] All 12 existing + 5 new dry-run tests pass (`poetry run pytest
backend/copilot/tools/test_dry_run.py -x -v`)
- [x] All 23 helpers tests pass (`poetry run pytest
backend/copilot/tools/helpers_test.py -x -v`)
- [x] All 13 run_block tests pass (`poetry run pytest
backend/copilot/tools/run_block_test.py -x -v`)
- [x] Backend linting passes (ruff check + format)
- [x] Frontend linting passes (next lint)
- [ ] Manual: trigger dry-run on a block with error output pin (e.g.
Komodo Image Generator) — should show "Simulated" status with clean
output, no misleading "error" section
- [ ] Manual: first click on Simulate button should immediately show
results (no race condition)

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: Nicholas Tindle <nicholas.tindle@agpt.co>
Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
2026-03-31 21:03:00 +00:00
Zamil Majdy
80581a8364 fix(copilot): add tool call circuit breakers and intermediate persistence (#12604)
## Why

CoPilot session `d2f7cba3` took **82 minutes** and cost **$20.66** for a
single user message. Root causes:
1. Redis session meta key expired after 1h, making the session invisible
to the resume endpoint — causing empty page on reload
2. Redis stream key also expired during sub-agent gaps (task_progress
events produced no chunks)
3. No intermediate persistence — session messages only saved to DB after
the entire turn completes
4. Sub-agents retried similar WebSearch queries (addressed via prompt
guidance)

## What

### Redis TTL fixes (root cause of empty session on reload)
- `publish_chunk()` now periodically refreshes **both** the session meta
key AND stream key TTL (every 60s).
- `task_progress` SDK events now emit `StreamHeartbeat` chunks, ensuring
`publish_chunk` is called even during long sub-agent gaps where no real
chunks are produced.
- Without this fix, turns exceeding the 1h `stream_ttl` lose their
"running" status and stream data, making `get_active_session()` return
False.

### Intermediate DB persistence
- Session messages flushed to DB every **30 seconds** or **10 new
messages** during the stream loop.
- Uses `asyncio.shield(upsert_chat_session())` matching the existing
`finally` block pattern.

### Orphaned message cleanup on rollback
- On stream attempt rollback, orphaned messages persisted by
intermediate flushes are now cleaned up from the DB via
`delete_messages_from_sequence`.
- Prevents stale messages from resurfacing on page reload after a failed
retry.

### Prompt guidance
- Added web search best practices to code supplement (search efficiency,
sub-agent scope separation).

### Approach: root cause fixes, not capability limits
- **No tool call caps** — artificial limits on WebSearch or total tool
calls would reduce autopilot capability without addressing why searches
were redundant.
- **Task tool remains enabled** — sub-agent delegation via Task is a
core capability. The existing `max_subtasks` concurrency guard is
sufficient.
- The real fixes (TTL refresh, persistence, prompt guidance) address the
underlying bugs and behavioral issues.

## How

### Files changed
- `stream_registry.py` — Redis meta + stream key TTL refresh in
`publish_chunk()`, module-level keepalive tracker
- `response_adapter.py` — `task_progress` SystemMessage →
StreamHeartbeat emission
- `service.py` — Intermediate DB persistence in `_run_stream_attempt`
stream loop, orphan cleanup on rollback
- `db.py` — `delete_messages_from_sequence` for rollback cleanup
- `prompting.py` — Web search best practices

### GCP log evidence
```
# Meta key expired during 82-min turn:
09:49 — GET_SESSION: active_session=False, msg_count=1  ← meta gone
10:18 — Session persisted in finally with 189 messages   ← turn completed

# T13 (1h45min) same bug reproduced live:
16:20 — task_progress events still arriving, but active_session=False

# Actual cost:
Turn usage: cache_read=347916, cache_create=212472, output=12375, cost_usd=20.66
```

### Test plan
- [x] task_progress emits StreamHeartbeat
- [x] Task background blocked, foreground allowed, slot release on
completion/failure
- [x] CI green (lint, type-check, tests, e2e, CodeQL)

---------

Co-authored-by: Zamil Majdy <majdy.zamil@gmail.com>
2026-03-31 21:01:56 +00:00
lif
3c046eb291 fix(frontend): show all agent outputs instead of only the last one (#12504)
Fixes #9175

### Changes 🏗️

The Agent Outputs panel only displayed the last execution result per
output node, discarding all prior outputs during a run.

**Root cause:** In `AgentOutputs.tsx`, the `outputs` useMemo extracted
only the last element from `nodeExecutionResults`:
```tsx
const latestResult = executionResults[executionResults.length - 1];
```

**Fix:** Changed `.map()` to `.flatMap()` over output nodes, iterating
through all `executionResults` for each node. Each execution result now
gets its own renderer lookup and metadata entry, so the panel shows
every output produced during the run.

### 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 TypeScript compiles without errors
- [x] Confirmed the flatMap logic correctly iterates all execution
results
  - [x] Verified existing filter for null renderers is preserved
- [x] Run an agent with multiple outputs and confirm all show in the
panel

---------

Signed-off-by: majiayu000 <1835304752@qq.com>
Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
2026-03-31 20:31:12 +00:00
Zamil Majdy
3e25488b2d feat(copilot): add session-level dry_run flag to autopilot sessions (#12582)
## Summary
- Adds a session-level `dry_run` flag that forces ALL tool calls
(`run_block`, `run_agent`) in a copilot/autopilot session to use dry-run
simulation mode
- Stores the flag in a typed `ChatSessionMetadata` JSON model on the
`ChatSession` DB row, accessed via `session.dry_run` property
- Adds `dry_run` to the AutoPilot block Input schema so graph builders
can create dry-run autopilot nodes
- Refactors multiple copilot tools from `**kwargs` to explicit
parameters for type safety

## Changes
- **Prisma schema**: Added `metadata` JSON column to `ChatSession` model
with migration
- **Python models**: Added `ChatSessionMetadata` model with `dry_run`
field, added `metadata` field to `ChatSessionInfo` and `ChatSession`,
updated `from_db()`, `new()`, and `create_chat_session()`
- **Session propagation**: `set_execution_context(user_id, session)`
called from `baseline/service.py` so tool handlers can read
session-level flags via `session.dry_run`
- **Tool enforcement**: `run_block` and `run_agent` check
`session.dry_run` and force `dry_run=True` when set; `run_agent` blocks
scheduling in dry-run sessions
- **AutoPilot block**: Added `dry_run` input field, passes it when
creating sessions
- **Chat API**: Added `CreateSessionRequest` model with `dry_run` field
to `POST /sessions` endpoint; added `metadata` to session responses
- **Frontend**: Updated `useChatSession.ts` to pass body to the create
session mutation
- **Tool refactoring**: Multiple copilot tools refactored from
`**kwargs` to explicit named parameters (agent_browser, manage_folders,
workspace_files, connect_integration, agent_output, bash_exec, etc.) for
better type safety

## Test plan
- [x] Unit tests for `ChatSession.new()` with dry_run parameter
- [x] Unit tests for `RunBlockTool` session dry_run override
- [x] Unit tests for `RunAgentTool` session dry_run override
- [x] Unit tests for session dry_run blocks scheduling
- [x] Existing dry_run tests still pass (12/12)
- [x] Existing permissions tests still pass
- [x] All pre-commit hooks pass (ruff, isort, pyright, tsc)
- [ ] Manual: Create autopilot session with `dry_run=True`, verify
run_block/run_agent calls use simulation

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-31 16:27:36 +00:00
Abhimanyu Yadav
57b17dc8e1 feat(platform): generic managed credential system with AgentMail auto-provisioning (#12537)
### Why / What / How

**Why:** We need a third credential type: **system-provided but unique
per user** (managed credentials). Currently we have system credentials
(same for all users) and user credentials (user provides their own
keys). Managed credentials bridge the gap — the platform provisions them
automatically, one per user, for integrations like AgentMail where each
user needs their own pod-scoped API key.

**What:**
- Generic **managed credential provider registry** — any integration can
register a provider that auto-provisions per-user credentials
- **AgentMail** is the first consumer: creates a pod + pod-scoped API
key using the org-level API key
- Managed credentials appear in the credential dropdown like normal API
keys but with `autogpt_managed=True` — users **cannot update or delete**
them
- **Auto-provisioning** on `GET /credentials` — lazily creates managed
credentials when users browse their credential list
- **Account deletion cleanup** utility — revokes external resources
(pods, API keys) before user deletion
- **Frontend UX** — hides the delete button for managed credentials on
the integrations page

**How:**

### Backend

**New files:**
- `backend/integrations/managed_credentials.py` —
`ManagedCredentialProvider` ABC, global registry,
`ensure_managed_credentials()` (with per-user asyncio lock +
`asyncio.gather` for concurrency), `cleanup_managed_credentials()`
- `backend/integrations/managed_providers/__init__.py` —
`register_all()` called at startup
- `backend/integrations/managed_providers/agentmail.py` —
`AgentMailManagedProvider` with `provision()` (creates pod + API key via
agentmail SDK) and `deprovision()` (deletes pod)

**Modified files:**
- `credentials_store.py` — `autogpt_managed` guards on update/delete,
`has_managed_credential()` / `add_managed_credential()` helpers
- `model.py` — `autogpt_managed: bool` + `metadata: dict` on
`_BaseCredentials`
- `router.py` — calls `ensure_managed_credentials()` in list endpoints,
removed explicit `/agentmail/connect` endpoint
- `user.py` — `cleanup_user_managed_credentials()` for account deletion
- `rest_api.py` — registers managed providers at startup
- `settings.py` — `agentmail_api_key` setting

### Frontend
- Added `autogpt_managed` to `CredentialsMetaResponse` type
- Conditionally hides delete button on integrations page for managed
credentials

### Key design decisions
- **Auto-provision in API layer, not data layer** — keeps
`get_all_creds()` side-effect-free
- **Race-safe** — per-(user, provider) asyncio lock with double-check
pattern prevents duplicate pods
- **Idempotent** — AgentMail SDK `client_id` ensures pod creation is
idempotent; `add_managed_credential()` uses upsert under Redis lock
- **Error-resilient** — provisioning failures are logged but never block
credential listing

### Changes 🏗️

| File | Action | Description |
|------|--------|-------------|
| `backend/integrations/managed_credentials.py` | NEW | ABC, registry,
ensure/cleanup |
| `backend/integrations/managed_providers/__init__.py` | NEW | Registers
all providers at startup |
| `backend/integrations/managed_providers/agentmail.py` | NEW |
AgentMail provisioning/deprovisioning |
| `backend/integrations/credentials_store.py` | MODIFY | Guards +
managed credential helpers |
| `backend/data/model.py` | MODIFY | `autogpt_managed` + `metadata`
fields |
| `backend/api/features/integrations/router.py` | MODIFY |
Auto-provision on list, removed `/agentmail/connect` |
| `backend/data/user.py` | MODIFY | Account deletion cleanup |
| `backend/api/rest_api.py` | MODIFY | Provider registration at startup
|
| `backend/util/settings.py` | MODIFY | `agentmail_api_key` setting |
| `frontend/.../integrations/page.tsx` | MODIFY | Hide delete for
managed creds |
| `frontend/.../types.ts` | MODIFY | `autogpt_managed` field |

### 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] 23 tests pass in `router_test.py` (9 new tests for
ensure/cleanup/auto-provisioning)
  - [x] `poetry run format && poetry run lint` — clean
  - [x] OpenAPI schema regenerated
- [x] Manual: verify managed credential appears in AgentMail block
dropdown
  - [x] Manual: verify delete button hidden for managed credentials
- [x] Manual: verify managed credential cannot be deleted via API (403)

#### For configuration changes:
- [x] `.env.default` is updated with `AGENTMAIL_API_KEY=`

---------

Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
2026-03-31 12:56:18 +00:00
Krishna Chaitanya
a20188ae59 fix(blocks): validate non-empty input in AIConversationBlock before LLM call (#12545)
### Why / What / How

**Why:** When `AIConversationBlock` receives an empty messages list and
an empty prompt, the block blindly forwards the empty array to the
downstream LLM API, which returns a cryptic `400 Bad Request` error:
`"Invalid 'messages': empty array. Expected an array with minimum length
1."` This is confusing for users who don't understand why their agent
failed.

**What:** Add early input validation in `AIConversationBlock.run()` that
raises a clear `ValueError` when both `messages` and `prompt` are empty.
Also add three unit tests covering the validation logic.

**How:** A simple guard clause at the top of the `run` method checks `if
not input_data.messages and not input_data.prompt` before the LLM call
is made. If both are empty, a descriptive `ValueError` is raised. If
either one has content, the block proceeds normally.

### Changes

- `autogpt_platform/backend/backend/blocks/llm.py`: Add validation guard
in `AIConversationBlock.run()` to reject empty messages + empty prompt
before calling the LLM
- `autogpt_platform/backend/backend/blocks/test/test_llm.py`: Add
`TestAIConversationBlockValidation` with three tests:
- `test_empty_messages_and_empty_prompt_raises_error` — validates the
guard clause
- `test_empty_messages_with_prompt_succeeds` — ensures prompt-only usage
still works
- `test_nonempty_messages_with_empty_prompt_succeeds` — ensures
messages-only usage still works

### 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] Lint passes (`ruff check`)
  - [x] Formatting passes (`ruff format`)
- [x] New unit tests validate the empty-input guard and the happy paths

Closes #11875

---------

Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
2026-03-31 12:43:42 +00:00
goingforstudying-ctrl
c410be890e fix: add empty choices guard in extract_openai_tool_calls() (#12540)
## Summary

`extract_openai_tool_calls()` in `llm.py` crashes with `IndexError` when
the LLM provider returns a response with an empty `choices` list.

### Changes 🏗️

- Added a guard check `if not response.choices: return None` before
accessing `response.choices[0]`
- This is consistent with the function's existing pattern of returning
`None` when no tool calls are found

### Bug Details

When an LLM provider returns a response with an empty choices list
(e.g., due to content filtering, rate limiting, or API errors),
`response.choices[0]` raises `IndexError`. This can crash the entire
agent execution pipeline.

### 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:
- Verified that the function returns `None` when `response.choices` is
empty
- Verified existing behavior is unchanged when `response.choices` is
non-empty

---------

Co-authored-by: goingforstudying-ctrl <forgithubuse@gmail.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
2026-03-31 20:10:27 +07:00
Zamil Majdy
37d9863552 feat(platform): add extended thinking execution mode to OrchestratorBlock (#12512)
## Summary
- Adds `ExecutionMode` enum with `BUILT_IN` (default built-in tool-call
loop) and `EXTENDED_THINKING` (delegates to Claude Agent SDK for richer
reasoning)
- Extracts shared `tool_call_loop` into `backend/util/tool_call_loop.py`
— reusable by both OrchestratorBlock agent mode and copilot baseline
- Refactors copilot baseline to use the shared `tool_call_loop` with
callback-driven iteration

## ExecutionMode enum
`ExecutionMode` (`backend/blocks/orchestrator.py`) controls how
OrchestratorBlock executes tool calls:
- **`BUILT_IN`** — Default mode. Runs the built-in tool-call loop
(supports all LLM providers).
- **`EXTENDED_THINKING`** — Delegates to the Claude Agent SDK for
extended thinking and multi-step planning. Requires Anthropic-compatible
providers (`anthropic` / `open_router`) and direct API credentials
(subscription mode not supported). Validates both provider and model
name at runtime.

## Shared tool_call_loop
`backend/util/tool_call_loop.py` provides a generic, provider-agnostic
conversation loop:
1. Call LLM with tools → 2. Extract tool calls → 3. Execute tools → 4.
Update conversation → 5. Repeat

Callers provide three callbacks:
- `llm_call`: wraps any LLM provider (OpenAI streaming, Anthropic,
llm.llm_call, etc.)
- `execute_tool`: wraps any tool execution (TOOL_REGISTRY, graph block
execution, etc.)
- `update_conversation`: formats messages for the specific protocol

## OrchestratorBlock EXTENDED_THINKING mode
- `_create_graph_mcp_server()` converts graph-connected blocks to MCP
tools
- `_execute_tools_sdk_mode()` runs `ClaudeSDKClient` with those MCP
tools
- Agent mode refactored to use shared `tool_call_loop`

## Copilot baseline refactored
- Streaming callbacks buffer `Stream*` events during loop execution
- Events are drained after `tool_call_loop` returns
- Same conversation logic, less code duplication

## SDK environment builder extraction
- `build_sdk_env()` extracted to `backend/copilot/sdk/env.py` for reuse
by both copilot SDK service and OrchestratorBlock

## Provider validation
EXTENDED_THINKING mode validates `provider in ('anthropic',
'open_router')` and `model_name.startswith('claude')` because the Claude
Agent SDK requires an Anthropic API key or OpenRouter key. Subscription
mode is not supported — it uses the platform's internal credit system
which doesn't provide raw API keys needed by the SDK. The validation
raises a clear `ValueError` if an unsupported provider or model is used.

## PR Dependencies
This PR builds on #12511 (Claude SDK client). It can be reviewed
independently — #12511 only adds the SDK client module which this PR
imports. If #12511 merges first, this PR will have no conflicts.

### 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 pre-commit hooks pass (typecheck, lint, format)
  - [x] Existing OrchestratorBlock tests still pass
- [x] Copilot baseline behavior unchanged (same stream events, same tool
execution)
- [x] Manual: OrchestratorBlock with execution_mode=EXTENDED_THINKING +
downstream blocks → SDK calls tools
  - [x] Agent mode regression test (non-SDK path works as before)
  - [x] SDK mode error handling (invalid provider raises ValueError)
2026-03-31 20:04:13 +07:00
Krishna Chaitanya
2f42ff9b47 fix(blocks): validate email recipients in Gmail blocks before API call (#12546)
### Why / What / How

**Why:** When a user or LLM supplies a malformed recipient string (e.g.
a bare username, a JSON blob, or an empty value) to `GmailSendBlock`,
`GmailCreateDraftBlock`, or any reply block, the Gmail API returns an
opaque `HttpError 400: "Invalid To header"`. This surfaces as a
`BlockUnknownError` with no actionable guidance, making it impossible
for the LLM to self-correct. (Fixes #11954)

**What:** Adds a lightweight `validate_email_recipients()` function that
checks every recipient against a simplified RFC 5322 pattern
(`local@domain.tld`) and raises a clear `ValueError` listing all invalid
entries before any API call is made.

**How:** The validation is called in two shared code paths —
`create_mime_message()` (used by send and draft blocks) and
`_build_reply_message()` (used by reply blocks) — so all Gmail blocks
that compose outgoing email benefit from it with zero per-block changes.
The regex is intentionally permissive (any `x@y.z` passes) to avoid
false positives on unusual but valid addresses.

### Changes 🏗️

- Added `validate_email_recipients()` helper in `gmail.py` with a
compiled regex
- Hooked validation into `create_mime_message()` for `to`, `cc`, and
`bcc` fields
- Hooked validation into `_build_reply_message()` for reply/draft-reply
blocks
- Added `TestValidateEmailRecipients` test class covering valid,
invalid, mixed, empty, JSON-string, and field-name scenarios

### 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 `validate_email_recipients` correctly accepts valid
emails (`user@example.com`, `a@b.com`, `test@sub.domain.co`)
- [x] Verified it rejects malformed entries (bare names, missing domain
dot, empty strings, JSON strings)
- [x] Verified error messages include the field name and all invalid
entries
  - [x] Verified empty recipient lists pass without error
  - [x] Confirmed `gmail.py` and test file parse correctly (AST check)

---------

Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
2026-03-31 12:37:33 +00:00
Zamil Majdy
914efc53e5 fix(backend): disambiguate duplicate tool names in OrchestratorBlock (#12555)
## Why
The OrchestratorBlock fails with `Tool names must be unique` when
multiple nodes use the same block type (e.g., two "Web Search" blocks
connected as tools). The Anthropic API rejects the request because
duplicate tool names are sent.

## What
- Detect duplicate tool names after building tool signatures
- Append `_1`, `_2`, etc. suffixes to disambiguate
- Enrich descriptions of duplicate tools with their hardcoded default
values so the LLM can distinguish between them
- Clean up internal `_hardcoded_defaults` metadata before sending to API
- Exclude sensitive/credential fields from default value descriptions

## How
- After `_create_tool_node_signatures` builds all tool functions, count
name occurrences
- For duplicates: rename with suffix and append `[Pre-configured:
key=value]` to description using the node's `input_default` (excluding
linked fields that the LLM provides)
- Added defensive `isinstance(defaults, dict)` check for compatibility
with test mocks
- Suffix collision avoidance: skips candidates that collide with
existing tool names
- Long tool names truncated to fit within 64-character API limit
- 47 unit tests covering: basic dedup, description enrichment, unique
names unchanged, no metadata leaks, single tool, triple duplicates,
linked field exclusion, mixed unique/duplicate scenarios, sensitive
field exclusion, long name truncation, suffix collision, malformed
tools, missing description, empty list, 10-tool all-same-name, multiple
distinct groups, large default truncation, suffix collision cascade,
parameter preservation, boundary name lengths, nested dict/list
defaults, null defaults, customized name priority, required fields

## Test plan
- [x] All 47 tests in `test_orchestrator_tool_dedup.py` pass
- [x] All 11 existing orchestrator unit tests pass (dict, dynamic
fields, responses API)
- [x] Pre-commit hooks pass (ruff, black, isort, pyright)
- [ ] Manual test: connect two same-type blocks to an orchestrator and
verify the LLM call succeeds

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-31 11:54:10 +00:00
Carson Kahn
17e78ca382 fix(docs): remove extraneous whitespace in README (#12587)
### Why / What / How

Remove extraneous whitespace in README.md:
- "Workflow Management" description: extra spaces between "block" and
"performs"
- "Agent Interaction" description: extra spaces between "user-friendly"
and "interface"

---------

Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
2026-03-31 08:38:45 +00:00
Ubbe
7ba05366ed feat(platform/copilot): live timer stats with persisted duration (#12583)
## Why

The copilot chat had no indication of how long the AI spent "thinking"
on a response. Users couldn't tell if a long wait was normal or
something was stuck. Additionally, the thinking duration was lost on
page reload since it was only tracked client-side.

## What

- **Live elapsed timer**: Shows elapsed time ("23s", "1m 5s") in the
ThinkingIndicator while the AI is processing (appears after 20s to avoid
spam on quick responses)
- **Frozen "Thought for Xm Ys"**: Displays the final thinking duration
in TurnStatsBar after the response completes
- **Persisted duration**: Saves `durationMs` on the last assistant
message in the DB so the timer survives page reloads

## How

**Backend:**
- Added `durationMs Int?` column to `ChatMessage` (Prisma migration)
- `mark_session_completed` in `stream_registry.py` computes wall-clock
duration from Redis session `created_at` and saves it via
`DatabaseManager.set_turn_duration()`
- Invalidates Redis session cache after writing so GET returns fresh
data

**Frontend:**
- `useElapsedTimer` hook tracks client-side elapsed seconds during
streaming
- `ThinkingIndicator` shows only the elapsed time (no phrases) after
20s, with `font-mono text-sm` styling
- `TurnStatsBar` displays "Thought for Xs" after completion, preferring
live `elapsedSeconds` and falling back to persisted `durationMs`
- `convertChatSessionToUiMessages` extracts `duration_ms` from
historical messages into a `Map<string, number>` threaded through to
`ChatMessagesContainer`

## Test plan

- [ ] Send a message in copilot — verify ThinkingIndicator shows elapsed
time after 20s
- [ ] After response completes — verify "Thought for Xs" appears below
the response
- [ ] Refresh the page — verify "Thought for Xs" still appears
(persisted from DB)
- [ ] Check older conversations — they should NOT show timer (no
historical data)
- [ ] Verify no Zod/SSE validation errors in browser console

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

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-30 16:46:31 +07:00
Zamil Majdy
ca74f980c1 fix(copilot): resolve host-scoped credentials for authenticated web requests (#12579)
## Summary
- Fixed `_resolve_discriminated_credentials()` in `helpers.py` to handle
URL/host-based credential discrimination (used by
`SendAuthenticatedWebRequestBlock`)
- Previously, only provider-based discrimination (with
`discriminator_mapping`) was handled; URL-based discrimination (with
`discriminator` set but no `discriminator_mapping`) was silently skipped
- This caused host-scoped credentials to either match the wrong host or
fail to match at all when the CoPilot called `run_block` for
authenticated HTTP requests
- Added 14 targeted tests covering discriminator resolution, host
matching, credential resolution integration, and RunBlockTool end-to-end
flows

## Root Cause
`_resolve_discriminated_credentials()` checked `if
field_info.discriminator and field_info.discriminator_mapping:` which
excluded host-scoped credentials where `discriminator="url"` but
`discriminator_mapping=None`. The URL from `input_data` was never added
to `discriminator_values`, so `_credential_is_for_host()` received empty
`discriminator_values` and returned `True` for **any** host-scoped
credential regardless of URL match.

## Fix
When `discriminator` is set without `discriminator_mapping`, the URL
value from `input_data` is now copied into `discriminator_values` on a
shallow copy of the field info (to avoid mutating the cached schema).
This enables `_credential_is_for_host()` to properly match the
credential's host against the target URL.

## Test plan
- [x] `TestResolveDiscriminatedCredentials` - 4 tests verifying URL
discriminator populates values, handles missing URL, doesn't mutate
original, preserves provider/type
- [x] `TestFindMatchingHostScopedCredential` - 5 tests verifying
correct/wrong host matching, wildcard hosts, multiple credential
selection
- [x] `TestResolveBlockCredentials` - 3 integration tests verifying full
credential resolution with matching/wrong/missing hosts
- [x] `TestRunBlockToolAuthenticatedHttp` - 2 end-to-end tests verifying
SetupRequirementsResponse when creds missing and BlockDetailsResponse
when creds matched
- [x] All 28 existing + new tests pass
- [x] Ruff lint, isort, Black formatting, pyright typecheck all pass

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-28 08:12:33 +00:00
Zamil Majdy
68f5d2ad08 fix(blocks): raise AIConditionBlock errors instead of swallowing them (#12593)
## Why

Sentry alert
[AUTOGPT-SERVER-8C8](https://significant-gravitas.sentry.io/issues/7367978095/)
— `AIConditionBlock` failing in prod with:

```
Invalid 'max_output_tokens': integer below minimum value.
Expected a value >= 16, but got 10 instead.
```

Two problems:
1. `max_tokens=10` is below OpenAI's new minimum of 16
2. The `except Exception` handler was calling `logger.error()` which
triggered Sentry for what are known block errors, AND silently
defaulting to `result=False` — making the block appear to succeed with
an incorrect answer

## What

- Bump `max_tokens` from 10 to 16 (fixes the root cause)
- Remove the `try/except` entirely — the executor already handles
exceptions correctly (`ValueError` = known/no Sentry, everything else =
unknown/Sentry). The old handler was just swallowing errors and
producing wrong results.

## Test plan

- [x] Existing `AIConditionBlock` tests pass (block only expects
"true"/"false", 16 tokens is plenty)
- [x] No more silent `result=False` on errors
- [x] No more spurious Sentry alerts from `logger.error()`

Fixes AUTOGPT-SERVER-8C8

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

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-27 10:28:14 +00:00
Nicholas Tindle
2b3d730ca9 dx(skills): add /open-pr and /setup-repo skills (#12591)
### Why / What / How

**Why:** Agents working in worktrees lack guidance on two of the most
common workflows: properly opening PRs (using the repo template,
validating test coverage, triggering the review bot) and bootstrapping
the repo from scratch with a worktree-based layout. Without these
skills, agents either skip steps (no test plan, wrong template) or
require manual hand-holding for setup.

**What:** Adds two new Claude Code skills under `.claude/skills/`:
- `/open-pr` — A structured PR creation workflow that enforces the
canonical `.github/PULL_REQUEST_TEMPLATE.md`, validates test coverage
for existing and new behaviors, supports a configurable base branch, and
integrates the `/review` bot workflow for agents without local testing
capability. Cross-references `/pr-test`, `/pr-review`, and `/pr-address`
for the full PR lifecycle.
- `/setup-repo` — An interactive repo bootstrapping skill that creates a
worktree-based layout (main + reviews + N numbered work branches).
Handles .env file provisioning with graceful fallbacks (.env.default,
.env.example), copies branchlet config, installs dependencies, and is
fully idempotent (safe to re-run).

**How:** Markdown-based SKILL.md files following the existing skill
conventions. Both skills use proper bash patterns (seq-based loops
instead of brace expansion with variables, existence checks before
branch/worktree creation, error reporting on install failures).
`/open-pr` delegates to AskUserQuestion-style prompts for base branch
selection. `/setup-repo` uses AskUserQuestion for interactive branch
count and base branch selection.

### Changes 🏗️

- Added `.claude/skills/open-pr/SKILL.md` — PR creation workflow with:
  - Pre-flight checks (committed, pushed, formatted)
- Test coverage validation (existing behavior not broken, new behavior
covered)
- Canonical PR template enforcement (read and fill verbatim, no
pre-checked boxes)
  - Configurable base branch (defaults to dev)
- Review bot workflow (`/review` comment + 30min wait) for agents
without local testing
  - Related skills table linking `/pr-test`, `/pr-review`, `/pr-address`

- Added `.claude/skills/setup-repo/SKILL.md` — Repo bootstrap workflow
with:
- Interactive setup (branch count: 4/8/16/custom, base branch selection)
- Idempotent branch creation (skips existing branches with info message)
  - Idempotent worktree creation (skips existing directories)
- .env provisioning with fallback chain (.env → .env.default →
.env.example → warning)
  - Branchlet config propagation
  - Dependency installation with success/failure reporting per worktree

### 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 SKILL.md frontmatter follows existing skill conventions
  - [x] Verified trigger conditions match expected user intents
  - [x] Verified cross-references to existing skills are accurate
- [x] Verified PR template section matches
`.github/PULL_REQUEST_TEMPLATE.md`
- [x] Verified bash snippets use correct patterns (seq, show-ref, quoted
vars)
  - [x] Pre-commit hooks pass on all commits
  - [x] Addressed all CodeRabbit, Sentry, and Cursor review comments

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

<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> **Low Risk**
> Low risk documentation-only change: adds new markdown skills without
modifying runtime code. Main risk is workflow guidance drift (e.g.,
`.env`/worktree steps) if it diverges from actual repo conventions.
> 
> **Overview**
> Adds two new Claude Code skills under `.claude/skills/` to standardize
common developer workflows.
> 
> `/open-pr` documents a PR creation flow that enforces using
`.github/PULL_REQUEST_TEMPLATE.md` verbatim, calls out required test
coverage, and describes how to trigger/poll the `/review` bot when local
testing isn’t available.
> 
> `/setup-repo` documents an idempotent, interactive bootstrap for a
multi-worktree layout (creates `reviews` and `branch1..N`, provisions
`.env` files with `.env.default`/`.env.example` fallbacks, copies
`.branchlet.json`, and installs dependencies), complementing the
existing `/worktree` skill.
> 
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
80dbeb1596. 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>
Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
2026-03-27 10:22:03 +00:00
Zamil Majdy
f28628e34b fix(backend): preserve thinking blocks during transcript compaction (#12574)
## Why

AutoPilot users hit `invalid_request_error` ("thinking or
redacted_thinking blocks in the latest assistant message cannot be
modified") when sessions get long enough to trigger transcript
compaction. The Anthropic API requires thinking blocks in the last
assistant message to be byte-for-byte identical to the original response
— our compaction was flattening them to plain text, destroying the
cryptographic signatures.

Reported in Discord `#breakage` by John Ababseh with session
`31d3f08a-cb94-45eb-9fce-56b3f0287ef4`.

## What

- **`compact_transcript`** now splits the transcript into a compressible
prefix and a preserved tail (last assistant entry + trailing entries).
Only the prefix is compressed; the tail is re-appended verbatim,
preserving thinking blocks exactly.
- **`_flatten_assistant_content`** now silently drops `thinking` and
`redacted_thinking` blocks instead of creating `[__thinking__]`
placeholders — they carry no useful context for compression summaries.
- **`response_adapter`** explicitly handles `ThinkingBlock` (skip
gracefully instead of silently falling through the isinstance chain).
- **`_format_sdk_content_blocks`** now passes through raw dict blocks
(e.g. `redacted_thinking` that the SDK may not have a typed class for)
verbatim to the transcript.

## How

The key insight is the Anthropic API's asymmetric constraint:
- **Last assistant message**: thinking/redacted_thinking blocks must be
preserved byte-for-byte
- **Older assistant messages**: thinking blocks can be removed entirely

`compact_transcript` uses `_find_last_assistant_entry()` to split the
JSONL into two parts:
1. **Prefix** (everything before the last assistant): flattened and
compressed normally
2. **Tail** (last assistant + any trailing user message): preserved
verbatim and re-chained via `_rechain_tail()` to maintain the
`parentUuid` chain

This ensures the API always sees the original thinking blocks in the
last assistant message while still achieving meaningful compression on
older turns.

## Test plan
- [x] 25 new tests across `thinking_blocks_test.py` (TDD: written before
implementation)
- [x] `_find_last_assistant_entry` splits correctly at last assistant,
handles edges (no assistant, index 0, trailing user)
  - [x] `_rechain_tail` patches parentUuid chain, handles empty tail
- [x] `_flatten_assistant_content` strips thinking/redacted_thinking
blocks, handles mixed content
  - [x] `compact_transcript` preserves last assistant's thinking blocks
- [x] `compact_transcript` strips thinking from older assistant messages
- [x] Edge cases: trailing user message, single assistant, no thinking
blocks
  - [x] `response_adapter` handles ThinkingBlock without crash
- [x] `_format_sdk_content_blocks` preserves thinking block format and
raw dict blocks
- [x] All existing copilot SDK tests pass
- [x] Pre-commit hooks (lint, format, typecheck) all pass
2026-03-27 06:36:52 +00:00
Zamil Majdy
b6a027fd2b fix(platform): fix prod Sentry errors and reduce on-call alert noise (#12565)
## Why

Multiple Sentry issues paging on-call in prod:

1. **AUTOGPT-SERVER-8BP**: `ConversionError: Failed to convert
anthropic/claude-sonnet-4-6 to <enum 'LlmModel'>` — the copilot passes
OpenRouter-style provider-prefixed model names
(`anthropic/claude-sonnet-4-6`) to blocks, but the `LlmModel` enum only
recognizes the bare model ID (`claude-sonnet-4-6`).

2. **BUILDER-7GF**: `Error invoking postEvent: Method not found` —
Sentry SDK internal error on Chrome Mobile Android, not a platform bug.

3. **XMLParserBlock**: `BlockUnknownError raised by XMLParserBlock with
message: Error in input xml syntax` — user sent bad XML but the block
raised `SyntaxError`, which gets wrapped as `BlockUnknownError`
(unexpected) instead of `BlockExecutionError` (expected).

4. **AUTOGPT-SERVER-8BS**: `Virus scanning failed for Screenshot
2026-03-26 091900.png: range() arg 3 must not be zero` — empty (0-byte)
file upload causes `range(0, 0, 0)` in the virus scanner chunking loop,
and the failure is logged at `error` level which pages on-call.

5. **AUTOGPT-SERVER-8BT**: `ValueError: <Token var=<ContextVar
name='current_context'>> was created in a different Context` —
OpenTelemetry `context.detach()` fails when the SDK streaming async
generator is garbage-collected in a different context than where it was
created (client disconnect mid-stream).

6. **AUTOGPT-SERVER-8BW**: `RuntimeError: Attempted to exit cancel scope
in a different task than it was entered in` — anyio's
`TaskGroup.__aexit__` detects cancel scope entered in one task but
exited in another when `GeneratorExit` interrupts the SDK cleanup during
client disconnect.

7. **Workspace UniqueViolationError**: `UniqueViolationError: Unique
constraint failed on (workspaceId, path)` — race condition during
concurrent file uploads handled by `WorkspaceManager._persist_db_record`
retry logic, but Sentry still captures the exception at the raise site.

8. **Library UniqueViolationError**: `UniqueViolationError` on
`LibraryAgent (userId, agentGraphId, agentGraphVersion)` — race
conditions in `add_graph_to_library` and `create_library_agent` caused
crashes or silent data loss.

9. **Graph version collision**: `UniqueViolationError` on `AgentGraph
(id, version)` — copilot re-saving an agent at an existing version
collides with the primary key.

## What

### Backend: `LlmModel._missing_()` for provider-prefixed model names
- Adds `_missing_` classmethod to `LlmModel` enum that strips the
provider prefix (e.g., `anthropic/`) when direct lookup fails
- Self-contained in the enum — no changes to the generic type conversion
system

### Frontend: Filter Sentry SDK noise
- Adds `postEvent: Method not found` to `ignoreErrors` — a known Sentry
SDK issue on certain mobile browsers

### Backend: XMLParserBlock — raise ValueError instead of SyntaxError
- Changed `_validate_tokens()` to raise `ValueError` instead of
`SyntaxError`
- Changed the `except SyntaxError` handler in `run()` to re-raise as
`ValueError`
- This ensures `Block.execute()` wraps XML parsing failures as
`BlockExecutionError` (expected/user-caused) instead of
`BlockUnknownError` (unexpected/alerts Sentry)

### Backend: Virus scanner — handle empty files + reduce alert noise
- Added early return for empty (0-byte) files in `scan_file()` to avoid
`range() arg 3 must not be zero` when `chunk_size` is 0
- Added `max(1, len(content))` guard on `chunk_size` as defense-in-depth
- Downgraded `scan_content_safe` failure log from `error` to `warning`
so single-file scan failures don't page on-call via Sentry

### Backend: Suppress SDK client cleanup errors on SSE disconnect
- Replaced `async with ClaudeSDKClient` in `_run_stream_attempt` with
manual `__aenter__`/`__aexit__` wrapped in new
`_safe_close_sdk_client()` helper
- `_safe_close_sdk_client()` catches `ValueError` (OTEL context token
mismatch) and `RuntimeError` (anyio cancel scope in wrong task) during
`__aexit__` and logs at `debug` level — these are expected when SSE
client disconnects mid-stream
- Added `_is_sdk_disconnect_error()` helper for defense-in-depth at the
outer `except BaseException` handler in `stream_chat_completion_sdk`
- Both Sentry errors (8BT and 8BW) are now suppressed without affecting
normal cleanup flow

### Backend: Filter workspace UniqueViolationError from Sentry alerts
- Added `before_send` filter in `_before_send()` to drop
`UniqueViolationError` events where the message contains `workspaceId`
and `path`
- The error is already handled by `WorkspaceManager._persist_db_record`
retry logic — it must propagate for the retry logic to work, so the fix
is at the Sentry filter level rather than catching/suppressing at source

### Backend: Library agent race condition fixes
- **`add_graph_to_library`**: Replaced check-then-create pattern with
create-then-catch-`UniqueViolationError`-then-update. On collision,
updates the existing row (restoring soft-deleted/archived agents)
instead of crashing.
- **`create_library_agent`**: Replaced `create` with `upsert` on the
`(userId, agentGraphId, agentGraphVersion)` composite unique constraint,
so concurrent adds restore soft-deleted entries instead of throwing.

### Backend: Graph version auto-increment on collision
- `__create_graph` now checks if the `(id, version)` already exists
before `create_many`, and auto-increments the version to `max_existing +
1` to avoid `UniqueViolationError` when the copilot re-saves an agent.

### Backend: Workspace `get_or_create_workspace` upsert
- Changed from find-then-create to `upsert` to atomically handle
concurrent workspace creation.

## Test plan

- [x] `LlmModel("anthropic/claude-sonnet-4-6")` resolves correctly
- [x] `LlmModel("claude-sonnet-4-6")` still works (no regression)
- [x] `LlmModel("invalid/nonexistent-model")` still raises `ValueError`
- [x] XMLParserBlock: unclosed tags, extra closing tags, empty XML all
raise `ValueError`
- [x] XMLParserBlock: `SyntaxError` from gravitasml library is caught
and re-raised as `ValueError`
- [x] Virus scanner: empty file (0 bytes) returns clean without hitting
ClamAV
- [x] Virus scanner: single-byte file scans normally (regression test)
- [x] Virus scanner: `scan_content_safe` logs at WARNING not ERROR on
failure
- [x] SDK disconnect: `_is_sdk_disconnect_error` correctly identifies
cancel scope and context var errors
- [x] SDK disconnect: `_is_sdk_disconnect_error` rejects unrelated
errors
- [x] SDK disconnect: `_safe_close_sdk_client` suppresses ValueError,
RuntimeError, and unexpected exceptions
- [x] SDK disconnect: `_safe_close_sdk_client` calls `__aexit__` on
clean exit
- [x] Library: `add_graph_to_library` creates new agent on first call
- [x] Library: `add_graph_to_library` updates existing on
UniqueViolationError
- [x] Library: `create_library_agent` uses upsert to handle concurrent
adds
- [x] All existing workspace overwrite tests still pass
- [x] All tests passing (existing + 4 XML syntax + 3 virus scanner + 10
SDK disconnect + library tests)
2026-03-27 06:09:42 +00:00
Zamil Majdy
fb74fcf4a4 feat(platform): add shared admin user search + rate-limit modal on spending page (#12577)
## Why
Admin rate-limit management required manually entering user UUIDs. The
spending page already had user search but it wasn't reusable.

## What
- Extract `AdminUserSearch` as shared component from spending page
search
- Add rate-limit modal (usage bars + reset) to spending page user rows
- Add email/name/UUID search to standalone rate-limits page
- Backend: add email query parameter to rate-limit endpoint

## How
- `AdminUserSearch` in `admin/components/` — reused by both spending and
rate-limits
- `RateLimitModal` opens from spending page "Rate Limits" button
- Backend `_resolve_user_id()` accepts email or user_id
- Smart routing: exact email → direct lookup, UUID → direct, partial →
fuzzy search

### Follow-up
- `AdminUserSearch` is a plain text input with no typeahead/fuzzy
suggestions — consider adding autocomplete dropdown with debounced
search

### Checklist 📋
- [x] Shared search component extracted and reused
- [x] Tests pass
- [x] Type-checked
2026-03-27 05:53:04 +00:00
Zamil Majdy
28b26dde94 feat(platform): spend credits to reset CoPilot daily rate limit (#12526)
## Summary
- When users hit their daily CoPilot token limit, they can now spend
credits ($2.00 default) to reset it and continue working
- Adds a dialog prompt when rate limit error occurs, offering the
credit-based reset option
- Adds a "Reset daily limit" button in the usage limits panel when the
daily limit is reached
- Backend: new `POST /api/chat/usage/reset` endpoint,
`reset_daily_usage()` Redis helper, `rate_limit_reset_cost` config
- Frontend: `RateLimitResetDialog` component, updated
`UsagePanelContent` with reset button, `useCopilotStream` exposes rate
limit state
- **NEW: Resetting the daily limit also reduces weekly usage by the
daily limit amount**, effectively granting 1 extra day's worth of weekly
capacity (e.g., daily_limit=10000 → weekly usage reduced by 10000,
clamped to 0)

## Context
Users have been confused about having credits available but being
blocked by rate limits (REQ-63, REQ-61). This provides a short-term
solution allowing users to spend credits to bypass their daily limit.

The weekly usage reduction ensures that a paid daily reset doesn't just
move the bottleneck to the weekly limit — users get genuine additional
capacity for the day they paid to unlock.

### 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] Hit daily rate limit → dialog appears with reset option
- [x] Click "Reset for $2.00" → credits charged, daily counter reset,
dialog closes
- [x] Usage panel shows "Reset daily limit" button when at 100% daily
usage
- [x] When `rate_limit_reset_cost=0` (disabled), rate limit shows toast
instead of dialog
  - [x] Insufficient credits → error toast shown
  - [x] Verify existing rate limit tests pass
  - [x] Unit tests: weekly counter reduced by daily_limit on reset
  - [x] Unit tests: weekly counter clamped to 0 when usage < daily_limit
  - [x] Unit tests: no weekly reduction when daily_token_limit=0

#### For configuration changes:
- [x] `.env.default` is updated or already compatible with my changes
(new config fields `rate_limit_reset_cost` and `max_daily_resets` have
defaults in code)
- [x] `docker-compose.yml` is updated or already compatible with my
changes (no Docker changes needed)
2026-03-26 13:52:08 +00:00
Zamil Majdy
d677978c90 feat(platform): admin rate limit check and reset with LD-configurable global limits (#12566)
## Why
Admins need visibility into per-user CoPilot rate limit usage and the
ability to reset a user's counters when needed (e.g., after a false
positive or for debugging). Additionally, the global rate limits were
hardcoded deploy-time constants with no way to adjust without
redeploying.

## What
- Admin endpoints to **check** a user's current rate limit usage and
**reset** their daily/weekly counters to zero
- Global rate limits are now **LaunchDarkly-configurable** via
`copilot-daily-token-limit` and `copilot-weekly-token-limit` flags,
falling back to existing `ChatConfig` values
- Frontend admin page at `/admin/rate-limits` with user lookup, usage
visualization, and reset capability
- Chat routes updated to source global limits from LD flags

## How
- **Backend**: Added `reset_user_usage()` to `rate_limit.py` that
deletes Redis usage keys. New admin routes in
`rate_limit_admin_routes.py` (GET `/api/copilot/admin/rate_limit` and
POST `/api/copilot/admin/rate_limit/reset`). Added
`COPILOT_DAILY_TOKEN_LIMIT` and `COPILOT_WEEKLY_TOKEN_LIMIT` to the
`Flag` enum. Chat routes use `_get_global_rate_limits()` helper that
checks LD first.
- **Frontend**: New `/admin/rate-limits` page with `RateLimitManager`
(user lookup) and `RateLimitDisplay` (usage bars + reset button). Added
`getUserRateLimit` and `resetUserRateLimit` to `BackendAPI` client.

## Test plan
- [x] Backend: 4 tests covering get, reset, redis failure, and
admin-only access
- [ ] Manual: Look up a user's rate limits in the admin UI
- [ ] Manual: Reset a user's usage counters
- [ ] Manual: Verify LD flag overrides are respected for global limits
2026-03-26 08:29:40 +00:00
Otto
a347c274b7 fix(frontend): replace unrealistic CoPilot suggestion prompt (#12564)
Replaces "Sort my bookmarks into categories" with "Summarize my unread
emails" in the Organize suggestion category. CoPilot has no access to
browser bookmarks or local files, so the original prompt was misleading.

---
Co-authored-by: Toran Bruce Richards (@Torantulino)
<Torantulino@users.noreply.github.com>
2026-03-26 08:10:28 +00:00
Zamil Majdy
f79d8f0449 fix(backend): move placeholder_values exclusively to AgentDropdownInputBlock (#12551)
## Why

`AgentInputBlock` has a `placeholder_values` field whose
`generate_schema()` converts it into a JSON schema `enum`. The frontend
renders any field with `enum` as a dropdown/select. This means
AI-generated agents that populate `placeholder_values` with example
values (e.g. URLs) on regular `AgentInputBlock` nodes end up with
dropdowns instead of free-text inputs — users can't type custom values.

Only `AgentDropdownInputBlock` should produce dropdown behavior.

## What

- Removed `placeholder_values` field from `AgentInputBlock.Input`
- Moved the `enum` generation logic to
`AgentDropdownInputBlock.Input.generate_schema()`
- Cleaned up test data for non-dropdown input blocks
- Updated copilot agent generation guide to stop suggesting
`placeholder_values` for `AgentInputBlock`

## How

The base `AgentInputBlock.Input.generate_schema()` no longer converts
`placeholder_values` → `enum`. Only `AgentDropdownInputBlock.Input`
defines `placeholder_values` and overrides `generate_schema()` to
produce the `enum`.

**Backward compatibility**: Existing agents with `placeholder_values` on
`AgentInputBlock` nodes load fine — `model_construct()` silently ignores
extra fields not defined on the model. Those inputs will now render as
text fields (desired behavior).

## Test plan
- [x] `poetry run pytest backend/blocks/test/test_block.py -xvs` — all
block tests pass
- [x] `poetry run format && poetry run lint` — clean
- [ ] Import an agent JSON with `placeholder_values` on an
`AgentInputBlock` — verify it loads and renders as text input
- [ ] Create an agent with `AgentDropdownInputBlock` — verify dropdown
still works
2026-03-26 08:09:38 +00:00
Otto
1bc48c55d5 feat(copilot): add copy button to user prompt messages [SECRT-2172] (#12571)
Requested by @itsababseh

Users can copy assistant output messages but not their own prompts. This
adds the same copy button to user messages — appears on hover,
right-aligned, using the existing `CopyButton` component.

## Why

Users write long prompts and need to copy them to reuse or share.
Currently requires manual text selection. ChatGPT shows copy on hover
for user messages — this matches that pattern.

## What

- Added `CopyButton` to user prompt messages in
`ChatMessagesContainer.tsx`
- Shows on hover (`group-hover:opacity-100`), positioned right-aligned
below the message
- Reuses the existing `CopyButton` and `MessageActions` components —
zero new code

## How

One file changed, 11 lines added:
1. Import `MessageActions` and `CopyButton`
2. Render them after user `MessageContent`, gated on `message.role ===
"user"` and having text parts

---
Co-authored-by: itsababseh (@itsababseh)
<36419647+itsababseh@users.noreply.github.com>
2026-03-26 08:02:28 +00:00
Abhimanyu Yadav
9d0a31c0f1 fix(frontend/builder): fix array field item layout and add FormRenderer stories (#12532)
Fix broken UI when selecting nodes with array fields (list[str],
list[Enum]) in the builder. The select/input inside array items was
squeezed by the Remove button instead of taking full width.
<img width="2559" height="1077" alt="Screenshot 2026-03-26 at 10 23
34 AM"
src="https://github.com/user-attachments/assets/2ffc28a2-8d6c-428c-897c-021b1575723c"
/>

### Changes 🏗️

- **ArrayFieldItemTemplate**: Changed layout from horizontal flex-row to
vertical flex-col so the input takes full width and Remove button sits
below aligned left, with tighter spacing between them
- **Storybook config**: Added `renderers/**` glob to
`.storybook/main.ts` so renderer stories are discoverable
- **FormRenderer stories**: Added comprehensive Storybook stories
covering all backend field types (string, int, float, bool, enum,
date/time, list[str], list[int], list[Enum], list[bool], nested objects,
Optional, anyOf unions, oneOf discriminated unions, multi-select, list
of objects, and a kitchen sink). Includes exact Twitter GetUserBlock
schema for realistic oneOf + multi-select testing.

### 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 array field items render with full-width input and Remove
button below in Storybook
  - [x] Verified list[Enum] select dropdown takes full width
  - [x] Verified list[str] text input takes full width
- [x] Verified all FormRenderer stories render without errors in
Storybook
- [x] Verified multi-select and oneOf discriminated union stories match
real backend schemas
2026-03-26 06:15:30 +00:00
Abhimanyu Yadav
9b086e39c6 fix(frontend): hide placeholder text when copilot voice recording is active (#12534)
### Why / What / How

**Why:** When voice recording is active in the CoPilot chat input, the
recording UI (waveform + timer) overlays on top of the placeholder/hint
text, creating a visually broken appearance. Reported by a user via
SECRT-2163.

**What:** Hide the textarea placeholder text while voice recording is
active so it doesn't bleed through the `RecordingIndicator` overlay.

**How:** When `isRecording` is true, the placeholder is set to an empty
string. The existing `RecordingIndicator` overlay (waveform animation +
elapsed time) then displays cleanly without the hint text showing
underneath.

### Changes 🏗️

- Clear the `PromptInputTextarea` placeholder to `""` when voice
recording is active, preventing it from rendering behind the
`RecordingIndicator` overlay

### 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 CoPilot chat at /copilot
- [x] Click the microphone button or press Space to start voice
recording
- [x] Verify the placeholder text ("Type your message..." / "What else
can I help with?") is hidden during recording
- [x] Verify the RecordingIndicator (waveform + timer) displays cleanly
without overlapping text
  - [x] Stop recording and verify placeholder text reappears
  - [x] Verify "Transcribing..." placeholder shows during transcription
2026-03-26 05:41:09 +00:00
Zamil Majdy
5867e4d613 Merge branch 'master' of github.com:Significant-Gravitas/AutoGPT into dev 2026-03-26 07:30:56 +07:00
Zamil Majdy
85f0d8353a fix(platform): fix prod Sentry errors and reduce on-call alert noise (#12560)
## Summary
Hotfix targeting master for production Sentry errors that are triggering
on-call pages. Fixes actual bugs and expands Sentry filters to suppress
user-caused errors that are not platform issues.

### Bug Fixes
- **Workspace race condition** (`get_or_create_workspace`): Replaced
Prisma's non-atomic `upsert` with find-then-create pattern. Prisma's
upsert translates to SELECT + INSERT (not PostgreSQL's native `INSERT
... ON CONFLICT`), causing `UniqueViolationError` when concurrent
requests hit for the same user (e.g. copilot + file upload
simultaneously).
- **ChatSidebar crash**: Added null-safe `?.` for `sessions` which can
be `undefined` during error/loading states, preventing `TypeError:
Cannot read properties of undefined (reading 'length')`.
- **UsageLimits crash**: Added null-safe `?.` for
`usage.daily`/`usage.weekly` which can be `undefined` when the API
returns partial data, preventing `TypeError: Cannot read properties of
undefined (reading 'limit')`.

### Sentry Filter Improvements
Expanded backend `_before_send` to stop user-caused errors from reaching
Sentry and triggering on-call alerts:
- **Consolidated auth keywords** into a shared `_USER_AUTH_KEYWORDS`
list used by both exception-based and log-based filters (previously
duplicated).
- **Added missing auth keywords**: `"unauthorized"`, `"bad
credentials"`, `"insufficient authentication scopes"` — these were
leaking through.
- **Added user integration HTTP error filter**: `"http 401 error"`,
`"http 403 error"`, `"http 404 error"` — catches `BlockUnknownError` and
`HTTPClientError` from user integrations (expired GitHub tokens, wrong
Airtable IDs, etc.).
- **Fixed log-based event gap**: User auth errors logged via
`logger.error()` (not raised as exceptions) were bypassing the
`exc_info` filter. Now the same `_USER_AUTH_KEYWORDS` list is checked
against log messages too.

## On-Call Alerts Addressed

### Fixed (actual bugs)
| Alert | Issue | Root Cause |
|-------|-------|------------|
| `Unique constraint failed on the fields: (userId)` |
[AUTOGPT-SERVER-8BM](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-8BM)
| Prisma upsert race condition |
| `Unique constraint failed on the fields: (userId)` |
[AUTOGPT-SERVER-8BK](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-8BK)
| Same — via `/api/workspace/files/upload` |
| `Unique constraint failed on the fields: (userId)` |
[AUTOGPT-SERVER-8BN](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-8BN)
| Same — via `tools/call run_block` |
| `Upload failed (500): Unique constraint failed` |
[BUILDER-7GA](https://significant-gravitas.sentry.io/issues/BUILDER-7GA)
| Frontend surface of same workspace bug |
| `Cannot read properties of undefined (reading 'length')` |
[BUILDER-7GD](https://significant-gravitas.sentry.io/issues/BUILDER-7GD)
| `sessions` undefined in ChatSidebar |
| `Cannot read properties of undefined (reading 'limit')` |
[BUILDER-7GB](https://significant-gravitas.sentry.io/issues/BUILDER-7GB)
| `usage.daily` undefined in UsageLimits |

### Filtered (user-caused, not platform bugs)
| Alert | Issue | Why it's not a platform bug |
|-------|-------|-----------------------------|
| `Anthropic API error: invalid x-api-key` |
[AUTOGPT-SERVER-8B6](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-8B6),
8B7, 8B8 | User provided invalid Anthropic API key |
| `AI condition evaluation failed: Incorrect API key` |
[AUTOGPT-SERVER-83Y](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-83Y)
| User's OpenAI key is wrong (4.5K events, 1 user) |
| `GithubListIssuesBlock: HTTP 401 Bad credentials` |
[AUTOGPT-SERVER-8BF](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-8BF)
| User's GitHub token expired |
| `HTTPClientError: HTTP 401 Unauthorized` |
[AUTOGPT-SERVER-8BG](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-8BG)
| Same — credential check endpoint |
| `GithubReadIssueBlock: HTTP 401 Bad credentials` |
[AUTOGPT-SERVER-8BH](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-8BH)
| Same — different block |
| `AirtableCreateBaseBlock: HTTP 404 MODEL_ID_NOT_FOUND` |
[AUTOGPT-SERVER-8BC](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-8BC)
| User's Airtable model ID is wrong |

### Not addressed in this PR
| Alert | Issue | Reason |
|-------|-------|--------|
| `Unexpected token '<', "<html><hea"...` |
[BUILDER-7GC](https://significant-gravitas.sentry.io/issues/BUILDER-7GC)
| Transient — backend briefly returned HTML error page |
| `undefined is not an object (activeResponse.state)` |
[BUILDER-71J](https://significant-gravitas.sentry.io/issues/BUILDER-71J)
| Bug in Vercel AI SDK `ai@6.0.59`, already resolved |
| `Last Tool Output is needed` |
[AUTOGPT-SERVER-72T](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-72T)
| User graph misconfiguration (1 user, 21 events) |
| `Cannot set property ethereum` |
[BUILDER-7G6](https://significant-gravitas.sentry.io/issues/BUILDER-7G6)
| Browser wallet extension conflict |
| `File already exists at path` |
[BUILDER-7FS](https://significant-gravitas.sentry.io/issues/BUILDER-7FS)
| Expected 409 conflict |

## Test plan
- [ ] Verify workspace creation works for new users
- [ ] Verify concurrent workspace access (e.g. copilot + file upload)
doesn't error
- [ ] Verify copilot ChatSidebar and UsageLimits load correctly when API
returns partial/error data
- [ ] Verify user auth errors (invalid API keys, expired tokens) no
longer appear in Sentry after deployment
2026-03-25 23:25:32 +07:00
An Vy Le
f871717f68 fix(backend): add sink input validation to AgentValidator (#12514)
## Summary

- Added `validate_sink_input_existence` method to `AgentValidator` to
ensure all sink names in links and input defaults reference valid input
schema fields in the corresponding block
- Added comprehensive tests covering valid/invalid sink names, nested
inputs, and default key handling
- Updated `ReadDiscordMessagesBlock` description to clarify it reads new
messages and triggers on new posts
- Removed leftover test function file

## Test plan

- [ ] Run `pytest` on `validator_test.py` to verify all sink input
validation cases pass
- [ ] Verify existing agent validation flow is unaffected
- [ ] Confirm `ReadDiscordMessagesBlock` description update is accurate

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

---------

Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
2026-03-25 16:08:17 +00:00
Ubbe
f08e52dc86 fix(frontend): marketplace card description 3 lines + fallback color (#12557)
## Summary
- Increase the marketplace StoreCard description from 2 lines to 3 lines
for better readability
- Change fallback background colour for missing agent images from
`bg-violet-50` to `rgb(216, 208, 255)`

<img width="933" height="458" alt="Screenshot 2026-03-25 at 20 25 41"
src="https://github.com/user-attachments/assets/ea433741-1397-4585-b64c-c7c3b8109584"
/>
<img width="350" height="457" alt="Screenshot 2026-03-25 at 20 25 55"
src="https://github.com/user-attachments/assets/e2029c09-518a-4404-aa95-e202b4064d0b"
/>


## Test plan
- [x] Verified `pnpm format`, `pnpm lint`, `pnpm types` all pass
- [x] Visually confirmed description shows 3 lines on marketplace cards
- [x] Visually confirmed fallback color renders correctly for cards
without images

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

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-25 20:58:45 +08:00
Ubbe
500b345b3b fix(frontend): auto-reconnect copilot chat after device sleep/wake (#12519)
## Summary

- Adds `visibilitychange`-based sleep/wake detection to the copilot chat
— when the page becomes visible after >30s hidden, automatically refetch
the session and either resume an active stream or hydrate completed
messages
- Blocks chat input during re-sync (`isSyncing` state) to prevent users
from accidentally sending a message that overwrites the agent's
completed work
- Replaces `PulseLoader` with a spinning `CircleNotch` icon on sidebar
session names for background streaming sessions (closer to ChatGPT's UX)

## How it works

1. When the page goes hidden, we record a timestamp
2. When the page becomes visible, we check elapsed time
3. If >30s elapsed (indicating sleep or long background), we refetch the
session from the API
4. If backend still has `active_stream=true` → remove stale assistant
message and resume SSE
5. If backend is done → the refetch triggers React Query invalidation
which hydrates the completed messages
6. Chat input stays disabled (`isSyncing=true`) until re-sync completes

## Test plan

- [ ] Open copilot, start a long-running agent task
- [ ] Close laptop lid / lock screen for >30 seconds
- [ ] Wake device — verify chat shows the agent's completed response (or
resumes streaming)
- [ ] Verify chat input is temporarily disabled during re-sync, then
re-enables
- [ ] Verify sidebar shows spinning icon (not pulse loader) for
background sessions
- [ ] Verify no duplicate messages appear after wake
- [ ] Verify normal streaming (no sleep) still works as expected

Resolves: [SECRT-2159](https://linear.app/autogpt/issue/SECRT-2159)

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

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-25 20:15:33 +08:00
Ubbe
995dd1b5f3 feat(platform): replace suggestion pills with themed prompt categories (#12515)
## Summary

<img width="700" height="575" alt="Screenshot 2026-03-23 at 21 40 07"
src="https://github.com/user-attachments/assets/f6138c63-dd5e-4bde-a2e4-7434d0d3ec72"
/>

Re-applies #12452 which was reverted as collateral in #12485 (invite
system revert).

Replaces the flat list of suggestion pills in the CoPilot empty session
with themed prompt categories (Learn, Create, Automate, Organize), each
shown as a popover with contextual prompts.

- **Backend**: Adds `suggested_prompts` as a themed `dict[str,
list[str]]` keyed by category. Updates Tally extraction LLM prompt to
generate prompts per theme, and the `/suggested-prompts` API to return
grouped themes. Legacy `list[str]` rows are preserved under a
`"General"` key for backward compatibility.
- **Frontend**: Replaces inline pill buttons with a `SuggestionThemes`
popover component. Each theme button (with icon) opens a dropdown of 5
relevant prompts. Falls back to hardcoded defaults when the API has no
personalized prompts. Normalizes partial API responses by padding
missing themes with defaults. Legacy `"General"` prompts are distributed
round-robin across themes.

### Changes 🏗️

- `backend/data/understanding.py`: `suggested_prompts` field added as
`dict[str, list[str]]`; legacy list rows preserved under `"General"` key
via `_json_to_themed_prompts`
- `backend/data/tally.py`: LLM prompt updated to generate themed
prompts; validation now per-theme with blank-string rejection
- `backend/api/features/chat/routes.py`: New `SuggestedTheme` model;
endpoint returns `themes[]`
- `frontend/copilot/components/EmptySession/EmptySession.tsx`: Uses
generated API hooks for suggested prompts
- `frontend/copilot/components/EmptySession/helpers.ts`:
`DEFAULT_THEMES` replaces `DEFAULT_QUICK_ACTIONS`; `getSuggestionThemes`
normalizes partial API responses
-
`frontend/copilot/components/EmptySession/components/SuggestionThemes/`:
New popover component with theme icons and loading states

### 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:
  - [x] Verify themed suggestion buttons render on CoPilot empty session
  - [x] Click each theme button and confirm popover opens with prompts
  - [x] Click a prompt and confirm it sends the message
- [x] Verify fallback to default themes when API returns no custom
prompts
- [x] Verify legacy users' personalized prompts are preserved and
visible

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

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-25 15:32:49 +08:00
Zamil Majdy
336114f217 fix(backend): prevent graph execution stuck + steer SDK away from bash_exec (#12548)
## Summary

Two backend fixes for CoPilot stability:

1. **Steer model away from bash_exec for SDK tool-result files** — When
the SDK returns tool results as file paths, the copilot model was
attempting to use `bash_exec` to read them instead of treating the
content directly. Added system prompt guidance to prevent this.

2. **Guard against missing 'name' in execution input_data** —
`GraphExecution.from_db()` assumed all INPUT/OUTPUT block node
executions have a `name` field in `input_data`. This crashes with
`KeyError: 'name'` when non-standard blocks (e.g., OrchestratorBlock)
produce node executions without this field. Added `"name" in
exec.input_data` guards.

## Why

- The bash_exec issue causes copilot to fail when processing SDK tool
outputs
- The KeyError crashes the `update_graph_execution_stats` endpoint,
causing graph executions to appear stuck (retries 35+ times, never
completes)

## How

- Added system prompt instruction to treat tool result file contents
directly
- Added `"name" in exec.input_data` guard in both input extraction (line
340) and output extraction (line 365) in `execution.py`

### Changes
- `backend/copilot/sdk/service.py` — system prompt guidance
- `backend/data/execution.py` — KeyError guard for missing `name` field

### 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] OrchestratorBlock graph execution no longer gets stuck
- [x] Standard Agent Input/Output blocks still work correctly
- [x] Copilot SDK tool results are processed without bash_exec
2026-03-25 13:58:24 +07:00
Nicholas Tindle
866563ad25 feat(platform): admin preview marketplace submissions before approving (#12536)
## Why

Admins reviewing marketplace submissions currently approve blindly —
they can see raw metadata in the admin table but cannot see what the
listing actually looks like (images, video, branding, layout). This
risks approving inappropriate content. With full-scale production
approaching, this is critical.

Additionally, when a creator un-publishes an agent, users who already
added it to their library lose access — breaking their workflows.
Product decided on a "you added it, you keep it" model.

## What

- **Admin preview page** at `/admin/marketplace/preview/[id]` — renders
the listing exactly as it would appear on the public marketplace
- **Add to Library** for admins to test-run pending agents before
approving
- **Library membership grants graph access** — if you added an agent to
your library, you keep access even if it's un-published or rejected
- **Preview button** on every submission row in the admin marketplace
table
- **Cross-reference comments** on original functions to prevent
SECRT-2162-style regressions

## How

### Backend

**Admin preview (`store/db.py`):**
- `get_store_agent_details_as_admin()` queries `StoreListingVersion`
directly, bypassing the APPROVED-only `StoreAgent` DB view
- Validates `CreatorProfile` FK integrity, reads all fields including
`recommendedScheduleCron`

**Admin add-to-library (`library/_add_to_library.py`):**
- Extracted shared logic into `resolve_graph_for_library()` +
`add_graph_to_library()` — eliminates duplication between public and
admin paths
- Admin path uses `get_graph_as_admin()` to bypass marketplace status
checks
- Handles concurrent double-click race via `UniqueViolationError` catch

**Library membership grants graph access (`data/graph.py`):**
- `get_graph()` now falls back to `LibraryAgent` lookup if ownership and
marketplace checks fail
- Only for authenticated users with non-deleted, non-archived library
records
- `validate_graph_execution_permissions()` updated to match — library
membership grants execution access too

**New endpoints (`store_admin_routes.py`):**
- `GET /admin/submissions/{id}/preview` — returns `StoreAgentDetails`
- `POST /admin/submissions/{id}/add-to-library` — creates `LibraryAgent`
via admin path

### Frontend

- Preview page reuses `AgentInfo` + `AgentImages` with admin banner
- Shows instructions, recommended schedule, and slug
- "Add to My Library" button wired to admin endpoint
- Preview button added to `ExpandableRow` (header + version history)
- Categories column uncommented in version history table

### Testing (19 tests)

**Graph access control (9 in `graph_test.py`):** Owner access,
marketplace access, library member access (unpublished),
deleted/archived/anonymous denied, null FK denied, efficiency checks

**Admin bypass (5 in `store_admin_routes_test.py`):** Preview uses
StoreListingVersion not StoreAgent, admin path uses get_graph_as_admin,
regular path uses get_graph, library member can view in builder

**Security (3):** Non-admin 403 on preview, non-admin 403 on
add-to-library, nonexistent 404

**SECRT-2162 regression (2):** Admin access to pending agent, export
with sub-graphs

### Checklist
- [x] Changes clearly listed
- [x] Test plan made
- [x] 19 backend tests pass
- [x] Frontend lints and types clean

## Test plan
- [x] Navigate to `/admin/marketplace`, click Preview on a PENDING
submission
- [x] Verify images, video, description, categories, instructions,
schedule render correctly
- [x] Click "Add to My Library", verify agent appears in library and
opens in builder
- [x] Verify non-admin users get 403
- [x] Verify un-publishing doesn't break access for users who already
added it

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

<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> **High Risk**
> Adds new admin-only endpoints that bypass marketplace
approval/ownership checks and changes `get_graph`/execution
authorization to grant access via library membership, which impacts
security-sensitive access control paths.
> 
> **Overview**
> Adds **admin preview + review workflow support** for marketplace
submissions: new admin routes to `GET /admin/submissions/{id}/preview`
(querying `StoreListingVersion` directly) and `POST
/admin/submissions/{id}/add-to-library` (admin bypass to pull pending
graphs into an admin’s library).
> 
> Refactors library add-from-store logic into shared helpers
(`resolve_graph_for_library`, `add_graph_to_library`) and introduces an
admin variant `add_store_agent_to_library_as_admin`, including restore
of archived/deleted entries and dedup/race handling.
> 
> Changes core graph access rules: `get_graph()` now falls back to
**library membership** (non-deleted/non-archived, version-specific) when
ownership and marketplace approval don’t apply, and
`validate_graph_execution_permissions()` is updated accordingly.
Frontend adds a preview link and a dedicated admin preview page with
“Add to My Library”; tests expand significantly to lock in the new
bypass and access-control behavior.
> 
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
a362415d12. 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>
2026-03-25 04:26:36 +00:00
Zamil Majdy
e79928a815 fix(backend): prevent logging sensitive data in SafeJson fallback (#12547)
### Why / What / How

**Why:** GitHub's code scanning detected a HIGH severity security
vulnerability in `/autogpt_platform/backend/backend/util/json.py:172`.
The error handler in `sanitize_json()` was logging sensitive data
(potentially including secrets, API keys, credentials) as clear text
when serialization fails.

**What:** This PR removes the logging of actual data content from the
error handler while preserving useful debugging metadata (error type,
error message, and data type).

**How:** Removed the `"Data preview: %s"` format parameter and the
corresponding `truncate(str(data), 100)` argument from the
logger.error() call. The error handler now logs only safe metadata that
helps debugging without exposing sensitive information.

### Changes 🏗️

- **Security Fix**: Modified `sanitize_json()` function in
`backend/util/json.py`
- Removed logging of data content (`truncate(str(data), 100)`) from the
error handler
  - Retained logging of error type (`type(e).__name__`)
- Retained logging of truncated error message (`truncate(str(e), 200)`)
  - Retained logging of data type (`type(data).__name__`)
- Error handler still provides useful debugging information without
exposing secrets

### 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 the code passes type checking (`poetry run pyright
backend/util/json.py`)
- [x] Verified the code passes linting (`poetry run ruff check
backend/util/json.py`)
  - [x] Verified all pre-commit hooks pass
- [x] Reviewed the diff to ensure only the sensitive data logging was
removed
- [x] Confirmed that useful debugging information (error type, error
message, data type) is still logged

#### For configuration changes:
- N/A - No configuration changes required
2026-03-25 04:21:21 +00:00
Zamil Majdy
1771ed3bef dx(skills): codify PR workflow rules in skill docs and CLAUDE.md (#12531)
## Summary

- **pr-address skill**: Add explicit rule against empty commits for CI
re-triggers, and strengthen push-immediately guidance with rationale
- **Platform CLAUDE.md**: Add "split PRs by concern" guideline under
Creating Pull Requests

### Changes
- Updated `.claude/skills/pr-address/SKILL.md`
- Updated `autogpt_platform/CLAUDE.md`

### 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

#### Test plan:
- [x] Documentation-only changes — no functional tests needed
- [x] Verified markdown renders correctly
2026-03-25 10:19:30 +07:00
Zamil Majdy
550fa5a319 fix(backend): register AutoPilot sessions with stream registry for SSE updates (#12500)
### Changes 🏗️
- When the AutoPilot block executes a copilot session via
`collect_copilot_response`, it calls `stream_chat_completion_sdk`
directly, bypassing the copilot executor and stream registry. This means
the frontend sees no `active_stream` on the session and cannot connect
via SSE — users see a frozen chat with no updates until the turn fully
completes.
- Fix: register a `stream_registry` session in
`collect_copilot_response` and publish each chunk to Redis as events are
consumed. This allows the frontend to detect `active_stream=true` and
connect via the SSE reconnect endpoint for live streaming updates during
AutoPilot execution.
- Error handling is graceful — if stream registry fails, AutoPilot still
works normally, just without real-time frontend updates.

### 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] Trigger an AutoPilot block execution that creates a new chat
session
- [x] Verify the new session appears in the sidebar with streaming
indicator
- [x] Click on the session while AutoPilot is still executing — verify
SSE connects and messages stream in real-time
- [x] Verify that after AutoPilot completes, the session shows as
complete (no active_stream)
- [x] Test reconnection: disconnect and reconnect while AutoPilot is
running — verify stream resumes (found and fixed GeneratorExit bug that
caused stuck sessions)
- [x] E2E: 10 stream events published to Redis (StreamStart,
3×ToolInput, 3×ToolOutput, TextStart, TextEnd, StreamFinish)
  - [x] E2E: Redis xadd latency 0.2–3.4ms per chunk
  - [x] E2E: Chat sessions registered in Redis (confirmed via redis-cli)
2026-03-25 01:08:49 +00:00
Zamil Majdy
8528dffbf2 fix(backend): allow /tmp as valid path in E2B sandbox file tools (#12501)
## Summary
- Allow `/tmp` as a valid writable directory in E2B sandbox file tools
(`write_file`, `read_file`, `edit_file`, `glob`, `grep`)
- The E2B sandbox is already fully isolated, so restricting writes to
only `/home/user` was unnecessarily limiting — scripts and tools
commonly use `/tmp` for temporary files
- Extract `is_within_allowed_dirs()` helper in `context.py` to
centralize the allowed-directory check for both path resolution and
symlink escape detection

## Changes
- `context.py`: Add `E2B_ALLOWED_DIRS` tuple and `E2B_ALLOWED_DIRS_STR`,
introduce `is_within_allowed_dirs()`, update `resolve_sandbox_path()` to
use it
- `e2b_file_tools.py`: Update `_check_sandbox_symlink_escape()` to use
`is_within_allowed_dirs()`, update tool descriptions
- Tests: Add coverage for `/tmp` paths in both `context_test.py` and
`e2b_file_tools_test.py`

### 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 59 existing + new tests pass (`poetry run pytest
backend/copilot/context_test.py
backend/copilot/sdk/e2b_file_tools_test.py`)
  - [x] `poetry run format` and `poetry run lint` pass clean
  - [x] Verify `/tmp` write works in live E2B sandbox
  - [x] E2E: Write file to /tmp/test.py in E2B sandbox via copilot
  - [x] E2E: Execute script from /tmp — output "Hello, World!"
  - [x] E2E: E2B sandbox lifecycle (create, use, pause) works correctly
2026-03-25 00:52:58 +00:00
Zamil Majdy
8fbf6a4b09 Merge branch 'master' of github.com:Significant-Gravitas/AutoGPT into dev 2026-03-25 06:55:47 +07:00
Zamil Majdy
239148596c fix(backend): filter SDK default credentials from credentials API responses (#12544)
## Summary

- Filter SDK-provisioned default credentials from credentials API list
endpoints
- Reuse `CredentialsMetaResponse` model from internal router in external
API (removes duplicate `CredentialSummary`)
- Add `is_sdk_default()` helper for identifying platform-provisioned
credentials
- Add `provider_matches()` to credential store for consistent provider
filtering
- Add tests for credential filtering behavior

### Changes
- `backend/data/model.py` — add `is_sdk_default()` helper
- `backend/api/features/integrations/router.py` — filter SDK defaults
from list endpoints
- `backend/api/external/v1/integrations.py` — reuse
`CredentialsMetaResponse`, filter SDK defaults
- `backend/integrations/credentials_store.py` — add `provider_matches()`
- `backend/sdk/registry.py` — update credential registration
- `backend/api/features/integrations/router_test.py` — new tests
- `backend/api/features/integrations/conftest.py` — test fixtures

### 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

#### Test plan:
- [x] Unit tests for credential filtering (`router_test.py`)
- [x] Verify SDK default credentials excluded from API responses
- [x] Verify user-created credentials still returned normally
2026-03-25 06:54:54 +07:00
Zamil Majdy
a880d73481 feat(platform): dry-run execution mode with LLM block simulation (#12483)
## Why

Agent generation and building needs a way to test-run agents without
requiring real credentials or producing side effects. Currently, every
execution hits real APIs, consumes credits, and requires valid
credentials — making it impossible to debug or validate agent graphs
during the build phase without real consequences.

## Summary

Adds a `dry_run` execution mode to the copilot's `run_block` and
`run_agent` tools. When `dry_run=True`, every block execution is
simulated by an LLM instead of calling the real service — no real API
calls, no credentials consumed, no side effects.

Inspired by
[Significant-Gravitas/agent-simulator](https://github.com/Significant-Gravitas/agent-simulator).

### How it works

- **`backend/executor/simulator.py`** (new): `simulate_block()` builds a
prompt from the block's name, description, input/output schemas, and
actual input values, then calls `gpt-4o-mini` via the existing
OpenRouter client with JSON mode. Retries up to 5 times on JSON parse
failures. Missing output pins are filled with `None` (or `""` for the
`error` pin). Long inputs (>20k chars) are truncated before sending to
the LLM.
- **`ExecutionContext`**: Added `dry_run: bool = False` field; threaded
through `add_graph_execution()` so graph-level dry runs propagate to
every block execution.
- **`execute_block()` helper**: When `dry_run=True`, the function
short-circuits before any credential injection or credit checks, calls
`simulate_block()`, and returns a `[DRY RUN]`-prefixed
`BlockOutputResponse`.
- **`RunBlockTool`**: New `dry_run` boolean parameter.
- **`RunAgentTool`**: New `dry_run` boolean parameter; passes
`ExecutionContext(dry_run=True)` to graph execution.

### Tests

11 tests in `backend/copilot/tools/test_dry_run.py`:
- Correct output tuples from LLM response
- JSON retry logic (3 total calls when first 2 fail)
- All-retries-exhausted yields `SIMULATOR ERROR`
- Missing output pins filled with `None`/`""`
- No-client case
- Input truncation at 20k chars
- `execute_block(dry_run=True)` skips real `block.execute()`
- Response format: `[DRY RUN]` message, `success=True`
- `dry_run=False` unchanged (real path)
- `RunBlockTool` parameter presence
- `dry_run` kwarg forwarding

## Test plan
- [x] Run `pytest backend/copilot/tools/test_dry_run.py -v` — all 11
pass
- [x] Call `run_block` with `dry_run=true` in copilot; verify no real
API calls occur and output contains `[DRY RUN]`
- [x] Call `run_agent` with `dry_run=true`; verify execution is created
with `dry_run=True` in context
- [x] E2E: Simulate button (flask icon) present in builder alongside
play button
- [x] E2E: Simulated run labeled with "(Simulated)" suffix and badge in
Library
- [x] E2E: No credits consumed during dry-run
2026-03-24 22:36:47 +00:00
Zamil Majdy
80bfd64ffa Merge branch 'master' of github.com:Significant-Gravitas/AutoGPT into dev 2026-03-24 21:18:11 +07:00
Zamil Majdy
0076ad2a1a hotfix(blocks): bump stagehand ^0.5.1 → ^3.4.0 to fix yanked litellm (#12539)
## Summary

**Critical CI fix** — litellm was compromised in a supply chain attack
(versions 1.82.7/1.82.8 contained infostealer malware) and PyPI
subsequently yanked many litellm versions including the 1.7x range that
stagehand 0.5.x depended on. This breaks `poetry lock` in CI for all
PRs.

- Bump `stagehand` from `^0.5.1` to `^3.4.0` — Stagehand v3 is a
Stainless-generated HTTP API client that **no longer depends on
litellm**, completely removing litellm from our dependency tree
- Migrate stagehand blocks to use `AsyncStagehand` + session-based API
(`sessions.start`, `session.navigate/act/observe/extract`)
- Net reduction of ~430 lines in `poetry.lock` from dropping litellm and
its transitive dependencies

## Why

All CI pipelines are blocked because `poetry lock` fails to resolve
yanked litellm versions that stagehand 0.5.x required.

## Test plan

- [x] CI passes (poetry lock resolves, backend tests green)
- [ ] Verify stagehand blocks still function with the new session-based
API
2026-03-24 21:17:19 +07:00
Zamil Majdy
edb3d322f0 feat(backend/copilot): parallel block execution via infrastructure-level pre-launch (#12472)
## Summary

- Implements **infrastructure-level parallel tool execution** for
CoPilot: all tools called in a single LLM turn now execute concurrently
with zero changes to individual tool implementations or LLM prompts.
- Adds `pre_launch_tool_call()` to `tool_adapter.py`: when an
`AssistantMessage` with `ToolUseBlock`s arrives, all tools are
immediately fired as `asyncio.Task`s before the SDK dispatches MCP
handlers. Each MCP handler then awaits its pre-launched task instead of
executing fresh.
- Adds a `_tool_task_queues` `ContextVar` (initialized per-session in
`set_execution_context()`) so concurrent sessions never share task
queues.
- DRY refactor: extracts `prepare_block_for_execution()`,
`check_hitl_review()`, and `BlockPreparation` dataclass into
`helpers.py` so the execution pipeline is reusable.
- 10 unit tests for the parallel pre-launch infrastructure (queue
enqueue/dequeue, MCP prefix stripping, fallback path, `CancelledError`
handling, multi-same-tool FIFO ordering).

## Root cause

The Claude Agent SDK CLI sends MCP tool calls as sequential
request-response pairs: it waits for each `control_response` before
issuing the next `mcp_message`. Even though Python dispatches handlers
with `start_soon`, the CLI never issues call B until call A's response
is sent — blocks always ran sequentially. The pre-launch pattern fixes
this at the infrastructure level by starting all tasks before the SDK
even dispatches the first handler.

## Test plan

- [x] `poetry run pytest backend/copilot/sdk/tool_adapter_test.py` — 27
tests pass (10 new parallel infra tests)
- [x] `poetry run pytest backend/copilot/tools/helpers_test.py` — 20
tests pass
- [x] `poetry run pytest backend/copilot/tools/run_block_test.py
backend/copilot/tools/test_run_block_details.py` — all pass
- [x] Manually test in CoPilot: ask the agent to run two blocks
simultaneously — verify both start executing before either completes
- [x] E2E: Both GetCurrentTimeBlock and CalculatorBlock executed
concurrently (time=09:35:42, 42×7=294)
- [x] E2E: Pre-launch mechanism active — two run_block events at same
timestamp (3ms apart)
- [x] E2E: Arg-mismatch fallback tested — system correctly cancels and
falls back to direct execution
2026-03-24 20:27:46 +07:00
Zamil Majdy
9381057079 refactor(platform): rename SmartDecisionMakerBlock to OrchestratorBlock (#12511)
## Summary
- Renames `SmartDecisionMakerBlock` to `OrchestratorBlock` across the
entire codebase
- The block supports iteration/agent mode and general tool
orchestration, so "Smart Decision Maker" no longer accurately describes
its capabilities
- Block UUID (`3b191d9f-356f-482d-8238-ba04b6d18381`) remains unchanged
— fully backward compatible with existing graphs

## Changes
- Renamed block class, constants, file names, test files, docs, and
frontend enum
- Updated copilot agent generator (helpers, validator, fixer) references
- Updated agent generation guide documentation
- No functional changes — pure rename refactor

### For code changes
- [x] I have clearly listed my changes in the PR description
- [x] I have made corresponding changes to the documentation
- [x] My changes do not generate new warnings or errors
- [x] New and existing unit tests pass locally with my changes

## Test plan
- [x] All pre-commit hooks pass (typecheck, lint, format)
- [x] Existing graphs with this block continue to load and execute (same
UUID)
- [x] Agent mode / iteration mode works as before
- [x] Copilot agent generator correctly references the renamed block
2026-03-24 19:16:42 +07:00
Otto
f21a36ca37 fix(backend): downgrade user-caused LLM API errors to warning level (#12516)
Requested by @majdyz

Follow-up to #12513. Anthropic/OpenAI 401, 403, and 429 errors are
user-caused (bad API keys, forbidden, rate limits) and should not hit
Sentry as exceptions.

### Changes

**Changes in `blocks/llm.py`:**
- Anthropic `APIError` handler (line ~950): check `status_code` — use
`logger.warning()` for 401/403/429, keep `logger.error()` for server
errors
- Generic `Exception` handler in LLM block `run()` (line ~1467): same
pattern — `logger.warning()` for user-caused status codes,
`logger.exception()` for everything else
- Extracted `USER_ERROR_STATUS_CODES = (401, 403, 429)` module-level
constant
- Added `break` to short-circuit retry loop for user-caused errors
- Removed double-logging from inner Anthropic handler

**Changes in `blocks/test/test_llm.py`:**
- Added 8 regression tests covering 401/403/429 fast-exit and 500 retry
behavior

**Sentry issues addressed:**
- AUTOGPT-SERVER-8B6, 8B7, 8B8 — `[LLM-Block] Anthropic API error: Error
code: 401 - invalid x-api-key`
- Any OpenAI 401/403/429 errors hitting the generic exception handler

Part of SECRT-2166

### 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

#### Test plan:
- [x] Unit tests for 401/403/429 Anthropic errors → warning log, no
retry
- [x] Unit tests for 500 Anthropic errors → error log, retry
- [x] Unit tests for 401/403/429 OpenAI errors → warning log, no retry
- [x] Unit tests for 500 OpenAI errors → error log, retry
- [x] Verified USER_ERROR_STATUS_CODES constant is used consistently
- [x] Verified no double-logging in Anthropic handler path

---
Co-authored-by: Zamil Majdy (@majdyz) <zamil.majdy@agpt.co>

---------

Co-authored-by: Zamil Majdy (@majdyz) <zamil.majdy@agpt.co>
2026-03-24 10:59:04 +00:00
Zamil Majdy
ee5382a064 feat(copilot): add tool/block capability filtering to AutoPilotBlock (#12482)
## Summary

- Adds `CopilotPermissions` model (`copilot/permissions.py`) — a
capability filter that restricts which tools and blocks the
AutoPilot/Copilot may use during a single execution
- Exposes 4 new `advanced=True` fields on `AutoPilotBlock`: `tools`,
`tools_exclude`, `blocks`, `blocks_exclude`
- Threads permissions through the full execution path: `AutoPilotBlock`
→ `collect_copilot_response` → `stream_chat_completion_sdk` →
`run_block`
- Implements recursion inheritance via contextvar: sub-agent executions
can only be *more* restrictive than their parent

## Design

**Tool filtering** (`tools` + `tools_exclude`):
- `tools_exclude=True` (default): `tools` is a **blacklist** — listed
tools denied, all others allowed. Empty list = allow all.
- `tools_exclude=False`: `tools` is a **whitelist** — only listed tools
are allowed.
- Users specify short names (`run_block`, `web_fetch`, `Read`, `Task`,
…) — mapped to full SDK format internally.
- Validated eagerly at block-run time with a clear error listing valid
names.

**Block filtering** (`blocks` + `blocks_exclude`):
- Same semantics as tool filtering, applied inside `run_block` via
contextvar.
- Each entry can be a full UUID, an 8-char partial UUID (first segment),
or a case-insensitive block name.
- Validated against the live block registry; invalid identifiers surface
a helpful error before the session is created.

**Recursion inheritance**:
- `_inherited_permissions` contextvar stores the parent execution's
permissions.
- On each `AutoPilotBlock.run()`, the child's permissions are merged
with the parent via `merged_with_parent()` — effective allowed sets are
intersected (tools) and the parent chain is kept for block checks.
- Sub-agents can never expand what the parent allowed.

## Test plan

- [x] 68 new unit tests in `copilot/permissions_test.py` and
`blocks/autopilot_permissions_test.py`
- [x] Block identifier matching: full UUID, partial UUID, name,
case-insensitivity
- [x] Tool allow/deny list semantics including edge cases (empty list,
unknown tool)
- [x] Parent/child merging and recursion ceiling correctness
- [x] `validate_tool_names` / `validate_block_identifiers` with mock
block registry
- [x] `apply_tool_permissions` SDK tool-list integration
- [x] `AutoPilotBlock.run()` — invalid tool/block yields error before
session creation
- [x] `AutoPilotBlock.run()` — valid permissions forwarded to
`execute_copilot`
- [x] Existing `AutoPilotBlock` block tests still pass (2/2)
- [x] All hooks pass (pyright, ruff, black, isort)
- [x] E2E: CoPilot chat works end-to-end with E2B sandbox (12s stream)
- [x] E2E: Permission fields render in Builder UI (Tools combobox,
exclude toggles)
- [x] E2E: Agent with restricted permissions (whitelist web_fetch only)
executes correctly
- [x] E2E: Permission values preserved through API round-trip
2026-03-24 07:49:58 +00:00
Nicholas Tindle
b80e5ea987 fix(backend): allow admins to download submitted agents pending review (#12535)
## Why

Admins cannot download submitted-but-not-yet-approved agents from
`/admin/marketplace`. Clicking "Download" fails silently with a Server
Components render error. This blocks admins from reviewing agents that
companies have submitted.

## What

Remove the redundant ownership/marketplace check from
`get_graph_as_admin()` that was silently tightened in PR #11323 (Nov
2025). Add regression tests for both the admin download path and the
non-admin marketplace access control.

## How

**Root cause:** In PR #11323, Reinier refactored an inline
`StoreListingVersion` query (which had no status filter) into a call to
`is_graph_published_in_marketplace()` (which requires `submissionStatus:
APPROVED`). This was collateral cleanup — his PR focused on sub-agent
execution permissions — but it broke admin download of pending agents.

**Fix:** Remove the ownership/marketplace check from
`get_graph_as_admin()`, keeping only the null guard. This is safe
because `get_graph_as_admin` is only callable through admin-protected
routes (`requires_admin_user` at router level).

**Tests added:**
- `test_admin_can_access_pending_agent_not_owned` — admin can access a
graph they don't own that isn't APPROVED
- `test_admin_download_pending_agent_with_subagents` — admin export
includes sub-graphs
- `test_get_graph_non_owner_approved_marketplace_agent` — protects PR
#11323: non-owners CAN access APPROVED agents
- `test_get_graph_non_owner_pending_marketplace_agent_denied` — protects
PR #11323: non-owners CANNOT access PENDING agents

### 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:
  - [x] 4 regression tests pass locally
  - [x] Admin can download pending agents (verified via unit test)
  - [x] Non-admin marketplace access control preserved

## Test plan
- [ ] Verify admin can download a submitted-but-not-approved agent from
`/admin/marketplace`
- [ ] Verify non-admin users still cannot access admin endpoints
- [ ] Verify the download succeeds without console errors

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

<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> **Medium Risk**
> Changes access-control behavior for admin graph retrieval; risk is
mitigated by route-level admin auth but misuse of `get_graph_as_admin()`
outside admin-protected routes would expose non-approved graphs.
> 
> **Overview**
> Admins can now download/review **submitted-but-not-approved**
marketplace agents: `get_graph_as_admin()` no longer enforces ownership
or *marketplace APPROVED* checks, only returning `None` when the graph
doesn’t exist.
> 
> Adds regression tests covering the admin download/export path
(including sub-graphs) and confirming non-admin behavior is unchanged:
non-owners can fetch **APPROVED** marketplace graphs but cannot access
**pending** ones.
> 
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
a6d2d69ae4. 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>
2026-03-24 07:40:17 +00:00
Zamil Majdy
3d4fcfacb6 fix(backend): add circuit breaker for infinite tool call retry loops (#12499)
## Summary
- Adds a two-layer circuit breaker to prevent AutoPilot from looping
infinitely when tool calls fail with empty parameters
- **Tool-level**: After 3 consecutive identical failures per tool,
returns a hard-stop message instructing the model to output content as
text instead of retrying
- **Stream-level**: After 6 consecutive empty tool calls (`input: {}`),
aborts the stream entirely with a user-visible error and retry button

## Background
In session `c5548b48`, the model completed all research successfully but
then spent 51+ minutes in an infinite loop trying to write output —
every tool call was sent with `input: {}` (likely due to context
saturation preventing argument serialization). 21+ identical failing
tool calls with no circuit breaker.

## Changes
- `tool_adapter.py`: Added `_check_circuit_breaker`,
`_record_tool_failure`, `_clear_tool_failures` functions with a
`ContextVar`-based tracker. Integrated into both `create_tool_handler`
(BaseTool) and the `_truncating` wrapper (all tools).
- `service.py`: Added empty-tool-call detection in the main stream loop
that counts consecutive `AssistantMessage`s with empty
`ToolUseBlock.input` and aborts after the limit.
- `test_circuit_breaker.py`: 7 unit tests covering threshold behavior,
per-args tracking, reset on success, and uninitialized tracker safety.

## Test plan
- [x] Unit tests pass (`pytest
backend/copilot/sdk/test_circuit_breaker.py` — 8/8 passing)
- [x] Pre-commit hooks pass (Ruff, Black, isort, typecheck all pass)
- [x] E2E: CoPilot tool calls work normally (GetCurrentTimeBlock
returned 09:16:39 UTC)
- [x] E2E: Circuit breaker pass-through verified (successful calls don't
trigger breaker)
- [x] E2E: Circuit breaker code integrated into tool_adapter truncating
wrapper
2026-03-24 05:45:12 +00:00
Zamil Majdy
32eac6d52e dx(skills): improve /pr-test to require screenshots, state verification, and fix accountability (#12527)
## Summary
- Add "Critical Requirements" section making screenshots at every step,
PR comment posting, state verification, negative tests, and full
evidence reports non-negotiable
- Add "State Manipulation for Realistic Testing" section with Redis CLI,
DB query, and API before/after patterns
- Strengthen fix mode to require before/after screenshot pairs, rebuild
only affected services, and commit after each fix
- Expand test report format to include API evidence and screenshot
evidence columns
- Bump version to 2.0.0

## Test plan
- [x] Run `/pr-test` on an existing PR and verify it follows the new
critical requirements
- [x] Verify screenshots are posted to PR comment
- [x] Verify fix mode produces before/after screenshot pairs
2026-03-24 12:35:05 +07:00
dependabot[bot]
9762f4cde7 chore(libs/deps-dev): bump the development-dependencies group across 1 directory with 2 updates (#12523)
Bumps the development-dependencies group with 2 updates in the
/autogpt_platform/autogpt_libs directory:
[pytest-cov](https://github.com/pytest-dev/pytest-cov) and
[ruff](https://github.com/astral-sh/ruff).

Updates `pytest-cov` from 7.0.0 to 7.1.0
<details>
<summary>Changelog</summary>
<p><em>Sourced from <a
href="https://github.com/pytest-dev/pytest-cov/blob/master/CHANGELOG.rst">pytest-cov's
changelog</a>.</em></p>
<blockquote>
<h2>7.1.0 (2026-03-21)</h2>
<ul>
<li>
<p>Fixed total coverage computation to always be consistent, regardless
of reporting settings.
Previously some reports could produce different total counts, and
consequently can make --cov-fail-under behave different depending on
reporting options.
See <code>[#641](https://github.com/pytest-dev/pytest-cov/issues/641)
&lt;https://github.com/pytest-dev/pytest-cov/issues/641&gt;</code>_.</p>
</li>
<li>
<p>Improve handling of ResourceWarning from sqlite3.</p>
<p>The plugin adds warning filter for sqlite3
<code>ResourceWarning</code> unclosed database (since 6.2.0).
It checks if there is already existing plugin for this message by
comparing filter regular expression.
When filter is specified on command line the message is escaped and does
not match an expected message.
A check for an escaped regular expression is added to handle this
case.</p>
<p>With this fix one can suppress <code>ResourceWarning</code> from
sqlite3 from command line::</p>
<p>pytest -W &quot;ignore:unclosed database in &lt;sqlite3.Connection
object at:ResourceWarning&quot; ...</p>
</li>
<li>
<p>Various improvements to documentation.
Contributed by Art Pelling in
<code>[#718](https://github.com/pytest-dev/pytest-cov/issues/718)
&lt;https://github.com/pytest-dev/pytest-cov/pull/718&gt;</code>_ and
&quot;vivodi&quot; in
<code>[#738](https://github.com/pytest-dev/pytest-cov/issues/738)
&lt;https://github.com/pytest-dev/pytest-cov/pull/738&gt;</code><em>.
Also closed
<code>[#736](https://github.com/pytest-dev/pytest-cov/issues/736)
&lt;https://github.com/pytest-dev/pytest-cov/issues/736&gt;</code></em>.</p>
</li>
<li>
<p>Fixed some assertions in tests.
Contributed by in Markéta Machová in
<code>[#722](https://github.com/pytest-dev/pytest-cov/issues/722)
&lt;https://github.com/pytest-dev/pytest-cov/pull/722&gt;</code>_.</p>
</li>
<li>
<p>Removed unnecessary coverage configuration copying (meant as a backup
because reporting commands had configuration side-effects before
coverage 5.0).</p>
</li>
</ul>
</blockquote>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a
href="66c8a526b1"><code>66c8a52</code></a>
Bump version: 7.0.0 → 7.1.0</li>
<li><a
href="f707662478"><code>f707662</code></a>
Make the examples use pypy 3.11.</li>
<li><a
href="6049a78478"><code>6049a78</code></a>
Make context test use the old ctracer (seems the new sysmon tracer
behaves di...</li>
<li><a
href="8ebf20bbbc"><code>8ebf20b</code></a>
Update changelog.</li>
<li><a
href="861d30e60d"><code>861d30e</code></a>
Remove the backup context manager - shouldn't be needed since coverage
5.0, ...</li>
<li><a
href="fd4c956014"><code>fd4c956</code></a>
Pass the precision on the nulled total (seems that there's some caching
goion...</li>
<li><a
href="78c9c4ecb0"><code>78c9c4e</code></a>
Only run the 3.9 on older deps.</li>
<li><a
href="4849a922e8"><code>4849a92</code></a>
Punctuation.</li>
<li><a
href="197c35e2f3"><code>197c35e</code></a>
Update changelog and hopefully I don't forget to publish release again
:))</li>
<li><a
href="14dc1c92d4"><code>14dc1c9</code></a>
Update examples to use 3.11 and make the adhoc layout example look a bit
more...</li>
<li>Additional commits viewable in <a
href="https://github.com/pytest-dev/pytest-cov/compare/v7.0.0...v7.1.0">compare
view</a></li>
</ul>
</details>
<br />

Updates `ruff` from 0.15.0 to 0.15.7
<details>
<summary>Release notes</summary>
<p><em>Sourced from <a
href="https://github.com/astral-sh/ruff/releases">ruff's
releases</a>.</em></p>
<blockquote>
<h2>0.15.7</h2>
<h2>Release Notes</h2>
<p>Released on 2026-03-19.</p>
<h3>Preview features</h3>
<ul>
<li>Display output severity in preview (<a
href="https://redirect.github.com/astral-sh/ruff/pull/23845">#23845</a>)</li>
<li>Don't show <code>noqa</code> hover for non-Python documents (<a
href="https://redirect.github.com/astral-sh/ruff/pull/24040">#24040</a>)</li>
</ul>
<h3>Rule changes</h3>
<ul>
<li>[<code>pycodestyle</code>] Recognize <code>pyrefly:</code> as a
pragma comment (<code>E501</code>) (<a
href="https://redirect.github.com/astral-sh/ruff/pull/24019">#24019</a>)</li>
</ul>
<h3>Server</h3>
<ul>
<li>Don't return code actions for non-Python documents (<a
href="https://redirect.github.com/astral-sh/ruff/pull/23905">#23905</a>)</li>
</ul>
<h3>Documentation</h3>
<ul>
<li>Add company AI policy to contributing guide (<a
href="https://redirect.github.com/astral-sh/ruff/pull/24021">#24021</a>)</li>
<li>Document editor features for Markdown code formatting (<a
href="https://redirect.github.com/astral-sh/ruff/pull/23924">#23924</a>)</li>
<li>[<code>pylint</code>] Improve phrasing (<code>PLC0208</code>) (<a
href="https://redirect.github.com/astral-sh/ruff/pull/24033">#24033</a>)</li>
</ul>
<h3>Other changes</h3>
<ul>
<li>Use PEP 639 license information (<a
href="https://redirect.github.com/astral-sh/ruff/pull/19661">#19661</a>)</li>
</ul>
<h3>Contributors</h3>
<ul>
<li><a
href="https://github.com/tmimmanuel"><code>@​tmimmanuel</code></a></li>
<li><a
href="https://github.com/DimitriPapadopoulos"><code>@​DimitriPapadopoulos</code></a></li>
<li><a
href="https://github.com/amyreese"><code>@​amyreese</code></a></li>
<li><a href="https://github.com/statxc"><code>@​statxc</code></a></li>
<li><a href="https://github.com/dylwil3"><code>@​dylwil3</code></a></li>
<li><a
href="https://github.com/hunterhogan"><code>@​hunterhogan</code></a></li>
<li><a
href="https://github.com/renovate"><code>@​renovate</code></a></li>
</ul>
<h2>Install ruff 0.15.7</h2>
<h3>Install prebuilt binaries via shell script</h3>
<pre lang="sh"><code>curl --proto '=https' --tlsv1.2 -LsSf
https://releases.astral.sh/github/ruff/releases/download/0.15.7/ruff-installer.sh
| sh
</code></pre>
<h3>Install prebuilt binaries via powershell script</h3>
<pre lang="sh"><code>powershell -ExecutionPolicy Bypass -c &quot;irm
https://releases.astral.sh/github/ruff/releases/download/0.15.7/ruff-installer.ps1
| iex&quot;
&lt;/tr&gt;&lt;/table&gt; 
</code></pre>
</blockquote>
<p>... (truncated)</p>
</details>
<details>
<summary>Changelog</summary>
<p><em>Sourced from <a
href="https://github.com/astral-sh/ruff/blob/main/CHANGELOG.md">ruff's
changelog</a>.</em></p>
<blockquote>
<h2>0.15.7</h2>
<p>Released on 2026-03-19.</p>
<h3>Preview features</h3>
<ul>
<li>Display output severity in preview (<a
href="https://redirect.github.com/astral-sh/ruff/pull/23845">#23845</a>)</li>
<li>Don't show <code>noqa</code> hover for non-Python documents (<a
href="https://redirect.github.com/astral-sh/ruff/pull/24040">#24040</a>)</li>
</ul>
<h3>Rule changes</h3>
<ul>
<li>[<code>pycodestyle</code>] Recognize <code>pyrefly:</code> as a
pragma comment (<code>E501</code>) (<a
href="https://redirect.github.com/astral-sh/ruff/pull/24019">#24019</a>)</li>
</ul>
<h3>Server</h3>
<ul>
<li>Don't return code actions for non-Python documents (<a
href="https://redirect.github.com/astral-sh/ruff/pull/23905">#23905</a>)</li>
</ul>
<h3>Documentation</h3>
<ul>
<li>Add company AI policy to contributing guide (<a
href="https://redirect.github.com/astral-sh/ruff/pull/24021">#24021</a>)</li>
<li>Document editor features for Markdown code formatting (<a
href="https://redirect.github.com/astral-sh/ruff/pull/23924">#23924</a>)</li>
<li>[<code>pylint</code>] Improve phrasing (<code>PLC0208</code>) (<a
href="https://redirect.github.com/astral-sh/ruff/pull/24033">#24033</a>)</li>
</ul>
<h3>Other changes</h3>
<ul>
<li>Use PEP 639 license information (<a
href="https://redirect.github.com/astral-sh/ruff/pull/19661">#19661</a>)</li>
</ul>
<h3>Contributors</h3>
<ul>
<li><a
href="https://github.com/tmimmanuel"><code>@​tmimmanuel</code></a></li>
<li><a
href="https://github.com/DimitriPapadopoulos"><code>@​DimitriPapadopoulos</code></a></li>
<li><a
href="https://github.com/amyreese"><code>@​amyreese</code></a></li>
<li><a href="https://github.com/statxc"><code>@​statxc</code></a></li>
<li><a href="https://github.com/dylwil3"><code>@​dylwil3</code></a></li>
<li><a
href="https://github.com/hunterhogan"><code>@​hunterhogan</code></a></li>
<li><a
href="https://github.com/renovate"><code>@​renovate</code></a></li>
</ul>
<h2>0.15.6</h2>
<p>Released on 2026-03-12.</p>
<h3>Preview features</h3>
<ul>
<li>Add support for <code>lazy</code> import parsing (<a
href="https://redirect.github.com/astral-sh/ruff/pull/23755">#23755</a>)</li>
<li>Add support for star-unpacking of comprehensions (PEP 798) (<a
href="https://redirect.github.com/astral-sh/ruff/pull/23788">#23788</a>)</li>
<li>Reject semantic syntax errors for lazy imports (<a
href="https://redirect.github.com/astral-sh/ruff/pull/23757">#23757</a>)</li>
<li>Drop a few rules from the preview default set (<a
href="https://redirect.github.com/astral-sh/ruff/pull/23879">#23879</a>)</li>
<li>[<code>airflow</code>] Flag <code>Variable.get()</code> calls
outside of task execution context (<code>AIR003</code>) (<a
href="https://redirect.github.com/astral-sh/ruff/pull/23584">#23584</a>)</li>
<li>[<code>airflow</code>] Flag runtime-varying values in DAG/task
constructor arguments (<code>AIR304</code>) (<a
href="https://redirect.github.com/astral-sh/ruff/pull/23631">#23631</a>)</li>
<li>[<code>flake8-bugbear</code>] Implement
<code>delattr-with-constant</code> (<code>B043</code>) (<a
href="https://redirect.github.com/astral-sh/ruff/pull/23737">#23737</a>)</li>
</ul>
<!-- raw HTML omitted -->
</blockquote>
<p>... (truncated)</p>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a
href="0ef39de46c"><code>0ef39de</code></a>
Bump 0.15.7 (<a
href="https://redirect.github.com/astral-sh/ruff/issues/24049">#24049</a>)</li>
<li><a
href="beb543b5c6"><code>beb543b</code></a>
[ty] ecosystem-analyzer: Fail on newly panicking projects (<a
href="https://redirect.github.com/astral-sh/ruff/issues/24043">#24043</a>)</li>
<li><a
href="378fe73092"><code>378fe73</code></a>
Don't show noqa hover for non-Python documents (<a
href="https://redirect.github.com/astral-sh/ruff/issues/24040">#24040</a>)</li>
<li><a
href="b5665bd18e"><code>b5665bd</code></a>
[<code>pylint</code>] Improve phrasing (<code>PLC0208</code>) (<a
href="https://redirect.github.com/astral-sh/ruff/issues/24033">#24033</a>)</li>
<li><a
href="6e20f22190"><code>6e20f22</code></a>
test: migrate <code>show_settings</code> and <code>version</code> tests
to use <code>CliTest</code> (<a
href="https://redirect.github.com/astral-sh/ruff/issues/23702">#23702</a>)</li>
<li><a
href="f99b284c1f"><code>f99b284</code></a>
Drain file watcher events during test setup (<a
href="https://redirect.github.com/astral-sh/ruff/issues/24030">#24030</a>)</li>
<li><a
href="744c996c35"><code>744c996</code></a>
[ty] Filter out unsatisfiable inference attempts during generic call
narrowin...</li>
<li><a
href="16160958bd"><code>1616095</code></a>
[ty] Avoid inferring intersection types for call arguments (<a
href="https://redirect.github.com/astral-sh/ruff/issues/23933">#23933</a>)</li>
<li><a
href="7f275f431b"><code>7f275f4</code></a>
[ty] Pin mypy_primer in <code>setup_primer_project.py</code> (<a
href="https://redirect.github.com/astral-sh/ruff/issues/24020">#24020</a>)</li>
<li><a
href="7255e362e4"><code>7255e36</code></a>
[<code>pycodestyle</code>] Recognize <code>pyrefly:</code> as a pragma
comment (<code>E501</code>) (<a
href="https://redirect.github.com/astral-sh/ruff/issues/24019">#24019</a>)</li>
<li>Additional commits viewable in <a
href="https://github.com/astral-sh/ruff/compare/0.15.0...0.15.7">compare
view</a></li>
</ul>
</details>
<br />


Dependabot will resolve any conflicts with this PR as long as you don't
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`@dependabot rebase`.

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Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2026-03-24 01:36:45 +00:00
Otto
76901ba22f docs: add Why/What/How structure to PR template, CLAUDE.md, and PR skills (#12525)
Requested by @majdyz

### Why / What / How

**Why:** PR descriptions currently explain the *what* and *how* but not
the *why*. Without motivation context, reviewers can't judge whether an
approach fits the problem. Nick flagged this in standup: "The PR
descriptions you use are explaining the what not the why."

**What:** Adds a consistent Why / What / How structure to PR
descriptions across the entire workflow — template, CLAUDE.md guidance,
and all PR-related skills (`/pr-review`, `/pr-test`, `/pr-address`).

**How:**
- **`.github/PULL_REQUEST_TEMPLATE.md`**: Replaced the old vague
`Changes` heading with a single `Why / What / How` section with guiding
comments
- **`autogpt_platform/CLAUDE.md`**: Added bullet under "Creating Pull
Requests" requiring the Why/What/How structure
- **`.claude/skills/pr-review/SKILL.md`**: Added "Read the PR
description" step before reading the diff, and "Description quality" to
the review checklist
- **`.claude/skills/pr-test/SKILL.md`**: Updated Step 1 to read the PR
description and understand Why/What/How before testing
- **`.claude/skills/pr-address/SKILL.md`**: Added "Read the PR
description" step before fetching comments

## Test plan
- [x] All five files reviewed for correct formatting and consistency

---
Co-authored-by: Zamil Majdy (@majdyz) <zamil.majdy@agpt.co>
2026-03-24 01:35:39 +00:00
Zamil Majdy
23b65939f3 fix(backend/db): add DB_STATEMENT_CACHE_SIZE env var for Prisma engine (#12521)
## Summary
- Add `DB_STATEMENT_CACHE_SIZE` env var support for Prisma query engine
- Wires through as `statement_cache_size` URL parameter to control the
LRU prepared statement cache per connection in the Rust binary engine

## Why
Live investigation on dev pods showed the Prisma Rust engine growing
from 34MB to 932MB over ~1hr due to unbounded query plan cache. Despite
`pgbouncer=true` in the DATABASE_URL (which should disable caching), the
engine still caches.

This gives explicit control: setting `DB_STATEMENT_CACHE_SIZE=0`
disables the cache entirely.

## Live data (dev)
```
Fresh pod:  Python=693MB, Engine=34MB,  Total=727MB
Bloated:    Python=2.1GB, Engine=932MB, Total=3GB
```

## Infra companion PR

[AutoGPT_cloud_infrastructure#299](https://github.com/Significant-Gravitas/AutoGPT_cloud_infrastructure/pull/299)
sets `DB_STATEMENT_CACHE_SIZE=0` along with `PYTHONMALLOC=malloc` and
memory limit changes.

## Test plan
- [ ] Deploy to dev and monitor Prisma engine memory over 1hr
- [ ] Verify queries still work correctly with cache disabled
- [ ] Compare engine RSS on fresh vs aged pods
2026-03-23 23:57:28 +07:00
Zamil Majdy
1c27eaac53 dx(skills): improve /pr-test skill to show screenshots with explanations (#12518)
## Summary
- Update /pr-test skill to consistently show screenshots inline to the
user with explanations
- Post PR comments with inline images and per-screenshot descriptions
(not just local file paths)
- Simplify GitHub Git API upload flow for screenshot hosting

## Changes
- Step 5: Take screenshots at every significant test step (aim for 1+
per scenario)
- Step 6 (new): Show every screenshot to the user via Read tool with 2-3
sentence explanations
- Step 7: Post PR comment with inline images, summary table, and
per-screenshot context

## Test plan
- [x] Tested end-to-end on PR #12512 — screenshots uploaded and rendered
correctly in PR comment
2026-03-23 23:11:21 +07:00
Zamil Majdy
923b164794 fix(backend): use system chromium for agent-browser on all architectures (#12473)
## Summary

- Replaces the arch-conditional chromium install (ARM64 vs AMD64) with a
single approach: always use the distro-packaged `chromium` and set
`AGENT_BROWSER_EXECUTABLE_PATH=/usr/bin/chromium`
- Removes `agent-browser install` entirely (it downloads Chrome for
Testing, which has no ARM64 binary)
- Removes the `entrypoint.sh` wrapper script that was setting the env
var at runtime
- Updates `autogpt_platform/db/docker/docker-compose.yml`: removes
`external: true` from the network declarations so the Supabase stack can
be brought up standalone (needed for the Docker integration tests in the
test plan below — without this, `docker compose up` fails unless the
platform stack is already running); also sets
`GOTRUE_MAILER_AUTOCONFIRM: true` for local dev convenience (no SMTP
setup required on first run — this compose file is not used in
production)
- Updates `autogpt_platform/docker-compose.platform.yml`: mounts the
`workspace` volume so agent-browser results (screenshots, snapshots) are
accessible from other services; without this the copilot workspace write
fails in Docker

## Verification

Tested via Docker build on arm64 (Apple Silicon):
```
=== Testing agent-browser with system chromium ===
✓ Example Domain
  https://example.com/
=== SUCCESS: agent-browser launched with system chromium ===
```
agent-browser navigated to example.com in ~1.5s using system chromium
(v146 from Debian trixie).

## Test plan

- [x] Docker build test on arm64: `agent-browser open
https://example.com` succeeds with system chromium
- [x] Verify amd64 Docker build still works (CI)
2026-03-23 20:54:03 +07:00
Zamil Majdy
e86ac21c43 feat(platform): add workflow import from other tools (n8n, Make.com, Zapier) (#12440)
## Summary
- Enable one-click import of workflows from other platforms (n8n,
Make.com, Zapier, etc.) into AutoGPT via CoPilot
- **No backend endpoint** — import is entirely client-side: the dialog
reads the file or fetches the n8n template URL, uploads the JSON to the
workspace via `uploadFileDirect`, stores the file reference in
`sessionStorage`, and redirects to CoPilot with `autosubmit=true`
- CoPilot receives the workflow JSON as a proper file attachment and
uses the existing agent-generator pipeline to convert it
- Library dialog redesigned: 2 tabs — "AutoGPT agent" (upload exported
agent JSON) and "Another platform" (file upload + optional n8n URL)

## How it works
1. User uploads a workflow JSON (or pastes an n8n template URL)
2. Frontend fetches/reads the JSON and uploads it to the user's
workspace via the existing file upload API
3. User is redirected to `/copilot?source=import&autosubmit=true`
4. CoPilot picks up the file from `sessionStorage` and sends it as a
`FileUIPart` attachment with a prompt to recreate the workflow as an
AutoGPT agent

## Test plan
- [x] Manual test: import a real n8n workflow JSON via the dialog
- [x] Manual test: paste an n8n template URL and verify it fetches +
converts
- [x] Manual test: import Make.com / Zapier workflow export JSON
- [x] Repeated imports don't cause 409 conflicts (filenames use
`crypto.randomUUID()`)
- [x] E2E: Import dialog has 2 tabs (AutoGPT agent + Another platform)
- [x] E2E: n8n quick-start template buttons present
- [x] E2E: n8n URL input enables Import button on valid URL
- [x] E2E: Workspace upload API returns file_id
2026-03-23 13:03:02 +00:00
Lluis Agusti
94224be841 Merge remote-tracking branch 'origin/master' into dev 2026-03-23 20:42:32 +08:00
Otto
da4bdc7ab9 fix(backend+frontend): reduce Sentry noise from user-caused errors (#12513)
Requested by @majdyz

User-caused errors (no payment method, webhook agent invocation, missing
credentials, bad API keys) were hitting Sentry via `logger.exception()`
in the `ValueError` handler, creating noise that obscures real bugs.
Additionally, a frontend crash on the copilot page (BUILDER-71J) needed
fixing.

**Changes:**

**Backend — rest_api.py**
- Set `log_error=False` for the `ValueError` exception handler (line
278), consistent with how `FolderValidationError` and `NotFoundError`
are already handled. User-caused 400 errors no longer trigger
`logger.exception()` → Sentry.

**Backend — executor/manager.py**
- Downgrade `ExecutionManager` input validation skip errors from `error`
to `warning` level. Missing credentials is expected user behavior, not
an internal error.

**Backend — blocks/llm.py**
- Sanitize unpaired surrogates in LLM prompt content before sending to
provider APIs. Prevents `UnicodeEncodeError: surrogates not allowed`
when httpx encodes the JSON body (AUTOGPT-SERVER-8AX).

**Frontend — package.json**
- Upgrade `ai` SDK from `6.0.59` to `6.0.134` to fix BUILDER-71J
(`TypeError: undefined is not an object (evaluating
'this.activeResponse.state')` on /copilot page). This is a known issue
in the Vercel AI SDK fixed in later patch versions.

**Sentry issues addressed:**
- `No payment method found` (ValueError → 400)
- `This agent is triggered by an external event (webhook)` (ValueError →
400)
- `Node input updated with non-existent credentials` (ValueError → 400)
- `[ExecutionManager] Skip execution, input validation error: missing
input {credentials}`
- `UnicodeEncodeError: surrogates not allowed` (AUTOGPT-SERVER-8AX)
- `TypeError: activeResponse.state` (BUILDER-71J)

Resolves SECRT-2166

---
Co-authored-by: Zamil Majdy (@majdyz) <zamil.majdy@agpt.co>

---------

Co-authored-by: Zamil Majdy (@majdyz) <zamil.majdy@agpt.co>
2026-03-23 12:22:49 +00:00
Zamil Majdy
7176cecf25 perf(copilot): reduce tool schema token cost by 34% (#12398)
## Summary

Reduce CoPilot per-turn token overhead by systematically trimming tool
descriptions, parameter schemas, and system prompt content. All 35 MCP
tool schemas are passed on every SDK call — this PR reduces their size.

### Strategy

1. **Tool descriptions**: Trimmed verbose multi-sentence explanations to
concise single-sentence summaries while preserving meaning
2. **Parameter schemas**: Shortened parameter descriptions to essential
info, removed some `default` values (handled in code)
3. **System prompt**: Condensed `_SHARED_TOOL_NOTES` and storage
supplement template in `prompting.py`
4. **Cross-tool references**: Removed duplicate workflow hints (e.g.
"call find_block before run_block" appeared in BOTH tools — kept only in
the dependent tool). Critical cross-tool references retained (e.g.
`continue_run_block` in `run_block`, `fix_agent_graph` in
`validate_agent`, `get_doc_page` in `search_docs`, `web_fetch`
preference in `browser_navigate`)

### Token Impact

| Metric | Before | After | Reduction |
|--------|--------|-------|-----------|
| System Prompt | ~865 tokens | ~497 tokens | 43% |
| Tool Schemas | ~9,744 tokens | ~6,470 tokens | 34% |
| **Grand Total** | **~10,609 tokens** | **~6,967 tokens** | **34%** |

Saves **~3,642 tokens per conversation turn**.

### Key Decisions

- **Mostly description changes**: Tool logic, parameters, and types
unchanged. However, some schema-level `default` fields were removed
(e.g. `save` in `customize_agent`) — these are machine-readable
metadata, not just prose, and may affect LLM behavior.
- **Quality preserved**: All descriptions still convey what the tool
does and essential usage patterns
- **Cross-references trimmed carefully**: Kept prerequisite hints in the
dependent tool (run_block mentions find_block) but removed the reverse
(find_block no longer mentions run_block). Critical cross-tool guidance
retained where removal would degrade model behavior.
- **`run_time` description fixed**: Added missing supported values
(today, last 30 days, ISO datetime) per review feedback

### Future Optimization

The SDK passes all 35 tools on every call. The MCP protocol's
`list_tools()` handler supports dynamic tool registration — a follow-up
PR could implement lazy tool loading (register core tools + a discovery
meta-tool) to further reduce per-turn token cost.

### Changes

- Trimmed descriptions across 25 tool files
- Condensed `_SHARED_TOOL_NOTES` and `_build_storage_supplement` in
`prompting.py`
- Fixed `run_time` schema description in `agent_output.py`

### 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 273 copilot tests pass locally
  - [x] All 35 tools load and produce valid schemas
  - [x] Before/after token dumps compared
  - [x] Formatting passes (`poetry run format`)
  - [x] CI green
2026-03-23 08:27:24 +00:00
Zamil Majdy
f35210761c feat(devops): add /pr-test skill + subscription mode auto-provisioning (#12507)
## Summary
- Adds `/pr-test` skill for automated E2E testing of PRs using docker
compose, agent-browser, and API calls
- Covers full environment setup (copy .env, configure copilot auth,
ARM64 Docker fix)
- Includes browser UI testing, direct API testing, screenshot capture,
and test report generation
- Has `--fix` mode for auto-fixing bugs found during testing (similar to
`/pr-address`)
- **Screenshot uploads use GitHub Git API** (blobs → tree → commit →
ref) — no local git operations, safe for worktrees
- **Subscription mode improvements:**
- Extract subscription auth logic to `sdk/subscription.py` — uses SDK's
bundled CLI binary instead of requiring `npm install -g
@anthropic-ai/claude-code`
- Auto-provision `~/.claude/.credentials.json` from
`CLAUDE_CODE_OAUTH_TOKEN` env var on container startup — no `claude
login` needed in Docker
- Add `scripts/refresh_claude_token.sh` — cross-platform helper
(macOS/Linux/Windows) to extract OAuth tokens from host and update
`backend/.env`

## Test plan
- [x] Validated skill on multiple PRs (#12482, #12483, #12499, #12500,
#12501, #12440, #12472) — all test scenarios passed
- [x] Confirmed screenshot upload via GitHub Git API renders correctly
on all 7 PRs
- [x] Verified subscription mode E2E in Docker:
`refresh_claude_token.sh` → `docker compose up` → copilot chat responds
correctly with no API keys (pure OAuth subscription)
- [x] Verified auto-provisioning of credentials file inside container
from `CLAUDE_CODE_OAUTH_TOKEN` env var
- [x] Confirmed bundled CLI detection
(`claude_agent_sdk._bundled/claude`) works without system-installed
`claude`
- [x] `poetry run pytest backend/copilot/sdk/service_test.py` — 24/24
tests pass
2026-03-23 15:29:00 +07:00
Zamil Majdy
1ebcf85669 fix(platform): resolve 5 production Sentry alerts (#12496)
## Summary

Fixes 5 high-priority Sentry alerts from production:

- **AUTOGPT-SERVER-8AM**: Fix `TypeError: TypedDict does not support
instance and class checks` — `_value_satisfies_type` in `type.py` now
handles TypedDict classes that don't support `isinstance()` checks
- **AUTOGPT-SERVER-8AN**: Fix `ValueError: No payment method found`
triggering Sentry error — catch the expected ValueError in the
auto-top-up endpoint and return HTTP 422 instead
- **BUILDER-7F5**: Fix `Upload failed (409): File already exists` — add
`overwrite` query param to workspace upload endpoint and set it to
`true` from the frontend direct-upload
- **BUILDER-7F0**: Fix `LaTeX-incompatible input` KaTeX warnings
flooding Sentry — set `strict: false` on rehype-katex plugin to suppress
warnings for unrecognized Unicode characters
- **AUTOGPT-SERVER-89N**: Fix `Tool execution with manager failed:
validation error for dict[str,list[any]]` — make RPC return type
validation resilient (log warning instead of crash) and downgrade
SmartDecisionMaker tool execution errors to warnings

## Test plan
- [ ] Verify TypedDict type coercion works for
GithubMultiFileCommitBlock inputs
- [ ] Verify auto-top-up without payment method returns 422, not 500
- [ ] Verify file re-upload in copilot succeeds (overwrites instead of
409)
- [ ] Verify LaTeX rendering with Unicode characters doesn't produce
console warnings
- [ ] Verify SmartDecisionMaker tool execution failures are logged at
warning level
2026-03-23 08:05:08 +00:00
Otto
ab7c38bda7 fix(frontend): detect closed OAuth popup and allow dismissing waiting modal (#12443)
Requested by @kcze

When a user closes the OAuth sign-in popup without completing
authentication, the 'Waiting on sign-in process' modal was stuck open
with no way to dismiss it, forcing a page refresh.

Two bugs caused this:

1. `oauth-popup.ts` had no detection for the popup being closed by the
user. The promise would hang until the 5-minute timeout.

2. The modal's cancel button aborted a disconnected `AbortController`
instead of the actual OAuth flow's abort function, so clicking
cancel/close did nothing.

### Changes

- Add `popup.closed` polling (500ms) in `openOAuthPopup()` that rejects
the promise when the user closes the auth window
- Add reject-on-abort so the cancel button properly terminates the flow
- Replace the disconnected `oAuthPopupController` with a direct
`cancelOAuthFlow()` function that calls the real abort ref
- Handle popup-closed and user-canceled as silent cancellations (no
error toast)

### Testing

Tested manually 
- [x] Start OAuth flow → close popup window → modal dismisses
automatically 
- [x] Start OAuth flow → click cancel on modal → popup closes, modal
dismisses 
- [x] Complete OAuth flow normally → works as before 

Resolves SECRT-2054

---
Co-authored-by: Krzysztof Czerwinski (@kcze)
<krzysztof.czerwinski@agpt.co>

---------

Co-authored-by: Krzysztof Czerwinski <kpczerwinski@gmail.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-20 14:41:09 +00:00
Ubbe
0f67e45d05 hotfix(marketplace): adjust card height overflow (#12497)
## Summary

### Before

<img width="500" height="501" alt="Screenshot 2026-03-20 at 21 50 31"
src="https://github.com/user-attachments/assets/6154cffb-6772-4c3d-a703-527c8ca0daff"
/>

### After

<img width="500" height="581" alt="Screenshot 2026-03-20 at 21 33 12"
src="https://github.com/user-attachments/assets/2f9bd69d-30c5-4d06-ad1e-ed76b184afe5"
/>

### Other minor fixes

- minor spacing adjustments in creator/search pages when empty and
between sections


### Summary

- Increase StoreCard height from 25rem to 26.5rem to prevent content
overflow
- Replace manual tooltip-based title truncation with `OverflowText`
component in StoreCard
- Adjust carousel indicator positioning and hide it on md+ when exactly
3 featured agents are shown

## Test plan
- [x] Verify marketplace cards display without text overflow
- [x] Verify featured section carousel indicators behave correctly
- [x] Check responsive behavior at common breakpoints

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

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-20 22:03:28 +08:00
Ubbe
b9ce37600e refactor(frontend/marketplace): move download below Add to library with contextual text (#12486)
## Summary

<img width="1487" height="670" alt="Screenshot 2026-03-20 at 00 52 58"
src="https://github.com/user-attachments/assets/f09de2a0-3c5b-4bce-b6f4-8a853f6792cf"
/>


- Move the download button from inline next to "Add to library" to a
separate line below it
- Add contextual text: "Want to use this agent locally? Download here"
- Style the "Download here" as a violet ghost button link with the
download icon

## Test plan
- [ ] Visit a marketplace agent page
- [ ] Verify "Add to library" button renders in its row
- [ ] Verify "Want to use this agent locally? Download here" appears
below it
- [ ] Click "Download here" and confirm the agent downloads correctly

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

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-20 13:13:59 +00:00
Otto
3921deaef1 fix(frontend): truncate marketplace card description to 2 lines (#12494)
Reduces `line-clamp` from 3 to 2 on the marketplace `StoreCard`
description to prevent text from overlapping with the
absolutely-positioned run count and +Add button at the bottom of the
card.

Resolves SECRT-2156.

---
Co-authored-by: Abhimanyu Yadav (@Abhi1992002)
<122007096+Abhi1992002@users.noreply.github.com>
2026-03-20 09:10:21 +00:00
Nicholas Tindle
f01f668674 fix(backend): support Responses API in SmartDecisionMakerBlock (#12489)
## Summary

- Fixes SmartDecisionMakerBlock conversation management to work with
OpenAI's Responses API, which was introduced in #12099 (commit 1240f38)
- The migration to `responses.create` updated the outbound LLM call but
missed the conversation history serialization — the `raw_response` is
now the entire `Response` object (not a `ChatCompletionMessage`), and
tool calls/results use `function_call` / `function_call_output` types
instead of role-based messages
- This caused a 400 error on the second LLM call in agent mode:
`"Invalid value: ''. Supported values are: 'assistant', 'system',
'developer', and 'user'."`

### Changes

**`smart_decision_maker.py`** — 6 functions updated:
| Function | Fix |
|---|---|
| `_convert_raw_response_to_dict` | Detects Responses API `Response`
objects, extracts output items as a list |
| `_get_tool_requests` | Recognizes `type: "function_call"` items |
| `_get_tool_responses` | Recognizes `type: "function_call_output"`
items |
| `_create_tool_response` | New `responses_api` kwarg produces
`function_call_output` format |
| `_update_conversation` | Handles list return from
`_convert_raw_response_to_dict` |
| Non-agent mode path | Same list handling for traditional execution |

**`test_smart_decision_maker_responses_api.py`** — 61 tests covering:
- Every branch of all 6 affected helper functions
- Chat Completions, Anthropic, and Responses API formats
- End-to-end agent mode and traditional mode conversation validity

## Test plan

- [x] 61 new unit tests all pass
- [x] 11 existing SmartDecisionMakerBlock tests still pass (no
regressions)
- [x] All pre-commit hooks pass (ruff, black, isort, pyright)
- [ ] CI integration tests

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

<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> **Medium Risk**
> Updates core LLM invocation and agent conversation/tool-call
bookkeeping to match OpenAI’s Responses API, which can affect tool
execution loops and prompt serialization across providers. Risk is
mitigated by extensive new unit tests, but regressions could surface in
production agent-mode flows or token/usage accounting.
> 
> **Overview**
> **Migrates OpenAI calls from Chat Completions to the Responses API
end-to-end**, including tool schema conversion, output parsing,
reasoning/text extraction, and updated token usage fields in
`LLMResponse`.
> 
> **Fixes SmartDecisionMakerBlock conversation/tool handling for
Responses API** by treating `raw_response` as a Response object
(splitting it into `output` items for replay), recognizing
`function_call`/`function_call_output` entries, and emitting tool
outputs in the correct Responses format to prevent invalid follow-up
prompts.
> 
> Also adjusts prompt compaction/token estimation to understand
Responses API tool items, changes
`get_execution_outputs_by_node_exec_id` to return list-valued
`CompletedBlockOutput`, removes `gpt-3.5-turbo` from model/cost/docs
lists, and adds focused unit tests plus a lightweight `conftest.py` to
run these tests without the full server stack.
> 
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
ff292efd3d. 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>
Co-authored-by: Otto <otto@agpt.co>
Co-authored-by: Krzysztof Czerwinski <kpczerwinski@gmail.com>
2026-03-20 03:23:52 +00:00
Otto
f7a3491f91 docs(platform): add TDD guidance to CLAUDE.md files (#12491)
Requested by @majdyz

Adds TDD (test-driven development) guidance to CLAUDE.md files so Claude
Code follows a test-first workflow when fixing bugs or adding features.

**Changes:**
- **Parent `CLAUDE.md`**: Cross-cutting TDD workflow — write a failing
`xfail` test, implement the fix, remove the marker
- **Backend `CLAUDE.md`**: Concrete pytest example with
`@pytest.mark.xfail` pattern
- **Frontend `CLAUDE.md`**: Note about using Playwright `.fixme`
annotation for bug-fix tests

The workflow is: write a failing test first → confirm it fails for the
right reason → implement → confirm it passes. This ensures every bug fix
is covered by a test that would have caught the regression.

---
Co-authored-by: Zamil Majdy (@majdyz) <zamil.majdy@agpt.co>
2026-03-20 02:13:16 +00:00
Nicholas Tindle
cbff3b53d3 Revert "feat(backend): migrate OpenAI provider to Responses API" (#12490)
Reverts Significant-Gravitas/AutoGPT#12099

<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> **Medium Risk**
> Reverts the OpenAI integration in `llm_call` from the Responses API
back to `chat.completions`, which can change tool-calling, JSON-mode
behavior, and token accounting across core AI blocks. The change is
localized but touches the primary LLM execution path and associated
tests/docs.
> 
> **Overview**
> Reverts the OpenAI path in `backend/blocks/llm.py` from the Responses
API back to `chat.completions`, including updating JSON-mode
(`response_format`), tool handling, and usage extraction to match the
Chat Completions response shape.
> 
> Removes the now-unused `backend/util/openai_responses.py` helpers and
their unit tests, updates LLM tests to mock `chat.completions.create`,
and adds `gpt-3.5-turbo` to the supported model list, cost config, and
LLM docs.
> 
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
7d6226d10e. This will update automatically
on new commits. Configure
[here](https://cursor.com/dashboard?tab=bugbot).</sup>
<!-- /CURSOR_SUMMARY -->
2026-03-20 01:51:56 +00:00
Reinier van der Leer
5b9a4c52c9 revert(platform): Revert invite system (#12485)
## Summary

Reverts the invite system PRs due to security gaps identified during
review:

- The move from Supabase-native `allowed_users` gating to
application-level gating allows orphaned Supabase auth accounts (valid
JWT without a platform `User`)
- The auth middleware never verifies `User` existence, so orphaned users
get 500s instead of clean 403s
- OAuth/Google SSO signup completely bypasses the invite gate
- The DB trigger that atomically created `User` + `Profile` on signup
was dropped in favor of a client-initiated API call, introducing a
failure window

### Reverted PRs
- Reverts #12347 — Foundation: InvitedUser model, invite-gated signup,
admin UI
- Reverts #12374 — Tally enrichment: personalized prompts from form
submissions
- Reverts #12451 — Pre-check: POST /auth/check-invite endpoint
- Reverts #12452 (collateral) — Themed prompt categories /
SuggestionThemes UI. This PR built on top of #12374's
`suggested_prompts` backend field and `/chat/suggested-prompts`
endpoint, so it cannot remain without #12374. The copilot empty session
falls back to hardcoded default prompts.

### Migration
Includes a new migration (`20260319120000_revert_invite_system`) that:
- Drops the `InvitedUser` table and its enums (`InvitedUserStatus`,
`TallyComputationStatus`)
- Restores the `add_user_and_profile_to_platform()` trigger on
`auth.users`
- Backfills `User` + `Profile` rows for any auth accounts created during
the invite-gate window

### What's NOT reverted
- The `generate_username()` function (never dropped, still used by
backfill migration)
- The old `add_user_to_platform()` function (superseded by
`add_user_and_profile_to_platform()`)
- PR #12471 (admin UX improvements) — was never merged, no action needed

## Test plan
- [x] Verify migration: `InvitedUser` table dropped, enums dropped,
trigger restored
- [x] Verify backfill: no orphaned auth users, no users without Profile
- [x] Verify existing users can still log in (email + OAuth)
- [x] Verify CoPilot chat page loads with default prompts
- [ ] Verify new user signup creates `User` + `Profile` via the restored
trigger
- [ ] Verify admin `/admin/users` page loads without crashing
- [ ] Run backend tests: `poetry run test`

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

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
2026-03-19 17:15:30 +00:00
Otto
0ce1c90b55 fix(frontend): rename "CoPilot" to "AutoPilot" on credits page (#12481)
Requested by @kcze

Renames "CoPilot" → "AutoPilot" on the credits/usage limits page:

- **Heading:** "CoPilot Usage Limits" → "AutoPilot Usage Limits"
- **Button:** "Open CoPilot" → "Open AutoPilot"
- Comment updated to match

---
Co-authored-by: Zamil Majdy (@majdyz) <zamil.majdy@agpt.co>

Co-authored-by: Zamil Majdy (@majdyz) <zamil.majdy@agpt.co>
2026-03-19 15:25:21 +00:00
Ubbe
d4c6eb9adc fix(frontend): collapse navbar text to icons below 1280px (#12484)
## Summary

<img width="400" height="339" alt="Screenshot 2026-03-19 at 22 53 23"
src="https://github.com/user-attachments/assets/2fa76b8f-424d-4764-90ac-b7a331f5f610"
/>

<img width="600" height="595" alt="Screenshot 2026-03-19 at 22 53 31"
src="https://github.com/user-attachments/assets/23f51cc7-b01e-4d83-97ba-2c43683877db"
/>

<img width="800" height="523" alt="Screenshot 2026-03-19 at 22 53 36"
src="https://github.com/user-attachments/assets/1e447b9a-1cca-428c-bccd-1730f1670b8e"
/>

Now that we have the `Give feedback` button on the Navigation bar,
collpase some of the links below `1280px` so there is more space and
they don't collide with each other...

- Collapse navbar link text to icon-only below 1280px (`xl` breakpoint)
to prevent crowding
- Wallet button shows only the wallet icon below 1280px instead of "Earn
credits" text
- Feedback button shows only the chat icon below 1280px instead of "Give
Feedback" text
- Added `whitespace-nowrap` to feedback button to prevent wrapping

## Changes
- `NavbarLink.tsx`: `lg:block` → `xl:block` for link text
- `Wallet.tsx`: `md:hidden`/`md:inline-block` →
`xl:hidden`/`xl:inline-block`
- `FeedbackButton.tsx`: wrap text in `hidden xl:inline` span, add
`whitespace-nowrap`

## Test plan
- [ ] Resize browser between 1024px–1280px and verify navbar shows only
icons
- [ ] At 1280px+ verify full text labels appear for links, wallet, and
feedback
- [ ] Verify mobile navbar still works correctly below `md` breakpoint

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

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-19 15:10:27 +00:00
Ubbe
1bb91b53b7 fix(frontend/marketplace): comprehensive marketplace UI redesign (#12462)
## Summary

<img width="600" height="964" alt="Screenshot_2026-03-19_at_00 07 52"
src="https://github.com/user-attachments/assets/95c0430a-26a3-499b-8f6a-25b9715d3012"
/>
<img width="600" height="968" alt="Screenshot_2026-03-19_at_00 08 01"
src="https://github.com/user-attachments/assets/d440c3b0-c247-4f13-bf82-a51ff2e50902"
/>
<img width="600" height="939" alt="Screenshot_2026-03-19_at_00 08 14"
src="https://github.com/user-attachments/assets/f19be759-e102-4a95-9474-64f18bce60cf"
/>"
<img width="600" height="953" alt="Screenshot_2026-03-19_at_00 08 24"
src="https://github.com/user-attachments/assets/ba4fa644-3958-45e2-89e9-a6a4448c63c5"
/>



- Re-style and re-skin the Marketplace pages to look more "professional"
...
- Move the `Give feedback` button to the header

## Test plan
- [x] Verify marketplace page search bar matches Form text field styling
- [x] Verify agent cards have padding and subtle border
- [x] Verify hover/focus states work correctly
- [x] Check responsive behavior at different breakpoints

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

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-19 22:28:01 +08:00
Ubbe
a5f9c43a41 feat(platform): replace suggestion pills with themed prompt categories (#12452)
## Summary



https://github.com/user-attachments/assets/13da6d36-5f35-429b-a6cf-e18316bb8709



Replaces the flat list of suggestion pills in the CoPilot empty session
with themed prompt categories (Learn, Create, Automate, Organize), each
shown as a popover with contextual prompts.

- **Backend**: Changes `suggested_prompts` from a flat `list[str]` to a
themed `dict[str, list[str]]` keyed by category. Updates Tally
extraction LLM prompt to generate prompts per theme, and the
`/suggested-prompts` API to return grouped themes. Legacy `list[str]`
rows are preserved under a `"General"` key for backward compatibility.
- **Frontend**: Replaces inline pill buttons with a `SuggestionThemes`
popover component. Each theme button (with icon) opens a dropdown of 5
relevant prompts. Falls back to hardcoded defaults when the API has no
personalized prompts. Normalizes partial API responses by padding
missing themes with defaults. Legacy `"General"` prompts are distributed
round-robin across themes so existing users keep their personalized
suggestions.

### Changes 🏗️

- `backend/data/understanding.py`: `suggested_prompts` field changed
from `list[str]` to `dict[str, list[str]]`; legacy list rows preserved
under `"General"` key; list items validated as strings
- `backend/data/tally.py`: LLM prompt updated to generate themed
prompts; validation now per-theme with blank-string rejection
- `backend/api/features/chat/routes.py`: New `SuggestedTheme` model;
endpoint returns `themes[]`
- `frontend/copilot/components/EmptySession/EmptySession.tsx`: Uses
generated API types directly (no cast)
- `frontend/copilot/components/EmptySession/helpers.ts`:
`DEFAULT_THEMES` replaces `DEFAULT_QUICK_ACTIONS`; `getSuggestionThemes`
normalizes partial API responses and distributes legacy `"General"`
prompts across themes
-
`frontend/copilot/components/EmptySession/components/SuggestionThemes/`:
New popover component with theme icons and loading states

### 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 themed suggestion buttons render on CoPilot empty session
  - [x] Click each theme button and confirm popover opens with prompts
  - [x] Click a prompt and confirm it sends the message
- [x] Verify fallback to default themes when API returns no custom
prompts
- [x] Verify legacy users' personalized prompts are preserved and
visible


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

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-19 18:46:12 +08:00
Otto
1240f38f75 feat(backend): migrate OpenAI provider to Responses API (#12099)
## Summary

Migrates the OpenAI provider in the LLM block from
`chat.completions.create` to `responses.create` — OpenAI's newer,
unified API. Also removes the obsolete GPT-3.5-turbo model.

Resolves #11624
Linear:
[OPEN-2911](https://linear.app/autogpt/issue/OPEN-2911/update-openai-calls-to-use-responsescreate)

## Changes

- **`backend/blocks/llm.py`** — OpenAI provider now uses
`responses.create` exclusively. Removed GPT-3.5-turbo enum + metadata.
- **`backend/util/openai_responses.py`** *(new)* — Helpers for the
Responses API: tool format conversion, content/reasoning/usage/tool-call
extraction.
- **`backend/util/openai_responses_test.py`** *(new)* — Unit tests for
all helper functions.
- **`backend/data/block_cost_config.py`** — Removed GPT-3.5 cost entry.
- **`docs/integrations/block-integrations/llm.md`** — Regenerated block
docs.

## Key API differences handled

| Aspect | Chat Completions | Responses API |
|--------|-----------------|---------------|
| Messages param | `messages` | `input` |
| Max tokens param | `max_completion_tokens` | `max_output_tokens` |
| Usage fields | `prompt_tokens` / `completion_tokens` | `input_tokens`
/ `output_tokens` |
| Tool format | Nested under `function` key | Flat structure |

## Test plan

- [x] Unit tests for all `openai_responses.py` helpers
- [x] Existing LLM block tests updated for Responses API mocks
- [x] Regular OpenAI models work
- [x] Reasoning OpenAI models work
- [x] Non-OpenAI models work

---------

Co-authored-by: Krzysztof Czerwinski <kpczerwinski@gmail.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-19 09:19:31 +00:00
Zamil Majdy
f617f50f0b dx(skills): improve pr-address skill — full thread context + PR description backtick fix (#12480)
## Summary

Improves the `pr-address` skill with two fixes:

- **Full comment thread loading**: Adds `--paginate` to the inline
comments fetch and explicit instructions to reconstruct threads using
`in_reply_to_id`, reading root-to-last-reply before acting. Previously,
only the opening comment was visible — missing reviewer replies led to
wrong fixes.
- **Backtick-safe PR descriptions**: Adds instructions to write the PR
body to a temp file via `<<'PREOF'` heredoc before passing to `gh pr
edit/create`. Inlining the body directly causes backticks to be
shell-escaped, breaking markdown rendering.

## Test plan
- [ ] Run `/pr-address` on a PR with multi-reply inline comment threads
— verify the last reply is what gets acted on
- [ ] Update a PR description containing backticks — verify they render
correctly in GitHub
2026-03-19 15:11:14 +07:00
Otto
943a1df815 dx(backend): Make Builder and Marketplace search work without embeddings (#12479)
When OpenAI credentials are unavailable (fork PRs, dev envs without API
keys), both builder block search and store agent functionality break:

1. **Block search returns wrong results.** `unified_hybrid_search` falls
back to a zero vector when embedding generation fails. With ~200 blocks
in `UnifiedContentEmbedding`, the zero-vector semantic scores are
garbage, and lexical matching on short block names is too weak — "Store
Value" doesn't appear in the top results for query "Store Value".

2. **Store submission approval fails entirely.**
`review_store_submission` calls `ensure_embedding()` inside a
transaction. When it throws, the entire transaction rolls back — no
store submissions get approved, the `StoreAgent` materialized view stays
empty, and all marketplace e2e tests fail.

3. **Store search returns nothing.** Even when store data exists,
`hybrid_search` queries `UnifiedContentEmbedding` which has no store
agent rows (backfill failed). It succeeds with zero results rather than
throwing, so the existing exception-based fallback never triggers.

### Changes 🏗️

- Replace `unified_hybrid_search` with in-memory text search in
`_hybrid_search_blocks` (-> `_text_search_blocks`). All ~200 blocks are
already loaded in memory, and `_score_primary_fields` provides correct
deterministic text relevance scoring against block name, description,
and input schema field descriptions — the same rich text the embedding
pipeline uses. CamelCase block names are split via `split_camelcase()`
to match the tokenization from PR #12400.

- Make embedding generation in `review_store_submission` best-effort:
catch failures and log a warning instead of rolling back the approval
transaction. The backfill scheduler retries later when credentials
become available.

- Fall through to direct DB search when `hybrid_search` returns empty
results (not just when it throws). The fallback uses ad-hoc
`to_tsvector`/`plainto_tsquery` with `ts_rank_cd` ranking on
`StoreAgent` view fields, restoring the search quality of the original
pre-hybrid implementation (stemming, stop-word removal, relevance
ranking).

- Fix Playwright artifact upload in end-to-end test CI

### 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] `build.spec.ts`: 8/8 pass locally (was 0/7 before fix)
  - [x] All 79 e2e tests pass in CI (was 15 failures before fix)

---
Co-authored-by: Reinier van der Leer (@Pwuts)

---------

Co-authored-by: Reinier van der Leer <pwuts@agpt.co>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-19 00:11:06 +00:00
Otto
593001e0c8 fix(frontend): Remove dead Tutorial button from TallyPopup (#12474)
After the legacy builder was removed in #12082, the TallyPopup component
still showed a "Tutorial" button (bottom-right, next to "Give Feedback")
that navigated to `/build?resetTutorial=true`. Nothing handles that
param anymore, so clicking it did nothing.

This removes the dead button and its associated state/handler from
TallyPopup and useTallyPopup. The working tutorial (Shepherd.js
chalkboard icon in CustomControls) is unaffected.

**Changes:**
- `TallyPopup.tsx`: Remove Tutorial button JSX, unused imports
(`usePathname`, `useSearchParams`), and `isNewBuilder` check
- `useTallyPopup.ts`: Remove `showTutorial` state, `handleResetTutorial`
handler, unused `useRouter` import

Resolves SECRT-2109

---
Co-authored-by: Reinier van der Leer (@Pwuts) <pwuts@agpt.co>

Co-authored-by: Reinier van der Leer (@Pwuts) <pwuts@agpt.co>
2026-03-19 00:09:46 +00:00
Ubbe
e1db8234a3 fix(frontend/copilot): constrain markdown heading sizes in user chat messages (#12463)
### Before

<img width="600" height="489" alt="Screenshot 2026-03-18 at 19 24 41"
src="https://github.com/user-attachments/assets/bb8dc0fa-04cd-4f32-8125-2d7930b4acde"
/>

Formatted headings in user messages would look massive

### After

<img width="600" height="549" alt="Screenshot 2026-03-18 at 19 24 33"
src="https://github.com/user-attachments/assets/51230232-c914-42dd-821f-3b067b80bab4"
/>

Markdown headings (`# H1` through `###### H6`) and setext-style headings
(`====`) in user chat messages rendered at their full HTML heading size,
which looked disproportionately large in the chat bubble context.

### Changes 🏗️

- Added Tailwind CSS overrides on the user message `MessageContent`
wrapper to cap all heading elements (h1-h6) at `text-lg font-semibold`
- Only affects user messages in copilot chat (via `group-[.is-user]`
selector); assistant messages are unchanged

### 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:
- [ ] Send a user message containing `# Heading 1` through `######
Heading 6` and verify they all render at constrained size
- [ ] Send a message with `====` separator pattern and verify it doesn't
render as a mega H1
  - [ ] Verify assistant messages with headings still render normally

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-19 00:33:09 +08:00
Zamil Majdy
282173be9d feat(copilot): GitHub CLI support — inject GH_TOKEN and connect_integration tool (#12426)
## Summary

- When a user has connected GitHub, `GH_TOKEN` is automatically injected
into the Claude Agent SDK subprocess environment so `gh` CLI commands
work without any manual auth step
- When GitHub is **not** connected, the copilot can call a new
`connect_integration(provider="github")` MCP tool, which surfaces the
same credential setup card used by regular GitHub blocks — the user
connects inline without leaving the chat
- After connecting, the copilot is instructed to retry the operation
automatically

## Changes

**Backend**
- `sdk/service.py`: `_get_github_token_for_user()` fetches OAuth2 or API
key credentials and injects `GH_TOKEN` + `GITHUB_TOKEN` into `sdk_env`
before the SDK subprocess starts (per-request, thread-safe via
`ClaudeAgentOptions.env`)
- `tools/connect_integration.py`: new `ConnectIntegrationTool` MCP tool
— returns `SetupRequirementsResponse` for a given provider (`github` for
now); extensible via `_PROVIDER_INFO` dict
- `tools/__init__.py`: registers `connect_integration` in
`TOOL_REGISTRY`
- `prompting.py`: adds GitHub CLI / `connect_integration` guidance to
`_SHARED_TOOL_NOTES`

**Frontend**
- `ConnectIntegrationTool/ConnectIntegrationTool.tsx`: thin wrapper
around the existing `SetupRequirementsCard` with a tailored retry
instruction
- `MessagePartRenderer.tsx`: dispatches `tool-connect_integration` to
the new component

## Test plan

- [ ] User with GitHub credentials: `gh pr list` works without any auth
step in copilot
- [ ] User without GitHub credentials: copilot calls
`connect_integration`, card renders with GitHub credential input, after
connecting copilot retries and `gh` works
- [ ] `GH_TOKEN` is NOT leaked across users (injected via
`ClaudeAgentOptions.env`, not `os.environ`)
- [ ] `connect_integration` with unknown provider returns a graceful
error message
2026-03-18 11:52:42 +00:00
Zamil Majdy
5d9a169e04 feat(blocks): add AutoPilotBlock for invoking AutoPilot from graphs (#12439)
## Summary
- Adds `AutogptCopilotBlock` that invokes the platform's copilot system
(`stream_chat_completion_sdk`) directly from graph executions
- Enables sub-agent patterns: copilot can call this block recursively
(with depth limiting via `contextvars`)
- Enables scheduled copilot execution through the agent executor system
- No user credentials needed — uses server-side copilot config

## Inputs/Outputs
**Inputs:** prompt, system_context, session_id (continuation), timeout,
max_recursion_depth
**Outputs:** response text, tool_calls list, conversation_history JSON,
session_id, token_usage

## Test plan
- [x] Block test passes (`test_available_blocks[AutogptCopilotBlock]`)
- [x] Pre-commit hooks pass (format, lint, typecheck)
- [ ] Manual test: add block to graph, send prompt, verify response
- [ ] Manual test: chain two copilot blocks with session_id to verify
continuation
2026-03-18 11:22:25 +00:00
Ubbe
6fd1050457 fix(backend): arch-conditional chromium in Docker for ARM64 compatibility (#12466)
## Summary
- On **amd64**: keep `agent-browser install` (Chrome for Testing —
pinned version tested with Playwright) + restore runtime libs
- On **arm64**: install system `chromium` package (Chrome for Testing
has no ARM64 binary) + skip `agent-browser install`
- An entrypoint script sets
`AGENT_BROWSER_EXECUTABLE_PATH=/usr/bin/chromium` at container startup
on arm64 (detected via presence of `/usr/bin/chromium`); on amd64 the
var is left unset so agent-browser uses Chrome for Testing as before

**Why not system chromium on amd64?** `agent-browser install` downloads
a specific Chrome for Testing version pinned to the Playwright version
in use. Using whatever Debian ships on amd64 could cause protocol
compatibility issues.

Introduced by #12301 (cc @Significant-Gravitas/zamil-majdy)

## Test plan
- [ ] `docker compose up --build` succeeds on ARM64 (Apple Silicon)
- [ ] `docker compose up --build` succeeds on x86_64
- [ ] Copilot browser tools (`browser_navigate`, `browser_act`,
`browser_screenshot`) work in a Copilot session on both architectures

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
2026-03-18 19:08:14 +08:00
Otto
02708bcd00 fix(platform): pre-check invite eligibility before Supabase signup (#12451)
Requested by @Swiftyos

The invite gate check in `get_or_activate_user()` runs after Supabase
creates the auth user, resulting in orphaned auth accounts with no
platform access when a non-invited user signs up. Users could create a
Supabase account but had no `User`, `Profile`, or `Onboarding` records —
they could log in but access nothing.

### Changes 🏗️

**Backend** (`v1.py`, `invited_user.py`):
- Add public `POST /api/auth/check-invite` endpoint (no auth required —
this is a pre-signup check)
- Add `check_invite_eligibility()` helper in the data layer
- Returns `{allowed: true}` when `enable_invite_gate` is disabled
- Extracted `is_internal_email()` helper to deduplicate `@agpt.co`
bypass logic (was duplicated between route and `get_or_activate_user`)
- Checks `InvitedUser` table for `INVITED` status
- Added IP-based Redis rate limiting (10 req/60 s per IP, fails open if
Redis unavailable, returns HTTP 429 when exceeded)
- Fixed Redis pipeline atomicity: `incr` + `expire` now sent in a single
pipeline round-trip, preventing a TTL-less key if `expire` had
previously failed after `incr`
- Fixed incorrect `await` on `pipe.incr()` / `pipe.expire()` — redis-py
async pipeline queue methods are synchronous; only `execute()` is
awaitable. The erroneous `await` was silently swallowed by the `except`
block, making the rate limiter completely non-functional

**Frontend** (`signup/actions.ts`):
- Call the generated `postV1CheckIfAnEmailIsAllowedToSignUp` client
(replacing raw `fetch`) before `supabase.auth.signUp()`
- `ApiError` (non-OK HTTP responses) logs a Sentry warning with the HTTP
status; network/other errors capture a Sentry exception
- If not allowed, return `not_allowed` error (existing
`EmailNotAllowedModal` handles this)
- Graceful fallback: if the pre-check fails (backend unreachable), falls
through to the existing flow — `get_or_activate_user()` remains as
defense-in-depth

**Tests** (`v1_test.py`, `invited_user_test.py`):
- 5 route-level tests covering: gate disabled → allowed, `@agpt.co`
bypass, eligible email, ineligible email, rate-limit exceeded
- Rate-limit test mock updated to use pipeline interface
(`pipeline().execute()` returns `[count, True]`)
- Existing `invited_user_test.py` updated to cover
`check_invite_eligibility` branches

**Not changed:**
- Google OAuth flow — already gated by OAuth provider settings
- `get_or_activate_user()` — stays as backend safety net
- All admin invite CRUD routes — unchanged

### Test plan
1. Email/password signup with invited email → signup proceeds normally
2. Email/password signup with non-invited email → `EmailNotAllowedModal`
shown, no Supabase user created
3. `enable_invite_gate=false` → all emails allowed
4. Backend unreachable during pre-check → falls through to existing flow
5. Same IP exceeds 10 requests/60 s → HTTP 429 returned

---
Co-authored-by: Craig Swift (@Swiftyos) <craigswift13@gmail.com>

---------

Co-authored-by: Craig Swift (@Swiftyos) <craigswift13@gmail.com>
Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
2026-03-18 10:36:50 +00:00
Zamil Majdy
156d61fe5c dx(skills): add merge conflict detection and resolution to pr-address (#12469)
## Summary
- Adds merge conflict detection as step 2 of the polling loop (between
CI check and comment check), including handling of the transient
`"UNKNOWN"` state
- Adds a "Resolving merge conflicts" section with step-by-step
instructions using 3-way merge (no force push needed since PRs are
squash-merged)
- Validates all three git conflict markers before staging to prevent
committing broken code
- Fixes `args` → `argument-hint` in skill frontmatter

## Test plan
- [ ] Verify skill renders correctly in Claude Code
2026-03-18 17:46:32 +07:00
Zamil Majdy
5a29de0e0e fix(platform): try-compact-retry for prompt-too-long errors in CoPilot SDK (#12413)
## Summary

When the Claude SDK returns a prompt-too-long error (e.g. transcript +
query exceeds the model's context window), the streaming loop now
retries with escalating fallbacks instead of failing immediately:

1. **Attempt 1**: Use the transcript as-is (normal path)
2. **Attempt 2**: Compact the transcript via LLM summarization
(`compact_transcript`) and retry
3. **Attempt 3**: Drop the transcript entirely and fall back to
DB-reconstructed context (`_build_query_message`)

If all 3 attempts fail, a `StreamError(code="prompt_too_long")` is
yielded to the frontend.

### Key changes

**`service.py`**
- Add `_is_prompt_too_long(err)` — pattern-matches SDK exceptions for
prompt-length errors (`prompt is too long`, `prompt_too_long`,
`context_length_exceeded`, `request too large`)
- Wrap `async with ClaudeSDKClient` in a 3-attempt retry `for` loop with
compaction/fallback logic
- Move `current_message`, `_build_query_message`, and
`_prepare_file_attachments` before the retry loop (computed once,
reused)
- Skip transcript upload in `finally` when `transcript_caused_error`
(avoids persisting a broken/empty transcript)
- Reset `stream_completed` between retry iterations
- Document outer-scope variable contract in `_run_stream_attempt`
closure (which variables are reassigned between retries vs read-only)

**`transcript.py`**
- Add `compact_transcript(content, log_prefix, model)` — converts JSONL
→ messages → `compress_context` (LLM summarization with truncation
fallback) → JSONL
- Add helpers: `_flatten_assistant_content`,
`_flatten_tool_result_content`, `_transcript_to_messages`,
`_messages_to_transcript`, `_run_compression`
- Returns `None` when compaction fails or transcript is already within
budget (signals caller to fall through to DB fallback)
- Truncation fallback wrapped in 30s timeout to prevent unbounded CPU
time on large transcripts
- Accepts `model` parameter to avoid creating a new `ChatConfig()` on
every call

**`util/prompt.py`**
- Fix `_truncate_middle_tokens` edge case: returns empty string when
`max_tok < 1`, properly handles `max_tok < 3`

**`config.py`**
- E2B sandbox timeout raised from 5 min to 15 min to accommodate
compaction retries

**`prompt_too_long_test.py`** (new, 45 tests)
- `_is_prompt_too_long` positive/negative patterns, case sensitivity,
BaseException handling
- Flatten helpers for assistant/tool_result content blocks
- `_transcript_to_messages` / `_messages_to_transcript` roundtrip,
strippable types, empty content
- `compact_transcript` async tests: too few messages, not compacted,
successful compaction, compression failure

**`retry_scenarios_test.py`** (new, 27 tests)
- Full retry state machine simulation covering all 8 scenarios:
  1. Normal flow (no retry)
  2. Compact succeeds → retry succeeds
  3. Compact fails → DB fallback succeeds
  4. No transcript → DB fallback succeeds
  5. Double fail → DB fallback on attempt 3
  6. All 3 attempts exhausted
  7. Non-prompt-too-long error (no retry)
  8. Compaction returns identical content → DB fallback
- Edge cases: nested exceptions, case insensitivity, unicode content,
large transcripts, resume-after-compaction flow

**Shared test fixtures** (`conftest.py`)
- Extracted `build_test_transcript` helper used across 3 test files to
eliminate duplication

## Test plan

- [x] `_is_prompt_too_long` correctly identifies prompt-length errors (8
positive, 5 negative patterns)
- [x] `compact_transcript` compacts oversized transcripts via LLM
summarization
- [x] `compact_transcript` returns `None` on failure or when already
within budget
- [x] Retry loop state machine: all 8 scenarios verified with state
assertions
- [x] `TranscriptBuilder` works correctly after loading compacted
transcripts
- [x] `_messages_to_transcript` roundtrip preserves content including
unicode
- [x] `transcript_caused_error` prevents stale transcript upload
- [x] Truncation timeout prevents unbounded CPU time
- [x] All 139 unit tests pass locally
- [x] CI green (tests 3.11/3.12/3.13, types, CodeQL, linting)
2026-03-18 10:27:31 +00:00
Otto
e657472162 feat(blocks): Add Nano Banana 2 to image generator, customizer, and editor blocks (#12218)
Requested by @Torantulino

Add `google/nano-banana-2` (Gemini 3.1 Flash Image) support across all
three image blocks.

### Changes

**`ai_image_customizer.py`**
- Add `NANO_BANANA_2 = "google/nano-banana-2"` to `GeminiImageModel`
enum
- Update block description to reference Nano-Banana models generically

**`ai_image_generator_block.py`**
- Add `NANO_BANANA_2` to `ImageGenModel` enum
- Add generation branch (identical to NBP except model name)

**`flux_kontext.py` (AI Image Editor)**
- Rename `FluxKontextModelName` → `ImageEditorModel` (with
backwards-compatible alias)
- Add `NANO_BANANA_PRO` and `NANO_BANANA_2` to the editor
- Model-aware branching in `run_model()`: NB models use `image_input`
list (not `input_image`), no `seed`, and add `output_format`

**`block_cost_config.py`**
- Add NB2 cost entries for all three blocks (14 credits, matching NBP)
- Add NB Pro cost entry for editor block
- Update editor block refs from `.PRO`/`.MAX` to
`.FLUX_KONTEXT_PRO`/`.FLUX_KONTEXT_MAX`

Resolves SECRT-2047

---------

Co-authored-by: Torantulino <Torantulino@users.noreply.github.com>
Co-authored-by: Abhimanyu Yadav <122007096+Abhi1992002@users.noreply.github.com>
2026-03-18 09:42:18 +00:00
DEEVEN SERU
4d00e0f179 fix(blocks): allow falsy entries in AddToListBlock (#12028)
## Summary
- treat AddToListBlock.entry as optional rather than truthy so
0/""/False are appended
- extend block self-tests with a falsy entry case

## Testing
- Not run (pytest not available in environment)

Co-authored-by: DEEVEN SERU <144827577+DEVELOPER-DEEVEN@users.noreply.github.com>
Co-authored-by: Nicholas Tindle <nicholas.tindle@agpt.co>
2026-03-18 09:42:14 +00:00
DEEVEN SERU
1d7282b5f3 fix(backend): Truncate filenames with excessively long 'extensions' (#12025)
Fixes issue where filenames with no dots until the end (or massive
extensions) bypassed truncation logic, causing OSError [Errno 36].
Limits extension preservation to 20 chars.

---------

Co-authored-by: DEVELOPER-DEEVEN <144827577+DEVELOPER-DEEVEN@users.noreply.github.com>
2026-03-18 09:42:06 +00:00
Reinier van der Leer
e3591fcaa3 ci(backend): Python version specific type checking (#12453)
- Resolves #10657
- Partially based on #10913

### Changes 🏗️

- Run Pyright separately for each supported Python version
  - Move type checking and linting into separate jobs
    - Add `--skip-pyright` option to lint script
- Move `linter.py` into `backend/scripts`
  - Move other scripts in `backend/` too for consistency

### 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:
  - CI

---

Co-authored-by: @Joaco2603 <jpappa2603@gmail.com>

---------

Co-authored-by: Joaco2603 <jpappa2603@gmail.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-18 09:41:35 +00:00
Reinier van der Leer
876dc32e17 chore(backend): Update poetry to v2.2.1 (#12459)
Poetry v2.2.1 has bugfixes that are relevant in context of our
`.pre-commit-config.yaml`

### Changes 🏗️

- Update `poetry` from v2.1.1 to v2.2.1 (latest version supported by
Dependabot)
- Re-generate `poetry.lock`

### 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:
  - CI
2026-03-18 09:41:28 +00:00
Reinier van der Leer
616e29f5e4 fix tests for 6d0e206 2026-03-18 10:39:51 +01:00
Zamil Majdy
280a98ad38 dx(skills): poll for new PR comments while waiting for CI (#12461)
## Summary
- Updates the `pr-address` skill to poll for new PR comments while
waiting for CI, instead of blocking solely on `gh pr checks --watch
--fail-fast`
- Runs CI watch in the background and polls all 3 comment endpoints
every 30s
- Allows bot comments (coderabbitai, sentry) to be addressed in parallel
with CI rather than sequentially

## Test plan
- [ ] Run `/pr-address` on a PR with pending CI and verify it detects
new comments while CI is running
- [ ] Verify CI failures are still handled correctly after the combined
wait
2026-03-18 15:07:13 +07:00
Reinier van der Leer
c7f2a7dd03 fix formatting 2026-03-17 20:30:33 +01:00
Otto
6d0e2063ec Merge commit from fork
* fix(backend): add resource limits to Jinja2 template rendering

Prevent DoS via computational exhaustion in FillTextTemplateBlock by:

- Subclassing SandboxedEnvironment to intercept ** and * operators
  with caps on exponent size (1000) and string repeat length (10K)
- Replacing range() global with a capped version (max 10K items)
- Wrapping template.render() in a ThreadPoolExecutor with a 10s
  timeout to kill runaway expressions

Addresses GHSA-ppw9-h7rv-gwq9 (CWE-400).

* address review: move helpers after TextFormatter, drop ThreadPoolExecutor

- Move _safe_range and _RestrictedEnvironment below TextFormatter
  (helpers after the function that uses them)
- Remove ThreadPoolExecutor timeout wrapper from format_string() —
  it has problematic behavior in async contexts and the static
  interception (operator caps, range limit) already covers the
  known attack vectors

* address review: extend sequence guard, harden format_email, add tests

- Extend * guard to cover list and tuple repetition, not just strings
  (blocks {{ [0] * 999999999 }} and {{ (0,) * 999999999 }})
- Rename MAX_STRING_REPEAT → MAX_SEQUENCE_REPEAT
- Use _RestrictedEnvironment in format_email (defense-in-depth)
- Add tests: list repeat, tuple repeat, negative exponent, nested
  exponentiation (18 tests total)

* add async timeout wrapper at block level

Wrap format_string calls in FillTextTemplateBlock and AgentOutputBlock
with asyncio.wait_for(asyncio.to_thread(...), timeout=10s).

This provides defense-in-depth: if an expression somehow bypasses the
static operator checks, the async timeout will cancel it. Uses
asyncio.to_thread for proper async integration (no event loop blocking)
and asyncio.wait_for for real cancellation on timeout.

* make format_string async with timeout kwarg

Move asyncio.wait_for + asyncio.to_thread into format_string() itself
with a timeout kwarg (default 10s). This way all callers get the
timeout automatically — no wrapper needed at each call site.

- format_string() is now async, callers use await
- format_email() is now async (calls format_string internally)
- Updated all callers: text.py, io.py, llm.py, smart_decision_maker.py,
  email.py, notifications.py
- Tests updated to use asyncio.run()

* use Jinja2 native async rendering instead of to_thread

Switch from asyncio.to_thread(template.render) to Jinja2's native
enable_async=True + template.render_async(). No thread overhead,
proper async integration. asyncio.wait_for timeout still applies.

---------

Co-authored-by: Reinier van der Leer <pwuts@agpt.co>
2026-03-17 20:24:04 +01:00
Zamil Majdy
8b577ae194 feat(backend/copilot): add direct ID lookup to find_agent and find_block tools (#12446)
## Summary
- Add direct `creator/slug` lookup to `find_agent` marketplace search,
bypassing full-text search when an exact identifier is provided
- Add direct UUID lookup to `find_block`, returning the block
immediately when a valid block ID is given
- Update tool descriptions and parameter hints to document the new
lookup capabilities

## Test plan
- [ ] Verify `find_agent` with a `creator/slug` query returns the exact
agent
- [ ] Verify `find_agent` falls back to search when slug lookup fails
- [ ] Verify `find_block` with a block UUID returns the exact block
- [ ] Verify `find_block` with a non-existent UUID falls through to
search
- [ ] Verify excluded block types/IDs are still filtered in direct
lookup
2026-03-17 16:41:17 +00:00
Zamil Majdy
d8f5f783ae feat(copilot): enable SmartDecisionMakerBlock in agent generator (#12438)
## Summary
- Enable the agent generator to create orchestrator agents using
**SmartDecisionMakerBlock** with agent mode
- SmartDecisionMaker + AgentExecutorBlock tools = autonomous agent that
decides which sub-agents to call, executes them, reads results, and
loops until done
- Follows existing patterns (AgentExecutorBlock/MCPToolBlock) for fixer,
validator, and guide documentation

## Changes
- Remove SmartDecisionMakerBlock from `COPILOT_EXCLUDED_BLOCK_IDS` in
`find_block.py`
- Add `SMART_DECISION_MAKER_BLOCK_ID` constant to `helpers.py`
- Add `fix_smart_decision_maker_blocks()` in `fixer.py` — populates
agent-mode defaults (`max_iterations=-1`,
`conversation_compaction=True`, etc.)
- Add `validate_smart_decision_maker_blocks()` in `validator.py` —
ensures downstream tool blocks are connected
- Add SmartDecisionMakerBlock documentation section in
`agent_generation_guide.md`
- Add 18 tests: 7 fixer, 7 validator, 4 e2e pipeline

## Test plan
- [x] All 18 new tests pass
(`test/agent_generator/test_smart_decision_maker.py`)
- [x] All 31 existing agent generator tests still pass
- [x] Pre-commit hooks (ruff, black, isort, pyright) all pass
- [ ] Manual: use CoPilot to generate an orchestrator agent with
SmartDecisionMakerBlock

---------

Co-authored-by: Reinier van der Leer <pwuts@agpt.co>
2026-03-17 16:30:04 +00:00
Reinier van der Leer
82d22f3680 dx(backend): Update CLAUDE.md (#12458)
- Prefer f-strings except for debug statements
- Top-down module/function/class ordering

As suggested by @majdyz, this is more effective than commenting on every
single instance on PRs.
2026-03-17 16:27:09 +00:00
Zamil Majdy
50622333d1 fix(backend/copilot): fix tool-result file read failures across turns (#12399)
## Summary
- **Path validation fix**: `is_allowed_local_path()` now correctly
handles the SDK's nested conversation UUID path structure
(`<encoded-cwd>/<conversation-uuid>/tool-results/<file>`) instead of
only matching `<encoded-cwd>/tool-results/<file>`
- **`read_workspace_file` fallback**: When the model mistakenly calls
`read_workspace_file` for an SDK tool-result path (local disk, not cloud
storage), the tool now falls back to reading from local disk instead of
returning "file not found"
- **Cross-turn cleanup fix**: Stopped deleting
`~/.claude/projects/<encoded-cwd>/` between turns — tool-result files
now persist across `--resume` turns so the model can re-read them. Added
TTL-based stale directory sweeping (24h) to prevent unbounded disk
growth.
- **System prompt**: Added guidance telling the model to use `read_file`
(not `read_workspace_file`) for SDK tool-result paths
- **Symlink escape fix** (e2b_file_tools.py): Added `readlink -f`
canonicalization inside the E2B sandbox to detect symlink-based path
escapes before writes
- **Stash timeout increase**: `wait_for_stash` timeout increased from
0.5s to 2.0s, with a post-timeout `sleep(0)` fallback

### Root cause
Investigated via Langfuse trace `5116befdca6a6ff9a8af6153753e267d`
(session `d5841fd8`). The model ran 3 Perplexity deep research calls,
SDK truncated large outputs to `~/.claude/projects/.../tool-results/`
files. Model then called `read_workspace_file` (cloud DB) instead of
`read_file` (local disk), getting "file not found". Additionally, the
path validation check didn't account for the SDK's nested UUID directory
structure, and cleanup between turns deleted tool-result files that the
transcript still referenced.

## Test plan
- [x] All 653 copilot tests pass (excluding 1 pre-existing infra test)
- [x] Security test `test_read_claude_projects_settings_json_denied`
still passes — non-tool-result files under the project dir are still
blocked
- [x] `poetry run format` passes all checks
2026-03-17 15:57:15 +00:00
Zamil Majdy
27af5782a9 feat(skills): add gh pr checks --watch to pr-address loop (#12457)
## Summary
- Teaches the `pr-address` skill to use `gh pr checks --watch
--fail-fast` for efficient CI waiting instead of manual polling
- Adds guidance on investigating failures with `gh run view
--log-failed`
- Adds explicit "between CI waits" section: re-fetch and address new bot
comments while CI runs

## Test plan
- [x] Verified the updated skill renders correctly
- [ ] Use `/pr-address` on a PR with pending CI to confirm the new flow
works
2026-03-17 22:10:18 +07:00
Otto
522f932e67 Merge commit from fork
SendEmailBlock accepted user-supplied smtp_server and smtp_port inputs
and passed them directly to smtplib.SMTP() with no IP validation,
bypassing the platform's SSRF protections in request.py.

This fix:
- Makes _resolve_and_check_blocked public in request.py so non-HTTP
  blocks can reuse the same IP validation
- Validates the SMTP server hostname via resolve_and_check_blocked()
  before connecting
- Restricts allowed SMTP ports to standard values (25, 465, 587, 2525)
- Catches SMTPConnectError and SMTPServerDisconnected to prevent TCP
  banner leakage in error messages

Fixes GHSA-4jwj-6mg5-wrwf
2026-03-17 15:55:49 +01:00
Otto
a6124b06d5 Merge commit from fork
* fix(backend): add HMAC signing to Redis cache to prevent pickle deserialization attacks

Add HMAC-SHA256 integrity verification to all values stored in the shared
Redis cache. This prevents cache poisoning attacks where an attacker with
Redis access injects malicious pickled payloads that execute arbitrary code
on deserialization.

Changes:
- Sign pickled values with HMAC-SHA256 before storing in Redis
- Verify HMAC signature before deserializing cached values
- Reject tampered or unsigned (legacy) cache entries gracefully
  (treated as cache misses, logged as warnings)
- Derive HMAC key from redis_password or unsubscribe_secret_key
- Add tests for HMAC round-trip, tamper detection, and legacy rejection

Fixes GHSA-rfg2-37xq-w4m9

* improve log message

---------

Co-authored-by: Reinier van der Leer <pwuts@agpt.co>
2026-03-17 15:52:37 +01:00
Otto
ae660ea04f Merge commit from fork
Replace NamedTemporaryFile(delete=False) with a direct Response,
preventing unbounded disk consumption on the public download endpoint.

Fixes: GHSA-374w-2pxq-c9jp
2026-03-17 15:33:55 +01:00
Otto
2479f3a1c4 Merge commit from fork
- Normalize IPv4-mapped IPv6 addresses (e.g. ::ffff:127.0.0.1) to IPv4
  before checking against blocked networks, preventing blocklist bypass
- Add missing blocked ranges: CGNAT (100.64.0.0/10), IETF Protocol
  Assignments (192.0.0.0/24), Benchmarking (198.18.0.0/15)
- Add comprehensive tests for IPv4-mapped bypass and new blocked ranges
2026-03-17 14:43:38 +01:00
Abhimanyu Yadav
8153306384 feat(frontend): reusable confetti with enhanced particles and dual bursts (#12454)
<!-- Clearly explain the need for these changes: -->

The previous confetti implementation using party-js was causing lag.
Replaced it with canvas-confetti for smoother, more performant
celebrations with enhanced visual effects.

### Changes 🏗️

- **New Confetti Component**: Reusable canvas-confetti wrapper with
AutoGPT purple color palette and Storybook stories demonstrating various
effects
- **Enhanced Wallet Confetti**: Dual simultaneous bursts at 45° and 135°
angles with larger particles (scalar 1.2) for better visibility
- **Enhanced Task Celebration**: Dual-burst confetti for task group and
individual task completion events
- **Onboarding Congrats Page**: Replaced party-js with canvas-confetti
for side-cannon animation effect
- **Dependency**: Added canvas-confetti v1.9.4, removed party-js

### 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] Trigger task completion in wallet to see dual-burst confetti at
45° and 135° angles
- [x] Complete tasks/groups to verify celebration confetti displays with
larger particles
  - [x] Visit onboarding congratulations page to see side-cannon effect
  - [x] Verify confetti rendering performance and no console errors
2026-03-17 12:49:15 +00:00
Abhimanyu Yadav
9c3d100a22 feat(frontend): add builder e2e tests for new Flow Editor (#12436)
### Changes
- Replace skipped legacy builder tests with 8 working Playwright e2e
tests
  targeting the new Flow Editor
- Rewrite `BuildPage` page object to match new `data-id`/`data-testid`
  selectors
- Update `agent-activity.spec.ts` to use new `BuildPage` API

### Tests added
  - Build page loads successfully (canvas + control buttons)
  - Add a block via block menu search
  - Add multiple blocks
  - Remove a block (select + Backspace)
  - Save an agent (name/description, verify flowID in URL)
  - Save and verify run button becomes enabled
  - Copy and paste a node (Cmd+C/V)
  - Run an agent from the builder

 ### Test plan
  - [x] All 8 builder tests pass locally (`pnpm test:no-build
  src/tests/build.spec.ts`)
  - [x] `pnpm format`, `pnpm lint`, `pnpm types` all clean
  - [x] CI passes
2026-03-17 12:48:59 +00:00
Zamil Majdy
fc3bf6c154 fix(copilot): handle transient Anthropic API connection errors gracefully (#12445)
## Summary
- Detect transient Anthropic API errors (ECONNRESET, "socket connection
was closed unexpectedly") across all error paths in the copilot SDK
streaming loop
- Replace raw technical error messages with user-friendly text:
**"Anthropic connection interrupted — please retry"**
- Add `retryable` field to `StreamError` model so the frontend can
distinguish retryable errors
- Add **"Try Again" button** on the error card for transient errors,
which re-sends the last user message

### Background
Sentry issue
[AUTOGPT-SERVER-875](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-875)
— 25+ events since March 13, caused by Anthropic API infrastructure
instability (confirmed by their status page). Same SDK/code on dev and
prod, prod-only because of higher volume of long-running streaming
sessions.

### Changes
**Backend (`constants.py`, `service.py`, `response_adapter.py`,
`response_model.py`):**
- `is_transient_api_error()` — pattern-matching helper for known
transient error strings
- Intercept transient errors in 3 places: `AssistantMessage.error`,
stream exceptions, `BaseException` handler
- Use friendly message in error markers persisted to session (so it
shows properly on page refresh too)
- `StreamError.retryable` field for frontend consumption

**Frontend (`ChatContainer`, `ChatMessagesContainer`,
`MessagePartRenderer`):**
- Thread `onRetry` callback from `ChatContainer` →
`ChatMessagesContainer` → `MessagePartRenderer`
- Detect transient error text in error markers and show "Try Again"
button via existing `ErrorCard.onRetry`
- Clicking "Try Again" re-sends the last user message (backend
auto-cleans stale error markers)

Fixes SECRT-2128, SECRT-2129, SECRT-2130

## Test plan
- [ ] Verify transient error detection with `is_transient_api_error()`
for known patterns
- [ ] Confirm error card shows "Anthropic connection interrupted —
please retry" instead of raw socket error
- [ ] Confirm "Try Again" button appears on transient error cards
- [ ] Confirm "Try Again" re-sends the last user message successfully
- [ ] Confirm non-transient errors (e.g., "Prompt is too long") still
show original error text without retry button
- [ ] Verify error marker persists correctly on page refresh
2026-03-17 12:48:53 +00:00
Abhimanyu Yadav
e32d258a7e feat(blocks): add AgentMail integration blocks (#12417)
## Summary
- Add a full AgentMail integration with blocks for managing inboxes,
messages, threads, drafts, attachments, lists, and pods
- Includes shared provider configuration (`_config.py`) with API key
authentication
- 8 block modules covering ~25 individual blocks across all AgentMail
API surfaces

  ## Block Modules
  | Module | Blocks |
  |--------|--------|
  | `inbox.py` | Create, Get, List, Update, Delete inboxes |
| `messages.py` | Send, Get, List, Delete messages + org-wide listing |
  | `threads.py` | Get, List, Delete threads + org-wide listing |
| `drafts.py` | Create, Get, List, Update, Send, Delete drafts +
org-wide listing |
  | `attachments.py` | Download attachments |
  | `lists.py` | Create, Get, List, Update, Delete mailing lists |
  | `pods.py` | Create, Get, List, Update, Delete pods |

  ## Test plan
- [x] `poetry run pytest 'backend/blocks/test/test_block.py' -xvs` — all
new blocks pass the standard block test suite
  - [x] test all blocks manually
2026-03-17 12:40:32 +00:00
Abhimanyu Yadav
3e86544bfe feat(frontend): add graph search functionality to new builder (#12395)
### Changes
- Integrates the existing graph search components into the new builder's
control panel
- Search by block name/title, block type, node inputs/outputs, and
description with fuzzy matching
  (Jaro-Winkler)
- Clicking a result zooms/navigates to the node on the canvas
- Keyboard shortcut Cmd/Ctrl+F to open search
- Arrow key navigation and Enter to select within results
- Styled to match the new builder's block menu card pattern


https://github.com/user-attachments/assets/41ed676d-83b1-4f00-8611-00d20987a7af


### Test plan

- [x] Open builder with a graph containing multiple nodes
- [x] Click magnifying glass icon in control panel — search panel opens
- [x] Type a query — results filter by name, type, inputs, outputs
- [x] Click a result — canvas zooms to that node
- [x] Use arrow keys + Enter to navigate and select results
- [x] Press Cmd/Ctrl+F — search panel opens
- [x] Press Escape or click outside — search panel closes and query
clears
2026-03-17 12:19:54 +00:00
Abhimanyu Yadav
c6b729bdfa fix(frontend): replace custom LibraryTabs with design system TabsLine (#12444)
Replaces the custom LibraryTabs component with the design system's
TabsLine component throughout the library page for better UI
consistency. Also wires up favorite animation refs and removes the
unused `agentGraphVersion` field from the test fixture.

### Changes 🏗️

- Replace `LibraryTabs` with `TabsLine` from design system in
`FavoritesSection`, `LibrarySubSection`, and `page.tsx`
- Add favorite animation ref registration in `FavoritesSection` and
`LibrarySubSection`
- Inline tab type definition as `{ id: string; title: string; icon: Icon
}` in component props
- Remove unused `agentGraphVersion` field from `load_store_agents.py`
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] Library page renders with both "All" and "Favorites" tabs using
TabsLine component
  - [x] Tab switching between all agents and favorites works correctly
  - [x] Favorite animations reference the correct tab element
2026-03-17 10:39:12 +00:00
Zamil Majdy
7a391fbd99 feat(platform): CoPilot credit charging, token rate limiting, and usage UI (#12385)
### Background
CoPilot block execution was not charging credits, LLM token usage was
not tracked, and there was no per-user rate limiting. This PR adds all
three, plus a frontend usage indicator.

### Screenshot

<!-- Drag-drop the usage limits screenshot here -->

### Changes

**Credit Charging** (`copilot/tools/helpers.py`)
- Pre-execution balance check + post-execution credit deduction via
`block_usage_cost` / `spend_credits`
- Uses adapter pattern (RPC fallback) so it works in the CoPilot
executor which has no Prisma connection

**Token Rate Limiting** (`copilot/rate_limit.py`)
- Redis-backed daily + weekly fixed-window counters per user
- Fail-open on Redis outages, clock-skew-safe weekly boundaries
- Configurable via `daily_token_limit` / `weekly_token_limit` (0 =
unlimited)

**Token Tracking**
- *Baseline* (`copilot/baseline/service.py`):
`stream_options={"include_usage": True}` with tiktoken fallback
estimation
- *SDK* (`copilot/sdk/service.py`): Extract usage from Claude Agent SDK
`ResultMessage`, including cached tokens
- Both: yield `StreamUsage` SSE events, persist `Usage` records, call
`record_token_usage` in `finally`

**Usage API** (`api/features/chat/routes.py`)
- `GET /api/chat/usage` — returns `CoPilotUsageStatus` (daily/weekly
used, limit, resets_at)
- Pre-turn `check_rate_limit` in `stream_chat_post` (returns 429 on
exceed)

**Frontend** (`copilot/components/UsageLimits/`)
- `UsageLimits` popover with daily/weekly progress bars, reset times,
dark mode
- `useUsageLimits` hook with 30s auto-refresh via generated Orval API
hook

### Tests
| Area | Tests | File |
|------|-------|------|
| Rate limiting | 22 | `rate_limit_test.py` |
| Credit charging | 12 | `helpers_test.py` |
| Usage API | 3 | `routes_test.py` |
| Frontend UI | 9 | `UsageLimits.test.tsx` |

### Checklist

- [x] Changes clearly listed
- [x] Test plan created and executed (46 backend + 9 frontend tests)
- [x] Pre-commit hooks pass (formatting, linting, type checks)
- [x] `.env.default` compatible (new config defaults to 0 = unlimited)
- [x] `docker-compose.yml` compatible (no changes needed)
2026-03-17 08:43:27 +00:00
Zamil Majdy
791dd7cb48 fix(backend): split CamelCase block names and filter disabled blocks before batch slicing (#12400)
## Summary

Two bugs causing blocks to be invisible in CoPilot search:

### Bug 1: CamelCase block names not tokenized
Block names like `AITextGeneratorBlock` were indexed as single tokens in
the search database. PostgreSQL's `plainto_tsquery('english', ...)` and
the BM25 tokenizer both treat CamelCase as one word, so searching for
"text generator" produced zero lexical/BM25 match.

**Fix:** Split CamelCase names into separate words before indexing (e.g.
`"AI Text Generator Block"`) and in the BM25 tokenizer.

### Bug 2: Disabled blocks exhausting batch budget (root cause of 36
missing blocks)
The `batch_size` limit in `get_missing_items()` was applied **before**
filtering out disabled blocks. With 120+ disabled blocks and
`batch_size=100`, the first 100 missing entries were all disabled
(skipped via `continue`), leaving the 36 enabled blocks beyond the slice
boundary **never indexed**. This made core blocks like
`AITextGeneratorBlock`, `AIConversationBlock`, `AIListGeneratorBlock`,
etc. completely invisible to search.

**Fix:** Filter disabled blocks from the missing list before slicing by
`batch_size`.

### Changes
- **`content_handlers.py`**: 
- Split CamelCase block names into space-separated words when building
`searchableText`
- Filter disabled blocks before applying `batch_size` slice so enabled
blocks aren't starved
- **`hybrid_search.py`**: Updated BM25 `tokenize()` to split CamelCase
tokens

### Evidence from local DB
```
Indexed blocks: 341
Total blocks: 497 (156 missing from index)
Missing (non-disabled): 36 — including AITextGeneratorBlock, AIConversationBlock, etc.

# batch_size analysis:
First 100 missing: 0 enabled, 100 disabled  ← batch exhausted by disabled blocks
After 100: 36 enabled                        ← never reached!
```

## Test plan
- [ ] Verify CamelCase splitting: `AITextGeneratorBlock` → `AI Text
Generator Block`
- [ ] Run `poetry run pytest backend/api/features/store/` for
regressions
- [ ] After deploy, trigger embedding backfill and verify all 36 blocks
get indexed
- [ ] Search for "text generator" in CoPilot and verify
`AITextGeneratorBlock` appears
2026-03-17 08:36:53 +00:00
Abhimanyu Yadav
f0800b9420 feat(frontend): add rich media previews for Builder node outputs and file inputs (#12432)
### Changes
- Add YouTube/Vimeo embed support to `VideoRenderer` — URLs render as
embedded
  iframe players instead of plain text
- Add new `AudioRenderer` — HTTP audio URLs (.mp3, .wav, .ogg, .m4a,
.aac,
  .flac) and data URIs render as inline audio players
- Add new `LinkRenderer` — any HTTP/HTTPS URL not claimed by a media
renderer
  becomes a clickable link with an external-link icon
- Add media preview button to `FileInput` — uploaded audio, video, and
image
files show an Eye icon that opens a preview dialog reusing the
OutputRenderer
  system
- Update `ContentRenderer` shortContent gate to allow new renderers
through in
  node previews


https://github.com/user-attachments/assets/eea27fb7-3870-4a1e-8d08-ba23b6e07d74

### Test plan
- [x] `pnpm vitest run src/components/contextual/OutputRenderers/` — 36
tests
  passing
- [x] `pnpm format && pnpm lint && pnpm types` — all clean
- [x] Manual: run a block that outputs a YouTube URL → embedded player
- [x] Manual: run a block that outputs an audio file URL → audio player
- [x] Manual: run a block that outputs a generic URL → clickable link
- [x] Manual: upload an audio/video/image file to a file input → Eye
icon
  appears, clicking opens preview dialog
2026-03-17 07:09:02 +00:00
Abhimanyu Yadav
60bc49ba50 fix(platform): fix image delete button on EditAgentForm (#12362)
### Summary
- SECRT-2094: Fix store image delete button accidentally submitting the
edit form — the remove image <button> in ThumbnailImages.tsx was missing
type="button", causing it to act as a form submit inside the
EditAgentForm. This closed the modal and showed a success toast without
the user clicking "Update submission".

https://github.com/user-attachments/assets/86cbdd7d-90b1-473c-9709-e75e956dea6b

###  Changes
- `frontend/.../ThumbnailImages.tsx` — added type="button" to image
remove button
2026-03-17 07:06:05 +00:00
Abhimanyu Yadav
ba4f4b6242 test(frontend): add integration tests for builder UI state stores and draft recovery (part-2) (#12435)
### Changes
- Add integration tests for `controlPanelStore` (sidebar panel state
  management)
- Add integration tests for `blockMenuStore` (search/filter/category
state,
  creator list deduplication, reset behavior)
- Add integration tests for `tutorialStore` (tutorial lifecycle, step
  progression, input values)
- Add integration tests for `DraftRecoveryPopup` (diff summary
rendering,
  restore/discard actions, null diff fallback, singular/plural text)

### Test plan
  - [x] All 54 tests pass across 4 new test files
  - [x] `pnpm format` clean
  - [x] `pnpm lint` clean
  - [x] `pnpm types` clean
2026-03-17 07:05:51 +00:00
Nicholas Tindle
8892bcd230 docs: Add workspace and media file architecture documentation (#11989)
### Changes 🏗️

- Added comprehensive architecture documentation at
`docs/platform/workspace-media-architecture.md` covering:
  - Database models (`UserWorkspace`, `UserWorkspaceFile`)
  - `WorkspaceManager` API with session scoping
- `store_media_file()` media normalization pipeline (input types, return
formats)
  - Virus scanning responsibility boundaries
- Decision tree for choosing `WorkspaceManager` vs `store_media_file()`
- Configuration reference including `clamav_max_concurrency` and
`clamav_mark_failed_scans_as_clean`
  - Common patterns with error handling examples
- Updated `autogpt_platform/backend/CLAUDE.md` with a "Workspace & Media
Files" section referencing the new docs
- Removed duplicate `scan_content_safe()` call from
`WriteWorkspaceFileTool` — `WorkspaceManager.write_file()` already scans
internally, so the tool was double-scanning every file
- Replaced removed comment in `workspace.py` with explicit ownership
comment clarifying that `WorkspaceManager` is the single scanning
boundary

### 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 `scan_content_safe()` is called inside
`WorkspaceManager.write_file()` (workspace.py:186)
- [x] Verified `store_media_file()` scans all input branches including
local paths (file.py:351)
- [x] Verified documentation accuracy against current source code after
merge with dev
  - [x] CI checks all passing

<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> **Low Risk**
> Mostly adds documentation and internal developer guidance; the only
code change is a comment clarifying `WorkspaceManager.write_file()` as
the single virus-scanning boundary, with no behavior change.
> 
> **Overview**
> Adds a new `docs/platform/workspace-media-architecture.md` describing
the Workspace storage layer vs the `store_media_file()` media pipeline,
including session scoping and virus-scanning/persistence responsibility
boundaries.
> 
> Updates backend `CLAUDE.md` to point contributors to the new doc when
working on CoPilot uploads/downloads or
`WorkspaceManager`/`store_media_file()`, and clarifies in
`WorkspaceManager.write_file()` (comment-only) that callers should not
duplicate virus scanning.
> 
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
18fcfa03f8. 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 <noreply@anthropic.com>
2026-03-17 06:12:26 +00:00
Zamil Majdy
48ff8300a4 Merge branch 'master' of github.com:Significant-Gravitas/AutoGPT into dev 2026-03-17 13:13:42 +07:00
Abhimanyu Yadav
c268fc6464 test(frontend/builder): add integration tests for builder stores, components, and hooks (part-1) (#12433)
### Changes
- Add 329 integration tests across 11 test files for the builder (visual
  workflow editor)
- Cover all Zustand stores (nodeStore, edgeStore, historyStore,
graphStore,
  copyPasteStore, blockMenuStore, controlPanelStore)
- Cover key components (CustomNode, NewBlockMenu, NewSaveControl,
RunGraph)
- Cover hooks (useFlow, useCopyPaste)

### Test files

  | File | Tests | Coverage |
  |------|-------|----------|
| `nodeStore.test.ts` | 58 | Node lifecycle, bulk ops, backend
conversion,
  execution tracking, status, errors, resolution mode |
  | `edgeStore.test.ts` | 37 | Edge CRUD, duplicate rejection, bead
  visualization, backend link conversion, upsert |
| `historyStore.test.ts` | 22 | Undo/redo, history limits (50),
microtask
  batching, deduplication, canUndo/canRedo |
| `graphStore.test.ts` | 28 | Execution status transitions,
isGraphRunning,
  schema management, sub-graphs |
| `copyPasteStore.test.ts` | 8 | Copy/paste with ID remapping, position
offset,
   edge preservation |
| `CustomNode.test.tsx` | 25 | Rendering by block type (NOTE, WEBHOOK,
AGENT,
  OUTPUT, AYRSHARE), error states |
| `NewBlockMenu.test.tsx` | 29 | Store state (search, filters, creators,
  categories), search/default view routing |
| `NewSaveControl.test.tsx` | 11 | Save dialog rendering, form
validation,
  version display, popover state |
| `RunGraph.test.tsx` | 11 | Run/stop button states, loading, click
handlers,
  RunInputDialog visibility |
  | `useFlow.test.ts` | 4 | Loading states, initial load completion |
| `useCopyPaste.test.ts` | 16 | Clipboard copy/paste, UUID remapping,
viewport
  centering, input field guard |
2026-03-17 05:24:55 +00:00
Reinier van der Leer
aff3fb44af ci(platform): Improve end-to-end CI & reduce its cost (#12437)
Our CI costs are skyrocketing, most of it because of
`platform-fullstack-ci.yml`. The `types` job currently uses in a
`big-boi` runner (= expensive), but doesn't need to.
Additionally, the "end-to-end tests" job is currently in
`platform-frontend-ci.yml` instead of `platform-fullstack-ci.yml`,
causing it not to run on backend changes (which it should).

### Changes 🏗️

- Simplify `check-api-types` job (renamed from `types`) and make it use
regular `ubuntu-latest` runner
- Export API schema from backend through CLI (instead of spinning it up
in docker)
- Fix dependency caching in `platform-fullstack-ci.yml` (based on recent
improvements in `platform-frontend-ci.yml`)
- Move `e2e_tests` job to `platform-fullstack-ci.yml`

Out-of-scope but necessary:
- Eliminate module-level init of OpenAI client in
`backend.copilot.service`

### 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:
  - CI
2026-03-16 23:08:18 +00:00
Zamil Majdy
9a41312769 feat(backend/copilot): parse @@agptfile bare refs by file extension (#12392)
The `@@agptfile:` expansion system previously used content-sniffing
(trying
`json.loads` then `csv.Sniffer`) to decide whether to parse file content
as
structured data. This was fragile — a file containing just `"42"` would
be
parsed as an integer, and the heuristics could misfire on ambiguous
content.

This PR replaces content-sniffing with **extension/MIME-based format
detection**.
When the file has a well-known extension (`.json`, `.csv`, etc.) or MIME
type
fragment (`workspace://id#application/json`), the content is parsed
accordingly.
Unknown formats or parse failures always fall back to plain string — no
surprises.

> [!NOTE]
> This PR builds on the `@@agptfile:` file reference protocol introduced
in #12332 and the structured data auto-parsing added in #12390.
>
> **What is `@@agptfile:`?**
> It is a special URI prefix (e.g. `@@agptfile:workspace:///report.csv`)
that the CoPilot SDK expands inline before sending tool arguments to
blocks. This lets the AI reference workspace files by name, and the SDK
automatically reads and injects the file content. See #12332 for the
full design.

### Changes 🏗️

**New utility: `backend/util/file_content_parser.py`**
- `infer_format(uri)` — determines format from file extension or MIME
fragment
- `parse_file_content(content, fmt)` — parses content, never raises
- Supported text formats: JSON, JSONL/NDJSON, CSV, TSV, YAML, TOML
- Supported binary formats: Parquet (via pyarrow), Excel/XLSX (via
openpyxl)
- JSON scalars (strings, numbers, booleans, null) stay as strings — only
  containers (arrays, objects) are promoted
- CSV/TSV require ≥1 row and ≥2 columns to qualify as tabular data
- Added `openpyxl` dependency for Excel reading via pandas
- Case-insensitive MIME fragment matching per RFC 2045
- Shared `PARSE_EXCEPTIONS` constant to avoid duplication between
modules

**Updated `expand_file_refs_in_args` in `file_ref.py`**
- Bare refs now use `infer_format` + `parse_file_content` instead of the
  old `_try_parse_structured` content-sniffing function
- Binary formats (parquet, xlsx) read raw bytes via `read_file_bytes`
- Embedded refs (text around `@@agptfile:`) still produce plain strings
- **Size guards**: Workspace and sandbox file reads now enforce a 10 MB
limit
  (matching the existing local file limit) to prevent OOM on large files

**Updated `blocks/github/commits.py`**
- Consolidated `_create_blob` and `_create_binary_blob` into a single
function
  with an `encoding` parameter

**Updated copilot system prompt**
- Documents the extension-based structured data parsing and supported
formats

**66 new tests** in `file_content_parser_test.py` covering:
- Format inference (extension, MIME, case-insensitive, precedence)
- All 8 format parsers (happy path + edge cases + fallbacks)
- Binary format handling (string input fallback, invalid bytes fallback)
- Unknown format passthrough

### 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 66 file_content_parser_test.py tests pass
  - [x] All 31 file_ref_test.py tests pass
  - [x] All 13 file_ref_integration_test.py tests pass
  - [x] `poetry run format` passes clean (including pyright)
2026-03-16 22:31:21 +00:00
Ubbe
048fb06b0a feat(frontend): add "Jump Back In" button to Library page (#12387)
Adds a "Jump Back In" CTA at the top of the Library page to encourage
users to quickly rerun their most recently successful agent.

Closes SECRT-1536

### Changes 🏗️

- New `JumpBackIn` component with `useJumpBackIn` hook at
`library/components/JumpBackIn/`
- Fetches first page of library agents sorted by `updatedAt`
- Finds the first agent with a `COMPLETED` execution in
`recent_executions`
- Shows banner with agent name + "Jump Back In" button linking to
`/library/agents/{id}`
- Returns `null` (hidden) when loading or when no agent with a
successful run exists

### 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`, `pnpm lint`, `pnpm types` all pass
- [x] Verified banner is hidden when no successful runs exist (edge
case)
- [x] Verified library page renders correctly with no visual regressions

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

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-16 21:35:03 +08:00
Zamil Majdy
3f653e6614 dx(.claude): refactor and consolidate Claude Code skills (#12424)
Refactors the Claude Code skills for a cleaner, more intuitive dev loop.

### Changes 🏗️

- **`/pr-review` (new)**: Actual code review skill — reads the PR diff,
fetches existing comments to avoid duplicates, and posts inline GitHub
comments with structured feedback (Blockers / Should Fix / Nice to Have
/ Nit) covering correctness, security, code quality, architecture, and
testing.

- **`/pr-address` (was `/babysit-pr`)**: Addresses review comments and
monitors CI until green. Renamed from `/babysit-pr` to `/pr-address` to
better reflect its purpose. Handles bot-specific feedback
(autogpt-reviewer, sentry, coderabbitai) and loops until all comments
are addressed and CI is green.

- **`/backend-check` + `/frontend-check` → `/check`**: Unified into a
single `/check` skill that auto-detects whether backend (Python) or
frontend (TypeScript) code changed and runs the appropriate formatting,
linting, type checking, and tests. Shared code quality rules applied to
both.

- **`/code-style` enhanced**: Now covers both Python and
TypeScript/React. Added learnings from real PR work: lazy `%s` logging,
TOCTOU awareness, SSE protocol rules (`data:` vs `: comment`), FastAPI
`Security()` vs `Depends()`, Redis pipeline atomicity, error path
sanitization, mock target rules after refactoring.

- **`/worktree` fixed**: Normal `git worktree` is now the default (was
branchlet-first). Branchlet moved to optional section. All paths derived
from `git rev-parse --show-toplevel`.

- **`/pr-create`, `/openapi-regen`, `/new-block` cleaned up**: Reference
`/check` and `/code-style` instead of duplicating instructions.

### 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 all skill files parse correctly (valid YAML frontmatter)
  - [x] Verified skill auto-detection triggers updated in descriptions
- [x] Verified old backend-check and frontend-check directories removed
- [x] Verified pr-review and pr-address directories created with correct
content
2026-03-16 10:35:05 +00:00
Zamil Majdy
c9c3d54b2b fix(platform): reduce Sentry noise by filtering expected errors and downgrading log levels (#12430)
## Summary

Reduces Sentry error noise by ~90% by filtering out expected/transient
errors and downgrading inappropriate error-level logs to warnings. Most
of the top Sentry issues are not actual bugs but expected conditions
(user errors, transient infra, business logic) that were incorrectly
logged at ERROR level, causing them to be captured as Sentry events.

## Changes

### 1. Sentry `before_send` filter (`metrics.py`)
Added a `before_send` hook to filter known expected errors before they
reach Sentry:
- **AMQP/RabbitMQ connection errors** — transient during
deploys/restarts
- **User credential errors** — invalid API keys, missing auth headers
(user error, not platform bug)
- **Insufficient balance** — expected business logic
- **Blocked IP access** — security check working as intended
- **Discord bot token errors** — misconfiguration, not runtime error
- **Google metadata DNS errors** — expected in non-GCP environments
- **Inactive email recipients** — expected for bounced addresses
- **Unclosed client sessions/connectors** — resource cleanup noise

### 2. Connection retry log levels (`retry.py`)
- `conn_retry` final failure: `error` → `warning` (these are infra
retries, not bugs)
- `conn_retry` wrapper final failure: `error` → `warning`
- Discord alert send failure: `error` → `warning`

### 3. Block execution Sentry capture (`manager.py`)
- Skip `sentry_sdk.capture_exception()` for `ValueError` subclasses
(BlockExecutionError, BlockInputError, InsufficientBalanceError, etc.) —
these are user-caused errors, not platform bugs
- Downgrade executor shutdown/disconnect errors to warning

### 4. Scheduler log levels (`scheduler.py`)
- Graph validation failure: `error` → `warning` (expected for
old/invalid graphs)
- Unable to unschedule graph: `error` → `warning`
- Job listener failure: `error` → `warning`
- Async operation failure: `error` → `warning`

### 5. Discord system alert (`notifications.py`)
- Wrapped `discord_system_alert` endpoint with try/catch to prevent
unhandled exceptions (fixes AUTOGPT-SERVER-743, AUTOGPT-SERVER-7MW)

### 6. Notification system log levels (`notifications.py`)
- All batch processing errors: `error` → `warning`
- User email not found: `error` → `warning`
- Notification parsing errors: `error` → `warning`
- Email sending failures: `error` → `warning`
- Summary data gathering failure: `error` → `warning`
- Cleaned up unprofessional error messages

### 7. Cloud storage cleanup (`cloud_storage.py`)
- Cleanup error: `error` → `warning`

## Sentry Issues Addressed

### AMQP/RabbitMQ (~3.4M events total)
-
[AUTOGPT-SERVER-3H2](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-3H2)
— AMQPConnector ConnectionRefusedError (1.2M events)
-
[AUTOGPT-SERVER-3H3](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-3H3)
— AMQPConnectionWorkflowFailed (770K events)
-
[AUTOGPT-SERVER-3H4](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-3H4)
— AMQP connection workflow failed (770K events)
-
[AUTOGPT-SERVER-3H5](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-3H5)
— AMQPConnectionWorkflow reporting failure (770K events)
-
[AUTOGPT-SERVER-3H7](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-3H7)
— Socket failed to connect (514K events)
-
[AUTOGPT-SERVER-3H8](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-3H8)
— TCP Connection attempt failed (514K events)
-
[AUTOGPT-SERVER-3H6](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-3H6)
— AMQPConnectionError (93K events)
-
[AUTOGPT-SERVER-7SX](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-7SX)
— Error creating transport (69K events)
-
[AUTOGPT-SERVER-1TN](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-1TN)
— ChannelInvalidStateError (39K events)
-
[AUTOGPT-SERVER-6JC](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-6JC)
— ConnectionClosedByBroker (2K events)
-
[AUTOGPT-SERVER-6RJ/6RK/6RN/6RQ/6RP/6RR](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-6RJ)
— Various connection failures (~15K events)
-
[AUTOGPT-SERVER-4A5/6RM/7XN](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-4A5)
— Connection close/transport errors (~540 events)

### User Credential Errors (~15K events)
-
[AUTOGPT-SERVER-6S5](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-6S5)
— Incorrect OpenAI API key (9.2K events)
-
[AUTOGPT-SERVER-7W4](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-7W4)
— Incorrect API key in AIConditionBlock (3.4K events)
-
[AUTOGPT-SERVER-83Y](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-83Y)
— AI condition invalid key (2.3K events)
-
[AUTOGPT-SERVER-7ZP](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-7ZP)
— Perplexity missing auth header (451 events)
-
[AUTOGPT-SERVER-7XK/7XM](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-7XK)
— Anthropic invalid key (125 events)
-
[AUTOGPT-SERVER-82C](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-82C)
— Missing auth header (27 events)
-
[AUTOGPT-SERVER-721](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-721)
— Ideogram invalid token (165 events)

### Business Logic / Validation (~120K events)
-
[AUTOGPT-SERVER-7YQ](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-7YQ)
— Disabled block used in graph (56K events)
-
[AUTOGPT-SERVER-6W3](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-6W3)
— Graph failed validation (46K events)
-
[AUTOGPT-SERVER-6W2](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-6W2)
— Unable to unschedule graph (46K events)
-
[AUTOGPT-SERVER-83X](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-83X)
— Blocked IP access (15K events)
-
[AUTOGPT-SERVER-6K9](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-6K9)
— Insufficient balance (4K events)

### Discord Alert Failures (~24K events)
-
[AUTOGPT-SERVER-743](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-743)
— Discord improper token (22K events)
-
[AUTOGPT-SERVER-7MW](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-7MW)
— Discord 403 Missing Access (1.5K events)

### Notification System (~16K events)
-
[AUTOGPT-SERVER-550](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-550)
— Notification batch create error (8.3K events)
-
[AUTOGPT-SERVER-58H](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-58H)
— ValidationError for NotificationEventModel (3K events)
-
[AUTOGPT-SERVER-5C6](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-5C6)
— Get notification batch error (2.1K events)
-
[AUTOGPT-SERVER-4BT](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-4BT)
— Notification batch create error (1.8K events)
-
[AUTOGPT-SERVER-5E4](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-5E4)
— NotificationPreference validation (1.4K events)
-
[AUTOGPT-SERVER-508](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-508)
— Inactive email recipients (702 events)

### Infrastructure / Transient (~20K events)
-
[AUTOGPT-SERVER-6WJ](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-6WJ)
— Unclosed client session (13K events)
-
[AUTOGPT-SERVER-745](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-745)
— Unclosed connector (5.8K events)
-
[AUTOGPT-SERVER-4V1](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-4V1)
— Google metadata DNS error (2.2K events)
-
[AUTOGPT-SERVER-80J](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-80J)
— CloudStorage DNS error (35 events)

### Executor Shutdown
-
[AUTOGPT-SERVER-55J](https://significant-gravitas.sentry.io/issues/AUTOGPT-SERVER-55J)
— Error disconnecting run client (118 events)

## Test plan
- [x] All pre-commit hooks pass (Ruff, isort, Black, Pyright typecheck)
- [x] All changed modules import successfully
- [ ] Deploy to staging and verify Sentry event volume drops
significantly
- [ ] Verify legitimate errors still appear in Sentry
2026-03-16 10:29:01 +00:00
Ubbe
53d58e21d3 feat(frontend): replace technical block terminology with user-friendly labels (#12389)
## Summary
- Replaces all user-facing "block" terminology in the CoPilot activity
stream with plain-English labels ("Step failed", "action",
"Credentials", etc.)
- Adds `humanizeFileName()` utility to display file names without
extensions, with title-case and spaces (e.g. `executive_memo.md` →
`"Executive Memo"`)
- Updates error messages across RunBlock, RunAgent, and FindBlocks tools
to use friendly language

## Test plan
- [ ] Open CoPilot and trigger a block execution — verify animation text
says "Running" / "Step failed" instead of "Running the block" / "Error
running block"
- [ ] Trigger a file read/write action — verify the activity shows
humanized file names (e.g. `Reading "Executive Memo"` not `Reading
executive_memo.md`)
- [ ] Trigger FindBlocks — verify labels say "Searching for actions" and
"Results" instead of "Searching for blocks" and "Block results"
- [ ] Check the work-done stats bar — verify it shows "action" /
"actions" instead of "block run" / "block runs"
- [ ] Trigger a setup requirements card — verify labels say
"Credentials" and "Inputs" instead of "Block credentials" and "Block
inputs"
- [ ] Visit `/copilot/styleguide` — verify error test data no longer
contains "Block execution" text

Resolves: [SECRT-2025](https://linear.app/autogpt/issue/SECRT-2025)

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

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-16 09:00:25 +00:00
Ubbe
fa04fb41d8 feat(frontend): add "Run now" button to schedule view (#12388)
Adds a "Run now" action to the schedule detail view and sidebar
dropdown, allowing users to immediately trigger a scheduled agent run
without waiting for the next cron execution.

### Changes 🏗️

- **`useSelectedScheduleActions.ts`**: Added
`usePostV1ExecuteGraphAgent` hook and `handleRunNow` function that
executes the agent using the schedule's stored `input_data` and
`input_credentials`. On success, invalidates runs query and navigates to
the new run
- **`SelectedScheduleActions.tsx`**: Added Play icon button as first
action button, with loading spinner while running
- **`SelectedScheduleView.tsx`**: Threads `onSelectRun` prop and
`schedule` object to action components (both mobile and desktop layouts)
- **`NewAgentLibraryView.tsx`**: Passes `onSelectRun` handler to enable
navigation to the new run after execution
- **`ScheduleActionsDropdown.tsx`**: Added "Run now" dropdown menu item
with same execution logic
- **`ScheduleListItem.tsx`**: Added `onRunCreated` prop passed to
dropdown
- **`SidebarRunsList.tsx`**: Connects sidebar dropdown to run
selection/navigation

### 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`, `pnpm lint`, `pnpm types` all pass
- [x] Code review: follows existing patterns (mirrors "Run Again" in
SelectedRunActions)
  - [x] No visual regressions on agent detail page

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

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-16 17:00:41 +08:00
Otto
d9c16ded65 fix(copilot): prioritize block discovery over MCP and sanitize HTML errors (#12394)
Requested by @majdyz

When a user asks for Google Sheets integration, the CoPilot agent skips
block discovery entirely (despite 55+ Google Sheets blocks being
available), jumps straight to MCP, guesses a fake URL
(`https://sheets.googleapis.com/mcp`), and gets a raw HTML 404 error
page dumped into the conversation.

**Changes:**

1. **MCP guide** (`mcp_tool_guide.md`): Added "Check blocks first"
section directing the agent to use `find_block` before attempting MCP
for any service not in the known servers list. Explicitly prohibits
guessing/constructing MCP server URLs.

2. **Error handling** (`run_mcp_tool.py`): Detects HTML error pages in
HTTP responses (e.g. raw 404 pages from non-MCP endpoints) and returns a
clean one-liner like "This URL does not appear to host an MCP server"
instead of dumping the full HTML body.

**Note:** The main CoPilot system prompt (managed externally, not in
repo) should also be updated to reinforce block-first behavior in the
Capability Check section. This PR covers the in-repo changes.

Session reference: `9216df83-5f4a-48eb-9457-3ba2057638ae` (turn 3)
Ticket: [SECRT-2116](https://linear.app/autogpt/issue/SECRT-2116)

---
Co-authored-by: Zamil Majdy (@majdyz) <majdyz@gmail.com>

---------

Co-authored-by: Zamil Majdy (@majdyz) <majdyz@gmail.com>
Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
2026-03-14 12:49:03 +00:00
Otto
6dc8429ae7 fix(copilot): downgrade agent validation failure log from error to warning (#12409)
Agent validation failures are expected when the LLM generates invalid
agent graphs (wrong block IDs, missing required inputs, bad output field
names). The validator catches these and returns proper error responses.

However, `validator.py:938` used `logger.error()`, which Sentry captures
as error events — flooding #platform-alerts with non-errors.

This changes it to `logger.warning()`, keeping the log visible for
debugging without triggering Sentry alerts.

Fixes SECRT-2120

---
Co-authored-by: Zamil Majdy (@majdyz) <zamil.majdy@agpt.co>
2026-03-14 12:48:36 +00:00
Zamil Majdy
cfe22e5a8f fix(backend/copilot): sync TranscriptBuilder with CLI on mid-stream compaction (#12401)
## Summary
- **Root cause**: `TranscriptBuilder` accumulates all raw SDK stream
messages including pre-compaction content. When the CLI compacts
mid-stream, the uploaded transcript was still uncompacted, causing
"Prompt is too long" errors on the next `--resume` turn.
- **Fix**: Detect mid-stream compaction via the `PreCompact` hook, read
the CLI's session file to get the compacted entries (summary +
post-compaction messages), and call
`TranscriptBuilder.replace_entries()` to sync it with the CLI's active
context. This ensures the uploaded transcript always matches what the
CLI sees.
- **Key changes**:
- `CompactionTracker`: stores `transcript_path` from `PreCompact` hook,
one-shot `compaction_just_ended` flag that correctly resets for multiple
compactions
- `read_compacted_entries()`: reads CLI session JSONL, finds
`isCompactSummary: true` entry, returns it + all entries after. Includes
path validation against the CLI projects directory.
- `TranscriptBuilder.replace_entries()`: clears and replaces all entries
with compacted ones, preserving `isCompactSummary` entries (which have
`type: "summary"` that would normally be stripped)
- `load_previous()`: also preserves `isCompactSummary` entries when
loading a previously compacted transcript
- Service stream loop: after compaction ends, reads compacted entries
and syncs TranscriptBuilder

## Test plan
- [x] 69 tests pass across `compaction_test.py` and `transcript_test.py`
- [x] Tests cover: one-shot flag behavior, multiple compactions within a
query, transcript path storage, path traversal rejection,
`read_compacted_entries` (7 tests), `replace_entries` (4 tests),
`load_previous` with compacted content (2 tests)
- [x] Pre-commit hooks pass (lint, format, typecheck)
- [ ] Manual test: trigger compaction in a multi-turn session and verify
the uploaded transcript reflects compaction
2026-03-13 22:17:46 +00:00
Otto
0b594a219c feat(copilot): support prompt-in-URL for shareable prompt links (#12406)
Requested by @torantula

Add support for shareable AutoPilot URLs that contain a prompt in the
URL hash fragment, inspired by [Lovable's
implementation](https://docs.lovable.dev/integrations/build-with-url).

**URL format:**
- `/copilot#prompt=URL-encoded-text` — pre-fills the input for the user
to review before sending
- `/copilot?autosubmit=true#prompt=...` — auto-creates a session and
sends the prompt immediately

**Example:**
```
https://platform.agpt.co/copilot#prompt=Create%20a%20todo%20app
https://platform.agpt.co/copilot?autosubmit=true#prompt=Create%20a%20todo%20app
```

**Key design decisions:**
- Uses URL fragment (`#`) instead of query params — fragments never hit
the server, so prompts stay client-side only (better for privacy, no
backend URL length limits)
- URL is cleaned via `history.replaceState` immediately after extraction
to prevent re-triggering on navigation/reload
- Leverages existing `pendingMessage` + `createSession()` flow for
auto-submit — no new backend APIs needed
- For populate-only mode, passes `initialPrompt` down through component
tree to pre-fill the chat input

**Files changed:**
- `useCopilotPage.ts` — URL hash extraction logic + `initialPrompt`
state
- `CopilotPage.tsx` — passes `initialPrompt` to `ChatContainer`
- `ChatContainer.tsx` — passes `initialPrompt` to `EmptySession`
- `EmptySession.tsx` — passes `initialPrompt` to `ChatInput`
- `ChatInput.tsx` / `useChatInput.ts` — accepts `initialValue` to
pre-fill the textarea

Fixes SECRT-2119

---
Co-authored-by: Toran Bruce Richards (@Torantulino) <toran@agpt.co>
2026-03-13 23:54:54 +07:00
Zamil Majdy
a8259ca935 feat(analytics): read-only SQL views layer with analytics schema (#12367)
### Changes 🏗️

Adds `autogpt_platform/analytics/` — 14 SQL view definitions that expose
production data safely through a locked-down `analytics` schema.

**Security model:**
- Views use `security_invoker = false` (PostgreSQL 15+), so they execute
as their owner (`postgres`), not the caller
- `analytics_readonly` role only has access to `analytics.*` — cannot
touch `platform` or `auth` tables directly

**Files:**
- `backend/generate_views.py` — does everything; auto-reads credentials
from `backend/.env`
- `analytics/queries/*.sql` — 14 documented view definitions (auth, user
activity, executions, onboarding funnel, cohort retention)

---

### Running locally (dev)

```bash
cd autogpt_platform/backend

# First time only — creates analytics schema, role, grants
poetry run analytics-setup

# Create / refresh views (auto-reads backend/.env)
poetry run analytics-views
```

### Running in production (Supabase)

```bash
cd autogpt_platform/backend

# Step 1 — first time only (run in Supabase SQL Editor as postgres superuser)
poetry run analytics-setup --dry-run
# Paste the output into Supabase SQL Editor and run

# Step 2 — apply views (use direct connection host, not pooler)
poetry run analytics-views --db-url "postgresql://postgres:PASSWORD@db.<ref>.supabase.co:5432/postgres"

# Step 3 — set password for analytics_readonly so external tools can connect
# Run in Supabase SQL Editor:
# ALTER ROLE analytics_readonly WITH PASSWORD 'your-password';
```

---

### 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] Setup + views applied cleanly on local Postgres 15
- [x] `analytics_readonly` can `SELECT` from all 14 `analytics.*` views
- [x] `analytics_readonly` gets `permission denied` on `platform.*` and
`auth.*` directly

---------

Co-authored-by: Otto (AGPT) <otto@agpt.co>
2026-03-13 12:04:42 +00:00
Swifty
1f1288d623 feat(copilot): generate personalized quick-action prompts from Tally business understanding (#12374)
During Tally data extraction, the system now also generates personalized
quick-action prompts as part of the existing LLM extraction call
(configurable model, defaults to GPT-4o-mini, `temperature=0.0`). The
prompt asks the LLM for 5 candidates, then the code validates (filters
prompts >20 words) and keeps the top 3. These prompts are stored in the
existing `CoPilotUnderstanding.data` JSON field (at the top level, not
under `business`) and served to the frontend via a new API endpoint. The
copilot chat page uses them instead of hardcoded defaults when
available.

### Changes 🏗️

**Backend – Data models** (`understanding.py`):
- Added `suggested_prompts` field to `BusinessUnderstandingInput`
(optional) and `BusinessUnderstanding` (default empty list)
- Updated `from_db()` to deserialize `suggested_prompts` from top-level
of the data JSON
- Updated `merge_business_understanding_data()` with overwrite strategy
for prompts (full replace, not append)
- `format_understanding_for_prompt()` intentionally does **not** include
`suggested_prompts` — they are UI-only

**Backend – Prompt generation** (`tally.py`):
- Extended `_EXTRACTION_PROMPT` to request 5 suggested prompts alongside
the existing business understanding fields — all extracted in a single
LLM call (`temperature=0.0`)
- Post-extraction validation filters out prompts exceeding 20 words and
slices to the top 3
- Model is now configurable via `tally_extraction_llm_model` setting
(defaults to `openai/gpt-4o-mini`)

**Backend – API endpoint** (`routes.py`):
- Added `GET /api/chat/suggested-prompts` (auth required)
- Returns `{prompts: string[]}` from the user's cached business
understanding (48h Redis TTL)
- Returns empty array if no understanding or no prompts exist

**Frontend** (`EmptySession/`):
- `helpers.ts`: Extracted defaults to `DEFAULT_QUICK_ACTIONS`,
`getQuickActions()` now accepts optional custom prompts and falls back
to defaults
- `EmptySession.tsx`: Calls `useGetV2GetSuggestedPrompts` hook
(`staleTime: Infinity`) and passes results to `getQuickActions()` with
hardcoded fallback
- Fixed `useEffect` resize handler that previously used
`window.innerWidth` as a dependency (re-ran every render); now uses a
proper resize event listener
- Added skeleton loading state while prompts are being fetched

**Generated** (`__generated__/`):
- Regenerated Orval API client with new endpoint types and hooks

### 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 + lint + pyright pass
  - [x] Frontend format + lint pass
  - [x] All existing tally tests pass (28/28)
  - [x] All chat route tests pass (9/9)
  - [x] All invited_user tests pass (7/7)
- [x] E2E: New user with tally data sees custom prompts on copilot page
  - [x] E2E: User without tally data sees hardcoded default prompts
  - [x] E2E: Clicking a custom prompt sends it as a chat message
2026-03-13 12:11:31 +01:00
Otto
02645732b8 feat(backend/copilot): enable E2B auto_resume and reduce safety-net timeout (#12397)
Enable E2B `auto_resume` lifecycle option and reduce the safety-net
timeout from 3 hours to 5 minutes.

Currently, if the explicit per-turn `pause_sandbox_direct()` call fails
(process crash, network issue, fire-and-forget task cancellation), the
sandbox keeps running for up to **3 hours** before the safety-net
timeout fires. With this change, worst-case billing drops to **5
minutes**.

### Changes
- Add `auto_resume: True` to sandbox lifecycle config — paused sandboxes
wake transparently on SDK activity
- Reduce `e2b_sandbox_timeout` default from 10800s (3h) → 300s (5min)
- Add `e2b_sandbox_auto_resume` config field (default: `True`)
- Guard: `auto_resume` only added when `on_timeout == "pause"`

### What doesn't change
- Explicit per-turn `pause_sandbox_direct()` remains the primary
mechanism
- `connect()` / `_try_reconnect()` flow unchanged
- Redis key management unchanged
- No latency impact (resume is ~1-2s regardless of trigger)

### Risk
Very low — `auto_resume` is additive. If it doesn't work as advertised,
`connect()` still resumes paused sandboxes exactly as before.

Ref: https://e2b.dev/docs/sandbox/auto-resume
Linear: SECRT-2118

---
Co-authored-by: Zamil Majdy (@majdyz) <zamil.majdy@agpt.co>
2026-03-13 10:29:28 +00:00
Swifty
ba301a3912 feat(platform): add whitelisting-backed beta user provisioning (#12347)
### Changes 🏗️

- add invite-backed beta provisioning with a new `InvitedUser` platform
model, Prisma migration, and first-login activation path that
materializes `User`, `Profile`, `UserOnboarding`, and
`CoPilotUnderstanding`
- replace the legacy beta allowlist check with invite-backed gating for
email/password signup and Tally pre-seeding during activation
- add admin backend APIs and frontend `/admin/users` management UI for
listing, creating, revoking, retrying, and bulk-uploading invited users
- add the design doc for the beta invite system and extend backend
coverage for invite activation, bulk uploads, and auth-route behavior
- configuration changes: introduce the new invite/tally schema objects
and migration; no new env vars or docker service changes are required

### 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] `cd autogpt_platform/backend && poetry run format`
- [x] `cd autogpt_platform/backend && poetry run pytest -q` (run against
an isolated local Postgres database with non-conflicting service port
overrides)

#### 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**)
2026-03-13 10:25:49 +01:00
Abhimanyu Yadav
0cd9c0d87a fix(frontend): show sub-folders when navigating inside a folder (#12316)
## Summary

When opening a folder in the library, sub-folders were not displayed —
only agents were shown. This was caused by two issues:

1. The folder list query always fetched root-level folders (no
`parent_id` filter), so sub-folders were never requested
2. `showFolders` was set to `false` whenever a folder was selected,
hiding all folders from the view

### Changes 🏗️

- Pass `parent_id` to the `useGetV2ListLibraryFolders` hook so it
fetches child folders of the currently selected folder
- Remove the `!selectedFolderId` condition from `showFolders` so folders
render inside other folders
- Fetch the current folder via `useGetV2GetFolder` instead of searching
the (now differently-scoped) folder list
- Clean up breadcrumb: remove emoji icon, match folder name text size to
"My Library", replace `Button` with plain `<button>` to remove extra
padding/gap

### 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 folder in the library and verify sub-folders are displayed
  - [x] Verify agents inside the folder still display correctly
- [x] Verify breadcrumb shows folder name without emoji, matching "My
Library" text size
- [x] Verify clicking "My Library" in breadcrumb navigates back to root
  - [x] Verify root-level view still shows all top-level folders
  - [x] Verify favorites tab does not show folders
2026-03-13 04:40:09 +00:00
Zamil Majdy
a083493aa2 fix(backend/copilot): auto-parse structured data and robust type coercion (#12390)
The copilot's `@@agptfile:` reference system always produces strings
when expanding
file references. This breaks blocks that expect structured types — e.g.
`GoogleSheetsWriteBlock` expects `values: list[list[str]]`, but receives
a raw CSV
string instead. Additionally, the copilot's input coercion was
duplicating logic from
the executor instead of reusing the shared `convert()` utility, and the
coercion had
no type-aware gating — it would always call `convert()`, which could
incorrectly
transform values that already matched the expected type (e.g.
stringifying a valid
`list[str]` in a `str | list[str]` union).

### Changes 🏗️

**Structured data parsing for `@@agptfile:` bare references:**
- When an entire tool argument value is a bare `@@agptfile:` reference,
the resolved
content is now auto-parsed: JSON → native types, CSV/TSV →
`list[list[str]]`
- Embedded references within larger strings still do plain text
substitution
- Updated copilot system prompt to document the structured data
capability

**Shared type coercion utility (`coerce_inputs_to_schema`):**
- Extracted `coerce_inputs_to_schema()` into `backend/util/type.py` —
shared by both
  the executor's `validate_exec()` and the copilot's `execute_block()`
- Uses Pydantic `model_fields` (not `__annotations__`) to include
inherited fields
- Added `_value_satisfies_type()` gate: only calls `convert()` when the
value doesn't
already match the target type, including recursive inner-element
checking for generics

**`_value_satisfies_type` — recursive type checking:**
- Handles `Any`, `Optional`, `Union`, `list[T]`, `dict[K,V]`, `set[T]`,
`tuple[T, ...]`,
  heterogeneous `tuple[str, int, bool]`, bare generics, nested generics
- Guards against non-runtime origins (`Literal`, etc.) to prevent
`isinstance()` crashes
- Returns `False` (not `True`) for unhandled generic origins as a safe
fallback

**Test coverage:**
- 51 new tests for `_value_satisfies_type` and `coerce_inputs_to_schema`
in `type_test.py`
- 8 new tests for `execute_block` type coercion in `helpers_test.py`

### 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 existing file_ref tests pass
- [x] All new type_test.py tests pass (51 tests covering
_value_satisfies_type and coerce_inputs_to_schema)
- [x] All new helpers_test.py tests pass (8 tests covering execute_block
coercion)
  - [x] `poetry run format` passes clean
  - [x] `poetry run lint` passes clean
  - [x] Pyright type checking passes
2026-03-12 19:27:41 +00:00
Zamil Majdy
c51dc7ad99 fix(backend): agent generator sets invalid model on PerplexityBlocks (#12391)
Fixes the agent generator setting `gpt-5.2-2025-12-11` (or `gpt-4o`) as
the model for PerplexityBlocks instead of valid Perplexity models,
causing 100% failure rate for agents using Perplexity blocks.

### Changes 🏗️

- **Fixer: block-aware model validation** — `fix_ai_model_parameter()`
now reads the block's `inputSchema` to check for `enum` constraints on
the model field. Blocks with their own model enum (PerplexityBlock,
IdeogramBlock, CodexBlock, etc.) are validated against their own allowed
values with the correct default, instead of the hardcoded generic set
(`gpt-4o`, `claude-opus-4-6`). This also fixes `edit_agent` which runs
through the same fixer pipeline.
- **PerplexityBlock: runtime fallback** — Added a `field_validator` on
the model field that gracefully falls back to `SONAR` instead of
crashing when an invalid model value is encountered at runtime. Also
overrides `validate_data` to sanitize invalid model values *before* JSON
schema validation (which runs in `Block._execute` before Pydantic
instantiation), ensuring the fallback is actually reachable during block
execution.
- **DB migration** — Fixes existing PerplexityBlock nodes with invalid
model values in both `AgentNode.constantInput` and
`AgentNodeExecutionInputOutput` (preset overrides), matching the pattern
from the Gemini migration.
- **Tests** — Fixer tests for block-specific enum validation, plus
`validate_data`-level tests ensuring invalid models are sanitized before
JSON schema validation rejects them.

Resolves [SECRT-2097](https://linear.app/autogpt/issue/SECRT-2097)

### 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 existing + new fixer tests pass
  - [x] PerplexityBlock block test passes
- [x] 11 perplexity_test.py tests pass (field_validator + validate_data
paths)
- [x] Verified invalid model (`gpt-5.2-2025-12-11`) falls back to
`perplexity/sonar` at runtime
  - [x] Verified valid Perplexity models are preserved by the fixer
  - [x] Migration covers both constantInput and preset overrides
2026-03-12 18:54:18 +00:00
Krzysztof Czerwinski
bc6b82218a feat(platform): add autopilot notification system (#12364)
Adds a notification system for the Copilot (AutoPilot) so users know
when background chats finish processing — via in-app indicators, sounds,
browser notifications, and document title badges.

### Changes 🏗️

**Backend**
- Add `is_processing` field to `SessionSummaryResponse` — batch-checks
Redis for active stream status on each session in the list endpoint
- Fix `is_processing` always returning `false` due to bytes vs string
comparison (`b"running"` → `"running"`) with `decode_responses=True`
Redis client
- Add `CopilotCompletionPayload` model for WebSocket notification events
- Publish `copilot_completion` notification via WebSocket when a session
completes in `stream_registry.mark_session_completed`

**Frontend — Notification UI**
- Add `NotificationBanner` component — amber banner prompting users to
enable browser notifications (auto-hides when already enabled or
dismissed)
- Add `NotificationDialog` component — modal dialog for enabling
notifications, supports force-open from sidebar menu for testing
- Fix repeated word "response" in dialog copy

**Frontend — Sidebar**
- Add bell icon in sidebar header with popover menu containing:
- Notifications toggle (requests browser permission on enable; shows
toast if denied)
  - Sound toggle (disabled when notifications are off)
  - "Show notification popup" button (for testing the dialog)
  - "Clear local data" button (resets all copilot localStorage keys)
- Bell icon states: `BellSlash` (disabled), `Bell` (enabled, no sound),
`BellRinging` (enabled + sound)
- Add processing indicator (PulseLoader) and completion checkmark
(CheckCircle) inline with chat title, to the left of the hamburger menu
- Processing indicator hides immediately when completion arrives (no
overlap with checkmark)
- Fix PulseLoader initial flash — start at `scale(0); opacity: 0` with
smoother keyframes
- Add 10s polling (`refetchInterval`) to session list so `is_processing`
updates automatically
- Clear document title badge when navigating to a completed chat
- Remove duplicate "Your chats" heading that appeared in both
SidebarHeader and SidebarContent

**Frontend — Notification Hook (`useCopilotNotifications`)**
- Listen for `copilot_completion` WebSocket events
- Track completed sessions in Zustand store
- Play notification sound (only for background sessions, not active
chat)
- Update `document.title` with unread count badge
- Send browser `Notification` when tab is hidden, with click-to-navigate
to the completed chat
- Reset document title on tab focus

**Frontend — Store & Storage**
- Add `completedSessionIDs`, `isNotificationsEnabled`, `isSoundEnabled`,
`showNotificationDialog`, `clearCopilotLocalData` to Zustand store
- Persist notification and sound preferences in localStorage
- On init, validate `isNotificationsEnabled` against actual
`Notification.permission`
- Add localStorage keys: `COPILOT_NOTIFICATIONS_ENABLED`,
`COPILOT_SOUND_ENABLED`, `COPILOT_NOTIFICATION_BANNER_DISMISSED`,
`COPILOT_NOTIFICATION_DIALOG_DISMISSED`

**Mobile**
- Add processing/completion indicators and sound toggle to MobileDrawer

### 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 copilot, start a chat, switch to another chat — verify
processing indicator appears on the background chat
- [x] Wait for background chat to complete — verify checkmark appears,
processing indicator disappears
- [x] Enable notifications via bell menu — verify browser permission
prompt appears
- [x] With notifications enabled, complete a background chat while on
another tab — verify system notification appears with sound
- [x] Click system notification — verify it navigates to the completed
chat
- [x] Verify document title shows unread count and resets when
navigating to the chat or focusing the tab
  - [x] Toggle sound off — verify no sound plays on completion
- [x] Toggle notifications off — verify no sound, no system
notification, no badge
  - [x] Clear local data — verify all preferences reset
- [x] Verify notification banner hides when notifications already
enabled
- [x] Verify dialog auto-shows for first-time users and can be
force-opened from menu

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-12 14:03:24 +00:00
Otto
83e49f71cd fix(frontend): pass through Supabase error params in password reset callback (#12384)
When Supabase rejects a password reset token (expired, already used,
etc.), it redirects to the callback URL with `error`, `error_code`, and
`error_description` params instead of a `code`. Previously, the callback
only checked for `!code` and returned a generic "Missing verification
code" error, swallowing the actual Supabase error.

This meant the `ExpiredLinkMessage` UX (added in SECRT-1369 / #12123)
was never triggered for these cases — users just saw the email input
form again with no explanation.

Now the callback reads Supabase's error params and forwards them to
`/reset-password`, where the existing expired link detection picks them
up correctly.

**Note:** This doesn't fix the root cause of Pwuts's token expiry issue
(likely link preview/prefetch consuming the OTP), but it ensures users
see the proper "link expired" message with a "Request new link" button
instead of a confusing silent redirect.

---
Co-authored-by: Reinier van der Leer (@Pwuts) <pwuts@agpt.co>
2026-03-12 13:51:15 +00:00
Bently
ef446e4fe9 feat(llm): Add Cohere Command A Family Models (#12339)
## Summary
Adds the Cohere Command A family of models to AutoGPT Platform with
proper pricing configuration.

## Models Added
- **Command A 03.2025**: Flagship model (256k context, 8k output) - 3
credits
- **Command A Translate 08.2025**: State-of-the-art translation (8k
context, 8k output) - 3 credits
- **Command A Reasoning 08.2025**: First reasoning model (256k context,
32k output) - 6 credits
- **Command A Vision 07.2025**: First vision-capable model (128k
context, 8k output) - 3 credits

## Changes
- Added 4 new LlmModel enum entries with proper OpenRouter model IDs
- Added ModelMetadata for each model with correct context windows,
output limits, and price tiers
- Added pricing configuration in block_cost_config.py

## Testing
- [ ] Models appear in AutoGPT Platform model selector
- [ ] Pricing is correctly applied when using models

Resolves **SECRT-2083**
2026-03-12 11:56:30 +00:00
Bently
7b1e8ed786 feat(llm): Add Microsoft Phi-4 model support (#12342)
## Changes
- Added `MICROSOFT_PHI_4` to LlmModel enum (`microsoft/phi-4`)
- Configured model metadata:
  - 16K context window
  - 16K max output tokens
  - OpenRouter provider
- Set cost tier: 1
  - Input: $0.06 per 1M tokens
  - Output: $0.14 per 1M tokens

## Details
Microsoft Phi-4 is a 14B parameter model available through OpenRouter.
This PR adds proper support in the autogpt_platform backend.

Resolves SECRT-2086
2026-03-12 11:15:27 +00:00
Abhimanyu Yadav
7ccfff1040 feat(frontend): add credential type selector for multi-auth providers (#12378)
### Changes

- When a provider supports multiple credential types (e.g. GitHub with
both OAuth and API Key),
clicking "Add credential" now opens a tabbed dialog where users can
choose which type to use.
  Previously, OAuth always took priority and API key was unreachable.
- Each credential in the list now shows a type-specific icon (provider
icon for OAuth, key for API Key,
password/lock for others) and a small label badge (e.g. "API Key",
"OAuth").
- The native dropdown options also include the credential type in
parentheses for clarity.
- Single credential type providers behave exactly as before — no dialog,
direct action.


https://github.com/user-attachments/assets/79f3a097-ea97-426b-a2d9-781d7dcdb8a4



  ## Test plan
- [x] Test with a provider that has only one credential type (e.g.
OpenAI with api_key only) — should
  behave as before
- [x] Test with a provider that has multiple types (e.g. GitHub with
OAuth + API Key configured) —
  should show tabbed dialog
  - [x] Verify OAuth tab triggers the OAuth flow correctly
  - [x] Verify API Key tab shows the inline form and creates credentials
  - [x] Verify credential list shows correct icons and type badges
  - [x] Verify dropdown options show type in parentheses
2026-03-12 10:17:58 +00:00
Otto
81c7685a82 fix(frontend): release test fixes — scheduler time picker, unpublished banner (#12376)
Two frontend fixes from release testing (2026-03-11):

**SECRT-2102:** The schedule dialog shows an "At [hh]:[mm]" time picker
when selecting Custom > Every x Minutes or Hours, which makes no sense
for sub-day intervals. Now only shows the time picker for Custom > Days
and other frequency types.

**SECRT-2103:** The "Unpublished changes" banner shows for agents the
user doesn't own or create. Root cause: `owner_user_id` is the library
copy owner, not the graph creator. Changed to use `can_access_graph`
which correctly reflects write access.

---
Co-authored-by: Reinier van der Leer (@Pwuts) <pwuts@agpt.co>

---------

Co-authored-by: Reinier van der Leer (@Pwuts) <reinier@agpt.co>
Co-authored-by: Reinier van der Leer <pwuts@agpt.co>
2026-03-12 10:02:26 +00:00
Bently
3595c6e769 feat(llm): add Perplexity Sonar Reasoning Pro model (#12341)
## Summary
Adds support for Perplexity's new reasoning model:
`perplexity/sonar-reasoning-pro`

## Changes
-  Added `PERPLEXITY_SONAR_REASONING_PRO` to `LlmModel` enum
-  Added model metadata (128K context window, 8K max output tokens,
tier 2)
-  Set pricing at 5 credits (matches sonar-pro tier)

## Model Details
- **Model ID:** `perplexity/sonar-reasoning-pro`
- **Provider:** OpenRouter
- **Context Window:** 128,000 tokens
- **Max Output:** 8,000 tokens
- **Pricing:** $0.000002/token (prompt), $0.000008/token (completion)
- **Cost Tier:** 2 (5 credits)

## Testing
-  Black formatting passed
-  Ruff linting passed

Resolves SECRT-2084
2026-03-12 09:58:29 +00:00
Abhimanyu Yadav
1c2953d61b fix(frontend): restore broken tutorial in builder (#12377)
### Changes
- Restored missing `shepherd.js/dist/css/shepherd.css` base styles
import
- Added missing .new-builder-tutorial-disable and
.new-builder-tutorial-highlight CSS classes to
  tutorial.css
- Fixed getFormContainerSelector() to include -node suffix matching the
actual DOM attribute

###  What broke
The old legacy-builder/tutorial.ts was the only file importing
Shepherd's base CSS. When #12082 removed
the legacy builder, the new tutorial lost all base Shepherd styles
(close button positioning, modal
overlay, tooltip layout). The new tutorial's custom CSS overrides
depended on these base styles
  existing.

  Test plan
  - [x] Start the tutorial from the builder (click the chalkboard icon)
- [x] Verify the close (X) button is positioned correctly in the
top-right of the popover
  - [x] Verify the modal overlay dims the background properly
- [x] Verify element highlighting works when the tutorial points to
blocks/buttons
- [x] Verify non-target blocks are grayed out during the "select
calculator" step
- [x] Complete the full tutorial flow end-to-end (add block → configure
→ connect → save → run)
2026-03-12 09:23:34 +00:00
Zamil Majdy
755bc84b1a fix(copilot): replace MCP jargon with user-friendly language (#12381)
Closes SECRT-2105

### Changes 🏗️

Replace all user-facing MCP technical terminology with plain, friendly
language across the CoPilot UI and LLM prompting.

**Backend (`run_mcp_tool.py`)**
- Added `_service_name()` helper that extracts a readable name from an
MCP host (`mcp.sentry.dev` → `Sentry`)
- `agent_name` in `SetupRequirementsResponse`: `"MCP: mcp.sentry.dev"` →
`"Sentry"`
- Auth message: `"The MCP server at X requires authentication. Please
connect your credentials to continue."` → `"To continue, sign in to
Sentry and approve access."`

**Backend (`mcp_tool_guide.md`)**
- Added "Communication style" section with before/after examples to
teach the LLM to avoid "MCP server", "OAuth", "credentials" jargon in
responses to users

**Frontend (`MCPSetupCard.tsx`)**
- Button: `"Connect to mcp.sentry.dev"` → `"Connect Sentry"`
- Connected state: `"Connected to mcp.sentry.dev!"` → `"Connected to
Sentry!"`
- Retry message: `"I've connected the MCP server credentials. Please
retry."` → `"I've connected. Please retry."`

**Frontend (`helpers.tsx`)**
- Added `serviceNameFromHost()` helper (exported, mirrors the backend
logic)
- Run text: `"Discovering MCP tools on mcp.sentry.dev"` → `"Connecting
to Sentry…"`
- Run text: `"Connecting to MCP server"` → `"Connecting…"`
- Run text: `"Connect to MCP: mcp.sentry.dev"` → `"Connect Sentry"`
(uses `agent_name` which is now just `"Sentry"`)
- Run text: `"Discovered N tool(s) on mcp.sentry.dev"` → `"Connected to
Sentry"`
- Error text: `"MCP error"` → `"Connection error"`

### 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:
- [ ] Open CoPilot and ask it to connect to a service (e.g. Sentry,
Notion)
- [ ] Verify the run text accordion title shows `"Connecting to
Sentry…"` instead of `"Discovering MCP tools on mcp.sentry.dev"`
- [ ] Verify the auth card button shows `"Connect Sentry"` instead of
`"Connect to mcp.sentry.dev"`
- [ ] Verify the connected state shows `"Connected to Sentry!"` instead
of `"Connected to mcp.sentry.dev!"`
- [ ] Verify the LLM response text avoids "MCP server", "OAuth",
"credentials" terminology
2026-03-12 08:54:15 +00:00
Bently
ade2baa58f feat(llm): Add Grok 3 model support (#12343)
## Summary
Adds support for xAI's Grok 3 model to AutoGPT.

## Changes
- Added `GROK_3` to `LlmModel` enum with identifier `x-ai/grok-3`
- Configured model metadata:
  - Context window: 131,072 tokens (128k)
  - Max output: 32,768 tokens (32k)  
  - Provider: OpenRouter
  - Creator: xAI
  - Price tier: 2 (mid-tier)
- Set model cost to 3 credits (mid-tier pricing between fast models and
Grok 4)
- Updated block documentation to include Grok 3 in model lists

## Pricing Rationale
- **Grok 4**: 9 credits (tier 3 - premium, 256k context)
- **Grok 3**: 3 credits (tier 2 - mid-tier, 128k context) ← NEW
- **Grok 4 Fast/4.1 Fast/Code Fast**: 1 credit (tier 1 - affordable)

Grok 3 is positioned as a mid-tier model, priced similarly to other tier
2 models.

## Testing
- [x] Code passes `black` formatting
- [x] Code passes `ruff` linting
- [x] Model metadata and cost configuration added
- [x] Documentation updated

Closes SECRT-2079
2026-03-12 07:31:59 +00:00
Reinier van der Leer
4d35534a89 Merge branch 'master' into dev 2026-03-11 22:26:35 +01:00
Zamil Majdy
2cc748f34c chore(frontend): remove accidentally committed generated file (#12373)
`responseType.ts` was accidentally committed inside
`src/app/api/__generated__/models/` despite that directory being listed
in `.gitignore` (added in PR #12238).

### Changes 🏗️

- Removes
`autogpt_platform/frontend/src/app/api/__generated__/models/responseType.ts`
from git tracking — the file is already covered by the `.gitignore` rule
`src/app/api/__generated__/` and should never have been 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] No functional changes — only removes a stale tracked file that is
already gitignored
2026-03-11 14:22:37 +00:00
Shunyu Wu
c2e79fa5e1 fix(gmail): fallback to raw HTML when html2text conversion fails (#12369)
## Summary
- keep Gmail body extraction resilient when `html2text` converter raises
- fallback to raw HTML instead of failing extraction
- add regression test for converter failure path

Closes #12368

## Testing
- added unit test in
`autogpt_platform/backend/test/blocks/test_gmail.py`

---------

Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
2026-03-11 11:46:57 +00:00
Bently
89a5b3178a fix(llm): Update Gemini model lineup - add 3.1 models, deprecate 3 Pro Preview (#12331)
## 🔴 URGENT: Gemini 3 Pro Preview Shutdown - March 9, 2026

Google is shutting down Gemini 3 Pro Preview **tomorrow (March 9,
2026)**. This PR addresses SECRT-2067 by updating the Gemini model
lineup to prevent disruption.

---

## Changes

###  P0 - Critical (This Week)
- [x] **Remove/Replace Gemini 3 Pro Preview** → Migrated to 3.1 Pro
Preview
- [x] **Add Gemini 3.1 Pro Preview** (released Feb 19, 2026)

###  P1 - High Priority  
- [x] **Add Gemini 3.1 Flash Lite Preview** (released Mar 3, 2026)
- [x] **Add Gemini 3 Flash Preview** (released Dec 17, 2025)

###  P2 - Medium Priority
- [x] **Add Gemini 2.5 Pro (stable/GA)** (released Jun 17, 2025)

---

## Model Details

| Model | Context | Input Cost | Output Cost | Price Tier |
|-------|---------|------------|-------------|------------|
| **Gemini 3.1 Pro Preview** | 1.05M | $2.00/1M | $12.00/1M | 2 |
| **Gemini 3.1 Flash Lite Preview** | 1.05M | $0.25/1M | $1.50/1M | 1 |
| **Gemini 3 Flash Preview** | 1.05M | $0.50/1M | $3.00/1M | 1 |
| **Gemini 2.5 Pro (GA)** | 1.05M | $1.25/1M | $10.00/1M | 2 |
| ~~Gemini 3 Pro Preview~~ | ~~1.05M~~ | ~~$2.00/1M~~ | ~~$12.00/1M~~ |
**DEPRECATED** |

---

## Migration Strategy

**Database Migration:**
`20260308095500_migrate_deprecated_gemini_3_pro_preview`

- Automatically migrates all existing graphs using
`google/gemini-3-pro-preview` to `google/gemini-3.1-pro-preview`
- Updates: AgentBlock, AgentGraphExecution, AgentNodeExecution,
AgentGraph
- Zero user-facing disruption
- Migration runs on next deployment (before March 9 shutdown)

---

## Testing

- [ ] Verify new models appear in LLM block dropdown
- [ ] Test migration on staging database
- [ ] Confirm existing graphs using deprecated model auto-migrate
- [ ] Validate cost calculations for new models

---

## References

- **Linear Issue:**
[SECRT-2067](https://linear.app/autogpt/issue/SECRT-2067)
- **OpenRouter Models:** https://openrouter.ai/models/google
- **Google Deprecation Notice:**
https://ai.google.dev/gemini-api/docs/deprecations

---

## Checklist

- [x] Models added to `LlmModel` enum
- [x] Model metadata configured
- [x] Cost config updated
- [x] Database migration created
- [x] Deprecated model commented out (not removed for historical
reference)
- [ ] PR reviewed and approved
- [ ] Merged before March 9, 2026 deadline

---

**Priority:** 🔴 Critical - Must merge before March 9, 2026
2026-03-11 11:21:16 +00:00
Abhimanyu Yadav
c62d9a24ff fix(frontend): show correct status in agent submission view modal (#12360)
### Changes 🏗️
- The "View" modal for agent submissions hardcoded "Agent is awaiting
review" regardless of actual status
- Now displays "Agent approved", "Agent rejected", or "Agent is awaiting
review" based on the submission's actual status
- Shows review feedback in a highlighted section for rejected agents
when review comments are available

<img width="1127" height="788" alt="Screenshot 2026-03-11 at 9 02 29 AM"
src="https://github.com/user-attachments/assets/840e0fb1-22c2-4fda-891b-967c8b8b4043"
/>
<img width="1105" height="680" alt="Screenshot 2026-03-11 at 9 02 46 AM"
src="https://github.com/user-attachments/assets/f0c407e6-c58e-4ec8-9988-9f5c69bfa9a7"
/>

  ## Test plan
- [x] Submit an agent and verify the view modal shows "Agent is awaiting
review"
- [x] View an approved agent submission and verify it shows "Agent
approved"
- [x] View a rejected agent submission and verify it shows "Agent
rejected"
- [x] View a rejected agent with review comments and verify the feedback
section appears

  Closes SECRT-2092
2026-03-11 10:08:17 +00:00
Abhimanyu Yadav
0e0bfaac29 fix(frontend): show specific error messages for store image upload failures (#12361)
### Changes
- Surface backend error details (file size limit, invalid file type,
virus detected, etc.) in the upload failed toast instead of showing a
generic "Upload Failed" message
- The backend already returns specific error messages (e.g., "File too
large. Maximum size is 50MB") but the frontend was discarding them with
a catch-all handler
  
<img width="1222" height="411" alt="Screenshot 2026-03-11 at 9 13 30 AM"
src="https://github.com/user-attachments/assets/34ab3d90-fffa-4788-917a-fe2a7f4144b9"
/>

  ## Test plan
- [x] Upload an image larger than 50MB to a store submission → should
see "File too large. Maximum size is 50MB"
- [x] Upload an unsupported file type → should see file type error
message
  - [x] Upload a valid image → should still work normally

  Resolves SECRT-2093
2026-03-11 10:07:37 +00:00
Bently
0633475915 fix(frontend/library): graceful schedule deletion with auto-selection (#12278)
### Motivation 🎯

Fixes the issue where deleting a schedule shows an error screen instead
of gracefully handling the deletion. Previously, when a user deleted a
schedule, a race condition occurred where the query cache refetch
completed before the URL
state updated, causing the component to try rendering a schedule that no
longer existed (resulting in a 404 error screen).

### Changes 🏗️

**1. Fixed deletion order to prevent error screen flash**
- `useSelectedScheduleActions.ts` - Call `onDeleted()` callback
**before** invalidating queries to clear selection first
- `ScheduleActionsDropdown.tsx` - Same fix for sidebar dropdown deletion

**2. Added smart auto-selection logic**
- `useNewAgentLibraryView.ts`:
  - Added query to fetch current schedules list
  - Added `handleScheduleDeleted(deletedScheduleId)` function that:
    - Auto-selects the first remaining schedule if others exist
    - Clears selection to show empty state if no schedules remain

**3. Wired up smart deletion handler throughout component tree**
- `NewAgentLibraryView.tsx` - Passes `handleScheduleDeleted` to child
components
- `SelectedScheduleView.tsx` - Changed callback from
`onClearSelectedRun` to `onScheduleDeleted` and passes schedule ID
- `SidebarRunsList.tsx` - Added `onScheduleDeleted` prop and passes it
through to list items

### Checklist 📋

**Test Plan:**
- [] Create 2-3 test schedules for an agent
- [] Delete a schedule from the detail view (trash icon in actions) when
other schedules exist → Verify next schedule auto-selects without error
- [] Delete a schedule from the sidebar dropdown (three-dot menu) when
other schedules exist → Verify next schedule auto-selects without error
- [] Delete all schedules until only one remains → Verify empty state
shows gracefully without error
- [] Verify "Schedule deleted" toast appears on successful deletion
- [] Verify no error screen appears at any point during deletion flow
2026-03-11 09:01:55 +00:00
Bently
34a2f9a0a2 feat(llm): add Mistral flagship models (Large 3, Medium 3.1, Small 3.2, Codestral) (#12337)
## Summary

Adds four missing Mistral AI flagship models to address the critical
coverage gap identified in
[SECRT-2082](https://linear.app/autogpt/issue/SECRT-2082).

## Models Added

| Model | Context | Max Output | Price Tier | Use Case |
|-------|---------|------------|------------|----------|
| **Mistral Large 3** | 262K | None | 2 (Medium) | Flagship reasoning
model, 41B active params (675B total), MoE architecture |
| **Mistral Medium 3.1** | 131K | None | 2 (Medium) | Balanced
performance/cost, 8x cheaper than traditional large models |
| **Mistral Small 3.2** | 131K | 131K | 1 (Low) | Fast, cost-efficient,
high-volume use cases |
| **Codestral 2508** | 256K | None | 1 (Low) | Code generation
specialist (FIM, correction, test gen) |

## Problem

Previously, the platform only offered:
- Mistral Nemo (1 official model)
- dolphin-mistral (third-party Ollama fine-tune)

This left significant gaps in Mistral's lineup, particularly:
- No flagship reasoning model
- No balanced mid-tier option
- No code-specialized model
- Missing multimodal capabilities (Large 3, Medium 3.1, Small 3.2 all
support text+image)

## Changes

**File:** `autogpt_platform/backend/backend/blocks/llm.py`

- Added 4 enum entries in `LlmModel` class
- Added 4 metadata entries in `MODEL_METADATA` dict
- All models use OpenRouter provider
- Follows existing pattern for model additions

## Testing

-  Enum values match OpenRouter model IDs
-  Metadata follows existing format
-  Context windows verified from OpenRouter API
-  Price tiers assigned appropriately

## Closes

- SECRT-2082

---

**Note:** All models are available via OpenRouter and tested. This
brings Mistral coverage in line with other major providers (OpenAI,
Anthropic, Google).
2026-03-11 08:48:48 +00:00
Zamil Majdy
9f4caa7dfc feat(blocks): add and harden GitHub blocks for full-cycle development (#12334)
## Summary
- Add 8 new GitHub blocks: GetRepositoryInfo, ForkRepository,
ListCommits, SearchCode, CompareBranches, GetRepositoryTree,
MultiFileCommit, MergePullRequest
- Split `repo.py` (2094 lines, 19 blocks) into domain-specific modules:
`repo.py`, `repo_branches.py`, `repo_files.py`, `commits.py`
- Concurrent blob creation via `asyncio.gather()` in MultiFileCommit
- URL-encode branch/ref params via `urllib.parse.quote()` for
defense-in-depth
- Step-level error handling in MultiFileCommit ref update with recovery
SHA
- Collapse FileOperation CREATE/UPDATE into UPSERT (Git Trees API treats
them identically)
- Add `ge=1, le=100` constraints on per_page SchemaFields
- Preserve URL scheme in `prepare_pr_api_url`
- Handle null commit authors gracefully in ListCommits
- Add unit tests for `prepare_pr_api_url`, error-path tests for
MergePR/MultiFileCommit, FileOperation enum validation tests

## Test plan
- [ ] Block tests pass for all 19 GitHub blocks (CI:
`test_available_blocks`)
- [ ] New test file `test_github_blocks.py` passes (prepare_pr_api_url,
error paths, enum)
- [ ] `check-docs-sync` passes with regenerated docs
- [ ] pyright/ruff clean on all changed files
2026-03-11 08:35:37 +00:00
Otto
0876d22e22 feat(frontend/copilot): improve TTS voice selection to avoid robotic voices (#12317)
Requested by @0ubbe

Refines the `pickBestVoice()` function to ensure non-robotic voices are
always preferred:

- **Filter out known low-quality engines** — eSpeak, Festival, MBROLA,
Flite, and Pico voices are deprioritized
- **Prefer remote/cloud-backed voices** — `localService: false` voices
are typically higher quality
- **Expand preferred voices list** — added Moira, Tessa (macOS), Jenny,
Aria, Guy (Windows OneCore)
- **Smarter fallback chain** — English default → English → any default →
first available

The previous fallback could select eSpeak or Festival voices on Linux
systems, resulting in robotic output. Now those are filtered out unless
they're the only option.

---
Co-authored-by: Ubbe <ubbe@users.noreply.github.com>

---------

Co-authored-by: Ubbe <hi@ubbe.dev>
Co-authored-by: Lluis Agusti <hi@llu.lu>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-11 16:47:42 +08:00
Zamil Majdy
15e3980d65 fix(frontend): buffer workspace file downloads to prevent truncation (#12349)
## Summary
- Workspace file downloads (images, CSVs, etc.) were silently truncated
(~10 KB lost from the end) when served through the Next.js proxy
- Root cause: `new NextResponse(response.body)` passes a
`ReadableStream` directly, which Next.js / Vercel silently truncates for
larger files
- Fix: fully buffer with `response.arrayBuffer()` before forwarding, and
set `Content-Length` from the actual buffer size
- Keeps the auth proxy intact — no signed URLs (which would be public
and expire, breaking chat history)

## Root cause verification
Confirmed locally on session `080f27f9-0379-4085-a67a-ee34cc40cd62`:
- Backend `write_workspace_file` logs **978,831 bytes** written
- Direct backend download (`curl
localhost:8006/api/workspace/files/.../download`): **978,831 bytes** 
- Browser download through Next.js proxy: **truncated** 

## Why not signed URLs?
- Signed URLs are effectively public — anyone with the link can download
the file (privacy concern)
- Signed URLs expire, but chat history persists — reopening a
conversation later would show broken downloads
- Buffering is fine: workspace files are capped at 100 MB, Vercel
function memory is 1 GB

## Related
- Discord thread: `#Truncated File Bug` channel
- Related PR #12319 (signed URL approach) — this fix is simpler and
preserves auth

## Test plan
- [ ] Download a workspace file (CSV, PNG, any type) through the copilot
UI
- [ ] Verify downloaded file size matches the original
- [ ] Verify PNGs open correctly and CSVs have all rows

cc @Swiftyos @uberdot @AdarshRawat1
2026-03-10 18:23:51 +00:00
Zamil Majdy
fe9eb2564b feat(copilot): HITL review for sensitive block execution (#12356)
## Summary
- Integrates existing Human-In-The-Loop (HITL) review infrastructure
into CoPilot's direct block execution (`run_block`) for blocks marked
with `is_sensitive_action=True`
- Removes the `PendingHumanReview → AgentGraphExecution` FK constraint
to support synthetic CoPilot session IDs (migration included)
- Adds `ReviewRequiredResponse` model + frontend `ReviewRequiredCard`
component to surface review status in the chat UI
- Auto-approval works within a CoPilot session: once a block is
approved, subsequent executions of the same block in the same session
are auto-approved (using `copilot-session-{session_id}` as
`graph_exec_id` and `copilot-node-{block_id}` as `node_id`)

## Test plan
- [x] All 11 `run_block_test.py` tests pass (3 new sensitive action
tests)
- [ ] Manual: Execute a block with `is_sensitive_action=True` in CoPilot
→ verify ReviewRequiredResponse is returned and rendered
- [ ] Manual: Approve in review panel → re-execute the same block →
verify auto-approval kicks in
- [ ] Manual: Verify non-sensitive blocks still execute without review
2026-03-10 18:20:11 +00:00
Otto
5641cdd3ca fix(backend): update test patches for validate_url → validate_url_host rename (#12358)
bfb843a renamed `validate_url` to `validate_url_host` in
`agent_browser`, `run_mcp_tool`, and MCP routes, but the corresponding
test files still patched the old name, causing `AttributeError` in CI.

Updates all mock patch targets and assertions across 3 test files:
- `agent_browser_test.py`
- `test_run_mcp_tool.py`  
- `mcp/test_routes.py`

---
Co-authored-by: Zamil Majdy (@majdyz) <zamil.majdy@agpt.co>
Co-authored-by: Reinier van der Leer (@Pwuts) <pwuts@agpt.co>
2026-03-10 17:22:11 +00:00
Otto
bfb843a56e Merge commit from fork
* Fix SSRF via user-controlled ollama_host field

Validate ollama_host against BLOCKED_IP_NETWORKS before passing to
ollama.AsyncClient(). The server-configured default (env: OLLAMA_HOST)
is allowed without validation; user-supplied values that differ are
checked for private/internal IP resolution.

Fixes GHSA-6jx2-4h7q-3fx3

* Generalize validate_ollama_host to validate_host; fix description line length

* Rename to validate_untrusted_host with whitelist parameter

* Apply PR suggestion: include whitelist in error message; run formatting

* Move whitelist check after URL normalization; match on netloc

* revert unrelated formatting changes

* Dedup validate_url and validate_untrusted_host; normalize whitelist

* Move _resolve_and_check_blocked after calling functions

* dedup and clean up

* make trusted_hostnames truly optional

---------

Co-authored-by: Reinier van der Leer <pwuts@agpt.co>
2026-03-10 15:51:58 +01:00
Abhimanyu Yadav
684845d946 fix(frontend/builder): handle discriminated unions and improve node layout (#12354)
## Summary
- **Discriminated union support (oneOf)**: Added a new `OneOfField`
component that properly
renders Pydantic discriminated unions. Hides the unusable parent object
handle, auto-populates
the discriminator value, shows a dropdown with variant titles (e.g.,
"Username" / "UserId"), and
filters out the internal discriminator field from the form.
Non-discriminated `oneOf` schemas
  fall back to existing `AnyOfField` behavior.
- **Collapsible object outputs**: Object-type outputs with nested keys
(e.g.,
`PersonLookupResponse.Url`, `PersonLookupResponse.profile`) are now
collapsed by default behind a
caret toggle. Nested keys show short names instead of the full
`Parent.Key` prefix.
- **Node layout cleanup**: Removed excessive bottom margin (`mb-6`) from
`FormRenderer`, hide the
Advanced toggle when no advanced fields exist, and add rounded bottom
corners on OUTPUT-type
  blocks.

<img width="440" height="427" alt="Screenshot 2026-03-10 at 11 31 55 AM"
src="https://github.com/user-attachments/assets/06cc5414-4e02-4371-bdeb-1695e7cb2c97"
/>
<img width="371" height="320" alt="Screenshot 2026-03-10 at 11 36 52 AM"
src="https://github.com/user-attachments/assets/1a55f87a-c602-4f4d-b91b-6e49f810e5d5"
/>

  ## Test plan
- [x] Add a Twitter Get User block — verify "Identifier" shows a
dropdown (Username/UserId) with
no unusable parent handle, discriminator field is hidden, and the block
can run without staying
  INCOMPLETE
- [x] Add any block with object outputs (e.g., PersonLookupResponse) —
verify nested keys are
  collapsed by default and expand on click with short labels
- [x] Verify blocks without advanced fields don't show the Advanced
toggle
- [x] Verify existing `anyOf` schemas (optional types, 3+ variant
unions) still render correctly
  - [x] Check OUTPUT-type blocks have rounded bottom corners

---------

Co-authored-by: Reinier van der Leer <pwuts@agpt.co>
Co-authored-by: eureka928 <meobius123@gmail.com>
2026-03-10 14:13:32 +00:00
Bently
6a6b23c2e1 fix(frontend): Remove unused Otto Server Action causing 107K+ errors (#12336)
## Summary

Fixes [OPEN-3025](https://linear.app/autogpt/issue/OPEN-3025) —
**107,571+ Server Action errors** in production

Removes the orphaned `askOtto` Server Action that was left behind after
the Otto chat widget removal in PR #12082.

## Problem

Next.js Server Actions that are never imported are excluded from the
server manifest. Old client bundles still reference the action ID,
causing "not found" errors.

**Sentry impact:**
- **BUILDER-3BN:** 107,571 events
- **BUILDER-729:** 285 events  
- **BUILDER-3QH:** 1,611 events
- **36+ users affected**

## Root Cause

1. **Mar 2025:** Otto widget added to `/build` page with `askOtto`
Server Action
2. **Feb 2026:** Otto widget removed (PR #12082), but `actions.ts` left
behind
3. **Result:** Dead code → not in manifest → errors

## Evidence

```bash
# Zero imports across frontend:
grep -r "askOtto" src/ --exclude="actions.ts"
# → No results

# Server manifest missing the action:
cat .next/server/server-reference-manifest.json
# → Only includes login/supabase actions, NOT build/actions
```

## Changes

-  Delete
`autogpt_platform/frontend/src/app/(platform)/build/actions.ts`

## Testing

1. Verify no imports of `askOtto` in codebase 
2. Check Sentry for error drop after deploy
3. Monitor for new "Server Action not found" errors

## Checklist

- [x] Dead code confirmed (zero imports)
- [x] Sentry issues documented
- [x] Clear commit message with context
2026-03-10 09:03:38 +00:00
Dream
d0a1d72e8a fix(frontend/builder): batch undo history for cascading operations (#12344)
## Summary

Fixes undo in the Builder not working correctly when deleting nodes.
When a node is deleted, React Flow fires `onNodesChange` (node removal)
and `onEdgesChange` (cascading edge cleanup) as separate callbacks —
each independently pushing to the undo history stack. This creates
intermediate states that break undo:

- Single undo restores a partial state (e.g. edges pointing to a deleted
node)
- Multiple undos required to fully restore the graph
- Redo also produces inconsistent states

Resolves #10999

### Changes 🏗️

- **`historyStore.ts`** — Added microtask-based batching to
`pushState()`. Multiple calls within the same synchronous execution
(same event loop tick) are coalesced into a single history entry,
keeping only the first pre-change snapshot. Uses `queueMicrotask` so all
cascading store updates from a single user action settle before the
history entry is committed.
- Reset `pendingState` in `initializeHistory()` and `clear()` to prevent
stale batched state from leaking across graph loads or navigation.

**Side benefit:** Copy/paste operations that add multiple nodes and
edges now also produce a single history entry instead of one per
node/edge.

### 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] Place 3 blocks A, B, C and connect A→B→C
  - [x] Delete block C (removes node + cascading edge B→C)
  - [x] Delete connection A→B
  - [x] Undo — connection A→B restored (single undo, not multiple)
  - [x] Undo — block C and connection B→C restored
  - [x] Redo — block C removed again with its connections
- [x] Copy/paste multiple connected blocks — single undo reverts entire
paste

---------

Co-authored-by: Reinier van der Leer <pwuts@agpt.co>
Co-authored-by: Abhimanyu Yadav <122007096+Abhi1992002@users.noreply.github.com>
2026-03-10 04:55:07 +00:00
Zamil Majdy
f1945d6a2f feat(platform/copilot): @@agptfile: file-ref protocol for tool call inputs + block input toggle (#12332)
## Summary

- **Problem**: When the LLM calls a tool with large file content, it
must rewrite all content token-by-token. This is wasteful since the
files are already accessible on disk.
- **Solution**: Introduces an \`@@agptfile:\` reference protocol. The
LLM passes a file path reference; the processor loads and substitutes
the content before executing the tool.

### Protocol

\`\`\`
@@agptfile:<uri>[<start>-<end>]
\`\`\`

**Supported URI types:**
| URI | Source |
|-----|--------|
| \`workspace://<file_id>\` | Persistent workspace file by ID |
| \`workspace:///<path>\` | Workspace file by virtual path |
| \`/absolute/path\` | Absolute host or sandbox path |

**Line range** is optional; omitting it reads the whole file.

### Backend changes

- Rename \`@file:\` → \`@@agptfile:\` prefix for uniqueness; extract
\`FILE_REF_PREFIX\` constant
- Extract shared execution-context ContextVars into
\`backend/copilot/context.py\` — eliminates duplicate ContextVar objects
that caused \`e2b_file_tools.py\` to always see empty context
- \`tool_adapter.py\` imports ContextVars from \`context.py\` (single
source of truth)
- \`expand_file_refs_in_string\` raises \`FileRefExpansionError\` on
failure (instead of inline error strings), blocking tool execution and
returning a clear error hint to the model
- Tighten URI regex: only expand refs starting with \`workspace://\` or
\`/\`
- Aggregate budget: 1 MB total expansion cap across all refs in one
string
- Per-file cap: 200 KB per individual ref
- Fix \`_read_file_handler\` to pass \`get_sdk_cwd()\` to
\`is_allowed_local_path\` — ephemeral working directory files were
incorrectly blocked
- Fix \`_is_allowed_local\` in \`e2b_file_tools.py\` to pass
\`get_sdk_cwd()\`
- Restrict local path allow-list to \`tool-results/\` subdirectory only
(was entire session project dir)
- Add \`raise_on_error\` param + remove two-pass \`_FILE_REF_ERROR_RE\`
detection
- Update system prompt docs and tool_adapter error messages

### Frontend changes

- \`BlockInputCard\`: hidden by default with Show/Hide toggle + \`mb-2\`
spacing

## Test plan

- [ ] \`poetry run pytest backend/copilot/ -x
--ignore=backend/copilot/sdk/file_ref_integration_test.py\` passes
- [ ] \`@@agptfile:workspace:///<path>[1-50]\` expands correctly in tool
calls
- [ ] Invalid line ranges produce \`[file-ref error: ...]\` inline
messages
- [ ] Files outside \`sdk_cwd\` / \`tool-results/\` are rejected
- [ ] Block input card shows hidden by default with toggle
2026-03-09 18:39:13 +00:00
Zamil Majdy
6491cb1e23 feat(copilot): local agent generation with validation, fixing, MCP & sub-agent support (#12238)
## Summary

Port the agent generation pipeline from the external AgentGenerator
service into local copilot tools, making the Claude Agent SDK itself
handle validation, fixing, and block recommendation — no separate inner
LLM calls needed.

Key capabilities:
- **Local agent generation**: Create, edit, and customize agents
entirely within the SDK session
- **Graph validation**: 9 validation checks (block existence, link
references, type compatibility, IO blocks, etc.)
- **Graph fixing**: 17+ auto-fix methods (ID repair, link rewiring, type
conversion, credential stripping, dynamic block sink names, etc.)
- **MCP tool blocks**: Guide and fixer support for MCPToolBlock nodes
with proper dynamic input schema handling
- **Sub-agent composition**: AgentExecutorBlock support with library
agent schema enrichment
- **Embedding fallback**: Falls back to OpenRouter for embeddings when
`openai_internal_api_key` is unavailable
- **Actionable error messages**: Excluded block types (MCP, Agent)
return specific hints redirecting to the correct tool

### New Tools
- `validate_agent_graph` — run 9 validation checks on agent JSON
- `fix_agent_graph` — apply 17+ auto-fixes to agent JSON
- `get_blocks_for_goal` — recommend blocks for a given goal (with
optimized descriptions)

### Refactored Tools
- `create_agent`, `edit_agent`, `customize_agent` — accept `agent_json`
for local generation with shared fix→validate→save pipeline
- `find_block` — added `include_schemas` parameter, excludes MCP/Agent
blocks with actionable hints
- `run_block` — actionable error messages for excluded block types
- `find_library_agent` — enriched with `graph_version`, `input_schema`,
`output_schema` for sub-agent composition

### Architecture
- Split 2,558-line `validation.py` into `fixer.py`, `validator.py`,
`helpers.py`, `pipeline.py`
- Extracted shared `fix_validate_and_save()` pipeline (was duplicated
across 3 tools)
- Shared `OPENROUTER_BASE_URL` constant across codebase
- Comprehensive test coverage: 78+ unit tests for fixer/validator, 8
run_block tests, 17 SDK compat tests

## Test plan
- [x] `poetry run format` passes
- [x] `poetry run pytest -s -vvv backend/copilot/` — all tests pass
- [x] CI green on all Python versions (3.11, 3.12, 3.13)
- [x] Manual E2E: copilot generates agents with correct IO blocks,
links, and node structure
- [x] Manual E2E: MCP tool blocks use bare field names for dynamic
inputs
- [x] Manual E2E: sub-agent composition with AgentExecutorBlock
2026-03-09 16:10:22 +00:00
nKOxxx
c7124a5240 Add documentation for Google Gemini integration (#12283)
## Summary
Adding comprehensive documentation for Google Gemini integration with
AutoGPT.

## Changes
- Added setup instructions for Gemini API
- Documented configuration options
- Added examples and best practices

## Related Issues
N/A - Documentation improvement

## Testing
- Verified documentation accuracy
- Tested all code examples

## Checklist
- [x] Code follows project style
- [x] Documentation updated
- [x] Tests pass (if applicable)
2026-03-09 15:13:28 +00:00
Zamil Majdy
5537cb2858 dx: add shared Claude Code skills as auto-triggered guidelines (#12297)
## Summary
- Add 8 Claude Code skills under \`.claude/skills/\` that act as
**auto-triggered guidelines** — the LLM invokes them automatically based
on context, no manual \`/command\` needed
- Skills: \`pr-review\`, \`pr-create\`, \`new-block\`,
\`openapi-regen\`, \`backend-check\`, \`frontend-check\`,
\`worktree-setup\`, \`code-style\`
- Each skill has an explicit TRIGGER condition so the LLM knows when to
apply it without being asked

## Changes

### Skills (all auto-triggered by context)
| Skill | Trigger |
|-------|---------|
| \`pr-review\` | User shares a PR URL or asks to address review
comments |
| \`pr-create\` | User asks to create a PR, push changes for review, or
submit work |
| \`new-block\` | User asks to create a new block or add a new
integration |
| \`openapi-regen\` | API routes change, new endpoints added, or
frontend types are stale |
| \`backend-check\` | Backend Python code has been modified |
| \`frontend-check\` | Frontend TypeScript/React code has been modified
|
| \`worktree-setup\` | User asks to work on a branch in isolation or set
up a worktree |
| \`code-style\` | Writing or reviewing Python code |

## Test plan
- [ ] Verify skills appear automatically in Claude Code when context
matches (no \`/command\` needed)
- [ ] Modify frontend code — confirm \`frontend-check\` fires
automatically
- [ ] Ask Claude to "create a PR" — confirm \`pr-create\` fires without
\`/pr-create\`
- [ ] Share a PR URL — confirm \`pr-review\` fires automatically

---------

Co-authored-by: Krzysztof Czerwinski <kpczerwinski@gmail.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-09 15:10:38 +00:00
Zamil Majdy
aef5f6d666 feat(copilot): E2B sandbox auto-pause between turns to eliminate idle billing (#12330)
## Summary

### Before
- E2B sandboxes ran continuously between CoPilot turns, billing for idle
time
- Sandbox timeout caused **termination** (kill), losing all session
state
- No explicit cleanup when sessions were deleted — sandboxes leaked
- Single timeout concept with no separation between pause and kill
semantics

### After
- **Per-turn pause**: `pause_sandbox()` is called in the `finally` block
after every CoPilot turn, stopping billing instantly between turns
(paused sandboxes cost \$0 compute)
- **Auto-pause safety net**: Sandboxes are created with
`lifecycle={"on_timeout": "pause"}` (`pause_timeout` = 4h default) so
they auto-pause rather than terminate if the explicit pause is missed
- **Auto-reconnect**: `AsyncSandbox.connect()` in e2b SDK v2
auto-resumes paused sandboxes transparently — no extra code needed
- **Session delete cleanup**: `kill_sandbox()` is now called in
`delete_chat_session()` to explicitly terminate sandboxes and free
resources
- **Two distinct timeouts**: `pause_timeout` (4h, e2b auto-pause) vs
`redis_ttl` (12h, session key lifetime)

### Key Changes

| File | Change |
|------|--------|
| `pyproject.toml` | Bump `e2b-code-interpreter` `1.x` → `2.x` |
| `e2b_sandbox.py` | Add `pause_sandbox()`, `kill_sandbox()`,
`_act_on_sandbox()` helper; `lifecycle={"on_timeout": "pause"}`;
separate `pause_timeout` / `redis_ttl` params |
| `sdk/service.py` | Call `pause_sandbox()` in `finally` block
**before** transcript upload; use walrus operator for type-safe
`e2b_api_key` narrowing |
| `model.py` | Call `kill_sandbox()` in `delete_chat_session()`; inline
import to avoid circular dependency |
| `config.py` | Add `e2b_active` property; rename `e2b_sandbox_timeout`
default to 4h |
| `e2b_sandbox_test.py` | Add `test_pause_then_reconnect_reuses_sandbox`
test; update all `sandbox_timeout` → `pause_timeout` |

### Verified E2E
- Used real `E2B_API_KEY` from k8s dev cluster to manually verify:
sandbox created → paused → `is_running() == False` → reconnected via
`connect()` → state preserved → killed

## Test plan
- [x] `poetry run pytest backend/copilot/tools/e2b_sandbox_test.py` —
all 19 tests pass
- [x] CI: test (3.11, 3.12, 3.13), types — all green
- [x] E2E verified with real E2B credentials
2026-03-09 14:55:10 +00:00
Ubbe
8063391d0a feat(frontend/copilot): pin interactive tool cards outside reasoning collapse (#12346)
## Summary

<img width="400" height="227" alt="Screenshot 2026-03-09 at 22 43 10"
src="https://github.com/user-attachments/assets/0116e260-860d-4466-9763-e02de2766e50"
/>

<img width="600" height="618" alt="Screenshot 2026-03-09 at 22 43 14"
src="https://github.com/user-attachments/assets/beaa6aca-afa8-483f-ac06-439bf162c951"
/>

- When the copilot stream finishes, tool calls that require user
interaction (credentials, inputs, clarification) are now **pinned**
outside the "Show reasoning" collapse instead of being hidden
- Added `isInteractiveToolPart()` helper that checks tool output's
`type` field against a set of interactive response types
- Modified `splitReasoningAndResponse()` to extract interactive tools
from reasoning into the visible response section
- Added styleguide section with 3 demos: `setup_requirements`,
`agent_details`, and `agent_saved` pinning scenarios

### Interactive response types kept visible:
`setup_requirements`, `agent_details`, `block_details`, `need_login`,
`input_validation_error`, `clarification_needed`, `suggested_goal`,
`agent_preview`, `agent_saved`

Error responses remain in reasoning (LLM explains them in final text).

Closes SECRT-2088

## Test plan
- [ ] Verify copilot stream with interactive tool (e.g. run_agent
requiring credentials) keeps the tool card visible after stream ends
- [ ] Verify non-interactive tools (find_block, bash_exec) still
collapse into "Show reasoning"
- [ ] Verify styleguide page at `/copilot/styleguide` renders the new
"Reasoning Collapse: Interactive Tool Pinning" section correctly
- [ ] Verify `pnpm types`, `pnpm lint`, `pnpm format` all pass

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

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-09 23:12:14 +08:00
Otto
0bbb12d688 fix(frontend/copilot): hide New Chat button on Autopilot homepage (#12321)
Requested by @0ubbe

The **New Chat** button was visible on the Autopilot homepage where
clicking it has no effect (since `sessionId` is already `null`). This
hides the button when no chat session is active, so it only appears when
the user is viewing a conversation and wants to start a new one.

**Changes:**
- `ChatSidebar.tsx` — hide button in both collapsed and expanded sidebar
states when `sessionId` is null
- `MobileDrawer.tsx` — same fix for mobile drawer

---
Co-authored-by: Ubbe <ubbe@users.noreply.github.com>
2026-03-09 22:41:11 +08:00
Otto
eadc68f2a5 feat(frontend/copilot): move microphone button to right side of input box (#12320)
Requested by @olivia-1421

Moves the microphone/recording button from the left-side tools group to
the right side, next to the submit button. The left side is now reserved
for the attachment/upload (plus) button only.

**Before:** `[ 📎 🎤 ] .................. [ ➤ ]`
**After:**  `[ 📎 ] .................. [ 🎤 ➤ ]`

---
Co-authored-by: Olivia <olivia-1421@users.noreply.github.com>

---------

Co-authored-by: Ubbe <hi@ubbe.dev>
Co-authored-by: Lluis Agusti <hi@llu.lu>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-09 18:37:02 +08:00
Reinier van der Leer
19d775c435 Merge commit from fork 2026-03-08 10:25:24 +01:00
Reinier van der Leer
eca7b5e793 Merge commit from fork 2026-03-08 10:24:44 +01:00
Otto
c304a4937a fix(backend): Handle manual run attempts for triggered agents (#12298)
When a webhook-triggered agent is executed directly (e.g. via Copilot)
without actual webhook data, `GraphExecution.from_db()` crashes with
`KeyError: 'payload'` because it does a hard key access on
`exec.input_data["payload"]` for webhook blocks.

This caused 232 Sentry events (AUTOGPT-SERVER-821) and multiple
INCOMPLETE graph executions due to retries.

**Changes:**

1. **Defensive fix in `from_db()`** — use `.get("payload")` instead of
`["payload"]` to handle missing keys gracefully (matches existing
pattern for input blocks using `.get("value")`)

2. **Upfront refusal in `_construct_starting_node_execution_input()`** —
refuse execution of webhook/webhook_manual blocks when no payload is
provided. The check is placed after `nodes_input_masks` application, so
legitimate webhook triggers (which inject payload via
`nodes_input_masks`) pass through fine.

Resolves [SENTRY-1113: Copilot is able to manually initiate runs for
triggered agents (which
fails)](https://linear.app/autogpt/issue/SENTRY-1113/copilot-is-able-to-manually-initiate-runs-for-triggered-agents-which)

---
Co-authored-by: Reinier van der Leer (@Pwuts) <pwuts@agpt.co>
2026-03-06 20:47:51 +00:00
Zamil Majdy
7ead4c040f hotfix(backend/copilot): capture tool results in transcript (#12323)
## Summary
- Fixes tool results not being captured in the CoPilot transcript during
SDK-based streaming
- Adds `transcript_builder.add_user_message()` call with `tool_result`
content block when a `StreamToolOutputAvailable` event is received
- Ensures transcript accurately reflects the full conversation including
tool outputs, which is critical for Langfuse tracing and debugging

## Context
After the transcript refactor in #12318, tool call results from the SDK
streaming loop were not being recorded in the transcript. This meant
Langfuse traces were missing tool outputs, making it hard to debug agent
behavior.

## Test plan
- [ ] Verify CoPilot conversation with tool calls captures tool results
in Langfuse traces
- [ ] Verify transcript includes tool_result content blocks after tool
execution
2026-03-06 18:58:48 +00:00
Zamil Majdy
8cfabcf4fd refactor(backend/copilot): centralize prompt building in prompting.py (#12324)
## Summary

Centralizes all prompt building logic into a new
`backend/copilot/prompting.py` module with clear SDK vs baseline and
local vs E2B distinctions.

### Key Changes

**New `prompting.py` module:**
- `get_sdk_supplement(use_e2b, cwd)` - For SDK mode (NO tool docs -
Claude gets schemas automatically)
- `get_baseline_supplement(use_e2b, cwd)` - For baseline mode (WITH
auto-generated tool docs from TOOL_REGISTRY)
- Handles local/E2B storage differences

**SDK mode (`sdk/service.py`):**
- Removed 165+ lines of duplicate constants
- Now imports and uses `get_sdk_supplement()`
- Cleaner, more maintainable

**Baseline mode (`baseline/service.py`):**
- Now appends `get_baseline_supplement()` to system prompt
- Baseline mode finally gets tool documentation!

**Enhanced tool descriptions:**
- `create_agent`: Added feedback loop workflow (suggested_goal,
clarifying_questions)
- `run_mcp_tool`: Added known server URLs, 2-step workflow, auth
handling

**Tests:**
- Updated to verify SDK excludes tool docs, baseline includes them
- All existing tests pass

### Architecture Benefits

 Single source of truth for prompt supplements
 Clear SDK vs baseline distinction (SDK doesn't need tool docs)
 Clear local vs E2B distinction (storage systems)
 Easy to maintain and update
 Eliminates code duplication

## Test plan

- [x] Unit tests pass (TestPromptSupplement class)
- [x] SDK mode excludes tool documentation
- [x] Baseline mode includes tool documentation
- [x] E2B vs local mode differences handled correctly
2026-03-06 18:56:20 +00:00
Zamil Majdy
7bf407b66c Merge branch 'master' of github.com:Significant-Gravitas/AutoGPT into dev 2026-03-07 02:01:41 +07:00
Abhimanyu Yadav
0f813f1bf9 feat(copilot): Add folder management tools to CoPilot (#12290)
Adds folder management capabilities to the CoPilot, allowing users to
organize agents into folders directly from the chat interface.

<img width="823" height="356" alt="Screenshot 2026-03-05 at 5 26 30 PM"
src="https://github.com/user-attachments/assets/4c55f926-1e71-488f-9eb6-fca87c4ab01b"
/>
<img width="797" height="150" alt="Screenshot 2026-03-05 at 5 28 40 PM"
src="https://github.com/user-attachments/assets/5c9c6f8b-57ac-4122-b17d-b9f091bb7c4e"
/>
<img width="763" height="196" alt="Screenshot 2026-03-05 at 5 28 36 PM"
src="https://github.com/user-attachments/assets/d1b22b5d-921d-44ac-90e8-a5820bb3146d"
/>
<img width="756" height="199" alt="Screenshot 2026-03-05 at 5 30 17 PM"
src="https://github.com/user-attachments/assets/40a59748-f42e-4521-bae0-cc786918a9b5"
/>

### Changes

**Backend -- 6 new CoPilot tools** (`manage_folders.py`):
- `create_folder` -- Create folders with optional parent, icon, and
color
- `list_folders` -- List folder tree or children of a specific folder,
with optional `include_agents` to show agents inside each folder
- `update_folder` -- Rename or change icon/color
- `move_folder` -- Reparent a folder or move to root
- `delete_folder` -- Soft-delete (agents moved to root, not deleted)
- `move_agents_to_folder` -- Bulk-move agents into a folder or back to
root

**Backend -- DatabaseManager RPC registration**:
- Registered all 7 folder DB functions (`create_folder`, `list_folders`,
`get_folder_tree`, `update_folder`, `move_folder`, `delete_folder`,
`bulk_move_agents_to_folder`) in `DatabaseManager` and
`DatabaseManagerAsyncClient` so they work via RPC in the CoPilotExecutor
process
- `manage_folders.py` uses `db_accessors.library_db()` pattern
(consistent with all other copilot tools) instead of direct Prisma
imports

**Backend -- folder_id threading**:
- `create_agent` and `customize_agent` tools accept optional `folder_id`
to save agents directly into a folder
- `save_agent_to_library` -> `create_graph_in_library` ->
`create_library_agent` pipeline passes `folder_id` through
- `create_library_agent` refactored from `asyncio.gather` to sequential
loop to support conditional `folderId` assignment on the main graph only
(not sub-graphs)

**Backend -- system prompt and models**:
- Added folder tool descriptions and usage guidance to Otto's system
prompt
- Added `FolderAgentSummary` model for lightweight agent info in folder
listings
- Added 6 `ResponseType` enum values and corresponding Pydantic response
models (`FolderInfo`, `FolderTreeInfo`, `FolderCreatedResponse`, etc.)

**Frontend -- FolderTool UI component**:
- `FolderTool.tsx` -- Renders folder operations in chat using the
`file-tree` molecule component for tree view, with `FileIcon` for agents
and `FolderIcon` for folders (both `text-neutral-600`)
- `helpers.ts` -- Type guards, output parsing, animation text helpers,
and `FolderAgentSummary` type
- `MessagePartRenderer.tsx` -- Routes 6 folder tool types to
`FolderTool` component
- Flat folder list view shows agents inside `FolderCard` when
`include_agents` is set

**Frontend -- file-tree molecule**:
- Fixed 3 pre-existing lint errors in `file-tree.tsx` (unused `ref`,
`handleSelect`, `className` params)
- Updated tree indicator line color from `bg-neutral-100` to
`bg-neutral-400` for visibility
- Added `file-tree.stories.tsx` with 5 stories: Default, AllExpanded,
FoldersOnly, WithInitialSelection, NoIndicator
- Added `ui/scroll-area.tsx` (dependency of file-tree, was missing from
non-legacy ui folder)

### 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] Create a folder via copilot chat ("create a folder called
Marketing")
  - [x] List folders ("show me my folders")
- [x] List folders with agents ("show me my folders and the agents in
them")
- [x] Update folder name/icon/color ("rename Marketing folder to Sales")
- [x] Move folder to a different parent ("move Sales into the Projects
folder")
  - [x] Delete a folder and verify agents move to root
- [x] Move agents into a folder ("put my newsletter agent in the
Marketing folder")
- [x] Create agent with folder_id ("create a scraper agent and save it
in my Tools folder")
- [x] Verify FolderTool UI renders loading, success, error, and empty
states correctly
- [x] Verify folder tree renders nested folders with file-tree component
- [x] Verify agents appear as FileIcon nodes in tree view when
include_agents is true
  - [x] Verify file-tree storybook stories render correctly
2026-03-06 14:59:03 +00:00
Reinier van der Leer
aa08063939 refactor(backend/db): Improve & clean up Marketplace DB layer & API (#12284)
These changes were part of #12206, but here they are separately for
easier review.
This is all primarily to make the v2 API (#11678) work possible/easier.

### Changes 🏗️

- Fix relations between `Profile`, `StoreListing`, and `AgentGraph`
- Redefine `StoreSubmission` view with more efficient joins (100x
speed-up on dev DB) and more consistent field names
- Clean up query functions in `store/db.py`
- Clean up models in `store/model.py`
- Add missing fields to `StoreAgent` and `StoreSubmission` views
- Rename ambiguous `agent_id` -> `graph_id`
- Clean up API route definitions & docs in `store/routes.py`
  - Make routes more consistent
- Avoid collision edge-case between `/agents/{username}/{agent_name}`
and `/agents/{store_listing_version_id}/*`
- Replace all usages of legacy `BackendAPI` for store endpoints with
generated client
- Remove scope requirements on public store endpoints in v1 external API

### 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] Test all Marketplace views (including admin views)
    - [x] Download an agent from the marketplace
  - [x] Submit an agent to the Marketplace
  - [x] Approve/reject Marketplace submission
2026-03-06 14:38:12 +00:00
Zamil Majdy
bde6a4c0df Merge branch 'master' of github.com:Significant-Gravitas/AutoGPT into dev
# Conflicts:
#	autogpt_platform/backend/backend/copilot/sdk/service.py
2026-03-06 21:07:37 +07:00
Zamil Majdy
d56452898a hotfix(backend/copilot): refactor transcript to SDK-based atomic full-context model (#12318)
## Summary

Major refactor to eliminate CLI transcript race conditions and simplify
the codebase by building transcripts directly from SDK messages instead
of reading CLI files.

## Problem

The previous approach had race conditions:
- SDK reads CLI transcript file during stop hook
- CLI may not have finished writing → incomplete transcript
- Complex merge logic to detect and fix incomplete writes
- ~200 lines of synthetic entry detection and merge code

## Solution

**Atomic Full-Context Transcript Model:**
- Build transcript from SDK messages during streaming
(`TranscriptBuilder`)
- Each upload REPLACES the previous transcript entirely (atomic)
- No CLI file reading → no race conditions
- Eliminates all merge complexity

## Key Changes

### Core Refactor
- **NEW**: `transcript_builder.py` - Build JSONL from SDK messages
during streaming
- **SIMPLIFIED**: `transcript.py` - Removed merge logic, simplified
upload/download
- **SIMPLIFIED**: `service.py` - Use TranscriptBuilder, removed stop
hook callback
- **CLEANED**: `security_hooks.py` - Removed `on_stop` parameter

### Performance & Code Quality
- **orjson migration**: Use `backend.util.json` (2-3x faster than
stdlib)
- Added `fallback` parameter to `json.loads()` for cleaner error
handling
- Moved SDK imports to top-level per code style guidelines

### Bug Fixes
- Fixed garbage collection bug in background task handling
- Fixed double upload bug in timeout handling  
- Downgraded PII-risk logging from WARNING to DEBUG
- Added 30s timeout to prevent session lock hang

## Code Removed (~200 lines)

- `merge_with_previous_transcript()` - No longer needed
- `read_transcript_file()` - No longer needed
- `CapturedTranscript` dataclass - No longer needed
- `_on_stop()` callback - No longer needed
- Synthetic entry detection logic - No longer needed
- Manual append/merge logic in finally block - No longer needed

## Testing

-  All transcript tests passing (24/24)
-  Verified with real session logs showing proper transcript growth
-  Verified with Langfuse traces showing proper turn tracking (1-8)

## Transcript Growth Pattern

From session logs:
- **Turn 1**: 2 entries (initial)
- **Turn 2**: 5 entries (+3), 2257B uploaded
- **Turn N**: ~2N entries (linear growth)

Each upload is the **complete atomic state** - always REPLACES, never
incremental.

## Files Changed

```
backend/copilot/sdk/transcript_builder.py (NEW)   | +140 lines
backend/copilot/sdk/transcript.py                  | -198, +125 lines  
backend/copilot/sdk/service.py                     | -214, +160 lines
backend/copilot/sdk/security_hooks.py              | -33, +10 lines
backend/copilot/sdk/transcript_test.py             | -85, +36 lines
backend/util/json.py                               | +45 lines
```

**Net result**: -200 lines, more reliable, faster JSON operations.

## Migration Notes

This is a **breaking change** for any code that:
- Directly calls `merge_with_previous_transcript()` or
`read_transcript_file()`
- Relies on incremental transcript uploads
- Expects stop hook callbacks

All internal usage has been updated.

---

@ntindle - Tagging for autogpt-reviewer
2026-03-06 21:03:49 +07:00
Ubbe
7507240177 feat(copilot): collapse repeated tool calls and fix stream stuck on completion (#12282)
## Summary
- **Frontend:** Group consecutive completed generic tool parts into
collapsible summary rows with a "Reasoning" collapse for finalized
messages. Merge consecutive assistant messages on hydration to avoid
split bubbles. Extract GenericTool helpers. Add `reconnectExhausted`
state and a brief delay before refetching session to reduce stale
`active_stream` reconnect cycles.
- **Backend:** Make transcript upload fire-and-forget instead of
blocking the generator exit. The 30s upload timeout in
`_try_upload_transcript` was delaying `mark_session_completed()`,
keeping the SSE stream alive with only heartbeats after the LLM had
finished — causing the UI to stay stuck in "streaming" state.

## Test plan
- [ ] Send a message in Copilot that triggers multiple tool calls —
verify they collapse into a grouped summary row once completed
- [ ] Verify the final text response appears below the collapsed
reasoning section
- [ ] Confirm the stream properly closes after the agent finishes (no
stuck "Stop" button)
- [ ] Refresh mid-stream and verify reconnection works correctly
- [ ] Click Stop during streaming — verify the UI becomes responsive
immediately

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

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-06 21:21:59 +08:00
Abhimanyu Yadav
d7c3f5b8fc fix(frontend): bypass Next.js proxy for file uploads to fix 413 error (#12315)
## Summary
- File uploads routed through the Next.js API proxy (`/api/proxy/...`)
fail with HTTP 413 for files >4.5MB due to Vercel's serverless function
body size limit
- Created shared `uploadFileDirect` utility (`src/lib/direct-upload.ts`)
that uploads files directly from the browser to the Python backend,
bypassing the proxy entirely
- Updated `useWorkspaceUpload` to use direct upload instead of the
generated hook (which went through the proxy)
- Deduplicated the copilot page's inline upload logic to use the same
shared utility

## Changes 🏗️
- **New**: `src/lib/direct-upload.ts` — shared utility for
direct-to-backend file uploads (up to 256MB)
- **Updated**: `useWorkspaceUpload.ts` — replaced proxy-based generated
hook with `uploadFileDirect`
- **Updated**: `useCopilotPage.ts` — replaced inline upload logic with
shared `uploadFileDirect`, removed unused imports

## 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] Upload a file >5MB via workspace file input (e.g. in agent
builder) — should succeed without 413
  - [x] Upload a file >5MB via copilot chat — should succeed without 413
  - [x] Upload a small file (<1MB) via both paths — should still work
  - [x] Verify file delete still works from workspace file input
2026-03-06 12:20:18 +00:00
Otto
3e108a813a fix(backend): Use db_manager for workspace in add_graph_execution (#12312)
When `add_graph_execution` is called from a context where the global
Prisma client isn't connected (e.g. CoPilot tools, external API), the
call to `get_or_create_workspace(user_id)` crashes with
`ClientNotConnectedError` because it directly accesses
`UserWorkspace.prisma()`.

The fix adds `workspace_db` to the existing `if prisma.is_connected()`
fallback pattern, consistent with how all other DB calls in the function
already work.

**Sentry:** AUTOGPT-SERVER-83T (and ~15 related issues going back to Jan
2026)

---
Co-authored-by: Reinier van der Leer (@Pwuts) <pwuts@agpt.co>

Co-authored-by: Reinier van der Leer (@Pwuts) <pwuts@agpt.co>
2026-03-06 08:48:15 +01:00
Krzysztof Czerwinski
08c49a78f8 feat(copilot): UX improvements (#12258)
CoPilot conversation UX improvements (SECRT-2055):

1. **Rename conversations** — Inline rename via the session dropdown
menu. New `PATCH /sessions/{session_id}/title` endpoint with server-side
validation (rejects blank/whitespace-only titles, normalizes
whitespace). Pressing Enter or clicking away submits; Escape cancels
without submitting.

2. **New Chat button moved to top & sticky** — The 'New Chat' button is
now at the top of the sidebar (under 'Your chats') instead of the
footer, and stays fixed — only the session list below it scrolls. A
subtle shadow separator mirrors the original footer style.

3. **Auto-generated title appears live** — After the first message in a
new chat, the sidebar polls for the backend-generated title and animates
it in smoothly once available. The backend also guards against
auto-title overwriting a user-set title.

4. **External Link popup redesign** — Replaced the CSS-hacked external
link confirmation dialog with a proper AutoGPT `Dialog` component using
the design system (`Button`, `Text`, `Dialog`). Removed the old
`globals.css` workaround.

<img width="321" height="263" alt="Screenshot 2026-03-03 at 6 31 50 pm"
src="https://github.com/user-attachments/assets/3cdd1c6f-cca6-4f16-8165-15a1dc2d53f7"
/>

<img width="374" height="74" alt="Screenshot 2026-03-02 at 6 39 07 pm"
src="https://github.com/user-attachments/assets/6f9fc953-5fa7-4469-9eab-7074e7604519"
/>

<img width="548" height="293" alt="Screenshot 2026-03-02 at 6 36 28 pm"
src="https://github.com/user-attachments/assets/0f34683b-7281-4826-ac6f-ac7926e67854"
/>

### Changes 🏗️

**Backend:**
- `routes.py`: Added `PATCH /sessions/{session_id}/title` endpoint with
`UpdateSessionTitleRequest` Pydantic model — validates non-blank title,
normalizes whitespace, returns 404 vs 500 correctly
- `routes_test.py`: New test file — 7 test cases covering success,
whitespace trimming, blank rejection (422), not found (404), internal
failure (500)
- `service.py`: Auto-title generation now checks if a user-set title
already exists before overwriting
- `openapi.json`: Updated with new endpoint schema

**Frontend:**
- `ChatSidebar.tsx`: Inline rename (Enter/blur submits, Escape cancels
via ref flag); "New Chat" button sticky at top with shadow separator;
session title animates when auto-generated title appears
(`AnimatePresence`)
- `useCopilotPage.ts`: Polls for auto-generated title after stream ends,
stops as soon as title appears in cache
- `MobileDrawer.tsx`: Updated to match sidebar layout changes
- `DeleteChatDialog.tsx`: Removed redundant `onClose` prop (controlled
Dialog already handles close)
- `message.tsx`: Added `ExternalLinkModal` using AutoGPT design system;
removed redundant `onClose` prop
- `globals.css`: Removed old CSS hack for external link modal

### 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] Create a new chat, send a message — verify auto-generated title
appears in sidebar without refresh
- [x] Rename a chat via dropdown — Enter submits, Escape reverts, blank
title rejected
- [x] Rename a chat, then send another message — verify user title is
not overwritten by auto-title
- [x] With many chats, scroll the sidebar — verify "New Chat" button
stays fixed at top
- [x] Click an external link in a message — verify the new dialog
appears with AutoGPT styling

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-06 06:01:41 +00:00
Bently
5d56548e6b fix(frontend): prevent crash on /library with 401 error from pagination helper (#12292)
## Changes
Fixes crash on `/library` page when backend returns a 401 authentication
error.

### Problem

When the backend returns a 401 error, React Query still calls
`getNextPageParam` with the error response. The response doesn't have
the expected pagination structure, causing `pagination` to be
`undefined`. The code then crashes trying
 to access `pagination.current_page`.

Error:
TypeError: Cannot read properties of undefined (reading 'current_page')
    at Object.getNextPageParam

### Solution

Added a defensive null check in `getPaginationNextPageNumber()` to
handle cases where `pagination` is undefined:

```typescript
const { pagination } = lastPage.data;
if (!pagination) return undefined;
```
When undefined is returned, React Query interprets this as "no next page
available" and gracefully stops pagination instead of crashing.

Testing

- Manual testing: Verify /library page handles 401 errors without
crashing
- The fix is defensive and doesn't change behavior for successful
responses

Related Issues

Closes OPEN-2684
2026-03-05 19:52:36 +00:00
Otto
6ecf55d214 fix(frontend): fix 'Open link' button text color to white for contrast (#12304)
Requested by @ntindle

The Streamdown external link safety modal's "Open link" button had dark
text (`color: black`) on a dark background, making it unreadable.
Changed to `color: white` for proper contrast per our design system.

**File:** `autogpt_platform/frontend/src/app/globals.css`

Resolves SECRT-2061

---
Co-authored-by: Nick Tindle (@ntindle)
2026-03-05 19:50:39 +00:00
Bently
7c8c7bf395 feat(llm): add Claude Sonnet 4.6 model (#12158)
## Summary
Adds Claude Sonnet 4.6 (`claude-sonnet-4-6`) to the platform.

## Model Details (from [Anthropic
docs](https://www.anthropic.com/news/claude-sonnet-4-6))
- **API ID:** `claude-sonnet-4-6`
- **Pricing:** $3 / input MTok, $15 / output MTok (same as Sonnet 4.5)
- **Context window:** 200K tokens (1M beta)
- **Max output:** 64K tokens
- **Knowledge cutoff:** Aug 2025 (reliable), Jan 2026 (training data)

## Changes
- Added `CLAUDE_4_6_SONNET` to `LlmModel` enum
- Added metadata entry with correct context/output limits
- Updated Stagehand to use Sonnet 4.6 (better for browser automation
tasks)

## Why
Sonnet 4.6 brings major improvements in coding, computer use, and
reasoning. Developers with early access often prefer it to even Opus
4.5.

---------

Co-authored-by: Nicholas Tindle <nicholas.tindle@agpt.co>
2026-03-05 19:36:56 +00:00
Zamil Majdy
0b9e0665dd Merge branch 'dev' of github.com:Significant-Gravitas/AutoGPT 2026-03-06 02:32:36 +07:00
Zamil Majdy
be18436e8f Merge branch 'master' of github.com:Significant-Gravitas/AutoGPT into dev 2026-03-06 02:31:40 +07:00
Zamil Majdy
f6f268a1f0 Merge branch 'dev' of github.com:Significant-Gravitas/AutoGPT into HEAD 2026-03-06 02:29:56 +07:00
Zamil Majdy
ea0333c1fc fix(copilot): always upload transcript instead of size-based skip (#12303)
## Summary

Fixes copilot sessions "forgetting" previous turns due to stale
transcript storage.

**Root cause:** The transcript upload logic used byte size comparison
(`existing >= new → skip`) to prevent overwriting newer transcripts with
older ones. However, with `--resume` the CLI compacts old tool results,
so newer transcripts can have **fewer bytes** despite containing **more
conversation events**. This caused the stored transcript to freeze at
whatever the largest historical upload was — every subsequent turn
downloaded the same stale transcript and the agent lost context of
recent turns.

**Evidence from prod session `41a3814c`:**
- Stored transcript: 764KB (frozen, never updated)
- Turn 1 output: 379KB (75 lines) → upload skipped (764KB >= 379KB)
- Turn 2 output: 422KB (71 lines) → upload skipped (764KB >= 422KB)
- Turn 3 output: **empty** → upload skipped
- Agent resumed from the same stale 764KB transcript every turn, losing
context of the PR it created

**Fix:** Remove the size comparison entirely. The executor holds a
cluster lock per session, so concurrent uploads cannot race. Just always
overwrite with the latest transcript.

## Test plan
- [x] `poetry run pytest backend/copilot/sdk/transcript_test.py` — 25/25
pass
- [x] All pre-commit hooks pass
- [ ] After deploy: verify multi-turn sessions retain context across
turns
2026-03-06 02:26:52 +07:00
Zamil Majdy
21c705af6e fix(backend/copilot): prevent title update from overwriting session messages (#12302)
### Changes 🏗️

Fixes a race condition in `update_session_title()` where the background
title generation task could overwrite the Redis session cache with a
stale snapshot, causing the copilot to "forget" its previous turns.

**Root cause:** `update_session_title()` performs a read-modify-write on
the Redis cache (read full session → set title → write back). Meanwhile,
`upsert_chat_session()` writes a newer version with more messages during
streaming. If the title task reads early (e.g., 34 messages) and writes
late (after streaming persisted 101 messages), the stale 34-message
version overwrites the 101-message version. When the next message lands
on a different pod, it loads the stale session from Redis.

**Fix:** Replace the read-modify-write with a simple cache invalidation
(`invalidate_session_cache`). The title is already updated in the DB;
the next access just reloads from DB with the correct title and
messages. No locks, no deserialization of the full session blob, no risk
of stale overwrites.

**Evidence from prod logs (session `41a3814c`):**
- Pod `tm2jb` persisted session with 101 messages
- Pod `phflm` loaded session from Redis cache with only 35 messages (66
messages lost)
- The title background task ran between these events, overwriting the
cache

### 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/model_test.py` — 15/15 pass
  - [x] All pre-commit hooks pass (ruff, black, isort, pyright)
- [ ] After deploy: verify long sessions no longer lose context on
multi-pod setups
2026-03-05 18:49:41 +00:00
Zamil Majdy
a576be9db2 fix(backend): install agent-browser + Chromium in Docker image (#12301)
The Copilot browser tool (`browser_navigate`, `browser_act`,
`browser_screenshot`) has been broken on dev because `agent-browser` CLI
+ Chromium were never installed in the backend Docker image.

### Changes 🏗️

- Added `npx playwright install-deps chromium` to install Chromium
runtime libraries (libnss3, libatk, etc.)
- Added `npm install -g agent-browser` to install the CLI
- Added `agent-browser install` to download the Chromium binary
- Layer is placed after existing COPY-from-builder lines to preserve
Docker cache ordering

### Root cause

Every `browser_navigate` call fails with:
```
WARNING  [browser_navigate] open failed for <url>: agent-browser is not installed
(run: npm install -g agent-browser && agent-browser install).
```
The error originates from `FileNotFoundError` in `agent_browser.py:101`
when the subprocess tries to execute the `agent-browser` binary which
doesn't exist in the container.

### 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 `agent-browser` binary is missing from current dev pod
via `kubectl logs`
- [x] Confirmed session `01eeac29-5a7` shows repeated failures for all
URLs
- [ ] After deploy: verify browser_navigate works in a Copilot session
on dev

#### 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**)
2026-03-05 18:44:55 +00:00
dependabot[bot]
5e90585f10 chore(deps): bump crazy-max/ghaction-github-runtime from 3 to 4 (#12262)
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2026-03-05 15:59:06 +00:00
Zamil Majdy
3e22a0e786 fix(copilot): pin claude-agent-sdk to 0.1.45 to fix tool_reference content block validation error (#12294)
Requested by @majdyz

## Problem

CoPilot throws `400 Invalid Anthropic Messages API request` errors on
first message, both locally and on Dev.

## Root Cause

The CLI's built-in `ToolSearch` tool returns `tool_reference` content
blocks (`{"type": "tool_reference", "tool_name":
"mcp__copilot__find_block"}`). When the CLI constructs the next
Anthropic API request, it passes these blocks as-is in the
`tool_result.content` field. However, the Anthropic Messages API only
accepts `text` and `image` content block types in tool results.

This causes a Zod validation error:
```
messages[3].content[0].content: Invalid input: expected string, received array
```

The error only manifests when using **OpenRouter** (`ANTHROPIC_BASE_URL`
set) because the Anthropic TypeScript SDK performs stricter client-side
Zod validation in that code path vs the subscription auth path.

PR #12288 bumped `claude-agent-sdk` from `0.1.39` to `^0.1.46`, which
upgraded the bundled Claude CLI from `v2.1.49` to `v2.1.69` where this
issue was introduced.

## Fix

Pin to `0.1.45` which has a CLI version that doesn't produce
`tool_reference` content blocks in tool results.

## Testing
- CoPilot first message should work without 400 errors via OpenRouter
- SDK compat tests should still pass
2026-03-05 13:12:26 +00:00
Ubbe
6abe39b33a feat(frontend/copilot): add per-turn work-done summary stats (#12257)
## Summary
- Adds per-turn work-done counters (e.g. "3 searches", "1 agent run")
shown as plain text on the final assistant message of each
user/assistant interaction pair
- Counters aggregate tool calls by category (searches, agents run,
blocks run, agents created/edited, agents scheduled)
- Copy and TTS actions now appear only on the final assistant message
per turn, with text aggregated from all assistant messages in that turn
- Removes the global JobStatsBar above the chat input

Resolves: SECRT-2026

## Test plan
- [ ] Work-done counters appear only on the last assistant message of
each turn (not on intermediate assistant messages)
- [ ] Counters increment correctly as tool call parts appear in messages
- [ ] Internal operations (add_understanding, search_docs, get_doc_page,
find_block) are NOT counted
- [ ] Max 3 counter categories shown, sorted by volume
- [ ] Copy/TTS actions appear only on the final assistant message per
turn
- [ ] Copy/TTS aggregate text from all assistant messages in the turn
- [ ] No counters or actions shown while streaming is still in progress
- [ ] No type errors, lint errors, or format issues introduced

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

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-05 19:32:48 +08:00
Zamil Majdy
476cf1c601 feat(copilot): support Claude Code subscription auth for SDK mode (#12288)
## Summary

- Adds `CHAT_USE_CLAUDE_CODE_SUBSCRIPTION` config flag to let the
copilot SDK path use the Claude CLI's own subscription auth (from
`claude login`) instead of API keys
- When enabled, the SDK subprocess inherits CLI credentials — no
`ANTHROPIC_BASE_URL`/`AUTH_TOKEN` override is injected
- Forces SDK mode regardless of LaunchDarkly flag (baseline path uses
`openai.AsyncOpenAI` which requires an API key)
- Validates CLI installation on first use with clear error messages

## Setup

```bash
npm install -g @anthropic-ai/claude-code
claude login
# then set in .env:
CHAT_USE_CLAUDE_CODE_SUBSCRIPTION=true
```

## Changes

| File | Change |
|------|--------|
| `copilot/config.py` | New `use_claude_code_subscription` field + env
var validator |
| `copilot/sdk/service.py` | `_validate_claude_code_subscription()` +
`_build_sdk_env()` early-return + fail-fast guard |
| `copilot/executor/processor.py` | Force SDK mode via short-circuit
`or` |

## Test plan

- [ ] Set `CHAT_USE_CLAUDE_CODE_SUBSCRIPTION=true`, unset all API keys
- [ ] Run `claude login` on the host
- [ ] Start backend, send a copilot message — verify SDK subprocess uses
CLI auth
- [ ] Verify existing OpenRouter/API key flows still work (no
regression)
2026-03-05 09:55:35 +00:00
Zamil Majdy
25022f2d1e fix(copilot): handle empty tool_call arguments in baseline path (#12289)
## Summary

Handle empty/None `tool_call.arguments` in the baseline copilot path
that cause OpenRouter 400 errors when converting to Anthropic format.

## Changes

**`backend/copilot/baseline/service.py`**:
- Default empty `tc["arguments"]` to `"{}"` to prevent OpenRouter from
failing on empty tool arguments during format conversion.

## Test plan

- [x] Existing baseline tests pass
- [ ] Verify on staging: trigger a tool call in baseline mode and
confirm normal flow works
2026-03-05 09:53:05 +00:00
Zamil Majdy
ce1675cfc7 feat(copilot): add Langfuse tracing to baseline LLM path (#12281)
## Summary
Depends on #12276 (baseline code).

- Swap shared OpenAI client to `langfuse.openai.AsyncOpenAI` —
auto-captures all LLM calls (token usage, latency, model, prompts) as
Langfuse generations when configured
- Add `propagate_attributes()` context in baseline streaming for
`user_id`/`session_id` attribution, matching the SDK path's OTEL tracing
- No-op when Langfuse is not configured — `langfuse.openai.AsyncOpenAI`
falls back to standard `openai.AsyncOpenAI` behavior

## Observability parity

| Aspect | SDK path | Baseline path (after this PR) |
|--------|----------|-------------------------------|
| LLM call tracing | OTEL via `configure_claude_agent_sdk()` |
`langfuse.openai.AsyncOpenAI` auto-instrumentation |
| User/session context | `propagate_attributes()` |
`propagate_attributes()` |
| Langfuse prompts | Shared `_build_system_prompt()` | Shared
`_build_system_prompt()` |
| Token/cost tracking | Via OTEL spans | Via Langfuse generation objects
|

## Test plan
- [x] `poetry run format` passes (pyright, ruff, black, isort)
- [ ] Verify Langfuse traces appear for baseline path with
`CHAT_USE_CLAUDE_AGENT_SDK=false`
- [ ] Verify SDK path tracing is unaffected
2026-03-05 09:51:16 +00:00
Otto
3d0ede9f34 feat(backend/copilot): attach uploaded images and PDFs as multimodal vision blocks (#12273)
Requested by @majdyz

When users upload images or PDFs to CoPilot, the AI couldn't see the
content because the CLI's Zod validator rejects large base64 in MCP tool
results and even small images were misidentified (the CLI silently drops
or corrupts image content blocks in tool results).

## Approach

Embed uploaded images directly as **vision content blocks** in the user
message via `client._transport.write()`. The SDK's `client.query()` only
accepts string content, so we bypass it for multimodal messages —
writing a properly structured user message with `[...image_blocks,
{"type": "text", "text": query}]` directly to the transport. This
ensures the CLI binary receives images as native vision blocks, matching
how the Anthropic API handles multimodal input.

For binary files accessed via workspace tools at runtime, we save them
to the SDK's ephemeral working directory (`sdk_cwd`) and return a file
path for the CLI's built-in `Read` tool to handle natively.

## Changes

### Vision content blocks for attached files — `service.py`
- `_prepare_file_attachments` downloads workspace files before the
query, converts images to base64 vision blocks (`{"type": "image",
"source": {"type": "base64", ...}}`)
- When vision blocks are present, writes multimodal user message
directly to `client._transport` instead of using `client.query()`
- Non-image files (PDFs, text) are saved to `sdk_cwd` with a hint to use
the Read tool

### File-path based access for workspace tools — `workspace_files.py`
- `read_workspace_file` saves binary files to `sdk_cwd` instead of
returning base64, returning a path for the Read tool

### SDK context for ephemeral directory — `tool_adapter.py`
- Added `sdk_cwd` context variable so workspace tools can access the
ephemeral directory
- Removed inline base64 multimodal block machinery
(`_extract_content_block`, `_strip_base64_from_text`, `_BLOCK_BUILDERS`,
etc.)

### Frontend — rendering improvements
- `MessageAttachments.tsx` — uses `OutputRenderers` system
(`globalRegistry` + `OutputItem`) for image/video preview rendering
instead of custom components
- `GenericTool.tsx` — uses `OutputRenderers` system for inline image
rendering of base64 content
- `routes.py` — returns 409 for duplicate workspace filenames

### Tests
- `tool_adapter_test.py` — removed multimodal extraction/stripping
tests, added `get_sdk_cwd` tests
- `service_test.py` — rewritten for `_prepare_file_attachments` with
file-on-disk assertions

Closes OPEN-3022

---------

Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
2026-03-05 09:09:59 +00:00
Ubbe
5474f7c495 feat(frontend/copilot): add output action buttons (upvote, downvote) with Langfuse feedback (#12260)
## Summary
- Feedback is submitted to the backend Langfuse integration
(`/api/chat/sessions/{id}/feedback`) for observability
- Downvote opens a modal dialog for optional detailed feedback text (max
2000 chars)
- Buttons are hidden during streaming and appear on hover; once feedback
is selected they stay visible

## Changes
- **`AssistantMessageActions.tsx`** (new): Renders copy (CopySimple),
thumbs-up, and thumbs-down buttons using `MessageAction` from the design
system. Visual states for selected feedback (green for upvote, red for
downvote with filled icons).
- **`FeedbackModal.tsx`** (new): Dialog with a textarea for optional
downvote comment, using the design system `Dialog` component.
- **`useMessageFeedback.ts`** (new): Hook managing per-message feedback
state and backend submission via `POST
/api/chat/sessions/{id}/feedback`.
- **`ChatMessagesContainer.tsx`** (modified): Renders
`AssistantMessageActions` after `MessageContent` for assistant messages
when not streaming.
- **`ChatContainer.tsx`** (modified): Passes `sessionID` prop through to
`ChatMessagesContainer`.

## Test plan
- [ ] Verify action buttons appear on hover over assistant messages
- [ ] Verify buttons are hidden during active streaming
- [ ] Click copy button → text copied to clipboard, success toast shown
- [ ] Click upvote → green highlight, "Thank you" toast, button locked
- [ ] Click downvote → red highlight, feedback modal opens
- [ ] Submit feedback modal with/without comment → modal closes,
feedback sent
- [ ] Cancel feedback modal → modal closes, downvote stays locked
- [ ] Verify feedback POST reaches `/api/chat/sessions/{id}/feedback`

### Linear issue
Closes SECRT-2051

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

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-05 17:01:05 +08:00
Abhimanyu Yadav
f1b771b7ee feat(platform): switch builder file inputs from base64 to workspace uploads (#12226)
## Summary

Builder node file inputs were stored as base64 data URIs directly in
graph JSON, bloating saves and causing lag. This PR uploads files to the
existing workspace system and stores lightweight `workspace://`
references instead.

## What changed

- **Upload**: When a user picks a file in a builder node input, it gets
uploaded to workspace storage and the graph stores a small
`workspace://file-id#mime/type` URI instead of a huge base64 string.

- **Delete**: When a user clears a file input, the workspace file is
soft-deleted from storage so it doesn't leave orphaned files behind.

- **Execution**: Wired up `workspace_id` on `ExecutionContext` so blocks
can resolve `workspace://` URIs during graph runs. `store_media_file()`
already knew how to handle them.

- **Output rendering**: Added a renderer that displays `workspace://`
URIs as images, videos, audio players, or download cards in node output.

- **Proxy fix**: Removed a `Content-Type: text/plain` override on
multipart form responses that was breaking the generated hooks' response
parsing.

Existing graphs with base64 `data:` URIs continue to work — no migration
needed.

## Test plan

- [x] Upload file in builder → spinner shows, completes, file label
appears
- [x] Save/reload graph → `workspace://` URI persists, not base64
- [x] Clear file input → workspace file is deleted
- [x] Run graph → blocks resolve `workspace://` files correctly
- [x] Output renders images/video/audio from `workspace://` URIs
- [x] Old graphs with base64 still work

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-05 08:38:18 +00:00
Otto
aa7a2f0a48 hotfix(frontend/signup): Add missing createUser() call in password signup (#12287)
Requested by @0ubbe

Password signup was missing the backend `createUser()` call that the
OAuth callback flow already had. This caused `getOnboardingStatus()` to
fail/hang for new users whose backend record didn't exist yet, resulting
in an infinite spinner after account creation.

## Root Cause

| Flow | createUser() | getOnboardingStatus() | Result |
|------|-------------|----------------------|--------|
| OAuth signup |  Called |  Works | Redirects correctly |
| Password signup |  Missing |  Fails/hangs | Infinite spinner |

## Fix

Adds `createUser()` call in `signup/actions.ts` after session is set,
before onboarding status check — matching the OAuth callback pattern.
Includes error handling with Sentry reporting.

## Testing

- Create a new password account → should redirect without spinner
- OAuth signup unaffected (no changes to that flow)

Fixes OPEN-3023

---------

Co-authored-by: Lluis Agusti <hi@llu.lu>
2026-03-05 16:11:51 +08:00
Nicholas Tindle
3722d05b9b fix(frontend/builder): make Google Drive file inputs chainable (#12274)
Resolves: OPEN-3018

Google Drive picker fields on INPUT blocks were missing connection
handles, making them non-chainable in the new builder.

### Changes 🏗️

- **Render `TitleFieldTemplate` with `InputNodeHandle`** — uses
`getHandleId()` with `fieldPathId.$id` (which correctly resolves to e.g.
`agpt_%_spreadsheet`), fixing the previous `_@_` handle error caused by
using `idSchema.$id` (undefined for custom RJSF FieldProps)
- **Override `showHandles: !!nodeId`** in uiOptions — the INPUT block's
`generate-ui-schema.ts` sets `showHandles: false`, but Google Drive
fields need handles to be chainable
- **Hide picker content when handle is connected** — uses
`useEdgeStore.isInputConnected()` to detect wired connections and
conditionally hides the picker/placeholder UI

### 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] Add a Google Drive file input block to a graph in the new builder
  - [x] Verify the connection handle appears on the input
  - [x] Connect another block's output to the Google Drive input handle
- [x] Verify the picker UI hides when connected and reappears when
disconnected
- [x] Verify the Google Drive picker still works normally on non-INPUT
block nodes

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

<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> **Medium Risk**
> Changes input-handle ID generation and conditional rendering for
Google Drive fields in the builder; regressions could break edge
connections or hide the picker unexpectedly on some nodes.
> 
> **Overview**
> Google Drive picker fields now render a proper RJSF
`TitleFieldTemplate` (and thus input handles) using a computed
`handleId` derived from `fieldPathId.$id`, and force `showHandles` on
when a `nodeId` is present.
> 
> The picker/placeholder UI is now conditionally hidden when
`useEdgeStore.isInputConnected()` reports the input handle is connected,
preventing duplicate input UI when the value comes from an upstream
node.
> 
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
1f1df53a38. 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 <noreply@anthropic.com>
Co-authored-by: abhi1992002 <abhimanyu1992002@gmail.com>
Co-authored-by: Abhimanyu Yadav <122007096+Abhi1992002@users.noreply.github.com>
2026-03-05 04:28:01 +00:00
Zamil Majdy
592830ce9b feat(copilot): persist large tool outputs to workspace with retrieval instructions (#12279)
## Summary
- Large tool outputs (>80K chars) are now persisted to session workspace
storage before truncation, preventing permanent data loss
- Truncated output includes a head preview (50K chars) with clear
retrieval instructions referencing `read_workspace_file` with
offset/length
- Added `offset` and `length` parameters to `ReadWorkspaceFileTool` for
paginated reads of large files without re-triggering truncation

## Problem
Tool outputs exceeding 100K chars were permanently lost — truncated by
`StreamToolOutputAvailable.model_post_init` using middle-out truncation.
The model had no way to retrieve the full output later, causing
recursive read loops where the agent repeatedly tries to re-read
truncated data.

## Solution
1. **`BaseTool.execute()`** — When output exceeds 80K chars, persist
full output to workspace at `tool-outputs/{tool_call_id}.json`, then
replace with a head preview wrapped in `<tool-output-truncated>` tags
containing retrieval instructions
2. **`ReadWorkspaceFileTool`** — New `offset`/`length` parameters enable
paginated reads so the agent can fetch slices without re-triggering
truncation
3. **Graceful fallback** — If workspace write fails, returns raw output
unchanged for existing truncation to handle

## Test plan
- [x] `base_test.py`: 5 tests covering persist+preview, fallback on
error, small output passthrough, large output persistence, anonymous
user skip
- [x] `workspace_files_test.py`: Ranged read test covering offset+length
slice, offset-only, offset beyond file length
- [ ] CI passes
- [ ] Review comments addressed
2026-03-05 00:50:01 +00:00
Zamil Majdy
6cc680f71c feat(copilot): improve SDK loading time (#12280)
## Summary
- Skip CLI version check at worker init (saves ~300ms/request)
- Pre-warm bundled CLI binary at startup to warm OS page caches (~500ms
saved on first request per worker)
- Parallelize E2B setup, system prompt fetch, and transcript download
with `asyncio.gather()` (saves ~200-500ms)
- Enable Langfuse prompt caching with configurable TTL (default 300s)

## Test plan
- [ ] `poetry run pytest backend/copilot/sdk/service_test.py -s -vvv`
- [ ] Manual: send copilot messages via SDK path, verify resume still
works on multi-turn
- [ ] Check executor logs for "CLI pre-warm done" messages
2026-03-05 00:49:14 +00:00
Otto
b342bfa3ba fix(frontend): revalidate layout after email/password login (#12285)
Requested by @ntindle

After logging in with email/password, the page navigates but renders a
blank/unauthenticated state (just logo + cookie banner). A manual page
refresh fixes it.

The `login` server action calls `signInWithPassword()` server-side but
doesn't call `revalidatePath()`, so Next.js serves cached RSC payloads
that don't reflect the new auth state. The OAuth callback route already
does this correctly.

**Fix:** Add `revalidatePath(next, "layout")` after successful login,
matching the OAuth callback pattern.

Closes SECRT-2059
2026-03-04 22:25:48 +00:00
Zamil Majdy
0215332386 feat(copilot): remove legacy copilot, add baseline non-SDK mode with tool calling (#12276)
## Summary
- Remove ~1200 lines of broken/unmaintained non-SDK copilot streaming
code (retry logic, parallel tool calls, context window management)
- Add `stream_chat_completion_baseline()` as a clean fallback LLM path
with full tool-calling support when `CHAT_USE_CLAUDE_AGENT_SDK=false`
(e.g. when Anthropic is down)
- Baseline reuses the same shared `TOOL_REGISTRY`,
`get_available_tools()`, and `execute_tool()` as the SDK path
- Move baseline code to dedicated `baseline/` folder (mirrors `sdk/`
structure)
- Clean up SDK service: remove unused params, fix model/env resolution,
fix stream error persistence
- Clean up config: remove `max_retries`, `thinking_enabled` fields
(non-SDK only)

## Changes
| File | Action |
|------|--------|
| `backend/copilot/baseline/__init__.py` | New — package export |
| `backend/copilot/baseline/service.py` | New — baseline streaming with
tool-call loop |
| `backend/copilot/baseline/service_test.py` | New — multi-turn keyword
recall test |
| `backend/copilot/service.py` | Remove ~1200 lines of legacy code, keep
shared helpers only |
| `backend/copilot/executor/processor.py` | Simplify branching to SDK vs
baseline |
| `backend/copilot/sdk/service.py` | Remove unused params, fix model/env
separation, fix stream error persistence |
| `backend/copilot/config.py` | Remove `max_retries`, `thinking_enabled`
|
| `backend/copilot/service_test.py` | Keep SDK test only (baseline test
moved) |
| `backend/copilot/parallel_tool_calls_test.py` | Deleted (tested
removed code) |

## Test plan
- [x] `poetry run format` passes
- [x] CI passes (all 3 Python versions, types, CodeQL)
- [ ] SDK path works unchanged in production
- [x] Baseline path (`CHAT_USE_CLAUDE_AGENT_SDK=false`) streams
responses with tool calling
- [x] Baseline emits correct Vercel AI SDK stream protocol events
2026-03-04 13:51:46 +00:00
Zamil Majdy
160d6eddfb feat(copilot): enable OpenRouter broadcast for SDK /messages endpoint (#12277)
## Summary

OpenRouter Broadcast silently drops traces for the Anthropic-native
`/api/v1/messages` endpoint unless an `x-session-id` HTTP header is
present. This was confirmed by systematic testing against our Langfuse
integration:

| Test | Endpoint | `x-session-id` header | Broadcast to Langfuse |
|------|----------|-----------------------|----------------------|
| 1 | `/chat/completions` | N/A (body fields work) |  |
| 2 | `/messages` (body fields only) |  |  |
| 3 | `/messages` (header + body) |  |  |
| 4 | `/messages` (`metadata.user_id` only) |  |  |
| 5 | `/messages` (header only) |  |  |

**Root cause:** OpenRouter only triggers broadcast for the `/messages`
endpoint when the `x-session-id` HTTP header is present — body-level
`session_id` and `metadata.user_id` are insufficient.

### Changes
- **SDK path:** Inject `x-session-id` and `x-user-id` via
`ANTHROPIC_CUSTOM_HEADERS` env var in `_build_sdk_env()`, which the
Claude Agent SDK CLI reads and attaches to every outgoing API request
- **Non-SDK path:** Add `trace` object (`trace_name` + `environment`) to
`extra_body` for richer broadcast metadata in Langfuse

This creates complementary traces alongside the existing OTEL
integration: broadcast provides cost/usage data from OpenRouter while
OTEL provides full tool-call observability with `userId`, `sessionId`,
`environment`, and `tags`.

## Test plan
- [x] Verified via test script: `/messages` with `x-session-id` header →
trace appears in Langfuse with correct `sessionId`
- [x] Verified `/chat/completions` with `trace` object → trace appears
with custom `trace_name`
- [x] Pre-commit hooks pass (ruff, black, isort, pyright)
- [ ] Deploy to dev and verify broadcast traces appear for real copilot
SDK sessions
2026-03-04 09:07:48 +00:00
Ubbe
a5db9c05d0 feat(frontend/copilot): add text-to-speech and share output actions (#12256)
## Summary
- Add text-to-speech action button to CoPilot assistant messages using
the browser Web Speech API
- Add share action button that uses the Web Share API with clipboard
fallback
- Replace inline SVG copy icon with Phosphor CopyIcon for consistency

## Linked Issue
SECRT-2052

## Test plan
- [ ] Verify copy button still works
- [ ] Click speaker icon and verify TTS reads aloud
- [ ] Click stop while playing and verify speech stops
- [ ] Click share icon and verify native share or clipboard fallback

Note: This PR should be merged after SECRT-2051 PR

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-04 16:08:54 +08:00
Otto
b74d41d50c fix(backend): handle UniqueViolationError in workspace file retry path (#12267)
Requested by @majdyz

When two concurrent requests write to the same workspace file path with
`overwrite=True`, the retry after deleting the conflicting file could
also hit a `UniqueViolationError`. This raw Prisma exception was
bubbling up unhandled to Sentry as a high-priority alert
(AUTOGPT-SERVER-7ZA).

Now the retry path catches `UniqueViolationError` specifically and
converts it to a `ValueError` with a clear message, matching the
existing pattern for the non-overwrite path.

**Change:** `autogpt_platform/backend/backend/util/workspace.py` — added
a specific `UniqueViolationError` catch before the generic `Exception`
catch in the retry block.

**Risk:** Minimal — only affects the already-failing retry path. No
behavior change for success paths.

---------

Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
2026-03-04 07:04:50 +00:00
Otto
a897f9e124 feat(copilot): render context compaction as tool-call UI events (#12250)
Requested by @majdyz

When CoPilot compacts (summarizes/truncates) conversation history to fit
within context limits, the user now sees it rendered like a tool call —
a spinner while compaction runs, then a completion notice.

**Backend:**
- Added `compaction_start_events()`, `compaction_end_events()`,
`compaction_events()` in `response_model.py` using the existing
tool-call SSE protocol (`tool-input-start` → `tool-input-available` →
`tool-output-available`)
- All three compaction paths (legacy `service.py`, SDK pre-query, SDK
mid-stream) use the same pattern
- Pre-query and SDK-internal compaction tracked independently so neither
suppresses the other

**Frontend:**
- Added `compaction` tool category to `GenericTool` with
`ArrowsClockwise` icon
- Shows "Summarizing earlier messages…" with spinner while running
- Shows "Earlier messages were summarized" when done
- No expandable accordion — just the status line

**Cleanup:**
- Removed unused `system_notice_start/end_events`,
`COMPACTION_STARTED_MSG`
- Removed unused `system_notice_events`, `system_error_events`,
`_system_text_events`

Closes SECRT-2053

---------

Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
2026-03-04 05:31:32 +00:00
Zamil Majdy
7fd26d3554 feat(copilot): run_mcp_tool — MCP server discovery and execution in Otto (#12213)
## Summary

Enables Otto (the AutoGPT copilot) to connect to any MCP (Model Context
Protocol) server, discover its tools, and execute them — with the same
credential login UI used in the graph builder.

**Why a dedicated `run_mcp_tool` instead of reusing `run_block` +
MCPToolBlock?**
Two blockers make `run_block` unworkable for MCP:
1. **No discovery mode** — `MCPToolBlock` errors with "No tool selected"
when `selected_tool` is empty; the agent can't learn what tools exist
before picking one.
2. **Credential matching bug** — `find_matching_credential()` (the block
execution path) does NOT check MCP server URLs; it would match any
stored MCP OAuth credential regardless of server. The correct
`_credential_is_for_mcp_server()` helper only applies in the graph path.

## Changes

### Backend
- **New `run_mcp_tool` copilot tool** (`run_mcp_tool.py`) — two-stage
flow:
1. `run_mcp_tool(server_url)` → discovers available tools via
`MCPClient.list_tools()`
2. `run_mcp_tool(server_url, tool_name, tool_arguments)` → executes via
`MCPClient.call_tool()`
- Lazy auth: fast DB credential lookup first
(`MCPToolBlock._auto_lookup_credential`); on HTTP 401/403 with no stored
creds, returns `SetupRequirementsResponse` so the frontend renders the
existing CredentialsGroupedView OAuth login card
- **New response models** in `models.py`: `MCPToolsDiscoveredResponse`,
`MCPToolOutputResponse`, `MCPToolInfo`
- **Exclude MCPToolBlock** from `find_block` / `run_block`
(`COPILOT_EXCLUDED_BLOCK_TYPES`)
- **System prompt update** — MCP section with two-step flow,
`input_schema` guidance, auth-wait instruction, and registry URL
(`registry.modelcontextprotocol.io`)

### Frontend
- **`RunMCPToolComponent`** — routes between credential prompt (reuses
`SetupRequirementsCard` from RunBlock) and result card; discovery step
shows only a minimal in-progress animation (agent-internal, not
user-facing)
- **`MCPToolOutputCard`** — renders tool result as formatted JSON or
plain text
- **`helpers.tsx`** — type guards (`isMCPToolOutput`,
`isSetupRequirementsOutput`, `isErrorOutput`), output parsing, animation
text
- Registered `tool-run_mcp_tool` case in `ChatMessagesContainer`

## Test plan

- [ ] Call `run_mcp_tool(server_url)` with a public MCP server → see
discovery animation, agent gets tool list
- [ ] Call `run_mcp_tool(server_url, tool_name, tool_arguments)` → see
`MCPToolOutputCard` with result
- [ ] Call with an auth-required server and no stored creds →
`SetupRequirementsCard` renders with MCP OAuth button
- [ ] After connecting credentials, retry → executes successfully
- [ ] `find_block("MCP")` returns no results (MCPToolBlock excluded)
- [ ] Backend unit tests: mock `MCPClient` for discovery + execution +
auth error paths

---------

Co-authored-by: Otto (AGPT) <otto@agpt.co>
2026-03-04 05:30:38 +00:00
Zamil Majdy
b504cf9854 feat(copilot): Add agent-browser multi-step browser automation tools (#12230)
## Summary

Adds three new Copilot tools for multi-step browser automation using the
[agent-browser](https://github.com/vercel-labs/agent-browser) CLI
(Playwright-based local daemon):

- **`browser_navigate`** — navigate to a URL and get an
accessibility-tree snapshot with `@ref` IDs
- **`browser_act`** — interact with page elements (click, fill, scroll,
check, press, select, `dblclick`, `type`, `wait`, back, forward,
reload); returns updated snapshot
- **`browser_screenshot`** — capture annotated screenshot (with `@ref`
overlays) and save to user workspace

Also adds **`browse_web`** (Stagehand + Browserbase) for one-shot
JS-rendered page extraction.

### Why two browser tools?

| Tool | When to use |
|------|-------------|
| `browse_web` | Single-shot extraction — cloud Browserbase session, no
local daemon needed |
| `browser_navigate` / `browser_act` | Multi-step flows (login →
navigate → scrape), persistent session within a Copilot session |

### Design decisions

- **SSRF protection**: Uses the same `validate_url()` from
`backend.util.request` as HTTP blocks — async DNS, all IPs checked, full
RFC 1918 + link-local + IPv6 coverage
- **Session isolation**: `_run()` passes both `--session <id>` (isolated
Chromium context per Copilot session) **and** `--session-name <id>`
(persist cookies within a session), preventing cross-session state
leakage while supporting login flows
- **Snapshot truncation**: Interactive-only accessibility tree
(`snapshot -i`) capped at 20 000 chars with a continuation hint
- **Screenshot storage**: PNG bytes uploaded to user workspace via
`WriteWorkspaceFileTool`; returns `file_id` for retrieval

### Bugs fixed in this PR

- Session isolation bug: `--session-name` alone shared browser history
across different Copilot sessions; added `--session` to isolate contexts
- Missing actions: added `dblclick`, `type` (append without clearing),
`wait` (CSS selector or ms delay)

## Test plan

- [x] 53 unit tests covering all three tools, all actions, SSRF
integration, auth check, session isolation, snapshot truncation,
timeout, missing binary
- [x] Integration test: real `agent-browser` CLI + Anthropic API
tool-calling loop (3/3 scenarios passed)
- [x] Linting (Ruff, isort, Black, Pyright) all passing

```
backend/copilot/tools/agent_browser_test.py  53 passed in 17.79s
```
2026-03-03 21:55:28 +00:00
Zamil Majdy
29da8db48e feat(copilot): E2B cloud sandbox — unified file tools, persistent execution, output truncation (#12212)
## Summary

- **E2B file tools**: New MCP tools
(`read_file`/`write_file`/`edit_file`/`glob`/`grep`) that operate
directly on the E2B sandbox filesystem (`/home/user`). When E2B is
active, these replace SDK built-in `Read/Write/Edit/Glob/Grep` so all
tools share a single coherent filesystem with `bash_exec` — no sync
needed.
- **E2B sandbox lifecycle**: New `e2b_sandbox.py` manages sandbox
creation and reconnection via Redis, with stale-key cleanup on
reconnection failure.
- **E2B enabled by default**: `use_e2b_sandbox` defaults to `True`; set
`CHAT_USE_E2B_SANDBOX=false` to disable.
- **Centralized output truncation**: All MCP tool outputs are truncated
via `_truncating` wrapper and stashed (`_pending_tool_outputs`) to
bypass SDK's head-truncation for the frontend.
- **Frontend tool display**: `GenericTool.tsx` now renders bash
stdout/stderr, file content, edit diffs (old/new), todo lists, and
glob/grep results with category-specific icons and status text.
- **Workspace file tools + E2B**: `read_workspace_file`'s `save_to_path`
and `write_workspace_file`'s `source_path` route to E2B sandbox when
active.

## Files changed

| Area | Files | What |
|------|-------|------|
| E2B file tools | `sdk/e2b_file_tools.py`, `sdk/e2b_file_tools_test.py`
| MCP file tool handlers + tests |
| E2B sandbox | `tools/e2b_sandbox.py` | Sandbox lifecycle
(create/reconnect/Redis) |
| Tool adapter | `sdk/tool_adapter.py` | MCP server, truncation, stash,
path validation |
| Service | `sdk/service.py` | E2B integration, prompt supplements |
| Security | `sdk/security_hooks.py`, `sdk/security_hooks_test.py` |
Path validation for E2B mode |
| Bash exec | `tools/bash_exec.py` | E2B execution path |
| Workspace files | `tools/workspace_files.py`,
`tools/workspace_files_test.py` | E2B-aware save/source paths |
| Config | `copilot/config.py` | E2B config fields (default on) |
| Truncation | `util/truncate.py` | Middle-out truncation fix |
| Frontend | `GenericTool.tsx` | Tool-specific display rendering |

## Test plan

- [x] `security_hooks_test.py` — 43 tests (path validation, tool access,
deny messages)
- [x] `e2b_file_tools_test.py` — 19 tests (path resolution, local read
safety)
- [x] `workspace_files_test.py` — 17 tests (ephemeral path validation)
- [x] CI green (backend 3.11/3.12/3.13, lint, types, e2e)
2026-03-03 21:31:38 +00:00
Nicholas Tindle
757ec1f064 feat(platform): Add file upload to copilot chat [SECRT-1788] (#12220)
## Summary

- Add file attachment support to copilot chat (documents, images,
spreadsheets, video, audio)
- Show upload progress with spinner overlays on file chips during upload
- Display attached files as styled pills in sent user messages using AI
SDK's native `FileUIPart`
- Backend upload endpoint with virus scanning (ClamAV), per-file size
limits, and per-user storage caps
- Enrich chat stream with file metadata so the LLM can access files via
`read_workspace_file`

Resolves: [SECRT-1788](https://linear.app/autogpt/issue/SECRT-1788)

### Backend
| File | Change |
|------|--------|
| `chat/routes.py` | Accept `file_ids` in stream request, enrich user
message with file metadata |
| `workspace/routes.py` | New `POST /files/upload` and `GET
/storage/usage` endpoints |
| `executor/utils.py` | Thread `file_ids` through
`CoPilotExecutionEntry` and RabbitMQ |
| `settings.py` | Add `max_file_size_mb` and `max_workspace_storage_mb`
config |

### Frontend
| File | Change |
|------|--------|
| `AttachmentMenu.tsx` | **New** — `+` button with popover for file
category selection |
| `FileChips.tsx` | **New** — file preview chips with upload spinner
state |
| `MessageAttachments.tsx` | **New** — paperclip pills rendering
`FileUIPart` in chat bubbles |
| `upload/route.ts` | **New** — Next.js API proxy for multipart uploads
to backend |
| `ChatInput.tsx` | Integrate attachment menu, file chips, upload
progress |
| `useCopilotPage.ts` | Upload flow, `FileUIPart` construction,
transport `file_ids` extraction |
| `ChatMessagesContainer.tsx` | Render file parts as
`MessageAttachments` |
| `ChatContainer.tsx` / `EmptySession.tsx` | Thread `isUploadingFiles`
prop |
| `useChatInput.ts` | `canSendEmpty` option for file-only sends |
| `stream/route.ts` | Forward `file_ids` to backend |

## Test plan

- [x] Attach files via `+` button → file chips appear with X buttons
- [x] Remove a chip → file is removed from the list
- [x] Send message with files → chips show upload spinners → message
appears with file attachment pills
- [x] Upload failure → toast error, chips revert to editable (no phantom
message sent)
- [x] New session (empty form): same upload flow works
- [x] Messages without files render normally
- [x] Network tab: `file_ids` present in stream POST body

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

<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> **Medium Risk**
> Adds authenticated file upload/storage-quota enforcement and threads
`file_ids` through the chat streaming path, which affects data handling
and storage behavior. Risk is mitigated by UUID/workspace scoping, size
limits, and virus scanning but still touches security- and
reliability-sensitive upload flows.
> 
> **Overview**
> Copilot chat now supports attaching files: the frontend adds
drag-and-drop and an attach button, shows selected files as removable
chips with an upload-in-progress state, and renders sent attachments
using AI SDK `FileUIPart` with download links.
> 
> On send, files are uploaded to the backend (with client-side limits
and failure handling) and the chat stream request includes `file_ids`;
the backend sanitizes/filters IDs, scopes them to the user’s workspace,
appends an `[Attached files]` metadata block to the user message for the
LLM, and forwards the sanitized IDs through `enqueue_copilot_turn`.
> 
> The backend adds `POST /workspace/files/upload` (filename
sanitization, per-file size limit, ClamAV scan, and per-user storage
quota with post-write rollback) plus `GET /workspace/storage/usage`,
introduces `max_workspace_storage_mb` config, optimizes workspace size
calculation, and fixes executor cleanup to avoid un-awaited coroutine
warnings; new route tests cover file ID validation and upload quota/scan
behaviors.
> 
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
8d3b95d046. 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 <noreply@anthropic.com>
2026-03-03 20:23:27 +00:00
Ubbe
9442c648a4 fix(platform/copilot): bypass Vercel SSE proxy, refactor hook architecture (#12254)
## Summary

Reliability, architecture, and UX improvements for the CoPilot SSE
streaming pipeline.

### Frontend

- **SSE proxy bypass**: Connect directly to the Python backend for SSE
streams, avoiding the Next.js serverless proxy and its 800s Vercel
function timeout ceiling
- **Hook refactor**: Decompose the 490-line `useCopilotPage` monolith
into focused domain modules:
- `helpers.ts` — pure functions (`deduplicateMessages`,
`resolveInProgressTools`)
- `store.ts` — Zustand store for shared UI state (`sessionToDelete`,
drawer open/close)
- `useCopilotStream.ts` — SSE transport, `useChat` wrapper,
reconnect/resume logic, stop+cancel
  - `useCopilotPage.ts` — thin orchestrator (~160 lines)
- **ChatMessagesContainer refactor**: Split 525-line monolith into
sub-components:
  - `helpers.ts` — pure text parsing (markers, workspace URLs)
- `components/ThinkingIndicator.tsx` — ScaleLoader animation + cycling
phrases with pulse
- `components/MessagePartRenderer.tsx` — tool dispatch switch +
workspace media
- **Stop UX fixes**:
- Guard `isReconnecting` and resume effect with `isUserStoppingRef` so
the input unlocks immediately after explicit stop (previously stuck
until page refresh)
- Inject cancellation marker locally in `stop()` so "You manually
stopped this chat" shows instantly
- **Thinking indicator polish**: Replace MorphingBlob SVG with
ScaleLoader (16px), fix initial dark circle flash via
`animation-fill-mode: backwards`, smooth `animate-pulse` text instead of
shimmer gradient
- **ChatSidebar consolidation**: Reads `sessionToDelete` from Zustand
store instead of duplicating delete state/mutation locally
- **Auth error handling**: `getAuthHeaders()` throws on failure instead
of silently returning empty headers; 401 errors show user-facing toast
- **Stale closure fix**: Use refs for reconnect guards to avoid stale
closures during rapid reconnect cycles
- **Session switch resume**: Clear `hasResumedRef` on session switch so
returning to a session with an active stream auto-reconnects
- **Target session cache invalidation**: Invalidate the target session's
React Query cache on switch so `active_stream` is accurate for resume
- **Dedup hardening**: Content-fingerprint dedup resets on non-assistant
messages, preventing legitimate repeated responses from being dropped
- **Marker prefixes**: Hex-suffixed markers (`[__COPILOT_ERROR_f7a1__]`)
to prevent LLM false-positives
- **Code style**: Remove unnecessary `useCallback` wrappers per project
convention, replace unsafe `as` cast with runtime type guard

### Backend (minimal)

- **Faster heartbeat**: 10s → 3s interval to keep SSE alive through
proxies/LBs
- **Faster stall detection**: SSE subscriber queue timeout 30s → 10s
- **Marker prefixes**: Matching hex-suffixed prefixes for error/system
markers

## Test plan

- [ ] Verify SSE streams connect directly to backend (no Next.js proxy
in network tab)
- [ ] Verify reconnect works on transient disconnects (up to 3 attempts
with backoff)
- [ ] Verify auth failure shows user-facing toast
- [ ] Verify switching sessions and switching back shows messages and
resumes active stream
- [ ] Verify deleting a chat from sidebar works (shared Zustand state)
- [ ] Verify mobile drawer delete works (shared Zustand state)
- [ ] Verify thinking indicator shows ScaleLoader + pulsing text, no
dark circle flash
- [ ] Verify stopping a stream immediately unlocks the input and shows
"You manually stopped this chat"
- [ ] Verify marker prefix parsing still works with hex-suffixed
prefixes
- [ ] `pnpm format && pnpm lint && pnpm types` pass

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

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-03 19:56:24 +08:00
Zamil Majdy
1c51dd18aa fix(test): backdate UserBalance.updatedAt in test_block_credit_reset (#12236)
## Root cause

The test constructs \`month3\` using \`datetime.now().replace(month=3,
day=1)\` — hardcoded to **March of the real current year**. When
\`update(balance=400)\` runs, Prisma auto-sets \`updatedAt\` to the
**real wall-clock time**.

The refill guard in \`BetaUserCredit.get_credits\` is:
\`\`\`python
if (snapshot_time.year, snapshot_time.month) == (cur_time.year,
cur_time.month):
    return balance  # same month → skip refill
\`\`\`

This means the test only fails when run **during the real month of
March**, because the mocked \`month3\` and the real \`updatedAt\` both
land in March:

| Test runs in | \`snapshot_time\` (real \`updatedAt\`) | \`cur_time\`
(mocked month3) | Same? | Result |
|---|---|---|---|---|
| January 2026 | \`(2026, 1)\` | \`(2026, 3)\` |  | refill triggers  |
| February 2026 | \`(2026, 2)\` | \`(2026, 3)\` |  | refill triggers 
|
| **March 2026** | **\`(2026, 3)\`** | **\`(2026, 3)\`** | **** |
**skips refill ** |
| April 2026 | \`(2026, 4)\` | \`(2026, 3)\` |  | refill triggers  |

It would silently pass again in April, then fail again next March 2027.

## Fix

Explicitly pass \`updatedAt=month2\` when updating the balance to 400,
so the month2→month3 transition is correctly detected regardless of when
the test actually runs. This matches the existing pattern used earlier
in the same test for the month1 setup.

## Test plan
- [ ] \`pytest backend/data/credit_test.py::test_block_credit_reset\`
passes
- [ ] No other credit tests broken
2026-03-01 07:46:04 +00:00
Zamil Majdy
6f4f80871d feat(copilot): Langfuse SDK tracing for Claude Agent SDK path (#12228)
## Problem

The Copilot SDK path (`ClaudeSDKClient`) routes API calls through `POST
/api/v1/messages` (Anthropic-native endpoint). OpenRouter Broadcast
**silently excludes** this endpoint — it only forwards `POST
/api/v1/chat/completions` (OpenAI-compat) to Langfuse. As a result, all
SDK-path turns were invisible in Langfuse.

**Root cause confirmed** via live pod test: two HTTP calls (one per
endpoint), only the `/chat/completions` one appeared in Langfuse.

## Solution

Add **Langfuse SDK direct tracing** in `sdk/service.py`, wrapping each
`stream_chat_completion_sdk()` call with a `generation` observation.

### What gets captured per user turn
| Field | Value |
|---|---|
| `name` | `copilot-sdk-session` |
| `model` | resolved SDK model |
| `input` | user message |
| `output` | final accumulated assistant text |
| `usage_details.input` | aggregated input tokens (from
`ResultMessage.usage`) |
| `usage_details.output` | aggregated output tokens |
| `cost_details.total` | total cost USD |
| trace `session_id` | copilot session ID |
| trace `user_id` | authenticated user ID |
| trace `tags` | `["sdk"]` |

Token counts and cost are **aggregated** across all internal Anthropic
API calls in the session (tool-use turns included), sourced from
`ResultMessage.usage`.

### Implementation notes
- Span is opened via
`start_as_current_observation(as_type='generation')` before
`ClaudeSDKClient` enters
- Span is **always closed in `finally`** — survives errors,
cancellations, and user stops
- Fails open: any Langfuse init error is caught and logged at `DEBUG`,
tracing is disabled for that turn but the session continues normally
- Only runs when `_is_langfuse_configured()` returns true (same guard as
the non-SDK path)

## Also included

`reproduce_openrouter_broadcast_gap.py` — standalone repro script (no
sensitive data) demonstrating that `/api/v1/messages` is not captured by
OpenRouter Broadcast while `/api/v1/chat/completions` is. To be filed
with OpenRouter support.

## Test plan

- [ ] Deploy to dev, send a Copilot message via the SDK path
- [ ] Confirm trace appears in Langfuse with `tags=["sdk"]`, correct
`session_id`/`user_id`, non-zero token counts
- [ ] Confirm session still works normally when `LANGFUSE_PUBLIC_KEY` is
not set (no-op path)
- [ ] Confirm session still works on error/cancellation (span closed in
finally)
2026-02-27 16:26:46 +00:00
Ubbe
e8cca6cd9a feat(frontend/copilot): migrate ChatInput to ai-sdk prompt-input component (#12207)
## Summary

- **Migrate ChatInput** to composable `PromptInput*` sub-components from
AI SDK Elements, replacing the custom implementation with a boxy,
Claude-style input layout (textarea + footer with tools and submit)
- **Eliminate JS-based DOM height manipulation** (60+ lines removed from
`useChatInput.ts`) in favor of CSS-driven auto-resize via
`min-h`/`max-h`, fixing input sizing jumps (SECRT-2040)
- **Change stop button color** from red to black (`bg-zinc-800`) per
SECRT-2038, while keeping mic recording button red
- **Add new UI primitives**: `InputGroup`, `Spinner`, `Textarea`, and
`prompt-input` composition layer

### New files
- `src/components/ai-elements/prompt-input.tsx` — Composable prompt
input sub-components (PromptInput, PromptInputBody, PromptInputTextarea,
PromptInputFooter, PromptInputTools, PromptInputButton,
PromptInputSubmit)
- `src/components/ui/input-group.tsx` — Layout primitive with flex-col
support, rounded-xlarge styling
- `src/components/ui/spinner.tsx` — Loading spinner using Phosphor
CircleNotch
- `src/components/ui/textarea.tsx` — Base shadcn Textarea component

### Modified files
- `ChatInput.tsx` — Rewritten to compose PromptInput* sub-components
with InputGroup
- `useChatInput.ts` — Simplified: removed maxRows, hasMultipleLines,
handleKeyDown, all DOM style manipulation
- `useVoiceRecording.ts` — Removed `baseHandleKeyDown` dependency;
PromptInputTextarea handles Enter→submit natively

## Resolves
- SECRT-2042: Migrate copilot chat input to ai-sdk prompt-input
component
- SECRT-2038: Change stop button color from red to black

## Test plan
- [ ] Type a message and send it — verify it submits and clears the
input
- [ ] Multi-line input grows smoothly without sizing jumps
- [ ] Press Enter to send, Shift+Enter for new line
- [ ] Voice recording: press space on empty input to start, space again
to stop
- [ ] Mic button stays red while recording; stop-generating button is
black
- [ ] Input has boxy rectangular shape with rounded-xlarge corners
- [ ] Streaming: stop button appears during generation, clicking it
stops the stream
- [ ] EmptySession layout renders correctly with the new input
- [ ] Input is disabled during transcription with "Transcribing..."
placeholder

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

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-27 15:24:19 +00:00
3238 changed files with 182222 additions and 845353 deletions

1
.agents/skills Symbolic link
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../.claude/skills

10
.claude/settings.json Normal file
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{
"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:*)"
]
}
}

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@@ -0,0 +1,106 @@
---
name: open-pr
description: Open a pull request with proper PR template, test coverage, and review workflow. Guides agents through creating a PR that follows repo conventions, ensures existing behaviors aren't broken, covers new behaviors with tests, and handles review via bot when local testing isn't possible. TRIGGER when user asks to "open a PR", "create a PR", "make a PR", "submit a PR", "open pull request", "push and create PR", or any variation of opening/submitting a pull request.
user-invocable: true
args: "[base-branch] — optional target branch (defaults to dev)."
metadata:
author: autogpt-team
version: "1.0.0"
---
# Open a Pull Request
## Step 1: Pre-flight checks
Before opening the PR:
1. Ensure all changes are committed
2. Ensure the branch is pushed to the remote (`git push -u origin <branch>`)
3. Run linters/formatters across the whole repo (not just changed files) and commit any fixes
## Step 2: Test coverage
**This is critical.** Before opening the PR, verify:
### Existing behavior is not broken
- Identify which modules/components your changes touch
- Run the existing test suites for those areas
- If tests fail, fix them before opening the PR — do not open a PR with known regressions
### New behavior has test coverage
- Every new feature, endpoint, or behavior change needs tests
- If you added a new block, add tests for that block
- If you changed API behavior, add or update API tests
- If you changed frontend behavior, verify it doesn't break existing flows
If you cannot run the full test suite locally, note which tests you ran and which you couldn't in the test plan.
## Step 3: Create the PR using the repo template
Read the canonical PR template at `.github/PULL_REQUEST_TEMPLATE.md` and use it **verbatim** as your PR body:
1. Read the template: `cat .github/PULL_REQUEST_TEMPLATE.md`
2. Preserve the exact section titles and formatting, including:
- `### Why / What / How`
- `### Changes 🏗️`
- `### Checklist 📋`
3. Replace HTML comment prompts (`<!-- ... -->`) with actual content; do not leave them in
4. **Do not pre-check boxes** — leave all checkboxes as `- [ ]` until each step is actually completed
5. Do not alter the template structure, rename sections, or remove any checklist items
**PR title must use conventional commit format** (e.g., `feat(backend): add new block`, `fix(frontend): resolve routing bug`, `dx(skills): update PR workflow`). See CLAUDE.md for the full list of scopes.
Use `gh pr create` with the base branch (defaults to `dev` if no `[base-branch]` was provided). Use `--body-file` to avoid shell interpretation of backticks and special characters:
```bash
BASE_BRANCH="${BASE_BRANCH:-dev}"
PR_BODY=$(mktemp)
cat > "$PR_BODY" << 'PREOF'
<filled-in template from .github/PULL_REQUEST_TEMPLATE.md>
PREOF
gh pr create --base "$BASE_BRANCH" --title "<type>(scope): short description" --body-file "$PR_BODY"
rm "$PR_BODY"
```
## Step 4: Review workflow
### If you have a workspace that allows testing (docker, running backend, etc.)
- Run `/pr-test` to do E2E manual testing of the PR using docker compose, agent-browser, and API calls. This is the most thorough way to validate your changes before review.
- After testing, run `/pr-review` to self-review the PR for correctness, security, code quality, and testing gaps before requesting human review.
### If you do NOT have a workspace that allows testing
This is common for agents running in worktrees without a full stack. In this case:
1. Run `/pr-review` locally to catch obvious issues before pushing
2. **Comment `/review` on the PR** after creating it to trigger the review bot
3. **Poll for the review** rather than blindly waiting — check for new review comments every 30 seconds using `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews --paginate` and the GraphQL inline threads query. The bot typically responds within 30 minutes, but polling lets the agent react as soon as it arrives.
4. Do NOT proceed or merge until the bot review comes back
5. Address any issues the bot raises — use `/pr-address` which has a full polling loop with CI + comment tracking
```bash
# After creating the PR:
PR_NUMBER=$(gh pr view --json number -q .number)
gh pr comment "$PR_NUMBER" --body "/review"
# Then use /pr-address to poll for and address the review when it arrives
```
## Step 5: Address review feedback
Once the review bot or human reviewers leave comments:
- Run `/pr-address` to address review comments. It will loop until CI is green and all comments are resolved.
- Do not merge without human approval.
## Related skills
| Skill | When to use |
|---|---|
| `/pr-test` | E2E testing with docker compose, agent-browser, API calls — use when you have a running workspace |
| `/pr-review` | Review for correctness, security, code quality — use before requesting human review |
| `/pr-address` | Address reviewer comments and loop until CI green — use after reviews come in |
## Step 6: Post-creation
After the PR is created and review is triggered:
- Share the PR URL with the user
- If waiting on the review bot, let the user know the expected wait time (~30 min)
- Do not merge without human approval

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@@ -0,0 +1,232 @@
---
name: pr-address
description: Address PR review comments and loop until CI green and all comments resolved. TRIGGER when user asks to address comments, fix PR feedback, respond to reviewers, or babysit/monitor a PR.
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 Address
## Find the PR
```bash
gh pr list --head $(git branch --show-current) --repo Significant-Gravitas/AutoGPT
gh pr view {N}
```
## Read the PR description
Understand the **Why / What / How** before addressing comments — you need context to make good fixes:
```bash
gh pr view {N} --json body --jq '.body'
```
## 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.
```bash
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 }
}
}
}
}
}
}'
```
If `pageInfo.hasNextPage` is true, fetch subsequent pages by adding `after: "<endCursor>"` to `reviewThreads(first: 100, after: "...")` and repeat until `hasNextPage` is false.
**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.
### 2. Top-level reviews — REST (MUST paginate)
```bash
gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews --paginate
```
**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:
- **Overall state**: look for `CHANGES_REQUESTED` or `APPROVED` reviews.
- **Actionable feedback**: non-empty bodies only. Empty-body reviews are thread-resolution events — they indicate progress but have no feedback to act on.
**Where each reviewer posts:**
- `autogpt-reviewer` — posts detailed structured reviews ("Blockers", "Should Fix", "Nice to Have") as **top-level reviews**. Not present on every PR. Address ALL items.
- `sentry[bot]` — posts bug predictions as **inline threads**. Fix real bugs, explain false positives.
- `coderabbitai[bot]` — posts summaries as **top-level reviews** AND actionable items as **inline threads**. Address actionable items.
- Human reviewers — can post in any source. Address ALL non-empty feedback.
### 3. PR conversation comments — REST
```bash
gh api repos/Significant-Gravitas/AutoGPT/issues/{N}/comments --paginate
```
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.
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):
| 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>"` |
## 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 $(gh pr view --json baseRefName --jq '.baseRefName')...HEAD`
2. For each uncovered file — extract inline logic to `helpers.ts`/`helpers.py` and test those (highest ROI). Colocate tests as `*_test.py` (backend) or `__tests__/*.test.ts` (frontend).
3. Run coverage locally to verify, commit, push.
## Format and commit
After fixing, format the changed code:
- **Backend** (from `autogpt_platform/backend/`): `poetry run format`
- **Frontend** (from `autogpt_platform/frontend/`): `pnpm format && pnpm lint && pnpm types`
If API routes changed, regenerate the frontend client:
```bash
cd autogpt_platform/backend && poetry run rest &
REST_PID=$!
trap "kill $REST_PID 2>/dev/null" EXIT
WAIT=0; until curl -sf http://localhost:8006/health > /dev/null 2>&1; do sleep 1; WAIT=$((WAIT+1)); [ $WAIT -ge 60 ] && echo "Timed out" && exit 1; done
cd ../frontend && pnpm generate:api:force
kill $REST_PID 2>/dev/null; trap - EXIT
```
Never manually edit files in `src/app/api/__generated__/`.
Then commit and **push immediately** — never batch commits without pushing. Each fix should be visible on GitHub right away so CI can start and reviewers can see progress.
**Never push empty commits** (`git commit --allow-empty`) to re-trigger CI or bot checks. When a check fails, investigate the root cause (unchecked PR checklist, unaddressed review comments, code issues) and fix those directly. Empty commits add noise to git history.
For backend commits in worktrees: `poetry run git commit` (pre-commit hooks).
## The loop
```text
address comments → format → commit → push
→ wait for CI (while addressing new comments) → fix failures → push
→ re-check comments after CI settles
→ repeat until: all comments addressed AND CI green AND no new comments arriving
```
### Polling for CI + new comments
After pushing, poll for **both** CI status and new comments in a single loop. Do not use `gh pr checks --watch` — it blocks the tool and prevents reacting to new comments while CI is running.
> **Note:** `gh pr checks --watch --fail-fast` is tempting but it blocks the entire Bash tool call, meaning the agent cannot check for or address new comments until CI fully completes. Always poll manually instead.
**Polling loop — repeat every 30 seconds:**
1. Check CI status:
```bash
gh pr checks {N} --repo Significant-Gravitas/AutoGPT --json bucket,name,link
```
Parse the results: if every check has `bucket` of `"pass"` or `"skipping"`, CI is green. If any has `"fail"`, CI has failed. Otherwise CI is still pending.
2. Check for merge conflicts:
```bash
gh pr view {N} --repo Significant-Gravitas/AutoGPT --json mergeable --jq '.mergeable'
```
If the result is `"CONFLICTING"`, the PR has a merge conflict — see "Resolving merge conflicts" below. If `"UNKNOWN"`, GitHub is still computing mergeability — wait and re-check next poll.
3. Check for new/changed comments (all three sources):
**Inline threads** — re-run the GraphQL query from "Fetch comments". For each unresolved thread, record `{thread_id, last_comment_databaseId}` as your baseline. On each poll, action is needed if:
- A new thread `id` appears that wasn't in the baseline (new thread), OR
- An existing thread's `last_comment_databaseId` has changed (new reply on existing thread)
**Conversation comments:**
```bash
gh api repos/Significant-Gravitas/AutoGPT/issues/{N}/comments --paginate
```
Compare total count and newest `id` against baseline. Filter to non-empty, non-bot, non-author-update messages.
**Top-level reviews:**
```bash
gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews --paginate
```
Watch for new non-empty reviews (`CHANGES_REQUESTED` or `COMMENTED` with body). Compare total count and newest `id` against baseline.
4. **React in this precedence order (first match wins):**
| What happened | Action |
|---|---|
| Merge conflict detected | See "Resolving merge conflicts" below. |
| Mergeability is `UNKNOWN` | GitHub is still computing mergeability. Sleep 30 seconds, then restart polling from the top. |
| New comments detected | Address them (fix → commit → push → reply). After pushing, re-fetch all comments to update your baseline, then restart this polling loop from the top (new commits invalidate CI status). |
| CI failed (bucket == "fail") | Get failed check links: `gh pr checks {N} --repo Significant-Gravitas/AutoGPT --json bucket,link --jq '.[] \| select(.bucket == "fail") \| .link'`. Extract run ID from link (format: `.../actions/runs/<run-id>/job/...`), read logs with `gh run view <run-id> --repo Significant-Gravitas/AutoGPT --log-failed`. Fix → commit → push → restart polling. |
| CI green + no new comments | **Do not exit immediately.** Bots (coderabbitai, sentry) often post reviews shortly after CI settles. Continue polling for **2 more cycles (60s)** after CI goes green. Only exit after 2 consecutive green+quiet polls. |
| CI pending + no new comments | Sleep 30 seconds, then poll again. |
**The loop ends when:** CI fully green + all comments addressed + **2 consecutive polls with no new comments after CI settled.**
### Resolving merge conflicts
1. Identify the PR's target branch and remote:
```bash
gh pr view {N} --repo Significant-Gravitas/AutoGPT --json baseRefName --jq '.baseRefName'
git remote -v # find the remote pointing to Significant-Gravitas/AutoGPT (typically 'upstream' in forks, 'origin' for direct contributors)
```
2. Pull the latest base branch with a 3-way merge:
```bash
git pull {base-remote} {base-branch} --no-rebase
```
3. Resolve conflicting files, then verify no conflict markers remain:
```bash
if grep -R -n -E '^(<<<<<<<|=======|>>>>>>>)' <conflicted-files>; then
echo "Unresolved conflict markers found — resolve before proceeding."
exit 1
fi
```
4. Stage and push:
```bash
git add <conflicted-files>
git commit -m "Resolve merge conflicts with {base-branch}"
git push
```
5. Restart the polling loop from the top — new commits reset CI status.

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@@ -0,0 +1,86 @@
---
name: pr-review
description: Review a PR for correctness, security, code quality, and testing issues. TRIGGER when user asks to review a PR, check PR quality, or give feedback on a PR.
user-invocable: true
args: "[PR number or URL] — if omitted, finds PR for current branch."
metadata:
author: autogpt-team
version: "1.0.0"
---
# PR Review
## Find the PR
```bash
gh pr list --head $(git branch --show-current) --repo Significant-Gravitas/AutoGPT
gh pr view {N}
```
## Read the PR description
Before reading code, understand the **why**, **what**, and **how** from the PR description:
```bash
gh pr view {N} --json body --jq '.body'
```
Every PR should have a Why / What / How structure. If any of these are missing, note it as feedback.
## Read the diff
```bash
gh pr diff {N}
```
## Fetch existing review comments
Before posting anything, fetch existing inline comments to avoid duplicates:
```bash
gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments --paginate
gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews
```
## What to check
**Description quality:** Does the PR description cover Why (motivation/problem), What (summary of changes), and How (approach/implementation details)? If any are missing, request them — you can't judge the approach without understanding the problem and intent.
**Correctness:** logic errors, off-by-one, missing edge cases, race conditions (TOCTOU in file access, credit charging), error handling gaps, async correctness (missing `await`, unclosed resources).
**Security:** input validation at boundaries, no injection (command, XSS, SQL), secrets not logged, file paths sanitized (`os.path.basename()` in error messages).
**Code quality:** apply rules from backend/frontend CLAUDE.md files.
**Architecture:** DRY, single responsibility, modular functions. `Security()` vs `Depends()` for FastAPI auth. `data:` for SSE events, `: comment` for heartbeats. `transaction=True` for Redis pipelines.
**Testing:** edge cases covered, colocated `*_test.py` (backend) / `__tests__/` (frontend), mocks target where symbol is **used** not defined, `AsyncMock` for async.
## Output format
Every comment **must** be prefixed with `🤖` and a criticality badge:
| Tier | Badge | Meaning |
|---|---|---|
| Blocker | `🔴 **Blocker**` | Must fix before merge |
| Should Fix | `🟠 **Should Fix**` | Important improvement |
| Nice to Have | `🟡 **Nice to Have**` | Minor suggestion |
| Nit | `🔵 **Nit**` | Style / wording |
Example: `🤖 🔴 **Blocker**: Missing error handling for X — suggest wrapping in try/except.`
## Post inline comments
For each finding, post an inline comment on the PR (do not just write a local report):
```bash
# Get the latest commit SHA for the PR
COMMIT_SHA=$(gh api repos/Significant-Gravitas/AutoGPT/pulls/{N} --jq '.head.sha')
# Post an inline comment on a specific file/line
gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments \
-f body="🤖 🔴 **Blocker**: <description>" \
-f commit_id="$COMMIT_SHA" \
-f path="<file path>" \
-F line=<line number>
```

View File

@@ -0,0 +1,886 @@
---
name: pr-test
description: "E2E manual testing of PRs/branches using docker compose, agent-browser, and API calls. TRIGGER when user asks to manually test a PR, test a feature end-to-end, or run integration tests against a running system."
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"
---
# Manual E2E Test
Test a PR/branch end-to-end by building the full platform, interacting via browser and API, capturing screenshots, and reporting results.
## Critical Requirements
These are NON-NEGOTIABLE. Every test run MUST satisfy ALL the following:
### 1. Screenshots at Every Step
- Take a screenshot at EVERY significant test step — not just at the end
- Every test scenario MUST have at least one BEFORE and one AFTER screenshot
- Name screenshots sequentially: `{NN}-{action}-{state}.png` (e.g., `01-credits-before.png`, `02-credits-after.png`)
- If a screenshot is missing for a scenario, the test is INCOMPLETE — go back and take it
### 2. Screenshots MUST Be Posted to PR
- Push ALL screenshots to a temp branch `test-screenshots/pr-{N}`
- Post a PR comment with ALL screenshots embedded inline using GitHub raw URLs
- This is NOT optional — every test run MUST end with a PR comment containing screenshots
- If screenshot upload fails, retry. If it still fails, list failed files and require manual drag-and-drop/paste attachment in the PR comment
### 3. State Verification with Before/After Evidence
- For EVERY state-changing operation (API call, user action), capture the state BEFORE and AFTER
- Log the actual API response values (e.g., `credits_before=100, credits_after=95`)
- Screenshot MUST show the relevant UI state change
- Compare expected vs actual values explicitly — do not just eyeball it
### 4. Negative Test Cases Are Mandatory
- Test at least ONE negative case per feature (e.g., insufficient credits, invalid input, unauthorized access)
- Verify error messages are user-friendly and accurate
- Verify the system state did NOT change after a rejected operation
### 5. Test Report Must Include Full Evidence
Each test scenario in the report MUST have:
- **Steps**: What was done (exact commands or UI actions)
- **Expected**: What should happen
- **Actual**: What actually happened
- **API Evidence**: Before/after API response values for state-changing operations
- **Screenshot Evidence**: Before/after screenshots with explanations
## State Manipulation for Realistic Testing
When testing features that depend on specific states (rate limits, credits, quotas):
1. **Use Redis CLI to set counters directly:**
```bash
# Find the Redis container
REDIS_CONTAINER=$(docker ps --format '{{.Names}}' | grep redis | head -1)
# Set a key with expiry
docker exec $REDIS_CONTAINER redis-cli SET key value EX ttl
# Example: Set rate limit counter to near-limit
docker exec $REDIS_CONTAINER redis-cli SET "rate_limit:user:test@test.com" 99 EX 3600
# Example: Check current value
docker exec $REDIS_CONTAINER redis-cli GET "rate_limit:user:test@test.com"
```
2. **Use API calls to check before/after state:**
```bash
# BEFORE: Record current state
BEFORE=$(curl -s -H "Authorization: Bearer $TOKEN" http://localhost:8006/api/credits | jq '.credits')
echo "Credits BEFORE: $BEFORE"
# Perform the action...
# AFTER: Record new state and compare
AFTER=$(curl -s -H "Authorization: Bearer $TOKEN" http://localhost:8006/api/credits | jq '.credits')
echo "Credits AFTER: $AFTER"
echo "Delta: $(( BEFORE - AFTER ))"
```
3. **Take screenshots BEFORE and AFTER state changes** — the UI must reflect the backend state change
4. **Never rely on mocked/injected browser state** — always use real backend state. Do NOT use `agent-browser eval` to fake UI state. The backend must be the source of truth.
5. **Use direct DB queries when needed:**
```bash
# Query via Supabase's PostgREST or docker exec into the DB
docker exec supabase-db psql -U supabase_admin -d postgres -c "SELECT credits FROM user_credits WHERE user_id = '...';"
```
6. **After every API test, verify the state change actually persisted:**
```bash
# Example: After a credits purchase, verify DB matches API
API_CREDITS=$(curl -s -H "Authorization: Bearer $TOKEN" http://localhost:8006/api/credits | jq '.credits')
DB_CREDITS=$(docker exec supabase-db psql -U supabase_admin -d postgres -t -c "SELECT credits FROM user_credits WHERE user_id = '...';" | tr -d ' ')
[ "$API_CREDITS" = "$DB_CREDITS" ] && echo "CONSISTENT" || echo "MISMATCH: API=$API_CREDITS DB=$DB_CREDITS"
```
## Arguments
- `$ARGUMENTS` — worktree path (e.g. `$REPO_ROOT`) or PR number
- If `--fix` flag is present, auto-fix bugs found and push fixes (like pr-address loop)
## Step 0: Resolve the target
```bash
# If argument is a PR number, find its worktree
gh pr view {N} --json headRefName --jq '.headRefName'
# If argument is a path, use it directly
```
Determine:
- `REPO_ROOT` — the root repo directory: `git -C "$WORKTREE_PATH" worktree list | head -1 | awk '{print $1}'` (or `git rev-parse --show-toplevel` if not a worktree)
- `WORKTREE_PATH` — the worktree directory
- `PLATFORM_DIR` — `$WORKTREE_PATH/autogpt_platform`
- `BACKEND_DIR` — `$PLATFORM_DIR/backend`
- `FRONTEND_DIR` — `$PLATFORM_DIR/frontend`
- `PR_NUMBER` — the PR number (from `gh pr list --head $(git branch --show-current)`)
- `PR_TITLE` — the PR title, slugified (e.g. "Add copilot permissions" → "add-copilot-permissions")
- `RESULTS_DIR` — `$REPO_ROOT/test-results/PR-{PR_NUMBER}-{slugified-title}`
Create the results directory:
```bash
PR_NUMBER=$(cd $WORKTREE_PATH && gh pr list --head $(git branch --show-current) --repo Significant-Gravitas/AutoGPT --json number --jq '.[0].number')
PR_TITLE=$(cd $WORKTREE_PATH && gh pr list --head $(git branch --show-current) --repo Significant-Gravitas/AutoGPT --json title --jq '.[0].title' | tr '[:upper:]' '[:lower:]' | sed 's/[^a-z0-9]/-/g' | sed 's/--*/-/g' | sed 's/^-//;s/-$//' | head -c 50)
RESULTS_DIR="$REPO_ROOT/test-results/PR-${PR_NUMBER}-${PR_TITLE}"
mkdir -p $RESULTS_DIR
```
**Test user credentials** (for logging into the UI or verifying results manually):
- Email: `test@test.com`
- Password: `testtest123`
## Step 1: Understand the PR
Before testing, understand what changed:
```bash
cd $WORKTREE_PATH
# Read PR description to understand the WHY
gh pr view {N} --json body --jq '.body'
git log --oneline dev..HEAD | head -20
git diff dev --stat
```
Read the PR description (Why / What / How) and changed files to understand:
0. **Why** does this PR exist? What problem does it solve?
1. **What** feature/fix does this PR implement?
2. **How** does it work? What's the approach?
3. What components are affected? (backend, frontend, copilot, executor, etc.)
4. What are the key user-facing behaviors to test?
## Step 2: Write test scenarios
Based on the PR analysis, write a test plan to `$RESULTS_DIR/test-plan.md`:
```markdown
# Test Plan: PR #{N} — {title}
## Scenarios
1. [Scenario name] — [what to verify]
2. ...
## API Tests (if applicable)
1. [Endpoint] — [expected behavior]
- Before state: [what to check before]
- After state: [what to verify changed]
## UI Tests (if applicable)
1. [Page/component] — [interaction to test]
- Screenshot before: [what to capture]
- Screenshot after: [what to capture]
## Negative Tests (REQUIRED — at least one per feature)
1. [What should NOT happen] — [how to trigger it]
- Expected error: [what error message/code]
- State unchanged: [what to verify did NOT change]
```
**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: Environment setup
### 3a. Copy .env files from the root worktree
The root worktree (`$REPO_ROOT`) has the canonical `.env` files with all API keys. Copy them to the target worktree:
```bash
# CRITICAL: .env files are NOT checked into git. They must be copied manually.
cp $REPO_ROOT/autogpt_platform/.env $PLATFORM_DIR/.env
cp $REPO_ROOT/autogpt_platform/backend/.env $BACKEND_DIR/.env
cp $REPO_ROOT/autogpt_platform/frontend/.env $FRONTEND_DIR/.env
```
### 3b. Configure copilot authentication
The copilot needs an LLM API to function. Two approaches (try subscription first):
#### Option 1: Subscription mode (preferred — uses your Claude Max/Pro subscription)
The `claude_agent_sdk` Python package **bundles its own Claude CLI binary** — no need to install `@anthropic-ai/claude-code` via npm. The backend auto-provisions credentials from environment variables on startup.
Run the helper script to extract tokens from your host and auto-update `backend/.env` (works on macOS, Linux, and Windows/WSL):
```bash
# Extracts OAuth tokens and writes CLAUDE_CODE_OAUTH_TOKEN + CLAUDE_CODE_REFRESH_TOKEN into .env
bash $BACKEND_DIR/scripts/refresh_claude_token.sh --env-file $BACKEND_DIR/.env
```
**How it works:** The script reads the OAuth token from:
- **macOS**: system keychain (`"Claude Code-credentials"`)
- **Linux/WSL**: `~/.claude/.credentials.json`
- **Windows**: `%APPDATA%/claude/.credentials.json`
It sets `CLAUDE_CODE_OAUTH_TOKEN`, `CLAUDE_CODE_REFRESH_TOKEN`, and `CHAT_USE_CLAUDE_CODE_SUBSCRIPTION=true` in the `.env` file. On container startup, the backend auto-provisions `~/.claude/.credentials.json` inside the container from these env vars. The SDK's bundled CLI then authenticates using that file. No `claude login`, no npm install needed.
**Note:** The OAuth token expires (~24h). If copilot returns auth errors, re-run the script and restart: `$BACKEND_DIR/scripts/refresh_claude_token.sh --env-file $BACKEND_DIR/.env && docker compose up -d copilot_executor`
#### Option 2: OpenRouter API key mode (fallback)
If subscription mode doesn't work, switch to API key mode using OpenRouter:
```bash
# In $BACKEND_DIR/.env, ensure these are set:
CHAT_USE_CLAUDE_CODE_SUBSCRIPTION=false
CHAT_API_KEY=<value of OPEN_ROUTER_API_KEY from the same .env>
CHAT_BASE_URL=https://openrouter.ai/api/v1
CHAT_USE_CLAUDE_AGENT_SDK=true
```
Use `sed` to update these values:
```bash
ORKEY=$(grep "^OPEN_ROUTER_API_KEY=" $BACKEND_DIR/.env | cut -d= -f2)
[ -n "$ORKEY" ] || { echo "ERROR: OPEN_ROUTER_API_KEY is missing in $BACKEND_DIR/.env"; exit 1; }
perl -i -pe 's/CHAT_USE_CLAUDE_CODE_SUBSCRIPTION=true/CHAT_USE_CLAUDE_CODE_SUBSCRIPTION=false/' $BACKEND_DIR/.env
# Add or update CHAT_API_KEY and CHAT_BASE_URL
grep -q "^CHAT_API_KEY=" $BACKEND_DIR/.env && perl -i -pe "s|^CHAT_API_KEY=.*|CHAT_API_KEY=$ORKEY|" $BACKEND_DIR/.env || echo "CHAT_API_KEY=$ORKEY" >> $BACKEND_DIR/.env
grep -q "^CHAT_BASE_URL=" $BACKEND_DIR/.env && perl -i -pe 's|^CHAT_BASE_URL=.*|CHAT_BASE_URL=https://openrouter.ai/api/v1|' $BACKEND_DIR/.env || echo "CHAT_BASE_URL=https://openrouter.ai/api/v1" >> $BACKEND_DIR/.env
```
### 3c. Stop conflicting containers
```bash
# Stop any running app containers (keep infra: supabase, redis, rabbitmq, clamav)
docker ps --format "{{.Names}}" | grep -E "rest_server|executor|copilot|websocket|database_manager|scheduler|notification|frontend|migrate" | while read name; do
docker stop "$name" 2>/dev/null
done
```
### 3e. Build and start
```bash
cd $PLATFORM_DIR && docker compose build --no-cache 2>&1 | tail -20
if [ ${PIPESTATUS[0]} -ne 0 ]; then echo "ERROR: Docker build failed"; exit 1; fi
cd $PLATFORM_DIR && docker compose up -d 2>&1 | tail -20
if [ ${PIPESTATUS[0]} -ne 0 ]; then echo "ERROR: Docker compose up failed"; exit 1; fi
```
**Note:** If the container appears to be running old code (e.g. missing PR changes), use `docker compose build --no-cache` to force a full rebuild. Docker BuildKit may sometimes reuse cached `COPY` layers from a previous build on a different branch.
**Expected time: 3-8 minutes** for build, 5-10 minutes with `--no-cache`.
### 3f. Wait for services to be ready
```bash
# Poll until backend and frontend respond
for i in $(seq 1 60); do
BACKEND=$(curl -s -o /dev/null -w "%{http_code}" http://localhost:8006/docs 2>/dev/null)
FRONTEND=$(curl -s -o /dev/null -w "%{http_code}" http://localhost:3000 2>/dev/null)
if [ "$BACKEND" = "200" ] && [ "$FRONTEND" = "200" ]; then
echo "Services ready"
break
fi
sleep 5
done
```
### 3h. Create test user and get auth token
```bash
ANON_KEY=$(grep "NEXT_PUBLIC_SUPABASE_ANON_KEY=" $FRONTEND_DIR/.env | sed 's/.*NEXT_PUBLIC_SUPABASE_ANON_KEY=//' | tr -d '[:space:]')
# Signup (idempotent — returns "User already registered" if exists)
RESULT=$(curl -s -X POST 'http://localhost:8000/auth/v1/signup' \
-H "apikey: $ANON_KEY" \
-H 'Content-Type: application/json' \
-d '{"email":"test@test.com","password":"testtest123"}')
# If "Database error finding user", restart supabase-auth and retry
if echo "$RESULT" | grep -q "Database error"; then
docker restart supabase-auth && sleep 5
curl -s -X POST 'http://localhost:8000/auth/v1/signup' \
-H "apikey: $ANON_KEY" \
-H 'Content-Type: application/json' \
-d '{"email":"test@test.com","password":"testtest123"}'
fi
# Get auth token
TOKEN=$(curl -s -X POST 'http://localhost:8000/auth/v1/token?grant_type=password' \
-H "apikey: $ANON_KEY" \
-H 'Content-Type: application/json' \
-d '{"email":"test@test.com","password":"testtest123"}' | jq -r '.access_token // ""')
```
**Use this token for ALL API calls:**
```bash
curl -H "Authorization: Bearer $TOKEN" http://localhost:8006/api/...
```
## Step 4: Run tests
### Service ports reference
| Service | Port | URL |
|---------|------|-----|
| Frontend | 3000 | http://localhost:3000 |
| Backend REST | 8006 | http://localhost:8006 |
| Supabase Auth (via Kong) | 8000 | http://localhost:8000 |
| Executor | 8002 | http://localhost:8002 |
| Copilot Executor | 8008 | http://localhost:8008 |
| WebSocket | 8001 | http://localhost:8001 |
| Database Manager | 8005 | http://localhost:8005 |
| Redis | 6379 | localhost:6379 |
| RabbitMQ | 5672 | localhost:5672 |
### API testing
Use `curl` with the auth token for backend API tests. **For EVERY API call that changes state, record before/after values:**
```bash
# Example: List agents
curl -s -H "Authorization: Bearer $TOKEN" http://localhost:8006/api/graphs | jq . | head -20
# Example: Create an agent
curl -s -X POST http://localhost:8006/api/graphs \
-H "Authorization: Bearer $TOKEN" \
-H 'Content-Type: application/json' \
-d '{...}' | jq .
# Example: Run an agent
curl -s -X POST "http://localhost:8006/api/graphs/{graph_id}/execute" \
-H "Authorization: Bearer $TOKEN" \
-H 'Content-Type: application/json' \
-d '{"data": {...}}'
# Example: Get execution results
curl -s -H "Authorization: Bearer $TOKEN" \
"http://localhost:8006/api/graphs/{graph_id}/executions/{exec_id}" | jq .
```
**State verification pattern (use for EVERY state-changing API call):**
```bash
# 1. Record BEFORE state
BEFORE_STATE=$(curl -s -H "Authorization: Bearer $TOKEN" http://localhost:8006/api/{resource} | jq '{relevant_fields}')
echo "BEFORE: $BEFORE_STATE"
# 2. Perform the action
ACTION_RESULT=$(curl -s -X POST ... | jq .)
echo "ACTION RESULT: $ACTION_RESULT"
# 3. Record AFTER state
AFTER_STATE=$(curl -s -H "Authorization: Bearer $TOKEN" http://localhost:8006/api/{resource} | jq '{relevant_fields}')
echo "AFTER: $AFTER_STATE"
# 4. Log the comparison
echo "=== STATE CHANGE VERIFICATION ==="
echo "Before: $BEFORE_STATE"
echo "After: $AFTER_STATE"
echo "Expected change: {describe what should have changed}"
```
### Browser testing with agent-browser
```bash
# Close any existing session
agent-browser close 2>/dev/null || true
# Use --session-name to persist cookies across navigations
# This means login only needs to happen once per test session
agent-browser --session-name pr-test open 'http://localhost:3000/login' --timeout 15000
# Get interactive elements
agent-browser --session-name pr-test snapshot | grep "textbox\|button"
# Login
agent-browser --session-name pr-test fill {email_ref} "test@test.com"
agent-browser --session-name pr-test fill {password_ref} "testtest123"
agent-browser --session-name pr-test click {login_button_ref}
sleep 5
# Dismiss cookie banner if present
agent-browser --session-name pr-test click 'text=Accept All' 2>/dev/null || true
# Navigate — cookies are preserved so login persists
agent-browser --session-name pr-test open 'http://localhost:3000/copilot' --timeout 10000
# Take screenshot
agent-browser --session-name pr-test screenshot $RESULTS_DIR/01-page.png
# Interact with elements
agent-browser --session-name pr-test fill {ref} "text"
agent-browser --session-name pr-test press "Enter"
agent-browser --session-name pr-test click {ref}
agent-browser --session-name pr-test click 'text=Button Text'
# Read page content
agent-browser --session-name pr-test snapshot | grep "text:"
```
**Key pages:**
- `/copilot` — CoPilot chat (for testing copilot features)
- `/build` — Agent builder (for testing block/node features)
- `/build?flowID={id}` — Specific agent in builder
- `/library` — Agent library (for testing listing/import features)
- `/library/agents/{id}` — Agent detail with run history
- `/marketplace` — Marketplace
### Checking logs
```bash
# Backend REST server
docker logs autogpt_platform-rest_server-1 2>&1 | tail -30
# Executor (runs agent graphs)
docker logs autogpt_platform-executor-1 2>&1 | tail -30
# Copilot executor (runs copilot chat sessions)
docker logs autogpt_platform-copilot_executor-1 2>&1 | tail -30
# Frontend
docker logs autogpt_platform-frontend-1 2>&1 | tail -30
# Filter for errors
docker logs autogpt_platform-executor-1 2>&1 | grep -i "error\|exception\|traceback" | tail -20
```
### Copilot chat testing
The copilot uses SSE streaming. To test via API:
```bash
# Create a session
SESSION_ID=$(curl -s -X POST 'http://localhost:8006/api/chat/sessions' \
-H "Authorization: Bearer $TOKEN" \
-H 'Content-Type: application/json' \
-d '{}' | jq -r '.id // .session_id // ""')
# Stream a message (SSE - will stream chunks)
curl -N -X POST "http://localhost:8006/api/chat/sessions/$SESSION_ID/stream" \
-H "Authorization: Bearer $TOKEN" \
-H 'Content-Type: application/json' \
-d '{"message": "Hello, what can you help me with?"}' \
--max-time 60 2>/dev/null | head -50
```
Or test via browser (preferred for UI verification):
```bash
agent-browser --session-name pr-test open 'http://localhost:3000/copilot' --timeout 10000
# ... fill chat input and press Enter, wait 20-30s for response
```
## Step 5: Record results and take screenshots
**Take a screenshot at EVERY significant test step** — before and after interactions, on success, and on failure. This is NON-NEGOTIABLE.
**Required screenshot pattern for each test scenario:**
```bash
# BEFORE the action
agent-browser --session-name pr-test screenshot $RESULTS_DIR/{NN}-{scenario}-before.png
# Perform the action...
# AFTER the action
agent-browser --session-name pr-test screenshot $RESULTS_DIR/{NN}-{scenario}-after.png
```
**Naming convention:**
```bash
# Examples:
# $RESULTS_DIR/01-login-page-before.png
# $RESULTS_DIR/02-login-page-after.png
# $RESULTS_DIR/03-credits-page-before.png
# $RESULTS_DIR/04-credits-purchase-after.png
# $RESULTS_DIR/05-negative-insufficient-credits.png
# $RESULTS_DIR/06-error-state.png
```
**Minimum requirements:**
- At least TWO screenshots per test scenario (before + after)
- At least ONE screenshot for each negative test case showing the error state
- If a test fails, screenshot the failure state AND any error logs visible in the UI
## Step 6: Show results to user with screenshots
**CRITICAL: After all tests complete, you MUST show every screenshot to the user using the Read tool, with an explanation of what each screenshot shows.** This is the most important part of the test report — the user needs to visually verify the results.
For each screenshot:
1. Use the `Read` tool to display the PNG file (Claude can read images)
2. Write a 1-2 sentence explanation below it describing:
- What page/state is being shown
- What the screenshot proves (which test scenario it validates)
- Any notable details visible in the UI
Format the output like this:
```markdown
### Screenshot 1: {descriptive title}
[Read the PNG file here]
**What it shows:** {1-2 sentence explanation of what this screenshot proves}
---
```
After showing all screenshots, output a **detailed** summary table:
| # | Scenario | Result | API Evidence | Screenshot Evidence |
|---|----------|--------|-------------|-------------------|
| 1 | {name} | PASS/FAIL | Before: X, After: Y | 01-before.png, 02-after.png |
| 2 | ... | ... | ... | ... |
**IMPORTANT:** As you show each screenshot and record test results, persist them in shell variables for Step 7:
```bash
# Build these variables during Step 6 — they are required by Step 7's script
# NOTE: declare -A requires Bash 4.0+. This is standard on modern systems (macOS ships zsh
# but Homebrew bash is 5.x; Linux typically has bash 5.x). If running on Bash <4, use a
# plain variable with a lookup function instead.
declare -A SCREENSHOT_EXPLANATIONS=(
# Each explanation MUST answer three things:
# 1. FLOW: Which test scenario / user journey is this part of?
# 2. STEPS: What exact actions were taken to reach this state?
# 3. EVIDENCE: What does this screenshot prove (pass/fail/data)?
#
# Good example:
# ["03-cost-log-after-run.png"]="Flow: LLM block cost tracking. Steps: Logged in as tester@gmail.com → ran 'Cost Test Agent' → waited for COMPLETED status. Evidence: PlatformCostLog table shows 1 new row with cost_microdollars=1234 and correct user_id."
#
# Bad example (too vague — never do this):
# ["03-cost-log.png"]="Shows the cost log table."
["01-login-page.png"]="Flow: Login flow. Steps: Opened /login. Evidence: Login page renders with email/password fields and SSO options visible."
["02-builder-with-block.png"]="Flow: Block execution. Steps: Logged in → /build → added LLM block. Evidence: Builder canvas shows block connected to trigger, ready to run."
# ... one entry per screenshot using the flow/steps/evidence format above
)
TEST_RESULTS_TABLE="| 1 | Login flow | PASS | N/A | 01-login-before.png, 02-login-after.png |
| 2 | Credits purchase | PASS | Before: 100, After: 95 | 03-credits-before.png, 04-credits-after.png |
| 3 | Insufficient credits (negative) | PASS | Credits: 0, rejected | 05-insufficient-credits-error.png |"
# ... one row per test scenario with actual results
```
## Step 7: Post test report as PR comment with screenshots
Upload screenshots to the PR using the GitHub Git API (no local git operations — safe for worktrees), then post a comment with inline images and per-screenshot explanations.
**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.
```bash
# Upload screenshots via GitHub Git API (creates blobs, tree, commit, and ref remotely)
REPO="Significant-Gravitas/AutoGPT"
SCREENSHOTS_BRANCH="test-screenshots/pr-${PR_NUMBER}"
SCREENSHOTS_DIR="test-screenshots/PR-${PR_NUMBER}"
# Step 1: Create blobs for each screenshot and build tree JSON
# Retry each blob upload up to 3 times. If still failing, list them at end of report.
shopt -s nullglob
SCREENSHOT_FILES=("$RESULTS_DIR"/*.png)
if [ ${#SCREENSHOT_FILES[@]} -eq 0 ]; then
echo "ERROR: No screenshots found in $RESULTS_DIR. Test run is incomplete."
exit 1
fi
TREE_JSON='['
FIRST=true
FAILED_UPLOADS=()
for img in "${SCREENSHOT_FILES[@]}"; do
BASENAME=$(basename "$img")
B64=$(base64 < "$img")
BLOB_SHA=""
for attempt in 1 2 3; do
BLOB_SHA=$(gh api "repos/${REPO}/git/blobs" -f content="$B64" -f encoding="base64" --jq '.sha' 2>/dev/null || true)
[ -n "$BLOB_SHA" ] && break
sleep 1
done
if [ -z "$BLOB_SHA" ]; then
FAILED_UPLOADS+=("$img")
continue
fi
if [ "$FIRST" = true ]; then FIRST=false; else TREE_JSON+=','; fi
TREE_JSON+="{\"path\":\"${SCREENSHOTS_DIR}/${BASENAME}\",\"mode\":\"100644\",\"type\":\"blob\",\"sha\":\"${BLOB_SHA}\"}"
done
TREE_JSON+=']'
# Step 2: Create tree, commit (with parent), and branch ref
TREE_SHA=$(echo "$TREE_JSON" | jq -c '{tree: .}' | gh api "repos/${REPO}/git/trees" --input - --jq '.sha')
# Resolve existing branch tip as parent (avoids orphan commits on repeat runs)
PARENT_SHA=$(gh api "repos/${REPO}/git/refs/heads/${SCREENSHOTS_BRANCH}" --jq '.object.sha' 2>/dev/null || true)
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
# First commit on this branch — no parent
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
```
Then post the comment with **inline images AND explanations for each screenshot**:
```bash
REPO_URL="https://raw.githubusercontent.com/${REPO}/${SCREENSHOTS_BRANCH}"
# Build image markdown using uploaded image URLs; skip FAILED_UPLOADS (listed separately)
IMAGE_MARKDOWN=""
for img in "${SCREENSHOT_FILES[@]}"; do
BASENAME=$(basename "$img")
TITLE=$(echo "${BASENAME%.png}" | sed 's/^[0-9]*-//' | sed 's/-/ /g' | awk '{for(i=1;i<=NF;i++) $i=toupper(substr($i,1,1)) tolower(substr($i,2))}1')
# Skip images that failed to upload — they will be listed at the end
IS_FAILED=false
for failed in "${FAILED_UPLOADS[@]}"; do
[ "$(basename "$failed")" = "$BASENAME" ] && IS_FAILED=true && break
done
if [ "$IS_FAILED" = true ]; then
continue
fi
EXPLANATION="${SCREENSHOT_EXPLANATIONS[$BASENAME]}"
if [ -z "$EXPLANATION" ]; then
echo "ERROR: Missing screenshot explanation for $BASENAME. Add it to SCREENSHOT_EXPLANATIONS in Step 6."
exit 1
fi
IMAGE_MARKDOWN="${IMAGE_MARKDOWN}
### ${TITLE}
![${BASENAME}](${REPO_URL}/${SCREENSHOTS_DIR}/${BASENAME})
${EXPLANATION}
"
done
# Write comment body to file to avoid shell interpretation issues with special characters
COMMENT_FILE=$(mktemp)
# If any uploads failed, append a section listing them with instructions
FAILED_SECTION=""
if [ ${#FAILED_UPLOADS[@]} -gt 0 ]; then
FAILED_SECTION="
## ⚠️ Failed Screenshot Uploads
The following screenshots could not be uploaded via the GitHub API after 3 retries.
**To add them:** drag-and-drop or paste these files into a PR comment manually:
"
for failed in "${FAILED_UPLOADS[@]}"; do
FAILED_SECTION="${FAILED_SECTION}
- \`$(basename "$failed")\` (local path: \`$failed\`)"
done
FAILED_SECTION="${FAILED_SECTION}
**Run status:** INCOMPLETE until the files above are manually attached and visible inline in the PR."
fi
cat > "$COMMENT_FILE" <<INNEREOF
## E2E Test Report
| # | Scenario | Result | API Evidence | Screenshot Evidence |
|---|----------|--------|-------------|-------------------|
${TEST_RESULTS_TABLE}
${IMAGE_MARKDOWN}
${FAILED_SECTION}
INNEREOF
POSTED_BODY=$(gh api "repos/${REPO}/issues/$PR_NUMBER/comments" -F body=@"$COMMENT_FILE" --jq '.body')
rm -f "$COMMENT_FILE"
```
**The PR comment MUST include:**
1. A summary table of all scenarios with PASS/FAIL and before/after API evidence
2. Every successfully uploaded screenshot rendered inline; any failed uploads listed with manual attachment instructions
3. A structured explanation below each screenshot covering: **Flow** (which scenario), **Steps** (exact actions taken to reach this state), **Evidence** (what this proves — pass/fail/data values). A bare "shows the page" caption is not acceptable.
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.
**Verify inline rendering after posting — this is required, not optional:**
```bash
# 1. Confirm the posted comment body contains inline image markdown syntax
if ! echo "$POSTED_BODY" | grep -q '!\['; then
echo "❌ FAIL: No inline image tags in posted comment body. Re-check IMAGE_MARKDOWN and re-post."
exit 1
fi
# 2. Verify at least one raw URL actually resolves (catches wrong branch name, wrong path, etc.)
FIRST_IMG_URL=$(echo "$POSTED_BODY" | grep -o 'https://raw.githubusercontent.com[^)]*' | head -1)
if [ -n "$FIRST_IMG_URL" ]; then
HTTP_STATUS=$(curl -s -o /dev/null -w "%{http_code}" --max-time 10 "$FIRST_IMG_URL")
if [ "$HTTP_STATUS" = "200" ]; then
echo "✅ Inline images confirmed and raw URL resolves (HTTP 200)"
else
echo "❌ FAIL: Raw image URL returned HTTP $HTTP_STATUS — images will not render inline."
echo " URL: $FIRST_IMG_URL"
echo " Check branch name, path, and that the push succeeded."
exit 1
fi
else
echo "⚠️ Could not extract a raw URL from the comment — verify manually."
fi
```
## Step 8: Evaluate test completeness and post a GitHub review
After posting the PR comment, evaluate whether the test run actually covered everything it needed to. This is NOT a rubber-stamp — be critical. Then post a formal GitHub review so the PR author and reviewers can see the verdict.
### 8a. Evaluate against the test plan
Re-read `$RESULTS_DIR/test-plan.md` (written in Step 2) and `$RESULTS_DIR/test-report.md` (written in Step 5). For each scenario in the plan, answer:
> **Note:** `test-report.md` is written in Step 5. If it doesn't exist, write it before proceeding here — see the Step 5 template. Do not skip evaluation because the file is missing; create it from your notes instead.
| Question | Pass criteria |
|----------|--------------|
| Was it tested? | Explicit steps were executed, not just described |
| Is there screenshot evidence? | At least one before/after screenshot per scenario |
| Did the core feature work correctly? | Expected state matches actual state |
| Were negative cases tested? | At least one failure/rejection case per feature |
| Was DB/API state verified (not just UI)? | Raw API response or DB query confirms state change |
Build a verdict:
- **APPROVE** — every scenario tested, evidence present, no bugs found or all bugs are minor/known
- **REQUEST_CHANGES** — one or more: untested scenarios, missing evidence, bugs found, data not verified
### 8b. Post the GitHub review
```bash
EVAL_FILE=$(mktemp)
# === STEP A: Write header ===
cat > "$EVAL_FILE" << 'ENDEVAL'
## 🧪 Test Evaluation
### Coverage checklist
ENDEVAL
# === STEP B: Append ONE line per scenario — do this BEFORE calculating verdict ===
# Format: "- ✅ **Scenario N name**: <what was done and verified>"
# or "- ❌ **Scenario N name**: <what is missing or broken>"
# Examples:
# echo "- ✅ **Scenario 1 Login flow**: tested, screenshot evidence present, auth token verified via API" >> "$EVAL_FILE"
# echo "- ❌ **Scenario 3 Cost logging**: NOT verified in DB — UI showed entry but raw SQL query was skipped" >> "$EVAL_FILE"
#
# !!! IMPORTANT: append ALL scenario lines here before proceeding to STEP C !!!
# === STEP C: Derive verdict from the checklist — runs AFTER all lines are appended ===
FAIL_COUNT=$(grep -c "^- ❌" "$EVAL_FILE" || true)
if [ "$FAIL_COUNT" -eq 0 ]; then
VERDICT="APPROVE"
else
VERDICT="REQUEST_CHANGES"
fi
# === STEP D: Append verdict section ===
cat >> "$EVAL_FILE" << ENDVERDICT
### Verdict
ENDVERDICT
if [ "$VERDICT" = "APPROVE" ]; then
echo "✅ All scenarios covered with evidence. No blocking issues found." >> "$EVAL_FILE"
else
echo "$FAIL_COUNT scenario(s) incomplete or have confirmed bugs. See ❌ items above." >> "$EVAL_FILE"
echo "" >> "$EVAL_FILE"
echo "**Required before merge:** address each ❌ item above." >> "$EVAL_FILE"
fi
# === STEP E: Post the review ===
gh api "repos/${REPO}/pulls/$PR_NUMBER/reviews" \
--method POST \
-f body="$(cat "$EVAL_FILE")" \
-f event="$VERDICT"
rm -f "$EVAL_FILE"
```
**Rules:**
- Never auto-approve without checking every scenario in the test plan
- `REQUEST_CHANGES` if ANY scenario is untested, lacks DB/API evidence, or has a confirmed bug
- The evaluation body must list every scenario explicitly (✅ or ❌) — not just the failures
- If you find new bugs during evaluation, add them to the request-changes body and (if `--fix` flag is set) fix them before posting
## Fix mode (--fix flag)
When `--fix` is present, the standard is HIGHER. Do not just note issues — FIX them immediately.
### Fix protocol for EVERY issue found (including UX issues):
1. **Identify** the root cause in the code — read the relevant source files
2. **Write a failing test first** (TDD): For backend bugs, write a test marked with `pytest.mark.xfail(reason="...")`. For frontend/Playwright bugs, write a test with `.fixme` annotation. Run it to confirm it fails as expected.
3. **Screenshot** the broken state: `agent-browser screenshot $RESULTS_DIR/{NN}-broken-{description}.png`
4. **Fix** the code in the worktree
5. **Rebuild** ONLY the affected service (not the whole stack):
```bash
cd $PLATFORM_DIR && docker compose up --build -d {service_name}
# e.g., docker compose up --build -d rest_server
# e.g., docker compose up --build -d frontend
```
6. **Wait** for the service to be ready (poll health endpoint)
7. **Re-test** the same scenario
8. **Screenshot** the fixed state: `agent-browser screenshot $RESULTS_DIR/{NN}-fixed-{description}.png`
9. **Remove the xfail/fixme marker** from the test written in step 2, and verify it passes
10. **Verify** the fix did not break other scenarios (run a quick smoke test)
11. **Commit and push** immediately:
```bash
cd $WORKTREE_PATH
git add -A
git commit -m "fix: {description of fix}"
git push
```
12. **Continue** to the next test scenario
### Fix loop (like pr-address)
```text
test scenario → find issue (bug OR UX problem) → screenshot broken state
→ fix code → rebuild affected service only → re-test → screenshot fixed state
→ verify no regressions → commit + push
→ repeat for next scenario
→ after ALL scenarios pass, run full re-test to verify everything together
```
**Key differences from non-fix mode:**
- UX issues count as bugs — fix them (bad alignment, confusing labels, missing loading states)
- Every fix MUST have a before/after screenshot pair proving it works
- Commit after EACH fix, not in a batch at the end
- The final re-test must produce a clean set of all-passing screenshots
## Known issues and workarounds
### Problem: "Database error finding user" on signup
**Cause:** Supabase auth service schema cache is stale after migration.
**Fix:** `docker restart supabase-auth && sleep 5` then retry signup.
### Problem: Copilot returns auth errors in subscription mode
**Cause:** `CHAT_USE_CLAUDE_CODE_SUBSCRIPTION=true` but `CLAUDE_CODE_OAUTH_TOKEN` is not set or expired.
**Fix:** Re-extract the OAuth token from macOS keychain (see step 3b, Option 1) and recreate the container (`docker compose up -d copilot_executor`). The backend auto-provisions `~/.claude/.credentials.json` from the env var on startup. No `npm install` or `claude login` needed — the SDK bundles its own CLI binary.
### Problem: agent-browser can't find chromium
**Cause:** The Dockerfile auto-provisions system chromium on all architectures (including ARM64). If your branch is behind `dev`, this may not be present yet.
**Fix:** Check if chromium exists: `which chromium || which chromium-browser`. If missing, install it: `apt-get install -y chromium` and set `AGENT_BROWSER_EXECUTABLE_PATH=/usr/bin/chromium` in the container environment.
### Problem: agent-browser selector matches multiple elements
**Cause:** `text=X` matches all elements containing that text.
**Fix:** Use `agent-browser snapshot` to get specific `ref=eNN` references, then use those: `agent-browser click eNN`.
### 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: 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`.
### Problem: Docker uses cached layers with old code (PR changes not visible)
**Cause:** `docker compose up --build` reuses cached `COPY` layers from previous builds. If the PR branch changes Python files but the previous build already cached that layer from `dev`, the container runs `dev` code.
**Fix:** Always use `docker compose build --no-cache` for the first build of a PR branch. Subsequent rebuilds within the same branch can use `--build`.
### Problem: `agent-browser open` loses login session
**Cause:** Without session persistence, `agent-browser open` starts fresh.
**Fix:** Use `--session-name pr-test` on ALL agent-browser commands. This auto-saves/restores cookies and localStorage across navigations. Alternatively, use `agent-browser eval "window.location.href = '...'"` to navigate within the same context.
### Problem: Supabase auth returns "Database error querying schema"
**Cause:** The database schema changed (migration ran) but supabase-auth has a stale schema cache.
**Fix:** `docker restart supabase-db && sleep 10 && docker restart supabase-auth && sleep 8`. If user data was lost, re-signup.

View File

@@ -0,0 +1,195 @@
---
name: setup-repo
description: Initialize a worktree-based repo layout for parallel development. Creates a main worktree, a reviews worktree for PR reviews, and N numbered work branches. Handles .env creation, dependency installation, and branchlet config. TRIGGER when user asks to set up the repo from scratch, initialize worktrees, bootstrap their dev environment, "setup repo", "setup worktrees", "initialize dev environment", "set up branches", or when a freshly cloned repo has no sibling worktrees.
user-invocable: true
args: "No arguments — interactive setup via prompts."
metadata:
author: autogpt-team
version: "1.0.0"
---
# Repository Setup
This skill sets up a worktree-based development layout from a freshly cloned repo. It creates:
- A **main** worktree (the primary checkout)
- A **reviews** worktree (for PR reviews)
- **N work branches** (branch1..branchN) for parallel development
## Step 1: Identify the repo
Determine the repo root and parent directory:
```bash
ROOT=$(git rev-parse --show-toplevel)
REPO_NAME=$(basename "$ROOT")
PARENT=$(dirname "$ROOT")
```
Detect if the repo is already inside a worktree layout by counting sibling worktrees (not just checking the directory name, which could be anything):
```bash
# Count worktrees that are siblings (live under $PARENT but aren't $ROOT itself)
SIBLING_COUNT=$(git worktree list --porcelain 2>/dev/null | grep "^worktree " | grep -c "$PARENT/" || true)
if [ "$SIBLING_COUNT" -gt 1 ]; then
echo "INFO: Existing worktree layout detected at $PARENT ($SIBLING_COUNT worktrees)"
# Use $ROOT as-is; skip renaming/restructuring
else
echo "INFO: Fresh clone detected, proceeding with setup"
fi
```
## Step 2: Ask the user questions
Use AskUserQuestion to gather setup preferences:
1. **How many parallel work branches do you need?** (Options: 4, 8, 16, or custom)
- These become `branch1` through `branchN`
2. **Which branch should be the base?** (Options: origin/master, origin/dev, or custom)
- All work branches and reviews will start from this
## Step 3: Fetch and set up branches
```bash
cd "$ROOT"
git fetch origin
# Create the reviews branch from base (skip if already exists)
if git show-ref --verify --quiet refs/heads/reviews; then
echo "INFO: Branch 'reviews' already exists, skipping"
else
git branch reviews <base-branch>
fi
# Create numbered work branches from base (skip if already exists)
for i in $(seq 1 "$COUNT"); do
if git show-ref --verify --quiet "refs/heads/branch$i"; then
echo "INFO: Branch 'branch$i' already exists, skipping"
else
git branch "branch$i" <base-branch>
fi
done
```
## Step 4: Create worktrees
Create worktrees as siblings to the main checkout:
```bash
if [ -d "$PARENT/reviews" ]; then
echo "INFO: Worktree '$PARENT/reviews' already exists, skipping"
else
git worktree add "$PARENT/reviews" reviews
fi
for i in $(seq 1 "$COUNT"); do
if [ -d "$PARENT/branch$i" ]; then
echo "INFO: Worktree '$PARENT/branch$i' already exists, skipping"
else
git worktree add "$PARENT/branch$i" "branch$i"
fi
done
```
## Step 5: Set up environment files
**Do NOT assume .env files exist.** For each worktree (including main if needed):
1. Check if `.env` exists in the source worktree for each path
2. If `.env` exists, copy it
3. If only `.env.default` or `.env.example` exists, copy that as `.env`
4. If neither exists, warn the user and list which env files are missing
Env file locations to check (same as the `/worktree` skill — keep these in sync):
- `autogpt_platform/.env`
- `autogpt_platform/backend/.env`
- `autogpt_platform/frontend/.env`
> **Note:** This env copying logic intentionally mirrors the `/worktree` skill's approach. If you update the path list or fallback logic here, update `/worktree` as well.
```bash
SOURCE="$ROOT"
WORKTREES="reviews"
for i in $(seq 1 "$COUNT"); do WORKTREES="$WORKTREES branch$i"; done
FOUND_ANY_ENV=0
for wt in $WORKTREES; do
TARGET="$PARENT/$wt"
for envpath in autogpt_platform autogpt_platform/backend autogpt_platform/frontend; do
if [ -f "$SOURCE/$envpath/.env" ]; then
FOUND_ANY_ENV=1
cp "$SOURCE/$envpath/.env" "$TARGET/$envpath/.env"
elif [ -f "$SOURCE/$envpath/.env.default" ]; then
FOUND_ANY_ENV=1
cp "$SOURCE/$envpath/.env.default" "$TARGET/$envpath/.env"
echo "NOTE: $wt/$envpath/.env was created from .env.default — you may need to edit it"
elif [ -f "$SOURCE/$envpath/.env.example" ]; then
FOUND_ANY_ENV=1
cp "$SOURCE/$envpath/.env.example" "$TARGET/$envpath/.env"
echo "NOTE: $wt/$envpath/.env was created from .env.example — you may need to edit it"
else
echo "WARNING: No .env, .env.default, or .env.example found at $SOURCE/$envpath/"
fi
done
done
if [ "$FOUND_ANY_ENV" -eq 0 ]; then
echo "WARNING: No environment files or templates were found in the source worktree."
# Use AskUserQuestion to confirm: "Continue setup without env files?"
# If the user declines, stop here and let them set up .env files first.
fi
```
## Step 6: Copy branchlet config
Copy `.branchlet.json` from main to each worktree so branchlet can manage sub-worktrees:
```bash
if [ -f "$ROOT/.branchlet.json" ]; then
for wt in $WORKTREES; do
cp "$ROOT/.branchlet.json" "$PARENT/$wt/.branchlet.json"
done
fi
```
## Step 7: Install dependencies
Install deps in all worktrees. Run these sequentially per worktree:
```bash
for wt in $WORKTREES; do
TARGET="$PARENT/$wt"
echo "=== Installing deps for $wt ==="
(cd "$TARGET/autogpt_platform/autogpt_libs" && poetry install) &&
(cd "$TARGET/autogpt_platform/backend" && poetry install && poetry run prisma generate) &&
(cd "$TARGET/autogpt_platform/frontend" && pnpm install) &&
echo "=== Done: $wt ===" ||
echo "=== FAILED: $wt ==="
done
```
This is slow. Run in background if possible and notify when complete.
## Step 8: Verify and report
After setup, verify and report to the user:
```bash
git worktree list
```
Summarize:
- Number of worktrees created
- Which env files were copied vs created from defaults vs missing
- Any warnings or errors encountered
## Final directory layout
```
parent/
main/ # Primary checkout (already exists)
reviews/ # PR review worktree
branch1/ # Work branch 1
branch2/ # Work branch 2
...
branchN/ # Work branch N
```

View File

@@ -0,0 +1,85 @@
---
name: worktree
description: Set up a new git worktree for parallel development. Creates the worktree, copies .env files, installs dependencies, and generates Prisma client. TRIGGER when user asks to set up a worktree, work on a branch in isolation, or needs a separate environment for a branch or PR.
user-invocable: true
args: "[name] — optional worktree name (e.g., 'AutoGPT7'). If omitted, uses next available AutoGPT<N>."
metadata:
author: autogpt-team
version: "3.0.0"
---
# Worktree Setup
## Create the worktree
Derive paths from the git toplevel. If a name is provided as argument, use it. Otherwise, check `git worktree list` and pick the next `AutoGPT<N>`.
```bash
ROOT=$(git rev-parse --show-toplevel)
PARENT=$(dirname "$ROOT")
# From an existing branch
git worktree add "$PARENT/<NAME>" <branch-name>
# From a new branch off dev
git worktree add -b <new-branch> "$PARENT/<NAME>" dev
```
## Copy environment files
Copy `.env` from the root worktree. Falls back to `.env.default` if `.env` doesn't exist.
```bash
ROOT=$(git rev-parse --show-toplevel)
TARGET="$(dirname "$ROOT")/<NAME>"
for envpath in autogpt_platform/backend autogpt_platform/frontend autogpt_platform; do
if [ -f "$ROOT/$envpath/.env" ]; then
cp "$ROOT/$envpath/.env" "$TARGET/$envpath/.env"
elif [ -f "$ROOT/$envpath/.env.default" ]; then
cp "$ROOT/$envpath/.env.default" "$TARGET/$envpath/.env"
fi
done
```
## Install dependencies
```bash
TARGET="$(dirname "$(git rev-parse --show-toplevel)")/<NAME>"
cd "$TARGET/autogpt_platform/autogpt_libs" && poetry install
cd "$TARGET/autogpt_platform/backend" && poetry install && poetry run prisma generate
cd "$TARGET/autogpt_platform/frontend" && pnpm install
```
Replace `<NAME>` with the actual worktree name (e.g., `AutoGPT7`).
## Running the app (optional)
Backend uses ports: 8001, 8002, 8003, 8005, 8006, 8007, 8008. Free them first if needed:
```bash
TARGET="$(dirname "$(git rev-parse --show-toplevel)")/<NAME>"
for port in 8001 8002 8003 8005 8006 8007 8008; do
lsof -ti :$port | xargs kill -9 2>/dev/null || true
done
cd "$TARGET/autogpt_platform/backend" && poetry run app
```
## CoPilot testing
SDK mode spawns a Claude subprocess — won't work inside Claude Code. Set `CHAT_USE_CLAUDE_AGENT_SDK=false` in `backend/.env` to use baseline mode.
## Cleanup
```bash
# Replace <NAME> with the actual worktree name (e.g., AutoGPT7)
git worktree remove "$(dirname "$(git rev-parse --show-toplevel)")/<NAME>"
```
## Alternative: Branchlet (optional)
If [branchlet](https://www.npmjs.com/package/branchlet) is installed:
```bash
branchlet create -n <name> -s <source-branch> -b <new-branch>
```

View File

@@ -0,0 +1,224 @@
---
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 that uses it
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. Hooks with non-trivial business logic
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
- 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

@@ -1,8 +1,12 @@
<!-- Clearly explain the need for these changes: -->
### Why / What / How
<!-- Why: Why does this PR exist? What problem does it solve, or what's broken/missing without it? -->
<!-- What: What does this PR change? Summarize the changes at a high level. -->
<!-- How: How does it work? Describe the approach, key implementation details, or architecture decisions. -->
### Changes 🏗️
<!-- Concisely describe all of the changes made in this pull request: -->
<!-- List the key changes. Keep it higher level than the diff but specific enough to highlight what's new/modified. -->
### Checklist 📋

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

@@ -5,12 +5,14 @@ on:
branches: [master, dev, ci-test*]
paths:
- ".github/workflows/platform-backend-ci.yml"
- ".github/workflows/scripts/get_package_version_from_lockfile.py"
- "autogpt_platform/backend/**"
- "autogpt_platform/autogpt_libs/**"
pull_request:
branches: [master, dev, release-*]
paths:
- ".github/workflows/platform-backend-ci.yml"
- ".github/workflows/scripts/get_package_version_from_lockfile.py"
- "autogpt_platform/backend/**"
- "autogpt_platform/autogpt_libs/**"
merge_group:
@@ -25,10 +27,91 @@ defaults:
working-directory: autogpt_platform/backend
jobs:
lint:
permissions:
contents: read
timeout-minutes: 10
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v6
- name: Set up Python 3.12
uses: actions/setup-python@v5
with:
python-version: "3.12"
- name: Set up Python dependency cache
uses: actions/cache@v5
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-py3.12-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
- name: Install Poetry
run: |
HEAD_POETRY_VERSION=$(python ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
echo "Using Poetry version ${HEAD_POETRY_VERSION}"
curl -sSL https://install.python-poetry.org | POETRY_VERSION=$HEAD_POETRY_VERSION python3 -
- name: Install Python dependencies
run: poetry install
- name: Run Linters
run: poetry run lint --skip-pyright
env:
CI: true
PLAIN_OUTPUT: True
type-check:
permissions:
contents: read
timeout-minutes: 10
strategy:
fail-fast: false
matrix:
python-version: ["3.11", "3.12", "3.13"]
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v6
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
- name: Set up Python dependency cache
uses: actions/cache@v5
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-py${{ matrix.python-version }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
- name: Install Poetry
run: |
HEAD_POETRY_VERSION=$(python ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
echo "Using Poetry version ${HEAD_POETRY_VERSION}"
curl -sSL https://install.python-poetry.org | POETRY_VERSION=$HEAD_POETRY_VERSION python3 -
- name: Install Python dependencies
run: poetry install
- name: Generate Prisma Client
run: poetry run prisma generate && poetry run gen-prisma-stub
- name: Run Pyright
run: poetry run pyright --pythonversion ${{ matrix.python-version }}
env:
CI: true
PLAIN_OUTPUT: True
test:
permissions:
contents: read
timeout-minutes: 30
timeout-minutes: 15
strategy:
fail-fast: false
matrix:
@@ -96,9 +179,9 @@ jobs:
uses: actions/cache@v5
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
key: poetry-${{ runner.os }}-py${{ matrix.python-version }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
- name: Install Poetry (Unix)
- name: Install Poetry
run: |
# Extract Poetry version from backend/poetry.lock
HEAD_POETRY_VERSION=$(python ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
@@ -156,22 +239,22 @@ jobs:
echo "Waiting for ClamAV daemon to start..."
max_attempts=60
attempt=0
until nc -z localhost 3310 || [ $attempt -eq $max_attempts ]; do
echo "ClamAV is unavailable - sleeping (attempt $((attempt+1))/$max_attempts)"
sleep 5
attempt=$((attempt+1))
done
if [ $attempt -eq $max_attempts ]; then
echo "ClamAV failed to start after $((max_attempts*5)) seconds"
echo "Checking ClamAV service logs..."
docker logs $(docker ps -q --filter "ancestor=clamav/clamav-debian:latest") 2>&1 | tail -50 || echo "No ClamAV container found"
exit 1
fi
echo "ClamAV is ready!"
# Verify ClamAV is responsive
echo "Testing ClamAV connection..."
timeout 10 bash -c 'echo "PING" | nc localhost 3310' || {
@@ -186,18 +269,15 @@ jobs:
DATABASE_URL: ${{ steps.supabase.outputs.DB_URL }}
DIRECT_URL: ${{ steps.supabase.outputs.DB_URL }}
- id: lint
name: Run Linter
run: poetry run lint
- name: Run pytest with coverage
run: |
if [[ "${{ 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
if: success() || (failure() && steps.lint.outcome == 'failure')
env:
LOG_LEVEL: ${{ runner.debug && 'DEBUG' || 'INFO' }}
DATABASE_URL: ${{ steps.supabase.outputs.DB_URL }}
@@ -209,6 +289,14 @@ jobs:
REDIS_PORT: "6379"
ENCRYPTION_KEY: "dvziYgz0KSK8FENhju0ZYi8-fRTfAdlz6YLhdB_jhNw=" # DO NOT USE IN PRODUCTION!!
- 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
PLAIN_OUTPUT: True
@@ -222,9 +310,3 @@ jobs:
# the backend service, docker composes, and examples
RABBITMQ_DEFAULT_USER: "rabbitmq_user_default"
RABBITMQ_DEFAULT_PASS: "k0VMxyIJF9S35f3x2uaw5IWAl6Y536O7"
# - name: Upload coverage reports to Codecov
# uses: codecov/codecov-action@v4
# with:
# token: ${{ secrets.CODECOV_TOKEN }}
# flags: backend,${{ runner.os }}

View File

@@ -120,175 +120,6 @@ jobs:
token: ${{ secrets.GITHUB_TOKEN }}
exitOnceUploaded: true
e2e_test:
name: end-to-end tests
runs-on: big-boi
steps:
- name: Checkout repository
uses: actions/checkout@v6
with:
submodules: recursive
- name: Set up Platform - Copy default supabase .env
run: |
cp ../.env.default ../.env
- name: Set up Platform - Copy backend .env and set OpenAI API key
run: |
cp ../backend/.env.default ../backend/.env
echo "OPENAI_INTERNAL_API_KEY=${{ secrets.OPENAI_API_KEY }}" >> ../backend/.env
env:
# Used by E2E test data script to generate embeddings for approved store agents
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
- name: Set up Platform - Set up Docker Buildx
uses: docker/setup-buildx-action@v3
with:
driver: docker-container
driver-opts: network=host
- name: Set up Platform - Expose GHA cache to docker buildx CLI
uses: crazy-max/ghaction-github-runtime@v3
- name: Set up Platform - Build Docker images (with cache)
working-directory: autogpt_platform
run: |
pip install pyyaml
# Resolve extends and generate a flat compose file that bake can understand
docker compose -f docker-compose.yml config > docker-compose.resolved.yml
# Add cache configuration to the resolved compose file
python ../.github/workflows/scripts/docker-ci-fix-compose-build-cache.py \
--source docker-compose.resolved.yml \
--cache-from "type=gha" \
--cache-to "type=gha,mode=max" \
--backend-hash "${{ hashFiles('autogpt_platform/backend/Dockerfile', 'autogpt_platform/backend/poetry.lock', 'autogpt_platform/backend/backend') }}" \
--frontend-hash "${{ hashFiles('autogpt_platform/frontend/Dockerfile', 'autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/src') }}" \
--git-ref "${{ 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
- name: Set up tests - Cache E2E test data
id: e2e-data-cache
uses: actions/cache@v5
with:
path: /tmp/e2e_test_data.sql
key: e2e-test-data-${{ hashFiles('autogpt_platform/backend/test/e2e_test_data.py', 'autogpt_platform/backend/migrations/**', '.github/workflows/platform-frontend-ci.yml') }}
- name: Set up Platform - Start Supabase DB + Auth
run: |
docker compose -f ../docker-compose.resolved.yml up -d db auth --no-build
echo "Waiting for database to be ready..."
timeout 60 sh -c 'until docker compose -f ../docker-compose.resolved.yml exec -T db pg_isready -U postgres 2>/dev/null; do sleep 2; done'
echo "Waiting for auth service to be ready..."
timeout 60 sh -c 'until docker compose -f ../docker-compose.resolved.yml exec -T db psql -U postgres -d postgres -c "SELECT 1 FROM auth.users LIMIT 1" 2>/dev/null; do sleep 2; done' || echo "Auth schema check timeout, continuing..."
- name: Set up Platform - Run migrations
run: |
echo "Running migrations..."
docker compose -f ../docker-compose.resolved.yml run --rm migrate
echo "✅ Migrations completed"
env:
NEXT_PUBLIC_PW_TEST: true
- name: Set up tests - Load cached E2E test data
if: steps.e2e-data-cache.outputs.cache-hit == 'true'
run: |
echo "✅ Found cached E2E test data, restoring..."
{
echo "SET session_replication_role = 'replica';"
cat /tmp/e2e_test_data.sql
echo "SET session_replication_role = 'origin';"
} | docker compose -f ../docker-compose.resolved.yml exec -T db psql -U postgres -d postgres -b
# Refresh materialized views after restore
docker compose -f ../docker-compose.resolved.yml exec -T db \
psql -U postgres -d postgres -b -c "SET search_path TO platform; SELECT refresh_store_materialized_views();" || true
echo "✅ E2E test data restored from cache"
- name: Set up Platform - Start (all other services)
run: |
docker compose -f ../docker-compose.resolved.yml up -d --no-build
echo "Waiting for rest_server to be ready..."
timeout 60 sh -c 'until curl -f http://localhost:8006/health 2>/dev/null; do sleep 2; done' || echo "Rest server health check timeout, continuing..."
env:
NEXT_PUBLIC_PW_TEST: true
- name: Set up tests - Create E2E test data
if: steps.e2e-data-cache.outputs.cache-hit != 'true'
run: |
echo "Creating E2E test data..."
docker cp ../backend/test/e2e_test_data.py $(docker compose -f ../docker-compose.resolved.yml ps -q rest_server):/tmp/e2e_test_data.py
docker compose -f ../docker-compose.resolved.yml exec -T rest_server sh -c "cd /app/autogpt_platform && python /tmp/e2e_test_data.py" || {
echo "❌ E2E test data creation failed!"
docker compose -f ../docker-compose.resolved.yml logs --tail=50 rest_server
exit 1
}
# Dump auth.users + platform schema for cache (two separate dumps)
echo "Dumping database for cache..."
{
docker compose -f ../docker-compose.resolved.yml exec -T db \
pg_dump -U postgres --data-only --column-inserts \
--table='auth.users' postgres
docker compose -f ../docker-compose.resolved.yml exec -T db \
pg_dump -U postgres --data-only --column-inserts \
--schema=platform \
--exclude-table='platform._prisma_migrations' \
--exclude-table='platform.apscheduler_jobs' \
--exclude-table='platform.apscheduler_jobs_batched_notifications' \
postgres
} > /tmp/e2e_test_data.sql
echo "✅ Database dump created for caching ($(wc -l < /tmp/e2e_test_data.sql) lines)"
- name: Set up tests - Enable corepack
run: corepack enable
- name: Set up tests - Set up Node
uses: actions/setup-node@v6
with:
node-version: "22.18.0"
cache: "pnpm"
cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
- 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
continue-on-error: false
- name: Upload Playwright report
if: always()
uses: actions/upload-artifact@v4
with:
name: playwright-report
path: playwright-report
if-no-files-found: ignore
retention-days: 3
- name: Upload Playwright test results
if: always()
uses: actions/upload-artifact@v4
with:
name: playwright-test-results
path: test-results
if-no-files-found: ignore
retention-days: 3
- name: Print Final Docker Compose logs
if: always()
run: docker compose -f ../docker-compose.resolved.yml logs
integration_test:
runs-on: ubuntu-latest
needs: setup
@@ -317,3 +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

@@ -1,14 +1,18 @@
name: AutoGPT Platform - Frontend CI
name: AutoGPT Platform - Full-stack CI
on:
push:
branches: [master, dev]
paths:
- ".github/workflows/platform-fullstack-ci.yml"
- ".github/workflows/scripts/docker-ci-fix-compose-build-cache.py"
- ".github/workflows/scripts/get_package_version_from_lockfile.py"
- "autogpt_platform/**"
pull_request:
paths:
- ".github/workflows/platform-fullstack-ci.yml"
- ".github/workflows/scripts/docker-ci-fix-compose-build-cache.py"
- ".github/workflows/scripts/get_package_version_from_lockfile.py"
- "autogpt_platform/**"
merge_group:
@@ -24,42 +28,28 @@ defaults:
jobs:
setup:
runs-on: ubuntu-latest
outputs:
cache-key: ${{ steps.cache-key.outputs.key }}
steps:
- name: Checkout repository
uses: actions/checkout@v6
- name: Set up Node.js
uses: actions/setup-node@v6
with:
node-version: "22.18.0"
- name: Enable corepack
run: corepack enable
- name: Generate cache key
id: cache-key
run: echo "key=${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}" >> $GITHUB_OUTPUT
- name: Cache dependencies
uses: actions/cache@v5
- name: Set up Node
uses: actions/setup-node@v6
with:
path: ~/.pnpm-store
key: ${{ steps.cache-key.outputs.key }}
restore-keys: |
${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml') }}
${{ runner.os }}-pnpm-
node-version: "22.18.0"
cache: "pnpm"
cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
- name: Install dependencies
- name: Install dependencies to populate cache
run: pnpm install --frozen-lockfile
types:
runs-on: big-boi
check-api-types:
name: check API types
runs-on: ubuntu-latest
needs: setup
strategy:
fail-fast: false
steps:
- name: Checkout repository
@@ -67,70 +57,279 @@ jobs:
with:
submodules: recursive
- name: Set up Node.js
# ------------------------ Backend setup ------------------------
- name: Set up Backend - Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.12"
- name: Set up Backend - Install Poetry
working-directory: autogpt_platform/backend
run: |
POETRY_VERSION=$(python ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
echo "Installing Poetry version ${POETRY_VERSION}"
curl -sSL https://install.python-poetry.org | POETRY_VERSION=$POETRY_VERSION python3 -
- name: Set up Backend - Set up dependency cache
uses: actions/cache@v5
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
- name: Set up Backend - Install dependencies
working-directory: autogpt_platform/backend
run: poetry install
- name: Set up Backend - Generate Prisma client
working-directory: autogpt_platform/backend
run: poetry run prisma generate && poetry run gen-prisma-stub
- name: Set up Frontend - Export OpenAPI schema from Backend
working-directory: autogpt_platform/backend
run: poetry run export-api-schema --output ../frontend/src/app/api/openapi.json
# ------------------------ Frontend setup ------------------------
- name: Set up Frontend - Enable corepack
run: corepack enable
- name: Set up Frontend - Set up Node
uses: actions/setup-node@v6
with:
node-version: "22.18.0"
cache: "pnpm"
cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
- name: Enable corepack
run: corepack enable
- name: Copy default supabase .env
run: |
cp ../.env.default ../.env
- name: Copy backend .env
run: |
cp ../backend/.env.default ../backend/.env
- name: Run docker compose
run: |
docker compose -f ../docker-compose.yml --profile local up -d deps_backend
- name: Restore dependencies cache
uses: actions/cache@v5
with:
path: ~/.pnpm-store
key: ${{ needs.setup.outputs.cache-key }}
restore-keys: |
${{ runner.os }}-pnpm-
- name: Install dependencies
- name: Set up Frontend - Install dependencies
run: pnpm install --frozen-lockfile
- name: Setup .env
run: cp .env.default .env
- name: Wait for services to be ready
run: |
echo "Waiting for rest_server to be ready..."
timeout 60 sh -c 'until curl -f http://localhost:8006/health 2>/dev/null; do sleep 2; done' || echo "Rest server health check timeout, continuing..."
echo "Waiting for database to be ready..."
timeout 60 sh -c 'until docker compose -f ../docker-compose.yml exec -T db pg_isready -U postgres 2>/dev/null; do sleep 2; done' || echo "Database ready check timeout, continuing..."
- name: Generate API queries
run: pnpm generate:api:force
- name: Set up Frontend - Format OpenAPI schema
id: format-schema
run: pnpm prettier --write ./src/app/api/openapi.json
- name: Check for API schema changes
run: |
if ! git diff --exit-code src/app/api/openapi.json; then
echo "❌ API schema changes detected in src/app/api/openapi.json"
echo ""
echo "The openapi.json file has been modified after running 'pnpm generate:api-all'."
echo "The openapi.json file has been modified after exporting the API schema."
echo "This usually means changes have been made in the BE endpoints without updating the Frontend."
echo "The API schema is now out of sync with the Front-end queries."
echo ""
echo "To fix this:"
echo "1. Pull the backend 'docker compose pull && docker compose up -d --build --force-recreate'"
echo "2. Run 'pnpm generate:api' locally"
echo "3. Run 'pnpm types' locally"
echo "4. Fix any TypeScript errors that may have been introduced"
echo "5. Commit and push your changes"
echo "\nIn the backend directory:"
echo "1. Run 'poetry run export-api-schema --output ../frontend/src/app/api/openapi.json'"
echo "\nIn the frontend directory:"
echo "2. Run 'pnpm prettier --write src/app/api/openapi.json'"
echo "3. Run 'pnpm generate:api'"
echo "4. Run 'pnpm types'"
echo "5. Fix any TypeScript errors that may have been introduced"
echo "6. Commit and push your changes"
echo ""
exit 1
else
echo "✅ No API schema changes detected"
fi
- name: Run Typescript checks
- name: Set up Frontend - Generate API client
id: generate-api-client
run: pnpm orval --config ./orval.config.ts
# Continue with type generation & check even if there are schema changes
if: success() || (steps.format-schema.outcome == 'success')
- name: Check for TypeScript errors
run: pnpm types
if: success() || (steps.generate-api-client.outcome == 'success')
e2e_test:
name: end-to-end tests
runs-on: big-boi
steps:
- name: Checkout repository
uses: actions/checkout@v6
with:
submodules: recursive
- name: Set up Platform - Copy default supabase .env
run: |
cp ../.env.default ../.env
- name: Set up Platform - Copy backend .env and set OpenAI API key
run: |
cp ../backend/.env.default ../backend/.env
echo "OPENAI_INTERNAL_API_KEY=${{ secrets.OPENAI_API_KEY }}" >> ../backend/.env
env:
# Used by E2E test data script to generate embeddings for approved store agents
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
- name: Set up Platform - Set up Docker Buildx
uses: docker/setup-buildx-action@v3
with:
driver: docker-container
driver-opts: network=host
- name: Set up Platform - Expose GHA cache to docker buildx CLI
uses: crazy-max/ghaction-github-runtime@v4
- name: Set up Platform - Build Docker images (with cache)
working-directory: autogpt_platform
run: |
pip install pyyaml
# Resolve extends and generate a flat compose file that bake can understand
export NEXT_PUBLIC_SOURCEMAPS NEXT_PUBLIC_PW_TEST
docker compose -f docker-compose.yml config > docker-compose.resolved.yml
# Ensure NEXT_PUBLIC_SOURCEMAPS is in resolved compose
# (docker compose config on some versions drops this arg)
if ! grep -q "NEXT_PUBLIC_SOURCEMAPS" docker-compose.resolved.yml; then
echo "Injecting NEXT_PUBLIC_SOURCEMAPS into resolved compose (docker compose config dropped it)"
sed -i '/NEXT_PUBLIC_PW_TEST/a\ NEXT_PUBLIC_SOURCEMAPS: "true"' docker-compose.resolved.yml
fi
# Add cache configuration to the resolved compose file
python ../.github/workflows/scripts/docker-ci-fix-compose-build-cache.py \
--source docker-compose.resolved.yml \
--cache-from "type=gha" \
--cache-to "type=gha,mode=max" \
--backend-hash "${{ hashFiles('autogpt_platform/backend/Dockerfile', 'autogpt_platform/backend/poetry.lock', 'autogpt_platform/backend/backend/**') }}" \
--frontend-hash "${{ hashFiles('autogpt_platform/frontend/Dockerfile', 'autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/src/**') }}-sourcemaps" \
--git-ref "${{ 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
uses: actions/cache@v5
with:
path: /tmp/e2e_test_data.sql
key: e2e-test-data-${{ hashFiles('autogpt_platform/backend/test/e2e_test_data.py', 'autogpt_platform/backend/migrations/**', '.github/workflows/platform-fullstack-ci.yml') }}
- name: Set up Platform - Start Supabase DB + Auth
run: |
docker compose -f ../docker-compose.resolved.yml up -d db auth --no-build
echo "Waiting for database to be ready..."
timeout 60 sh -c 'until docker compose -f ../docker-compose.resolved.yml exec -T db pg_isready -U postgres 2>/dev/null; do sleep 2; done'
echo "Waiting for auth service to be ready..."
timeout 60 sh -c 'until docker compose -f ../docker-compose.resolved.yml exec -T db psql -U postgres -d postgres -c "SELECT 1 FROM auth.users LIMIT 1" 2>/dev/null; do sleep 2; done' || echo "Auth schema check timeout, continuing..."
- name: Set up Platform - Run migrations
run: |
echo "Running migrations..."
docker compose -f ../docker-compose.resolved.yml run --rm migrate
echo "✅ Migrations completed"
env:
NEXT_PUBLIC_PW_TEST: true
- name: Set up tests - Load cached E2E test data
if: steps.e2e-data-cache.outputs.cache-hit == 'true'
run: |
echo "✅ Found cached E2E test data, restoring..."
{
echo "SET session_replication_role = 'replica';"
cat /tmp/e2e_test_data.sql
echo "SET session_replication_role = 'origin';"
} | docker compose -f ../docker-compose.resolved.yml exec -T db psql -U postgres -d postgres -b
# Refresh materialized views after restore
docker compose -f ../docker-compose.resolved.yml exec -T db \
psql -U postgres -d postgres -b -c "SET search_path TO platform; SELECT refresh_store_materialized_views();" || true
echo "✅ E2E test data restored from cache"
- name: Set up Platform - Start (all other services)
run: |
docker compose -f ../docker-compose.resolved.yml up -d --no-build
echo "Waiting for rest_server to be ready..."
timeout 60 sh -c 'until curl -f http://localhost:8006/health 2>/dev/null; do sleep 2; done' || echo "Rest server health check timeout, continuing..."
env:
NEXT_PUBLIC_PW_TEST: true
- name: Set up tests - Create E2E test data
if: steps.e2e-data-cache.outputs.cache-hit != 'true'
run: |
echo "Creating E2E test data..."
docker cp ../backend/test/e2e_test_data.py $(docker compose -f ../docker-compose.resolved.yml ps -q rest_server):/tmp/e2e_test_data.py
docker compose -f ../docker-compose.resolved.yml exec -T rest_server sh -c "cd /app/autogpt_platform && python /tmp/e2e_test_data.py" || {
echo "❌ E2E test data creation failed!"
docker compose -f ../docker-compose.resolved.yml logs --tail=50 rest_server
exit 1
}
# Dump auth.users + platform schema for cache (two separate dumps)
echo "Dumping database for cache..."
{
docker compose -f ../docker-compose.resolved.yml exec -T db \
pg_dump -U postgres --data-only --column-inserts \
--table='auth.users' postgres
docker compose -f ../docker-compose.resolved.yml exec -T db \
pg_dump -U postgres --data-only --column-inserts \
--schema=platform \
--exclude-table='platform._prisma_migrations' \
--exclude-table='platform.apscheduler_jobs' \
--exclude-table='platform.apscheduler_jobs_batched_notifications' \
postgres
} > /tmp/e2e_test_data.sql
echo "✅ Database dump created for caching ($(wc -l < /tmp/e2e_test_data.sql) lines)"
- name: Set up tests - Enable corepack
run: corepack enable
- name: Set up tests - Set up Node
uses: actions/setup-node@v6
with:
node-version: "22.18.0"
cache: "pnpm"
cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
- 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
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
with:
name: playwright-report
path: autogpt_platform/frontend/playwright-report
if-no-files-found: ignore
retention-days: 3
- name: Upload Playwright test results
if: always()
uses: actions/upload-artifact@v4
with:
name: playwright-test-results
path: autogpt_platform/frontend/test-results
if-no-files-found: ignore
retention-days: 3
- name: Print Final Docker Compose logs
if: always()
run: docker compose -f ../docker-compose.resolved.yml logs

10
.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 +183,13 @@ autogpt_platform/backend/settings.py
*.ign.*
.test-contents
**/.claude/settings.local.json
.claude/settings.local.json
CLAUDE.local.md
/autogpt_platform/backend/logs
# Test database
test.db
.next
# Implementation plans (generated by AI agents)
plans/

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

1
.nvmrc Normal file
View File

@@ -0,0 +1 @@
22

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

467
.secrets.baseline Normal file
View File

@@ -0,0 +1,467 @@
{
"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_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$",
"pnpm-lock\\.yaml$",
"\\.env\\.(default|example|template)$",
"__pycache__",
"_test\\.py$",
"test_.*\\.py$",
"conftest\\.py$",
"poetry\\.lock$",
"node_modules"
]
}
],
"results": {
"autogpt_platform/backend/backend/api/external/v1/integrations.py": [
{
"type": "Secret Keyword",
"filename": "autogpt_platform/backend/backend/api/external/v1/integrations.py",
"hashed_secret": "665b1e3851eefefa3fb878654292f16597d25155",
"is_verified": false,
"line_number": 289
}
],
"autogpt_platform/backend/backend/blocks/airtable/_config.py": [
{
"type": "Secret Keyword",
"filename": "autogpt_platform/backend/backend/blocks/airtable/_config.py",
"hashed_secret": "57e168b03afb7c1ee3cdc4ee3db2fe1cc6e0df26",
"is_verified": false,
"line_number": 29
}
],
"autogpt_platform/backend/backend/blocks/dataforseo/_config.py": [
{
"type": "Secret Keyword",
"filename": "autogpt_platform/backend/backend/blocks/dataforseo/_config.py",
"hashed_secret": "32ce93887331fa5d192f2876ea15ec000c7d58b8",
"is_verified": false,
"line_number": 12
}
],
"autogpt_platform/backend/backend/blocks/github/checks.py": [
{
"type": "Hex High Entropy String",
"filename": "autogpt_platform/backend/backend/blocks/github/checks.py",
"hashed_secret": "8ac6f92737d8586790519c5d7bfb4d2eb172c238",
"is_verified": false,
"line_number": 108
}
],
"autogpt_platform/backend/backend/blocks/github/ci.py": [
{
"type": "Hex High Entropy String",
"filename": "autogpt_platform/backend/backend/blocks/github/ci.py",
"hashed_secret": "90bd1b48e958257948487b90bee080ba5ed00caa",
"is_verified": false,
"line_number": 123
}
],
"autogpt_platform/backend/backend/blocks/github/example_payloads/pull_request.synchronize.json": [
{
"type": "Hex High Entropy String",
"filename": "autogpt_platform/backend/backend/blocks/github/example_payloads/pull_request.synchronize.json",
"hashed_secret": "f96896dafced7387dcd22343b8ea29d3d2c65663",
"is_verified": false,
"line_number": 42
},
{
"type": "Hex High Entropy String",
"filename": "autogpt_platform/backend/backend/blocks/github/example_payloads/pull_request.synchronize.json",
"hashed_secret": "b80a94d5e70bedf4f5f89d2f5a5255cc9492d12e",
"is_verified": false,
"line_number": 193
},
{
"type": "Hex High Entropy String",
"filename": "autogpt_platform/backend/backend/blocks/github/example_payloads/pull_request.synchronize.json",
"hashed_secret": "75b17e517fe1b3136394f6bec80c4f892da75e42",
"is_verified": false,
"line_number": 344
},
{
"type": "Hex High Entropy String",
"filename": "autogpt_platform/backend/backend/blocks/github/example_payloads/pull_request.synchronize.json",
"hashed_secret": "b0bfb5e4e2394e7f8906e5ed1dffd88b2bc89dd5",
"is_verified": false,
"line_number": 534
}
],
"autogpt_platform/backend/backend/blocks/github/statuses.py": [
{
"type": "Hex High Entropy String",
"filename": "autogpt_platform/backend/backend/blocks/github/statuses.py",
"hashed_secret": "8ac6f92737d8586790519c5d7bfb4d2eb172c238",
"is_verified": false,
"line_number": 85
}
],
"autogpt_platform/backend/backend/blocks/google/docs.py": [
{
"type": "Hex High Entropy String",
"filename": "autogpt_platform/backend/backend/blocks/google/docs.py",
"hashed_secret": "c95da0c6696342c867ef0c8258d2f74d20fd94d4",
"is_verified": false,
"line_number": 203
}
],
"autogpt_platform/backend/backend/blocks/google/sheets.py": [
{
"type": "Base64 High Entropy String",
"filename": "autogpt_platform/backend/backend/blocks/google/sheets.py",
"hashed_secret": "bd5a04fa3667e693edc13239b6d310c5c7a8564b",
"is_verified": false,
"line_number": 57
}
],
"autogpt_platform/backend/backend/blocks/linear/_config.py": [
{
"type": "Secret Keyword",
"filename": "autogpt_platform/backend/backend/blocks/linear/_config.py",
"hashed_secret": "b37f020f42d6d613b6ce30103e4d408c4499b3bb",
"is_verified": false,
"line_number": 53
}
],
"autogpt_platform/backend/backend/blocks/medium.py": [
{
"type": "Hex High Entropy String",
"filename": "autogpt_platform/backend/backend/blocks/medium.py",
"hashed_secret": "ff998abc1ce6d8f01a675fa197368e44c8916e9c",
"is_verified": false,
"line_number": 131
}
],
"autogpt_platform/backend/backend/blocks/replicate/replicate_block.py": [
{
"type": "Hex High Entropy String",
"filename": "autogpt_platform/backend/backend/blocks/replicate/replicate_block.py",
"hashed_secret": "8bbdd6f26368f58ea4011d13d7f763cb662e66f0",
"is_verified": false,
"line_number": 55
}
],
"autogpt_platform/backend/backend/blocks/slant3d/webhook.py": [
{
"type": "Hex High Entropy String",
"filename": "autogpt_platform/backend/backend/blocks/slant3d/webhook.py",
"hashed_secret": "36263c76947443b2f6e6b78153967ac4a7da99f9",
"is_verified": false,
"line_number": 100
}
],
"autogpt_platform/backend/backend/blocks/talking_head.py": [
{
"type": "Base64 High Entropy String",
"filename": "autogpt_platform/backend/backend/blocks/talking_head.py",
"hashed_secret": "44ce2d66222529eea4a32932823466fc0601c799",
"is_verified": false,
"line_number": 113
}
],
"autogpt_platform/backend/backend/blocks/wordpress/_config.py": [
{
"type": "Secret Keyword",
"filename": "autogpt_platform/backend/backend/blocks/wordpress/_config.py",
"hashed_secret": "e62679512436161b78e8a8d68c8829c2a1031ccb",
"is_verified": false,
"line_number": 17
}
],
"autogpt_platform/backend/backend/util/cache.py": [
{
"type": "Secret Keyword",
"filename": "autogpt_platform/backend/backend/util/cache.py",
"hashed_secret": "37f0c918c3fa47ca4a70e42037f9f123fdfbc75b",
"is_verified": false,
"line_number": 449
}
],
"autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/helpers.ts": [
{
"type": "Secret Keyword",
"filename": "autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/helpers.ts",
"hashed_secret": "5baa61e4c9b93f3f0682250b6cf8331b7ee68fd8",
"is_verified": false,
"line_number": 6
}
],
"autogpt_platform/frontend/src/app/(platform)/dictionaries/en.json": [
{
"type": "Secret Keyword",
"filename": "autogpt_platform/frontend/src/app/(platform)/dictionaries/en.json",
"hashed_secret": "8be3c943b1609fffbfc51aad666d0a04adf83c9d",
"is_verified": false,
"line_number": 5
}
],
"autogpt_platform/frontend/src/app/(platform)/dictionaries/es.json": [
{
"type": "Secret Keyword",
"filename": "autogpt_platform/frontend/src/app/(platform)/dictionaries/es.json",
"hashed_secret": "5a6d1c612954979ea99ee33dbb2d231b00f6ac0a",
"is_verified": false,
"line_number": 5
}
],
"autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/AgentInputsReadOnly/helpers.ts": [
{
"type": "Secret Keyword",
"filename": "autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/AgentInputsReadOnly/helpers.ts",
"hashed_secret": "cf678cab87dc1f7d1b95b964f15375e088461679",
"is_verified": false,
"line_number": 6
},
{
"type": "Secret Keyword",
"filename": "autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/AgentInputsReadOnly/helpers.ts",
"hashed_secret": "f72cbb45464d487064610c5411c576ca4019d380",
"is_verified": false,
"line_number": 8
}
],
"autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentModal/components/ModalRunSection/helpers.ts": [
{
"type": "Secret Keyword",
"filename": "autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentModal/components/ModalRunSection/helpers.ts",
"hashed_secret": "cf678cab87dc1f7d1b95b964f15375e088461679",
"is_verified": false,
"line_number": 5
},
{
"type": "Secret Keyword",
"filename": "autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentModal/components/ModalRunSection/helpers.ts",
"hashed_secret": "f72cbb45464d487064610c5411c576ca4019d380",
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"autogpt_platform/frontend/src/lib/autogpt-server-api/utils.ts": [
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}

View File

@@ -1,6 +1,6 @@
# AutoGPT Platform Contribution Guide
This guide provides context for Codex when updating the **autogpt_platform** folder.
This guide provides context for coding agents when updating the **autogpt_platform** folder.
## Directory overview
@@ -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`).

1
CLAUDE.md Normal file
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@@ -0,0 +1 @@
@AGENTS.md

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@@ -83,13 +83,13 @@ The AutoGPT frontend is where users interact with our powerful AI automation pla
**Agent Builder:** For those who want to customize, our intuitive, low-code interface allows you to design and configure your own AI agents.
**Workflow Management:** Build, modify, and optimize your automation workflows with ease. You build your agent by connecting blocks, where each block performs a single action.
**Workflow Management:** Build, modify, and optimize your automation workflows with ease. You build your agent by connecting blocks, where each block performs a single action.
**Deployment Controls:** Manage the lifecycle of your agents, from testing to production.
**Ready-to-Use Agents:** Don't want to build? Simply select from our library of pre-configured agents and put them to work immediately.
**Agent Interaction:** Whether you've built your own or are using pre-configured agents, easily run and interact with them through our user-friendly interface.
**Agent Interaction:** Whether you've built your own or are using pre-configured agents, easily run and interact with them through our user-friendly interface.
**Monitoring and Analytics:** Keep track of your agents' performance and gain insights to continually improve your automation processes.

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@@ -1,2 +1,3 @@
*.ignore.*
*.ign.*
*.ign.*
.application.logs

120
autogpt_platform/AGENTS.md Normal file
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@@ -0,0 +1,120 @@
# AutoGPT Platform
This file provides guidance to coding agents when working with code in this repository.
## Repository Overview
AutoGPT Platform is a monorepo containing:
- **Backend** (`backend`): Python FastAPI server with async support
- **Frontend** (`frontend`): Next.js React application
- **Shared Libraries** (`autogpt_libs`): Common Python utilities
## Component Documentation
- **Backend**: See @backend/AGENTS.md for backend-specific commands, architecture, and development tasks
- **Frontend**: See @frontend/AGENTS.md for frontend-specific commands, architecture, and development patterns
## Key Concepts
1. **Agent Graphs**: Workflow definitions stored as JSON, executed by the backend
2. **Blocks**: Reusable components in `backend/backend/blocks/` that perform specific tasks
3. **Integrations**: OAuth and API connections stored per user
4. **Store**: Marketplace for sharing agent templates
5. **Virus Scanning**: ClamAV integration for file upload security
### Environment Configuration
#### Configuration Files
- **Backend**: `backend/.env.default` (defaults) → `backend/.env` (user overrides)
- **Frontend**: `frontend/.env.default` (defaults) → `frontend/.env` (user overrides)
- **Platform**: `.env.default` (Supabase/shared defaults) → `.env` (user overrides)
#### Docker Environment Loading Order
1. `.env.default` files provide base configuration (tracked in git)
2. `.env` files provide user-specific overrides (gitignored)
3. Docker Compose `environment:` sections provide service-specific overrides
4. Shell environment variables have highest precedence
#### Key Points
- All services use hardcoded defaults in docker-compose files (no `${VARIABLE}` substitutions)
- The `env_file` directive loads variables INTO containers at runtime
- Backend/Frontend services use YAML anchors for consistent configuration
- Supabase services (`db/docker/docker-compose.yml`) follow the same pattern
### Branching Strategy
- **`dev`** is the main development branch. All PRs should target `dev`.
- **`master`** is the production branch. Only used for production releases.
### Creating Pull Requests
- Create the PR against the `dev` branch of the repository.
- **Split PRs by concern** — each PR should have a single clear purpose. For example, "usage tracking" and "credit charging" should be separate PRs even if related. Combining multiple concerns makes it harder for reviewers to understand what belongs to what.
- Ensure the branch name is descriptive (e.g., `feature/add-new-block`)
- Use conventional commit messages (see below)
- **Structure the PR description with Why / What / How** — Why: the motivation (what problem it solves, what's broken/missing without it); What: high-level summary of changes; How: approach, key implementation details, or architecture decisions. Reviewers need all three to judge whether the approach fits the problem.
- Fill out the .github/PULL_REQUEST_TEMPLATE.md template as the PR description
- Always use `--body-file` to pass PR body — avoids shell interpretation of backticks and special characters:
```bash
PR_BODY=$(mktemp)
cat > "$PR_BODY" << 'PREOF'
## Summary
- use `backticks` freely here
PREOF
gh pr create --title "..." --body-file "$PR_BODY" --base dev
rm "$PR_BODY"
```
- Run the github pre-commit hooks to ensure code quality.
### Test-Driven Development (TDD)
When fixing a bug or adding a feature, follow a test-first approach:
1. **Write a failing test first** — create a test that reproduces the bug or validates the new behavior, marked with `@pytest.mark.xfail` (backend) or `.fixme` (Playwright). Run it to confirm it fails for the right reason.
2. **Implement the fix/feature** — write the minimal code to make the test pass.
3. **Remove the xfail marker** — once the test passes, remove the `xfail`/`.fixme` annotation and run the full test suite to confirm nothing else broke.
This ensures every change is covered by a test and that the test actually validates the intended behavior.
### Reviewing/Revising Pull Requests
Use `/pr-review` to review a PR or `/pr-address` to address comments.
When fetching comments manually:
- `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews --paginate` — top-level reviews
- `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments --paginate` — inline review comments (always paginate to avoid missing comments beyond page 1)
- `gh api repos/Significant-Gravitas/AutoGPT/issues/{N}/comments` — PR conversation comments
### Conventional Commits
Use this format for commit messages and Pull Request titles:
**Conventional Commit Types:**
- `feat`: Introduces a new feature to the codebase
- `fix`: Patches a bug in the codebase
- `refactor`: Code change that neither fixes a bug nor adds a feature; also applies to removing features
- `ci`: Changes to CI configuration
- `docs`: Documentation-only changes
- `dx`: Improvements to the developer experience
**Recommended Base Scopes:**
- `platform`: Changes affecting both frontend and backend
- `frontend`
- `backend`
- `infra`
- `blocks`: Modifications/additions of individual blocks
**Subscope Examples:**
- `backend/executor`
- `backend/db`
- `frontend/builder` (includes changes to the block UI component)
- `infra/prod`
Use these scopes and subscopes for clarity and consistency in commit messages.

View File

@@ -1,95 +1 @@
# CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
## Repository Overview
AutoGPT Platform is a monorepo containing:
- **Backend** (`backend`): Python FastAPI server with async support
- **Frontend** (`frontend`): Next.js React application
- **Shared Libraries** (`autogpt_libs`): Common Python utilities
## Component Documentation
- **Backend**: See @backend/CLAUDE.md for backend-specific commands, architecture, and development tasks
- **Frontend**: See @frontend/CLAUDE.md for frontend-specific commands, architecture, and development patterns
## Key Concepts
1. **Agent Graphs**: Workflow definitions stored as JSON, executed by the backend
2. **Blocks**: Reusable components in `backend/backend/blocks/` that perform specific tasks
3. **Integrations**: OAuth and API connections stored per user
4. **Store**: Marketplace for sharing agent templates
5. **Virus Scanning**: ClamAV integration for file upload security
### Environment Configuration
#### Configuration Files
- **Backend**: `backend/.env.default` (defaults) → `backend/.env` (user overrides)
- **Frontend**: `frontend/.env.default` (defaults) → `frontend/.env` (user overrides)
- **Platform**: `.env.default` (Supabase/shared defaults) → `.env` (user overrides)
#### Docker Environment Loading Order
1. `.env.default` files provide base configuration (tracked in git)
2. `.env` files provide user-specific overrides (gitignored)
3. Docker Compose `environment:` sections provide service-specific overrides
4. Shell environment variables have highest precedence
#### Key Points
- All services use hardcoded defaults in docker-compose files (no `${VARIABLE}` substitutions)
- The `env_file` directive loads variables INTO containers at runtime
- Backend/Frontend services use YAML anchors for consistent configuration
- Supabase services (`db/docker/docker-compose.yml`) follow the same pattern
### Branching Strategy
- **`dev`** is the main development branch. All PRs should target `dev`.
- **`master`** is the production branch. Only used for production releases.
### Creating Pull Requests
- Create the PR against the `dev` branch of the repository.
- Ensure the branch name is descriptive (e.g., `feature/add-new-block`)
- Use conventional commit messages (see below)
- Fill out the .github/PULL_REQUEST_TEMPLATE.md template as the PR description
- Run the github pre-commit hooks to ensure code quality.
### Reviewing/Revising Pull Requests
- When the user runs /pr-comments or tries to fetch them, also run gh api /repos/Significant-Gravitas/AutoGPT/pulls/[issuenum]/reviews to get the reviews
- Use gh api /repos/Significant-Gravitas/AutoGPT/pulls/[issuenum]/reviews/[review_id]/comments to get the review contents
- Use gh api /repos/Significant-Gravitas/AutoGPT/issues/9924/comments to get the pr specific comments
### Conventional Commits
Use this format for commit messages and Pull Request titles:
**Conventional Commit Types:**
- `feat`: Introduces a new feature to the codebase
- `fix`: Patches a bug in the codebase
- `refactor`: Code change that neither fixes a bug nor adds a feature; also applies to removing features
- `ci`: Changes to CI configuration
- `docs`: Documentation-only changes
- `dx`: Improvements to the developer experience
**Recommended Base Scopes:**
- `platform`: Changes affecting both frontend and backend
- `frontend`
- `backend`
- `infra`
- `blocks`: Modifications/additions of individual blocks
**Subscope Examples:**
- `backend/executor`
- `backend/db`
- `frontend/builder` (includes changes to the block UI component)
- `infra/prod`
Use these scopes and subscopes for clarity and consistency in commit messages.
@AGENTS.md

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@@ -0,0 +1,40 @@
-- =============================================================
-- View: analytics.auth_activities
-- Looker source alias: ds49 | Charts: 1
-- =============================================================
-- DESCRIPTION
-- Tracks authentication events (login, logout, SSO, password
-- reset, etc.) from Supabase's internal audit log.
-- Useful for monitoring sign-in patterns and detecting anomalies.
--
-- SOURCE TABLES
-- auth.audit_log_entries — Supabase internal auth event log
--
-- OUTPUT COLUMNS
-- created_at TIMESTAMPTZ When the auth event occurred
-- actor_id TEXT User ID who triggered the event
-- actor_via_sso TEXT Whether the action was via SSO ('true'/'false')
-- action TEXT Event type (e.g. 'login', 'logout', 'token_refreshed')
--
-- WINDOW
-- Rolling 90 days from current date
--
-- EXAMPLE QUERIES
-- -- Daily login counts
-- SELECT DATE_TRUNC('day', created_at) AS day, COUNT(*) AS logins
-- FROM analytics.auth_activities
-- WHERE action = 'login'
-- GROUP BY 1 ORDER BY 1;
--
-- -- SSO vs password login breakdown
-- SELECT actor_via_sso, COUNT(*) FROM analytics.auth_activities
-- WHERE action = 'login' GROUP BY 1;
-- =============================================================
SELECT
created_at,
payload->>'actor_id' AS actor_id,
payload->>'actor_via_sso' AS actor_via_sso,
payload->>'action' AS action
FROM auth.audit_log_entries
WHERE created_at >= NOW() - INTERVAL '90 days'

View File

@@ -0,0 +1,105 @@
-- =============================================================
-- View: analytics.graph_execution
-- Looker source alias: ds16 | Charts: 21
-- =============================================================
-- DESCRIPTION
-- One row per agent graph execution (last 90 days).
-- Unpacks the JSONB stats column into individual numeric columns
-- and normalises the executionStatus — runs that failed due to
-- insufficient credits are reclassified as 'NO_CREDITS' for
-- easier filtering. Error messages are scrubbed of IDs and URLs
-- to allow safe grouping.
--
-- SOURCE TABLES
-- platform.AgentGraphExecution — Execution records
-- platform.AgentGraph — Agent graph metadata (for name)
-- platform.LibraryAgent — To flag possibly-AI (safe-mode) agents
--
-- OUTPUT COLUMNS
-- id TEXT Execution UUID
-- agentGraphId TEXT Agent graph UUID
-- agentGraphVersion INT Graph version number
-- executionStatus TEXT COMPLETED | FAILED | NO_CREDITS | RUNNING | QUEUED | TERMINATED
-- createdAt TIMESTAMPTZ When the execution was queued
-- updatedAt TIMESTAMPTZ Last status update time
-- userId TEXT Owner user UUID
-- agentGraphName TEXT Human-readable agent name
-- cputime DECIMAL Total CPU seconds consumed
-- walltime DECIMAL Total wall-clock seconds
-- node_count DECIMAL Number of nodes in the graph
-- nodes_cputime DECIMAL CPU time across all nodes
-- nodes_walltime DECIMAL Wall time across all nodes
-- execution_cost DECIMAL Credit cost of this execution
-- correctness_score FLOAT AI correctness score (if available)
-- possibly_ai BOOLEAN True if agent has sensitive_action_safe_mode enabled
-- groupedErrorMessage TEXT Scrubbed error string (IDs/URLs replaced with wildcards)
--
-- WINDOW
-- Rolling 90 days (createdAt > CURRENT_DATE - 90 days)
--
-- EXAMPLE QUERIES
-- -- Daily execution counts by status
-- SELECT DATE_TRUNC('day', "createdAt") AS day, "executionStatus", COUNT(*)
-- FROM analytics.graph_execution
-- GROUP BY 1, 2 ORDER BY 1;
--
-- -- Average cost per execution by agent
-- SELECT "agentGraphName", AVG("execution_cost") AS avg_cost, COUNT(*) AS runs
-- FROM analytics.graph_execution
-- WHERE "executionStatus" = 'COMPLETED'
-- GROUP BY 1 ORDER BY avg_cost DESC;
--
-- -- Top error messages
-- SELECT "groupedErrorMessage", COUNT(*) AS occurrences
-- FROM analytics.graph_execution
-- WHERE "executionStatus" = 'FAILED'
-- GROUP BY 1 ORDER BY 2 DESC LIMIT 20;
-- =============================================================
SELECT
ge."id" AS id,
ge."agentGraphId" AS agentGraphId,
ge."agentGraphVersion" AS agentGraphVersion,
CASE
WHEN jsonb_exists(ge."stats"::jsonb, 'error')
AND (
(ge."stats"::jsonb->>'error') ILIKE '%insufficient balance%'
OR (ge."stats"::jsonb->>'error') ILIKE '%you have no credits left%'
)
THEN 'NO_CREDITS'
ELSE CAST(ge."executionStatus" AS TEXT)
END AS executionStatus,
ge."createdAt" AS createdAt,
ge."updatedAt" AS updatedAt,
ge."userId" AS userId,
g."name" AS agentGraphName,
(ge."stats"::jsonb->>'cputime')::decimal AS cputime,
(ge."stats"::jsonb->>'walltime')::decimal AS walltime,
(ge."stats"::jsonb->>'node_count')::decimal AS node_count,
(ge."stats"::jsonb->>'nodes_cputime')::decimal AS nodes_cputime,
(ge."stats"::jsonb->>'nodes_walltime')::decimal AS nodes_walltime,
(ge."stats"::jsonb->>'cost')::decimal AS execution_cost,
(ge."stats"::jsonb->>'correctness_score')::float AS correctness_score,
COALESCE(la.possibly_ai, FALSE) AS possibly_ai,
REGEXP_REPLACE(
REGEXP_REPLACE(
TRIM(BOTH '"' FROM ge."stats"::jsonb->>'error'),
'(https?://)([A-Za-z0-9.-]+)(:[0-9]+)?(/[^\s]*)?',
'\1\2/...', 'gi'
),
'[a-zA-Z0-9_:-]*\d[a-zA-Z0-9_:-]*', '*', 'g'
) AS groupedErrorMessage
FROM platform."AgentGraphExecution" ge
LEFT JOIN platform."AgentGraph" g
ON ge."agentGraphId" = g."id"
AND ge."agentGraphVersion" = g."version"
LEFT JOIN (
SELECT DISTINCT ON ("userId", "agentGraphId")
"userId", "agentGraphId",
("settings"::jsonb->>'sensitive_action_safe_mode')::boolean AS possibly_ai
FROM platform."LibraryAgent"
WHERE "isDeleted" = FALSE
AND "isArchived" = FALSE
ORDER BY "userId", "agentGraphId", "agentGraphVersion" DESC
) la ON la."userId" = ge."userId" AND la."agentGraphId" = ge."agentGraphId"
WHERE ge."createdAt" > CURRENT_DATE - INTERVAL '90 days'

View File

@@ -0,0 +1,101 @@
-- =============================================================
-- View: analytics.node_block_execution
-- Looker source alias: ds14 | Charts: 11
-- =============================================================
-- DESCRIPTION
-- One row per node (block) execution (last 90 days).
-- Unpacks stats JSONB and joins to identify which block type
-- was run. For failed nodes, joins the error output and
-- scrubs it for safe grouping.
--
-- SOURCE TABLES
-- platform.AgentNodeExecution — Node execution records
-- platform.AgentNode — Node → block mapping
-- platform.AgentBlock — Block name/ID
-- platform.AgentNodeExecutionInputOutput — Error output values
--
-- OUTPUT COLUMNS
-- id TEXT Node execution UUID
-- agentGraphExecutionId TEXT Parent graph execution UUID
-- agentNodeId TEXT Node UUID within the graph
-- executionStatus TEXT COMPLETED | FAILED | QUEUED | RUNNING | TERMINATED
-- addedTime TIMESTAMPTZ When the node was queued
-- queuedTime TIMESTAMPTZ When it entered the queue
-- startedTime TIMESTAMPTZ When execution started
-- endedTime TIMESTAMPTZ When execution finished
-- inputSize BIGINT Input payload size in bytes
-- outputSize BIGINT Output payload size in bytes
-- walltime NUMERIC Wall-clock seconds for this node
-- cputime NUMERIC CPU seconds for this node
-- llmRetryCount INT Number of LLM retries
-- llmCallCount INT Number of LLM API calls made
-- inputTokenCount BIGINT LLM input tokens consumed
-- outputTokenCount BIGINT LLM output tokens produced
-- blockName TEXT Human-readable block name (e.g. 'OpenAIBlock')
-- blockId TEXT Block UUID
-- groupedErrorMessage TEXT Scrubbed error (IDs/URLs wildcarded)
-- errorMessage TEXT Raw error output (only set when FAILED)
--
-- WINDOW
-- Rolling 90 days (addedTime > CURRENT_DATE - 90 days)
--
-- EXAMPLE QUERIES
-- -- Most-used blocks by execution count
-- SELECT "blockName", COUNT(*) AS executions,
-- COUNT(*) FILTER (WHERE "executionStatus"='FAILED') AS failures
-- FROM analytics.node_block_execution
-- GROUP BY 1 ORDER BY executions DESC LIMIT 20;
--
-- -- Average LLM token usage per block
-- SELECT "blockName",
-- AVG("inputTokenCount") AS avg_input_tokens,
-- AVG("outputTokenCount") AS avg_output_tokens
-- FROM analytics.node_block_execution
-- WHERE "llmCallCount" > 0
-- GROUP BY 1 ORDER BY avg_input_tokens DESC;
--
-- -- Top failure reasons
-- SELECT "blockName", "groupedErrorMessage", COUNT(*) AS count
-- FROM analytics.node_block_execution
-- WHERE "executionStatus" = 'FAILED'
-- GROUP BY 1, 2 ORDER BY count DESC LIMIT 20;
-- =============================================================
SELECT
ne."id" AS id,
ne."agentGraphExecutionId" AS agentGraphExecutionId,
ne."agentNodeId" AS agentNodeId,
CAST(ne."executionStatus" AS TEXT) AS executionStatus,
ne."addedTime" AS addedTime,
ne."queuedTime" AS queuedTime,
ne."startedTime" AS startedTime,
ne."endedTime" AS endedTime,
(ne."stats"::jsonb->>'input_size')::bigint AS inputSize,
(ne."stats"::jsonb->>'output_size')::bigint AS outputSize,
(ne."stats"::jsonb->>'walltime')::numeric AS walltime,
(ne."stats"::jsonb->>'cputime')::numeric AS cputime,
(ne."stats"::jsonb->>'llm_retry_count')::int AS llmRetryCount,
(ne."stats"::jsonb->>'llm_call_count')::int AS llmCallCount,
(ne."stats"::jsonb->>'input_token_count')::bigint AS inputTokenCount,
(ne."stats"::jsonb->>'output_token_count')::bigint AS outputTokenCount,
b."name" AS blockName,
b."id" AS blockId,
REGEXP_REPLACE(
REGEXP_REPLACE(
TRIM(BOTH '"' FROM eio."data"::text),
'(https?://)([A-Za-z0-9.-]+)(:[0-9]+)?(/[^\s]*)?',
'\1\2/...', 'gi'
),
'[a-zA-Z0-9_:-]*\d[a-zA-Z0-9_:-]*', '*', 'g'
) AS groupedErrorMessage,
eio."data" AS errorMessage
FROM platform."AgentNodeExecution" ne
LEFT JOIN platform."AgentNode" nd
ON ne."agentNodeId" = nd."id"
LEFT JOIN platform."AgentBlock" b
ON nd."agentBlockId" = b."id"
LEFT JOIN platform."AgentNodeExecutionInputOutput" eio
ON eio."referencedByOutputExecId" = ne."id"
AND eio."name" = 'error'
AND ne."executionStatus" = 'FAILED'
WHERE ne."addedTime" > CURRENT_DATE - INTERVAL '90 days'

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-- =============================================================
-- View: analytics.retention_agent
-- Looker source alias: ds35 | Charts: 2
-- =============================================================
-- DESCRIPTION
-- Weekly cohort retention broken down per individual agent.
-- Cohort = week of a user's first use of THAT specific agent.
-- Tells you which agents keep users coming back vs. one-shot
-- use. Only includes cohorts from the last 180 days.
--
-- SOURCE TABLES
-- platform.AgentGraphExecution — Execution records (user × agent × time)
-- platform.AgentGraph — Agent names
--
-- OUTPUT COLUMNS
-- agent_id TEXT Agent graph UUID
-- agent_label TEXT 'AgentName [first8chars]'
-- agent_label_n TEXT 'AgentName [first8chars] (n=total_users)'
-- cohort_week_start DATE Week users first ran this agent
-- cohort_label TEXT ISO week label
-- cohort_label_n TEXT ISO week label with cohort size
-- user_lifetime_week INT Weeks since first use of this agent
-- cohort_users BIGINT Users in this cohort for this agent
-- active_users BIGINT Users who ran the agent again in week k
-- retention_rate FLOAT active_users / cohort_users
-- cohort_users_w0 BIGINT cohort_users only at week 0 (safe to SUM)
-- agent_total_users BIGINT Total users across all cohorts for this agent
--
-- EXAMPLE QUERIES
-- -- Best-retained agents at week 2
-- SELECT agent_label, AVG(retention_rate) AS w2_retention
-- FROM analytics.retention_agent
-- WHERE user_lifetime_week = 2 AND cohort_users >= 10
-- GROUP BY 1 ORDER BY w2_retention DESC LIMIT 10;
--
-- -- Agents with most unique users
-- SELECT DISTINCT agent_label, agent_total_users
-- FROM analytics.retention_agent
-- ORDER BY agent_total_users DESC LIMIT 20;
-- =============================================================
WITH params AS (SELECT 12::int AS max_weeks, (CURRENT_DATE - INTERVAL '180 days') AS cohort_start),
events AS (
SELECT e."userId"::text AS user_id, e."agentGraphId" AS agent_id,
e."createdAt"::timestamptz AS created_at,
DATE_TRUNC('week', e."createdAt")::date AS week_start
FROM platform."AgentGraphExecution" e
),
first_use AS (
SELECT user_id, agent_id, MIN(created_at) AS first_use_at,
DATE_TRUNC('week', MIN(created_at))::date AS cohort_week_start
FROM events GROUP BY 1,2
HAVING MIN(created_at) >= (SELECT cohort_start FROM params)
),
activity_weeks AS (SELECT DISTINCT user_id, agent_id, week_start FROM events),
user_week_age AS (
SELECT aw.user_id, aw.agent_id, fu.cohort_week_start,
((aw.week_start - DATE_TRUNC('week',fu.first_use_at)::date)/7)::int AS user_lifetime_week
FROM activity_weeks aw JOIN first_use fu USING (user_id, agent_id)
WHERE aw.week_start >= DATE_TRUNC('week',fu.first_use_at)::date
),
active_counts AS (
SELECT agent_id, cohort_week_start, user_lifetime_week, COUNT(DISTINCT user_id) AS active_users
FROM user_week_age WHERE user_lifetime_week >= 0 GROUP BY 1,2,3
),
cohort_sizes AS (
SELECT agent_id, cohort_week_start, COUNT(DISTINCT user_id) AS cohort_users FROM first_use GROUP BY 1,2
),
cohort_caps AS (
SELECT cs.agent_id, cs.cohort_week_start, cs.cohort_users,
LEAST((SELECT max_weeks FROM params),
GREATEST(0,((DATE_TRUNC('week',CURRENT_DATE)::date-cs.cohort_week_start)/7)::int)) AS cap_weeks
FROM cohort_sizes cs
),
grid AS (
SELECT cc.agent_id, cc.cohort_week_start, gs AS user_lifetime_week, cc.cohort_users
FROM cohort_caps cc CROSS JOIN LATERAL generate_series(0, cc.cap_weeks) gs
),
agent_names AS (SELECT DISTINCT ON (g."id") g."id" AS agent_id, g."name" AS agent_name FROM platform."AgentGraph" g ORDER BY g."id", g."version" DESC),
agent_total_users AS (SELECT agent_id, SUM(cohort_users) AS agent_total_users FROM cohort_sizes GROUP BY 1)
SELECT
g.agent_id,
COALESCE(an.agent_name,'(unnamed)')||' ['||LEFT(g.agent_id::text,8)||']' AS agent_label,
COALESCE(an.agent_name,'(unnamed)')||' ['||LEFT(g.agent_id::text,8)||'] (n='||COALESCE(atu.agent_total_users,0)||')' AS agent_label_n,
g.cohort_week_start,
TO_CHAR(g.cohort_week_start,'IYYY-"W"IW') AS cohort_label,
TO_CHAR(g.cohort_week_start,'IYYY-"W"IW')||' (n='||g.cohort_users||')' AS cohort_label_n,
g.user_lifetime_week, g.cohort_users,
COALESCE(ac.active_users,0) AS active_users,
COALESCE(ac.active_users,0)::float / NULLIF(g.cohort_users,0) AS retention_rate,
CASE WHEN g.user_lifetime_week=0 THEN g.cohort_users ELSE 0 END AS cohort_users_w0,
COALESCE(atu.agent_total_users,0) AS agent_total_users
FROM grid g
LEFT JOIN active_counts ac ON ac.agent_id=g.agent_id AND ac.cohort_week_start=g.cohort_week_start AND ac.user_lifetime_week=g.user_lifetime_week
LEFT JOIN agent_names an ON an.agent_id=g.agent_id
LEFT JOIN agent_total_users atu ON atu.agent_id=g.agent_id
ORDER BY agent_label, g.cohort_week_start, g.user_lifetime_week;

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-- =============================================================
-- View: analytics.retention_execution_daily
-- Looker source alias: ds111 | Charts: 1
-- =============================================================
-- DESCRIPTION
-- Daily cohort retention based on agent executions.
-- Cohort anchor = day of user's FIRST ever execution.
-- Only includes cohorts from the last 90 days, up to day 30.
-- Great for early engagement analysis (did users run another
-- agent the next day?).
--
-- SOURCE TABLES
-- platform.AgentGraphExecution — Execution records
--
-- OUTPUT COLUMNS
-- Same pattern as retention_login_daily.
-- cohort_day_start = day of first execution (not first login)
--
-- EXAMPLE QUERIES
-- -- Day-3 execution retention
-- SELECT cohort_label, retention_rate_bounded AS d3_retention
-- FROM analytics.retention_execution_daily
-- WHERE user_lifetime_day = 3 ORDER BY cohort_day_start;
-- =============================================================
WITH params AS (SELECT 30::int AS max_days, (CURRENT_DATE - INTERVAL '90 days') AS cohort_start),
events AS (
SELECT e."userId"::text AS user_id, e."createdAt"::timestamptz AS created_at,
DATE_TRUNC('day', e."createdAt")::date AS day_start
FROM platform."AgentGraphExecution" e WHERE e."userId" IS NOT NULL
),
first_exec AS (
SELECT user_id, MIN(created_at) AS first_exec_at,
DATE_TRUNC('day', MIN(created_at))::date AS cohort_day_start
FROM events GROUP BY 1
HAVING MIN(created_at) >= (SELECT cohort_start FROM params)
),
activity_days AS (SELECT DISTINCT user_id, day_start FROM events),
user_day_age AS (
SELECT ad.user_id, fe.cohort_day_start,
(ad.day_start - DATE_TRUNC('day',fe.first_exec_at)::date)::int AS user_lifetime_day
FROM activity_days ad JOIN first_exec fe USING (user_id)
WHERE ad.day_start >= DATE_TRUNC('day',fe.first_exec_at)::date
),
bounded_counts AS (
SELECT cohort_day_start, user_lifetime_day, COUNT(DISTINCT user_id) AS active_users_bounded
FROM user_day_age WHERE user_lifetime_day >= 0 GROUP BY 1,2
),
last_active AS (
SELECT cohort_day_start, user_id, MAX(user_lifetime_day) AS last_active_day FROM user_day_age GROUP BY 1,2
),
unbounded_counts AS (
SELECT la.cohort_day_start, gs AS user_lifetime_day, COUNT(*) AS retained_users_unbounded
FROM last_active la
CROSS JOIN LATERAL generate_series(0, LEAST(la.last_active_day,(SELECT max_days FROM params))) gs
GROUP BY 1,2
),
cohort_sizes AS (SELECT cohort_day_start, COUNT(DISTINCT user_id) AS cohort_users FROM first_exec GROUP BY 1),
cohort_caps AS (
SELECT cs.cohort_day_start, cs.cohort_users,
LEAST((SELECT max_days FROM params), GREATEST(0,(CURRENT_DATE-cs.cohort_day_start)::int)) AS cap_days
FROM cohort_sizes cs
),
grid AS (
SELECT cc.cohort_day_start, gs AS user_lifetime_day, cc.cohort_users
FROM cohort_caps cc CROSS JOIN LATERAL generate_series(0, cc.cap_days) gs
)
SELECT
g.cohort_day_start,
TO_CHAR(g.cohort_day_start,'YYYY-MM-DD') AS cohort_label,
TO_CHAR(g.cohort_day_start,'YYYY-MM-DD')||' (n='||g.cohort_users||')' AS cohort_label_n,
g.user_lifetime_day, g.cohort_users,
COALESCE(b.active_users_bounded,0) AS active_users_bounded,
COALESCE(u.retained_users_unbounded,0) AS retained_users_unbounded,
CASE WHEN g.cohort_users>0 THEN COALESCE(b.active_users_bounded,0)::float/g.cohort_users END AS retention_rate_bounded,
CASE WHEN g.cohort_users>0 THEN COALESCE(u.retained_users_unbounded,0)::float/g.cohort_users END AS retention_rate_unbounded,
CASE WHEN g.user_lifetime_day=0 THEN g.cohort_users ELSE 0 END AS cohort_users_d0
FROM grid g
LEFT JOIN bounded_counts b ON b.cohort_day_start=g.cohort_day_start AND b.user_lifetime_day=g.user_lifetime_day
LEFT JOIN unbounded_counts u ON u.cohort_day_start=g.cohort_day_start AND u.user_lifetime_day=g.user_lifetime_day
ORDER BY g.cohort_day_start, g.user_lifetime_day;

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-- =============================================================
-- View: analytics.retention_execution_weekly
-- Looker source alias: ds92 | Charts: 2
-- =============================================================
-- DESCRIPTION
-- Weekly cohort retention based on agent executions.
-- Cohort anchor = week of user's FIRST ever agent execution
-- (not first login). Only includes cohorts from the last 180 days.
-- Useful when you care about product engagement, not just visits.
--
-- SOURCE TABLES
-- platform.AgentGraphExecution — Execution records
--
-- OUTPUT COLUMNS
-- Same pattern as retention_login_weekly.
-- cohort_week_start = week of first execution (not first login)
--
-- EXAMPLE QUERIES
-- -- Week-2 execution retention
-- SELECT cohort_label, retention_rate_bounded
-- FROM analytics.retention_execution_weekly
-- WHERE user_lifetime_week = 2 ORDER BY cohort_week_start;
-- =============================================================
WITH params AS (SELECT 12::int AS max_weeks, (CURRENT_DATE - INTERVAL '180 days') AS cohort_start),
events AS (
SELECT e."userId"::text AS user_id, e."createdAt"::timestamptz AS created_at,
DATE_TRUNC('week', e."createdAt")::date AS week_start
FROM platform."AgentGraphExecution" e WHERE e."userId" IS NOT NULL
),
first_exec AS (
SELECT user_id, MIN(created_at) AS first_exec_at,
DATE_TRUNC('week', MIN(created_at))::date AS cohort_week_start
FROM events GROUP BY 1
HAVING MIN(created_at) >= (SELECT cohort_start FROM params)
),
activity_weeks AS (SELECT DISTINCT user_id, week_start FROM events),
user_week_age AS (
SELECT aw.user_id, fe.cohort_week_start,
((aw.week_start - DATE_TRUNC('week',fe.first_exec_at)::date)/7)::int AS user_lifetime_week
FROM activity_weeks aw JOIN first_exec fe USING (user_id)
WHERE aw.week_start >= DATE_TRUNC('week',fe.first_exec_at)::date
),
bounded_counts AS (
SELECT cohort_week_start, user_lifetime_week, COUNT(DISTINCT user_id) AS active_users_bounded
FROM user_week_age WHERE user_lifetime_week >= 0 GROUP BY 1,2
),
last_active AS (
SELECT cohort_week_start, user_id, MAX(user_lifetime_week) AS last_active_week FROM user_week_age GROUP BY 1,2
),
unbounded_counts AS (
SELECT la.cohort_week_start, gs AS user_lifetime_week, COUNT(*) AS retained_users_unbounded
FROM last_active la
CROSS JOIN LATERAL generate_series(0, LEAST(la.last_active_week,(SELECT max_weeks FROM params))) gs
GROUP BY 1,2
),
cohort_sizes AS (SELECT cohort_week_start, COUNT(DISTINCT user_id) AS cohort_users FROM first_exec GROUP BY 1),
cohort_caps AS (
SELECT cs.cohort_week_start, cs.cohort_users,
LEAST((SELECT max_weeks FROM params),
GREATEST(0,((DATE_TRUNC('week',CURRENT_DATE)::date-cs.cohort_week_start)/7)::int)) AS cap_weeks
FROM cohort_sizes cs
),
grid AS (
SELECT cc.cohort_week_start, gs AS user_lifetime_week, cc.cohort_users
FROM cohort_caps cc CROSS JOIN LATERAL generate_series(0, cc.cap_weeks) gs
)
SELECT
g.cohort_week_start,
TO_CHAR(g.cohort_week_start,'IYYY-"W"IW') AS cohort_label,
TO_CHAR(g.cohort_week_start,'IYYY-"W"IW')||' (n='||g.cohort_users||')' AS cohort_label_n,
g.user_lifetime_week, g.cohort_users,
COALESCE(b.active_users_bounded,0) AS active_users_bounded,
COALESCE(u.retained_users_unbounded,0) AS retained_users_unbounded,
CASE WHEN g.cohort_users>0 THEN COALESCE(b.active_users_bounded,0)::float/g.cohort_users END AS retention_rate_bounded,
CASE WHEN g.cohort_users>0 THEN COALESCE(u.retained_users_unbounded,0)::float/g.cohort_users END AS retention_rate_unbounded,
CASE WHEN g.user_lifetime_week=0 THEN g.cohort_users ELSE 0 END AS cohort_users_w0
FROM grid g
LEFT JOIN bounded_counts b ON b.cohort_week_start=g.cohort_week_start AND b.user_lifetime_week=g.user_lifetime_week
LEFT JOIN unbounded_counts u ON u.cohort_week_start=g.cohort_week_start AND u.user_lifetime_week=g.user_lifetime_week
ORDER BY g.cohort_week_start, g.user_lifetime_week;

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-- =============================================================
-- View: analytics.retention_login_daily
-- Looker source alias: ds112 | Charts: 1
-- =============================================================
-- DESCRIPTION
-- Daily cohort retention based on login sessions.
-- Same logic as retention_login_weekly but at day granularity,
-- showing up to day 30 for cohorts from the last 90 days.
-- Useful for analysing early activation (days 1-7) in detail.
--
-- SOURCE TABLES
-- auth.sessions — Login session records
--
-- OUTPUT COLUMNS (same pattern as retention_login_weekly)
-- cohort_day_start DATE First day the cohort logged in
-- cohort_label TEXT Date string (e.g. '2025-03-01')
-- cohort_label_n TEXT Date + cohort size (e.g. '2025-03-01 (n=12)')
-- user_lifetime_day INT Days since first login (0 = signup day)
-- cohort_users BIGINT Total users in cohort
-- active_users_bounded BIGINT Users active on exactly day k
-- retained_users_unbounded BIGINT Users active any time on/after day k
-- retention_rate_bounded FLOAT bounded / cohort_users
-- retention_rate_unbounded FLOAT unbounded / cohort_users
-- cohort_users_d0 BIGINT cohort_users only at day 0, else 0 (safe to SUM)
--
-- EXAMPLE QUERIES
-- -- Day-1 retention rate (came back next day)
-- SELECT cohort_label, retention_rate_bounded AS d1_retention
-- FROM analytics.retention_login_daily
-- WHERE user_lifetime_day = 1 ORDER BY cohort_day_start;
--
-- -- Average retention curve across all cohorts
-- SELECT user_lifetime_day,
-- SUM(active_users_bounded)::float / NULLIF(SUM(cohort_users_d0), 0) AS avg_retention
-- FROM analytics.retention_login_daily
-- GROUP BY 1 ORDER BY 1;
-- =============================================================
WITH params AS (SELECT 30::int AS max_days, (CURRENT_DATE - INTERVAL '90 days')::date AS cohort_start),
events AS (
SELECT s.user_id::text AS user_id, s.created_at::timestamptz AS created_at,
DATE_TRUNC('day', s.created_at)::date AS day_start
FROM auth.sessions s WHERE s.user_id IS NOT NULL
),
first_login AS (
SELECT user_id, MIN(created_at) AS first_login_time,
DATE_TRUNC('day', MIN(created_at))::date AS cohort_day_start
FROM events GROUP BY 1
HAVING MIN(created_at) >= (SELECT cohort_start FROM params)
),
activity_days AS (SELECT DISTINCT user_id, day_start FROM events),
user_day_age AS (
SELECT ad.user_id, fl.cohort_day_start,
(ad.day_start - DATE_TRUNC('day', fl.first_login_time)::date)::int AS user_lifetime_day
FROM activity_days ad JOIN first_login fl USING (user_id)
WHERE ad.day_start >= DATE_TRUNC('day', fl.first_login_time)::date
),
bounded_counts AS (
SELECT cohort_day_start, user_lifetime_day, COUNT(DISTINCT user_id) AS active_users_bounded
FROM user_day_age WHERE user_lifetime_day >= 0 GROUP BY 1,2
),
last_active AS (
SELECT cohort_day_start, user_id, MAX(user_lifetime_day) AS last_active_day FROM user_day_age GROUP BY 1,2
),
unbounded_counts AS (
SELECT la.cohort_day_start, gs AS user_lifetime_day, COUNT(*) AS retained_users_unbounded
FROM last_active la
CROSS JOIN LATERAL generate_series(0, LEAST(la.last_active_day,(SELECT max_days FROM params))) gs
GROUP BY 1,2
),
cohort_sizes AS (SELECT cohort_day_start, COUNT(DISTINCT user_id) AS cohort_users FROM first_login GROUP BY 1),
cohort_caps AS (
SELECT cs.cohort_day_start, cs.cohort_users,
LEAST((SELECT max_days FROM params), GREATEST(0,(CURRENT_DATE-cs.cohort_day_start)::int)) AS cap_days
FROM cohort_sizes cs
),
grid AS (
SELECT cc.cohort_day_start, gs AS user_lifetime_day, cc.cohort_users
FROM cohort_caps cc CROSS JOIN LATERAL generate_series(0, cc.cap_days) gs
)
SELECT
g.cohort_day_start,
TO_CHAR(g.cohort_day_start,'YYYY-MM-DD') AS cohort_label,
TO_CHAR(g.cohort_day_start,'YYYY-MM-DD')||' (n='||g.cohort_users||')' AS cohort_label_n,
g.user_lifetime_day, g.cohort_users,
COALESCE(b.active_users_bounded,0) AS active_users_bounded,
COALESCE(u.retained_users_unbounded,0) AS retained_users_unbounded,
CASE WHEN g.cohort_users>0 THEN COALESCE(b.active_users_bounded,0)::float/g.cohort_users END AS retention_rate_bounded,
CASE WHEN g.cohort_users>0 THEN COALESCE(u.retained_users_unbounded,0)::float/g.cohort_users END AS retention_rate_unbounded,
CASE WHEN g.user_lifetime_day=0 THEN g.cohort_users ELSE 0 END AS cohort_users_d0
FROM grid g
LEFT JOIN bounded_counts b ON b.cohort_day_start=g.cohort_day_start AND b.user_lifetime_day=g.user_lifetime_day
LEFT JOIN unbounded_counts u ON u.cohort_day_start=g.cohort_day_start AND u.user_lifetime_day=g.user_lifetime_day
ORDER BY g.cohort_day_start, g.user_lifetime_day;

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-- =============================================================
-- View: analytics.retention_login_onboarded_weekly
-- Looker source alias: ds101 | Charts: 2
-- =============================================================
-- DESCRIPTION
-- Weekly cohort retention from login sessions, restricted to
-- users who "onboarded" — defined as running at least one
-- agent within 365 days of their first login.
-- Filters out users who signed up but never activated,
-- giving a cleaner view of engaged-user retention.
--
-- SOURCE TABLES
-- auth.sessions — Login session records
-- platform.AgentGraphExecution — Used to identify onboarders
--
-- OUTPUT COLUMNS
-- Same as retention_login_weekly (cohort_week_start, user_lifetime_week,
-- retention_rate_bounded, retention_rate_unbounded, etc.)
-- Only difference: cohort is filtered to onboarded users only.
--
-- EXAMPLE QUERIES
-- -- Compare week-4 retention: all users vs onboarded only
-- SELECT 'all_users' AS segment, AVG(retention_rate_bounded) AS w4_retention
-- FROM analytics.retention_login_weekly WHERE user_lifetime_week = 4
-- UNION ALL
-- SELECT 'onboarded', AVG(retention_rate_bounded)
-- FROM analytics.retention_login_onboarded_weekly WHERE user_lifetime_week = 4;
-- =============================================================
WITH params AS (SELECT 12::int AS max_weeks, 365::int AS onboarding_window_days),
events AS (
SELECT s.user_id::text AS user_id, s.created_at::timestamptz AS created_at,
DATE_TRUNC('week', s.created_at)::date AS week_start
FROM auth.sessions s WHERE s.user_id IS NOT NULL
),
first_login_all AS (
SELECT user_id, MIN(created_at) AS first_login_time,
DATE_TRUNC('week', MIN(created_at))::date AS cohort_week_start
FROM events GROUP BY 1
),
onboarders AS (
SELECT fl.user_id FROM first_login_all fl
WHERE EXISTS (
SELECT 1 FROM platform."AgentGraphExecution" e
WHERE e."userId"::text = fl.user_id
AND e."createdAt" >= fl.first_login_time
AND e."createdAt" < fl.first_login_time
+ make_interval(days => (SELECT onboarding_window_days FROM params))
)
),
first_login AS (SELECT * FROM first_login_all WHERE user_id IN (SELECT user_id FROM onboarders)),
activity_weeks AS (SELECT DISTINCT user_id, week_start FROM events),
user_week_age AS (
SELECT aw.user_id, fl.cohort_week_start,
((aw.week_start - DATE_TRUNC('week',fl.first_login_time)::date)/7)::int AS user_lifetime_week
FROM activity_weeks aw JOIN first_login fl USING (user_id)
WHERE aw.week_start >= DATE_TRUNC('week',fl.first_login_time)::date
),
bounded_counts AS (
SELECT cohort_week_start, user_lifetime_week, COUNT(DISTINCT user_id) AS active_users_bounded
FROM user_week_age WHERE user_lifetime_week >= 0 GROUP BY 1,2
),
last_active AS (
SELECT cohort_week_start, user_id, MAX(user_lifetime_week) AS last_active_week FROM user_week_age GROUP BY 1,2
),
unbounded_counts AS (
SELECT la.cohort_week_start, gs AS user_lifetime_week, COUNT(*) AS retained_users_unbounded
FROM last_active la
CROSS JOIN LATERAL generate_series(0, LEAST(la.last_active_week,(SELECT max_weeks FROM params))) gs
GROUP BY 1,2
),
cohort_sizes AS (SELECT cohort_week_start, COUNT(DISTINCT user_id) AS cohort_users FROM first_login GROUP BY 1),
cohort_caps AS (
SELECT cs.cohort_week_start, cs.cohort_users,
LEAST((SELECT max_weeks FROM params),
GREATEST(0,((DATE_TRUNC('week',CURRENT_DATE)::date-cs.cohort_week_start)/7)::int)) AS cap_weeks
FROM cohort_sizes cs
),
grid AS (
SELECT cc.cohort_week_start, gs AS user_lifetime_week, cc.cohort_users
FROM cohort_caps cc CROSS JOIN LATERAL generate_series(0, cc.cap_weeks) gs
)
SELECT
g.cohort_week_start,
TO_CHAR(g.cohort_week_start,'IYYY-"W"IW') AS cohort_label,
TO_CHAR(g.cohort_week_start,'IYYY-"W"IW')||' (n='||g.cohort_users||')' AS cohort_label_n,
g.user_lifetime_week, g.cohort_users,
COALESCE(b.active_users_bounded,0) AS active_users_bounded,
COALESCE(u.retained_users_unbounded,0) AS retained_users_unbounded,
CASE WHEN g.cohort_users>0 THEN COALESCE(b.active_users_bounded,0)::float/g.cohort_users END AS retention_rate_bounded,
CASE WHEN g.cohort_users>0 THEN COALESCE(u.retained_users_unbounded,0)::float/g.cohort_users END AS retention_rate_unbounded,
CASE WHEN g.user_lifetime_week=0 THEN g.cohort_users ELSE 0 END AS cohort_users_w0
FROM grid g
LEFT JOIN bounded_counts b ON b.cohort_week_start=g.cohort_week_start AND b.user_lifetime_week=g.user_lifetime_week
LEFT JOIN unbounded_counts u ON u.cohort_week_start=g.cohort_week_start AND u.user_lifetime_week=g.user_lifetime_week
ORDER BY g.cohort_week_start, g.user_lifetime_week;

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-- =============================================================
-- View: analytics.retention_login_weekly
-- Looker source alias: ds83 | Charts: 2
-- =============================================================
-- DESCRIPTION
-- Weekly cohort retention based on login sessions.
-- Users are grouped by the ISO week of their first ever login.
-- For each cohort × lifetime-week combination, outputs both:
-- - bounded rate: % active in exactly that week
-- - unbounded rate: % who were ever active on or after that week
-- Weeks are capped to the cohort's actual age (no future data points).
--
-- SOURCE TABLES
-- auth.sessions — Login session records
--
-- HOW TO READ THE OUTPUT
-- cohort_week_start The Monday of the week users first logged in
-- user_lifetime_week 0 = signup week, 1 = one week later, etc.
-- retention_rate_bounded = active_users_bounded / cohort_users
-- retention_rate_unbounded = retained_users_unbounded / cohort_users
--
-- OUTPUT COLUMNS
-- cohort_week_start DATE First day of the cohort's signup week
-- cohort_label TEXT ISO week label (e.g. '2025-W01')
-- cohort_label_n TEXT ISO week label with cohort size (e.g. '2025-W01 (n=42)')
-- user_lifetime_week INT Weeks since first login (0 = signup week)
-- cohort_users BIGINT Total users in this cohort (denominator)
-- active_users_bounded BIGINT Users active in exactly week k
-- retained_users_unbounded BIGINT Users active any time on/after week k
-- retention_rate_bounded FLOAT bounded active / cohort_users
-- retention_rate_unbounded FLOAT unbounded retained / cohort_users
-- cohort_users_w0 BIGINT cohort_users only at week 0, else 0 (safe to SUM in pivot tables)
--
-- EXAMPLE QUERIES
-- -- Week-1 retention rate per cohort
-- SELECT cohort_label, retention_rate_bounded AS w1_retention
-- FROM analytics.retention_login_weekly
-- WHERE user_lifetime_week = 1
-- ORDER BY cohort_week_start;
--
-- -- Overall average retention curve (all cohorts combined)
-- SELECT user_lifetime_week,
-- SUM(active_users_bounded)::float / NULLIF(SUM(cohort_users_w0), 0) AS avg_retention
-- FROM analytics.retention_login_weekly
-- GROUP BY 1 ORDER BY 1;
-- =============================================================
WITH params AS (SELECT 12::int AS max_weeks),
events AS (
SELECT s.user_id::text AS user_id, s.created_at::timestamptz AS created_at,
DATE_TRUNC('week', s.created_at)::date AS week_start
FROM auth.sessions s WHERE s.user_id IS NOT NULL
),
first_login AS (
SELECT user_id, MIN(created_at) AS first_login_time,
DATE_TRUNC('week', MIN(created_at))::date AS cohort_week_start
FROM events GROUP BY 1
),
activity_weeks AS (SELECT DISTINCT user_id, week_start FROM events),
user_week_age AS (
SELECT aw.user_id, fl.cohort_week_start,
((aw.week_start - DATE_TRUNC('week', fl.first_login_time)::date) / 7)::int AS user_lifetime_week
FROM activity_weeks aw JOIN first_login fl USING (user_id)
WHERE aw.week_start >= DATE_TRUNC('week', fl.first_login_time)::date
),
bounded_counts AS (
SELECT cohort_week_start, user_lifetime_week, COUNT(DISTINCT user_id) AS active_users_bounded
FROM user_week_age WHERE user_lifetime_week >= 0 GROUP BY 1,2
),
last_active AS (
SELECT cohort_week_start, user_id, MAX(user_lifetime_week) AS last_active_week FROM user_week_age GROUP BY 1,2
),
unbounded_counts AS (
SELECT la.cohort_week_start, gs AS user_lifetime_week, COUNT(*) AS retained_users_unbounded
FROM last_active la
CROSS JOIN LATERAL generate_series(0, LEAST(la.last_active_week,(SELECT max_weeks FROM params))) gs
GROUP BY 1,2
),
cohort_sizes AS (SELECT cohort_week_start, COUNT(DISTINCT user_id) AS cohort_users FROM first_login GROUP BY 1),
cohort_caps AS (
SELECT cs.cohort_week_start, cs.cohort_users,
LEAST((SELECT max_weeks FROM params),
GREATEST(0,((DATE_TRUNC('week',CURRENT_DATE)::date - cs.cohort_week_start)/7)::int)) AS cap_weeks
FROM cohort_sizes cs
),
grid AS (
SELECT cc.cohort_week_start, gs AS user_lifetime_week, cc.cohort_users
FROM cohort_caps cc CROSS JOIN LATERAL generate_series(0, cc.cap_weeks) gs
)
SELECT
g.cohort_week_start,
TO_CHAR(g.cohort_week_start,'IYYY-"W"IW') AS cohort_label,
TO_CHAR(g.cohort_week_start,'IYYY-"W"IW')||' (n='||g.cohort_users||')' AS cohort_label_n,
g.user_lifetime_week, g.cohort_users,
COALESCE(b.active_users_bounded,0) AS active_users_bounded,
COALESCE(u.retained_users_unbounded,0) AS retained_users_unbounded,
CASE WHEN g.cohort_users>0 THEN COALESCE(b.active_users_bounded,0)::float/g.cohort_users END AS retention_rate_bounded,
CASE WHEN g.cohort_users>0 THEN COALESCE(u.retained_users_unbounded,0)::float/g.cohort_users END AS retention_rate_unbounded,
CASE WHEN g.user_lifetime_week=0 THEN g.cohort_users ELSE 0 END AS cohort_users_w0
FROM grid g
LEFT JOIN bounded_counts b ON b.cohort_week_start=g.cohort_week_start AND b.user_lifetime_week=g.user_lifetime_week
LEFT JOIN unbounded_counts u ON u.cohort_week_start=g.cohort_week_start AND u.user_lifetime_week=g.user_lifetime_week
ORDER BY g.cohort_week_start, g.user_lifetime_week

View File

@@ -0,0 +1,71 @@
-- =============================================================
-- View: analytics.user_block_spending
-- Looker source alias: ds6 | Charts: 5
-- =============================================================
-- DESCRIPTION
-- One row per credit transaction (last 90 days).
-- Shows how users spend credits broken down by block type,
-- LLM provider and model. Joins node execution stats for
-- token-level detail.
--
-- SOURCE TABLES
-- platform.CreditTransaction — Credit debit/credit records
-- platform.AgentNodeExecution — Node execution stats (for token counts)
--
-- OUTPUT COLUMNS
-- transactionKey TEXT Unique transaction identifier
-- userId TEXT User who was charged
-- amount DECIMAL Credit amount (positive = credit, negative = debit)
-- negativeAmount DECIMAL amount * -1 (convenience for spend charts)
-- transactionType TEXT Transaction type (e.g. 'USAGE', 'REFUND', 'TOP_UP')
-- transactionTime TIMESTAMPTZ When the transaction was recorded
-- blockId TEXT Block UUID that triggered the spend
-- blockName TEXT Human-readable block name
-- llm_provider TEXT LLM provider (e.g. 'openai', 'anthropic')
-- llm_model TEXT Model name (e.g. 'gpt-4o', 'claude-3-5-sonnet')
-- node_exec_id TEXT Linked node execution UUID
-- llm_call_count INT LLM API calls made in that execution
-- llm_retry_count INT LLM retries in that execution
-- llm_input_token_count INT Input tokens consumed
-- llm_output_token_count INT Output tokens produced
--
-- WINDOW
-- Rolling 90 days (createdAt > CURRENT_DATE - 90 days)
--
-- EXAMPLE QUERIES
-- -- Total spend per user (last 90 days)
-- SELECT "userId", SUM("negativeAmount") AS total_spent
-- FROM analytics.user_block_spending
-- WHERE "transactionType" = 'USAGE'
-- GROUP BY 1 ORDER BY total_spent DESC;
--
-- -- Spend by LLM provider + model
-- SELECT "llm_provider", "llm_model",
-- SUM("negativeAmount") AS total_cost,
-- SUM("llm_input_token_count") AS input_tokens,
-- SUM("llm_output_token_count") AS output_tokens
-- FROM analytics.user_block_spending
-- WHERE "llm_provider" IS NOT NULL
-- GROUP BY 1, 2 ORDER BY total_cost DESC;
-- =============================================================
SELECT
c."transactionKey" AS transactionKey,
c."userId" AS userId,
c."amount" AS amount,
c."amount" * -1 AS negativeAmount,
c."type" AS transactionType,
c."createdAt" AS transactionTime,
c.metadata->>'block_id' AS blockId,
c.metadata->>'block' AS blockName,
c.metadata->'input'->'credentials'->>'provider' AS llm_provider,
c.metadata->'input'->>'model' AS llm_model,
c.metadata->>'node_exec_id' AS node_exec_id,
(ne."stats"->>'llm_call_count')::int AS llm_call_count,
(ne."stats"->>'llm_retry_count')::int AS llm_retry_count,
(ne."stats"->>'input_token_count')::int AS llm_input_token_count,
(ne."stats"->>'output_token_count')::int AS llm_output_token_count
FROM platform."CreditTransaction" c
LEFT JOIN platform."AgentNodeExecution" ne
ON (c.metadata->>'node_exec_id') = ne."id"::text
WHERE c."createdAt" > CURRENT_DATE - INTERVAL '90 days'

View File

@@ -0,0 +1,45 @@
-- =============================================================
-- View: analytics.user_onboarding
-- Looker source alias: ds68 | Charts: 3
-- =============================================================
-- DESCRIPTION
-- One row per user onboarding record. Contains the user's
-- stated usage reason, selected integrations, completed
-- onboarding steps and optional first agent selection.
-- Full history (no date filter) since onboarding happens
-- once per user.
--
-- SOURCE TABLES
-- platform.UserOnboarding — Onboarding state per user
--
-- OUTPUT COLUMNS
-- id TEXT Onboarding record UUID
-- createdAt TIMESTAMPTZ When onboarding started
-- updatedAt TIMESTAMPTZ Last update to onboarding state
-- usageReason TEXT Why user signed up (e.g. 'work', 'personal')
-- integrations TEXT[] Array of integration names the user selected
-- userId TEXT User UUID
-- completedSteps TEXT[] Array of onboarding step enums completed
-- selectedStoreListingVersionId TEXT First marketplace agent the user chose (if any)
--
-- EXAMPLE QUERIES
-- -- Usage reason breakdown
-- SELECT "usageReason", COUNT(*) FROM analytics.user_onboarding GROUP BY 1;
--
-- -- Completion rate per step
-- SELECT step, COUNT(*) AS users_completed
-- FROM analytics.user_onboarding
-- CROSS JOIN LATERAL UNNEST("completedSteps") AS step
-- GROUP BY 1 ORDER BY users_completed DESC;
-- =============================================================
SELECT
id,
"createdAt",
"updatedAt",
"usageReason",
integrations,
"userId",
"completedSteps",
"selectedStoreListingVersionId"
FROM platform."UserOnboarding"

View File

@@ -0,0 +1,100 @@
-- =============================================================
-- View: analytics.user_onboarding_funnel
-- Looker source alias: ds74 | Charts: 1
-- =============================================================
-- DESCRIPTION
-- Pre-aggregated onboarding funnel showing how many users
-- completed each step and the drop-off percentage from the
-- previous step. One row per onboarding step (all 22 steps
-- always present, even with 0 completions — prevents sparse
-- gaps from making LAG compare the wrong predecessors).
--
-- SOURCE TABLES
-- platform.UserOnboarding — Onboarding records with completedSteps array
--
-- OUTPUT COLUMNS
-- step TEXT Onboarding step enum name (e.g. 'WELCOME', 'CONGRATS')
-- step_order INT Numeric position in the funnel (1=first, 22=last)
-- users_completed BIGINT Distinct users who completed this step
-- pct_from_prev NUMERIC % of users from the previous step who reached this one
--
-- STEP ORDER
-- 1 WELCOME 9 MARKETPLACE_VISIT 17 SCHEDULE_AGENT
-- 2 USAGE_REASON 10 MARKETPLACE_ADD_AGENT 18 RUN_AGENTS
-- 3 INTEGRATIONS 11 MARKETPLACE_RUN_AGENT 19 RUN_3_DAYS
-- 4 AGENT_CHOICE 12 BUILDER_OPEN 20 TRIGGER_WEBHOOK
-- 5 AGENT_NEW_RUN 13 BUILDER_SAVE_AGENT 21 RUN_14_DAYS
-- 6 AGENT_INPUT 14 BUILDER_RUN_AGENT 22 RUN_AGENTS_100
-- 7 CONGRATS 15 VISIT_COPILOT
-- 8 GET_RESULTS 16 RE_RUN_AGENT
--
-- WINDOW
-- Users who started onboarding in the last 90 days
--
-- EXAMPLE QUERIES
-- -- Full funnel
-- SELECT * FROM analytics.user_onboarding_funnel ORDER BY step_order;
--
-- -- Biggest drop-off point
-- SELECT step, pct_from_prev FROM analytics.user_onboarding_funnel
-- ORDER BY pct_from_prev ASC LIMIT 3;
-- =============================================================
WITH all_steps AS (
-- Complete ordered grid of all 22 steps so zero-completion steps
-- are always present, keeping LAG comparisons correct.
SELECT step_name, step_order
FROM (VALUES
('WELCOME', 1),
('USAGE_REASON', 2),
('INTEGRATIONS', 3),
('AGENT_CHOICE', 4),
('AGENT_NEW_RUN', 5),
('AGENT_INPUT', 6),
('CONGRATS', 7),
('GET_RESULTS', 8),
('MARKETPLACE_VISIT', 9),
('MARKETPLACE_ADD_AGENT', 10),
('MARKETPLACE_RUN_AGENT', 11),
('BUILDER_OPEN', 12),
('BUILDER_SAVE_AGENT', 13),
('BUILDER_RUN_AGENT', 14),
('VISIT_COPILOT', 15),
('RE_RUN_AGENT', 16),
('SCHEDULE_AGENT', 17),
('RUN_AGENTS', 18),
('RUN_3_DAYS', 19),
('TRIGGER_WEBHOOK', 20),
('RUN_14_DAYS', 21),
('RUN_AGENTS_100', 22)
) AS t(step_name, step_order)
),
raw AS (
SELECT
u."userId",
step_txt::text AS step
FROM platform."UserOnboarding" u
CROSS JOIN LATERAL UNNEST(u."completedSteps") AS step_txt
WHERE u."createdAt" >= CURRENT_DATE - INTERVAL '90 days'
),
step_counts AS (
SELECT step, COUNT(DISTINCT "userId") AS users_completed
FROM raw GROUP BY step
),
funnel AS (
SELECT
a.step_name AS step,
a.step_order,
COALESCE(sc.users_completed, 0) AS users_completed,
ROUND(
100.0 * COALESCE(sc.users_completed, 0)
/ NULLIF(
LAG(COALESCE(sc.users_completed, 0)) OVER (ORDER BY a.step_order),
0
),
2
) AS pct_from_prev
FROM all_steps a
LEFT JOIN step_counts sc ON sc.step = a.step_name
)
SELECT * FROM funnel ORDER BY step_order

View File

@@ -0,0 +1,41 @@
-- =============================================================
-- View: analytics.user_onboarding_integration
-- Looker source alias: ds75 | Charts: 1
-- =============================================================
-- DESCRIPTION
-- Pre-aggregated count of users who selected each integration
-- during onboarding. One row per integration type, sorted
-- by popularity.
--
-- SOURCE TABLES
-- platform.UserOnboarding — integrations array column
--
-- OUTPUT COLUMNS
-- integration TEXT Integration name (e.g. 'github', 'slack', 'notion')
-- users_with_integration BIGINT Distinct users who selected this integration
--
-- WINDOW
-- Users who started onboarding in the last 90 days
--
-- EXAMPLE QUERIES
-- -- Full integration popularity ranking
-- SELECT * FROM analytics.user_onboarding_integration;
--
-- -- Top 5 integrations
-- SELECT * FROM analytics.user_onboarding_integration LIMIT 5;
-- =============================================================
WITH exploded AS (
SELECT
u."userId" AS user_id,
UNNEST(u."integrations") AS integration
FROM platform."UserOnboarding" u
WHERE u."createdAt" >= CURRENT_DATE - INTERVAL '90 days'
)
SELECT
integration,
COUNT(DISTINCT user_id) AS users_with_integration
FROM exploded
WHERE integration IS NOT NULL AND integration <> ''
GROUP BY integration
ORDER BY users_with_integration DESC

View File

@@ -0,0 +1,145 @@
-- =============================================================
-- View: analytics.users_activities
-- Looker source alias: ds56 | Charts: 5
-- =============================================================
-- DESCRIPTION
-- One row per user with lifetime activity summary.
-- Joins login sessions with agent graphs, executions and
-- node-level runs to give a full picture of how engaged
-- each user is. Includes a convenience flag for 7-day
-- activation (did the user return at least 7 days after
-- their first login?).
--
-- SOURCE TABLES
-- auth.sessions — Login/session records
-- platform.AgentGraph — Graphs (agents) built by the user
-- platform.AgentGraphExecution — Agent run history
-- platform.AgentNodeExecution — Individual block execution history
--
-- PERFORMANCE NOTE
-- Each CTE aggregates its own table independently by userId.
-- This avoids the fan-out that occurs when driving every join
-- from user_logins across the two largest tables
-- (AgentGraphExecution and AgentNodeExecution).
--
-- OUTPUT COLUMNS
-- user_id TEXT Supabase user UUID
-- first_login_time TIMESTAMPTZ First ever session created_at
-- last_login_time TIMESTAMPTZ Most recent session created_at
-- last_visit_time TIMESTAMPTZ Max of last refresh or login
-- last_agent_save_time TIMESTAMPTZ Last time user saved an agent graph
-- agent_count BIGINT Number of distinct active graphs built (0 if none)
-- first_agent_run_time TIMESTAMPTZ First ever graph execution
-- last_agent_run_time TIMESTAMPTZ Most recent graph execution
-- unique_agent_runs BIGINT Distinct agent graphs ever run (0 if none)
-- agent_runs BIGINT Total graph execution count (0 if none)
-- node_execution_count BIGINT Total node executions across all runs
-- node_execution_failed BIGINT Node executions with FAILED status
-- node_execution_completed BIGINT Node executions with COMPLETED status
-- node_execution_terminated BIGINT Node executions with TERMINATED status
-- node_execution_queued BIGINT Node executions with QUEUED status
-- node_execution_running BIGINT Node executions with RUNNING status
-- is_active_after_7d INT 1=returned after day 7, 0=did not, NULL=too early to tell
-- node_execution_incomplete BIGINT Node executions with INCOMPLETE status
-- node_execution_review BIGINT Node executions with REVIEW status
--
-- EXAMPLE QUERIES
-- -- Users who ran at least one agent and returned after 7 days
-- SELECT COUNT(*) FROM analytics.users_activities
-- WHERE agent_runs > 0 AND is_active_after_7d = 1;
--
-- -- Top 10 most active users by agent runs
-- SELECT user_id, agent_runs, node_execution_count
-- FROM analytics.users_activities
-- ORDER BY agent_runs DESC LIMIT 10;
--
-- -- 7-day activation rate
-- SELECT
-- SUM(CASE WHEN is_active_after_7d = 1 THEN 1 ELSE 0 END)::float
-- / NULLIF(COUNT(CASE WHEN is_active_after_7d IS NOT NULL THEN 1 END), 0)
-- AS activation_rate
-- FROM analytics.users_activities;
-- =============================================================
WITH user_logins AS (
SELECT
user_id::text AS user_id,
MIN(created_at) AS first_login_time,
MAX(created_at) AS last_login_time,
GREATEST(
MAX(refreshed_at)::timestamptz,
MAX(created_at)::timestamptz
) AS last_visit_time
FROM auth.sessions
GROUP BY user_id
),
user_agents AS (
-- Aggregate AgentGraph directly by userId (no fan-out from user_logins)
SELECT
"userId"::text AS user_id,
MAX("updatedAt") AS last_agent_save_time,
COUNT(DISTINCT "id") AS agent_count
FROM platform."AgentGraph"
WHERE "isActive"
GROUP BY "userId"
),
user_graph_runs AS (
-- Aggregate AgentGraphExecution directly by userId
SELECT
"userId"::text AS user_id,
MIN("createdAt") AS first_agent_run_time,
MAX("createdAt") AS last_agent_run_time,
COUNT(DISTINCT "agentGraphId") AS unique_agent_runs,
COUNT("id") AS agent_runs
FROM platform."AgentGraphExecution"
GROUP BY "userId"
),
user_node_runs AS (
-- Aggregate AgentNodeExecution directly; resolve userId via a
-- single join to AgentGraphExecution instead of fanning out from
-- user_logins through both large tables.
SELECT
g."userId"::text AS user_id,
COUNT(*) AS node_execution_count,
COUNT(*) FILTER (WHERE n."executionStatus" = 'FAILED') AS node_execution_failed,
COUNT(*) FILTER (WHERE n."executionStatus" = 'COMPLETED') AS node_execution_completed,
COUNT(*) FILTER (WHERE n."executionStatus" = 'TERMINATED') AS node_execution_terminated,
COUNT(*) FILTER (WHERE n."executionStatus" = 'QUEUED') AS node_execution_queued,
COUNT(*) FILTER (WHERE n."executionStatus" = 'RUNNING') AS node_execution_running,
COUNT(*) FILTER (WHERE n."executionStatus" = 'INCOMPLETE') AS node_execution_incomplete,
COUNT(*) FILTER (WHERE n."executionStatus" = 'REVIEW') AS node_execution_review
FROM platform."AgentNodeExecution" n
JOIN platform."AgentGraphExecution" g
ON g."id" = n."agentGraphExecutionId"
GROUP BY g."userId"
)
SELECT
ul.user_id,
ul.first_login_time,
ul.last_login_time,
ul.last_visit_time,
ua.last_agent_save_time,
COALESCE(ua.agent_count, 0) AS agent_count,
gr.first_agent_run_time,
gr.last_agent_run_time,
COALESCE(gr.unique_agent_runs, 0) AS unique_agent_runs,
COALESCE(gr.agent_runs, 0) AS agent_runs,
COALESCE(nr.node_execution_count, 0) AS node_execution_count,
COALESCE(nr.node_execution_failed, 0) AS node_execution_failed,
COALESCE(nr.node_execution_completed, 0) AS node_execution_completed,
COALESCE(nr.node_execution_terminated, 0) AS node_execution_terminated,
COALESCE(nr.node_execution_queued, 0) AS node_execution_queued,
COALESCE(nr.node_execution_running, 0) AS node_execution_running,
CASE
WHEN ul.first_login_time < NOW() - INTERVAL '7 days'
AND ul.last_visit_time >= ul.first_login_time + INTERVAL '7 days' THEN 1
WHEN ul.first_login_time < NOW() - INTERVAL '7 days'
AND ul.last_visit_time < ul.first_login_time + INTERVAL '7 days' THEN 0
ELSE NULL
END AS is_active_after_7d,
COALESCE(nr.node_execution_incomplete, 0) AS node_execution_incomplete,
COALESCE(nr.node_execution_review, 0) AS node_execution_review
FROM user_logins ul
LEFT JOIN user_agents ua ON ul.user_id = ua.user_id
LEFT JOIN user_graph_runs gr ON ul.user_id = gr.user_id
LEFT JOIN user_node_runs nr ON ul.user_id = nr.user_id

View File

@@ -1,4 +1,4 @@
# This file is automatically @generated by Poetry 2.1.1 and should not be changed by hand.
# This file is automatically @generated by Poetry 2.2.1 and should not be changed by hand.
[[package]]
name = "annotated-doc"
@@ -67,7 +67,7 @@ description = "Backport of asyncio.Runner, a context manager that controls event
optional = false
python-versions = "<3.11,>=3.8"
groups = ["dev"]
markers = "python_version < \"3.11\""
markers = "python_version == \"3.10\""
files = [
{file = "backports_asyncio_runner-1.2.0-py3-none-any.whl", hash = "sha256:0da0a936a8aeb554eccb426dc55af3ba63bcdc69fa1a600b5bb305413a4477b5"},
{file = "backports_asyncio_runner-1.2.0.tar.gz", hash = "sha256:a5aa7b2b7d8f8bfcaa2b57313f70792df84e32a2a746f585213373f900b42162"},
@@ -541,7 +541,7 @@ description = "Backport of PEP 654 (exception groups)"
optional = false
python-versions = ">=3.7"
groups = ["main", "dev"]
markers = "python_version < \"3.11\""
markers = "python_version == \"3.10\""
files = [
{file = "exceptiongroup-1.3.0-py3-none-any.whl", hash = "sha256:4d111e6e0c13d0644cad6ddaa7ed0261a0b36971f6d23e7ec9b4b9097da78a10"},
{file = "exceptiongroup-1.3.0.tar.gz", hash = "sha256:b241f5885f560bc56a59ee63ca4c6a8bfa46ae4ad651af316d4e81817bb9fd88"},
@@ -2181,14 +2181,14 @@ testing = ["coverage (>=6.2)", "hypothesis (>=5.7.1)"]
[[package]]
name = "pytest-cov"
version = "7.0.0"
version = "7.1.0"
description = "Pytest plugin for measuring coverage."
optional = false
python-versions = ">=3.9"
groups = ["dev"]
files = [
{file = "pytest_cov-7.0.0-py3-none-any.whl", hash = "sha256:3b8e9558b16cc1479da72058bdecf8073661c7f57f7d3c5f22a1c23507f2d861"},
{file = "pytest_cov-7.0.0.tar.gz", hash = "sha256:33c97eda2e049a0c5298e91f519302a1334c26ac65c1a483d6206fd458361af1"},
{file = "pytest_cov-7.1.0-py3-none-any.whl", hash = "sha256:a0461110b7865f9a271aa1b51e516c9a95de9d696734a2f71e3e78f46e1d4678"},
{file = "pytest_cov-7.1.0.tar.gz", hash = "sha256:30674f2b5f6351aa09702a9c8c364f6a01c27aae0c1366ae8016160d1efc56b2"},
]
[package.dependencies]
@@ -2342,30 +2342,30 @@ pyasn1 = ">=0.1.3"
[[package]]
name = "ruff"
version = "0.15.0"
version = "0.15.7"
description = "An extremely fast Python linter and code formatter, written in Rust."
optional = false
python-versions = ">=3.7"
groups = ["dev"]
files = [
{file = "ruff-0.15.0-py3-none-linux_armv6l.whl", hash = "sha256:aac4ebaa612a82b23d45964586f24ae9bc23ca101919f5590bdb368d74ad5455"},
{file = "ruff-0.15.0-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:dcd4be7cc75cfbbca24a98d04d0b9b36a270d0833241f776b788d59f4142b14d"},
{file = "ruff-0.15.0-py3-none-macosx_11_0_arm64.whl", hash = "sha256:d747e3319b2bce179c7c1eaad3d884dc0a199b5f4d5187620530adf9105268ce"},
{file = "ruff-0.15.0-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:650bd9c56ae03102c51a5e4b554d74d825ff3abe4db22b90fd32d816c2e90621"},
{file = "ruff-0.15.0-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:a6664b7eac559e3048223a2da77769c2f92b43a6dfd4720cef42654299a599c9"},
{file = "ruff-0.15.0-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6f811f97b0f092b35320d1556f3353bf238763420ade5d9e62ebd2b73f2ff179"},
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{file = "ruff-0.15.0-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:940f11c2604d317e797b289f4f9f3fa5555ffe4fb574b55ed006c3d9b6f0eb78"},
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]
[[package]]
@@ -2564,7 +2564,7 @@ description = "A lil' TOML parser"
optional = false
python-versions = ">=3.8"
groups = ["dev"]
markers = "python_version < \"3.11\""
markers = "python_version == \"3.10\""
files = [
{file = "tomli-2.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:678e4fa69e4575eb77d103de3df8a895e1591b48e740211bd1067378c69e8249"},
{file = "tomli-2.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:023aa114dd824ade0100497eb2318602af309e5a55595f76b626d6d9f3b7b0a6"},
@@ -2912,4 +2912,4 @@ type = ["pytest-mypy"]
[metadata]
lock-version = "2.1"
python-versions = ">=3.10,<4.0"
content-hash = "9619cae908ad38fa2c48016a58bcf4241f6f5793aa0e6cc140276e91c433cbbb"
content-hash = "e0936a065565550afed18f6298b7e04e814b44100def7049f1a0d68662624a39"

View File

@@ -26,8 +26,8 @@ pyright = "^1.1.408"
pytest = "^8.4.1"
pytest-asyncio = "^1.3.0"
pytest-mock = "^3.15.1"
pytest-cov = "^7.0.0"
ruff = "^0.15.0"
pytest-cov = "^7.1.0"
ruff = "^0.15.7"
[build-system]
requires = ["poetry-core"]

View File

@@ -178,6 +178,7 @@ SMTP_USERNAME=
SMTP_PASSWORD=
# Business & Marketing Tools
AGENTMAIL_API_KEY=
APOLLO_API_KEY=
ENRICHLAYER_API_KEY=
AYRSHARE_API_KEY=

View File

@@ -0,0 +1,227 @@
# Backend
This file provides guidance to coding agents when working with the backend.
## Essential Commands
To run something with Python package dependencies you MUST use `poetry run ...`.
```bash
# Install dependencies
poetry install
# Run database migrations
poetry run prisma migrate dev
# Start all services (database, redis, rabbitmq, clamav)
docker compose up -d
# Run the backend as a whole
poetry run app
# Run tests
poetry run test
# Run specific test
poetry run pytest path/to/test_file.py::test_function_name
# Run block tests (tests that validate all blocks work correctly)
poetry run pytest backend/blocks/test/test_block.py -xvs
# Run tests for a specific block (e.g., GetCurrentTimeBlock)
poetry run pytest 'backend/blocks/test/test_block.py::test_available_blocks[GetCurrentTimeBlock]' -xvs
# Lint and format
# prefer format if you want to just "fix" it and only get the errors that can't be autofixed
poetry run format # Black + isort
poetry run lint # ruff
```
More details can be found in @TESTING.md
### Creating/Updating Snapshots
When you first write a test or when the expected output changes:
```bash
poetry run pytest path/to/test.py --snapshot-update
```
⚠️ **Important**: Always review snapshot changes before committing! Use `git diff` to verify the changes are expected.
## Architecture
- **API Layer**: FastAPI with REST and WebSocket endpoints
- **Database**: PostgreSQL with Prisma ORM, includes pgvector for embeddings
- **Queue System**: RabbitMQ for async task processing
- **Execution Engine**: Separate executor service processes agent workflows
- **Authentication**: JWT-based with Supabase integration
- **Security**: Cache protection middleware prevents sensitive data caching in browsers/proxies
## Code Style
- **Top-level imports only** — no local/inner imports (lazy imports only for heavy optional deps like `openpyxl`)
- **Absolute imports** — use `from backend.module import ...` for cross-package imports. Single-dot relative (`from .sibling import ...`) is acceptable for sibling modules within the same package (e.g., blocks). Avoid double-dot relative imports (`from ..parent import ...`) — use the absolute path instead
- **No duck typing** — no `hasattr`/`getattr`/`isinstance` for type dispatch; use typed interfaces/unions/protocols
- **Pydantic models** over dataclass/namedtuple/dict for structured data
- **No linter suppressors** — no `# type: ignore`, `# noqa`, `# pyright: ignore`; fix the type/code
- **List comprehensions** over manual loop-and-append
- **Early return** — guard clauses first, avoid deep nesting
- **f-strings vs printf syntax in log statements** — Use `%s` for deferred interpolation in `debug` statements, f-strings elsewhere for readability: `logger.debug("Processing %s items", count)`, `logger.info(f"Processing {count} items")`
- **Sanitize error paths** — `os.path.basename()` in error messages to avoid leaking directory structure
- **TOCTOU awareness** — avoid check-then-act patterns for file access and credit charging
- **`Security()` vs `Depends()`** — use `Security()` for auth deps to get proper OpenAPI security spec
- **Redis pipelines** — `transaction=True` for atomicity on multi-step operations
- **`max(0, value)` guards** — for computed values that should never be negative
- **SSE protocol** — `data:` lines for frontend-parsed events (must match Zod schema), `: comment` lines for heartbeats/status
- **File length** — keep files under ~300 lines; if a file grows beyond this, split by responsibility (e.g. extract helpers, models, or a sub-module into a new file). Never keep appending to a long file.
- **Function length** — keep functions under ~40 lines; extract named helpers when a function grows longer. Long functions are a sign of mixed concerns, not complexity.
- **Top-down ordering** — define the main/public function or class first, then the helpers it uses below. A reader should encounter high-level logic before implementation details.
## Testing Approach
- Uses pytest with snapshot testing for API responses
- Test files are colocated with source files (`*_test.py`)
- Mock at boundaries — mock where the symbol is **used**, not where it's **defined**
- After refactoring, update mock targets to match new module paths
- Use `AsyncMock` for async functions (`from unittest.mock import AsyncMock`)
### Test-Driven Development (TDD)
When fixing a bug or adding a feature, write the test **before** the implementation:
```python
# 1. Write a failing test marked xfail
@pytest.mark.xfail(reason="Bug #1234: widget crashes on empty input")
def test_widget_handles_empty_input():
result = widget.process("")
assert result == Widget.EMPTY_RESULT
# 2. Run it — confirm it fails (XFAIL)
# poetry run pytest path/to/test.py::test_widget_handles_empty_input -xvs
# 3. Implement the fix
# 4. Remove xfail, run again — confirm it passes
def test_widget_handles_empty_input():
result = widget.process("")
assert result == Widget.EMPTY_RESULT
```
This catches regressions and proves the fix actually works. **Every bug fix should include a test that would have caught it.**
## Database Schema
Key models (defined in `schema.prisma`):
- `User`: Authentication and profile data
- `AgentGraph`: Workflow definitions with version control
- `AgentGraphExecution`: Execution history and results
- `AgentNode`: Individual nodes in a workflow
- `StoreListing`: Marketplace listings for sharing agents
## Environment Configuration
- **Backend**: `.env.default` (defaults) → `.env` (user overrides)
## Common Development Tasks
### Adding a new block
Follow the comprehensive [Block SDK Guide](@../../docs/platform/block-sdk-guide.md) which covers:
- Provider configuration with `ProviderBuilder`
- Block schema definition
- Authentication (API keys, OAuth, webhooks)
- Testing and validation
- File organization
Quick steps:
1. Create new file in `backend/blocks/`
2. Configure provider using `ProviderBuilder` in `_config.py`
3. Inherit from `Block` base class
4. Define input/output schemas using `BlockSchema`
5. Implement async `run` method
6. Generate unique block ID using `uuid.uuid4()`
7. Test with `poetry run pytest backend/blocks/test/test_block.py`
Note: when making many new blocks analyze the interfaces for each of these blocks and picture if they would go well together in a graph-based editor or would they struggle to connect productively?
ex: do the inputs and outputs tie well together?
If you get any pushback or hit complex block conditions check the new_blocks guide in the docs.
#### Handling files in blocks with `store_media_file()`
When blocks need to work with files (images, videos, documents), use `store_media_file()` from `backend.util.file`. The `return_format` parameter determines what you get back:
| Format | Use When | Returns |
|--------|----------|---------|
| `"for_local_processing"` | Processing with local tools (ffmpeg, MoviePy, PIL) | Local file path (e.g., `"image.png"`) |
| `"for_external_api"` | Sending content to external APIs (Replicate, OpenAI) | Data URI (e.g., `"data:image/png;base64,..."`) |
| `"for_block_output"` | Returning output from your block | Smart: `workspace://` in CoPilot, data URI in graphs |
**Examples:**
```python
# INPUT: Need to process file locally with ffmpeg
local_path = await store_media_file(
file=input_data.video,
execution_context=execution_context,
return_format="for_local_processing",
)
# local_path = "video.mp4" - use with Path/ffmpeg/etc
# INPUT: Need to send to external API like Replicate
image_b64 = await store_media_file(
file=input_data.image,
execution_context=execution_context,
return_format="for_external_api",
)
# image_b64 = "data:image/png;base64,iVBORw0..." - send to API
# OUTPUT: Returning result from block
result_url = await store_media_file(
file=generated_image_url,
execution_context=execution_context,
return_format="for_block_output",
)
yield "image_url", result_url
# In CoPilot: result_url = "workspace://abc123"
# In graphs: result_url = "data:image/png;base64,..."
```
**Key points:**
- `for_block_output` is the ONLY format that auto-adapts to execution context
- Always use `for_block_output` for block outputs unless you have a specific reason not to
- Never hardcode workspace checks - let `for_block_output` handle it
### Modifying the API
1. Update route in `backend/api/features/`
2. Add/update Pydantic models in same directory
3. Write tests alongside the route file
4. Run `poetry run test` to verify
## Workspace & Media Files
**Read [Workspace & Media Architecture](../../docs/platform/workspace-media-architecture.md) when:**
- Working on CoPilot file upload/download features
- Building blocks that handle `MediaFileType` inputs/outputs
- Modifying `WorkspaceManager` or `store_media_file()`
- Debugging file persistence or virus scanning issues
Covers: `WorkspaceManager` (persistent storage with session scoping), `store_media_file()` (media normalization pipeline), and responsibility boundaries for virus scanning and persistence.
## Security Implementation
### Cache Protection Middleware
- Located in `backend/api/middleware/security.py`
- Default behavior: Disables caching for ALL endpoints with `Cache-Control: no-store, no-cache, must-revalidate, private`
- Uses an allow list approach - only explicitly permitted paths can be cached
- Cacheable paths include: static assets (`static/*`, `_next/static/*`), health checks, public store pages, documentation
- Prevents sensitive data (auth tokens, API keys, user data) from being cached by browsers/proxies
- To allow caching for a new endpoint, add it to `CACHEABLE_PATHS` in the middleware
- Applied to both main API server and external API applications

View File

@@ -1,170 +1 @@
# CLAUDE.md - Backend
This file provides guidance to Claude Code when working with the backend.
## Essential Commands
To run something with Python package dependencies you MUST use `poetry run ...`.
```bash
# Install dependencies
poetry install
# Run database migrations
poetry run prisma migrate dev
# Start all services (database, redis, rabbitmq, clamav)
docker compose up -d
# Run the backend as a whole
poetry run app
# Run tests
poetry run test
# Run specific test
poetry run pytest path/to/test_file.py::test_function_name
# Run block tests (tests that validate all blocks work correctly)
poetry run pytest backend/blocks/test/test_block.py -xvs
# Run tests for a specific block (e.g., GetCurrentTimeBlock)
poetry run pytest 'backend/blocks/test/test_block.py::test_available_blocks[GetCurrentTimeBlock]' -xvs
# Lint and format
# prefer format if you want to just "fix" it and only get the errors that can't be autofixed
poetry run format # Black + isort
poetry run lint # ruff
```
More details can be found in @TESTING.md
### Creating/Updating Snapshots
When you first write a test or when the expected output changes:
```bash
poetry run pytest path/to/test.py --snapshot-update
```
⚠️ **Important**: Always review snapshot changes before committing! Use `git diff` to verify the changes are expected.
## Architecture
- **API Layer**: FastAPI with REST and WebSocket endpoints
- **Database**: PostgreSQL with Prisma ORM, includes pgvector for embeddings
- **Queue System**: RabbitMQ for async task processing
- **Execution Engine**: Separate executor service processes agent workflows
- **Authentication**: JWT-based with Supabase integration
- **Security**: Cache protection middleware prevents sensitive data caching in browsers/proxies
## Testing Approach
- Uses pytest with snapshot testing for API responses
- Test files are colocated with source files (`*_test.py`)
## Database Schema
Key models (defined in `schema.prisma`):
- `User`: Authentication and profile data
- `AgentGraph`: Workflow definitions with version control
- `AgentGraphExecution`: Execution history and results
- `AgentNode`: Individual nodes in a workflow
- `StoreListing`: Marketplace listings for sharing agents
## Environment Configuration
- **Backend**: `.env.default` (defaults) → `.env` (user overrides)
## Common Development Tasks
### Adding a new block
Follow the comprehensive [Block SDK Guide](@../../docs/content/platform/block-sdk-guide.md) which covers:
- Provider configuration with `ProviderBuilder`
- Block schema definition
- Authentication (API keys, OAuth, webhooks)
- Testing and validation
- File organization
Quick steps:
1. Create new file in `backend/blocks/`
2. Configure provider using `ProviderBuilder` in `_config.py`
3. Inherit from `Block` base class
4. Define input/output schemas using `BlockSchema`
5. Implement async `run` method
6. Generate unique block ID using `uuid.uuid4()`
7. Test with `poetry run pytest backend/blocks/test/test_block.py`
Note: when making many new blocks analyze the interfaces for each of these blocks and picture if they would go well together in a graph-based editor or would they struggle to connect productively?
ex: do the inputs and outputs tie well together?
If you get any pushback or hit complex block conditions check the new_blocks guide in the docs.
#### Handling files in blocks with `store_media_file()`
When blocks need to work with files (images, videos, documents), use `store_media_file()` from `backend.util.file`. The `return_format` parameter determines what you get back:
| Format | Use When | Returns |
|--------|----------|---------|
| `"for_local_processing"` | Processing with local tools (ffmpeg, MoviePy, PIL) | Local file path (e.g., `"image.png"`) |
| `"for_external_api"` | Sending content to external APIs (Replicate, OpenAI) | Data URI (e.g., `"data:image/png;base64,..."`) |
| `"for_block_output"` | Returning output from your block | Smart: `workspace://` in CoPilot, data URI in graphs |
**Examples:**
```python
# INPUT: Need to process file locally with ffmpeg
local_path = await store_media_file(
file=input_data.video,
execution_context=execution_context,
return_format="for_local_processing",
)
# local_path = "video.mp4" - use with Path/ffmpeg/etc
# INPUT: Need to send to external API like Replicate
image_b64 = await store_media_file(
file=input_data.image,
execution_context=execution_context,
return_format="for_external_api",
)
# image_b64 = "data:image/png;base64,iVBORw0..." - send to API
# OUTPUT: Returning result from block
result_url = await store_media_file(
file=generated_image_url,
execution_context=execution_context,
return_format="for_block_output",
)
yield "image_url", result_url
# In CoPilot: result_url = "workspace://abc123"
# In graphs: result_url = "data:image/png;base64,..."
```
**Key points:**
- `for_block_output` is the ONLY format that auto-adapts to execution context
- Always use `for_block_output` for block outputs unless you have a specific reason not to
- Never hardcode workspace checks - let `for_block_output` handle it
### Modifying the API
1. Update route in `backend/api/features/`
2. Add/update Pydantic models in same directory
3. Write tests alongside the route file
4. Run `poetry run test` to verify
## Security Implementation
### Cache Protection Middleware
- Located in `backend/api/middleware/security.py`
- Default behavior: Disables caching for ALL endpoints with `Cache-Control: no-store, no-cache, must-revalidate, private`
- Uses an allow list approach - only explicitly permitted paths can be cached
- Cacheable paths include: static assets (`static/*`, `_next/static/*`), health checks, public store pages, documentation
- Prevents sensitive data (auth tokens, API keys, user data) from being cached by browsers/proxies
- To allow caching for a new endpoint, add it to `CACHEABLE_PATHS` in the middleware
- Applied to both main API server and external API applications
@AGENTS.md

View File

@@ -50,7 +50,7 @@ RUN poetry install --no-ansi --no-root
# Generate Prisma client
COPY autogpt_platform/backend/schema.prisma ./
COPY autogpt_platform/backend/backend/data/partial_types.py ./backend/data/partial_types.py
COPY autogpt_platform/backend/gen_prisma_types_stub.py ./
COPY autogpt_platform/backend/scripts/gen_prisma_types_stub.py ./scripts/
RUN poetry run prisma generate && poetry run gen-prisma-stub
# =============================== DB MIGRATOR =============================== #
@@ -82,7 +82,7 @@ RUN pip3 install prisma>=0.15.0 --break-system-packages
COPY autogpt_platform/backend/schema.prisma ./
COPY autogpt_platform/backend/backend/data/partial_types.py ./backend/data/partial_types.py
COPY autogpt_platform/backend/gen_prisma_types_stub.py ./
COPY autogpt_platform/backend/scripts/gen_prisma_types_stub.py ./scripts/
COPY autogpt_platform/backend/migrations ./migrations
# ============================== BACKEND SERVER ============================== #
@@ -95,7 +95,7 @@ ENV DEBIAN_FRONTEND=noninteractive
# Install Python, FFmpeg, ImageMagick, and CLI tools for agent use.
# bubblewrap provides OS-level sandbox (whitelist-only FS + no network)
# for the bash_exec MCP tool.
# for the bash_exec MCP tool (fallback when E2B is not configured).
# Using --no-install-recommends saves ~650MB by skipping unnecessary deps like llvm, mesa, etc.
RUN apt-get update && apt-get install -y --no-install-recommends \
python3.13 \
@@ -111,13 +111,31 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
# Copy poetry (build-time only, for `poetry install --only-root` to create entry points)
COPY --from=builder /usr/local/lib/python3* /usr/local/lib/python3*
COPY --from=builder /usr/local/bin/poetry /usr/local/bin/poetry
# Copy Node.js installation for Prisma
# Copy Node.js installation for Prisma and agent-browser.
# npm/npx are symlinks in the builder (-> ../lib/node_modules/npm/bin/*-cli.js);
# COPY resolves them to regular files, breaking require() paths. Recreate as
# proper symlinks so npm/npx can find their modules.
COPY --from=builder /usr/bin/node /usr/bin/node
COPY --from=builder /usr/lib/node_modules /usr/lib/node_modules
COPY --from=builder /usr/bin/npm /usr/bin/npm
COPY --from=builder /usr/bin/npx /usr/bin/npx
RUN ln -s ../lib/node_modules/npm/bin/npm-cli.js /usr/bin/npm \
&& ln -s ../lib/node_modules/npm/bin/npx-cli.js /usr/bin/npx
COPY --from=builder /root/.cache/prisma-python/binaries /root/.cache/prisma-python/binaries
# Install agent-browser (Copilot browser tool) using the system chromium package.
# Chrome for Testing (the binary agent-browser downloads via `agent-browser install`)
# has no ARM64 builds, so we use the distro-packaged chromium instead — verified to
# work with agent-browser via Docker tests on arm64; amd64 is validated in CI.
# Note: system chromium tracks the Debian package schedule rather than a pinned
# Chrome for Testing release. If agent-browser requires a specific Chrome version,
# verify compatibility against the chromium package version in the base image.
RUN apt-get update \
&& apt-get install -y --no-install-recommends chromium fonts-liberation \
&& rm -rf /var/lib/apt/lists/* \
&& npm install -g agent-browser \
&& rm -rf /tmp/* /root/.npm
ENV AGENT_BROWSER_EXECUTABLE_PATH=/usr/bin/chromium
WORKDIR /app/autogpt_platform/backend
# Copy only the .venv from builder (not the entire /app directory)

View File

@@ -18,14 +18,22 @@ from pydantic import BaseModel, Field, SecretStr
from backend.api.external.middleware import require_permission
from backend.api.features.integrations.models import get_all_provider_names
from backend.api.features.integrations.router import (
CredentialsMetaResponse,
to_meta_response,
)
from backend.data.auth.base import APIAuthorizationInfo
from backend.data.model import (
APIKeyCredentials,
Credentials,
CredentialsType,
HostScopedCredentials,
OAuth2Credentials,
UserPasswordCredentials,
is_sdk_default,
)
from backend.integrations.credentials_store import (
is_system_credential,
provider_matches,
)
from backend.integrations.creds_manager import IntegrationCredentialsManager
from backend.integrations.oauth import CREDENTIALS_BY_PROVIDER, HANDLERS_BY_NAME
@@ -91,18 +99,6 @@ class OAuthCompleteResponse(BaseModel):
)
class CredentialSummary(BaseModel):
"""Summary of a credential without sensitive data."""
id: str
provider: str
type: CredentialsType
title: Optional[str] = None
scopes: Optional[list[str]] = None
username: Optional[str] = None
host: Optional[str] = None
class ProviderInfo(BaseModel):
"""Information about an integration provider."""
@@ -473,12 +469,12 @@ async def complete_oauth(
)
@integrations_router.get("/credentials", response_model=list[CredentialSummary])
@integrations_router.get("/credentials", response_model=list[CredentialsMetaResponse])
async def list_credentials(
auth: APIAuthorizationInfo = Security(
require_permission(APIKeyPermission.READ_INTEGRATIONS)
),
) -> list[CredentialSummary]:
) -> list[CredentialsMetaResponse]:
"""
List all credentials for the authenticated user.
@@ -486,28 +482,19 @@ async def list_credentials(
"""
credentials = await creds_manager.store.get_all_creds(auth.user_id)
return [
CredentialSummary(
id=cred.id,
provider=cred.provider,
type=cred.type,
title=cred.title,
scopes=cred.scopes if isinstance(cred, OAuth2Credentials) else None,
username=cred.username if isinstance(cred, OAuth2Credentials) else None,
host=cred.host if isinstance(cred, HostScopedCredentials) else None,
)
for cred in credentials
to_meta_response(cred) for cred in credentials if not is_sdk_default(cred.id)
]
@integrations_router.get(
"/{provider}/credentials", response_model=list[CredentialSummary]
"/{provider}/credentials", response_model=list[CredentialsMetaResponse]
)
async def list_credentials_by_provider(
provider: Annotated[str, Path(title="The provider to list credentials for")],
auth: APIAuthorizationInfo = Security(
require_permission(APIKeyPermission.READ_INTEGRATIONS)
),
) -> list[CredentialSummary]:
) -> list[CredentialsMetaResponse]:
"""
List credentials for a specific provider.
"""
@@ -515,16 +502,7 @@ async def list_credentials_by_provider(
auth.user_id, provider
)
return [
CredentialSummary(
id=cred.id,
provider=cred.provider,
type=cred.type,
title=cred.title,
scopes=cred.scopes if isinstance(cred, OAuth2Credentials) else None,
username=cred.username if isinstance(cred, OAuth2Credentials) else None,
host=cred.host if isinstance(cred, HostScopedCredentials) else None,
)
for cred in credentials
to_meta_response(cred) for cred in credentials if not is_sdk_default(cred.id)
]
@@ -597,11 +575,11 @@ async def create_credential(
# Store credentials
try:
await creds_manager.create(auth.user_id, credentials)
except Exception as e:
logger.error(f"Failed to store credentials: {e}")
except Exception:
logger.exception("Failed to store credentials")
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=f"Failed to store credentials: {str(e)}",
detail="Failed to store credentials",
)
logger.info(f"Created {request.type} credentials for provider {provider}")
@@ -639,15 +617,23 @@ async def delete_credential(
use the main API's delete endpoint which handles webhook cleanup and
token revocation.
"""
if is_sdk_default(cred_id):
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND, detail="Credentials not found"
)
if is_system_credential(cred_id):
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail="System-managed credentials cannot be deleted",
)
creds = await creds_manager.store.get_creds_by_id(auth.user_id, cred_id)
if not creds:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND, detail="Credentials not found"
)
if creds.provider != provider:
if not provider_matches(creds.provider, provider):
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Credentials do not match the specified provider",
status_code=status.HTTP_404_NOT_FOUND, detail="Credentials not found"
)
await creds_manager.delete(auth.user_id, cred_id)

View File

@@ -1,7 +1,7 @@
import logging
import urllib.parse
from collections import defaultdict
from typing import Annotated, Any, Literal, Optional, Sequence
from typing import Annotated, Any, Optional, Sequence
from fastapi import APIRouter, Body, HTTPException, Security
from prisma.enums import AgentExecutionStatus, APIKeyPermission
@@ -9,9 +9,10 @@ from pydantic import BaseModel, Field
from typing_extensions import TypedDict
import backend.api.features.store.cache as store_cache
import backend.api.features.store.db as store_db
import backend.api.features.store.model as store_model
import backend.blocks
from backend.api.external.middleware import require_permission
from backend.api.external.middleware import require_auth, require_permission
from backend.data import execution as execution_db
from backend.data import graph as graph_db
from backend.data import user as user_db
@@ -230,13 +231,13 @@ async def get_graph_execution_results(
@v1_router.get(
path="/store/agents",
tags=["store"],
dependencies=[Security(require_permission(APIKeyPermission.READ_STORE))],
dependencies=[Security(require_auth)], # data is public; auth required as anti-DDoS
response_model=store_model.StoreAgentsResponse,
)
async def get_store_agents(
featured: bool = False,
creator: str | None = None,
sorted_by: Literal["rating", "runs", "name", "updated_at"] | None = None,
sorted_by: store_db.StoreAgentsSortOptions | None = None,
search_query: str | None = None,
category: str | None = None,
page: int = 1,
@@ -278,7 +279,7 @@ async def get_store_agents(
@v1_router.get(
path="/store/agents/{username}/{agent_name}",
tags=["store"],
dependencies=[Security(require_permission(APIKeyPermission.READ_STORE))],
dependencies=[Security(require_auth)], # data is public; auth required as anti-DDoS
response_model=store_model.StoreAgentDetails,
)
async def get_store_agent(
@@ -306,13 +307,13 @@ async def get_store_agent(
@v1_router.get(
path="/store/creators",
tags=["store"],
dependencies=[Security(require_permission(APIKeyPermission.READ_STORE))],
dependencies=[Security(require_auth)], # data is public; auth required as anti-DDoS
response_model=store_model.CreatorsResponse,
)
async def get_store_creators(
featured: bool = False,
search_query: str | None = None,
sorted_by: Literal["agent_rating", "agent_runs", "num_agents"] | None = None,
sorted_by: store_db.StoreCreatorsSortOptions | None = None,
page: int = 1,
page_size: int = 20,
) -> store_model.CreatorsResponse:
@@ -348,7 +349,7 @@ async def get_store_creators(
@v1_router.get(
path="/store/creators/{username}",
tags=["store"],
dependencies=[Security(require_permission(APIKeyPermission.READ_STORE))],
dependencies=[Security(require_auth)], # data is public; auth required as anti-DDoS
response_model=store_model.CreatorDetails,
)
async def get_store_creator(

View File

@@ -72,7 +72,7 @@ class RunAgentRequest(BaseModel):
def _create_ephemeral_session(user_id: str) -> ChatSession:
"""Create an ephemeral session for stateless API requests."""
return ChatSession.new(user_id)
return ChatSession.new(user_id, dry_run=False)
@tools_router.post(

View File

@@ -0,0 +1,98 @@
import logging
from datetime import datetime
from autogpt_libs.auth import get_user_id, requires_admin_user
from cachetools import TTLCache
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,
)
from backend.util.models import Pagination
logger = logging.getLogger(__name__)
# Cache dashboard results for 30 seconds per unique filter combination.
# The table is append-only so stale reads are acceptable for analytics.
_DASHBOARD_CACHE_TTL = 30
_dashboard_cache: TTLCache[tuple, PlatformCostDashboard] = TTLCache(
maxsize=256, ttl=_DASHBOARD_CACHE_TTL
)
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),
):
logger.info("Admin %s fetching platform cost dashboard", admin_user_id)
cache_key = (start, end, provider, user_id)
cached = _dashboard_cache.get(cache_key)
if cached is not None:
return cached
result = await get_platform_cost_dashboard(
start=start,
end=end,
provider=provider,
user_id=user_id,
)
_dashboard_cache[cache_key] = result
return result
@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),
):
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,
)
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,
),
)

View File

@@ -0,0 +1,192 @@
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 PlatformCostDashboard
from . import platform_cost_routes
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"]
# Clear TTL cache so each test starts cold.
platform_cost_routes._dashboard_cache.clear()
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_cache_hit(
mocker: pytest_mock.MockerFixture,
) -> None:
"""Second identical request returns cached result without calling the DB again."""
real_dashboard = PlatformCostDashboard(
by_provider=[],
by_user=[],
total_cost_microdollars=42,
total_requests=1,
total_users=1,
)
mock_fn = mocker.patch(
"backend.api.features.admin.platform_cost_routes.get_platform_cost_dashboard",
AsyncMock(return_value=real_dashboard),
)
client.get("/platform-costs/dashboard")
client.get("/platform-costs/dashboard")
mock_fn.assert_awaited_once() # second request hit the cache

View File

@@ -0,0 +1,259 @@
"""Admin endpoints for checking and resetting user CoPilot rate limit usage."""
import logging
from typing import Optional
from autogpt_libs.auth import get_user_id, requires_admin_user
from fastapi import APIRouter, Body, HTTPException, Security
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, search_users
logger = logging.getLogger(__name__)
config = ChatConfig()
router = APIRouter(
prefix="/admin",
tags=["copilot", "admin"],
dependencies=[Security(requires_admin_user)],
)
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
tier: SubscriptionTier
class UserTierResponse(BaseModel):
user_id: str
tier: SubscriptionTier
class SetUserTierRequest(BaseModel):
user_id: str
tier: SubscriptionTier
async def _resolve_user_id(
user_id: Optional[str], email: Optional[str]
) -> tuple[str, Optional[str]]:
"""Resolve a user_id and email from the provided parameters.
Returns (user_id, email). Accepts either user_id or email; at least one
must be provided. When both are provided, ``email`` takes precedence.
"""
if email:
user = await get_user_by_email(email)
if not user:
raise HTTPException(
status_code=404, detail="No user found with the provided email."
)
return user.id, email
if not user_id:
raise HTTPException(
status_code=400,
detail="Either user_id or email query parameter is required.",
)
# We have a user_id; try to look up their email for display purposes.
# This is non-critical -- a failure should not block the response.
try:
resolved_email = await get_user_email_by_id(user_id)
except Exception:
logger.warning("Failed to resolve email for user %s", user_id, exc_info=True)
resolved_email = None
return user_id, resolved_email
@router.get(
"/rate_limit",
response_model=UserRateLimitResponse,
summary="Get User Rate Limit",
)
async def get_user_rate_limit(
user_id: Optional[str] = None,
email: Optional[str] = None,
admin_user_id: str = Security(get_user_id),
) -> UserRateLimitResponse:
"""Get a user's current usage and effective rate limits. Admin-only.
Accepts either ``user_id`` or ``email`` as a query parameter.
When ``email`` is provided the user is looked up by email first.
"""
resolved_id, resolved_email = await _resolve_user_id(user_id, email)
logger.info("Admin %s checking rate limit for user %s", admin_user_id, resolved_id)
daily_limit, weekly_limit, tier = await get_global_rate_limits(
resolved_id, config.daily_token_limit, config.weekly_token_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,
tier=tier,
)
@router.post(
"/rate_limit/reset",
response_model=UserRateLimitResponse,
summary="Reset User Rate Limit Usage",
)
async def reset_user_rate_limit(
user_id: str = Body(embed=True),
reset_weekly: bool = Body(False, embed=True),
admin_user_id: str = Security(get_user_id),
) -> UserRateLimitResponse:
"""Reset a user's daily usage counter (and optionally weekly). Admin-only."""
logger.info(
"Admin %s resetting rate limit for user %s (reset_weekly=%s)",
admin_user_id,
user_id,
reset_weekly,
)
try:
await reset_user_usage(user_id, reset_weekly=reset_weekly)
except Exception as e:
logger.exception("Failed to reset user usage")
raise HTTPException(status_code=500, detail="Failed to reset usage") from e
daily_limit, weekly_limit, tier = await get_global_rate_limits(
user_id, config.daily_token_limit, config.weekly_token_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)
except Exception:
logger.warning("Failed to resolve email for user %s", user_id, exc_info=True)
resolved_email = None
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,
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

@@ -0,0 +1,566 @@
import json
from types import SimpleNamespace
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 pytest_snapshot.plugin import Snapshot
from backend.copilot.rate_limit import CoPilotUsageStatus, SubscriptionTier, UsageWindow
from .rate_limit_admin_routes import router as rate_limit_admin_router
app = fastapi.FastAPI()
app.include_router(rate_limit_admin_router)
client = fastapi.testclient.TestClient(app)
_MOCK_MODULE = "backend.api.features.admin.rate_limit_admin_routes"
_TARGET_EMAIL = "target@example.com"
@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 _mock_usage_status(
daily_used: int = 500_000, weekly_used: int = 3_000_000
) -> CoPilotUsageStatus:
from datetime import UTC, datetime, timedelta
now = datetime.now(UTC)
return CoPilotUsageStatus(
daily=UsageWindow(
used=daily_used, limit=2_500_000, resets_at=now + timedelta(hours=6)
),
weekly=UsageWindow(
used=weekly_used, limit=12_500_000, resets_at=now + timedelta(days=3)
),
)
def _patch_rate_limit_deps(
mocker: pytest_mock.MockerFixture,
target_user_id: str,
daily_used: int = 500_000,
weekly_used: int = 3_000_000,
):
"""Patch the common rate-limit + user-lookup dependencies."""
mocker.patch(
f"{_MOCK_MODULE}.get_global_rate_limits",
new_callable=AsyncMock,
return_value=(2_500_000, 12_500_000, SubscriptionTier.FREE),
)
mocker.patch(
f"{_MOCK_MODULE}.get_usage_status",
new_callable=AsyncMock,
return_value=_mock_usage_status(daily_used=daily_used, weekly_used=weekly_used),
)
mocker.patch(
f"{_MOCK_MODULE}.get_user_email_by_id",
new_callable=AsyncMock,
return_value=_TARGET_EMAIL,
)
def test_get_rate_limit(
mocker: pytest_mock.MockerFixture,
configured_snapshot: Snapshot,
target_user_id: str,
) -> None:
"""Test getting rate limit and usage for a user."""
_patch_rate_limit_deps(mocker, target_user_id)
response = client.get("/admin/rate_limit", params={"user_id": target_user_id})
assert response.status_code == 200
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["tier"] == "FREE"
configured_snapshot.assert_match(
json.dumps(data, indent=2, sort_keys=True) + "\n",
"get_rate_limit",
)
def test_get_rate_limit_by_email(
mocker: pytest_mock.MockerFixture,
target_user_id: str,
) -> None:
"""Test looking up rate limits via email instead of user_id."""
_patch_rate_limit_deps(mocker, target_user_id)
mock_user = SimpleNamespace(id=target_user_id, email=_TARGET_EMAIL)
mocker.patch(
f"{_MOCK_MODULE}.get_user_by_email",
new_callable=AsyncMock,
return_value=mock_user,
)
response = client.get("/admin/rate_limit", params={"email": _TARGET_EMAIL})
assert response.status_code == 200
data = response.json()
assert data["user_id"] == target_user_id
assert data["user_email"] == _TARGET_EMAIL
assert data["daily_token_limit"] == 2_500_000
def test_get_rate_limit_by_email_not_found(
mocker: pytest_mock.MockerFixture,
) -> None:
"""Test that looking up a non-existent email returns 404."""
mocker.patch(
f"{_MOCK_MODULE}.get_user_by_email",
new_callable=AsyncMock,
return_value=None,
)
response = client.get("/admin/rate_limit", params={"email": "nobody@example.com"})
assert response.status_code == 404
def test_get_rate_limit_no_params() -> None:
"""Test that omitting both user_id and email returns 400."""
response = client.get("/admin/rate_limit")
assert response.status_code == 400
def test_reset_user_usage_daily_only(
mocker: pytest_mock.MockerFixture,
configured_snapshot: Snapshot,
target_user_id: str,
) -> None:
"""Test resetting only daily usage (default behaviour)."""
mock_reset = mocker.patch(
f"{_MOCK_MODULE}.reset_user_usage",
new_callable=AsyncMock,
)
_patch_rate_limit_deps(mocker, target_user_id, daily_used=0, weekly_used=3_000_000)
response = client.post(
"/admin/rate_limit/reset",
json={"user_id": target_user_id},
)
assert response.status_code == 200
data = response.json()
assert data["daily_tokens_used"] == 0
# Weekly is untouched
assert data["weekly_tokens_used"] == 3_000_000
assert data["tier"] == "FREE"
mock_reset.assert_awaited_once_with(target_user_id, reset_weekly=False)
configured_snapshot.assert_match(
json.dumps(data, indent=2, sort_keys=True) + "\n",
"reset_user_usage_daily_only",
)
def test_reset_user_usage_daily_and_weekly(
mocker: pytest_mock.MockerFixture,
configured_snapshot: Snapshot,
target_user_id: str,
) -> None:
"""Test resetting both daily and weekly usage."""
mock_reset = mocker.patch(
f"{_MOCK_MODULE}.reset_user_usage",
new_callable=AsyncMock,
)
_patch_rate_limit_deps(mocker, target_user_id, daily_used=0, weekly_used=0)
response = client.post(
"/admin/rate_limit/reset",
json={"user_id": target_user_id, "reset_weekly": True},
)
assert response.status_code == 200
data = response.json()
assert data["daily_tokens_used"] == 0
assert data["weekly_tokens_used"] == 0
assert data["tier"] == "FREE"
mock_reset.assert_awaited_once_with(target_user_id, reset_weekly=True)
configured_snapshot.assert_match(
json.dumps(data, indent=2, sort_keys=True) + "\n",
"reset_user_usage_daily_and_weekly",
)
def test_reset_user_usage_redis_failure(
mocker: pytest_mock.MockerFixture,
target_user_id: str,
) -> None:
"""Test that Redis failure on reset returns 500."""
mocker.patch(
f"{_MOCK_MODULE}.reset_user_usage",
new_callable=AsyncMock,
side_effect=Exception("Redis connection refused"),
)
response = client.post(
"/admin/rate_limit/reset",
json={"user_id": target_user_id},
)
assert response.status_code == 500
def test_get_rate_limit_email_lookup_failure(
mocker: pytest_mock.MockerFixture,
target_user_id: str,
) -> None:
"""Test that failing to resolve a user email degrades gracefully."""
mocker.patch(
f"{_MOCK_MODULE}.get_global_rate_limits",
new_callable=AsyncMock,
return_value=(2_500_000, 12_500_000, SubscriptionTier.FREE),
)
mocker.patch(
f"{_MOCK_MODULE}.get_usage_status",
new_callable=AsyncMock,
return_value=_mock_usage_status(),
)
mocker.patch(
f"{_MOCK_MODULE}.get_user_email_by_id",
new_callable=AsyncMock,
side_effect=Exception("DB connection lost"),
)
response = client.get("/admin/rate_limit", params={"user_id": target_user_id})
assert response.status_code == 200
data = response.json()
assert data["user_id"] == target_user_id
assert data["user_email"] is None
def test_admin_endpoints_require_admin_role(mock_jwt_user) -> None:
"""Test that rate limit admin endpoints require admin role."""
app.dependency_overrides[get_jwt_payload] = mock_jwt_user["get_jwt_payload"]
response = client.get("/admin/rate_limit", params={"user_id": "test"})
assert response.status_code == 403
response = client.post(
"/admin/rate_limit/reset",
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.FREE,
)
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 FREE."""
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": "FREE"},
)
assert response.status_code == 200
data = response.json()
assert data["user_id"] == target_user_id
assert data["tier"] == "FREE"
mock_set.assert_awaited_once_with(target_user_id, SubscriptionTier.FREE)
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.FREE,
)
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

@@ -7,6 +7,8 @@ import fastapi
import fastapi.responses
import prisma.enums
import backend.api.features.library.db as library_db
import backend.api.features.library.model as library_model
import backend.api.features.store.cache as store_cache
import backend.api.features.store.db as store_db
import backend.api.features.store.model as store_model
@@ -24,14 +26,13 @@ router = fastapi.APIRouter(
@router.get(
"/listings",
summary="Get Admin Listings History",
response_model=store_model.StoreListingsWithVersionsResponse,
)
async def get_admin_listings_with_versions(
status: typing.Optional[prisma.enums.SubmissionStatus] = None,
search: typing.Optional[str] = None,
page: int = 1,
page_size: int = 20,
):
) -> store_model.StoreListingsWithVersionsAdminViewResponse:
"""
Get store listings with their version history for admins.
@@ -45,36 +46,26 @@ async def get_admin_listings_with_versions(
page_size: Number of items per page
Returns:
StoreListingsWithVersionsResponse with listings and their versions
Paginated listings with their versions
"""
try:
listings = await store_db.get_admin_listings_with_versions(
status=status,
search_query=search,
page=page,
page_size=page_size,
)
return listings
except Exception as e:
logger.exception("Error getting admin listings with versions: %s", e)
return fastapi.responses.JSONResponse(
status_code=500,
content={
"detail": "An error occurred while retrieving listings with versions"
},
)
listings = await store_db.get_admin_listings_with_versions(
status=status,
search_query=search,
page=page,
page_size=page_size,
)
return listings
@router.post(
"/submissions/{store_listing_version_id}/review",
summary="Review Store Submission",
response_model=store_model.StoreSubmission,
)
async def review_submission(
store_listing_version_id: str,
request: store_model.ReviewSubmissionRequest,
user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
):
) -> store_model.StoreSubmissionAdminView:
"""
Review a store listing submission.
@@ -84,31 +75,24 @@ async def review_submission(
user_id: Authenticated admin user performing the review
Returns:
StoreSubmission with updated review information
StoreSubmissionAdminView with updated review information
"""
try:
already_approved = await store_db.check_submission_already_approved(
store_listing_version_id=store_listing_version_id,
)
submission = await store_db.review_store_submission(
store_listing_version_id=store_listing_version_id,
is_approved=request.is_approved,
external_comments=request.comments,
internal_comments=request.internal_comments or "",
reviewer_id=user_id,
)
already_approved = await store_db.check_submission_already_approved(
store_listing_version_id=store_listing_version_id,
)
submission = await store_db.review_store_submission(
store_listing_version_id=store_listing_version_id,
is_approved=request.is_approved,
external_comments=request.comments,
internal_comments=request.internal_comments or "",
reviewer_id=user_id,
)
state_changed = already_approved != request.is_approved
# Clear caches when the request is approved as it updates what is shown on the store
if state_changed:
store_cache.clear_all_caches()
return submission
except Exception as e:
logger.exception("Error reviewing submission: %s", e)
return fastapi.responses.JSONResponse(
status_code=500,
content={"detail": "An error occurred while reviewing the submission"},
)
state_changed = already_approved != request.is_approved
# Clear caches whenever approval state changes, since store visibility can change
if state_changed:
store_cache.clear_all_caches()
return submission
@router.get(
@@ -150,3 +134,40 @@ async def admin_download_agent_file(
return fastapi.responses.FileResponse(
tmp_file.name, filename=file_name, media_type="application/json"
)
@router.get(
"/submissions/{store_listing_version_id}/preview",
summary="Admin Preview Submission Listing",
)
async def admin_preview_submission(
store_listing_version_id: str,
) -> store_model.StoreAgentDetails:
"""
Preview a marketplace submission as it would appear on the listing page.
Bypasses the APPROVED-only StoreAgent view so admins can preview pending
submissions before approving.
"""
return await store_db.get_store_agent_details_as_admin(store_listing_version_id)
@router.post(
"/submissions/{store_listing_version_id}/add-to-library",
summary="Admin Add Pending Agent to Library",
status_code=201,
)
async def admin_add_agent_to_library(
store_listing_version_id: str,
user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
) -> library_model.LibraryAgent:
"""
Add a pending marketplace agent to the admin's library for review.
Uses admin-level access to bypass marketplace APPROVED-only checks.
The builder can load the graph because get_graph() checks library
membership as a fallback: "you added it, you keep it."
"""
return await library_db.add_store_agent_to_library_as_admin(
store_listing_version_id=store_listing_version_id,
user_id=user_id,
)

View File

@@ -0,0 +1,335 @@
"""Tests for admin store routes and the bypass logic they depend on.
Tests are organized by what they protect:
- SECRT-2162: get_graph_as_admin bypasses ownership/marketplace checks
- SECRT-2167 security: admin endpoints reject non-admin users
- SECRT-2167 bypass: preview queries StoreListingVersion (not StoreAgent view),
and add-to-library uses get_graph_as_admin (not get_graph)
"""
from datetime import datetime, timezone
from unittest.mock import AsyncMock, MagicMock, patch
import fastapi
import fastapi.responses
import fastapi.testclient
import pytest
import pytest_mock
from autogpt_libs.auth.jwt_utils import get_jwt_payload
from backend.data.graph import get_graph_as_admin
from backend.util.exceptions import NotFoundError
from .store_admin_routes import router as store_admin_router
# Shared constants
ADMIN_USER_ID = "admin-user-id"
CREATOR_USER_ID = "other-creator-id"
GRAPH_ID = "test-graph-id"
GRAPH_VERSION = 3
SLV_ID = "test-store-listing-version-id"
def _make_mock_graph(user_id: str = CREATOR_USER_ID) -> MagicMock:
graph = MagicMock()
graph.userId = user_id
graph.id = GRAPH_ID
graph.version = GRAPH_VERSION
graph.Nodes = []
return graph
# ---- SECRT-2162: get_graph_as_admin bypasses ownership checks ---- #
@pytest.mark.asyncio
async def test_admin_can_access_pending_agent_not_owned() -> None:
"""get_graph_as_admin must return a graph even when the admin doesn't own
it and it's not APPROVED in the marketplace."""
mock_graph = _make_mock_graph()
mock_graph_model = MagicMock(name="GraphModel")
with (
patch("backend.data.graph.AgentGraph.prisma") as mock_prisma,
patch(
"backend.data.graph.GraphModel.from_db",
return_value=mock_graph_model,
),
):
mock_prisma.return_value.find_first = AsyncMock(return_value=mock_graph)
result = await get_graph_as_admin(
graph_id=GRAPH_ID,
version=GRAPH_VERSION,
user_id=ADMIN_USER_ID,
for_export=False,
)
assert result is mock_graph_model
@pytest.mark.asyncio
async def test_admin_download_pending_agent_with_subagents() -> None:
"""get_graph_as_admin with for_export=True must call get_sub_graphs
and pass sub_graphs to GraphModel.from_db."""
mock_graph = _make_mock_graph()
mock_sub_graph = MagicMock(name="SubGraph")
mock_graph_model = MagicMock(name="GraphModel")
with (
patch("backend.data.graph.AgentGraph.prisma") as mock_prisma,
patch(
"backend.data.graph.get_sub_graphs",
new_callable=AsyncMock,
return_value=[mock_sub_graph],
) as mock_get_sub,
patch(
"backend.data.graph.GraphModel.from_db",
return_value=mock_graph_model,
) as mock_from_db,
):
mock_prisma.return_value.find_first = AsyncMock(return_value=mock_graph)
result = await get_graph_as_admin(
graph_id=GRAPH_ID,
version=GRAPH_VERSION,
user_id=ADMIN_USER_ID,
for_export=True,
)
assert result is mock_graph_model
mock_get_sub.assert_awaited_once_with(mock_graph)
mock_from_db.assert_called_once_with(
graph=mock_graph,
sub_graphs=[mock_sub_graph],
for_export=True,
)
# ---- SECRT-2167 security: admin endpoints reject non-admin users ---- #
app = fastapi.FastAPI()
app.include_router(store_admin_router)
@app.exception_handler(NotFoundError)
async def _not_found_handler(
request: fastapi.Request, exc: NotFoundError
) -> fastapi.responses.JSONResponse:
return fastapi.responses.JSONResponse(status_code=404, content={"detail": str(exc)})
client = fastapi.testclient.TestClient(app)
@pytest.fixture(autouse=True)
def setup_app_admin_auth(mock_jwt_admin):
"""Setup admin auth overrides for all route tests in this module."""
app.dependency_overrides[get_jwt_payload] = mock_jwt_admin["get_jwt_payload"]
yield
app.dependency_overrides.clear()
def test_preview_requires_admin(mock_jwt_user) -> None:
"""Non-admin users must get 403 on the preview endpoint."""
app.dependency_overrides[get_jwt_payload] = mock_jwt_user["get_jwt_payload"]
response = client.get(f"/admin/submissions/{SLV_ID}/preview")
assert response.status_code == 403
def test_add_to_library_requires_admin(mock_jwt_user) -> None:
"""Non-admin users must get 403 on the add-to-library endpoint."""
app.dependency_overrides[get_jwt_payload] = mock_jwt_user["get_jwt_payload"]
response = client.post(f"/admin/submissions/{SLV_ID}/add-to-library")
assert response.status_code == 403
def test_preview_nonexistent_submission(
mocker: pytest_mock.MockerFixture,
) -> None:
"""Preview of a nonexistent submission returns 404."""
mocker.patch(
"backend.api.features.admin.store_admin_routes.store_db"
".get_store_agent_details_as_admin",
side_effect=NotFoundError("not found"),
)
response = client.get(f"/admin/submissions/{SLV_ID}/preview")
assert response.status_code == 404
# ---- SECRT-2167 bypass: verify the right data sources are used ---- #
@pytest.mark.asyncio
async def test_preview_queries_store_listing_version_not_store_agent() -> None:
"""get_store_agent_details_as_admin must query StoreListingVersion
directly (not the APPROVED-only StoreAgent view). This is THE test that
prevents the bypass from being accidentally reverted."""
from backend.api.features.store.db import get_store_agent_details_as_admin
mock_slv = MagicMock()
mock_slv.id = SLV_ID
mock_slv.name = "Test Agent"
mock_slv.subHeading = "Short desc"
mock_slv.description = "Long desc"
mock_slv.videoUrl = None
mock_slv.agentOutputDemoUrl = None
mock_slv.imageUrls = ["https://example.com/img.png"]
mock_slv.instructions = None
mock_slv.categories = ["productivity"]
mock_slv.version = 1
mock_slv.agentGraphId = GRAPH_ID
mock_slv.agentGraphVersion = GRAPH_VERSION
mock_slv.updatedAt = datetime(2026, 3, 24, tzinfo=timezone.utc)
mock_slv.recommendedScheduleCron = "0 9 * * *"
mock_listing = MagicMock()
mock_listing.id = "listing-id"
mock_listing.slug = "test-agent"
mock_listing.activeVersionId = SLV_ID
mock_listing.hasApprovedVersion = False
mock_listing.CreatorProfile = MagicMock(username="creator", avatarUrl="")
mock_slv.StoreListing = mock_listing
with (
patch(
"backend.api.features.store.db.prisma.models" ".StoreListingVersion.prisma",
) as mock_slv_prisma,
patch(
"backend.api.features.store.db.prisma.models.StoreAgent.prisma",
) as mock_store_agent_prisma,
):
mock_slv_prisma.return_value.find_unique = AsyncMock(return_value=mock_slv)
result = await get_store_agent_details_as_admin(SLV_ID)
# Verify it queried StoreListingVersion (not the APPROVED-only StoreAgent)
mock_slv_prisma.return_value.find_unique.assert_awaited_once()
await_args = mock_slv_prisma.return_value.find_unique.await_args
assert await_args is not None
assert await_args.kwargs["where"] == {"id": SLV_ID}
# Verify the APPROVED-only StoreAgent view was NOT touched
mock_store_agent_prisma.assert_not_called()
# Verify the result has the right data
assert result.agent_name == "Test Agent"
assert result.agent_image == ["https://example.com/img.png"]
assert result.has_approved_version is False
assert result.runs == 0
assert result.rating == 0.0
@pytest.mark.asyncio
async def test_resolve_graph_admin_uses_get_graph_as_admin() -> None:
"""resolve_graph_for_library(admin=True) must call get_graph_as_admin,
not get_graph. This is THE test that prevents the add-to-library bypass
from being accidentally reverted."""
from backend.api.features.library._add_to_library import resolve_graph_for_library
mock_slv = MagicMock()
mock_slv.AgentGraph = MagicMock(id=GRAPH_ID, version=GRAPH_VERSION)
mock_graph_model = MagicMock(name="GraphModel")
with (
patch(
"backend.api.features.library._add_to_library.prisma.models"
".StoreListingVersion.prisma",
) as mock_prisma,
patch(
"backend.api.features.library._add_to_library.graph_db"
".get_graph_as_admin",
new_callable=AsyncMock,
return_value=mock_graph_model,
) as mock_admin,
patch(
"backend.api.features.library._add_to_library.graph_db.get_graph",
new_callable=AsyncMock,
) as mock_regular,
):
mock_prisma.return_value.find_unique = AsyncMock(return_value=mock_slv)
result = await resolve_graph_for_library(SLV_ID, ADMIN_USER_ID, admin=True)
assert result is mock_graph_model
mock_admin.assert_awaited_once_with(
graph_id=GRAPH_ID, version=GRAPH_VERSION, user_id=ADMIN_USER_ID
)
mock_regular.assert_not_awaited()
@pytest.mark.asyncio
async def test_resolve_graph_regular_uses_get_graph() -> None:
"""resolve_graph_for_library(admin=False) must call get_graph,
not get_graph_as_admin. Ensures the non-admin path is preserved."""
from backend.api.features.library._add_to_library import resolve_graph_for_library
mock_slv = MagicMock()
mock_slv.AgentGraph = MagicMock(id=GRAPH_ID, version=GRAPH_VERSION)
mock_graph_model = MagicMock(name="GraphModel")
with (
patch(
"backend.api.features.library._add_to_library.prisma.models"
".StoreListingVersion.prisma",
) as mock_prisma,
patch(
"backend.api.features.library._add_to_library.graph_db"
".get_graph_as_admin",
new_callable=AsyncMock,
) as mock_admin,
patch(
"backend.api.features.library._add_to_library.graph_db.get_graph",
new_callable=AsyncMock,
return_value=mock_graph_model,
) as mock_regular,
):
mock_prisma.return_value.find_unique = AsyncMock(return_value=mock_slv)
result = await resolve_graph_for_library(SLV_ID, "regular-user-id", admin=False)
assert result is mock_graph_model
mock_regular.assert_awaited_once_with(
graph_id=GRAPH_ID, version=GRAPH_VERSION, user_id="regular-user-id"
)
mock_admin.assert_not_awaited()
# ---- Library membership grants graph access (product decision) ---- #
@pytest.mark.asyncio
async def test_library_member_can_view_pending_agent_in_builder() -> None:
"""After adding a pending agent to their library, the user should be
able to load the graph in the builder via get_graph()."""
mock_graph = _make_mock_graph()
mock_graph_model = MagicMock(name="GraphModel")
mock_library_agent = MagicMock()
mock_library_agent.AgentGraph = mock_graph
with (
patch("backend.data.graph.AgentGraph.prisma") as mock_ag_prisma,
patch(
"backend.data.graph.StoreListingVersion.prisma",
) as mock_slv_prisma,
patch("backend.data.graph.LibraryAgent.prisma") as mock_lib_prisma,
patch(
"backend.data.graph.GraphModel.from_db",
return_value=mock_graph_model,
),
):
mock_ag_prisma.return_value.find_first = AsyncMock(return_value=None)
mock_slv_prisma.return_value.find_first = AsyncMock(return_value=None)
mock_lib_prisma.return_value.find_first = AsyncMock(
return_value=mock_library_agent
)
from backend.data.graph import get_graph
result = await get_graph(
graph_id=GRAPH_ID,
version=GRAPH_VERSION,
user_id=ADMIN_USER_ID,
)
assert result is mock_graph_model, "Library membership should grant graph access"

View File

@@ -4,14 +4,12 @@ from difflib import SequenceMatcher
from typing import Any, Sequence, get_args, get_origin
import prisma
from prisma.enums import ContentType
from prisma.models import mv_suggested_blocks
import backend.api.features.library.db as library_db
import backend.api.features.library.model as library_model
import backend.api.features.store.db as store_db
import backend.api.features.store.model as store_model
from backend.api.features.store.hybrid_search import unified_hybrid_search
from backend.blocks import load_all_blocks
from backend.blocks._base import (
AnyBlockSchema,
@@ -24,6 +22,7 @@ from backend.blocks.llm import LlmModel
from backend.integrations.providers import ProviderName
from backend.util.cache import cached
from backend.util.models import Pagination
from backend.util.text import split_camelcase
from .model import (
BlockCategoryResponse,
@@ -271,7 +270,7 @@ async def _build_cached_search_results(
# Use hybrid search when query is present, otherwise list all blocks
if (include_blocks or include_integrations) and normalized_query:
block_results, block_total, integration_total = await _hybrid_search_blocks(
block_results, block_total, integration_total = await _text_search_blocks(
query=search_query,
include_blocks=include_blocks,
include_integrations=include_integrations,
@@ -383,117 +382,75 @@ def _collect_block_results(
return results, block_count, integration_count
async def _hybrid_search_blocks(
async def _text_search_blocks(
*,
query: str,
include_blocks: bool,
include_integrations: bool,
) -> tuple[list[_ScoredItem], int, int]:
"""
Search blocks using hybrid search with builder-specific filtering.
Search blocks using in-memory text matching over the block registry.
Uses unified_hybrid_search for semantic + lexical search, then applies
post-filtering for block/integration types and scoring adjustments.
All blocks are already loaded in memory, so this is fast and reliable
regardless of whether OpenAI embeddings are available.
Scoring:
- Base: hybrid relevance score (0-1) scaled to 0-100, plus BLOCK_SCORE_BOOST
- Base: text relevance via _score_primary_fields, plus BLOCK_SCORE_BOOST
to prioritize blocks over marketplace agents in combined results
- +30 for exact name match, +15 for prefix name match
- +20 if the block has an LlmModel field and the query matches an LLM model name
Args:
query: The search query string
include_blocks: Whether to include regular blocks
include_integrations: Whether to include integration blocks
Returns:
Tuple of (scored_items, block_count, integration_count)
"""
results: list[_ScoredItem] = []
block_count = 0
integration_count = 0
if not include_blocks and not include_integrations:
return results, block_count, integration_count
return results, 0, 0
normalized_query = query.strip().lower()
# Fetch more results to account for post-filtering
search_results, _ = await unified_hybrid_search(
query=query,
content_types=[ContentType.BLOCK],
page=1,
page_size=150,
min_score=0.10,
all_results, _, _ = _collect_block_results(
include_blocks=include_blocks,
include_integrations=include_integrations,
)
# Load all blocks for getting BlockInfo
all_blocks = load_all_blocks()
for result in search_results:
block_id = result["content_id"]
for item in all_results:
block_info = item.item
assert isinstance(block_info, BlockInfo)
name = split_camelcase(block_info.name).lower()
# Skip excluded blocks
if block_id in EXCLUDED_BLOCK_IDS:
continue
# Build rich description including input field descriptions,
# matching the searchable text that the embedding pipeline uses
desc_parts = [block_info.description or ""]
block_cls = all_blocks.get(block_info.id)
if block_cls is not None:
block: AnyBlockSchema = block_cls()
desc_parts += [
f"{f}: {info.description}"
for f, info in block.input_schema.model_fields.items()
if info.description
]
description = " ".join(desc_parts).lower()
metadata = result.get("metadata", {})
hybrid_score = result.get("relevance", 0.0)
# Get the actual block class
if block_id not in all_blocks:
continue
block_cls = all_blocks[block_id]
block: AnyBlockSchema = block_cls()
if block.disabled:
continue
# Check block/integration filter using metadata
is_integration = metadata.get("is_integration", False)
if is_integration and not include_integrations:
continue
if not is_integration and not include_blocks:
continue
# Get block info
block_info = block.get_info()
# Calculate final score: scale hybrid score and add builder-specific bonuses
# Hybrid scores are 0-1, builder scores were 0-200+
# Add BLOCK_SCORE_BOOST to prioritize blocks over marketplace agents
final_score = hybrid_score * 100 + BLOCK_SCORE_BOOST
score = _score_primary_fields(name, description, normalized_query)
# Add LLM model match bonus
has_llm_field = metadata.get("has_llm_model_field", False)
if has_llm_field and _matches_llm_model(block.input_schema, normalized_query):
final_score += 20
if block_cls is not None and _matches_llm_model(
block_cls().input_schema, normalized_query
):
score += 20
# Add exact/prefix match bonus for deterministic tie-breaking
name = block_info.name.lower()
if name == normalized_query:
final_score += 30
elif name.startswith(normalized_query):
final_score += 15
# Track counts
filter_type: FilterType = "integrations" if is_integration else "blocks"
if is_integration:
integration_count += 1
else:
block_count += 1
results.append(
_ScoredItem(
item=block_info,
filter_type=filter_type,
score=final_score,
sort_key=name,
if score >= MIN_SCORE_FOR_FILTERED_RESULTS:
results.append(
_ScoredItem(
item=block_info,
filter_type=item.filter_type,
score=score + BLOCK_SCORE_BOOST,
sort_key=name,
)
)
)
block_count = sum(1 for r in results if r.filter_type == "blocks")
integration_count = sum(1 for r in results if r.filter_type == "integrations")
return results, block_count, integration_count

View File

@@ -2,29 +2,47 @@
import asyncio
import logging
import re
from collections.abc import AsyncGenerator
from typing import Annotated
from uuid import uuid4
from autogpt_libs import auth
from fastapi import APIRouter, Depends, HTTPException, Query, Response, Security
from fastapi import APIRouter, HTTPException, Query, Response, Security
from fastapi.responses import StreamingResponse
from pydantic import BaseModel
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.config import ChatConfig, 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,
ChatSession,
ChatSessionMetadata,
append_and_save_message,
create_chat_session,
delete_chat_session,
get_chat_session,
get_user_sessions,
update_session_title,
)
from backend.copilot.rate_limit import (
CoPilotUsageStatus,
RateLimitExceeded,
acquire_reset_lock,
check_rate_limit,
get_daily_reset_count,
get_global_rate_limits,
get_usage_status,
increment_daily_reset_count,
release_reset_lock,
reset_daily_usage,
)
from backend.copilot.response_model import StreamError, StreamFinish, StreamHeartbeat
from backend.copilot.tools.e2b_sandbox import kill_sandbox
from backend.copilot.tools.models import (
AgentDetailsResponse,
AgentOutputResponse,
@@ -40,6 +58,8 @@ from backend.copilot.tools.models import (
ErrorResponse,
ExecutionStartedResponse,
InputValidationErrorResponse,
MCPToolOutputResponse,
MCPToolsDiscoveredResponse,
NeedLoginResponse,
NoResultsResponse,
SetupRequirementsResponse,
@@ -47,12 +67,22 @@ from backend.copilot.tools.models import (
UnderstandingUpdatedResponse,
)
from backend.copilot.tracking import track_user_message
from backend.util.exceptions import NotFoundError
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.util.exceptions import InsufficientBalanceError, NotFoundError
from backend.util.settings import Settings
settings = Settings()
logger = logging.getLogger(__name__)
config = ChatConfig()
logger = logging.getLogger(__name__)
_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(
@@ -79,6 +109,26 @@ class StreamChatRequest(BaseModel):
message: str
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).",
)
class CreateSessionRequest(BaseModel):
"""Request model for creating a new chat session.
``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
class CreateSessionResponse(BaseModel):
@@ -87,6 +137,7 @@ class CreateSessionResponse(BaseModel):
id: str
created_at: str
user_id: str | None
metadata: ChatSessionMetadata = ChatSessionMetadata()
class ActiveStreamInfo(BaseModel):
@@ -105,6 +156,11 @@ 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()
class SessionSummaryResponse(BaseModel):
@@ -114,6 +170,7 @@ class SessionSummaryResponse(BaseModel):
created_at: str
updated_at: str
title: str | None = None
is_processing: bool
class ListSessionsResponse(BaseModel):
@@ -130,6 +187,20 @@ class CancelSessionResponse(BaseModel):
reason: str | None = None
class UpdateSessionTitleRequest(BaseModel):
"""Request model for updating a session's title."""
title: str
@field_validator("title")
@classmethod
def title_must_not_be_blank(cls, v: str) -> str:
stripped = v.strip()
if not stripped:
raise ValueError("Title must not be blank")
return stripped
# ========== Routes ==========
@@ -158,6 +229,28 @@ async def list_sessions(
"""
sessions, total_count = await get_user_sessions(user_id, limit, offset)
# Batch-check Redis for active stream status on each session
processing_set: set[str] = set()
if sessions:
try:
redis = await get_redis_async()
pipe = redis.pipeline(transaction=False)
for session in sessions:
pipe.hget(
f"{config.session_meta_prefix}{session.session_id}",
"status",
)
statuses = await pipe.execute()
processing_set = {
session.session_id
for session, st in zip(sessions, statuses)
if st == "running"
}
except Exception:
logger.warning(
"Failed to fetch processing status from Redis; defaulting to empty"
)
return ListSessionsResponse(
sessions=[
SessionSummaryResponse(
@@ -165,6 +258,7 @@ async def list_sessions(
created_at=session.started_at.isoformat(),
updated_at=session.updated_at.isoformat(),
title=session.title,
is_processing=session.session_id in processing_set,
)
for session in sessions
],
@@ -176,7 +270,8 @@ async def list_sessions(
"/sessions",
)
async def create_session(
user_id: Annotated[str, Depends(auth.get_user_id)],
user_id: Annotated[str, Security(auth.get_user_id)],
request: CreateSessionRequest | None = None,
) -> CreateSessionResponse:
"""
Create a new chat session.
@@ -185,22 +280,28 @@ async def create_session(
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.
Returns:
CreateSessionResponse: Details of the created session.
"""
dry_run = request.dry_run if request else False
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 ''}"
)
session = await create_chat_session(user_id)
session = await create_chat_session(user_id, dry_run=dry_run)
return CreateSessionResponse(
id=session.session_id,
created_at=session.started_at.isoformat(),
user_id=session.user_id,
metadata=session.metadata,
)
@@ -238,62 +339,335 @@ async def delete_session(
detail=f"Session {session_id} not found or access denied",
)
# Best-effort cleanup of the E2B sandbox (if any).
# sandbox_id is in Redis; kill_sandbox() fetches it from there.
e2b_cfg = ChatConfig()
if e2b_cfg.e2b_active:
assert e2b_cfg.e2b_api_key # guaranteed by e2b_active check
try:
await kill_sandbox(session_id, e2b_cfg.e2b_api_key)
except Exception:
logger.warning(
"[E2B] Failed to kill sandbox for session %s", session_id[:12]
)
return Response(status_code=204)
@router.patch(
"/sessions/{session_id}/title",
summary="Update session title",
dependencies=[Security(auth.requires_user)],
status_code=200,
responses={404: {"description": "Session not found or access denied"}},
)
async def update_session_title_route(
session_id: str,
request: UpdateSessionTitleRequest,
user_id: Annotated[str, Security(auth.get_user_id)],
) -> dict:
"""
Update the title of a chat session.
Allows the user to rename their chat session.
Args:
session_id: The session ID to update.
request: Request body containing the new title.
user_id: The authenticated user's ID.
Returns:
dict: Status of the update.
Raises:
HTTPException: 404 if session not found or not owned by user.
"""
success = await update_session_title(session_id, user_id, request.title)
if not success:
raise HTTPException(
status_code=404,
detail=f"Session {session_id} not found or access denied",
)
return {"status": "ok"}
@router.get(
"/sessions/{session_id}",
)
async def get_session(
session_id: str,
user_id: Annotated[str | None, Depends(auth.get_user_id)],
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.
Supports cursor-based pagination via ``limit`` and ``before_sequence``.
When no pagination params are provided, returns the most recent messages.
Args:
session_id: The unique identifier for the desired chat session.
user_id: The optional authenticated user ID, or None for anonymous access.
user_id: The authenticated user's ID.
limit: Maximum number of messages to return (1-200, default 50).
before_sequence: Return messages with sequence < this value (cursor).
Returns:
SessionDetailResponse: Details for the requested session, including active_stream info if applicable.
SessionDetailResponse: Details for the requested session, including
active_stream info and pagination metadata.
"""
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 page.messages]
messages = [message.model_dump() for message in session.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
)
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:
active_stream_info = ActiveStreamInfo(
turn_id=active_session.turn_id,
last_message_id=last_message_id,
)
# 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,
)
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=page.session.metadata,
)
@router.get(
"/usage",
)
async def get_copilot_usage(
user_id: Annotated[str, Security(auth.get_user_id)],
) -> CoPilotUsageStatus:
"""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).
Includes the user's rate-limit tier.
"""
daily_limit, weekly_limit, tier = await get_global_rate_limits(
user_id, config.daily_token_limit, config.weekly_token_limit
)
return await get_usage_status(
user_id=user_id,
daily_token_limit=daily_limit,
weekly_token_limit=weekly_limit,
rate_limit_reset_cost=config.rate_limit_reset_cost,
tier=tier,
)
class RateLimitResetResponse(BaseModel):
"""Response from resetting the daily rate limit."""
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")
@router.post(
"/usage/reset",
status_code=200,
responses={
400: {
"description": "Bad Request (feature disabled or daily limit not reached)"
},
402: {"description": "Payment Required (insufficient credits)"},
429: {
"description": "Too Many Requests (max daily resets exceeded or reset in progress)"
},
503: {
"description": "Service Unavailable (Redis reset failed; credits refunded or support needed)"
},
},
)
async def reset_copilot_usage(
user_id: Annotated[str, Security(auth.get_user_id)],
) -> RateLimitResetResponse:
"""Reset the daily CoPilot rate limit by spending credits.
Allows users who have hit their daily token 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.
"""
cost = config.rate_limit_reset_cost
if cost <= 0:
raise HTTPException(
status_code=400,
detail="Rate limit reset is not available.",
)
if not settings.config.enable_credit:
raise HTTPException(
status_code=400,
detail="Rate limit reset is not available (credit system is disabled).",
)
daily_limit, weekly_limit, tier = await get_global_rate_limits(
user_id, config.daily_token_limit, config.weekly_token_limit
)
if daily_limit <= 0:
raise HTTPException(
status_code=400,
detail="No daily limit is configured — nothing to reset.",
)
# Check max daily resets. get_daily_reset_count returns None when Redis
# is unavailable; reject the reset in that case to prevent unlimited
# free resets when the counter store is down.
reset_count = await get_daily_reset_count(user_id)
if reset_count is None:
raise HTTPException(
status_code=503,
detail="Unable to verify reset eligibility — please try again later.",
)
if config.max_daily_resets > 0 and reset_count >= config.max_daily_resets:
raise HTTPException(
status_code=429,
detail=f"You've used all {config.max_daily_resets} resets for today.",
)
# Acquire a per-user lock to prevent TOCTOU races (concurrent resets).
if not await acquire_reset_lock(user_id):
raise HTTPException(
status_code=429,
detail="A reset is already in progress. Please try again.",
)
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,
tier=tier,
)
if daily_limit > 0 and usage_status.daily.used < daily_limit:
raise HTTPException(
status_code=400,
detail="You have not reached your daily limit yet.",
)
# If the weekly limit is also exhausted, resetting the daily counter
# won't help — the user would still be blocked by the weekly limit.
if weekly_limit > 0 and usage_status.weekly.used >= weekly_limit:
raise HTTPException(
status_code=400,
detail="Your weekly limit is also reached. Resetting the daily limit won't help.",
)
# Charge credits.
credit_model = await get_user_credit_model(user_id)
try:
remaining = await credit_model.spend_credits(
user_id=user_id,
cost=cost,
metadata=UsageTransactionMetadata(
reason="CoPilot daily rate limit reset",
),
)
except InsufficientBalanceError as e:
raise HTTPException(
status_code=402,
detail="Insufficient credits to reset your rate limit.",
) from e
# 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):
# Compensate: refund the charged credits.
refunded = False
try:
await credit_model.top_up_credits(user_id, cost)
refunded = True
logger.warning(
"Refunded %d credits to user %s after Redis reset failure",
cost,
user_id[:8],
)
except Exception:
logger.error(
"CRITICAL: Failed to refund %d credits to user %s "
"after Redis reset failure — manual intervention required",
cost,
user_id[:8],
exc_info=True,
)
if refunded:
raise HTTPException(
status_code=503,
detail="Rate limit reset failed — please try again later. "
"Your credits have not been charged.",
)
raise HTTPException(
status_code=503,
detail="Rate limit reset failed and the automatic refund "
"also failed. Please contact support for assistance.",
)
# Track the reset count for daily cap enforcement.
await increment_daily_reset_count(user_id)
finally:
await release_reset_lock(user_id)
# Return updated usage status.
updated_usage = await get_usage_status(
user_id=user_id,
daily_token_limit=daily_limit,
weekly_token_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,
)
@@ -303,7 +677,7 @@ async def get_session(
)
async def cancel_session_task(
session_id: str,
user_id: Annotated[str | None, Depends(auth.get_user_id)],
user_id: Annotated[str, Security(auth.get_user_id)],
) -> CancelSessionResponse:
"""Cancel the active streaming task for a session.
@@ -348,7 +722,7 @@ async def cancel_session_task(
async def stream_chat_post(
session_id: str,
request: StreamChatRequest,
user_id: str | None = Depends(auth.get_user_id),
user_id: str = Security(auth.get_user_id),
):
"""
Stream chat responses for a session (POST with context support).
@@ -365,7 +739,7 @@ async def stream_chat_post(
Args:
session_id: The chat session identifier to associate with the streamed messages.
request: Request body containing message, is_user_message, and optional context.
user_id: Optional authenticated user ID.
user_id: Authenticated user ID.
Returns:
StreamingResponse: SSE-formatted response chunks.
@@ -374,9 +748,7 @@ async def stream_chat_post(
import time
stream_start_time = time.perf_counter()
log_meta = {"component": "ChatStream", "session_id": session_id}
if user_id:
log_meta["user_id"] = user_id
log_meta = {"component": "ChatStream", "session_id": session_id, "user_id": user_id}
logger.info(
f"[TIMING] stream_chat_post STARTED, session={session_id}, "
@@ -394,6 +766,54 @@ async def stream_chat_post(
},
)
# Pre-turn rate limit check (token-based).
# 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
)
await check_rate_limit(
user_id=user_id,
daily_token_limit=daily_limit,
weekly_token_limit=weekly_limit,
)
except RateLimitExceeded as e:
raise HTTPException(status_code=429, detail=str(e)) from e
# Enrich message with file metadata if file_ids are provided.
# 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
# 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
@@ -445,6 +865,8 @@ async def stream_chat_post(
turn_id=turn_id,
is_user_message=request.is_user_message,
context=request.context,
file_ids=sanitized_file_ids,
mode=request.mode,
)
setup_time = (time.perf_counter() - stream_start_time) * 1000
@@ -487,7 +909,7 @@ async def stream_chat_post(
)
while True:
try:
chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=30.0)
chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=10.0)
chunks_yielded += 1
if not first_chunk_yielded:
@@ -595,7 +1017,7 @@ async def stream_chat_post(
)
async def resume_session_stream(
session_id: str,
user_id: str | None = Depends(auth.get_user_id),
user_id: str = Security(auth.get_user_id),
):
"""
Resume an active stream for a session.
@@ -640,7 +1062,7 @@ async def resume_session_stream(
try:
while True:
try:
chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=30.0)
chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=10.0)
if chunk_count < 3:
logger.info(
"Resume stream chunk",
@@ -697,7 +1119,6 @@ async def resume_session_stream(
@router.patch(
"/sessions/{session_id}/assign-user",
dependencies=[Security(auth.requires_user)],
status_code=200,
)
async def session_assign_user(
session_id: str,
@@ -720,6 +1141,47 @@ async def session_assign_user(
return {"status": "ok"}
# ========== Suggested Prompts ==========
class SuggestedTheme(BaseModel):
"""A themed group of suggested prompts."""
name: str
prompts: list[str]
class SuggestedPromptsResponse(BaseModel):
"""Response model for user-specific suggested prompts grouped by theme."""
themes: list[SuggestedTheme]
@router.get(
"/suggested-prompts",
dependencies=[Security(auth.requires_user)],
)
async def get_suggested_prompts(
user_id: Annotated[str, Security(auth.get_user_id)],
) -> SuggestedPromptsResponse:
"""
Get LLM-generated suggested prompts grouped by theme.
Returns personalized quick-action prompts based on the user's
business understanding. Returns empty themes list if no custom
prompts are available.
"""
understanding = await get_business_understanding(user_id)
if understanding is None or not understanding.suggested_prompts:
return SuggestedPromptsResponse(themes=[])
themes = [
SuggestedTheme(name=name, prompts=prompts)
for name, prompts in understanding.suggested_prompts.items()
]
return SuggestedPromptsResponse(themes=themes)
# ========== Configuration ==========
@@ -768,7 +1230,7 @@ async def health_check() -> dict:
)
# Create and retrieve session to verify full data layer
session = await create_chat_session(health_check_user_id)
session = await create_chat_session(health_check_user_id, dry_run=False)
await get_chat_session(session.session_id, health_check_user_id)
return {
@@ -800,6 +1262,8 @@ ToolResponseUnion = (
| BlockOutputResponse
| DocSearchResultsResponse
| DocPageResponse
| MCPToolsDiscoveredResponse
| MCPToolOutputResponse
)

View File

@@ -0,0 +1,581 @@
"""Tests for chat API routes: session title update, file attachment validation, usage, and rate limiting."""
from datetime import UTC, datetime, timedelta
from unittest.mock import AsyncMock, MagicMock
import fastapi
import fastapi.testclient
import pytest
import pytest_mock
from backend.api.features.chat import routes as chat_routes
from backend.copilot.rate_limit import SubscriptionTier
app = fastapi.FastAPI()
app.include_router(chat_routes.router)
client = fastapi.testclient.TestClient(app)
TEST_USER_ID = "3e53486c-cf57-477e-ba2a-cb02dc828e1a"
@pytest.fixture(autouse=True)
def setup_app_auth(mock_jwt_user):
"""Setup auth overrides for all tests in this module"""
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 _mock_update_session_title(
mocker: pytest_mock.MockerFixture, *, success: bool = True
):
"""Mock update_session_title."""
return mocker.patch(
"backend.api.features.chat.routes.update_session_title",
new_callable=AsyncMock,
return_value=success,
)
# ─── Update title: success ─────────────────────────────────────────────
def test_update_title_success(
mocker: pytest_mock.MockerFixture,
test_user_id: str,
) -> None:
mock_update = _mock_update_session_title(mocker, success=True)
response = client.patch(
"/sessions/sess-1/title",
json={"title": "My project"},
)
assert response.status_code == 200
assert response.json() == {"status": "ok"}
mock_update.assert_called_once_with("sess-1", test_user_id, "My project")
def test_update_title_trims_whitespace(
mocker: pytest_mock.MockerFixture,
test_user_id: str,
) -> None:
mock_update = _mock_update_session_title(mocker, success=True)
response = client.patch(
"/sessions/sess-1/title",
json={"title": " trimmed "},
)
assert response.status_code == 200
mock_update.assert_called_once_with("sess-1", test_user_id, "trimmed")
# ─── Update title: blank / whitespace-only → 422 ──────────────────────
def test_update_title_blank_rejected(
test_user_id: str,
) -> None:
"""Whitespace-only titles must be rejected before hitting the DB."""
response = client.patch(
"/sessions/sess-1/title",
json={"title": " "},
)
assert response.status_code == 422
def test_update_title_empty_rejected(
test_user_id: str,
) -> None:
response = client.patch(
"/sessions/sess-1/title",
json={"title": ""},
)
assert response.status_code == 422
# ─── Update title: session not found or wrong user → 404 ──────────────
def test_update_title_not_found(
mocker: pytest_mock.MockerFixture,
test_user_id: str,
) -> None:
_mock_update_session_title(mocker, success=False)
response = client.patch(
"/sessions/sess-1/title",
json={"title": "New name"},
)
assert response.status_code == 404
# ─── file_ids Pydantic validation ─────────────────────────────────────
def test_stream_chat_rejects_too_many_file_ids():
"""More than 20 file_ids should be rejected by Pydantic validation (422)."""
response = client.post(
"/sessions/sess-1/stream",
json={
"message": "hello",
"file_ids": [f"00000000-0000-0000-0000-{i:012d}" for i in range(21)],
},
)
assert response.status_code == 422
def _mock_stream_internals(mocker: pytest_mock.MockFixture):
"""Mock the async internals of stream_chat_post so tests can exercise
validation and enrichment logic without needing Redis/RabbitMQ."""
mocker.patch(
"backend.api.features.chat.routes._validate_and_get_session",
return_value=None,
)
mocker.patch(
"backend.api.features.chat.routes.append_and_save_message",
return_value=None,
)
mock_registry = mocker.MagicMock()
mock_registry.create_session = mocker.AsyncMock(return_value=None)
mocker.patch(
"backend.api.features.chat.routes.stream_registry",
mock_registry,
)
mocker.patch(
"backend.api.features.chat.routes.enqueue_copilot_turn",
return_value=None,
)
mocker.patch(
"backend.api.features.chat.routes.track_user_message",
return_value=None,
)
def test_stream_chat_accepts_20_file_ids(mocker: pytest_mock.MockFixture):
"""Exactly 20 file_ids should be accepted (not rejected by validation)."""
_mock_stream_internals(mocker)
# Patch workspace lookup as imported by the routes module
mocker.patch(
"backend.api.features.chat.routes.get_or_create_workspace",
return_value=type("W", (), {"id": "ws-1"})(),
)
mock_prisma = mocker.MagicMock()
mock_prisma.find_many = mocker.AsyncMock(return_value=[])
mocker.patch(
"prisma.models.UserWorkspaceFile.prisma",
return_value=mock_prisma,
)
response = client.post(
"/sessions/sess-1/stream",
json={
"message": "hello",
"file_ids": [f"00000000-0000-0000-0000-{i:012d}" for i in range(20)],
},
)
# Should get past validation — 200 streaming response expected
assert response.status_code == 200
# ─── UUID format filtering ─────────────────────────────────────────────
def test_file_ids_filters_invalid_uuids(mocker: pytest_mock.MockFixture):
"""Non-UUID strings in file_ids should be silently filtered out
and NOT passed to the database query."""
_mock_stream_internals(mocker)
mocker.patch(
"backend.api.features.chat.routes.get_or_create_workspace",
return_value=type("W", (), {"id": "ws-1"})(),
)
mock_prisma = mocker.MagicMock()
mock_prisma.find_many = mocker.AsyncMock(return_value=[])
mocker.patch(
"prisma.models.UserWorkspaceFile.prisma",
return_value=mock_prisma,
)
valid_id = "aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee"
client.post(
"/sessions/sess-1/stream",
json={
"message": "hello",
"file_ids": [
valid_id,
"not-a-uuid",
"../../../etc/passwd",
"",
],
},
)
# The find_many call should only receive the one valid UUID
mock_prisma.find_many.assert_called_once()
call_kwargs = mock_prisma.find_many.call_args[1]
assert call_kwargs["where"]["id"]["in"] == [valid_id]
# ─── Cross-workspace file_ids ─────────────────────────────────────────
def test_file_ids_scoped_to_workspace(mocker: pytest_mock.MockFixture):
"""The batch query should scope to the user's workspace."""
_mock_stream_internals(mocker)
mocker.patch(
"backend.api.features.chat.routes.get_or_create_workspace",
return_value=type("W", (), {"id": "my-workspace-id"})(),
)
mock_prisma = mocker.MagicMock()
mock_prisma.find_many = mocker.AsyncMock(return_value=[])
mocker.patch(
"prisma.models.UserWorkspaceFile.prisma",
return_value=mock_prisma,
)
fid = "aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee"
client.post(
"/sessions/sess-1/stream",
json={"message": "hi", "file_ids": [fid]},
)
call_kwargs = mock_prisma.find_many.call_args[1]
assert call_kwargs["where"]["workspaceId"] == "my-workspace-id"
assert call_kwargs["where"]["isDeleted"] is False
# ─── Rate limit → 429 ─────────────────────────────────────────────────
def test_stream_chat_returns_429_on_daily_rate_limit(mocker: pytest_mock.MockFixture):
"""When check_rate_limit raises RateLimitExceeded for daily limit the endpoint returns 429."""
from backend.copilot.rate_limit import RateLimitExceeded
_mock_stream_internals(mocker)
# Ensure the rate-limit branch is entered by setting a non-zero limit.
mocker.patch.object(chat_routes.config, "daily_token_limit", 10000)
mocker.patch.object(chat_routes.config, "weekly_token_limit", 50000)
mocker.patch(
"backend.api.features.chat.routes.check_rate_limit",
side_effect=RateLimitExceeded("daily", datetime.now(UTC) + timedelta(hours=1)),
)
response = client.post(
"/sessions/sess-1/stream",
json={"message": "hello"},
)
assert response.status_code == 429
assert "daily" in response.json()["detail"].lower()
def test_stream_chat_returns_429_on_weekly_rate_limit(mocker: pytest_mock.MockFixture):
"""When check_rate_limit raises RateLimitExceeded for weekly limit the endpoint returns 429."""
from backend.copilot.rate_limit import RateLimitExceeded
_mock_stream_internals(mocker)
mocker.patch.object(chat_routes.config, "daily_token_limit", 10000)
mocker.patch.object(chat_routes.config, "weekly_token_limit", 50000)
resets_at = datetime.now(UTC) + timedelta(days=3)
mocker.patch(
"backend.api.features.chat.routes.check_rate_limit",
side_effect=RateLimitExceeded("weekly", resets_at),
)
response = client.post(
"/sessions/sess-1/stream",
json={"message": "hello"},
)
assert response.status_code == 429
detail = response.json()["detail"].lower()
assert "weekly" in detail
assert "resets in" in detail
def test_stream_chat_429_includes_reset_time(mocker: pytest_mock.MockFixture):
"""The 429 response detail should include the human-readable reset time."""
from backend.copilot.rate_limit import RateLimitExceeded
_mock_stream_internals(mocker)
mocker.patch.object(chat_routes.config, "daily_token_limit", 10000)
mocker.patch.object(chat_routes.config, "weekly_token_limit", 50000)
mocker.patch(
"backend.api.features.chat.routes.check_rate_limit",
side_effect=RateLimitExceeded(
"daily", datetime.now(UTC) + timedelta(hours=2, minutes=30)
),
)
response = client.post(
"/sessions/sess-1/stream",
json={"message": "hello"},
)
assert response.status_code == 429
detail = response.json()["detail"]
assert "2h" in detail
assert "Resets in" in detail
# ─── Usage endpoint ───────────────────────────────────────────────────
def _mock_usage(
mocker: pytest_mock.MockerFixture,
*,
daily_used: int = 500,
weekly_used: int = 2000,
daily_limit: int = 10000,
weekly_limit: int = 50000,
tier: "SubscriptionTier" = SubscriptionTier.FREE,
) -> AsyncMock:
"""Mock get_usage_status and get_global_rate_limits for usage endpoint tests.
Mocks both ``get_global_rate_limits`` (returns the given limits + tier) and
``get_usage_status`` so that tests exercise the endpoint without hitting
LaunchDarkly or Prisma.
"""
from backend.copilot.rate_limit import CoPilotUsageStatus, UsageWindow
mocker.patch(
"backend.api.features.chat.routes.get_global_rate_limits",
new_callable=AsyncMock,
return_value=(daily_limit, weekly_limit, tier),
)
resets_at = datetime.now(UTC) + timedelta(days=1)
status = CoPilotUsageStatus(
daily=UsageWindow(used=daily_used, limit=daily_limit, resets_at=resets_at),
weekly=UsageWindow(used=weekly_used, limit=weekly_limit, resets_at=resets_at),
)
return mocker.patch(
"backend.api.features.chat.routes.get_usage_status",
new_callable=AsyncMock,
return_value=status,
)
def test_usage_returns_daily_and_weekly(
mocker: pytest_mock.MockerFixture,
test_user_id: str,
) -> None:
"""GET /usage returns daily and weekly usage."""
mock_get = _mock_usage(mocker, daily_used=500, weekly_used=2000)
mocker.patch.object(chat_routes.config, "daily_token_limit", 10000)
mocker.patch.object(chat_routes.config, "weekly_token_limit", 50000)
response = client.get("/usage")
assert response.status_code == 200
data = response.json()
assert data["daily"]["used"] == 500
assert data["weekly"]["used"] == 2000
mock_get.assert_called_once_with(
user_id=test_user_id,
daily_token_limit=10000,
weekly_token_limit=50000,
rate_limit_reset_cost=chat_routes.config.rate_limit_reset_cost,
tier=SubscriptionTier.FREE,
)
def test_usage_uses_config_limits(
mocker: pytest_mock.MockerFixture,
test_user_id: str,
) -> None:
"""The endpoint forwards resolved limits from get_global_rate_limits to get_usage_status."""
mock_get = _mock_usage(mocker, daily_limit=99999, weekly_limit=77777)
mocker.patch.object(chat_routes.config, "rate_limit_reset_cost", 500)
response = client.get("/usage")
assert response.status_code == 200
mock_get.assert_called_once_with(
user_id=test_user_id,
daily_token_limit=99999,
weekly_token_limit=77777,
rate_limit_reset_cost=500,
tier=SubscriptionTier.FREE,
)
def test_usage_rejects_unauthenticated_request() -> None:
"""GET /usage should return 401 when no valid JWT is provided."""
unauthenticated_app = fastapi.FastAPI()
unauthenticated_app.include_router(chat_routes.router)
unauthenticated_client = fastapi.testclient.TestClient(unauthenticated_app)
response = unauthenticated_client.get("/usage")
assert response.status_code == 401
# ─── Suggested prompts endpoint ──────────────────────────────────────
def _mock_get_business_understanding(
mocker: pytest_mock.MockerFixture,
*,
return_value=None,
):
"""Mock get_business_understanding."""
return mocker.patch(
"backend.api.features.chat.routes.get_business_understanding",
new_callable=AsyncMock,
return_value=return_value,
)
def test_suggested_prompts_returns_themes(
mocker: pytest_mock.MockerFixture,
test_user_id: str,
) -> None:
"""User with themed prompts gets them back as themes list."""
mock_understanding = MagicMock()
mock_understanding.suggested_prompts = {
"Learn": ["L1", "L2"],
"Create": ["C1"],
}
_mock_get_business_understanding(mocker, return_value=mock_understanding)
response = client.get("/suggested-prompts")
assert response.status_code == 200
data = response.json()
assert "themes" in data
themes_by_name = {t["name"]: t["prompts"] for t in data["themes"]}
assert themes_by_name["Learn"] == ["L1", "L2"]
assert themes_by_name["Create"] == ["C1"]
def test_suggested_prompts_no_understanding(
mocker: pytest_mock.MockerFixture,
test_user_id: str,
) -> None:
"""User with no understanding gets empty themes list."""
_mock_get_business_understanding(mocker, return_value=None)
response = client.get("/suggested-prompts")
assert response.status_code == 200
assert response.json() == {"themes": []}
def test_suggested_prompts_empty_prompts(
mocker: pytest_mock.MockerFixture,
test_user_id: str,
) -> None:
"""User with understanding but empty prompts gets empty themes list."""
mock_understanding = MagicMock()
mock_understanding.suggested_prompts = {}
_mock_get_business_understanding(mocker, return_value=mock_understanding)
response = client.get("/suggested-prompts")
assert response.status_code == 200
assert response.json() == {"themes": []}
# ─── Create session: dry_run contract ─────────────────────────────────
def _mock_create_chat_session(mocker: pytest_mock.MockerFixture):
"""Mock create_chat_session to return a fake session."""
from backend.copilot.model import ChatSession
async def _fake_create(user_id: str, *, dry_run: bool):
return ChatSession.new(user_id, dry_run=dry_run)
return mocker.patch(
"backend.api.features.chat.routes.create_chat_session",
new_callable=AsyncMock,
side_effect=_fake_create,
)
def test_create_session_dry_run_true(
mocker: pytest_mock.MockerFixture,
test_user_id: str,
) -> None:
"""Sending ``{"dry_run": true}`` sets metadata.dry_run to True."""
_mock_create_chat_session(mocker)
response = client.post("/sessions", json={"dry_run": True})
assert response.status_code == 200
assert response.json()["metadata"]["dry_run"] is True
def test_create_session_dry_run_default_false(
mocker: pytest_mock.MockerFixture,
test_user_id: str,
) -> None:
"""Empty body defaults dry_run to False."""
_mock_create_chat_session(mocker)
response = client.post("/sessions")
assert response.status_code == 200
assert response.json()["metadata"]["dry_run"] is False
def test_create_session_rejects_nested_metadata(
test_user_id: str,
) -> None:
"""Sending ``{"metadata": {"dry_run": true}}`` must return 422, not silently
default to ``dry_run=False``. This guards against the common mistake of
nesting dry_run inside metadata instead of providing it at the top level."""
response = client.post(
"/sessions",
json={"metadata": {"dry_run": True}},
)
assert response.status_code == 422
class TestStreamChatRequestModeValidation:
"""Pydantic-level validation of the ``mode`` field on StreamChatRequest."""
def test_rejects_invalid_mode_value(self) -> None:
"""Any string outside the Literal set must raise ValidationError."""
from pydantic import ValidationError
from backend.api.features.chat.routes import StreamChatRequest
with pytest.raises(ValidationError):
StreamChatRequest(message="hi", mode="turbo") # type: ignore[arg-type]
def test_accepts_fast_mode(self) -> None:
from backend.api.features.chat.routes import StreamChatRequest
req = StreamChatRequest(message="hi", mode="fast")
assert req.mode == "fast"
def test_accepts_extended_thinking_mode(self) -> None:
from backend.api.features.chat.routes import StreamChatRequest
req = StreamChatRequest(message="hi", mode="extended_thinking")
assert req.mode == "extended_thinking"
def test_accepts_none_mode(self) -> None:
"""``mode=None`` is valid (server decides via feature flags)."""
from backend.api.features.chat.routes import StreamChatRequest
req = StreamChatRequest(message="hi", mode=None)
assert req.mode is None
def test_mode_defaults_to_none_when_omitted(self) -> None:
from backend.api.features.chat.routes import StreamChatRequest
req = StreamChatRequest(message="hi")
assert req.mode is None

View File

@@ -638,7 +638,7 @@ async def test_process_review_action_auto_approve_creates_auto_approval_records(
# Mock get_node_executions to return node_id mapping
mock_get_node_executions = mocker.patch(
"backend.data.execution.get_node_executions"
"backend.api.features.executions.review.routes.get_node_executions"
)
mock_node_exec = mocker.Mock(spec=NodeExecutionResult)
mock_node_exec.node_exec_id = "test_node_123"
@@ -936,7 +936,7 @@ async def test_process_review_action_auto_approve_only_applies_to_approved_revie
# Mock get_node_executions to return node_id mapping
mock_get_node_executions = mocker.patch(
"backend.data.execution.get_node_executions"
"backend.api.features.executions.review.routes.get_node_executions"
)
mock_node_exec = mocker.Mock(spec=NodeExecutionResult)
mock_node_exec.node_exec_id = "node_exec_approved"
@@ -1148,7 +1148,7 @@ async def test_process_review_action_per_review_auto_approve_granularity(
# Mock get_node_executions to return batch node data
mock_get_node_executions = mocker.patch(
"backend.data.execution.get_node_executions"
"backend.api.features.executions.review.routes.get_node_executions"
)
# Create mock node executions for each review
mock_node_execs = []

View File

@@ -6,10 +6,15 @@ import autogpt_libs.auth as autogpt_auth_lib
from fastapi import APIRouter, HTTPException, Query, Security, status
from prisma.enums import ReviewStatus
from backend.copilot.constants import (
is_copilot_synthetic_id,
parse_node_id_from_exec_id,
)
from backend.data.execution import (
ExecutionContext,
ExecutionStatus,
get_graph_execution_meta,
get_node_executions,
)
from backend.data.graph import get_graph_settings
from backend.data.human_review import (
@@ -22,6 +27,7 @@ from backend.data.human_review import (
)
from backend.data.model import USER_TIMEZONE_NOT_SET
from backend.data.user import get_user_by_id
from backend.data.workspace import get_or_create_workspace
from backend.executor.utils import add_graph_execution
from .model import PendingHumanReviewModel, ReviewRequest, ReviewResponse
@@ -35,6 +41,38 @@ router = APIRouter(
)
async def _resolve_node_ids(
node_exec_ids: list[str],
graph_exec_id: str,
is_copilot: bool,
) -> dict[str, str]:
"""Resolve node_exec_id -> node_id for auto-approval records.
CoPilot synthetic IDs encode node_id in the format "{node_id}:{random}".
Graph executions look up node_id from NodeExecution records.
"""
if not node_exec_ids:
return {}
if is_copilot:
return {neid: parse_node_id_from_exec_id(neid) for neid in node_exec_ids}
node_execs = await get_node_executions(
graph_exec_id=graph_exec_id, include_exec_data=False
)
node_exec_map = {ne.node_exec_id: ne.node_id for ne in node_execs}
result = {}
for neid in node_exec_ids:
if neid in node_exec_map:
result[neid] = node_exec_map[neid]
else:
logger.error(
f"Failed to resolve node_id for {neid}: Node execution not found."
)
return result
@router.get(
"/pending",
summary="Get Pending Reviews",
@@ -109,14 +147,16 @@ async def list_pending_reviews_for_execution(
"""
# Verify user owns the graph execution before returning reviews
graph_exec = await get_graph_execution_meta(
user_id=user_id, execution_id=graph_exec_id
)
if not graph_exec:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail=f"Graph execution #{graph_exec_id} not found",
# (CoPilot synthetic IDs don't have graph execution records)
if not is_copilot_synthetic_id(graph_exec_id):
graph_exec = await get_graph_execution_meta(
user_id=user_id, execution_id=graph_exec_id
)
if not graph_exec:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail=f"Graph execution #{graph_exec_id} not found",
)
return await get_pending_reviews_for_execution(graph_exec_id, user_id)
@@ -159,30 +199,26 @@ async def process_review_action(
)
graph_exec_id = next(iter(graph_exec_ids))
is_copilot = is_copilot_synthetic_id(graph_exec_id)
# Validate execution status before processing reviews
graph_exec_meta = await get_graph_execution_meta(
user_id=user_id, execution_id=graph_exec_id
)
if not graph_exec_meta:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail=f"Graph execution #{graph_exec_id} not found",
)
# Only allow processing reviews if execution is paused for review
# or incomplete (partial execution with some reviews already processed)
if graph_exec_meta.status not in (
ExecutionStatus.REVIEW,
ExecutionStatus.INCOMPLETE,
):
raise HTTPException(
status_code=status.HTTP_409_CONFLICT,
detail=f"Cannot process reviews while execution status is {graph_exec_meta.status}. "
f"Reviews can only be processed when execution is paused (REVIEW status). "
f"Current status: {graph_exec_meta.status}",
# Validate execution status for graph executions (skip for CoPilot synthetic IDs)
if not is_copilot:
graph_exec_meta = await get_graph_execution_meta(
user_id=user_id, execution_id=graph_exec_id
)
if not graph_exec_meta:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail=f"Graph execution #{graph_exec_id} not found",
)
if graph_exec_meta.status not in (
ExecutionStatus.REVIEW,
ExecutionStatus.INCOMPLETE,
):
raise HTTPException(
status_code=status.HTTP_409_CONFLICT,
detail=f"Cannot process reviews while execution status is {graph_exec_meta.status}",
)
# Build review decisions map and track which reviews requested auto-approval
# Auto-approved reviews use original data (no modifications allowed)
@@ -235,7 +271,7 @@ async def process_review_action(
)
return (node_id, False)
# Collect node_exec_ids that need auto-approval
# Collect node_exec_ids that need auto-approval and resolve their node_ids
node_exec_ids_needing_auto_approval = [
node_exec_id
for node_exec_id, review_result in updated_reviews.items()
@@ -243,29 +279,16 @@ async def process_review_action(
and auto_approve_requests.get(node_exec_id, False)
]
# Batch-fetch node executions to get node_ids
node_id_map = await _resolve_node_ids(
node_exec_ids_needing_auto_approval, graph_exec_id, is_copilot
)
# Deduplicate by node_id — one auto-approval per node
nodes_needing_auto_approval: dict[str, Any] = {}
if node_exec_ids_needing_auto_approval:
from backend.data.execution import get_node_executions
node_execs = await get_node_executions(
graph_exec_id=graph_exec_id, include_exec_data=False
)
node_exec_map = {node_exec.node_exec_id: node_exec for node_exec in node_execs}
for node_exec_id in node_exec_ids_needing_auto_approval:
node_exec = node_exec_map.get(node_exec_id)
if node_exec:
review_result = updated_reviews[node_exec_id]
# Use the first approved review for this node (deduplicate by node_id)
if node_exec.node_id not in nodes_needing_auto_approval:
nodes_needing_auto_approval[node_exec.node_id] = review_result
else:
logger.error(
f"Failed to create auto-approval record for {node_exec_id}: "
f"Node execution not found. This may indicate a race condition "
f"or data inconsistency."
)
for node_exec_id in node_exec_ids_needing_auto_approval:
node_id = node_id_map.get(node_exec_id)
if node_id and node_id not in nodes_needing_auto_approval:
nodes_needing_auto_approval[node_id] = updated_reviews[node_exec_id]
# Execute all auto-approval creations in parallel (deduplicated by node_id)
auto_approval_results = await asyncio.gather(
@@ -280,13 +303,11 @@ async def process_review_action(
auto_approval_failed_count = 0
for result in auto_approval_results:
if isinstance(result, Exception):
# Unexpected exception during auto-approval creation
auto_approval_failed_count += 1
logger.error(
f"Unexpected exception during auto-approval creation: {result}"
)
elif isinstance(result, tuple) and len(result) == 2 and not result[1]:
# Auto-approval creation failed (returned False)
auto_approval_failed_count += 1
# Count results
@@ -301,30 +322,31 @@ async def process_review_action(
if review.status == ReviewStatus.REJECTED
)
# Resume execution only if ALL pending reviews for this execution have been processed
if updated_reviews:
# Resume graph execution only for real graph executions (not CoPilot)
# CoPilot sessions are resumed by the LLM retrying run_block with review_id
if not is_copilot and updated_reviews:
still_has_pending = await has_pending_reviews_for_graph_exec(graph_exec_id)
if not still_has_pending:
# Get the graph_id from any processed review
first_review = next(iter(updated_reviews.values()))
try:
# Fetch user and settings to build complete execution context
user = await get_user_by_id(user_id)
settings = await get_graph_settings(
user_id=user_id, graph_id=first_review.graph_id
)
# Preserve user's timezone preference when resuming execution
user_timezone = (
user.timezone if user.timezone != USER_TIMEZONE_NOT_SET else "UTC"
)
workspace = await get_or_create_workspace(user_id)
execution_context = ExecutionContext(
human_in_the_loop_safe_mode=settings.human_in_the_loop_safe_mode,
sensitive_action_safe_mode=settings.sensitive_action_safe_mode,
user_timezone=user_timezone,
workspace_id=workspace.id,
)
await add_graph_execution(

View File

@@ -0,0 +1,13 @@
"""Override session-scoped fixtures so unit tests run without the server."""
import pytest
@pytest.fixture(scope="session")
def server():
yield None
@pytest.fixture(scope="session", autouse=True)
def graph_cleanup():
yield

View File

@@ -34,16 +34,21 @@ from backend.data.model import (
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 provider_matches
from backend.integrations.credentials_store import (
is_system_credential,
provider_matches,
)
from backend.integrations.creds_manager import (
IntegrationCredentialsManager,
create_mcp_oauth_handler,
)
from backend.integrations.managed_credentials import ensure_managed_credentials
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
@@ -109,6 +114,7 @@ class CredentialsMetaResponse(BaseModel):
default=None,
description="Host pattern for host-scoped or MCP server URL for MCP credentials",
)
is_managed: bool = False
@model_validator(mode="before")
@classmethod
@@ -138,6 +144,19 @@ class CredentialsMetaResponse(BaseModel):
return None
def to_meta_response(cred: Credentials) -> CredentialsMetaResponse:
return CredentialsMetaResponse(
id=cred.id,
provider=cred.provider,
type=cred.type,
title=cred.title,
scopes=cred.scopes if isinstance(cred, OAuth2Credentials) else None,
username=cred.username if isinstance(cred, OAuth2Credentials) else None,
host=CredentialsMetaResponse.get_host(cred),
is_managed=cred.is_managed,
)
@router.post("/{provider}/callback", summary="Exchange OAuth code for tokens")
async def callback(
provider: Annotated[
@@ -204,34 +223,20 @@ async def callback(
f"and provider {provider.value}"
)
return CredentialsMetaResponse(
id=credentials.id,
provider=credentials.provider,
type=credentials.type,
title=credentials.title,
scopes=credentials.scopes,
username=credentials.username,
host=(CredentialsMetaResponse.get_host(credentials)),
)
return to_meta_response(credentials)
@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))
credentials = await creds_manager.store.get_all_creds(user_id)
return [
CredentialsMetaResponse(
id=cred.id,
provider=cred.provider,
type=cred.type,
title=cred.title,
scopes=cred.scopes if isinstance(cred, OAuth2Credentials) else None,
username=cred.username if isinstance(cred, OAuth2Credentials) else None,
host=CredentialsMetaResponse.get_host(cred),
)
for cred in credentials
to_meta_response(cred) for cred in credentials if not is_sdk_default(cred.id)
]
@@ -242,19 +247,11 @@ 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))
credentials = await creds_manager.store.get_creds_by_provider(user_id, provider)
return [
CredentialsMetaResponse(
id=cred.id,
provider=cred.provider,
type=cred.type,
title=cred.title,
scopes=cred.scopes if isinstance(cred, OAuth2Credentials) else None,
username=cred.username if isinstance(cred, OAuth2Credentials) else None,
host=CredentialsMetaResponse.get_host(cred),
)
for cred in credentials
to_meta_response(cred) for cred in credentials if not is_sdk_default(cred.id)
]
@@ -267,18 +264,21 @@ async def get_credential(
],
cred_id: Annotated[str, Path(title="The ID of the credentials to retrieve")],
user_id: Annotated[str, Security(get_user_id)],
) -> Credentials:
) -> CredentialsMetaResponse:
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 credential.provider != provider:
if not provider_matches(credential.provider, provider):
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Credentials do not match the specified provider",
status_code=status.HTTP_404_NOT_FOUND, detail="Credentials not found"
)
return credential
return to_meta_response(credential)
@router.post("/{provider}/credentials", status_code=201, summary="Create Credentials")
@@ -288,16 +288,22 @@ async def create_credentials(
ProviderName, Path(title="The provider to create credentials for")
],
credentials: Credentials,
) -> Credentials:
) -> CredentialsMetaResponse:
if is_sdk_default(credentials.id):
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail="Cannot create credentials with a reserved ID",
)
credentials.provider = provider
try:
await creds_manager.create(user_id, credentials)
except Exception as e:
except Exception:
logger.exception("Failed to store credentials")
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=f"Failed to store credentials: {str(e)}",
detail="Failed to store credentials",
)
return credentials
return to_meta_response(credentials)
class CredentialsDeletionResponse(BaseModel):
@@ -332,15 +338,29 @@ async def delete_credentials(
bool, Query(title="Whether to proceed if any linked webhooks are still in use")
] = False,
) -> CredentialsDeletionResponse | CredentialsDeletionNeedsConfirmationResponse:
if is_sdk_default(cred_id):
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND, detail="Credentials not found"
)
if is_system_credential(cred_id):
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail="System-managed credentials cannot be deleted",
)
creds = await creds_manager.store.get_creds_by_id(user_id, cred_id)
if not creds:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND, detail="Credentials not found"
)
if creds.provider != provider:
if not provider_matches(creds.provider, provider):
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Credentials do not match the specified provider",
detail="Credentials not found",
)
if creds.is_managed:
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail="AutoGPT-managed credentials cannot be deleted",
)
try:

View File

@@ -0,0 +1,570 @@
"""Tests for credentials API security: no secret leakage, SDK defaults filtered."""
from contextlib import asynccontextmanager
from unittest.mock import AsyncMock, MagicMock, patch
import fastapi
import fastapi.testclient
import pytest
from pydantic import SecretStr
from backend.api.features.integrations.router import router
from backend.data.model import (
APIKeyCredentials,
HostScopedCredentials,
OAuth2Credentials,
UserPasswordCredentials,
)
app = fastapi.FastAPI()
app.include_router(router)
client = fastapi.testclient.TestClient(app)
TEST_USER_ID = "test-user-id"
def _make_api_key_cred(cred_id: str = "cred-123", provider: str = "openai"):
return APIKeyCredentials(
id=cred_id,
provider=provider,
title="My API Key",
api_key=SecretStr("sk-secret-key-value"),
)
def _make_oauth2_cred(cred_id: str = "cred-456", provider: str = "github"):
return OAuth2Credentials(
id=cred_id,
provider=provider,
title="My OAuth",
access_token=SecretStr("ghp_secret_token"),
refresh_token=SecretStr("ghp_refresh_secret"),
scopes=["repo", "user"],
username="testuser",
)
def _make_user_password_cred(cred_id: str = "cred-789", provider: str = "openai"):
return UserPasswordCredentials(
id=cred_id,
provider=provider,
title="My Login",
username=SecretStr("admin"),
password=SecretStr("s3cret-pass"),
)
def _make_host_scoped_cred(cred_id: str = "cred-host", provider: str = "openai"):
return HostScopedCredentials(
id=cred_id,
provider=provider,
title="Host Cred",
host="https://api.example.com",
headers={"Authorization": SecretStr("Bearer top-secret")},
)
def _make_sdk_default_cred(provider: str = "openai"):
return APIKeyCredentials(
id=f"{provider}-default",
provider=provider,
title=f"{provider} (default)",
api_key=SecretStr("sk-platform-secret-key"),
)
@pytest.fixture(autouse=True)
def setup_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()
class TestGetCredentialReturnsMetaOnly:
"""GET /{provider}/credentials/{cred_id} must not return secrets."""
def test_api_key_credential_no_secret(self):
cred = _make_api_key_cred()
with (
patch.object(router, "dependencies", []),
patch("backend.api.features.integrations.router.creds_manager") as mock_mgr,
):
mock_mgr.get = AsyncMock(return_value=cred)
resp = client.get("/openai/credentials/cred-123")
assert resp.status_code == 200
data = resp.json()
assert data["id"] == "cred-123"
assert data["provider"] == "openai"
assert data["type"] == "api_key"
assert "api_key" not in data
assert "sk-secret-key-value" not in str(data)
def test_oauth2_credential_no_secret(self):
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
data = resp.json()
assert data["id"] == "cred-456"
assert data["scopes"] == ["repo", "user"]
assert data["username"] == "testuser"
assert "access_token" not in data
assert "refresh_token" not in data
assert "ghp_" not in str(data)
def test_user_password_credential_no_secret(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.get("/openai/credentials/cred-789")
assert resp.status_code == 200
data = resp.json()
assert data["id"] == "cred-789"
assert "password" not in data
assert "username" not in data or data["username"] is None
assert "s3cret-pass" not in str(data)
assert "admin" not in str(data)
def test_host_scoped_credential_no_secret(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.get("/openai/credentials/cred-host")
assert resp.status_code == 200
data = resp.json()
assert data["id"] == "cred-host"
assert data["host"] == "https://api.example.com"
assert "headers" not in data
assert "top-secret" not in str(data)
def test_get_credential_wrong_provider_returns_404(self):
"""Provider mismatch should return generic 404, not leak credential existence."""
cred = _make_api_key_cred(provider="openai")
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-123")
assert resp.status_code == 404
assert resp.json()["detail"] == "Credentials not found"
def test_list_credentials_no_secrets(self):
"""List endpoint must not leak secrets in any credential."""
creds = [_make_api_key_cred(), _make_oauth2_cred()]
with patch(
"backend.api.features.integrations.router.creds_manager"
) as mock_mgr:
mock_mgr.store.get_all_creds = AsyncMock(return_value=creds)
resp = client.get("/credentials")
assert resp.status_code == 200
raw = str(resp.json())
assert "sk-secret-key-value" not in raw
assert "ghp_secret_token" not in raw
assert "ghp_refresh_secret" not in raw
class TestSdkDefaultCredentialsNotAccessible:
"""SDK default credentials (ID ending in '-default') must be hidden."""
def test_get_sdk_default_returns_404(self):
with patch(
"backend.api.features.integrations.router.creds_manager"
) as mock_mgr:
mock_mgr.get = AsyncMock()
resp = client.get("/openai/credentials/openai-default")
assert resp.status_code == 404
mock_mgr.get.assert_not_called()
def test_list_credentials_excludes_sdk_defaults(self):
user_cred = _make_api_key_cred()
sdk_cred = _make_sdk_default_cred("openai")
with patch(
"backend.api.features.integrations.router.creds_manager"
) as mock_mgr:
mock_mgr.store.get_all_creds = AsyncMock(return_value=[user_cred, sdk_cred])
resp = client.get("/credentials")
assert resp.status_code == 200
data = resp.json()
ids = [c["id"] for c in data]
assert "cred-123" in ids
assert "openai-default" not in ids
def test_list_by_provider_excludes_sdk_defaults(self):
user_cred = _make_api_key_cred()
sdk_cred = _make_sdk_default_cred("openai")
with patch(
"backend.api.features.integrations.router.creds_manager"
) as mock_mgr:
mock_mgr.store.get_creds_by_provider = AsyncMock(
return_value=[user_cred, sdk_cred]
)
resp = client.get("/openai/credentials")
assert resp.status_code == 200
data = resp.json()
ids = [c["id"] for c in data]
assert "cred-123" in ids
assert "openai-default" not in ids
def test_delete_sdk_default_returns_404(self):
with patch(
"backend.api.features.integrations.router.creds_manager"
) as mock_mgr:
mock_mgr.store.get_creds_by_id = AsyncMock()
resp = client.request("DELETE", "/openai/credentials/openai-default")
assert resp.status_code == 404
mock_mgr.store.get_creds_by_id.assert_not_called()
class TestCreateCredentialNoSecretInResponse:
"""POST /{provider}/credentials must not return secrets."""
def test_create_api_key_no_secret_in_response(self):
with patch(
"backend.api.features.integrations.router.creds_manager"
) as mock_mgr:
mock_mgr.create = AsyncMock()
resp = client.post(
"/openai/credentials",
json={
"id": "new-cred",
"provider": "openai",
"type": "api_key",
"title": "New Key",
"api_key": "sk-newsecret",
},
)
assert resp.status_code == 201
data = resp.json()
assert data["id"] == "new-cred"
assert "api_key" not in data
assert "sk-newsecret" not in str(data)
def test_create_with_sdk_default_id_rejected(self):
with patch(
"backend.api.features.integrations.router.creds_manager"
) as mock_mgr:
mock_mgr.create = AsyncMock()
resp = client.post(
"/openai/credentials",
json={
"id": "openai-default",
"provider": "openai",
"type": "api_key",
"title": "Sneaky",
"api_key": "sk-evil",
},
)
assert resp.status_code == 403
mock_mgr.create.assert_not_called()
class TestManagedCredentials:
"""AutoGPT-managed credentials cannot be deleted by users."""
def test_delete_is_managed_returns_403(self):
cred = APIKeyCredentials(
id="managed-cred-1",
provider="agent_mail",
title="AgentMail (managed by AutoGPT)",
api_key=SecretStr("sk-managed-key"),
is_managed=True,
)
with patch(
"backend.api.features.integrations.router.creds_manager"
) as mock_mgr:
mock_mgr.store.get_creds_by_id = AsyncMock(return_value=cred)
resp = client.request("DELETE", "/agent_mail/credentials/managed-cred-1")
assert resp.status_code == 403
assert "AutoGPT-managed" in resp.json()["detail"]
def test_list_credentials_includes_is_managed_field(self):
managed = APIKeyCredentials(
id="managed-1",
provider="agent_mail",
title="AgentMail (managed)",
api_key=SecretStr("sk-key"),
is_managed=True,
)
regular = APIKeyCredentials(
id="regular-1",
provider="openai",
title="My Key",
api_key=SecretStr("sk-key"),
)
with patch(
"backend.api.features.integrations.router.creds_manager"
) as mock_mgr:
mock_mgr.store.get_all_creds = AsyncMock(return_value=[managed, regular])
resp = client.get("/credentials")
assert resp.status_code == 200
data = resp.json()
managed_cred = next(c for c in data if c["id"] == "managed-1")
regular_cred = next(c for c in data if c["id"] == "regular-1")
assert managed_cred["is_managed"] is True
assert regular_cred["is_managed"] is False
# ---------------------------------------------------------------------------
# Managed credential provisioning infrastructure
# ---------------------------------------------------------------------------
def _make_managed_cred(
provider: str = "agent_mail", pod_id: str = "pod-abc"
) -> APIKeyCredentials:
return APIKeyCredentials(
id="managed-auto",
provider=provider,
title="AgentMail (managed by AutoGPT)",
api_key=SecretStr("sk-pod-key"),
is_managed=True,
metadata={"pod_id": pod_id},
)
def _make_store_mock(**kwargs) -> MagicMock:
"""Create a store mock with a working async ``locks()`` context manager."""
@asynccontextmanager
async def _noop_locked(key):
yield
locks_obj = MagicMock()
locks_obj.locked = _noop_locked
store = MagicMock(**kwargs)
store.locks = AsyncMock(return_value=locks_obj)
return store
class TestEnsureManagedCredentials:
"""Unit tests for the ensure/cleanup helpers in managed_credentials.py."""
@pytest.mark.asyncio
async def test_provisions_when_missing(self):
"""Provider.provision() is called when no managed credential exists."""
from backend.integrations.managed_credentials import (
_PROVIDERS,
_provisioned_users,
ensure_managed_credentials,
)
cred = _make_managed_cred()
provider = MagicMock()
provider.provider_name = "test_provider"
provider.is_available = AsyncMock(return_value=True)
provider.provision = AsyncMock(return_value=cred)
store = _make_store_mock()
store.has_managed_credential = AsyncMock(return_value=False)
store.add_managed_credential = AsyncMock()
saved = dict(_PROVIDERS)
_PROVIDERS.clear()
_PROVIDERS["test_provider"] = provider
_provisioned_users.pop("user-1", None)
try:
await ensure_managed_credentials("user-1", store)
finally:
_PROVIDERS.clear()
_PROVIDERS.update(saved)
_provisioned_users.pop("user-1", None)
provider.provision.assert_awaited_once_with("user-1")
store.add_managed_credential.assert_awaited_once_with("user-1", cred)
@pytest.mark.asyncio
async def test_skips_when_already_exists(self):
"""Provider.provision() is NOT called when managed credential exists."""
from backend.integrations.managed_credentials import (
_PROVIDERS,
_provisioned_users,
ensure_managed_credentials,
)
provider = MagicMock()
provider.provider_name = "test_provider"
provider.is_available = AsyncMock(return_value=True)
provider.provision = AsyncMock()
store = _make_store_mock()
store.has_managed_credential = AsyncMock(return_value=True)
saved = dict(_PROVIDERS)
_PROVIDERS.clear()
_PROVIDERS["test_provider"] = provider
_provisioned_users.pop("user-1", None)
try:
await ensure_managed_credentials("user-1", store)
finally:
_PROVIDERS.clear()
_PROVIDERS.update(saved)
_provisioned_users.pop("user-1", None)
provider.provision.assert_not_awaited()
@pytest.mark.asyncio
async def test_skips_when_unavailable(self):
"""Provider.provision() is NOT called when provider is not available."""
from backend.integrations.managed_credentials import (
_PROVIDERS,
_provisioned_users,
ensure_managed_credentials,
)
provider = MagicMock()
provider.provider_name = "test_provider"
provider.is_available = AsyncMock(return_value=False)
provider.provision = AsyncMock()
store = _make_store_mock()
store.has_managed_credential = AsyncMock()
saved = dict(_PROVIDERS)
_PROVIDERS.clear()
_PROVIDERS["test_provider"] = provider
_provisioned_users.pop("user-1", None)
try:
await ensure_managed_credentials("user-1", store)
finally:
_PROVIDERS.clear()
_PROVIDERS.update(saved)
_provisioned_users.pop("user-1", None)
provider.provision.assert_not_awaited()
store.has_managed_credential.assert_not_awaited()
@pytest.mark.asyncio
async def test_provision_failure_does_not_propagate(self):
"""A failed provision is logged but does not raise."""
from backend.integrations.managed_credentials import (
_PROVIDERS,
_provisioned_users,
ensure_managed_credentials,
)
provider = MagicMock()
provider.provider_name = "test_provider"
provider.is_available = AsyncMock(return_value=True)
provider.provision = AsyncMock(side_effect=RuntimeError("boom"))
store = _make_store_mock()
store.has_managed_credential = AsyncMock(return_value=False)
saved = dict(_PROVIDERS)
_PROVIDERS.clear()
_PROVIDERS["test_provider"] = provider
_provisioned_users.pop("user-1", None)
try:
await ensure_managed_credentials("user-1", store)
finally:
_PROVIDERS.clear()
_PROVIDERS.update(saved)
_provisioned_users.pop("user-1", None)
# No exception raised — provisioning failure is swallowed.
class TestCleanupManagedCredentials:
"""Unit tests for cleanup_managed_credentials."""
@pytest.mark.asyncio
async def test_calls_deprovision_for_managed_creds(self):
from backend.integrations.managed_credentials import (
_PROVIDERS,
cleanup_managed_credentials,
)
cred = _make_managed_cred()
provider = MagicMock()
provider.provider_name = "agent_mail"
provider.deprovision = AsyncMock()
store = MagicMock()
store.get_all_creds = AsyncMock(return_value=[cred])
saved = dict(_PROVIDERS)
_PROVIDERS.clear()
_PROVIDERS["agent_mail"] = provider
try:
await cleanup_managed_credentials("user-1", store)
finally:
_PROVIDERS.clear()
_PROVIDERS.update(saved)
provider.deprovision.assert_awaited_once_with("user-1", cred)
@pytest.mark.asyncio
async def test_skips_non_managed_creds(self):
from backend.integrations.managed_credentials import (
_PROVIDERS,
cleanup_managed_credentials,
)
regular = _make_api_key_cred()
provider = MagicMock()
provider.provider_name = "openai"
provider.deprovision = AsyncMock()
store = MagicMock()
store.get_all_creds = AsyncMock(return_value=[regular])
saved = dict(_PROVIDERS)
_PROVIDERS.clear()
_PROVIDERS["openai"] = provider
try:
await cleanup_managed_credentials("user-1", store)
finally:
_PROVIDERS.clear()
_PROVIDERS.update(saved)
provider.deprovision.assert_not_awaited()
@pytest.mark.asyncio
async def test_deprovision_failure_does_not_propagate(self):
from backend.integrations.managed_credentials import (
_PROVIDERS,
cleanup_managed_credentials,
)
cred = _make_managed_cred()
provider = MagicMock()
provider.provider_name = "agent_mail"
provider.deprovision = AsyncMock(side_effect=RuntimeError("boom"))
store = MagicMock()
store.get_all_creds = AsyncMock(return_value=[cred])
saved = dict(_PROVIDERS)
_PROVIDERS.clear()
_PROVIDERS["agent_mail"] = provider
try:
await cleanup_managed_credentials("user-1", store)
finally:
_PROVIDERS.clear()
_PROVIDERS.update(saved)
# No exception raised — cleanup failure is swallowed.

View File

@@ -0,0 +1,120 @@
"""Shared logic for adding store agents to a user's library.
Both `add_store_agent_to_library` and `add_store_agent_to_library_as_admin`
delegate to these helpers so the duplication-prone create/restore/dedup
logic lives in exactly one place.
"""
import logging
import prisma.errors
import prisma.models
import backend.api.features.library.model as library_model
import backend.data.graph as graph_db
from backend.data.graph import GraphModel, GraphSettings
from backend.data.includes import library_agent_include
from backend.util.exceptions import NotFoundError
from backend.util.json import SafeJson
logger = logging.getLogger(__name__)
async def resolve_graph_for_library(
store_listing_version_id: str,
user_id: str,
*,
admin: bool,
) -> GraphModel:
"""Look up a StoreListingVersion and resolve its graph.
When ``admin=True``, uses ``get_graph_as_admin`` to bypass the marketplace
APPROVED-only check. Otherwise uses the regular ``get_graph``.
"""
slv = await prisma.models.StoreListingVersion.prisma().find_unique(
where={"id": store_listing_version_id}, include={"AgentGraph": True}
)
if not slv or not slv.AgentGraph:
raise NotFoundError(
f"Store listing version {store_listing_version_id} not found or invalid"
)
ag = slv.AgentGraph
if admin:
graph_model = await graph_db.get_graph_as_admin(
graph_id=ag.id, version=ag.version, user_id=user_id
)
else:
graph_model = await graph_db.get_graph(
graph_id=ag.id, version=ag.version, user_id=user_id
)
if not graph_model:
raise NotFoundError(f"Graph #{ag.id} v{ag.version} not found or accessible")
return graph_model
async def add_graph_to_library(
store_listing_version_id: str,
graph_model: GraphModel,
user_id: str,
) -> library_model.LibraryAgent:
"""Check existing / restore soft-deleted / create new LibraryAgent.
Uses a create-then-catch-UniqueViolationError-then-update pattern on
the (userId, agentGraphId, agentGraphVersion) composite unique constraint.
This is more robust than ``upsert`` because Prisma's upsert atomicity
guarantees are not well-documented for all versions.
"""
settings_json = SafeJson(GraphSettings.from_graph(graph_model).model_dump())
_include = library_agent_include(
user_id, include_nodes=False, include_executions=False
)
try:
added_agent = await prisma.models.LibraryAgent.prisma().create(
data={
"User": {"connect": {"id": user_id}},
"AgentGraph": {
"connect": {
"graphVersionId": {
"id": graph_model.id,
"version": graph_model.version,
}
}
},
"isCreatedByUser": False,
"useGraphIsActiveVersion": False,
"settings": settings_json,
},
include=_include,
)
except prisma.errors.UniqueViolationError:
# Already exists — update to restore if previously soft-deleted/archived
added_agent = await prisma.models.LibraryAgent.prisma().update(
where={
"userId_agentGraphId_agentGraphVersion": {
"userId": user_id,
"agentGraphId": graph_model.id,
"agentGraphVersion": graph_model.version,
}
},
data={
"isDeleted": False,
"isArchived": False,
"settings": settings_json,
},
include=_include,
)
if added_agent is None:
raise NotFoundError(
f"LibraryAgent for graph #{graph_model.id} "
f"v{graph_model.version} not found after UniqueViolationError"
)
logger.debug(
f"Added graph #{graph_model.id} v{graph_model.version} "
f"for store listing version #{store_listing_version_id} "
f"to library for user #{user_id}"
)
return library_model.LibraryAgent.from_db(added_agent)

View File

@@ -0,0 +1,80 @@
from unittest.mock import AsyncMock, MagicMock, patch
import prisma.errors
import pytest
from ._add_to_library import add_graph_to_library
@pytest.mark.asyncio
async def test_add_graph_to_library_create_new_agent() -> None:
"""When no matching LibraryAgent exists, create inserts a new one."""
graph_model = MagicMock(id="graph-id", version=2, nodes=[])
created_agent = MagicMock(name="CreatedLibraryAgent")
converted_agent = MagicMock(name="ConvertedLibraryAgent")
with (
patch(
"backend.api.features.library._add_to_library.prisma.models.LibraryAgent.prisma"
) as mock_prisma,
patch(
"backend.api.features.library._add_to_library.library_model.LibraryAgent.from_db",
return_value=converted_agent,
) as mock_from_db,
):
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)
# Verify create was called with correct data
create_call = mock_prisma.return_value.create.call_args
create_data = create_call.kwargs["data"]
assert create_data["User"] == {"connect": {"id": "user-id"}}
assert create_data["AgentGraph"] == {
"connect": {"graphVersionId": {"id": "graph-id", "version": 2}}
}
assert create_data["isCreatedByUser"] is False
assert create_data["useGraphIsActiveVersion"] is False
@pytest.mark.asyncio
async def test_add_graph_to_library_unique_violation_updates_existing() -> None:
"""UniqueViolationError on create falls back to update."""
graph_model = MagicMock(id="graph-id", version=2, nodes=[])
updated_agent = MagicMock(name="UpdatedLibraryAgent")
converted_agent = MagicMock(name="ConvertedLibraryAgent")
with (
patch(
"backend.api.features.library._add_to_library.prisma.models.LibraryAgent.prisma"
) as mock_prisma,
patch(
"backend.api.features.library._add_to_library.library_model.LibraryAgent.from_db",
return_value=converted_agent,
) as mock_from_db,
):
mock_prisma.return_value.create = AsyncMock(
side_effect=prisma.errors.UniqueViolationError(
MagicMock(), message="unique constraint"
)
)
mock_prisma.return_value.update = AsyncMock(return_value=updated_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(updated_agent)
# Verify update was called with correct where and data
update_call = mock_prisma.return_value.update.call_args
assert update_call.kwargs["where"] == {
"userId_agentGraphId_agentGraphVersion": {
"userId": "user-id",
"agentGraphId": "graph-id",
"agentGraphVersion": 2,
}
}
update_data = update_call.kwargs["data"]
assert update_data["isDeleted"] is False
assert update_data["isArchived"] is False

View File

@@ -8,7 +8,6 @@ import prisma.errors
import prisma.models
import prisma.types
import backend.api.features.store.exceptions as store_exceptions
import backend.api.features.store.image_gen as store_image_gen
import backend.api.features.store.media as store_media
import backend.data.graph as graph_db
@@ -251,7 +250,7 @@ async def get_library_agent(id: str, user_id: str) -> library_model.LibraryAgent
The requested LibraryAgent.
Raises:
AgentNotFoundError: If the specified agent does not exist.
NotFoundError: If the specified agent does not exist.
DatabaseError: If there's an error during retrieval.
"""
library_agent = await prisma.models.LibraryAgent.prisma().find_first(
@@ -337,12 +336,15 @@ async def get_library_agent_by_graph_id(
user_id: str,
graph_id: str,
graph_version: Optional[int] = None,
include_archived: bool = False,
) -> library_model.LibraryAgent | None:
filter: prisma.types.LibraryAgentWhereInput = {
"agentGraphId": graph_id,
"userId": user_id,
"isDeleted": False,
}
if not include_archived:
filter["isArchived"] = False
if graph_version is not None:
filter["agentGraphVersion"] = graph_version
@@ -398,6 +400,7 @@ async def create_library_agent(
hitl_safe_mode: bool = True,
sensitive_action_safe_mode: bool = False,
create_library_agents_for_sub_graphs: bool = True,
folder_id: str | None = None,
) -> list[library_model.LibraryAgent]:
"""
Adds an agent to the user's library (LibraryAgent table).
@@ -414,12 +417,18 @@ async def create_library_agent(
If the graph has sub-graphs, the parent graph will always be the first entry in the list.
Raises:
AgentNotFoundError: If the specified agent does not exist.
NotFoundError: If the specified agent does not exist.
DatabaseError: If there's an error during creation or if image generation fails.
"""
logger.info(
f"Creating library agent for graph #{graph.id} v{graph.version}; user:<redacted>"
)
# Authorization: FK only checks existence, not ownership.
# Verify the folder belongs to this user to prevent cross-user nesting.
if folder_id:
await get_folder(folder_id, user_id)
graph_entries = (
[graph, *graph.sub_graphs] if create_library_agents_for_sub_graphs else [graph]
)
@@ -427,28 +436,58 @@ async def create_library_agent(
async with transaction() as tx:
library_agents = await asyncio.gather(
*(
prisma.models.LibraryAgent.prisma(tx).create(
data=prisma.types.LibraryAgentCreateInput(
isCreatedByUser=(user_id == user_id),
useGraphIsActiveVersion=True,
User={"connect": {"id": user_id}},
# Creator={"connect": {"id": user_id}},
AgentGraph={
"connect": {
"graphVersionId": {
"id": graph_entry.id,
"version": graph_entry.version,
prisma.models.LibraryAgent.prisma(tx).upsert(
where={
"userId_agentGraphId_agentGraphVersion": {
"userId": user_id,
"agentGraphId": graph_entry.id,
"agentGraphVersion": graph_entry.version,
}
},
data={
"create": prisma.types.LibraryAgentCreateInput(
isCreatedByUser=(user_id == graph.user_id),
useGraphIsActiveVersion=True,
User={"connect": {"id": user_id}},
AgentGraph={
"connect": {
"graphVersionId": {
"id": graph_entry.id,
"version": graph_entry.version,
}
}
}
},
settings=SafeJson(
GraphSettings.from_graph(
graph_entry,
hitl_safe_mode=hitl_safe_mode,
sensitive_action_safe_mode=sensitive_action_safe_mode,
).model_dump()
},
settings=SafeJson(
GraphSettings.from_graph(
graph_entry,
hitl_safe_mode=hitl_safe_mode,
sensitive_action_safe_mode=sensitive_action_safe_mode,
).model_dump()
),
**(
{"Folder": {"connect": {"id": folder_id}}}
if folder_id and graph_entry is graph
else {}
),
),
),
"update": {
"isDeleted": False,
"isArchived": False,
"useGraphIsActiveVersion": True,
"settings": SafeJson(
GraphSettings.from_graph(
graph_entry,
hitl_safe_mode=hitl_safe_mode,
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(
user_id, include_nodes=False, include_executions=False
),
@@ -529,6 +568,7 @@ async def update_agent_version_in_library(
async def create_graph_in_library(
graph: graph_db.Graph,
user_id: str,
folder_id: str | None = None,
) -> tuple[graph_db.GraphModel, library_model.LibraryAgent]:
"""Create a new graph and add it to the user's library."""
graph.version = 1
@@ -542,6 +582,7 @@ async def create_graph_in_library(
user_id=user_id,
sensitive_action_safe_mode=True,
create_library_agents_for_sub_graphs=False,
folder_id=folder_id,
)
if created_graph.is_active:
@@ -570,7 +611,9 @@ async def update_graph_in_library(
created_graph = await graph_db.create_graph(graph_model, user_id)
library_agent = await get_library_agent_by_graph_id(user_id, created_graph.id)
library_agent = await get_library_agent_by_graph_id(
user_id, created_graph.id, include_archived=True
)
if not library_agent:
raise NotFoundError(f"Library agent not found for graph {created_graph.id}")
@@ -806,92 +849,38 @@ async def delete_library_agent_by_graph_id(graph_id: str, user_id: str) -> None:
async def add_store_agent_to_library(
store_listing_version_id: str, user_id: str
) -> library_model.LibraryAgent:
"""Adds a marketplace agent to the users library.
See also: `add_store_agent_to_library_as_admin()` which uses
`get_graph_as_admin` to bypass marketplace status checks for admin review.
"""
Adds an agent from a store listing version to the user's library if they don't already have it.
from ._add_to_library import add_graph_to_library, resolve_graph_for_library
Args:
store_listing_version_id: The ID of the store listing version containing the agent.
user_id: The users library to which the agent is being added.
Returns:
The newly created LibraryAgent if successfully added, the existing corresponding one if any.
Raises:
AgentNotFoundError: If the store listing or associated agent is not found.
DatabaseError: If there's an issue creating the LibraryAgent record.
"""
logger.debug(
f"Adding agent from store listing version #{store_listing_version_id} "
f"to library for user #{user_id}"
)
store_listing_version = (
await prisma.models.StoreListingVersion.prisma().find_unique(
where={"id": store_listing_version_id}, include={"AgentGraph": True}
)
graph_model = await resolve_graph_for_library(
store_listing_version_id, user_id, admin=False
)
if not store_listing_version or not store_listing_version.AgentGraph:
logger.warning(f"Store listing version not found: {store_listing_version_id}")
raise store_exceptions.AgentNotFoundError(
f"Store listing version {store_listing_version_id} not found or invalid"
)
return await add_graph_to_library(store_listing_version_id, graph_model, user_id)
graph = store_listing_version.AgentGraph
# Convert to GraphModel to check for HITL blocks
graph_model = await graph_db.get_graph(
graph_id=graph.id,
version=graph.version,
user_id=user_id,
include_subgraphs=False,
async def add_store_agent_to_library_as_admin(
store_listing_version_id: str, user_id: str
) -> library_model.LibraryAgent:
"""Admin variant that uses `get_graph_as_admin` to bypass marketplace
APPROVED-only checks, allowing admins to add pending agents for review."""
from ._add_to_library import add_graph_to_library, resolve_graph_for_library
logger.warning(
f"ADMIN adding agent from store listing version "
f"#{store_listing_version_id} to library for user #{user_id}"
)
if not graph_model:
raise store_exceptions.AgentNotFoundError(
f"Graph #{graph.id} v{graph.version} not found or accessible"
)
# Check if user already has this agent (non-deleted)
if existing := await get_library_agent_by_graph_id(
user_id, graph.id, graph.version
):
return existing
# Check for soft-deleted version and restore it
deleted_agent = await prisma.models.LibraryAgent.prisma().find_unique(
where={
"userId_agentGraphId_agentGraphVersion": {
"userId": user_id,
"agentGraphId": graph.id,
"agentGraphVersion": graph.version,
}
},
graph_model = await resolve_graph_for_library(
store_listing_version_id, user_id, admin=True
)
if deleted_agent and deleted_agent.isDeleted:
return await update_library_agent(deleted_agent.id, user_id, is_deleted=False)
# Create LibraryAgent entry
added_agent = await prisma.models.LibraryAgent.prisma().create(
data={
"User": {"connect": {"id": user_id}},
"AgentGraph": {
"connect": {
"graphVersionId": {"id": graph.id, "version": graph.version}
}
},
"isCreatedByUser": False,
"useGraphIsActiveVersion": False,
"settings": SafeJson(GraphSettings.from_graph(graph_model).model_dump()),
},
include=library_agent_include(
user_id, include_nodes=False, include_executions=False
),
)
logger.debug(
f"Added graph #{graph.id} v{graph.version}"
f"for store listing version #{store_listing_version.id} "
f"to library for user #{user_id}"
)
return library_model.LibraryAgent.from_db(added_agent)
return await add_graph_to_library(store_listing_version_id, graph_model, user_id)
##############################################
@@ -1481,6 +1470,67 @@ async def bulk_move_agents_to_folder(
return [library_model.LibraryAgent.from_db(agent) for agent in agents]
def collect_tree_ids(
nodes: list[library_model.LibraryFolderTree],
visited: set[str] | None = None,
) -> list[str]:
"""Collect all folder IDs from a folder tree."""
if visited is None:
visited = set()
ids: list[str] = []
for n in nodes:
if n.id in visited:
continue
visited.add(n.id)
ids.append(n.id)
ids.extend(collect_tree_ids(n.children, visited))
return ids
async def get_folder_agent_summaries(
user_id: str, folder_id: str
) -> list[dict[str, str | None]]:
"""Get a lightweight list of agents in a folder (id, name, description)."""
all_agents: list[library_model.LibraryAgent] = []
for page in itertools.count(1):
resp = await list_library_agents(
user_id=user_id, folder_id=folder_id, page=page
)
all_agents.extend(resp.agents)
if page >= resp.pagination.total_pages:
break
return [
{"id": a.id, "name": a.name, "description": a.description} for a in all_agents
]
async def get_root_agent_summaries(
user_id: str,
) -> list[dict[str, str | None]]:
"""Get a lightweight list of root-level agents (folderId IS NULL)."""
all_agents: list[library_model.LibraryAgent] = []
for page in itertools.count(1):
resp = await list_library_agents(
user_id=user_id, include_root_only=True, page=page
)
all_agents.extend(resp.agents)
if page >= resp.pagination.total_pages:
break
return [
{"id": a.id, "name": a.name, "description": a.description} for a in all_agents
]
async def get_folder_agents_map(
user_id: str, folder_ids: list[str]
) -> dict[str, list[dict[str, str | None]]]:
"""Get agent summaries for multiple folders concurrently."""
results = await asyncio.gather(
*(get_folder_agent_summaries(user_id, fid) for fid in folder_ids)
)
return dict(zip(folder_ids, results))
##############################################
########### Presets DB Functions #############
##############################################

View File

@@ -1,10 +1,11 @@
from contextlib import asynccontextmanager
from datetime import datetime
from unittest.mock import AsyncMock, MagicMock, patch
import prisma.enums
import prisma.models
import pytest
import backend.api.features.store.exceptions
from backend.data.db import connect
from backend.data.includes import library_agent_include
@@ -86,10 +87,6 @@ async def test_get_library_agents(mocker):
async def test_add_agent_to_library(mocker):
await connect()
# Mock the transaction context
mock_transaction = mocker.patch("backend.api.features.library.db.transaction")
mock_transaction.return_value.__aenter__ = mocker.AsyncMock(return_value=None)
mock_transaction.return_value.__aexit__ = mocker.AsyncMock(return_value=None)
# Mock data
mock_store_listing_data = prisma.models.StoreListingVersion(
id="version123",
@@ -144,15 +141,18 @@ async def test_add_agent_to_library(mocker):
)
mock_library_agent = mocker.patch("prisma.models.LibraryAgent.prisma")
mock_library_agent.return_value.find_first = mocker.AsyncMock(return_value=None)
mock_library_agent.return_value.find_unique = mocker.AsyncMock(return_value=None)
mock_library_agent.return_value.create = mocker.AsyncMock(
return_value=mock_library_agent_data
)
# Mock graph_db.get_graph function that's called to check for HITL blocks
mock_graph_db = mocker.patch("backend.api.features.library.db.graph_db")
# Mock graph_db.get_graph function that's called in resolve_graph_for_library
# (lives in _add_to_library.py after refactor, not db.py)
mock_graph_db = mocker.patch(
"backend.api.features.library._add_to_library.graph_db"
)
mock_graph_model = mocker.Mock()
mock_graph_model.id = "agent1"
mock_graph_model.version = 1
mock_graph_model.nodes = (
[]
) # Empty list so _has_human_in_the_loop_blocks returns False
@@ -171,37 +171,27 @@ async def test_add_agent_to_library(mocker):
mock_store_listing_version.return_value.find_unique.assert_called_once_with(
where={"id": "version123"}, include={"AgentGraph": True}
)
mock_library_agent.return_value.find_unique.assert_called_once_with(
where={
"userId_agentGraphId_agentGraphVersion": {
"userId": "test-user",
"agentGraphId": "agent1",
"agentGraphVersion": 1,
}
},
)
# Check that create was called with the expected data including settings
create_call_args = mock_library_agent.return_value.create.call_args
assert create_call_args is not None
# Verify the main structure
expected_data = {
# Verify the create data structure
create_data = create_call_args.kwargs["data"]
expected_create = {
"User": {"connect": {"id": "test-user"}},
"AgentGraph": {"connect": {"graphVersionId": {"id": "agent1", "version": 1}}},
"isCreatedByUser": False,
"useGraphIsActiveVersion": False,
}
actual_data = create_call_args[1]["data"]
# Check that all expected fields are present
for key, value in expected_data.items():
assert actual_data[key] == value
for key, value in expected_create.items():
assert create_data[key] == value
# Check that settings field is present and is a SafeJson object
assert "settings" in actual_data
assert hasattr(actual_data["settings"], "__class__") # Should be a SafeJson object
assert "settings" in create_data
assert hasattr(create_data["settings"], "__class__") # Should be a SafeJson object
# Check include parameter
assert create_call_args[1]["include"] == library_agent_include(
assert create_call_args.kwargs["include"] == library_agent_include(
"test-user", include_nodes=False, include_executions=False
)
@@ -218,10 +208,148 @@ async def test_add_agent_to_library_not_found(mocker):
)
# Call function and verify exception
with pytest.raises(backend.api.features.store.exceptions.AgentNotFoundError):
with pytest.raises(db.NotFoundError):
await db.add_store_agent_to_library("version123", "test-user")
# Verify mock called correctly
mock_store_listing_version.return_value.find_unique.assert_called_once_with(
where={"id": "version123"}, include={"AgentGraph": True}
)
@pytest.mark.asyncio
async def test_get_library_agent_by_graph_id_excludes_archived(mocker):
mock_library_agent = mocker.patch("prisma.models.LibraryAgent.prisma")
mock_library_agent.return_value.find_first = mocker.AsyncMock(return_value=None)
result = await db.get_library_agent_by_graph_id("test-user", "agent1", 7)
assert result is None
mock_library_agent.return_value.find_first.assert_called_once()
where = mock_library_agent.return_value.find_first.call_args.kwargs["where"]
assert where == {
"agentGraphId": "agent1",
"userId": "test-user",
"isDeleted": False,
"isArchived": False,
"agentGraphVersion": 7,
}
@pytest.mark.asyncio
async def test_get_library_agent_by_graph_id_can_include_archived(mocker):
mock_library_agent = mocker.patch("prisma.models.LibraryAgent.prisma")
mock_library_agent.return_value.find_first = mocker.AsyncMock(return_value=None)
result = await db.get_library_agent_by_graph_id(
"test-user",
"agent1",
7,
include_archived=True,
)
assert result is None
mock_library_agent.return_value.find_first.assert_called_once()
where = mock_library_agent.return_value.find_first.call_args.kwargs["where"]
assert where == {
"agentGraphId": "agent1",
"userId": "test-user",
"isDeleted": False,
"agentGraphVersion": 7,
}
@pytest.mark.asyncio
async def test_update_graph_in_library_allows_archived_library_agent(mocker):
graph = mocker.Mock(id="graph-id")
existing_version = mocker.Mock(version=1, is_active=True)
graph_model = mocker.Mock()
created_graph = mocker.Mock(id="graph-id", version=2, is_active=False)
current_library_agent = mocker.Mock()
updated_library_agent = mocker.Mock()
mocker.patch(
"backend.api.features.library.db.graph_db.get_graph_all_versions",
new=mocker.AsyncMock(return_value=[existing_version]),
)
mocker.patch(
"backend.api.features.library.db.graph_db.make_graph_model",
return_value=graph_model,
)
mocker.patch(
"backend.api.features.library.db.graph_db.create_graph",
new=mocker.AsyncMock(return_value=created_graph),
)
mock_get_library_agent = mocker.patch(
"backend.api.features.library.db.get_library_agent_by_graph_id",
new=mocker.AsyncMock(return_value=current_library_agent),
)
mock_update_library_agent = mocker.patch(
"backend.api.features.library.db.update_library_agent_version_and_settings",
new=mocker.AsyncMock(return_value=updated_library_agent),
)
result_graph, result_library_agent = await db.update_graph_in_library(
graph,
"test-user",
)
assert result_graph is created_graph
assert result_library_agent is updated_library_agent
assert graph.version == 2
graph_model.reassign_ids.assert_called_once_with(
user_id="test-user", reassign_graph_id=False
)
mock_get_library_agent.assert_awaited_once_with(
"test-user",
"graph-id",
include_archived=True,
)
mock_update_library_agent.assert_awaited_once_with("test-user", created_graph)
@pytest.mark.asyncio
async def test_create_library_agent_uses_upsert():
"""create_library_agent should use upsert (not create) to handle duplicates."""
mock_graph = MagicMock()
mock_graph.id = "graph-1"
mock_graph.version = 1
mock_graph.user_id = "user-1"
mock_graph.nodes = []
mock_graph.sub_graphs = []
mock_upserted = MagicMock(name="UpsertedLibraryAgent")
@asynccontextmanager
async def fake_tx():
yield None
with (
patch("backend.api.features.library.db.transaction", fake_tx),
patch("prisma.models.LibraryAgent.prisma") as mock_prisma,
patch(
"backend.api.features.library.db.add_generated_agent_image",
new=AsyncMock(),
),
patch(
"backend.api.features.library.model.LibraryAgent.from_db",
return_value=MagicMock(),
),
):
mock_prisma.return_value.upsert = AsyncMock(return_value=mock_upserted)
result = await db.create_library_agent(mock_graph, "user-1")
assert len(result) == 1
upsert_call = mock_prisma.return_value.upsert.call_args
assert upsert_call is not None
# Verify the upsert where clause uses the composite unique key
where = upsert_call.kwargs["where"]
assert "userId_agentGraphId_agentGraphVersion" in where
# Verify the upsert data has both create and update branches
data = upsert_call.kwargs["data"]
assert "create" in data
assert "update" in data
# Verify update branch restores soft-deleted/archived agents
assert data["update"]["isDeleted"] is False
assert data["update"]["isArchived"] is False

View File

@@ -165,7 +165,6 @@ class LibraryAgent(pydantic.BaseModel):
id: str
graph_id: str
graph_version: int
owner_user_id: str
image_url: str | None
@@ -206,7 +205,9 @@ class LibraryAgent(pydantic.BaseModel):
default_factory=list,
description="List of recent executions with status, score, and summary",
)
can_access_graph: bool
can_access_graph: bool = pydantic.Field(
description="Indicates whether the same user owns the corresponding graph"
)
is_latest_version: bool
is_favorite: bool
folder_id: str | None = None
@@ -324,7 +325,6 @@ class LibraryAgent(pydantic.BaseModel):
id=agent.id,
graph_id=agent.agentGraphId,
graph_version=agent.agentGraphVersion,
owner_user_id=agent.userId,
image_url=agent.imageUrl,
creator_name=creator_name,
creator_image_url=creator_image_url,

View File

@@ -42,7 +42,6 @@ async def test_get_library_agents_success(
id="test-agent-1",
graph_id="test-agent-1",
graph_version=1,
owner_user_id=test_user_id,
name="Test Agent 1",
description="Test Description 1",
image_url=None,
@@ -67,7 +66,6 @@ async def test_get_library_agents_success(
id="test-agent-2",
graph_id="test-agent-2",
graph_version=1,
owner_user_id=test_user_id,
name="Test Agent 2",
description="Test Description 2",
image_url=None,
@@ -131,7 +129,6 @@ async def test_get_favorite_library_agents_success(
id="test-agent-1",
graph_id="test-agent-1",
graph_version=1,
owner_user_id=test_user_id,
name="Favorite Agent 1",
description="Test Favorite Description 1",
image_url=None,
@@ -184,7 +181,6 @@ def test_add_agent_to_library_success(
id="test-library-agent-id",
graph_id="test-agent-1",
graph_version=1,
owner_user_id=test_user_id,
name="Test Agent 1",
description="Test Description 1",
image_url=None,

View File

@@ -7,20 +7,24 @@ frontend can list available tools on an MCP server before placing a block.
import logging
from typing import Annotated, Any
from urllib.parse import urlparse
import fastapi
from autogpt_libs.auth import get_user_id
from fastapi import Security
from pydantic import BaseModel, Field
from pydantic import BaseModel, Field, SecretStr
from backend.api.features.integrations.router import CredentialsMetaResponse
from backend.blocks.mcp.client import MCPClient, MCPClientError
from backend.blocks.mcp.helpers import (
auto_lookup_mcp_credential,
normalize_mcp_url,
server_host,
)
from backend.blocks.mcp.oauth import MCPOAuthHandler
from backend.data.model import OAuth2Credentials
from backend.integrations.creds_manager import IntegrationCredentialsManager
from backend.integrations.providers import ProviderName
from backend.util.request import HTTPClientError, Requests
from backend.util.request import HTTPClientError, Requests, validate_url_host
from backend.util.settings import Settings
logger = logging.getLogger(__name__)
@@ -74,32 +78,20 @@ async def discover_tools(
If the user has a stored MCP credential for this server URL, it will be
used automatically — no need to pass an explicit auth token.
"""
# Validate URL to prevent SSRF — blocks loopback and private IP ranges.
try:
await validate_url_host(request.server_url)
except ValueError as e:
raise fastapi.HTTPException(status_code=400, detail=f"Invalid server URL: {e}")
auth_token = request.auth_token
# Auto-use stored MCP credential when no explicit token is provided.
if not auth_token:
mcp_creds = await creds_manager.store.get_creds_by_provider(
user_id, ProviderName.MCP.value
best_cred = await auto_lookup_mcp_credential(
user_id, normalize_mcp_url(request.server_url)
)
# Find the freshest credential for this server URL
best_cred: OAuth2Credentials | None = None
for cred in mcp_creds:
if (
isinstance(cred, OAuth2Credentials)
and (cred.metadata or {}).get("mcp_server_url") == request.server_url
):
if best_cred is None or (
(cred.access_token_expires_at or 0)
> (best_cred.access_token_expires_at or 0)
):
best_cred = cred
if best_cred:
# Refresh the token if expired before using it
best_cred = await creds_manager.refresh_if_needed(user_id, best_cred)
logger.info(
f"Using MCP credential {best_cred.id} for {request.server_url}, "
f"expires_at={best_cred.access_token_expires_at}"
)
auth_token = best_cred.access_token.get_secret_value()
client = MCPClient(request.server_url, auth_token=auth_token)
@@ -134,7 +126,7 @@ async def discover_tools(
],
server_name=(
init_result.get("serverInfo", {}).get("name")
or urlparse(request.server_url).hostname
or server_host(request.server_url)
or "MCP"
),
protocol_version=init_result.get("protocolVersion"),
@@ -173,7 +165,16 @@ async def mcp_oauth_login(
3. Performs Dynamic Client Registration (RFC 7591) if available
4. Returns the authorization URL for the frontend to open in a popup
"""
client = MCPClient(request.server_url)
# Validate URL to prevent SSRF — blocks loopback and private IP ranges.
try:
await validate_url_host(request.server_url)
except ValueError as e:
raise fastapi.HTTPException(status_code=400, detail=f"Invalid server URL: {e}")
# Normalize the URL so that credentials stored here are matched consistently
# by auto_lookup_mcp_credential (which also uses normalized URLs).
server_url = normalize_mcp_url(request.server_url)
client = MCPClient(server_url)
# Step 1: Discover protected-resource metadata (RFC 9728)
protected_resource = await client.discover_auth()
@@ -182,7 +183,16 @@ async def mcp_oauth_login(
if protected_resource and protected_resource.get("authorization_servers"):
auth_server_url = protected_resource["authorization_servers"][0]
resource_url = protected_resource.get("resource", request.server_url)
resource_url = protected_resource.get("resource", server_url)
# Validate the auth server URL from metadata to prevent SSRF.
try:
await validate_url_host(auth_server_url)
except ValueError as e:
raise fastapi.HTTPException(
status_code=400,
detail=f"Invalid authorization server URL in metadata: {e}",
)
# Step 2a: Discover auth-server metadata (RFC 8414)
metadata = await client.discover_auth_server_metadata(auth_server_url)
@@ -192,7 +202,7 @@ async def mcp_oauth_login(
# Don't assume a resource_url — omitting it lets the auth server choose
# the correct audience for the token (RFC 8707 resource is optional).
resource_url = None
metadata = await client.discover_auth_server_metadata(request.server_url)
metadata = await client.discover_auth_server_metadata(server_url)
if (
not metadata
@@ -222,12 +232,18 @@ async def mcp_oauth_login(
client_id = ""
client_secret = ""
if registration_endpoint:
reg_result = await _register_mcp_client(
registration_endpoint, redirect_uri, request.server_url
)
if reg_result:
client_id = reg_result.get("client_id", "")
client_secret = reg_result.get("client_secret", "")
# Validate the registration endpoint to prevent SSRF via metadata.
try:
await validate_url_host(registration_endpoint)
except ValueError:
pass # Skip registration, fall back to default client_id
else:
reg_result = await _register_mcp_client(
registration_endpoint, redirect_uri, server_url
)
if reg_result:
client_id = reg_result.get("client_id", "")
client_secret = reg_result.get("client_secret", "")
if not client_id:
client_id = "autogpt-platform"
@@ -245,7 +261,7 @@ async def mcp_oauth_login(
"token_url": token_url,
"revoke_url": revoke_url,
"resource_url": resource_url,
"server_url": request.server_url,
"server_url": server_url,
"client_id": client_id,
"client_secret": client_secret,
},
@@ -342,7 +358,7 @@ async def mcp_oauth_callback(
credentials.metadata["mcp_token_url"] = meta["token_url"]
credentials.metadata["mcp_resource_url"] = meta.get("resource_url", "")
hostname = urlparse(meta["server_url"]).hostname or meta["server_url"]
hostname = server_host(meta["server_url"])
credentials.title = f"MCP: {hostname}"
# Remove old MCP credentials for the same server to prevent stale token buildup.
@@ -357,7 +373,9 @@ async def mcp_oauth_callback(
):
await creds_manager.store.delete_creds_by_id(user_id, old.id)
logger.info(
f"Removed old MCP credential {old.id} for {meta['server_url']}"
"Removed old MCP credential %s for %s",
old.id,
server_host(meta["server_url"]),
)
except Exception:
logger.debug("Could not clean up old MCP credentials", exc_info=True)
@@ -375,6 +393,93 @@ async def mcp_oauth_callback(
)
# ======================== Bearer Token ======================== #
class MCPStoreTokenRequest(BaseModel):
"""Request to store a bearer token for an MCP server that doesn't support OAuth."""
server_url: str = Field(
description="MCP server URL the token authenticates against"
)
token: SecretStr = Field(
min_length=1, description="Bearer token / API key for the MCP server"
)
@router.post(
"/token",
summary="Store a bearer token for an MCP server",
)
async def mcp_store_token(
request: MCPStoreTokenRequest,
user_id: Annotated[str, Security(get_user_id)],
) -> CredentialsMetaResponse:
"""
Store a manually provided bearer token as an MCP credential.
Used by the Copilot MCPSetupCard when the server doesn't support the MCP
OAuth discovery flow (returns 400 from /oauth/login). Subsequent
``run_mcp_tool`` calls will automatically pick up the token via
``_auto_lookup_credential``.
"""
token = request.token.get_secret_value().strip()
if not token:
raise fastapi.HTTPException(status_code=422, detail="Token must not be blank.")
# Validate URL to prevent SSRF — blocks loopback and private IP ranges.
try:
await validate_url_host(request.server_url)
except ValueError as e:
raise fastapi.HTTPException(status_code=400, detail=f"Invalid server URL: {e}")
# Normalize URL so trailing-slash variants match existing credentials.
server_url = normalize_mcp_url(request.server_url)
hostname = server_host(server_url)
# Collect IDs of old credentials to clean up after successful create.
old_cred_ids: list[str] = []
try:
old_creds = await creds_manager.store.get_creds_by_provider(
user_id, ProviderName.MCP.value
)
old_cred_ids = [
old.id
for old in old_creds
if isinstance(old, OAuth2Credentials)
and normalize_mcp_url((old.metadata or {}).get("mcp_server_url", ""))
== server_url
]
except Exception:
logger.debug("Could not query old MCP token credentials", exc_info=True)
credentials = OAuth2Credentials(
provider=ProviderName.MCP.value,
title=f"MCP: {hostname}",
access_token=SecretStr(token),
scopes=[],
metadata={"mcp_server_url": server_url},
)
await creds_manager.create(user_id, credentials)
# Only delete old credentials after the new one is safely stored.
for old_id in old_cred_ids:
try:
await creds_manager.store.delete_creds_by_id(user_id, old_id)
except Exception:
logger.debug("Could not clean up old MCP token credential", exc_info=True)
return CredentialsMetaResponse(
id=credentials.id,
provider=credentials.provider,
type=credentials.type,
title=credentials.title,
scopes=credentials.scopes,
username=credentials.username,
host=hostname,
)
# ======================== Helpers ======================== #
@@ -400,5 +505,7 @@ async def _register_mcp_client(
return data
return None
except Exception as e:
logger.warning(f"Dynamic client registration failed for {server_url}: {e}")
logger.warning(
"Dynamic client registration failed for %s: %s", server_host(server_url), e
)
return None

View File

@@ -11,9 +11,11 @@ import httpx
import pytest
import pytest_asyncio
from autogpt_libs.auth import get_user_id
from pydantic import SecretStr
from backend.api.features.mcp.routes import router
from backend.blocks.mcp.client import MCPClientError, MCPTool
from backend.data.model import OAuth2Credentials
from backend.util.request import HTTPClientError
app = fastapi.FastAPI()
@@ -28,6 +30,16 @@ async def client():
yield c
@pytest.fixture(autouse=True)
def _bypass_ssrf_validation():
"""Bypass validate_url_host in all route tests (test URLs don't resolve)."""
with patch(
"backend.api.features.mcp.routes.validate_url_host",
new_callable=AsyncMock,
):
yield
class TestDiscoverTools:
@pytest.mark.asyncio(loop_scope="session")
async def test_discover_tools_success(self, client):
@@ -56,9 +68,12 @@ class TestDiscoverTools:
with (
patch("backend.api.features.mcp.routes.MCPClient") as MockClient,
patch("backend.api.features.mcp.routes.creds_manager") as mock_cm,
patch(
"backend.api.features.mcp.routes.auto_lookup_mcp_credential",
new_callable=AsyncMock,
return_value=None,
),
):
mock_cm.store.get_creds_by_provider = AsyncMock(return_value=[])
instance = MockClient.return_value
instance.initialize = AsyncMock(
return_value={
@@ -107,10 +122,6 @@ class TestDiscoverTools:
@pytest.mark.asyncio(loop_scope="session")
async def test_discover_tools_auto_uses_stored_credential(self, client):
"""When no explicit token is given, stored MCP credentials are used."""
from pydantic import SecretStr
from backend.data.model import OAuth2Credentials
stored_cred = OAuth2Credentials(
provider="mcp",
title="MCP: example.com",
@@ -124,10 +135,12 @@ class TestDiscoverTools:
with (
patch("backend.api.features.mcp.routes.MCPClient") as MockClient,
patch("backend.api.features.mcp.routes.creds_manager") as mock_cm,
patch(
"backend.api.features.mcp.routes.auto_lookup_mcp_credential",
new_callable=AsyncMock,
return_value=stored_cred,
),
):
mock_cm.store.get_creds_by_provider = AsyncMock(return_value=[stored_cred])
mock_cm.refresh_if_needed = AsyncMock(return_value=stored_cred)
instance = MockClient.return_value
instance.initialize = AsyncMock(
return_value={"serverInfo": {}, "protocolVersion": "2025-03-26"}
@@ -149,9 +162,12 @@ class TestDiscoverTools:
async def test_discover_tools_mcp_error(self, client):
with (
patch("backend.api.features.mcp.routes.MCPClient") as MockClient,
patch("backend.api.features.mcp.routes.creds_manager") as mock_cm,
patch(
"backend.api.features.mcp.routes.auto_lookup_mcp_credential",
new_callable=AsyncMock,
return_value=None,
),
):
mock_cm.store.get_creds_by_provider = AsyncMock(return_value=[])
instance = MockClient.return_value
instance.initialize = AsyncMock(
side_effect=MCPClientError("Connection refused")
@@ -169,9 +185,12 @@ class TestDiscoverTools:
async def test_discover_tools_generic_error(self, client):
with (
patch("backend.api.features.mcp.routes.MCPClient") as MockClient,
patch("backend.api.features.mcp.routes.creds_manager") as mock_cm,
patch(
"backend.api.features.mcp.routes.auto_lookup_mcp_credential",
new_callable=AsyncMock,
return_value=None,
),
):
mock_cm.store.get_creds_by_provider = AsyncMock(return_value=[])
instance = MockClient.return_value
instance.initialize = AsyncMock(side_effect=Exception("Network timeout"))
@@ -187,9 +206,12 @@ class TestDiscoverTools:
async def test_discover_tools_auth_required(self, client):
with (
patch("backend.api.features.mcp.routes.MCPClient") as MockClient,
patch("backend.api.features.mcp.routes.creds_manager") as mock_cm,
patch(
"backend.api.features.mcp.routes.auto_lookup_mcp_credential",
new_callable=AsyncMock,
return_value=None,
),
):
mock_cm.store.get_creds_by_provider = AsyncMock(return_value=[])
instance = MockClient.return_value
instance.initialize = AsyncMock(
side_effect=HTTPClientError("HTTP 401 Error: Unauthorized", 401)
@@ -207,9 +229,12 @@ class TestDiscoverTools:
async def test_discover_tools_forbidden(self, client):
with (
patch("backend.api.features.mcp.routes.MCPClient") as MockClient,
patch("backend.api.features.mcp.routes.creds_manager") as mock_cm,
patch(
"backend.api.features.mcp.routes.auto_lookup_mcp_credential",
new_callable=AsyncMock,
return_value=None,
),
):
mock_cm.store.get_creds_by_provider = AsyncMock(return_value=[])
instance = MockClient.return_value
instance.initialize = AsyncMock(
side_effect=HTTPClientError("HTTP 403 Error: Forbidden", 403)
@@ -331,10 +356,6 @@ class TestOAuthLogin:
class TestOAuthCallback:
@pytest.mark.asyncio(loop_scope="session")
async def test_oauth_callback_success(self, client):
from pydantic import SecretStr
from backend.data.model import OAuth2Credentials
mock_creds = OAuth2Credentials(
provider="mcp",
title=None,
@@ -434,3 +455,118 @@ class TestOAuthCallback:
assert response.status_code == 400
assert "token exchange failed" in response.json()["detail"].lower()
class TestStoreToken:
@pytest.mark.asyncio(loop_scope="session")
async def test_store_token_success(self, client):
with patch("backend.api.features.mcp.routes.creds_manager") as mock_cm:
mock_cm.store.get_creds_by_provider = AsyncMock(return_value=[])
mock_cm.create = AsyncMock()
response = await client.post(
"/token",
json={
"server_url": "https://mcp.example.com/mcp",
"token": "my-api-key-123",
},
)
assert response.status_code == 200
data = response.json()
assert data["provider"] == "mcp"
assert data["type"] == "oauth2"
assert data["host"] == "mcp.example.com"
mock_cm.create.assert_called_once()
@pytest.mark.asyncio(loop_scope="session")
async def test_store_token_blank_rejected(self, client):
"""Blank token string (after stripping) should return 422."""
response = await client.post(
"/token",
json={
"server_url": "https://mcp.example.com/mcp",
"token": " ",
},
)
# Pydantic min_length=1 catches the whitespace-only token
assert response.status_code == 422
@pytest.mark.asyncio(loop_scope="session")
async def test_store_token_replaces_old_credential(self, client):
old_cred = OAuth2Credentials(
provider="mcp",
title="MCP: mcp.example.com",
access_token=SecretStr("old-token"),
scopes=[],
metadata={"mcp_server_url": "https://mcp.example.com/mcp"},
)
with patch("backend.api.features.mcp.routes.creds_manager") as mock_cm:
mock_cm.store.get_creds_by_provider = AsyncMock(return_value=[old_cred])
mock_cm.create = AsyncMock()
mock_cm.store.delete_creds_by_id = AsyncMock()
response = await client.post(
"/token",
json={
"server_url": "https://mcp.example.com/mcp",
"token": "new-token",
},
)
assert response.status_code == 200
mock_cm.store.delete_creds_by_id.assert_called_once_with(
"test-user-id", old_cred.id
)
class TestSSRFValidation:
"""Verify that validate_url_host is enforced on all endpoints."""
@pytest.mark.asyncio(loop_scope="session")
async def test_discover_tools_ssrf_blocked(self, client):
with patch(
"backend.api.features.mcp.routes.validate_url_host",
new_callable=AsyncMock,
side_effect=ValueError("blocked loopback"),
):
response = await client.post(
"/discover-tools",
json={"server_url": "http://localhost/mcp"},
)
assert response.status_code == 400
assert "blocked loopback" in response.json()["detail"].lower()
@pytest.mark.asyncio(loop_scope="session")
async def test_oauth_login_ssrf_blocked(self, client):
with patch(
"backend.api.features.mcp.routes.validate_url_host",
new_callable=AsyncMock,
side_effect=ValueError("blocked private IP"),
):
response = await client.post(
"/oauth/login",
json={"server_url": "http://10.0.0.1/mcp"},
)
assert response.status_code == 400
assert "blocked private ip" in response.json()["detail"].lower()
@pytest.mark.asyncio(loop_scope="session")
async def test_store_token_ssrf_blocked(self, client):
with patch(
"backend.api.features.mcp.routes.validate_url_host",
new_callable=AsyncMock,
side_effect=ValueError("blocked loopback"),
):
response = await client.post(
"/token",
json={
"server_url": "http://127.0.0.1/mcp",
"token": "some-token",
},
)
assert response.status_code == 400
assert "blocked loopback" in response.json()["detail"].lower()

View File

@@ -12,6 +12,7 @@ Tests cover:
5. Complete OAuth flow end-to-end
"""
import asyncio
import base64
import hashlib
import secrets
@@ -58,14 +59,27 @@ async def test_user(server, test_user_id: str):
yield test_user_id
# Cleanup - delete in correct order due to foreign key constraints
await PrismaOAuthAccessToken.prisma().delete_many(where={"userId": test_user_id})
await PrismaOAuthRefreshToken.prisma().delete_many(where={"userId": test_user_id})
await PrismaOAuthAuthorizationCode.prisma().delete_many(
where={"userId": test_user_id}
)
await PrismaOAuthApplication.prisma().delete_many(where={"ownerId": test_user_id})
await PrismaUser.prisma().delete(where={"id": test_user_id})
# Cleanup - delete in correct order due to foreign key constraints.
# Wrap in try/except because the event loop or Prisma engine may already
# be closed during session teardown on Python 3.12+.
try:
await asyncio.gather(
PrismaOAuthAccessToken.prisma().delete_many(where={"userId": test_user_id}),
PrismaOAuthRefreshToken.prisma().delete_many(
where={"userId": test_user_id}
),
PrismaOAuthAuthorizationCode.prisma().delete_many(
where={"userId": test_user_id}
),
)
await asyncio.gather(
PrismaOAuthApplication.prisma().delete_many(
where={"ownerId": test_user_id}
),
PrismaUser.prisma().delete(where={"id": test_user_id}),
)
except RuntimeError:
pass
@pytest_asyncio.fixture

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

@@ -1,5 +1,3 @@
from typing import Literal
from backend.util.cache import cached
from . import db as store_db
@@ -23,7 +21,7 @@ def clear_all_caches():
async def _get_cached_store_agents(
featured: bool,
creator: str | None,
sorted_by: Literal["rating", "runs", "name", "updated_at"] | None,
sorted_by: store_db.StoreAgentsSortOptions | None,
search_query: str | None,
category: str | None,
page: int,
@@ -57,7 +55,7 @@ async def _get_cached_agent_details(
async def _get_cached_store_creators(
featured: bool,
search_query: str | None,
sorted_by: Literal["agent_rating", "agent_runs", "num_agents"] | None,
sorted_by: store_db.StoreCreatorsSortOptions | None,
page: int,
page_size: int,
):
@@ -75,4 +73,4 @@ async def _get_cached_store_creators(
@cached(maxsize=100, ttl_seconds=300, shared_cache=True)
async def _get_cached_creator_details(username: str):
"""Cached helper to get creator details."""
return await store_db.get_store_creator_details(username=username.lower())
return await store_db.get_store_creator(username=username.lower())

View File

@@ -5,16 +5,26 @@ Pluggable system for different content sources (store agents, blocks, docs).
Each handler knows how to fetch and process its content type for embedding.
"""
from __future__ import annotations
import asyncio
import functools
import itertools
import logging
from abc import ABC, abstractmethod
from dataclasses import dataclass
from pathlib import Path
from typing import Any, get_args, get_origin
from typing import TYPE_CHECKING, Any, get_args, get_origin
from prisma.enums import ContentType
from backend.blocks import get_blocks
from backend.blocks.llm import LlmModel
from backend.data.db import query_raw_with_schema
from backend.util.text import split_camelcase
if TYPE_CHECKING:
from backend.blocks._base import AnyBlockSchema
logger = logging.getLogger(__name__)
@@ -154,6 +164,28 @@ class StoreAgentHandler(ContentHandler):
}
@functools.lru_cache(maxsize=1)
def _get_enabled_blocks() -> dict[str, AnyBlockSchema]:
"""Return ``{block_id: block_instance}`` for all enabled, instantiable blocks.
Disabled blocks and blocks that fail to instantiate are silently skipped
(with a warning log), so callers never need their own try/except loop.
Results are cached for the process lifetime via ``lru_cache`` because
blocks are registered at import time and never change while running.
"""
enabled: dict[str, AnyBlockSchema] = {}
for block_id, block_cls in get_blocks().items():
try:
instance = block_cls()
except Exception as e:
logger.warning(f"Skipping block {block_id}: init failed: {e}")
continue
if not instance.disabled:
enabled[block_id] = instance
return enabled
class BlockHandler(ContentHandler):
"""Handler for block definitions (Python classes)."""
@@ -163,16 +195,14 @@ class BlockHandler(ContentHandler):
async def get_missing_items(self, batch_size: int) -> list[ContentItem]:
"""Fetch blocks without embeddings."""
from backend.blocks import get_blocks
# Get all available blocks
all_blocks = get_blocks()
# Check which ones have embeddings
if not all_blocks:
# to_thread keeps the first (heavy) call off the event loop. On
# subsequent calls the lru_cache makes this a dict lookup, so the
# thread-pool overhead is negligible compared to the DB queries below.
enabled = await asyncio.to_thread(_get_enabled_blocks)
if not enabled:
return []
block_ids = list(all_blocks.keys())
block_ids = list(enabled.keys())
# Query for existing embeddings
placeholders = ",".join([f"${i+1}" for i in range(len(block_ids))])
@@ -187,52 +217,42 @@ class BlockHandler(ContentHandler):
)
existing_ids = {row["contentId"] for row in existing_result}
missing_blocks = [
(block_id, block_cls)
for block_id, block_cls in all_blocks.items()
if block_id not in existing_ids
]
# Convert to ContentItem
# Convert to ContentItem — disabled filtering already done by
# _get_enabled_blocks so batch_size won't be exhausted by disabled blocks.
missing = ((bid, b) for bid, b in enabled.items() if bid not in existing_ids)
items = []
for block_id, block_cls in missing_blocks[:batch_size]:
for block_id, block in itertools.islice(missing, batch_size):
try:
block_instance = block_cls()
if block_instance.disabled:
continue
# Build searchable text from block metadata
parts = []
if block_instance.name:
parts.append(block_instance.name)
if block_instance.description:
parts.append(block_instance.description)
if block_instance.categories:
parts.append(
" ".join(str(cat.value) for cat in block_instance.categories)
if not block.name:
logger.warning(
f"Block {block_id} has no name — using block_id as fallback"
)
display_name = split_camelcase(block.name) if block.name else ""
parts = []
if display_name:
parts.append(display_name)
if block.description:
parts.append(block.description)
if block.categories:
parts.append(" ".join(str(cat.value) for cat in block.categories))
# Add input schema field descriptions
block_input_fields = block_instance.input_schema.model_fields
parts += [
f"{field_name}: {field_info.description}"
for field_name, field_info in block_input_fields.items()
for field_name, field_info in block.input_schema.model_fields.items()
if field_info.description
]
searchable_text = " ".join(parts)
categories_list = (
[cat.value for cat in block_instance.categories]
if block_instance.categories
else []
[cat.value for cat in block.categories] if block.categories else []
)
# Extract provider names from credentials fields
credentials_info = (
block_instance.input_schema.get_credentials_fields_info()
)
credentials_info = block.input_schema.get_credentials_fields_info()
is_integration = len(credentials_info) > 0
provider_names = [
provider.value.lower()
@@ -243,7 +263,7 @@ class BlockHandler(ContentHandler):
# Check if block has LlmModel field in input schema
has_llm_model_field = any(
_contains_type(field.annotation, LlmModel)
for field in block_instance.input_schema.model_fields.values()
for field in block.input_schema.model_fields.values()
)
items.append(
@@ -252,13 +272,13 @@ class BlockHandler(ContentHandler):
content_type=ContentType.BLOCK,
searchable_text=searchable_text,
metadata={
"name": block_instance.name,
"name": display_name or block.name or block_id,
"categories": categories_list,
"providers": provider_names,
"has_llm_model_field": has_llm_model_field,
"is_integration": is_integration,
},
user_id=None, # Blocks are public
user_id=None,
)
)
except Exception as e:
@@ -269,22 +289,13 @@ class BlockHandler(ContentHandler):
async def get_stats(self) -> dict[str, int]:
"""Get statistics about block embedding coverage."""
from backend.blocks import get_blocks
all_blocks = get_blocks()
# Filter out disabled blocks - they're not indexed
enabled_block_ids = [
block_id
for block_id, block_cls in all_blocks.items()
if not block_cls().disabled
]
total_blocks = len(enabled_block_ids)
enabled = await asyncio.to_thread(_get_enabled_blocks)
total_blocks = len(enabled)
if total_blocks == 0:
return {"total": 0, "with_embeddings": 0, "without_embeddings": 0}
block_ids = enabled_block_ids
block_ids = list(enabled.keys())
placeholders = ",".join([f"${i+1}" for i in range(len(block_ids))])
embedded_result = await query_raw_with_schema(

View File

@@ -1,7 +1,5 @@
"""
E2E tests for content handlers (blocks, store agents, documentation).
Tests the full flow: discovering content → generating embeddings → storing.
Tests for content handlers (blocks, store agents, documentation).
"""
from pathlib import Path
@@ -15,15 +13,103 @@ from backend.api.features.store.content_handlers import (
BlockHandler,
DocumentationHandler,
StoreAgentHandler,
_get_enabled_blocks,
)
@pytest.fixture(autouse=True)
def _clear_block_cache():
"""Clear the lru_cache on _get_enabled_blocks before each test."""
_get_enabled_blocks.cache_clear()
yield
_get_enabled_blocks.cache_clear()
# ---------------------------------------------------------------------------
# Helper to build a mock block class that returns a pre-configured instance
# ---------------------------------------------------------------------------
def _make_block_class(
*,
name: str = "Block",
description: str = "",
disabled: bool = False,
categories: list[MagicMock] | None = None,
fields: dict[str, str] | None = None,
raise_on_init: Exception | None = None,
) -> MagicMock:
cls = MagicMock()
if raise_on_init is not None:
cls.side_effect = raise_on_init
return cls
inst = MagicMock()
inst.name = name
inst.disabled = disabled
inst.description = description
inst.categories = categories or []
field_mocks = {
fname: MagicMock(description=fdesc) for fname, fdesc in (fields or {}).items()
}
inst.input_schema.model_fields = field_mocks
inst.input_schema.get_credentials_fields_info.return_value = {}
cls.return_value = inst
return cls
# ---------------------------------------------------------------------------
# _get_enabled_blocks
# ---------------------------------------------------------------------------
def test_get_enabled_blocks_filters_disabled():
"""Disabled blocks are excluded."""
blocks = {
"enabled": _make_block_class(name="E", disabled=False),
"disabled": _make_block_class(name="D", disabled=True),
}
with patch(
"backend.api.features.store.content_handlers.get_blocks", return_value=blocks
):
result = _get_enabled_blocks()
assert list(result.keys()) == ["enabled"]
def test_get_enabled_blocks_skips_broken():
"""Blocks that raise on init are skipped without crashing."""
blocks = {
"good": _make_block_class(name="Good"),
"bad": _make_block_class(raise_on_init=RuntimeError("boom")),
}
with patch(
"backend.api.features.store.content_handlers.get_blocks", return_value=blocks
):
result = _get_enabled_blocks()
assert list(result.keys()) == ["good"]
def test_get_enabled_blocks_cached():
"""_get_enabled_blocks() calls get_blocks() only once across multiple calls."""
blocks = {"b1": _make_block_class(name="B1")}
with patch(
"backend.api.features.store.content_handlers.get_blocks", return_value=blocks
) as mock_get_blocks:
result1 = _get_enabled_blocks()
result2 = _get_enabled_blocks()
assert result1 is result2
mock_get_blocks.assert_called_once()
# ---------------------------------------------------------------------------
# StoreAgentHandler
# ---------------------------------------------------------------------------
@pytest.mark.asyncio(loop_scope="session")
async def test_store_agent_handler_get_missing_items(mocker):
"""Test StoreAgentHandler fetches approved agents without embeddings."""
handler = StoreAgentHandler()
# Mock database query
mock_missing = [
{
"id": "agent-1",
@@ -54,9 +140,7 @@ async def test_store_agent_handler_get_stats(mocker):
"""Test StoreAgentHandler returns correct stats."""
handler = StoreAgentHandler()
# Mock approved count query
mock_approved = [{"count": 50}]
# Mock embedded count query
mock_embedded = [{"count": 30}]
with patch(
@@ -70,74 +154,130 @@ async def test_store_agent_handler_get_stats(mocker):
assert stats["without_embeddings"] == 20
# ---------------------------------------------------------------------------
# BlockHandler
# ---------------------------------------------------------------------------
@pytest.mark.asyncio(loop_scope="session")
async def test_block_handler_get_missing_items(mocker):
async def test_block_handler_get_missing_items():
"""Test BlockHandler discovers blocks without embeddings."""
handler = BlockHandler()
# Mock get_blocks to return test blocks
mock_block_class = MagicMock()
mock_block_instance = MagicMock()
mock_block_instance.name = "Calculator Block"
mock_block_instance.description = "Performs calculations"
mock_block_instance.categories = [MagicMock(value="MATH")]
mock_block_instance.disabled = False
mock_field = MagicMock()
mock_field.description = "Math expression to evaluate"
mock_block_instance.input_schema.model_fields = {"expression": mock_field}
mock_block_instance.input_schema.get_credentials_fields_info.return_value = {}
mock_block_class.return_value = mock_block_instance
mock_blocks = {"block-uuid-1": mock_block_class}
# Mock existing embeddings query (no embeddings exist)
mock_existing = []
blocks = {
"block-uuid-1": _make_block_class(
name="CalculatorBlock",
description="Performs calculations",
categories=[MagicMock(value="MATH")],
fields={"expression": "Math expression to evaluate"},
),
}
with patch(
"backend.blocks.get_blocks",
return_value=mock_blocks,
"backend.api.features.store.content_handlers.get_blocks", return_value=blocks
):
with patch(
"backend.api.features.store.content_handlers.query_raw_with_schema",
return_value=mock_existing,
return_value=[],
):
items = await handler.get_missing_items(batch_size=10)
assert len(items) == 1
assert items[0].content_id == "block-uuid-1"
assert items[0].content_type == ContentType.BLOCK
# CamelCase should be split in searchable text and metadata name
assert "Calculator Block" in items[0].searchable_text
assert "Performs calculations" in items[0].searchable_text
assert "MATH" in items[0].searchable_text
assert "expression: Math expression" in items[0].searchable_text
assert items[0].metadata["name"] == "Calculator Block"
assert items[0].user_id is None
@pytest.mark.asyncio(loop_scope="session")
async def test_block_handler_get_stats(mocker):
async def test_block_handler_get_missing_items_splits_camelcase():
"""CamelCase block names are split for better search indexing."""
handler = BlockHandler()
blocks = {
"ai-block": _make_block_class(name="AITextGeneratorBlock"),
}
with patch(
"backend.api.features.store.content_handlers.get_blocks", return_value=blocks
):
with patch(
"backend.api.features.store.content_handlers.query_raw_with_schema",
return_value=[],
):
items = await handler.get_missing_items(batch_size=10)
assert len(items) == 1
assert "AI Text Generator Block" in items[0].searchable_text
@pytest.mark.asyncio(loop_scope="session")
async def test_block_handler_get_missing_items_batch_size_zero():
"""batch_size=0 returns an empty list; the DB is still queried to find missing IDs."""
handler = BlockHandler()
blocks = {"b1": _make_block_class(name="B1")}
with patch(
"backend.api.features.store.content_handlers.get_blocks", return_value=blocks
):
with patch(
"backend.api.features.store.content_handlers.query_raw_with_schema",
return_value=[],
) as mock_query:
items = await handler.get_missing_items(batch_size=0)
assert items == []
# DB query is still issued to learn which blocks lack embeddings;
# the empty result comes from itertools.islice limiting to 0 items.
mock_query.assert_called_once()
@pytest.mark.asyncio(loop_scope="session")
async def test_block_handler_disabled_dont_exhaust_batch():
"""Disabled blocks don't consume batch budget, so enabled blocks get indexed."""
handler = BlockHandler()
# 5 disabled + 3 enabled, batch_size=2
blocks = {
**{
f"dis-{i}": _make_block_class(name=f"D{i}", disabled=True) for i in range(5)
},
**{f"en-{i}": _make_block_class(name=f"E{i}") for i in range(3)},
}
with patch(
"backend.api.features.store.content_handlers.get_blocks", return_value=blocks
):
with patch(
"backend.api.features.store.content_handlers.query_raw_with_schema",
return_value=[],
):
items = await handler.get_missing_items(batch_size=2)
assert len(items) == 2
assert all(item.content_id.startswith("en-") for item in items)
@pytest.mark.asyncio(loop_scope="session")
async def test_block_handler_get_stats():
"""Test BlockHandler returns correct stats."""
handler = BlockHandler()
# Mock get_blocks - each block class returns an instance with disabled=False
def make_mock_block_class():
mock_class = MagicMock()
mock_instance = MagicMock()
mock_instance.disabled = False
mock_class.return_value = mock_instance
return mock_class
mock_blocks = {
"block-1": make_mock_block_class(),
"block-2": make_mock_block_class(),
"block-3": make_mock_block_class(),
blocks = {
"block-1": _make_block_class(name="B1"),
"block-2": _make_block_class(name="B2"),
"block-3": _make_block_class(name="B3"),
}
# Mock embedded count query (2 blocks have embeddings)
mock_embedded = [{"count": 2}]
with patch(
"backend.blocks.get_blocks",
return_value=mock_blocks,
"backend.api.features.store.content_handlers.get_blocks", return_value=blocks
):
with patch(
"backend.api.features.store.content_handlers.query_raw_with_schema",
@@ -150,21 +290,123 @@ async def test_block_handler_get_stats(mocker):
assert stats["without_embeddings"] == 1
@pytest.mark.asyncio(loop_scope="session")
async def test_block_handler_get_stats_skips_broken():
"""get_stats skips broken blocks instead of crashing."""
handler = BlockHandler()
blocks = {
"good": _make_block_class(name="Good"),
"bad": _make_block_class(raise_on_init=RuntimeError("boom")),
}
mock_embedded = [{"count": 1}]
with patch(
"backend.api.features.store.content_handlers.get_blocks", return_value=blocks
):
with patch(
"backend.api.features.store.content_handlers.query_raw_with_schema",
return_value=mock_embedded,
):
stats = await handler.get_stats()
assert stats["total"] == 1 # only the good block
assert stats["with_embeddings"] == 1
@pytest.mark.asyncio(loop_scope="session")
async def test_block_handler_handles_none_name():
"""When block.name is None the fallback display name logic is used."""
handler = BlockHandler()
blocks = {
"none-name-block": _make_block_class(
name="placeholder", # will be overridden to None below
description="A block with no name",
),
}
# Override the name to None after construction so _make_block_class
# doesn't interfere with the mock wiring.
blocks["none-name-block"].return_value.name = None
with patch(
"backend.api.features.store.content_handlers.get_blocks", return_value=blocks
):
with patch(
"backend.api.features.store.content_handlers.query_raw_with_schema",
return_value=[],
):
items = await handler.get_missing_items(batch_size=10)
assert len(items) == 1
# display_name should be "" because block.name is None
# searchable_text should still contain the description
assert "A block with no name" in items[0].searchable_text
# metadata["name"] falls back to block_id when both display_name
# and block.name are falsy, ensuring it is always a non-empty string.
assert items[0].metadata["name"] == "none-name-block"
@pytest.mark.asyncio(loop_scope="session")
async def test_block_handler_handles_empty_attributes():
"""Test BlockHandler handles blocks with empty/falsy attribute values."""
handler = BlockHandler()
blocks = {"block-minimal": _make_block_class(name="Minimal Block")}
with patch(
"backend.api.features.store.content_handlers.get_blocks", return_value=blocks
):
with patch(
"backend.api.features.store.content_handlers.query_raw_with_schema",
return_value=[],
):
items = await handler.get_missing_items(batch_size=10)
assert len(items) == 1
assert items[0].searchable_text == "Minimal Block"
@pytest.mark.asyncio(loop_scope="session")
async def test_block_handler_skips_failed_blocks():
"""Test BlockHandler skips blocks that fail to instantiate."""
handler = BlockHandler()
blocks = {
"good-block": _make_block_class(name="Good Block", description="Works fine"),
"bad-block": _make_block_class(raise_on_init=Exception("Instantiation failed")),
}
with patch(
"backend.api.features.store.content_handlers.get_blocks", return_value=blocks
):
with patch(
"backend.api.features.store.content_handlers.query_raw_with_schema",
return_value=[],
):
items = await handler.get_missing_items(batch_size=10)
assert len(items) == 1
assert items[0].content_id == "good-block"
# ---------------------------------------------------------------------------
# DocumentationHandler
# ---------------------------------------------------------------------------
@pytest.mark.asyncio(loop_scope="session")
async def test_documentation_handler_get_missing_items(tmp_path, mocker):
"""Test DocumentationHandler discovers docs without embeddings."""
handler = DocumentationHandler()
# Create temporary docs directory with test files
docs_root = tmp_path / "docs"
docs_root.mkdir()
(docs_root / "guide.md").write_text("# Getting Started\n\nThis is a guide.")
(docs_root / "api.mdx").write_text("# API Reference\n\nAPI documentation.")
# Mock _get_docs_root to return temp dir
with patch.object(handler, "_get_docs_root", return_value=docs_root):
# Mock existing embeddings query (no embeddings exist)
with patch(
"backend.api.features.store.content_handlers.query_raw_with_schema",
return_value=[],
@@ -173,7 +415,6 @@ async def test_documentation_handler_get_missing_items(tmp_path, mocker):
assert len(items) == 2
# Check guide.md (content_id format: doc_path::section_index)
guide_item = next(
(item for item in items if item.content_id == "guide.md::0"), None
)
@@ -184,7 +425,6 @@ async def test_documentation_handler_get_missing_items(tmp_path, mocker):
assert guide_item.metadata["doc_title"] == "Getting Started"
assert guide_item.user_id is None
# Check api.mdx (content_id format: doc_path::section_index)
api_item = next(
(item for item in items if item.content_id == "api.mdx::0"), None
)
@@ -197,14 +437,12 @@ async def test_documentation_handler_get_stats(tmp_path, mocker):
"""Test DocumentationHandler returns correct stats."""
handler = DocumentationHandler()
# Create temporary docs directory
docs_root = tmp_path / "docs"
docs_root.mkdir()
(docs_root / "doc1.md").write_text("# Doc 1")
(docs_root / "doc2.md").write_text("# Doc 2")
(docs_root / "doc3.mdx").write_text("# Doc 3")
# Mock embedded count query (1 doc has embedding)
mock_embedded = [{"count": 1}]
with patch.object(handler, "_get_docs_root", return_value=docs_root):
@@ -224,13 +462,11 @@ async def test_documentation_handler_title_extraction(tmp_path):
"""Test DocumentationHandler extracts title from markdown heading."""
handler = DocumentationHandler()
# Test with heading
doc_with_heading = tmp_path / "with_heading.md"
doc_with_heading.write_text("# My Title\n\nContent here")
title = handler._extract_doc_title(doc_with_heading)
assert title == "My Title"
# Test without heading
doc_without_heading = tmp_path / "no-heading.md"
doc_without_heading.write_text("Just content, no heading")
title = handler._extract_doc_title(doc_without_heading)
@@ -242,7 +478,6 @@ async def test_documentation_handler_markdown_chunking(tmp_path):
"""Test DocumentationHandler chunks markdown by headings."""
handler = DocumentationHandler()
# Test document with multiple sections
doc_with_sections = tmp_path / "sections.md"
doc_with_sections.write_text(
"# Document Title\n\n"
@@ -254,7 +489,6 @@ async def test_documentation_handler_markdown_chunking(tmp_path):
)
sections = handler._chunk_markdown_by_headings(doc_with_sections)
# Should have 3 sections: intro (with doc title), section one, section two
assert len(sections) == 3
assert sections[0].title == "Document Title"
assert sections[0].index == 0
@@ -268,7 +502,6 @@ async def test_documentation_handler_markdown_chunking(tmp_path):
assert sections[2].index == 2
assert "Content for section two" in sections[2].content
# Test document without headings
doc_no_sections = tmp_path / "no-sections.md"
doc_no_sections.write_text("Just plain content without any headings.")
sections = handler._chunk_markdown_by_headings(doc_no_sections)
@@ -282,21 +515,39 @@ async def test_documentation_handler_section_content_ids():
"""Test DocumentationHandler creates and parses section content IDs."""
handler = DocumentationHandler()
# Test making content ID
content_id = handler._make_section_content_id("docs/guide.md", 2)
assert content_id == "docs/guide.md::2"
# Test parsing content ID
doc_path, section_index = handler._parse_section_content_id("docs/guide.md::2")
assert doc_path == "docs/guide.md"
assert section_index == 2
# Test parsing legacy format (no section index)
doc_path, section_index = handler._parse_section_content_id("docs/old-format.md")
assert doc_path == "docs/old-format.md"
assert section_index == 0
@pytest.mark.asyncio(loop_scope="session")
async def test_documentation_handler_missing_docs_directory():
"""Test DocumentationHandler handles missing docs directory gracefully."""
handler = DocumentationHandler()
fake_path = Path("/nonexistent/docs")
with patch.object(handler, "_get_docs_root", return_value=fake_path):
items = await handler.get_missing_items(batch_size=10)
assert items == []
stats = await handler.get_stats()
assert stats["total"] == 0
assert stats["with_embeddings"] == 0
assert stats["without_embeddings"] == 0
# ---------------------------------------------------------------------------
# Registry
# ---------------------------------------------------------------------------
@pytest.mark.asyncio(loop_scope="session")
async def test_content_handlers_registry():
"""Test all content types are registered."""
@@ -307,88 +558,3 @@ async def test_content_handlers_registry():
assert isinstance(CONTENT_HANDLERS[ContentType.STORE_AGENT], StoreAgentHandler)
assert isinstance(CONTENT_HANDLERS[ContentType.BLOCK], BlockHandler)
assert isinstance(CONTENT_HANDLERS[ContentType.DOCUMENTATION], DocumentationHandler)
@pytest.mark.asyncio(loop_scope="session")
async def test_block_handler_handles_empty_attributes():
"""Test BlockHandler handles blocks with empty/falsy attribute values."""
handler = BlockHandler()
# Mock block with empty values (all attributes exist but are falsy)
mock_block_class = MagicMock()
mock_block_instance = MagicMock()
mock_block_instance.name = "Minimal Block"
mock_block_instance.disabled = False
mock_block_instance.description = ""
mock_block_instance.categories = set()
mock_block_instance.input_schema.model_fields = {}
mock_block_instance.input_schema.get_credentials_fields_info.return_value = {}
mock_block_class.return_value = mock_block_instance
mock_blocks = {"block-minimal": mock_block_class}
with patch(
"backend.blocks.get_blocks",
return_value=mock_blocks,
):
with patch(
"backend.api.features.store.content_handlers.query_raw_with_schema",
return_value=[],
):
items = await handler.get_missing_items(batch_size=10)
assert len(items) == 1
assert items[0].searchable_text == "Minimal Block"
@pytest.mark.asyncio(loop_scope="session")
async def test_block_handler_skips_failed_blocks():
"""Test BlockHandler skips blocks that fail to instantiate."""
handler = BlockHandler()
# Mock one good block and one bad block
good_block = MagicMock()
good_instance = MagicMock()
good_instance.name = "Good Block"
good_instance.description = "Works fine"
good_instance.categories = []
good_instance.disabled = False
good_instance.input_schema.model_fields = {}
good_instance.input_schema.get_credentials_fields_info.return_value = {}
good_block.return_value = good_instance
bad_block = MagicMock()
bad_block.side_effect = Exception("Instantiation failed")
mock_blocks = {"good-block": good_block, "bad-block": bad_block}
with patch(
"backend.blocks.get_blocks",
return_value=mock_blocks,
):
with patch(
"backend.api.features.store.content_handlers.query_raw_with_schema",
return_value=[],
):
items = await handler.get_missing_items(batch_size=10)
# Should only get the good block
assert len(items) == 1
assert items[0].content_id == "good-block"
@pytest.mark.asyncio(loop_scope="session")
async def test_documentation_handler_missing_docs_directory():
"""Test DocumentationHandler handles missing docs directory gracefully."""
handler = DocumentationHandler()
# Mock _get_docs_root to return non-existent path
fake_path = Path("/nonexistent/docs")
with patch.object(handler, "_get_docs_root", return_value=fake_path):
items = await handler.get_missing_items(batch_size=10)
assert items == []
stats = await handler.get_stats()
assert stats["total"] == 0
assert stats["with_embeddings"] == 0
assert stats["without_embeddings"] == 0

File diff suppressed because it is too large Load Diff

View File

@@ -26,7 +26,7 @@ async def test_get_store_agents(mocker):
mock_agents = [
prisma.models.StoreAgent(
listing_id="test-id",
storeListingVersionId="version123",
listing_version_id="version123",
slug="test-agent",
agent_name="Test Agent",
agent_video=None,
@@ -40,11 +40,11 @@ async def test_get_store_agents(mocker):
runs=10,
rating=4.5,
versions=["1.0"],
agentGraphVersions=["1"],
agentGraphId="test-graph-id",
graph_id="test-graph-id",
graph_versions=["1"],
updated_at=datetime.now(),
is_available=False,
useForOnboarding=False,
use_for_onboarding=False,
)
]
@@ -68,10 +68,10 @@ async def test_get_store_agents(mocker):
@pytest.mark.asyncio(loop_scope="session")
async def test_get_store_agent_details(mocker):
# Mock data
# Mock data - StoreAgent view already contains the active version data
mock_agent = prisma.models.StoreAgent(
listing_id="test-id",
storeListingVersionId="version123",
listing_version_id="version123",
slug="test-agent",
agent_name="Test Agent",
agent_video="video.mp4",
@@ -85,102 +85,38 @@ async def test_get_store_agent_details(mocker):
runs=10,
rating=4.5,
versions=["1.0"],
agentGraphVersions=["1"],
agentGraphId="test-graph-id",
updated_at=datetime.now(),
is_available=False,
useForOnboarding=False,
)
# Mock active version agent (what we want to return for active version)
mock_active_agent = prisma.models.StoreAgent(
listing_id="test-id",
storeListingVersionId="active-version-id",
slug="test-agent",
agent_name="Test Agent Active",
agent_video="active_video.mp4",
agent_image=["active_image.jpg"],
featured=False,
creator_username="creator",
creator_avatar="avatar.jpg",
sub_heading="Test heading active",
description="Test description active",
categories=["test"],
runs=15,
rating=4.8,
versions=["1.0", "2.0"],
agentGraphVersions=["1", "2"],
agentGraphId="test-graph-id-active",
graph_id="test-graph-id",
graph_versions=["1"],
updated_at=datetime.now(),
is_available=True,
useForOnboarding=False,
use_for_onboarding=False,
)
# Create a mock StoreListing result
mock_store_listing = mocker.MagicMock()
mock_store_listing.activeVersionId = "active-version-id"
mock_store_listing.hasApprovedVersion = True
mock_store_listing.ActiveVersion = mocker.MagicMock()
mock_store_listing.ActiveVersion.recommendedScheduleCron = None
# Mock StoreAgent prisma call - need to handle multiple calls
# Mock StoreAgent prisma call
mock_store_agent = mocker.patch("prisma.models.StoreAgent.prisma")
# Set up side_effect to return different results for different calls
def mock_find_first_side_effect(*args, **kwargs):
where_clause = kwargs.get("where", {})
if "storeListingVersionId" in where_clause:
# Second call for active version
return mock_active_agent
else:
# First call for initial lookup
return mock_agent
mock_store_agent.return_value.find_first = mocker.AsyncMock(
side_effect=mock_find_first_side_effect
)
# Mock Profile prisma call
mock_profile = mocker.MagicMock()
mock_profile.userId = "user-id-123"
mock_profile_db = mocker.patch("prisma.models.Profile.prisma")
mock_profile_db.return_value.find_first = mocker.AsyncMock(
return_value=mock_profile
)
# Mock StoreListing prisma call
mock_store_listing_db = mocker.patch("prisma.models.StoreListing.prisma")
mock_store_listing_db.return_value.find_first = mocker.AsyncMock(
return_value=mock_store_listing
)
mock_store_agent.return_value.find_first = mocker.AsyncMock(return_value=mock_agent)
# Call function
result = await db.get_store_agent_details("creator", "test-agent")
# Verify results - should use active version data
# Verify results - constructed from the StoreAgent view
assert result.slug == "test-agent"
assert result.agent_name == "Test Agent Active" # From active version
assert result.active_version_id == "active-version-id"
assert result.agent_name == "Test Agent"
assert result.active_version_id == "version123"
assert result.has_approved_version is True
assert (
result.store_listing_version_id == "active-version-id"
) # Should be active version ID
assert result.store_listing_version_id == "version123"
assert result.graph_id == "test-graph-id"
assert result.runs == 10
assert result.rating == 4.5
# Verify mocks called correctly - now expecting 2 calls
assert mock_store_agent.return_value.find_first.call_count == 2
# Check the specific calls
calls = mock_store_agent.return_value.find_first.call_args_list
assert calls[0] == mocker.call(
# Verify single StoreAgent lookup
mock_store_agent.return_value.find_first.assert_called_once_with(
where={"creator_username": "creator", "slug": "test-agent"}
)
assert calls[1] == mocker.call(where={"storeListingVersionId": "active-version-id"})
mock_store_listing_db.return_value.find_first.assert_called_once()
@pytest.mark.asyncio(loop_scope="session")
async def test_get_store_creator_details(mocker):
async def test_get_store_creator(mocker):
# Mock data
mock_creator_data = prisma.models.Creator(
name="Test Creator",
@@ -202,7 +138,7 @@ async def test_get_store_creator_details(mocker):
mock_creator.return_value.find_unique.return_value = mock_creator_data
# Call function
result = await db.get_store_creator_details("creator")
result = await db.get_store_creator("creator")
# Verify results
assert result.username == "creator"
@@ -218,61 +154,111 @@ async def test_get_store_creator_details(mocker):
@pytest.mark.asyncio(loop_scope="session")
async def test_create_store_submission(mocker):
# Mock data
now = datetime.now()
# Mock agent graph (with no pending submissions) and user with profile
mock_profile = prisma.models.Profile(
id="profile-id",
userId="user-id",
name="Test User",
username="testuser",
description="Test",
isFeatured=False,
links=[],
createdAt=now,
updatedAt=now,
)
mock_user = prisma.models.User(
id="user-id",
email="test@example.com",
createdAt=now,
updatedAt=now,
Profile=[mock_profile],
emailVerified=True,
metadata="{}", # type: ignore[reportArgumentType]
integrations="",
maxEmailsPerDay=1,
notifyOnAgentRun=True,
notifyOnZeroBalance=True,
notifyOnLowBalance=True,
notifyOnBlockExecutionFailed=True,
notifyOnContinuousAgentError=True,
notifyOnDailySummary=True,
notifyOnWeeklySummary=True,
notifyOnMonthlySummary=True,
notifyOnAgentApproved=True,
notifyOnAgentRejected=True,
timezone="Europe/Delft",
subscriptionTier=prisma.enums.SubscriptionTier.FREE, # type: ignore[reportCallIssue,reportAttributeAccessIssue]
)
mock_agent = prisma.models.AgentGraph(
id="agent-id",
version=1,
userId="user-id",
createdAt=datetime.now(),
createdAt=now,
isActive=True,
StoreListingVersions=[],
User=mock_user,
)
mock_listing = prisma.models.StoreListing(
# Mock the created StoreListingVersion (returned by create)
mock_store_listing_obj = prisma.models.StoreListing(
id="listing-id",
createdAt=datetime.now(),
updatedAt=datetime.now(),
createdAt=now,
updatedAt=now,
isDeleted=False,
hasApprovedVersion=False,
slug="test-agent",
agentGraphId="agent-id",
agentGraphVersion=1,
owningUserId="user-id",
Versions=[
prisma.models.StoreListingVersion(
id="version-id",
agentGraphId="agent-id",
agentGraphVersion=1,
name="Test Agent",
description="Test description",
createdAt=datetime.now(),
updatedAt=datetime.now(),
subHeading="Test heading",
imageUrls=["image.jpg"],
categories=["test"],
isFeatured=False,
isDeleted=False,
version=1,
storeListingId="listing-id",
submissionStatus=prisma.enums.SubmissionStatus.PENDING,
isAvailable=True,
)
],
useForOnboarding=False,
)
mock_version = prisma.models.StoreListingVersion(
id="version-id",
agentGraphId="agent-id",
agentGraphVersion=1,
name="Test Agent",
description="Test description",
createdAt=now,
updatedAt=now,
subHeading="",
imageUrls=[],
categories=[],
isFeatured=False,
isDeleted=False,
version=1,
storeListingId="listing-id",
submissionStatus=prisma.enums.SubmissionStatus.PENDING,
isAvailable=True,
submittedAt=now,
StoreListing=mock_store_listing_obj,
)
# 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_store_listing = mocker.patch("prisma.models.StoreListing.prisma")
mock_store_listing.return_value.find_first = mocker.AsyncMock(return_value=None)
mock_store_listing.return_value.create = mocker.AsyncMock(return_value=mock_listing)
# 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),
),
)
mock_sl = mocker.patch("prisma.models.StoreListing.prisma")
mock_sl.return_value.find_unique = mocker.AsyncMock(return_value=None)
mock_slv = mocker.patch("prisma.models.StoreListingVersion.prisma")
mock_slv.return_value.create = mocker.AsyncMock(return_value=mock_version)
# Call function
result = await db.create_store_submission(
user_id="user-id",
agent_id="agent-id",
agent_version=1,
graph_id="agent-id",
graph_version=1,
slug="test-agent",
name="Test Agent",
description="Test description",
@@ -281,11 +267,11 @@ async def test_create_store_submission(mocker):
# Verify results
assert result.name == "Test Agent"
assert result.description == "Test description"
assert result.store_listing_version_id == "version-id"
assert result.listing_version_id == "version-id"
# Verify mocks called correctly
mock_agent_graph.return_value.find_first.assert_called_once()
mock_store_listing.return_value.create.assert_called_once()
mock_slv.return_value.create.assert_called_once()
@pytest.mark.asyncio(loop_scope="session")
@@ -318,7 +304,6 @@ async def test_update_profile(mocker):
description="Test description",
links=["link1"],
avatar_url="avatar.jpg",
is_featured=False,
)
# Call function
@@ -389,7 +374,7 @@ async def test_get_store_agents_with_search_and_filters_parameterized():
creators=["creator1'; DROP TABLE Users; --", "creator2"],
category="AI'; DELETE FROM StoreAgent; --",
featured=True,
sorted_by="rating",
sorted_by=db.StoreAgentsSortOptions.RATING,
page=1,
page_size=20,
)

View File

@@ -15,6 +15,7 @@ from prisma.enums import ContentType
from tiktoken import encoding_for_model
from backend.api.features.store.content_handlers import CONTENT_HANDLERS
from backend.blocks import get_blocks
from backend.data.db import execute_raw_with_schema, query_raw_with_schema
from backend.util.clients import get_openai_client
from backend.util.json import dumps
@@ -662,8 +663,6 @@ async def cleanup_orphaned_embeddings() -> dict[str, Any]:
)
current_ids = {row["id"] for row in valid_agents}
elif content_type == ContentType.BLOCK:
from backend.blocks import get_blocks
current_ids = set(get_blocks().keys())
elif content_type == ContentType.DOCUMENTATION:
# Use DocumentationHandler to get section-based content IDs

View File

@@ -57,12 +57,6 @@ class StoreError(ValueError):
pass
class AgentNotFoundError(NotFoundError):
"""Raised when an agent is not found"""
pass
class CreatorNotFoundError(NotFoundError):
"""Raised when a creator is not found"""

View File

@@ -31,12 +31,10 @@ logger = logging.getLogger(__name__)
def tokenize(text: str) -> list[str]:
"""Simple tokenizer for BM25 - lowercase and split on non-alphanumeric."""
"""Tokenize text for BM25."""
if not text:
return []
# Lowercase and split on non-alphanumeric characters
tokens = re.findall(r"\b\w+\b", text.lower())
return tokens
return re.findall(r"\b\w+\b", text.lower())
def bm25_rerank(
@@ -568,7 +566,7 @@ async def hybrid_search(
SELECT uce."contentId" as "storeListingVersionId"
FROM {{schema_prefix}}"UnifiedContentEmbedding" uce
INNER JOIN {{schema_prefix}}"StoreAgent" sa
ON uce."contentId" = sa."storeListingVersionId"
ON uce."contentId" = sa.listing_version_id
WHERE uce."contentType" = 'STORE_AGENT'::{{schema_prefix}}"ContentType"
AND uce."userId" IS NULL
AND uce.search @@ plainto_tsquery('english', {query_param})
@@ -582,7 +580,7 @@ async def hybrid_search(
SELECT uce."contentId", uce.embedding
FROM {{schema_prefix}}"UnifiedContentEmbedding" uce
INNER JOIN {{schema_prefix}}"StoreAgent" sa
ON uce."contentId" = sa."storeListingVersionId"
ON uce."contentId" = sa.listing_version_id
WHERE uce."contentType" = 'STORE_AGENT'::{{schema_prefix}}"ContentType"
AND uce."userId" IS NULL
AND {where_clause}
@@ -605,7 +603,7 @@ async def hybrid_search(
sa.featured,
sa.is_available,
sa.updated_at,
sa."agentGraphId",
sa.graph_id,
-- Searchable text for BM25 reranking
COALESCE(sa.agent_name, '') || ' ' || COALESCE(sa.sub_heading, '') || ' ' || COALESCE(sa.description, '') as searchable_text,
-- Semantic score
@@ -627,9 +625,9 @@ async def hybrid_search(
sa.runs as popularity_raw
FROM candidates c
INNER JOIN {{schema_prefix}}"StoreAgent" sa
ON c."storeListingVersionId" = sa."storeListingVersionId"
ON c."storeListingVersionId" = sa.listing_version_id
INNER JOIN {{schema_prefix}}"UnifiedContentEmbedding" uce
ON sa."storeListingVersionId" = uce."contentId"
ON sa.listing_version_id = uce."contentId"
AND uce."contentType" = 'STORE_AGENT'::{{schema_prefix}}"ContentType"
),
max_vals AS (
@@ -665,7 +663,7 @@ async def hybrid_search(
featured,
is_available,
updated_at,
"agentGraphId",
graph_id,
searchable_text,
semantic_score,
lexical_score,

View File

@@ -14,9 +14,27 @@ from backend.api.features.store.hybrid_search import (
HybridSearchWeights,
UnifiedSearchWeights,
hybrid_search,
tokenize,
unified_hybrid_search,
)
# ---------------------------------------------------------------------------
# tokenize (BM25)
# ---------------------------------------------------------------------------
@pytest.mark.parametrize(
"input_text, expected",
[
("AITextGeneratorBlock", ["aitextgeneratorblock"]),
("hello world", ["hello", "world"]),
("", []),
("HTTPRequest", ["httprequest"]),
],
)
def test_tokenize(input_text: str, expected: list[str]):
assert tokenize(input_text) == expected
@pytest.mark.asyncio(loop_scope="session")
@pytest.mark.integration

View File

@@ -1,11 +1,14 @@
import datetime
from typing import List
from typing import TYPE_CHECKING, List, Self
import prisma.enums
import pydantic
from backend.util.models import Pagination
if TYPE_CHECKING:
import prisma.models
class ChangelogEntry(pydantic.BaseModel):
version: str
@@ -13,9 +16,9 @@ class ChangelogEntry(pydantic.BaseModel):
date: datetime.datetime
class MyAgent(pydantic.BaseModel):
agent_id: str
agent_version: int
class MyUnpublishedAgent(pydantic.BaseModel):
graph_id: str
graph_version: int
agent_name: str
agent_image: str | None = None
description: str
@@ -23,8 +26,8 @@ class MyAgent(pydantic.BaseModel):
recommended_schedule_cron: str | None = None
class MyAgentsResponse(pydantic.BaseModel):
agents: list[MyAgent]
class MyUnpublishedAgentsResponse(pydantic.BaseModel):
agents: list[MyUnpublishedAgent]
pagination: Pagination
@@ -40,6 +43,21 @@ class StoreAgent(pydantic.BaseModel):
rating: float
agent_graph_id: str
@classmethod
def from_db(cls, agent: "prisma.models.StoreAgent") -> "StoreAgent":
return cls(
slug=agent.slug,
agent_name=agent.agent_name,
agent_image=agent.agent_image[0] if agent.agent_image else "",
creator=agent.creator_username or "Needs Profile",
creator_avatar=agent.creator_avatar or "",
sub_heading=agent.sub_heading,
description=agent.description,
runs=agent.runs,
rating=agent.rating,
agent_graph_id=agent.graph_id,
)
class StoreAgentsResponse(pydantic.BaseModel):
agents: list[StoreAgent]
@@ -62,81 +80,192 @@ class StoreAgentDetails(pydantic.BaseModel):
runs: int
rating: float
versions: list[str]
agentGraphVersions: list[str]
agentGraphId: str
graph_id: str
graph_versions: list[str]
last_updated: datetime.datetime
recommended_schedule_cron: str | None = None
active_version_id: str | None = None
has_approved_version: bool = False
active_version_id: str
has_approved_version: bool
# Optional changelog data when include_changelog=True
changelog: list[ChangelogEntry] | None = None
class Creator(pydantic.BaseModel):
name: str
username: str
description: str
avatar_url: str
num_agents: int
agent_rating: float
agent_runs: int
is_featured: bool
class CreatorsResponse(pydantic.BaseModel):
creators: List[Creator]
pagination: Pagination
class CreatorDetails(pydantic.BaseModel):
name: str
username: str
description: str
links: list[str]
avatar_url: str
agent_rating: float
agent_runs: int
top_categories: list[str]
@classmethod
def from_db(cls, agent: "prisma.models.StoreAgent") -> "StoreAgentDetails":
return cls(
store_listing_version_id=agent.listing_version_id,
slug=agent.slug,
agent_name=agent.agent_name,
agent_video=agent.agent_video or "",
agent_output_demo=agent.agent_output_demo or "",
agent_image=agent.agent_image,
creator=agent.creator_username or "",
creator_avatar=agent.creator_avatar or "",
sub_heading=agent.sub_heading,
description=agent.description,
categories=agent.categories,
runs=agent.runs,
rating=agent.rating,
versions=agent.versions,
graph_id=agent.graph_id,
graph_versions=agent.graph_versions,
last_updated=agent.updated_at,
recommended_schedule_cron=agent.recommended_schedule_cron,
active_version_id=agent.listing_version_id,
has_approved_version=True, # StoreAgent view only has approved agents
)
class Profile(pydantic.BaseModel):
name: str
"""Marketplace user profile (only attributes that the user can update)"""
username: str
name: str
description: str
avatar_url: str | None
links: list[str]
avatar_url: str
is_featured: bool = False
class ProfileDetails(Profile):
"""Marketplace user profile (including read-only fields)"""
is_featured: bool
@classmethod
def from_db(cls, profile: "prisma.models.Profile") -> "ProfileDetails":
return cls(
name=profile.name,
username=profile.username,
avatar_url=profile.avatarUrl,
description=profile.description,
links=profile.links,
is_featured=profile.isFeatured,
)
class CreatorDetails(ProfileDetails):
"""Marketplace creator profile details, including aggregated stats"""
num_agents: int
agent_runs: int
agent_rating: float
top_categories: list[str]
@classmethod
def from_db(cls, creator: "prisma.models.Creator") -> "CreatorDetails": # type: ignore[override]
return cls(
name=creator.name,
username=creator.username,
avatar_url=creator.avatar_url,
description=creator.description,
links=creator.links,
is_featured=creator.is_featured,
num_agents=creator.num_agents,
agent_runs=creator.agent_runs,
agent_rating=creator.agent_rating,
top_categories=creator.top_categories,
)
class CreatorsResponse(pydantic.BaseModel):
creators: List[CreatorDetails]
pagination: Pagination
class StoreSubmission(pydantic.BaseModel):
# From StoreListing:
listing_id: str
agent_id: str
agent_version: int
user_id: str
slug: str
# From StoreListingVersion:
listing_version_id: str
listing_version: int
graph_id: str
graph_version: int
name: str
sub_heading: str
slug: str
description: str
instructions: str | None = None
instructions: str | None
categories: list[str]
image_urls: list[str]
date_submitted: datetime.datetime
status: prisma.enums.SubmissionStatus
runs: int
rating: float
store_listing_version_id: str | None = None
version: int | None = None # Actual version number from the database
video_url: str | None
agent_output_demo_url: str | None
submitted_at: datetime.datetime | None
changes_summary: str | None
status: prisma.enums.SubmissionStatus
reviewed_at: datetime.datetime | None = None
reviewer_id: str | None = None
review_comments: str | None = None # External comments visible to creator
internal_comments: str | None = None # Private notes for admin use only
reviewed_at: datetime.datetime | None = None
changes_summary: str | None = None
# Additional fields for editing
video_url: str | None = None
agent_output_demo_url: str | None = None
categories: list[str] = []
# Aggregated from AgentGraphExecutions and StoreListingReviews:
run_count: int = 0
review_count: int = 0
review_avg_rating: float = 0.0
@classmethod
def from_db(cls, _sub: "prisma.models.StoreSubmission") -> Self:
"""Construct from the StoreSubmission Prisma view."""
return cls(
listing_id=_sub.listing_id,
user_id=_sub.user_id,
slug=_sub.slug,
listing_version_id=_sub.listing_version_id,
listing_version=_sub.listing_version,
graph_id=_sub.graph_id,
graph_version=_sub.graph_version,
name=_sub.name,
sub_heading=_sub.sub_heading,
description=_sub.description,
instructions=_sub.instructions,
categories=_sub.categories,
image_urls=_sub.image_urls,
video_url=_sub.video_url,
agent_output_demo_url=_sub.agent_output_demo_url,
submitted_at=_sub.submitted_at,
changes_summary=_sub.changes_summary,
status=_sub.status,
reviewed_at=_sub.reviewed_at,
reviewer_id=_sub.reviewer_id,
review_comments=_sub.review_comments,
run_count=_sub.run_count,
review_count=_sub.review_count,
review_avg_rating=_sub.review_avg_rating,
)
@classmethod
def from_listing_version(cls, _lv: "prisma.models.StoreListingVersion") -> Self:
"""
Construct from the StoreListingVersion Prisma model (with StoreListing included)
"""
if not (_l := _lv.StoreListing):
raise ValueError("StoreListingVersion must have included StoreListing")
return cls(
listing_id=_l.id,
user_id=_l.owningUserId,
slug=_l.slug,
listing_version_id=_lv.id,
listing_version=_lv.version,
graph_id=_lv.agentGraphId,
graph_version=_lv.agentGraphVersion,
name=_lv.name,
sub_heading=_lv.subHeading,
description=_lv.description,
instructions=_lv.instructions,
categories=_lv.categories,
image_urls=_lv.imageUrls,
video_url=_lv.videoUrl,
agent_output_demo_url=_lv.agentOutputDemoUrl,
submitted_at=_lv.submittedAt,
changes_summary=_lv.changesSummary,
status=_lv.submissionStatus,
reviewed_at=_lv.reviewedAt,
reviewer_id=_lv.reviewerId,
review_comments=_lv.reviewComments,
)
class StoreSubmissionsResponse(pydantic.BaseModel):
@@ -144,33 +273,12 @@ class StoreSubmissionsResponse(pydantic.BaseModel):
pagination: Pagination
class StoreListingWithVersions(pydantic.BaseModel):
"""A store listing with its version history"""
listing_id: str
slug: str
agent_id: str
agent_version: int
active_version_id: str | None = None
has_approved_version: bool = False
creator_email: str | None = None
latest_version: StoreSubmission | None = None
versions: list[StoreSubmission] = []
class StoreListingsWithVersionsResponse(pydantic.BaseModel):
"""Response model for listings with version history"""
listings: list[StoreListingWithVersions]
pagination: Pagination
class StoreSubmissionRequest(pydantic.BaseModel):
agent_id: str = pydantic.Field(
..., min_length=1, description="Agent ID cannot be empty"
graph_id: str = pydantic.Field(
..., min_length=1, description="Graph ID cannot be empty"
)
agent_version: int = pydantic.Field(
..., gt=0, description="Agent version must be greater than 0"
graph_version: int = pydantic.Field(
..., gt=0, description="Graph version must be greater than 0"
)
slug: str
name: str
@@ -198,12 +306,42 @@ class StoreSubmissionEditRequest(pydantic.BaseModel):
recommended_schedule_cron: str | None = None
class ProfileDetails(pydantic.BaseModel):
name: str
username: str
description: str
links: list[str]
avatar_url: str | None = None
class StoreSubmissionAdminView(StoreSubmission):
internal_comments: str | None # Private admin notes
@classmethod
def from_db(cls, _sub: "prisma.models.StoreSubmission") -> Self:
return cls(
**StoreSubmission.from_db(_sub).model_dump(),
internal_comments=_sub.internal_comments,
)
@classmethod
def from_listing_version(cls, _lv: "prisma.models.StoreListingVersion") -> Self:
return cls(
**StoreSubmission.from_listing_version(_lv).model_dump(),
internal_comments=_lv.internalComments,
)
class StoreListingWithVersionsAdminView(pydantic.BaseModel):
"""A store listing with its version history"""
listing_id: str
graph_id: str
slug: str
active_listing_version_id: str | None = None
has_approved_version: bool = False
creator_email: str | None = None
latest_version: StoreSubmissionAdminView | None = None
versions: list[StoreSubmissionAdminView] = []
class StoreListingsWithVersionsAdminViewResponse(pydantic.BaseModel):
"""Response model for listings with version history"""
listings: list[StoreListingWithVersionsAdminView]
pagination: Pagination
class StoreReview(pydantic.BaseModel):

View File

@@ -1,203 +0,0 @@
import datetime
import prisma.enums
from . import model as store_model
def test_pagination():
pagination = store_model.Pagination(
total_items=100, total_pages=5, current_page=2, page_size=20
)
assert pagination.total_items == 100
assert pagination.total_pages == 5
assert pagination.current_page == 2
assert pagination.page_size == 20
def test_store_agent():
agent = store_model.StoreAgent(
slug="test-agent",
agent_name="Test Agent",
agent_image="test.jpg",
creator="creator1",
creator_avatar="avatar.jpg",
sub_heading="Test subheading",
description="Test description",
runs=50,
rating=4.5,
agent_graph_id="test-graph-id",
)
assert agent.slug == "test-agent"
assert agent.agent_name == "Test Agent"
assert agent.runs == 50
assert agent.rating == 4.5
assert agent.agent_graph_id == "test-graph-id"
def test_store_agents_response():
response = store_model.StoreAgentsResponse(
agents=[
store_model.StoreAgent(
slug="test-agent",
agent_name="Test Agent",
agent_image="test.jpg",
creator="creator1",
creator_avatar="avatar.jpg",
sub_heading="Test subheading",
description="Test description",
runs=50,
rating=4.5,
agent_graph_id="test-graph-id",
)
],
pagination=store_model.Pagination(
total_items=1, total_pages=1, current_page=1, page_size=20
),
)
assert len(response.agents) == 1
assert response.pagination.total_items == 1
def test_store_agent_details():
details = store_model.StoreAgentDetails(
store_listing_version_id="version123",
slug="test-agent",
agent_name="Test Agent",
agent_video="video.mp4",
agent_output_demo="demo.mp4",
agent_image=["image1.jpg", "image2.jpg"],
creator="creator1",
creator_avatar="avatar.jpg",
sub_heading="Test subheading",
description="Test description",
categories=["cat1", "cat2"],
runs=50,
rating=4.5,
versions=["1.0", "2.0"],
agentGraphVersions=["1", "2"],
agentGraphId="test-graph-id",
last_updated=datetime.datetime.now(),
)
assert details.slug == "test-agent"
assert len(details.agent_image) == 2
assert len(details.categories) == 2
assert len(details.versions) == 2
def test_creator():
creator = store_model.Creator(
agent_rating=4.8,
agent_runs=1000,
name="Test Creator",
username="creator1",
description="Test description",
avatar_url="avatar.jpg",
num_agents=5,
is_featured=False,
)
assert creator.name == "Test Creator"
assert creator.num_agents == 5
def test_creators_response():
response = store_model.CreatorsResponse(
creators=[
store_model.Creator(
agent_rating=4.8,
agent_runs=1000,
name="Test Creator",
username="creator1",
description="Test description",
avatar_url="avatar.jpg",
num_agents=5,
is_featured=False,
)
],
pagination=store_model.Pagination(
total_items=1, total_pages=1, current_page=1, page_size=20
),
)
assert len(response.creators) == 1
assert response.pagination.total_items == 1
def test_creator_details():
details = store_model.CreatorDetails(
name="Test Creator",
username="creator1",
description="Test description",
links=["link1.com", "link2.com"],
avatar_url="avatar.jpg",
agent_rating=4.8,
agent_runs=1000,
top_categories=["cat1", "cat2"],
)
assert details.name == "Test Creator"
assert len(details.links) == 2
assert details.agent_rating == 4.8
assert len(details.top_categories) == 2
def test_store_submission():
submission = store_model.StoreSubmission(
listing_id="listing123",
agent_id="agent123",
agent_version=1,
sub_heading="Test subheading",
name="Test Agent",
slug="test-agent",
description="Test description",
image_urls=["image1.jpg", "image2.jpg"],
date_submitted=datetime.datetime(2023, 1, 1),
status=prisma.enums.SubmissionStatus.PENDING,
runs=50,
rating=4.5,
)
assert submission.name == "Test Agent"
assert len(submission.image_urls) == 2
assert submission.status == prisma.enums.SubmissionStatus.PENDING
def test_store_submissions_response():
response = store_model.StoreSubmissionsResponse(
submissions=[
store_model.StoreSubmission(
listing_id="listing123",
agent_id="agent123",
agent_version=1,
sub_heading="Test subheading",
name="Test Agent",
slug="test-agent",
description="Test description",
image_urls=["image1.jpg"],
date_submitted=datetime.datetime(2023, 1, 1),
status=prisma.enums.SubmissionStatus.PENDING,
runs=50,
rating=4.5,
)
],
pagination=store_model.Pagination(
total_items=1, total_pages=1, current_page=1, page_size=20
),
)
assert len(response.submissions) == 1
assert response.pagination.total_items == 1
def test_store_submission_request():
request = store_model.StoreSubmissionRequest(
agent_id="agent123",
agent_version=1,
slug="test-agent",
name="Test Agent",
sub_heading="Test subheading",
video_url="video.mp4",
image_urls=["image1.jpg", "image2.jpg"],
description="Test description",
categories=["cat1", "cat2"],
)
assert request.agent_id == "agent123"
assert request.agent_version == 1
assert len(request.image_urls) == 2
assert len(request.categories) == 2

View File

@@ -1,16 +1,16 @@
import logging
import tempfile
import typing
import urllib.parse
from typing import Literal
import autogpt_libs.auth
import fastapi
import fastapi.responses
import prisma.enums
from fastapi import Query, Security
from pydantic import BaseModel
import backend.data.graph
import backend.util.json
from backend.util.exceptions import NotFoundError
from backend.util.models import Pagination
from . import cache as store_cache
@@ -34,22 +34,15 @@ router = fastapi.APIRouter()
"/profile",
summary="Get user profile",
tags=["store", "private"],
dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
response_model=store_model.ProfileDetails,
dependencies=[Security(autogpt_libs.auth.requires_user)],
)
async def get_profile(
user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
):
"""
Get the profile details for the authenticated user.
Cached for 1 hour per user.
"""
user_id: str = Security(autogpt_libs.auth.get_user_id),
) -> store_model.ProfileDetails:
"""Get the profile details for the authenticated user."""
profile = await store_db.get_user_profile(user_id)
if profile is None:
return fastapi.responses.JSONResponse(
status_code=404,
content={"detail": "Profile not found"},
)
raise NotFoundError("User does not have a profile yet")
return profile
@@ -57,98 +50,17 @@ async def get_profile(
"/profile",
summary="Update user profile",
tags=["store", "private"],
dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
response_model=store_model.CreatorDetails,
dependencies=[Security(autogpt_libs.auth.requires_user)],
)
async def update_or_create_profile(
profile: store_model.Profile,
user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
):
"""
Update the store profile for the authenticated user.
Args:
profile (Profile): The updated profile details
user_id (str): ID of the authenticated user
Returns:
CreatorDetails: The updated profile
Raises:
HTTPException: If there is an error updating the profile
"""
user_id: str = Security(autogpt_libs.auth.get_user_id),
) -> store_model.ProfileDetails:
"""Update the store profile for the authenticated user."""
updated_profile = await store_db.update_profile(user_id=user_id, profile=profile)
return updated_profile
##############################################
############### Agent Endpoints ##############
##############################################
@router.get(
"/agents",
summary="List store agents",
tags=["store", "public"],
response_model=store_model.StoreAgentsResponse,
)
async def get_agents(
featured: bool = False,
creator: str | None = None,
sorted_by: Literal["rating", "runs", "name", "updated_at"] | None = None,
search_query: str | None = None,
category: str | None = None,
page: int = 1,
page_size: int = 20,
):
"""
Get a paginated list of agents from the store with optional filtering and sorting.
Args:
featured (bool, optional): Filter to only show featured agents. Defaults to False.
creator (str | None, optional): Filter agents by creator username. Defaults to None.
sorted_by (str | None, optional): Sort agents by "runs" or "rating". Defaults to None.
search_query (str | None, optional): Search agents by name, subheading and description. Defaults to None.
category (str | None, optional): Filter agents by category. Defaults to None.
page (int, optional): Page number for pagination. Defaults to 1.
page_size (int, optional): Number of agents per page. Defaults to 20.
Returns:
StoreAgentsResponse: Paginated list of agents matching the filters
Raises:
HTTPException: If page or page_size are less than 1
Used for:
- Home Page Featured Agents
- Home Page Top Agents
- Search Results
- Agent Details - Other Agents By Creator
- Agent Details - Similar Agents
- Creator Details - Agents By Creator
"""
if page < 1:
raise fastapi.HTTPException(
status_code=422, detail="Page must be greater than 0"
)
if page_size < 1:
raise fastapi.HTTPException(
status_code=422, detail="Page size must be greater than 0"
)
agents = await store_cache._get_cached_store_agents(
featured=featured,
creator=creator,
sorted_by=sorted_by,
search_query=search_query,
category=category,
page=page,
page_size=page_size,
)
return agents
##############################################
############### Search Endpoints #############
##############################################
@@ -158,60 +70,30 @@ async def get_agents(
"/search",
summary="Unified search across all content types",
tags=["store", "public"],
response_model=store_model.UnifiedSearchResponse,
)
async def unified_search(
query: str,
content_types: list[str] | None = fastapi.Query(
content_types: list[prisma.enums.ContentType] | None = Query(
default=None,
description="Content types to search: STORE_AGENT, BLOCK, DOCUMENTATION. If not specified, searches all.",
description="Content types to search. If not specified, searches all.",
),
page: int = 1,
page_size: int = 20,
user_id: str | None = fastapi.Security(
page: int = Query(ge=1, default=1),
page_size: int = Query(ge=1, default=20),
user_id: str | None = Security(
autogpt_libs.auth.get_optional_user_id, use_cache=False
),
):
) -> store_model.UnifiedSearchResponse:
"""
Search across all content types (store agents, blocks, documentation) using hybrid search.
Search across all content types (marketplace agents, blocks, documentation)
using hybrid search.
Combines semantic (embedding-based) and lexical (text-based) search for best results.
Args:
query: The search query string
content_types: Optional list of content types to filter by (STORE_AGENT, BLOCK, DOCUMENTATION)
page: Page number for pagination (default 1)
page_size: Number of results per page (default 20)
user_id: Optional authenticated user ID (for user-scoped content in future)
Returns:
UnifiedSearchResponse: Paginated list of search results with relevance scores
"""
if page < 1:
raise fastapi.HTTPException(
status_code=422, detail="Page must be greater than 0"
)
if page_size < 1:
raise fastapi.HTTPException(
status_code=422, detail="Page size must be greater than 0"
)
# Convert string content types to enum
content_type_enums: list[prisma.enums.ContentType] | None = None
if content_types:
try:
content_type_enums = [prisma.enums.ContentType(ct) for ct in content_types]
except ValueError as e:
raise fastapi.HTTPException(
status_code=422,
detail=f"Invalid content type. Valid values: STORE_AGENT, BLOCK, DOCUMENTATION. Error: {e}",
)
# Perform unified hybrid search
results, total = await store_hybrid_search.unified_hybrid_search(
query=query,
content_types=content_type_enums,
content_types=content_types,
user_id=user_id,
page=page,
page_size=page_size,
@@ -245,22 +127,69 @@ async def unified_search(
)
##############################################
############### Agent Endpoints ##############
##############################################
@router.get(
"/agents",
summary="List store agents",
tags=["store", "public"],
)
async def get_agents(
featured: bool = Query(
default=False, description="Filter to only show featured agents"
),
creator: str | None = Query(
default=None, description="Filter agents by creator username"
),
category: str | None = Query(default=None, description="Filter agents by category"),
search_query: str | None = Query(
default=None, description="Literal + semantic search on names and descriptions"
),
sorted_by: store_db.StoreAgentsSortOptions | None = Query(
default=None,
description="Property to sort results by. Ignored if search_query is provided.",
),
page: int = Query(ge=1, default=1),
page_size: int = Query(ge=1, default=20),
) -> store_model.StoreAgentsResponse:
"""
Get a paginated list of agents from the marketplace,
with optional filtering and sorting.
Used for:
- Home Page Featured Agents
- Home Page Top Agents
- Search Results
- Agent Details - Other Agents By Creator
- Agent Details - Similar Agents
- Creator Details - Agents By Creator
"""
agents = await store_cache._get_cached_store_agents(
featured=featured,
creator=creator,
sorted_by=sorted_by,
search_query=search_query,
category=category,
page=page,
page_size=page_size,
)
return agents
@router.get(
"/agents/{username}/{agent_name}",
summary="Get specific agent",
tags=["store", "public"],
response_model=store_model.StoreAgentDetails,
)
async def get_agent(
async def get_agent_by_name(
username: str,
agent_name: str,
include_changelog: bool = fastapi.Query(default=False),
):
"""
This is only used on the AgentDetails Page.
It returns the store listing agents details.
"""
include_changelog: bool = Query(default=False),
) -> store_model.StoreAgentDetails:
"""Get details of a marketplace agent"""
username = urllib.parse.unquote(username).lower()
# URL decode the agent name since it comes from the URL path
agent_name = urllib.parse.unquote(agent_name).lower()
@@ -270,76 +199,79 @@ async def get_agent(
return agent
@router.get(
"/graph/{store_listing_version_id}",
summary="Get agent graph",
tags=["store"],
dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
)
async def get_graph_meta_by_store_listing_version_id(
store_listing_version_id: str,
) -> backend.data.graph.GraphModelWithoutNodes:
"""
Get Agent Graph from Store Listing Version ID.
"""
graph = await store_db.get_available_graph(store_listing_version_id)
return graph
@router.get(
"/agents/{store_listing_version_id}",
summary="Get agent by version",
tags=["store"],
dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
response_model=store_model.StoreAgentDetails,
)
async def get_store_agent(store_listing_version_id: str):
"""
Get Store Agent Details from Store Listing Version ID.
"""
agent = await store_db.get_store_agent_by_version_id(store_listing_version_id)
return agent
@router.post(
"/agents/{username}/{agent_name}/review",
summary="Create agent review",
tags=["store"],
dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
response_model=store_model.StoreReview,
dependencies=[Security(autogpt_libs.auth.requires_user)],
)
async def create_review(
async def post_user_review_for_agent(
username: str,
agent_name: str,
review: store_model.StoreReviewCreate,
user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
):
"""
Create a review for a store agent.
Args:
username: Creator's username
agent_name: Name/slug of the agent
review: Review details including score and optional comments
user_id: ID of authenticated user creating the review
Returns:
The created review
"""
user_id: str = Security(autogpt_libs.auth.get_user_id),
) -> store_model.StoreReview:
"""Post a user review on a marketplace agent listing"""
username = urllib.parse.unquote(username).lower()
agent_name = urllib.parse.unquote(agent_name).lower()
# Create the review
created_review = await store_db.create_store_review(
user_id=user_id,
store_listing_version_id=review.store_listing_version_id,
score=review.score,
comments=review.comments,
)
return created_review
@router.get(
"/listings/versions/{store_listing_version_id}",
summary="Get agent by version",
tags=["store"],
dependencies=[Security(autogpt_libs.auth.requires_user)],
)
async def get_agent_by_listing_version(
store_listing_version_id: str,
) -> store_model.StoreAgentDetails:
agent = await store_db.get_store_agent_by_version_id(store_listing_version_id)
return agent
@router.get(
"/listings/versions/{store_listing_version_id}/graph",
summary="Get agent graph",
tags=["store"],
dependencies=[Security(autogpt_libs.auth.requires_user)],
)
async def get_graph_meta_by_store_listing_version_id(
store_listing_version_id: str,
) -> backend.data.graph.GraphModelWithoutNodes:
"""Get outline of graph belonging to a specific marketplace listing version"""
graph = await store_db.get_available_graph(store_listing_version_id)
return graph
@router.get(
"/listings/versions/{store_listing_version_id}/graph/download",
summary="Download agent file",
tags=["store", "public"],
)
async def download_agent_file(
store_listing_version_id: str,
) -> fastapi.responses.Response:
"""Download agent graph file for a specific marketplace listing version"""
graph_data = await store_db.get_agent(store_listing_version_id)
file_name = f"agent_{graph_data.id}_v{graph_data.version or 'latest'}.json"
return fastapi.responses.Response(
content=backend.util.json.dumps(graph_data),
media_type="application/json",
headers={
"Content-Disposition": f'attachment; filename="{file_name}"',
},
)
##############################################
############# Creator Endpoints #############
##############################################
@@ -349,37 +281,19 @@ async def create_review(
"/creators",
summary="List store creators",
tags=["store", "public"],
response_model=store_model.CreatorsResponse,
)
async def get_creators(
featured: bool = False,
search_query: str | None = None,
sorted_by: Literal["agent_rating", "agent_runs", "num_agents"] | None = None,
page: int = 1,
page_size: int = 20,
):
"""
This is needed for:
- Home Page Featured Creators
- Search Results Page
---
To support this functionality we need:
- featured: bool - to limit the list to just featured agents
- search_query: str - vector search based on the creators profile description.
- sorted_by: [agent_rating, agent_runs] -
"""
if page < 1:
raise fastapi.HTTPException(
status_code=422, detail="Page must be greater than 0"
)
if page_size < 1:
raise fastapi.HTTPException(
status_code=422, detail="Page size must be greater than 0"
)
featured: bool = Query(
default=False, description="Filter to only show featured creators"
),
search_query: str | None = Query(
default=None, description="Literal + semantic search on names and descriptions"
),
sorted_by: store_db.StoreCreatorsSortOptions | None = None,
page: int = Query(ge=1, default=1),
page_size: int = Query(ge=1, default=20),
) -> store_model.CreatorsResponse:
"""List or search marketplace creators"""
creators = await store_cache._get_cached_store_creators(
featured=featured,
search_query=search_query,
@@ -391,18 +305,12 @@ async def get_creators(
@router.get(
"/creator/{username}",
"/creators/{username}",
summary="Get creator details",
tags=["store", "public"],
response_model=store_model.CreatorDetails,
)
async def get_creator(
username: str,
):
"""
Get the details of a creator.
- Creator Details Page
"""
async def get_creator(username: str) -> store_model.CreatorDetails:
"""Get details on a marketplace creator"""
username = urllib.parse.unquote(username).lower()
creator = await store_cache._get_cached_creator_details(username=username)
return creator
@@ -414,20 +322,17 @@ async def get_creator(
@router.get(
"/myagents",
"/my-unpublished-agents",
summary="Get my agents",
tags=["store", "private"],
dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
response_model=store_model.MyAgentsResponse,
dependencies=[Security(autogpt_libs.auth.requires_user)],
)
async def get_my_agents(
user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
page: typing.Annotated[int, fastapi.Query(ge=1)] = 1,
page_size: typing.Annotated[int, fastapi.Query(ge=1)] = 20,
):
"""
Get user's own agents.
"""
async def get_my_unpublished_agents(
user_id: str = Security(autogpt_libs.auth.get_user_id),
page: int = Query(ge=1, default=1),
page_size: int = Query(ge=1, default=20),
) -> store_model.MyUnpublishedAgentsResponse:
"""List the authenticated user's unpublished agents"""
agents = await store_db.get_my_agents(user_id, page=page, page_size=page_size)
return agents
@@ -436,28 +341,17 @@ async def get_my_agents(
"/submissions/{submission_id}",
summary="Delete store submission",
tags=["store", "private"],
dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
response_model=bool,
dependencies=[Security(autogpt_libs.auth.requires_user)],
)
async def delete_submission(
submission_id: str,
user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
):
"""
Delete a store listing submission.
Args:
user_id (str): ID of the authenticated user
submission_id (str): ID of the submission to be deleted
Returns:
bool: True if the submission was successfully deleted, False otherwise
"""
user_id: str = Security(autogpt_libs.auth.get_user_id),
) -> bool:
"""Delete a marketplace listing submission"""
result = await store_db.delete_store_submission(
user_id=user_id,
submission_id=submission_id,
)
return result
@@ -465,37 +359,14 @@ async def delete_submission(
"/submissions",
summary="List my submissions",
tags=["store", "private"],
dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
response_model=store_model.StoreSubmissionsResponse,
dependencies=[Security(autogpt_libs.auth.requires_user)],
)
async def get_submissions(
user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
page: int = 1,
page_size: int = 20,
):
"""
Get a paginated list of store submissions for the authenticated user.
Args:
user_id (str): ID of the authenticated user
page (int, optional): Page number for pagination. Defaults to 1.
page_size (int, optional): Number of submissions per page. Defaults to 20.
Returns:
StoreListingsResponse: Paginated list of store submissions
Raises:
HTTPException: If page or page_size are less than 1
"""
if page < 1:
raise fastapi.HTTPException(
status_code=422, detail="Page must be greater than 0"
)
if page_size < 1:
raise fastapi.HTTPException(
status_code=422, detail="Page size must be greater than 0"
)
user_id: str = Security(autogpt_libs.auth.get_user_id),
page: int = Query(ge=1, default=1),
page_size: int = Query(ge=1, default=20),
) -> store_model.StoreSubmissionsResponse:
"""List the authenticated user's marketplace listing submissions"""
listings = await store_db.get_store_submissions(
user_id=user_id,
page=page,
@@ -508,30 +379,17 @@ async def get_submissions(
"/submissions",
summary="Create store submission",
tags=["store", "private"],
dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
response_model=store_model.StoreSubmission,
dependencies=[Security(autogpt_libs.auth.requires_user)],
)
async def create_submission(
submission_request: store_model.StoreSubmissionRequest,
user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
):
"""
Create a new store listing submission.
Args:
submission_request (StoreSubmissionRequest): The submission details
user_id (str): ID of the authenticated user submitting the listing
Returns:
StoreSubmission: The created store submission
Raises:
HTTPException: If there is an error creating the submission
"""
user_id: str = Security(autogpt_libs.auth.get_user_id),
) -> store_model.StoreSubmission:
"""Submit a new marketplace listing for review"""
result = await store_db.create_store_submission(
user_id=user_id,
agent_id=submission_request.agent_id,
agent_version=submission_request.agent_version,
graph_id=submission_request.graph_id,
graph_version=submission_request.graph_version,
slug=submission_request.slug,
name=submission_request.name,
video_url=submission_request.video_url,
@@ -544,7 +402,6 @@ async def create_submission(
changes_summary=submission_request.changes_summary or "Initial Submission",
recommended_schedule_cron=submission_request.recommended_schedule_cron,
)
return result
@@ -552,28 +409,14 @@ async def create_submission(
"/submissions/{store_listing_version_id}",
summary="Edit store submission",
tags=["store", "private"],
dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
response_model=store_model.StoreSubmission,
dependencies=[Security(autogpt_libs.auth.requires_user)],
)
async def edit_submission(
store_listing_version_id: str,
submission_request: store_model.StoreSubmissionEditRequest,
user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
):
"""
Edit an existing store listing submission.
Args:
store_listing_version_id (str): ID of the store listing version to edit
submission_request (StoreSubmissionRequest): The updated submission details
user_id (str): ID of the authenticated user editing the listing
Returns:
StoreSubmission: The updated store submission
Raises:
HTTPException: If there is an error editing the submission
"""
user_id: str = Security(autogpt_libs.auth.get_user_id),
) -> store_model.StoreSubmission:
"""Update a pending marketplace listing submission"""
result = await store_db.edit_store_submission(
user_id=user_id,
store_listing_version_id=store_listing_version_id,
@@ -588,7 +431,6 @@ async def edit_submission(
changes_summary=submission_request.changes_summary,
recommended_schedule_cron=submission_request.recommended_schedule_cron,
)
return result
@@ -596,115 +438,61 @@ async def edit_submission(
"/submissions/media",
summary="Upload submission media",
tags=["store", "private"],
dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
dependencies=[Security(autogpt_libs.auth.requires_user)],
)
async def upload_submission_media(
file: fastapi.UploadFile,
user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
):
"""
Upload media (images/videos) for a store listing submission.
Args:
file (UploadFile): The media file to upload
user_id (str): ID of the authenticated user uploading the media
Returns:
str: URL of the uploaded media file
Raises:
HTTPException: If there is an error uploading the media
"""
user_id: str = Security(autogpt_libs.auth.get_user_id),
) -> str:
"""Upload media for a marketplace listing submission"""
media_url = await store_media.upload_media(user_id=user_id, file=file)
return media_url
class ImageURLResponse(BaseModel):
image_url: str
@router.post(
"/submissions/generate_image",
summary="Generate submission image",
tags=["store", "private"],
dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
dependencies=[Security(autogpt_libs.auth.requires_user)],
)
async def generate_image(
agent_id: str,
user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
) -> fastapi.responses.Response:
graph_id: str,
user_id: str = Security(autogpt_libs.auth.get_user_id),
) -> ImageURLResponse:
"""
Generate an image for a store listing submission.
Args:
agent_id (str): ID of the agent to generate an image for
user_id (str): ID of the authenticated user
Returns:
JSONResponse: JSON containing the URL of the generated image
Generate an image for a marketplace listing submission based on the properties
of a given graph.
"""
agent = await backend.data.graph.get_graph(
graph_id=agent_id, version=None, user_id=user_id
graph = await backend.data.graph.get_graph(
graph_id=graph_id, version=None, user_id=user_id
)
if not agent:
raise fastapi.HTTPException(
status_code=404, detail=f"Agent with ID {agent_id} not found"
)
if not graph:
raise NotFoundError(f"Agent graph #{graph_id} not found")
# Use .jpeg here since we are generating JPEG images
filename = f"agent_{agent_id}.jpeg"
filename = f"agent_{graph_id}.jpeg"
existing_url = await store_media.check_media_exists(user_id, filename)
if existing_url:
logger.info(f"Using existing image for agent {agent_id}")
return fastapi.responses.JSONResponse(content={"image_url": existing_url})
logger.info(f"Using existing image for agent graph {graph_id}")
return ImageURLResponse(image_url=existing_url)
# Generate agent image as JPEG
image = await store_image_gen.generate_agent_image(agent=agent)
image = await store_image_gen.generate_agent_image(agent=graph)
# Create UploadFile with the correct filename and content_type
image_file = fastapi.UploadFile(
file=image,
filename=filename,
)
image_url = await store_media.upload_media(
user_id=user_id, file=image_file, use_file_name=True
)
return fastapi.responses.JSONResponse(content={"image_url": image_url})
@router.get(
"/download/agents/{store_listing_version_id}",
summary="Download agent file",
tags=["store", "public"],
)
async def download_agent_file(
store_listing_version_id: str = fastapi.Path(
..., description="The ID of the agent to download"
),
) -> fastapi.responses.FileResponse:
"""
Download the agent file by streaming its content.
Args:
store_listing_version_id (str): The ID of the agent to download
Returns:
StreamingResponse: A streaming response containing the agent's graph data.
Raises:
HTTPException: If the agent is not found or an unexpected error occurs.
"""
graph_data = await store_db.get_agent(store_listing_version_id)
file_name = f"agent_{graph_data.id}_v{graph_data.version or 'latest'}.json"
# Sending graph as a stream (similar to marketplace v1)
with tempfile.NamedTemporaryFile(
mode="w", suffix=".json", delete=False
) as tmp_file:
tmp_file.write(backend.util.json.dumps(graph_data))
tmp_file.flush()
return fastapi.responses.FileResponse(
tmp_file.name, filename=file_name, media_type="application/json"
)
return ImageURLResponse(image_url=image_url)
##############################################

View File

@@ -8,6 +8,8 @@ import pytest
import pytest_mock
from pytest_snapshot.plugin import Snapshot
from backend.api.features.store.db import StoreAgentsSortOptions
from . import model as store_model
from . import routes as store_routes
@@ -196,7 +198,7 @@ def test_get_agents_sorted(
mock_db_call.assert_called_once_with(
featured=False,
creators=None,
sorted_by="runs",
sorted_by=StoreAgentsSortOptions.RUNS,
search_query=None,
category=None,
page=1,
@@ -380,9 +382,11 @@ def test_get_agent_details(
runs=100,
rating=4.5,
versions=["1.0.0", "1.1.0"],
agentGraphVersions=["1", "2"],
agentGraphId="test-graph-id",
graph_versions=["1", "2"],
graph_id="test-graph-id",
last_updated=FIXED_NOW,
active_version_id="test-version-id",
has_approved_version=True,
)
mock_db_call = mocker.patch("backend.api.features.store.db.get_store_agent_details")
mock_db_call.return_value = mocked_value
@@ -435,15 +439,17 @@ def test_get_creators_pagination(
) -> None:
mocked_value = store_model.CreatorsResponse(
creators=[
store_model.Creator(
store_model.CreatorDetails(
name=f"Creator {i}",
username=f"creator{i}",
description=f"Creator {i} description",
avatar_url=f"avatar{i}.jpg",
num_agents=1,
agent_rating=4.5,
agent_runs=100,
description=f"Creator {i} description",
links=[f"user{i}.link.com"],
is_featured=False,
num_agents=1,
agent_runs=100,
agent_rating=4.5,
top_categories=["cat1", "cat2", "cat3"],
)
for i in range(5)
],
@@ -496,19 +502,19 @@ def test_get_creator_details(
mocked_value = store_model.CreatorDetails(
name="Test User",
username="creator1",
avatar_url="avatar.jpg",
description="Test creator description",
links=["link1.com", "link2.com"],
avatar_url="avatar.jpg",
agent_rating=4.8,
is_featured=True,
num_agents=5,
agent_runs=1000,
agent_rating=4.8,
top_categories=["category1", "category2"],
)
mock_db_call = mocker.patch(
"backend.api.features.store.db.get_store_creator_details"
)
mock_db_call = mocker.patch("backend.api.features.store.db.get_store_creator")
mock_db_call.return_value = mocked_value
response = client.get("/creator/creator1")
response = client.get("/creators/creator1")
assert response.status_code == 200
data = store_model.CreatorDetails.model_validate(response.json())
@@ -528,19 +534,26 @@ def test_get_submissions_success(
submissions=[
store_model.StoreSubmission(
listing_id="test-listing-id",
name="Test Agent",
description="Test agent description",
image_urls=["test.jpg"],
date_submitted=FIXED_NOW,
status=prisma.enums.SubmissionStatus.APPROVED,
runs=50,
rating=4.2,
agent_id="test-agent-id",
agent_version=1,
sub_heading="Test agent subheading",
user_id="test-user-id",
slug="test-agent",
video_url="test.mp4",
listing_version_id="test-version-id",
listing_version=1,
graph_id="test-agent-id",
graph_version=1,
name="Test Agent",
sub_heading="Test agent subheading",
description="Test agent description",
instructions="Click the button!",
categories=["test-category"],
image_urls=["test.jpg"],
video_url="test.mp4",
agent_output_demo_url="demo_video.mp4",
submitted_at=FIXED_NOW,
changes_summary="Initial Submission",
status=prisma.enums.SubmissionStatus.APPROVED,
run_count=50,
review_count=5,
review_avg_rating=4.2,
)
],
pagination=store_model.Pagination(

View File

@@ -11,6 +11,7 @@ import pytest
from backend.util.models import Pagination
from . import cache as store_cache
from .db import StoreAgentsSortOptions
from .model import StoreAgent, StoreAgentsResponse
@@ -215,7 +216,7 @@ class TestCacheDeletion:
await store_cache._get_cached_store_agents(
featured=True,
creator="testuser",
sorted_by="rating",
sorted_by=StoreAgentsSortOptions.RATING,
search_query="AI assistant",
category="productivity",
page=2,
@@ -227,7 +228,7 @@ class TestCacheDeletion:
deleted = store_cache._get_cached_store_agents.cache_delete(
featured=True,
creator="testuser",
sorted_by="rating",
sorted_by=StoreAgentsSortOptions.RATING,
search_query="AI assistant",
category="productivity",
page=2,
@@ -239,7 +240,7 @@ class TestCacheDeletion:
deleted = store_cache._get_cached_store_agents.cache_delete(
featured=True,
creator="testuser",
sorted_by="rating",
sorted_by=StoreAgentsSortOptions.RATING,
search_query="AI assistant",
category="productivity",
page=2,

View File

@@ -0,0 +1,5 @@
"""Backward-compatibility shim — ``split_camelcase`` now lives in backend.util.text."""
from backend.util.text import split_camelcase # noqa: F401
__all__ = ["split_camelcase"]

View File

@@ -0,0 +1,49 @@
"""Tests for split_camelcase (now in backend.util.text)."""
import pytest
from backend.util.text import split_camelcase
# ---------------------------------------------------------------------------
# split_camelcase
# ---------------------------------------------------------------------------
@pytest.mark.parametrize(
"input_text, expected",
[
("AITextGeneratorBlock", "AI Text Generator Block"),
("HTTPRequestBlock", "HTTP Request Block"),
("simpleWord", "simple Word"),
("already spaced", "already spaced"),
("XMLParser", "XML Parser"),
("getHTTPResponse", "get HTTP Response"),
("Block", "Block"),
("", ""),
("OAuth2Block", "OAuth2 Block"),
("IOError", "IO Error"),
("getHTTPSResponse", "get HTTPS Response"),
# Known limitation: single-letter uppercase prefixes are NOT split.
# "ABlock" stays "ABlock" because the algorithm requires the left
# part of an uppercase run to retain at least 2 uppercase chars.
("ABlock", "ABlock"),
# Digit-to-uppercase transitions
("Base64Encoder", "Base64 Encoder"),
("UTF8Decoder", "UTF8 Decoder"),
# Pure digits — no camelCase boundaries to split
("123", "123"),
# Known limitation: single-letter uppercase segments after digits
# are not split from the following word. "3D" is only 1 uppercase
# char so the uppercase-run rule cannot fire, producing "3 DRenderer"
# rather than the ideal "3D Renderer".
("3DRenderer", "3 DRenderer"),
# Exception list — compound terms that should stay together
("YouTubeBlock", "YouTube Block"),
("OpenAIBlock", "OpenAI Block"),
("AutoGPTAgent", "AutoGPT Agent"),
("GitHubIntegration", "GitHub Integration"),
("LinkedInBlock", "LinkedIn Block"),
],
)
def test_split_camelcase(input_text: str, expected: str):
assert split_camelcase(input_text) == expected

View File

@@ -63,12 +63,17 @@ 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,
@@ -282,35 +287,33 @@ 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 +328,38 @@ 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 ###########################
########################################################
@@ -449,7 +484,6 @@ async def execute_graph_block(
async def upload_file(
user_id: Annotated[str, Security(get_user_id)],
file: UploadFile = File(...),
provider: str = "gcs",
expiration_hours: int = 24,
) -> UploadFileResponse:
"""
@@ -512,7 +546,6 @@ async def upload_file(
storage_path = await cloud_storage.store_file(
content=content,
filename=file_name,
provider=provider,
expiration_hours=expiration_hours,
user_id=user_id,
)
@@ -594,6 +627,11 @@ async def fulfill_checkout(user_id: Annotated[str, Security(get_user_id)]):
async def configure_user_auto_top_up(
request: AutoTopUpConfig, user_id: Annotated[str, Security(get_user_id)]
) -> str:
"""Configure auto top-up settings and perform an immediate top-up if needed.
Raises HTTPException(422) if the request parameters are invalid or if
the credit top-up fails.
"""
if request.threshold < 0:
raise HTTPException(status_code=422, detail="Threshold must be greater than 0")
if request.amount < 500 and request.amount != 0:
@@ -608,10 +646,20 @@ async def configure_user_auto_top_up(
user_credit_model = await get_user_credit_model(user_id)
current_balance = await user_credit_model.get_credits(user_id)
if current_balance < request.threshold:
await user_credit_model.top_up_credits(user_id, request.amount)
else:
await user_credit_model.top_up_credits(user_id, 0)
try:
if current_balance < request.threshold:
await user_credit_model.top_up_credits(user_id, request.amount)
else:
await user_credit_model.top_up_credits(user_id, 0)
except ValueError as e:
known_messages = (
"must not be negative",
"already exists for user",
"No payment method found",
)
if any(msg in str(e) for msg in known_messages):
raise HTTPException(status_code=422, detail=str(e))
raise
await set_auto_top_up(
user_id, AutoTopUpConfig(threshold=request.threshold, amount=request.amount)
@@ -967,14 +1015,16 @@ async def execute_graph(
source: Annotated[GraphExecutionSource | None, Body(embed=True)] = None,
graph_version: Optional[int] = None,
preset_id: Optional[str] = None,
dry_run: Annotated[bool, Body(embed=True)] = False,
) -> execution_db.GraphExecutionMeta:
user_credit_model = await get_user_credit_model(user_id)
current_balance = await user_credit_model.get_credits(user_id)
if current_balance <= 0:
raise HTTPException(
status_code=402,
detail="Insufficient balance to execute the agent. Please top up your account.",
)
if not dry_run:
user_credit_model = await get_user_credit_model(user_id)
current_balance = await user_credit_model.get_credits(user_id)
if current_balance <= 0:
raise HTTPException(
status_code=402,
detail="Insufficient balance to execute the agent. Please top up your account.",
)
try:
result = await execution_utils.add_graph_execution(
@@ -984,6 +1034,7 @@ async def execute_graph(
preset_id=preset_id,
graph_version=graph_version,
graph_credentials_inputs=credentials_inputs,
dry_run=dry_run,
)
# Record successful graph execution
record_graph_execution(graph_id=graph_id, status="success", user_id=user_id)

View File

@@ -515,7 +515,6 @@ async def test_upload_file_success(test_user_id: str):
result = await upload_file(
file=upload_file_mock,
user_id=test_user_id,
provider="gcs",
expiration_hours=24,
)
@@ -533,7 +532,6 @@ async def test_upload_file_success(test_user_id: str):
mock_handler.store_file.assert_called_once_with(
content=file_content,
filename="test.txt",
provider="gcs",
expiration_hours=24,
user_id=test_user_id,
)

View File

@@ -3,15 +3,29 @@ Workspace API routes for managing user file storage.
"""
import logging
import os
import re
from typing import Annotated
from urllib.parse import quote
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, Field
from backend.data.workspace import WorkspaceFile, get_workspace, get_workspace_file
from backend.data.workspace import (
WorkspaceFile,
count_workspace_files,
get_or_create_workspace,
get_workspace,
get_workspace_file,
get_workspace_total_size,
soft_delete_workspace_file,
)
from backend.util.settings import Config
from backend.util.virus_scanner import scan_content_safe
from backend.util.workspace import WorkspaceManager
from backend.util.workspace_storage import get_workspace_storage
@@ -98,9 +112,45 @@ async def _create_file_download_response(file: WorkspaceFile) -> Response:
raise
class UploadFileResponse(BaseModel):
file_id: str
name: str
path: str
mime_type: str
size_bytes: int
class DeleteFileResponse(BaseModel):
deleted: bool
class StorageUsageResponse(BaseModel):
used_bytes: int
limit_bytes: int
used_percent: float
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)],
@@ -120,3 +170,222 @@ async def download_file(
raise fastapi.HTTPException(status_code=404, detail="File not found")
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)],
file_id: str,
) -> DeleteFileResponse:
"""
Soft-delete a workspace file and attempt to remove it from storage.
Used when a user clears a file input in the builder.
"""
workspace = await get_workspace(user_id)
if workspace is None:
raise fastapi.HTTPException(status_code=404, detail="Workspace not found")
manager = WorkspaceManager(user_id, workspace.id)
deleted = await manager.delete_file(file_id)
if not deleted:
raise fastapi.HTTPException(status_code=404, detail="File not found")
return DeleteFileResponse(deleted=True)
@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)],
file: UploadFile,
session_id: str | None = Query(default=None),
overwrite: bool = Query(default=False),
) -> UploadFileResponse:
"""
Upload a file to the user's workspace.
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
filename = os.path.basename(file.filename or "upload") or "upload"
# Read file content with early abort on size limit
max_file_bytes = config.max_file_size_mb * 1024 * 1024
chunks: list[bytes] = []
total_size = 0
while chunk := await file.read(64 * 1024): # 64KB chunks
total_size += len(chunk)
if total_size > max_file_bytes:
raise fastapi.HTTPException(
status_code=413,
detail=f"File exceeds maximum size of {config.max_file_size_mb} MB",
)
chunks.append(chunk)
content = b"".join(chunks)
# Get or create workspace
workspace = await get_or_create_workspace(user_id)
# Pre-write storage cap check (soft check — final enforcement is post-write)
storage_limit_bytes = config.max_workspace_storage_mb * 1024 * 1024
current_usage = await get_workspace_total_size(workspace.id)
if storage_limit_bytes and current_usage + len(content) > storage_limit_bytes:
used_percent = (current_usage / storage_limit_bytes) * 100
raise fastapi.HTTPException(
status_code=413,
detail={
"message": "Storage limit exceeded",
"used_bytes": current_usage,
"limit_bytes": storage_limit_bytes,
"used_percent": round(used_percent, 1),
},
)
# Warn at 80% usage
if (
storage_limit_bytes
and (usage_ratio := (current_usage + len(content)) / storage_limit_bytes) >= 0.8
):
logger.warning(
f"User {user_id} workspace storage at {usage_ratio * 100:.1f}% "
f"({current_usage + len(content)} / {storage_limit_bytes} bytes)"
)
# Virus scan
await scan_content_safe(content, filename=filename)
# Write file via WorkspaceManager
manager = WorkspaceManager(user_id, workspace.id, session_id)
try:
workspace_file = await manager.write_file(
content, filename, overwrite=overwrite, metadata={"origin": "user-upload"}
)
except ValueError as 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:
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={
"message": "Storage limit exceeded (concurrent upload)",
"used_bytes": new_total,
"limit_bytes": storage_limit_bytes,
},
)
return UploadFileResponse(
file_id=workspace_file.id,
name=workspace_file.name,
path=workspace_file.path,
mime_type=workspace_file.mime_type,
size_bytes=workspace_file.size_bytes,
)
@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)],
) -> StorageUsageResponse:
"""
Get storage usage information for the user's workspace.
"""
config = Config()
workspace = await get_or_create_workspace(user_id)
used_bytes = await get_workspace_total_size(workspace.id)
file_count = await count_workspace_files(workspace.id)
limit_bytes = config.max_workspace_storage_mb * 1024 * 1024
return StorageUsageResponse(
used_bytes=used_bytes,
limit_bytes=limit_bytes,
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

@@ -0,0 +1,602 @@
import io
from datetime import datetime, timezone
from unittest.mock import AsyncMock, MagicMock, patch
import fastapi
import fastapi.testclient
import pytest
from backend.api.features.workspace.routes import router
from backend.data.workspace import Workspace, WorkspaceFile
app = fastapi.FastAPI()
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 the REST app."""
return fastapi.responses.JSONResponse(status_code=400, content={"detail": str(exc)})
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 _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",
):
return client.post(
"/files/upload?session_id=sess-1",
files={"file": (filename, io.BytesIO(content), content_type)},
)
_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):
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(return_value=_MOCK_FILE)
mocker.patch(
"backend.api.features.workspace.routes.WorkspaceManager",
return_value=mock_manager,
)
response = _upload()
assert response.status_code == 200
data = response.json()
assert data["file_id"] == "file-aaa-bbb"
assert data["name"] == "hello.txt"
assert data["size_bytes"] == 13
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
cfg.return_value.max_workspace_storage_mb = 500
response = _upload(content=b"x" * 1024)
assert response.status_code == 413
def test_upload_storage_quota_exceeded(mocker):
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=500 * 1024 * 1024,
)
response = _upload()
assert response.status_code == 413
assert "Storage limit exceeded" in response.text
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=_make_workspace(),
)
mocker.patch(
"backend.api.features.workspace.routes.get_workspace_total_size",
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)
mocker.patch(
"backend.api.features.workspace.routes.WorkspaceManager",
return_value=mock_manager,
)
mock_delete = mocker.patch(
"backend.api.features.workspace.routes.soft_delete_workspace_file",
return_value=None,
)
response = _upload()
assert response.status_code == 413
mock_delete.assert_called_once_with("file-aaa-bbb", "ws-001")
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=_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(return_value=_MOCK_FILE)
mocker.patch(
"backend.api.features.workspace.routes.WorkspaceManager",
return_value=mock_manager,
)
response = _upload(filename="data.xyz", content=b"arbitrary")
assert response.status_code == 200
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=_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",
side_effect=VirusDetectedError("Eicar-Test-Signature"),
)
mock_manager = mocker.MagicMock()
mock_manager.write_file = mocker.AsyncMock(return_value=_MOCK_FILE)
mocker.patch(
"backend.api.features.workspace.routes.WorkspaceManager",
return_value=mock_manager,
)
response = _upload(filename="evil.exe", content=b"X5O!P%@AP...")
assert response.status_code == 400
mock_manager.write_file.assert_not_called()
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=_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(return_value=_MOCK_FILE)
mocker.patch(
"backend.api.features.workspace.routes.WorkspaceManager",
return_value=mock_manager,
)
response = _upload(
filename="Makefile",
content=b"all:\n\techo hello",
content_type="application/octet-stream",
)
assert response.status_code == 200
mock_manager.write_file.assert_called_once()
assert mock_manager.write_file.call_args[0][1] == "Makefile"
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=_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(return_value=_MOCK_FILE)
mocker.patch(
"backend.api.features.workspace.routes.WorkspaceManager",
return_value=mock_manager,
)
_upload(filename="../../etc/passwd.txt")
mock_manager.write_file.assert_called_once()
call_args = mock_manager.write_file.call_args
assert call_args[0][1] == "passwd.txt"
def test_download_file_not_found(mocker):
mocker.patch(
"backend.api.features.workspace.routes.get_workspace",
return_value=_make_workspace(),
)
mocker.patch(
"backend.api.features.workspace.routes.get_workspace_file",
return_value=None,
)
response = client.get("/files/some-file-id/download")
assert response.status_code == 404
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=_make_workspace(),
)
mock_manager = mocker.MagicMock()
mock_manager.delete_file = mocker.AsyncMock(return_value=True)
mocker.patch(
"backend.api.features.workspace.routes.WorkspaceManager",
return_value=mock_manager,
)
response = client.delete("/files/file-aaa-bbb")
assert response.status_code == 200
assert response.json() == {"deleted": True}
mock_manager.delete_file.assert_called_once_with("file-aaa-bbb")
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=_make_workspace(),
)
mock_manager = mocker.MagicMock()
mock_manager.delete_file = mocker.AsyncMock(return_value=False)
mocker.patch(
"backend.api.features.workspace.routes.WorkspaceManager",
return_value=mock_manager,
)
response = client.delete("/files/nonexistent-id")
assert response.status_code == 404
assert "File not found" in response.text
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",
return_value=None,
)
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
)

View File

@@ -94,3 +94,8 @@ class NotificationPayload(pydantic.BaseModel):
class OnboardingNotificationPayload(NotificationPayload):
step: OnboardingStep | None
class CopilotCompletionPayload(NotificationPayload):
session_id: str
status: Literal["completed", "failed"]

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