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Author SHA1 Message Date
Zamil Majdy
c5c40c8f8a test(backend/copilot): E2E test screenshots for PR #12575 dry-run special blocks (round 4) 2026-04-02 09:38:04 +02:00
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
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
5077 changed files with 1387890 additions and 0 deletions

1
.agents/skills Symbolic link
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../.claude/skills

36
.branchlet.json Normal file
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@@ -0,0 +1,36 @@
{
"worktreeCopyPatterns": [
".env*",
".vscode/**",
".auth/**",
".claude/**",
"autogpt_platform/.env*",
"autogpt_platform/backend/.env*",
"autogpt_platform/frontend/.env*",
"autogpt_platform/frontend/.auth/**",
"autogpt_platform/db/docker/.env*"
],
"worktreeCopyIgnores": [
"**/node_modules/**",
"**/dist/**",
"**/.git/**",
"**/Thumbs.db",
"**/.DS_Store",
"**/.next/**",
"**/__pycache__/**",
"**/.ruff_cache/**",
"**/.pytest_cache/**",
"**/*.pyc",
"**/playwright-report/**",
"**/logs/**",
"**/site/**"
],
"worktreePathTemplate": "$BASE_PATH.worktree",
"postCreateCmd": [
"cd autogpt_platform/autogpt_libs && poetry install",
"cd autogpt_platform/backend && poetry install && poetry run prisma generate",
"cd autogpt_platform/frontend && pnpm install"
],
"terminalCommand": "code .",
"deleteBranchWithWorktree": false
}

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---
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 +1,210 @@
---
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>"` |
## 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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---
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 +1,754 @@
---
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=(
["01-login-page.png"]="Shows the login page loaded successfully with SSO options visible."
["02-builder-with-block.png"]="The builder canvas displays the newly added block connected to the trigger."
# ... one entry per screenshot, using the same explanations you showed the user 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.**
```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, and branch ref
TREE_SHA=$(echo "$TREE_JSON" | jq -c '{tree: .}' | gh api "repos/${REPO}/git/trees" --input - --jq '.sha')
COMMIT_SHA=$(gh api "repos/${REPO}/git/commits" \
-f message="test: add E2E test screenshots for PR #${PR_NUMBER}" \
-f tree="$TREE_SHA" \
--jq '.sha')
gh api "repos/${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}
${FAILED_SECTION}
INNEREOF
gh api "repos/${REPO}/issues/$PR_NUMBER/comments" -F body=@"$COMMENT_FILE"
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 1-2 sentence explanation below each screenshot describing what it proves
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.
## 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.

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---
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
```

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---
name: vercel-react-best-practices
description: React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
license: MIT
metadata:
author: vercel
version: "1.0.0"
---
# Vercel React Best Practices
Comprehensive performance optimization guide for React and Next.js applications, maintained by Vercel. Contains 45 rules across 8 categories, prioritized by impact to guide automated refactoring and code generation.
## When to Apply
Reference these guidelines when:
- Writing new React components or Next.js pages
- Implementing data fetching (client or server-side)
- Reviewing code for performance issues
- Refactoring existing React/Next.js code
- Optimizing bundle size or load times
## Rule Categories by Priority
| Priority | Category | Impact | Prefix |
|----------|----------|--------|--------|
| 1 | Eliminating Waterfalls | CRITICAL | `async-` |
| 2 | Bundle Size Optimization | CRITICAL | `bundle-` |
| 3 | Server-Side Performance | HIGH | `server-` |
| 4 | Client-Side Data Fetching | MEDIUM-HIGH | `client-` |
| 5 | Re-render Optimization | MEDIUM | `rerender-` |
| 6 | Rendering Performance | MEDIUM | `rendering-` |
| 7 | JavaScript Performance | LOW-MEDIUM | `js-` |
| 8 | Advanced Patterns | LOW | `advanced-` |
## Quick Reference
### 1. Eliminating Waterfalls (CRITICAL)
- `async-defer-await` - Move await into branches where actually used
- `async-parallel` - Use Promise.all() for independent operations
- `async-dependencies` - Use better-all for partial dependencies
- `async-api-routes` - Start promises early, await late in API routes
- `async-suspense-boundaries` - Use Suspense to stream content
### 2. Bundle Size Optimization (CRITICAL)
- `bundle-barrel-imports` - Import directly, avoid barrel files
- `bundle-dynamic-imports` - Use next/dynamic for heavy components
- `bundle-defer-third-party` - Load analytics/logging after hydration
- `bundle-conditional` - Load modules only when feature is activated
- `bundle-preload` - Preload on hover/focus for perceived speed
### 3. Server-Side Performance (HIGH)
- `server-cache-react` - Use React.cache() for per-request deduplication
- `server-cache-lru` - Use LRU cache for cross-request caching
- `server-serialization` - Minimize data passed to client components
- `server-parallel-fetching` - Restructure components to parallelize fetches
- `server-after-nonblocking` - Use after() for non-blocking operations
### 4. Client-Side Data Fetching (MEDIUM-HIGH)
- `client-swr-dedup` - Use SWR for automatic request deduplication
- `client-event-listeners` - Deduplicate global event listeners
### 5. Re-render Optimization (MEDIUM)
- `rerender-defer-reads` - Don't subscribe to state only used in callbacks
- `rerender-memo` - Extract expensive work into memoized components
- `rerender-dependencies` - Use primitive dependencies in effects
- `rerender-derived-state` - Subscribe to derived booleans, not raw values
- `rerender-functional-setstate` - Use functional setState for stable callbacks
- `rerender-lazy-state-init` - Pass function to useState for expensive values
- `rerender-transitions` - Use startTransition for non-urgent updates
### 6. Rendering Performance (MEDIUM)
- `rendering-animate-svg-wrapper` - Animate div wrapper, not SVG element
- `rendering-content-visibility` - Use content-visibility for long lists
- `rendering-hoist-jsx` - Extract static JSX outside components
- `rendering-svg-precision` - Reduce SVG coordinate precision
- `rendering-hydration-no-flicker` - Use inline script for client-only data
- `rendering-activity` - Use Activity component for show/hide
- `rendering-conditional-render` - Use ternary, not && for conditionals
### 7. JavaScript Performance (LOW-MEDIUM)
- `js-batch-dom-css` - Group CSS changes via classes or cssText
- `js-index-maps` - Build Map for repeated lookups
- `js-cache-property-access` - Cache object properties in loops
- `js-cache-function-results` - Cache function results in module-level Map
- `js-cache-storage` - Cache localStorage/sessionStorage reads
- `js-combine-iterations` - Combine multiple filter/map into one loop
- `js-length-check-first` - Check array length before expensive comparison
- `js-early-exit` - Return early from functions
- `js-hoist-regexp` - Hoist RegExp creation outside loops
- `js-min-max-loop` - Use loop for min/max instead of sort
- `js-set-map-lookups` - Use Set/Map for O(1) lookups
- `js-tosorted-immutable` - Use toSorted() for immutability
### 8. Advanced Patterns (LOW)
- `advanced-event-handler-refs` - Store event handlers in refs
- `advanced-use-latest` - useLatest for stable callback refs
## How to Use
Read individual rule files for detailed explanations and code examples:
```
rules/async-parallel.md
rules/bundle-barrel-imports.md
rules/_sections.md
```
Each rule file contains:
- Brief explanation of why it matters
- Incorrect code example with explanation
- Correct code example with explanation
- Additional context and references
## Full Compiled Document
For the complete guide with all rules expanded: `AGENTS.md`

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---
title: Store Event Handlers in Refs
impact: LOW
impactDescription: stable subscriptions
tags: advanced, hooks, refs, event-handlers, optimization
---
## Store Event Handlers in Refs
Store callbacks in refs when used in effects that shouldn't re-subscribe on callback changes.
**Incorrect (re-subscribes on every render):**
```tsx
function useWindowEvent(event: string, handler: () => void) {
useEffect(() => {
window.addEventListener(event, handler)
return () => window.removeEventListener(event, handler)
}, [event, handler])
}
```
**Correct (stable subscription):**
```tsx
function useWindowEvent(event: string, handler: () => void) {
const handlerRef = useRef(handler)
useEffect(() => {
handlerRef.current = handler
}, [handler])
useEffect(() => {
const listener = () => handlerRef.current()
window.addEventListener(event, listener)
return () => window.removeEventListener(event, listener)
}, [event])
}
```
**Alternative: use `useEffectEvent` if you're on latest React:**
```tsx
import { useEffectEvent } from 'react'
function useWindowEvent(event: string, handler: () => void) {
const onEvent = useEffectEvent(handler)
useEffect(() => {
window.addEventListener(event, onEvent)
return () => window.removeEventListener(event, onEvent)
}, [event])
}
```
`useEffectEvent` provides a cleaner API for the same pattern: it creates a stable function reference that always calls the latest version of the handler.

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---
title: useLatest for Stable Callback Refs
impact: LOW
impactDescription: prevents effect re-runs
tags: advanced, hooks, useLatest, refs, optimization
---
## useLatest for Stable Callback Refs
Access latest values in callbacks without adding them to dependency arrays. Prevents effect re-runs while avoiding stale closures.
**Implementation:**
```typescript
function useLatest<T>(value: T) {
const ref = useRef(value)
useEffect(() => {
ref.current = value
}, [value])
return ref
}
```
**Incorrect (effect re-runs on every callback change):**
```tsx
function SearchInput({ onSearch }: { onSearch: (q: string) => void }) {
const [query, setQuery] = useState('')
useEffect(() => {
const timeout = setTimeout(() => onSearch(query), 300)
return () => clearTimeout(timeout)
}, [query, onSearch])
}
```
**Correct (stable effect, fresh callback):**
```tsx
function SearchInput({ onSearch }: { onSearch: (q: string) => void }) {
const [query, setQuery] = useState('')
const onSearchRef = useLatest(onSearch)
useEffect(() => {
const timeout = setTimeout(() => onSearchRef.current(query), 300)
return () => clearTimeout(timeout)
}, [query])
}
```

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---
title: Prevent Waterfall Chains in API Routes
impact: CRITICAL
impactDescription: 2-10× improvement
tags: api-routes, server-actions, waterfalls, parallelization
---
## Prevent Waterfall Chains in API Routes
In API routes and Server Actions, start independent operations immediately, even if you don't await them yet.
**Incorrect (config waits for auth, data waits for both):**
```typescript
export async function GET(request: Request) {
const session = await auth()
const config = await fetchConfig()
const data = await fetchData(session.user.id)
return Response.json({ data, config })
}
```
**Correct (auth and config start immediately):**
```typescript
export async function GET(request: Request) {
const sessionPromise = auth()
const configPromise = fetchConfig()
const session = await sessionPromise
const [config, data] = await Promise.all([
configPromise,
fetchData(session.user.id)
])
return Response.json({ data, config })
}
```
For operations with more complex dependency chains, use `better-all` to automatically maximize parallelism (see Dependency-Based Parallelization).

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---
title: Defer Await Until Needed
impact: HIGH
impactDescription: avoids blocking unused code paths
tags: async, await, conditional, optimization
---
## Defer Await Until Needed
Move `await` operations into the branches where they're actually used to avoid blocking code paths that don't need them.
**Incorrect (blocks both branches):**
```typescript
async function handleRequest(userId: string, skipProcessing: boolean) {
const userData = await fetchUserData(userId)
if (skipProcessing) {
// Returns immediately but still waited for userData
return { skipped: true }
}
// Only this branch uses userData
return processUserData(userData)
}
```
**Correct (only blocks when needed):**
```typescript
async function handleRequest(userId: string, skipProcessing: boolean) {
if (skipProcessing) {
// Returns immediately without waiting
return { skipped: true }
}
// Fetch only when needed
const userData = await fetchUserData(userId)
return processUserData(userData)
}
```
**Another example (early return optimization):**
```typescript
// Incorrect: always fetches permissions
async function updateResource(resourceId: string, userId: string) {
const permissions = await fetchPermissions(userId)
const resource = await getResource(resourceId)
if (!resource) {
return { error: 'Not found' }
}
if (!permissions.canEdit) {
return { error: 'Forbidden' }
}
return await updateResourceData(resource, permissions)
}
// Correct: fetches only when needed
async function updateResource(resourceId: string, userId: string) {
const resource = await getResource(resourceId)
if (!resource) {
return { error: 'Not found' }
}
const permissions = await fetchPermissions(userId)
if (!permissions.canEdit) {
return { error: 'Forbidden' }
}
return await updateResourceData(resource, permissions)
}
```
This optimization is especially valuable when the skipped branch is frequently taken, or when the deferred operation is expensive.

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---
title: Dependency-Based Parallelization
impact: CRITICAL
impactDescription: 2-10× improvement
tags: async, parallelization, dependencies, better-all
---
## Dependency-Based Parallelization
For operations with partial dependencies, use `better-all` to maximize parallelism. It automatically starts each task at the earliest possible moment.
**Incorrect (profile waits for config unnecessarily):**
```typescript
const [user, config] = await Promise.all([
fetchUser(),
fetchConfig()
])
const profile = await fetchProfile(user.id)
```
**Correct (config and profile run in parallel):**
```typescript
import { all } from 'better-all'
const { user, config, profile } = await all({
async user() { return fetchUser() },
async config() { return fetchConfig() },
async profile() {
return fetchProfile((await this.$.user).id)
}
})
```
Reference: [https://github.com/shuding/better-all](https://github.com/shuding/better-all)

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---
title: Promise.all() for Independent Operations
impact: CRITICAL
impactDescription: 2-10× improvement
tags: async, parallelization, promises, waterfalls
---
## Promise.all() for Independent Operations
When async operations have no interdependencies, execute them concurrently using `Promise.all()`.
**Incorrect (sequential execution, 3 round trips):**
```typescript
const user = await fetchUser()
const posts = await fetchPosts()
const comments = await fetchComments()
```
**Correct (parallel execution, 1 round trip):**
```typescript
const [user, posts, comments] = await Promise.all([
fetchUser(),
fetchPosts(),
fetchComments()
])
```

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---
title: Strategic Suspense Boundaries
impact: HIGH
impactDescription: faster initial paint
tags: async, suspense, streaming, layout-shift
---
## Strategic Suspense Boundaries
Instead of awaiting data in async components before returning JSX, use Suspense boundaries to show the wrapper UI faster while data loads.
**Incorrect (wrapper blocked by data fetching):**
```tsx
async function Page() {
const data = await fetchData() // Blocks entire page
return (
<div>
<div>Sidebar</div>
<div>Header</div>
<div>
<DataDisplay data={data} />
</div>
<div>Footer</div>
</div>
)
}
```
The entire layout waits for data even though only the middle section needs it.
**Correct (wrapper shows immediately, data streams in):**
```tsx
function Page() {
return (
<div>
<div>Sidebar</div>
<div>Header</div>
<div>
<Suspense fallback={<Skeleton />}>
<DataDisplay />
</Suspense>
</div>
<div>Footer</div>
</div>
)
}
async function DataDisplay() {
const data = await fetchData() // Only blocks this component
return <div>{data.content}</div>
}
```
Sidebar, Header, and Footer render immediately. Only DataDisplay waits for data.
**Alternative (share promise across components):**
```tsx
function Page() {
// Start fetch immediately, but don't await
const dataPromise = fetchData()
return (
<div>
<div>Sidebar</div>
<div>Header</div>
<Suspense fallback={<Skeleton />}>
<DataDisplay dataPromise={dataPromise} />
<DataSummary dataPromise={dataPromise} />
</Suspense>
<div>Footer</div>
</div>
)
}
function DataDisplay({ dataPromise }: { dataPromise: Promise<Data> }) {
const data = use(dataPromise) // Unwraps the promise
return <div>{data.content}</div>
}
function DataSummary({ dataPromise }: { dataPromise: Promise<Data> }) {
const data = use(dataPromise) // Reuses the same promise
return <div>{data.summary}</div>
}
```
Both components share the same promise, so only one fetch occurs. Layout renders immediately while both components wait together.
**When NOT to use this pattern:**
- Critical data needed for layout decisions (affects positioning)
- SEO-critical content above the fold
- Small, fast queries where suspense overhead isn't worth it
- When you want to avoid layout shift (loading → content jump)
**Trade-off:** Faster initial paint vs potential layout shift. Choose based on your UX priorities.

View File

@@ -0,0 +1,59 @@
---
title: Avoid Barrel File Imports
impact: CRITICAL
impactDescription: 200-800ms import cost, slow builds
tags: bundle, imports, tree-shaking, barrel-files, performance
---
## Avoid Barrel File Imports
Import directly from source files instead of barrel files to avoid loading thousands of unused modules. **Barrel files** are entry points that re-export multiple modules (e.g., `index.js` that does `export * from './module'`).
Popular icon and component libraries can have **up to 10,000 re-exports** in their entry file. For many React packages, **it takes 200-800ms just to import them**, affecting both development speed and production cold starts.
**Why tree-shaking doesn't help:** When a library is marked as external (not bundled), the bundler can't optimize it. If you bundle it to enable tree-shaking, builds become substantially slower analyzing the entire module graph.
**Incorrect (imports entire library):**
```tsx
import { Check, X, Menu } from 'lucide-react'
// Loads 1,583 modules, takes ~2.8s extra in dev
// Runtime cost: 200-800ms on every cold start
import { Button, TextField } from '@mui/material'
// Loads 2,225 modules, takes ~4.2s extra in dev
```
**Correct (imports only what you need):**
```tsx
import Check from 'lucide-react/dist/esm/icons/check'
import X from 'lucide-react/dist/esm/icons/x'
import Menu from 'lucide-react/dist/esm/icons/menu'
// Loads only 3 modules (~2KB vs ~1MB)
import Button from '@mui/material/Button'
import TextField from '@mui/material/TextField'
// Loads only what you use
```
**Alternative (Next.js 13.5+):**
```js
// next.config.js - use optimizePackageImports
module.exports = {
experimental: {
optimizePackageImports: ['lucide-react', '@mui/material']
}
}
// Then you can keep the ergonomic barrel imports:
import { Check, X, Menu } from 'lucide-react'
// Automatically transformed to direct imports at build time
```
Direct imports provide 15-70% faster dev boot, 28% faster builds, 40% faster cold starts, and significantly faster HMR.
Libraries commonly affected: `lucide-react`, `@mui/material`, `@mui/icons-material`, `@tabler/icons-react`, `react-icons`, `@headlessui/react`, `@radix-ui/react-*`, `lodash`, `ramda`, `date-fns`, `rxjs`, `react-use`.
Reference: [How we optimized package imports in Next.js](https://vercel.com/blog/how-we-optimized-package-imports-in-next-js)

View File

@@ -0,0 +1,31 @@
---
title: Conditional Module Loading
impact: HIGH
impactDescription: loads large data only when needed
tags: bundle, conditional-loading, lazy-loading
---
## Conditional Module Loading
Load large data or modules only when a feature is activated.
**Example (lazy-load animation frames):**
```tsx
function AnimationPlayer({ enabled }: { enabled: boolean }) {
const [frames, setFrames] = useState<Frame[] | null>(null)
useEffect(() => {
if (enabled && !frames && typeof window !== 'undefined') {
import('./animation-frames.js')
.then(mod => setFrames(mod.frames))
.catch(() => setEnabled(false))
}
}, [enabled, frames])
if (!frames) return <Skeleton />
return <Canvas frames={frames} />
}
```
The `typeof window !== 'undefined'` check prevents bundling this module for SSR, optimizing server bundle size and build speed.

View File

@@ -0,0 +1,49 @@
---
title: Defer Non-Critical Third-Party Libraries
impact: MEDIUM
impactDescription: loads after hydration
tags: bundle, third-party, analytics, defer
---
## Defer Non-Critical Third-Party Libraries
Analytics, logging, and error tracking don't block user interaction. Load them after hydration.
**Incorrect (blocks initial bundle):**
```tsx
import { Analytics } from '@vercel/analytics/react'
export default function RootLayout({ children }) {
return (
<html>
<body>
{children}
<Analytics />
</body>
</html>
)
}
```
**Correct (loads after hydration):**
```tsx
import dynamic from 'next/dynamic'
const Analytics = dynamic(
() => import('@vercel/analytics/react').then(m => m.Analytics),
{ ssr: false }
)
export default function RootLayout({ children }) {
return (
<html>
<body>
{children}
<Analytics />
</body>
</html>
)
}
```

View File

@@ -0,0 +1,35 @@
---
title: Dynamic Imports for Heavy Components
impact: CRITICAL
impactDescription: directly affects TTI and LCP
tags: bundle, dynamic-import, code-splitting, next-dynamic
---
## Dynamic Imports for Heavy Components
Use `next/dynamic` to lazy-load large components not needed on initial render.
**Incorrect (Monaco bundles with main chunk ~300KB):**
```tsx
import { MonacoEditor } from './monaco-editor'
function CodePanel({ code }: { code: string }) {
return <MonacoEditor value={code} />
}
```
**Correct (Monaco loads on demand):**
```tsx
import dynamic from 'next/dynamic'
const MonacoEditor = dynamic(
() => import('./monaco-editor').then(m => m.MonacoEditor),
{ ssr: false }
)
function CodePanel({ code }: { code: string }) {
return <MonacoEditor value={code} />
}
```

View File

@@ -0,0 +1,50 @@
---
title: Preload Based on User Intent
impact: MEDIUM
impactDescription: reduces perceived latency
tags: bundle, preload, user-intent, hover
---
## Preload Based on User Intent
Preload heavy bundles before they're needed to reduce perceived latency.
**Example (preload on hover/focus):**
```tsx
function EditorButton({ onClick }: { onClick: () => void }) {
const preload = () => {
if (typeof window !== 'undefined') {
void import('./monaco-editor')
}
}
return (
<button
onMouseEnter={preload}
onFocus={preload}
onClick={onClick}
>
Open Editor
</button>
)
}
```
**Example (preload when feature flag is enabled):**
```tsx
function FlagsProvider({ children, flags }: Props) {
useEffect(() => {
if (flags.editorEnabled && typeof window !== 'undefined') {
void import('./monaco-editor').then(mod => mod.init())
}
}, [flags.editorEnabled])
return <FlagsContext.Provider value={flags}>
{children}
</FlagsContext.Provider>
}
```
The `typeof window !== 'undefined'` check prevents bundling preloaded modules for SSR, optimizing server bundle size and build speed.

View File

@@ -0,0 +1,74 @@
---
title: Deduplicate Global Event Listeners
impact: LOW
impactDescription: single listener for N components
tags: client, swr, event-listeners, subscription
---
## Deduplicate Global Event Listeners
Use `useSWRSubscription()` to share global event listeners across component instances.
**Incorrect (N instances = N listeners):**
```tsx
function useKeyboardShortcut(key: string, callback: () => void) {
useEffect(() => {
const handler = (e: KeyboardEvent) => {
if (e.metaKey && e.key === key) {
callback()
}
}
window.addEventListener('keydown', handler)
return () => window.removeEventListener('keydown', handler)
}, [key, callback])
}
```
When using the `useKeyboardShortcut` hook multiple times, each instance will register a new listener.
**Correct (N instances = 1 listener):**
```tsx
import useSWRSubscription from 'swr/subscription'
// Module-level Map to track callbacks per key
const keyCallbacks = new Map<string, Set<() => void>>()
function useKeyboardShortcut(key: string, callback: () => void) {
// Register this callback in the Map
useEffect(() => {
if (!keyCallbacks.has(key)) {
keyCallbacks.set(key, new Set())
}
keyCallbacks.get(key)!.add(callback)
return () => {
const set = keyCallbacks.get(key)
if (set) {
set.delete(callback)
if (set.size === 0) {
keyCallbacks.delete(key)
}
}
}
}, [key, callback])
useSWRSubscription('global-keydown', () => {
const handler = (e: KeyboardEvent) => {
if (e.metaKey && keyCallbacks.has(e.key)) {
keyCallbacks.get(e.key)!.forEach(cb => cb())
}
}
window.addEventListener('keydown', handler)
return () => window.removeEventListener('keydown', handler)
})
}
function Profile() {
// Multiple shortcuts will share the same listener
useKeyboardShortcut('p', () => { /* ... */ })
useKeyboardShortcut('k', () => { /* ... */ })
// ...
}
```

View File

@@ -0,0 +1,56 @@
---
title: Use SWR for Automatic Deduplication
impact: MEDIUM-HIGH
impactDescription: automatic deduplication
tags: client, swr, deduplication, data-fetching
---
## Use SWR for Automatic Deduplication
SWR enables request deduplication, caching, and revalidation across component instances.
**Incorrect (no deduplication, each instance fetches):**
```tsx
function UserList() {
const [users, setUsers] = useState([])
useEffect(() => {
fetch('/api/users')
.then(r => r.json())
.then(setUsers)
}, [])
}
```
**Correct (multiple instances share one request):**
```tsx
import useSWR from 'swr'
function UserList() {
const { data: users } = useSWR('/api/users', fetcher)
}
```
**For immutable data:**
```tsx
import { useImmutableSWR } from '@/lib/swr'
function StaticContent() {
const { data } = useImmutableSWR('/api/config', fetcher)
}
```
**For mutations:**
```tsx
import { useSWRMutation } from 'swr/mutation'
function UpdateButton() {
const { trigger } = useSWRMutation('/api/user', updateUser)
return <button onClick={() => trigger()}>Update</button>
}
```
Reference: [https://swr.vercel.app](https://swr.vercel.app)

View File

@@ -0,0 +1,82 @@
---
title: Batch DOM CSS Changes
impact: MEDIUM
impactDescription: reduces reflows/repaints
tags: javascript, dom, css, performance, reflow
---
## Batch DOM CSS Changes
Avoid changing styles one property at a time. Group multiple CSS changes together via classes or `cssText` to minimize browser reflows.
**Incorrect (multiple reflows):**
```typescript
function updateElementStyles(element: HTMLElement) {
// Each line triggers a reflow
element.style.width = '100px'
element.style.height = '200px'
element.style.backgroundColor = 'blue'
element.style.border = '1px solid black'
}
```
**Correct (add class - single reflow):**
```typescript
// CSS file
.highlighted-box {
width: 100px;
height: 200px;
background-color: blue;
border: 1px solid black;
}
// JavaScript
function updateElementStyles(element: HTMLElement) {
element.classList.add('highlighted-box')
}
```
**Correct (change cssText - single reflow):**
```typescript
function updateElementStyles(element: HTMLElement) {
element.style.cssText = `
width: 100px;
height: 200px;
background-color: blue;
border: 1px solid black;
`
}
```
**React example:**
```tsx
// Incorrect: changing styles one by one
function Box({ isHighlighted }: { isHighlighted: boolean }) {
const ref = useRef<HTMLDivElement>(null)
useEffect(() => {
if (ref.current && isHighlighted) {
ref.current.style.width = '100px'
ref.current.style.height = '200px'
ref.current.style.backgroundColor = 'blue'
}
}, [isHighlighted])
return <div ref={ref}>Content</div>
}
// Correct: toggle class
function Box({ isHighlighted }: { isHighlighted: boolean }) {
return (
<div className={isHighlighted ? 'highlighted-box' : ''}>
Content
</div>
)
}
```
Prefer CSS classes over inline styles when possible. Classes are cached by the browser and provide better separation of concerns.

View File

@@ -0,0 +1,80 @@
---
title: Cache Repeated Function Calls
impact: MEDIUM
impactDescription: avoid redundant computation
tags: javascript, cache, memoization, performance
---
## Cache Repeated Function Calls
Use a module-level Map to cache function results when the same function is called repeatedly with the same inputs during render.
**Incorrect (redundant computation):**
```typescript
function ProjectList({ projects }: { projects: Project[] }) {
return (
<div>
{projects.map(project => {
// slugify() called 100+ times for same project names
const slug = slugify(project.name)
return <ProjectCard key={project.id} slug={slug} />
})}
</div>
)
}
```
**Correct (cached results):**
```typescript
// Module-level cache
const slugifyCache = new Map<string, string>()
function cachedSlugify(text: string): string {
if (slugifyCache.has(text)) {
return slugifyCache.get(text)!
}
const result = slugify(text)
slugifyCache.set(text, result)
return result
}
function ProjectList({ projects }: { projects: Project[] }) {
return (
<div>
{projects.map(project => {
// Computed only once per unique project name
const slug = cachedSlugify(project.name)
return <ProjectCard key={project.id} slug={slug} />
})}
</div>
)
}
```
**Simpler pattern for single-value functions:**
```typescript
let isLoggedInCache: boolean | null = null
function isLoggedIn(): boolean {
if (isLoggedInCache !== null) {
return isLoggedInCache
}
isLoggedInCache = document.cookie.includes('auth=')
return isLoggedInCache
}
// Clear cache when auth changes
function onAuthChange() {
isLoggedInCache = null
}
```
Use a Map (not a hook) so it works everywhere: utilities, event handlers, not just React components.
Reference: [How we made the Vercel Dashboard twice as fast](https://vercel.com/blog/how-we-made-the-vercel-dashboard-twice-as-fast)

View File

@@ -0,0 +1,28 @@
---
title: Cache Property Access in Loops
impact: LOW-MEDIUM
impactDescription: reduces lookups
tags: javascript, loops, optimization, caching
---
## Cache Property Access in Loops
Cache object property lookups in hot paths.
**Incorrect (3 lookups × N iterations):**
```typescript
for (let i = 0; i < arr.length; i++) {
process(obj.config.settings.value)
}
```
**Correct (1 lookup total):**
```typescript
const value = obj.config.settings.value
const len = arr.length
for (let i = 0; i < len; i++) {
process(value)
}
```

View File

@@ -0,0 +1,70 @@
---
title: Cache Storage API Calls
impact: LOW-MEDIUM
impactDescription: reduces expensive I/O
tags: javascript, localStorage, storage, caching, performance
---
## Cache Storage API Calls
`localStorage`, `sessionStorage`, and `document.cookie` are synchronous and expensive. Cache reads in memory.
**Incorrect (reads storage on every call):**
```typescript
function getTheme() {
return localStorage.getItem('theme') ?? 'light'
}
// Called 10 times = 10 storage reads
```
**Correct (Map cache):**
```typescript
const storageCache = new Map<string, string | null>()
function getLocalStorage(key: string) {
if (!storageCache.has(key)) {
storageCache.set(key, localStorage.getItem(key))
}
return storageCache.get(key)
}
function setLocalStorage(key: string, value: string) {
localStorage.setItem(key, value)
storageCache.set(key, value) // keep cache in sync
}
```
Use a Map (not a hook) so it works everywhere: utilities, event handlers, not just React components.
**Cookie caching:**
```typescript
let cookieCache: Record<string, string> | null = null
function getCookie(name: string) {
if (!cookieCache) {
cookieCache = Object.fromEntries(
document.cookie.split('; ').map(c => c.split('='))
)
}
return cookieCache[name]
}
```
**Important (invalidate on external changes):**
If storage can change externally (another tab, server-set cookies), invalidate cache:
```typescript
window.addEventListener('storage', (e) => {
if (e.key) storageCache.delete(e.key)
})
document.addEventListener('visibilitychange', () => {
if (document.visibilityState === 'visible') {
storageCache.clear()
}
})
```

View File

@@ -0,0 +1,32 @@
---
title: Combine Multiple Array Iterations
impact: LOW-MEDIUM
impactDescription: reduces iterations
tags: javascript, arrays, loops, performance
---
## Combine Multiple Array Iterations
Multiple `.filter()` or `.map()` calls iterate the array multiple times. Combine into one loop.
**Incorrect (3 iterations):**
```typescript
const admins = users.filter(u => u.isAdmin)
const testers = users.filter(u => u.isTester)
const inactive = users.filter(u => !u.isActive)
```
**Correct (1 iteration):**
```typescript
const admins: User[] = []
const testers: User[] = []
const inactive: User[] = []
for (const user of users) {
if (user.isAdmin) admins.push(user)
if (user.isTester) testers.push(user)
if (!user.isActive) inactive.push(user)
}
```

View File

@@ -0,0 +1,50 @@
---
title: Early Return from Functions
impact: LOW-MEDIUM
impactDescription: avoids unnecessary computation
tags: javascript, functions, optimization, early-return
---
## Early Return from Functions
Return early when result is determined to skip unnecessary processing.
**Incorrect (processes all items even after finding answer):**
```typescript
function validateUsers(users: User[]) {
let hasError = false
let errorMessage = ''
for (const user of users) {
if (!user.email) {
hasError = true
errorMessage = 'Email required'
}
if (!user.name) {
hasError = true
errorMessage = 'Name required'
}
// Continues checking all users even after error found
}
return hasError ? { valid: false, error: errorMessage } : { valid: true }
}
```
**Correct (returns immediately on first error):**
```typescript
function validateUsers(users: User[]) {
for (const user of users) {
if (!user.email) {
return { valid: false, error: 'Email required' }
}
if (!user.name) {
return { valid: false, error: 'Name required' }
}
}
return { valid: true }
}
```

View File

@@ -0,0 +1,45 @@
---
title: Hoist RegExp Creation
impact: LOW-MEDIUM
impactDescription: avoids recreation
tags: javascript, regexp, optimization, memoization
---
## Hoist RegExp Creation
Don't create RegExp inside render. Hoist to module scope or memoize with `useMemo()`.
**Incorrect (new RegExp every render):**
```tsx
function Highlighter({ text, query }: Props) {
const regex = new RegExp(`(${query})`, 'gi')
const parts = text.split(regex)
return <>{parts.map((part, i) => ...)}</>
}
```
**Correct (memoize or hoist):**
```tsx
const EMAIL_REGEX = /^[^\s@]+@[^\s@]+\.[^\s@]+$/
function Highlighter({ text, query }: Props) {
const regex = useMemo(
() => new RegExp(`(${escapeRegex(query)})`, 'gi'),
[query]
)
const parts = text.split(regex)
return <>{parts.map((part, i) => ...)}</>
}
```
**Warning (global regex has mutable state):**
Global regex (`/g`) has mutable `lastIndex` state:
```typescript
const regex = /foo/g
regex.test('foo') // true, lastIndex = 3
regex.test('foo') // false, lastIndex = 0
```

View File

@@ -0,0 +1,37 @@
---
title: Build Index Maps for Repeated Lookups
impact: LOW-MEDIUM
impactDescription: 1M ops to 2K ops
tags: javascript, map, indexing, optimization, performance
---
## Build Index Maps for Repeated Lookups
Multiple `.find()` calls by the same key should use a Map.
**Incorrect (O(n) per lookup):**
```typescript
function processOrders(orders: Order[], users: User[]) {
return orders.map(order => ({
...order,
user: users.find(u => u.id === order.userId)
}))
}
```
**Correct (O(1) per lookup):**
```typescript
function processOrders(orders: Order[], users: User[]) {
const userById = new Map(users.map(u => [u.id, u]))
return orders.map(order => ({
...order,
user: userById.get(order.userId)
}))
}
```
Build map once (O(n)), then all lookups are O(1).
For 1000 orders × 1000 users: 1M ops → 2K ops.

View File

@@ -0,0 +1,49 @@
---
title: Early Length Check for Array Comparisons
impact: MEDIUM-HIGH
impactDescription: avoids expensive operations when lengths differ
tags: javascript, arrays, performance, optimization, comparison
---
## Early Length Check for Array Comparisons
When comparing arrays with expensive operations (sorting, deep equality, serialization), check lengths first. If lengths differ, the arrays cannot be equal.
In real-world applications, this optimization is especially valuable when the comparison runs in hot paths (event handlers, render loops).
**Incorrect (always runs expensive comparison):**
```typescript
function hasChanges(current: string[], original: string[]) {
// Always sorts and joins, even when lengths differ
return current.sort().join() !== original.sort().join()
}
```
Two O(n log n) sorts run even when `current.length` is 5 and `original.length` is 100. There is also overhead of joining the arrays and comparing the strings.
**Correct (O(1) length check first):**
```typescript
function hasChanges(current: string[], original: string[]) {
// Early return if lengths differ
if (current.length !== original.length) {
return true
}
// Only sort/join when lengths match
const currentSorted = current.toSorted()
const originalSorted = original.toSorted()
for (let i = 0; i < currentSorted.length; i++) {
if (currentSorted[i] !== originalSorted[i]) {
return true
}
}
return false
}
```
This new approach is more efficient because:
- It avoids the overhead of sorting and joining the arrays when lengths differ
- It avoids consuming memory for the joined strings (especially important for large arrays)
- It avoids mutating the original arrays
- It returns early when a difference is found

View File

@@ -0,0 +1,82 @@
---
title: Use Loop for Min/Max Instead of Sort
impact: LOW
impactDescription: O(n) instead of O(n log n)
tags: javascript, arrays, performance, sorting, algorithms
---
## Use Loop for Min/Max Instead of Sort
Finding the smallest or largest element only requires a single pass through the array. Sorting is wasteful and slower.
**Incorrect (O(n log n) - sort to find latest):**
```typescript
interface Project {
id: string
name: string
updatedAt: number
}
function getLatestProject(projects: Project[]) {
const sorted = [...projects].sort((a, b) => b.updatedAt - a.updatedAt)
return sorted[0]
}
```
Sorts the entire array just to find the maximum value.
**Incorrect (O(n log n) - sort for oldest and newest):**
```typescript
function getOldestAndNewest(projects: Project[]) {
const sorted = [...projects].sort((a, b) => a.updatedAt - b.updatedAt)
return { oldest: sorted[0], newest: sorted[sorted.length - 1] }
}
```
Still sorts unnecessarily when only min/max are needed.
**Correct (O(n) - single loop):**
```typescript
function getLatestProject(projects: Project[]) {
if (projects.length === 0) return null
let latest = projects[0]
for (let i = 1; i < projects.length; i++) {
if (projects[i].updatedAt > latest.updatedAt) {
latest = projects[i]
}
}
return latest
}
function getOldestAndNewest(projects: Project[]) {
if (projects.length === 0) return { oldest: null, newest: null }
let oldest = projects[0]
let newest = projects[0]
for (let i = 1; i < projects.length; i++) {
if (projects[i].updatedAt < oldest.updatedAt) oldest = projects[i]
if (projects[i].updatedAt > newest.updatedAt) newest = projects[i]
}
return { oldest, newest }
}
```
Single pass through the array, no copying, no sorting.
**Alternative (Math.min/Math.max for small arrays):**
```typescript
const numbers = [5, 2, 8, 1, 9]
const min = Math.min(...numbers)
const max = Math.max(...numbers)
```
This works for small arrays but can be slower for very large arrays due to spread operator limitations. Use the loop approach for reliability.

View File

@@ -0,0 +1,24 @@
---
title: Use Set/Map for O(1) Lookups
impact: LOW-MEDIUM
impactDescription: O(n) to O(1)
tags: javascript, set, map, data-structures, performance
---
## Use Set/Map for O(1) Lookups
Convert arrays to Set/Map for repeated membership checks.
**Incorrect (O(n) per check):**
```typescript
const allowedIds = ['a', 'b', 'c', ...]
items.filter(item => allowedIds.includes(item.id))
```
**Correct (O(1) per check):**
```typescript
const allowedIds = new Set(['a', 'b', 'c', ...])
items.filter(item => allowedIds.has(item.id))
```

View File

@@ -0,0 +1,57 @@
---
title: Use toSorted() Instead of sort() for Immutability
impact: MEDIUM-HIGH
impactDescription: prevents mutation bugs in React state
tags: javascript, arrays, immutability, react, state, mutation
---
## Use toSorted() Instead of sort() for Immutability
`.sort()` mutates the array in place, which can cause bugs with React state and props. Use `.toSorted()` to create a new sorted array without mutation.
**Incorrect (mutates original array):**
```typescript
function UserList({ users }: { users: User[] }) {
// Mutates the users prop array!
const sorted = useMemo(
() => users.sort((a, b) => a.name.localeCompare(b.name)),
[users]
)
return <div>{sorted.map(renderUser)}</div>
}
```
**Correct (creates new array):**
```typescript
function UserList({ users }: { users: User[] }) {
// Creates new sorted array, original unchanged
const sorted = useMemo(
() => users.toSorted((a, b) => a.name.localeCompare(b.name)),
[users]
)
return <div>{sorted.map(renderUser)}</div>
}
```
**Why this matters in React:**
1. Props/state mutations break React's immutability model - React expects props and state to be treated as read-only
2. Causes stale closure bugs - Mutating arrays inside closures (callbacks, effects) can lead to unexpected behavior
**Browser support (fallback for older browsers):**
`.toSorted()` is available in all modern browsers (Chrome 110+, Safari 16+, Firefox 115+, Node.js 20+). For older environments, use spread operator:
```typescript
// Fallback for older browsers
const sorted = [...items].sort((a, b) => a.value - b.value)
```
**Other immutable array methods:**
- `.toSorted()` - immutable sort
- `.toReversed()` - immutable reverse
- `.toSpliced()` - immutable splice
- `.with()` - immutable element replacement

View File

@@ -0,0 +1,26 @@
---
title: Use Activity Component for Show/Hide
impact: MEDIUM
impactDescription: preserves state/DOM
tags: rendering, activity, visibility, state-preservation
---
## Use Activity Component for Show/Hide
Use React's `<Activity>` to preserve state/DOM for expensive components that frequently toggle visibility.
**Usage:**
```tsx
import { Activity } from 'react'
function Dropdown({ isOpen }: Props) {
return (
<Activity mode={isOpen ? 'visible' : 'hidden'}>
<ExpensiveMenu />
</Activity>
)
}
```
Avoids expensive re-renders and state loss.

View File

@@ -0,0 +1,47 @@
---
title: Animate SVG Wrapper Instead of SVG Element
impact: LOW
impactDescription: enables hardware acceleration
tags: rendering, svg, css, animation, performance
---
## Animate SVG Wrapper Instead of SVG Element
Many browsers don't have hardware acceleration for CSS3 animations on SVG elements. Wrap SVG in a `<div>` and animate the wrapper instead.
**Incorrect (animating SVG directly - no hardware acceleration):**
```tsx
function LoadingSpinner() {
return (
<svg
className="animate-spin"
width="24"
height="24"
viewBox="0 0 24 24"
>
<circle cx="12" cy="12" r="10" stroke="currentColor" />
</svg>
)
}
```
**Correct (animating wrapper div - hardware accelerated):**
```tsx
function LoadingSpinner() {
return (
<div className="animate-spin">
<svg
width="24"
height="24"
viewBox="0 0 24 24"
>
<circle cx="12" cy="12" r="10" stroke="currentColor" />
</svg>
</div>
)
}
```
This applies to all CSS transforms and transitions (`transform`, `opacity`, `translate`, `scale`, `rotate`). The wrapper div allows browsers to use GPU acceleration for smoother animations.

View File

@@ -0,0 +1,40 @@
---
title: Use Explicit Conditional Rendering
impact: LOW
impactDescription: prevents rendering 0 or NaN
tags: rendering, conditional, jsx, falsy-values
---
## Use Explicit Conditional Rendering
Use explicit ternary operators (`? :`) instead of `&&` for conditional rendering when the condition can be `0`, `NaN`, or other falsy values that render.
**Incorrect (renders "0" when count is 0):**
```tsx
function Badge({ count }: { count: number }) {
return (
<div>
{count && <span className="badge">{count}</span>}
</div>
)
}
// When count = 0, renders: <div>0</div>
// When count = 5, renders: <div><span class="badge">5</span></div>
```
**Correct (renders nothing when count is 0):**
```tsx
function Badge({ count }: { count: number }) {
return (
<div>
{count > 0 ? <span className="badge">{count}</span> : null}
</div>
)
}
// When count = 0, renders: <div></div>
// When count = 5, renders: <div><span class="badge">5</span></div>
```

View File

@@ -0,0 +1,38 @@
---
title: CSS content-visibility for Long Lists
impact: HIGH
impactDescription: faster initial render
tags: rendering, css, content-visibility, long-lists
---
## CSS content-visibility for Long Lists
Apply `content-visibility: auto` to defer off-screen rendering.
**CSS:**
```css
.message-item {
content-visibility: auto;
contain-intrinsic-size: 0 80px;
}
```
**Example:**
```tsx
function MessageList({ messages }: { messages: Message[] }) {
return (
<div className="overflow-y-auto h-screen">
{messages.map(msg => (
<div key={msg.id} className="message-item">
<Avatar user={msg.author} />
<div>{msg.content}</div>
</div>
))}
</div>
)
}
```
For 1000 messages, browser skips layout/paint for ~990 off-screen items (10× faster initial render).

View File

@@ -0,0 +1,46 @@
---
title: Hoist Static JSX Elements
impact: LOW
impactDescription: avoids re-creation
tags: rendering, jsx, static, optimization
---
## Hoist Static JSX Elements
Extract static JSX outside components to avoid re-creation.
**Incorrect (recreates element every render):**
```tsx
function LoadingSkeleton() {
return <div className="animate-pulse h-20 bg-gray-200" />
}
function Container() {
return (
<div>
{loading && <LoadingSkeleton />}
</div>
)
}
```
**Correct (reuses same element):**
```tsx
const loadingSkeleton = (
<div className="animate-pulse h-20 bg-gray-200" />
)
function Container() {
return (
<div>
{loading && loadingSkeleton}
</div>
)
}
```
This is especially helpful for large and static SVG nodes, which can be expensive to recreate on every render.
**Note:** If your project has [React Compiler](https://react.dev/learn/react-compiler) enabled, the compiler automatically hoists static JSX elements and optimizes component re-renders, making manual hoisting unnecessary.

View File

@@ -0,0 +1,82 @@
---
title: Prevent Hydration Mismatch Without Flickering
impact: MEDIUM
impactDescription: avoids visual flicker and hydration errors
tags: rendering, ssr, hydration, localStorage, flicker
---
## Prevent Hydration Mismatch Without Flickering
When rendering content that depends on client-side storage (localStorage, cookies), avoid both SSR breakage and post-hydration flickering by injecting a synchronous script that updates the DOM before React hydrates.
**Incorrect (breaks SSR):**
```tsx
function ThemeWrapper({ children }: { children: ReactNode }) {
// localStorage is not available on server - throws error
const theme = localStorage.getItem('theme') || 'light'
return (
<div className={theme}>
{children}
</div>
)
}
```
Server-side rendering will fail because `localStorage` is undefined.
**Incorrect (visual flickering):**
```tsx
function ThemeWrapper({ children }: { children: ReactNode }) {
const [theme, setTheme] = useState('light')
useEffect(() => {
// Runs after hydration - causes visible flash
const stored = localStorage.getItem('theme')
if (stored) {
setTheme(stored)
}
}, [])
return (
<div className={theme}>
{children}
</div>
)
}
```
Component first renders with default value (`light`), then updates after hydration, causing a visible flash of incorrect content.
**Correct (no flicker, no hydration mismatch):**
```tsx
function ThemeWrapper({ children }: { children: ReactNode }) {
return (
<>
<div id="theme-wrapper">
{children}
</div>
<script
dangerouslySetInnerHTML={{
__html: `
(function() {
try {
var theme = localStorage.getItem('theme') || 'light';
var el = document.getElementById('theme-wrapper');
if (el) el.className = theme;
} catch (e) {}
})();
`,
}}
/>
</>
)
}
```
The inline script executes synchronously before showing the element, ensuring the DOM already has the correct value. No flickering, no hydration mismatch.
This pattern is especially useful for theme toggles, user preferences, authentication states, and any client-only data that should render immediately without flashing default values.

View File

@@ -0,0 +1,28 @@
---
title: Optimize SVG Precision
impact: LOW
impactDescription: reduces file size
tags: rendering, svg, optimization, svgo
---
## Optimize SVG Precision
Reduce SVG coordinate precision to decrease file size. The optimal precision depends on the viewBox size, but in general reducing precision should be considered.
**Incorrect (excessive precision):**
```svg
<path d="M 10.293847 20.847362 L 30.938472 40.192837" />
```
**Correct (1 decimal place):**
```svg
<path d="M 10.3 20.8 L 30.9 40.2" />
```
**Automate with SVGO:**
```bash
npx svgo --precision=1 --multipass icon.svg
```

View File

@@ -0,0 +1,39 @@
---
title: Defer State Reads to Usage Point
impact: MEDIUM
impactDescription: avoids unnecessary subscriptions
tags: rerender, searchParams, localStorage, optimization
---
## Defer State Reads to Usage Point
Don't subscribe to dynamic state (searchParams, localStorage) if you only read it inside callbacks.
**Incorrect (subscribes to all searchParams changes):**
```tsx
function ShareButton({ chatId }: { chatId: string }) {
const searchParams = useSearchParams()
const handleShare = () => {
const ref = searchParams.get('ref')
shareChat(chatId, { ref })
}
return <button onClick={handleShare}>Share</button>
}
```
**Correct (reads on demand, no subscription):**
```tsx
function ShareButton({ chatId }: { chatId: string }) {
const handleShare = () => {
const params = new URLSearchParams(window.location.search)
const ref = params.get('ref')
shareChat(chatId, { ref })
}
return <button onClick={handleShare}>Share</button>
}
```

View File

@@ -0,0 +1,45 @@
---
title: Narrow Effect Dependencies
impact: LOW
impactDescription: minimizes effect re-runs
tags: rerender, useEffect, dependencies, optimization
---
## Narrow Effect Dependencies
Specify primitive dependencies instead of objects to minimize effect re-runs.
**Incorrect (re-runs on any user field change):**
```tsx
useEffect(() => {
console.log(user.id)
}, [user])
```
**Correct (re-runs only when id changes):**
```tsx
useEffect(() => {
console.log(user.id)
}, [user.id])
```
**For derived state, compute outside effect:**
```tsx
// Incorrect: runs on width=767, 766, 765...
useEffect(() => {
if (width < 768) {
enableMobileMode()
}
}, [width])
// Correct: runs only on boolean transition
const isMobile = width < 768
useEffect(() => {
if (isMobile) {
enableMobileMode()
}
}, [isMobile])
```

View File

@@ -0,0 +1,29 @@
---
title: Subscribe to Derived State
impact: MEDIUM
impactDescription: reduces re-render frequency
tags: rerender, derived-state, media-query, optimization
---
## Subscribe to Derived State
Subscribe to derived boolean state instead of continuous values to reduce re-render frequency.
**Incorrect (re-renders on every pixel change):**
```tsx
function Sidebar() {
const width = useWindowWidth() // updates continuously
const isMobile = width < 768
return <nav className={isMobile ? 'mobile' : 'desktop'}>
}
```
**Correct (re-renders only when boolean changes):**
```tsx
function Sidebar() {
const isMobile = useMediaQuery('(max-width: 767px)')
return <nav className={isMobile ? 'mobile' : 'desktop'}>
}
```

View File

@@ -0,0 +1,74 @@
---
title: Use Functional setState Updates
impact: MEDIUM
impactDescription: prevents stale closures and unnecessary callback recreations
tags: react, hooks, useState, useCallback, callbacks, closures
---
## Use Functional setState Updates
When updating state based on the current state value, use the functional update form of setState instead of directly referencing the state variable. This prevents stale closures, eliminates unnecessary dependencies, and creates stable callback references.
**Incorrect (requires state as dependency):**
```tsx
function TodoList() {
const [items, setItems] = useState(initialItems)
// Callback must depend on items, recreated on every items change
const addItems = useCallback((newItems: Item[]) => {
setItems([...items, ...newItems])
}, [items]) // ❌ items dependency causes recreations
// Risk of stale closure if dependency is forgotten
const removeItem = useCallback((id: string) => {
setItems(items.filter(item => item.id !== id))
}, []) // ❌ Missing items dependency - will use stale items!
return <ItemsEditor items={items} onAdd={addItems} onRemove={removeItem} />
}
```
The first callback is recreated every time `items` changes, which can cause child components to re-render unnecessarily. The second callback has a stale closure bug—it will always reference the initial `items` value.
**Correct (stable callbacks, no stale closures):**
```tsx
function TodoList() {
const [items, setItems] = useState(initialItems)
// Stable callback, never recreated
const addItems = useCallback((newItems: Item[]) => {
setItems(curr => [...curr, ...newItems])
}, []) // ✅ No dependencies needed
// Always uses latest state, no stale closure risk
const removeItem = useCallback((id: string) => {
setItems(curr => curr.filter(item => item.id !== id))
}, []) // ✅ Safe and stable
return <ItemsEditor items={items} onAdd={addItems} onRemove={removeItem} />
}
```
**Benefits:**
1. **Stable callback references** - Callbacks don't need to be recreated when state changes
2. **No stale closures** - Always operates on the latest state value
3. **Fewer dependencies** - Simplifies dependency arrays and reduces memory leaks
4. **Prevents bugs** - Eliminates the most common source of React closure bugs
**When to use functional updates:**
- Any setState that depends on the current state value
- Inside useCallback/useMemo when state is needed
- Event handlers that reference state
- Async operations that update state
**When direct updates are fine:**
- Setting state to a static value: `setCount(0)`
- Setting state from props/arguments only: `setName(newName)`
- State doesn't depend on previous value
**Note:** If your project has [React Compiler](https://react.dev/learn/react-compiler) enabled, the compiler can automatically optimize some cases, but functional updates are still recommended for correctness and to prevent stale closure bugs.

View File

@@ -0,0 +1,58 @@
---
title: Use Lazy State Initialization
impact: MEDIUM
impactDescription: wasted computation on every render
tags: react, hooks, useState, performance, initialization
---
## Use Lazy State Initialization
Pass a function to `useState` for expensive initial values. Without the function form, the initializer runs on every render even though the value is only used once.
**Incorrect (runs on every render):**
```tsx
function FilteredList({ items }: { items: Item[] }) {
// buildSearchIndex() runs on EVERY render, even after initialization
const [searchIndex, setSearchIndex] = useState(buildSearchIndex(items))
const [query, setQuery] = useState('')
// When query changes, buildSearchIndex runs again unnecessarily
return <SearchResults index={searchIndex} query={query} />
}
function UserProfile() {
// JSON.parse runs on every render
const [settings, setSettings] = useState(
JSON.parse(localStorage.getItem('settings') || '{}')
)
return <SettingsForm settings={settings} onChange={setSettings} />
}
```
**Correct (runs only once):**
```tsx
function FilteredList({ items }: { items: Item[] }) {
// buildSearchIndex() runs ONLY on initial render
const [searchIndex, setSearchIndex] = useState(() => buildSearchIndex(items))
const [query, setQuery] = useState('')
return <SearchResults index={searchIndex} query={query} />
}
function UserProfile() {
// JSON.parse runs only on initial render
const [settings, setSettings] = useState(() => {
const stored = localStorage.getItem('settings')
return stored ? JSON.parse(stored) : {}
})
return <SettingsForm settings={settings} onChange={setSettings} />
}
```
Use lazy initialization when computing initial values from localStorage/sessionStorage, building data structures (indexes, maps), reading from the DOM, or performing heavy transformations.
For simple primitives (`useState(0)`), direct references (`useState(props.value)`), or cheap literals (`useState({})`), the function form is unnecessary.

View File

@@ -0,0 +1,44 @@
---
title: Extract to Memoized Components
impact: MEDIUM
impactDescription: enables early returns
tags: rerender, memo, useMemo, optimization
---
## Extract to Memoized Components
Extract expensive work into memoized components to enable early returns before computation.
**Incorrect (computes avatar even when loading):**
```tsx
function Profile({ user, loading }: Props) {
const avatar = useMemo(() => {
const id = computeAvatarId(user)
return <Avatar id={id} />
}, [user])
if (loading) return <Skeleton />
return <div>{avatar}</div>
}
```
**Correct (skips computation when loading):**
```tsx
const UserAvatar = memo(function UserAvatar({ user }: { user: User }) {
const id = useMemo(() => computeAvatarId(user), [user])
return <Avatar id={id} />
})
function Profile({ user, loading }: Props) {
if (loading) return <Skeleton />
return (
<div>
<UserAvatar user={user} />
</div>
)
}
```
**Note:** If your project has [React Compiler](https://react.dev/learn/react-compiler) enabled, manual memoization with `memo()` and `useMemo()` is not necessary. The compiler automatically optimizes re-renders.

View File

@@ -0,0 +1,40 @@
---
title: Use Transitions for Non-Urgent Updates
impact: MEDIUM
impactDescription: maintains UI responsiveness
tags: rerender, transitions, startTransition, performance
---
## Use Transitions for Non-Urgent Updates
Mark frequent, non-urgent state updates as transitions to maintain UI responsiveness.
**Incorrect (blocks UI on every scroll):**
```tsx
function ScrollTracker() {
const [scrollY, setScrollY] = useState(0)
useEffect(() => {
const handler = () => setScrollY(window.scrollY)
window.addEventListener('scroll', handler, { passive: true })
return () => window.removeEventListener('scroll', handler)
}, [])
}
```
**Correct (non-blocking updates):**
```tsx
import { startTransition } from 'react'
function ScrollTracker() {
const [scrollY, setScrollY] = useState(0)
useEffect(() => {
const handler = () => {
startTransition(() => setScrollY(window.scrollY))
}
window.addEventListener('scroll', handler, { passive: true })
return () => window.removeEventListener('scroll', handler)
}, [])
}
```

View File

@@ -0,0 +1,73 @@
---
title: Use after() for Non-Blocking Operations
impact: MEDIUM
impactDescription: faster response times
tags: server, async, logging, analytics, side-effects
---
## Use after() for Non-Blocking Operations
Use Next.js's `after()` to schedule work that should execute after a response is sent. This prevents logging, analytics, and other side effects from blocking the response.
**Incorrect (blocks response):**
```tsx
import { logUserAction } from '@/app/utils'
export async function POST(request: Request) {
// Perform mutation
await updateDatabase(request)
// Logging blocks the response
const userAgent = request.headers.get('user-agent') || 'unknown'
await logUserAction({ userAgent })
return new Response(JSON.stringify({ status: 'success' }), {
status: 200,
headers: { 'Content-Type': 'application/json' }
})
}
```
**Correct (non-blocking):**
```tsx
import { after } from 'next/server'
import { headers, cookies } from 'next/headers'
import { logUserAction } from '@/app/utils'
export async function POST(request: Request) {
// Perform mutation
await updateDatabase(request)
// Log after response is sent
after(async () => {
const userAgent = (await headers()).get('user-agent') || 'unknown'
const sessionCookie = (await cookies()).get('session-id')?.value || 'anonymous'
logUserAction({ sessionCookie, userAgent })
})
return new Response(JSON.stringify({ status: 'success' }), {
status: 200,
headers: { 'Content-Type': 'application/json' }
})
}
```
The response is sent immediately while logging happens in the background.
**Common use cases:**
- Analytics tracking
- Audit logging
- Sending notifications
- Cache invalidation
- Cleanup tasks
**Important notes:**
- `after()` runs even if the response fails or redirects
- Works in Server Actions, Route Handlers, and Server Components
Reference: [https://nextjs.org/docs/app/api-reference/functions/after](https://nextjs.org/docs/app/api-reference/functions/after)

View File

@@ -0,0 +1,41 @@
---
title: Cross-Request LRU Caching
impact: HIGH
impactDescription: caches across requests
tags: server, cache, lru, cross-request
---
## Cross-Request LRU Caching
`React.cache()` only works within one request. For data shared across sequential requests (user clicks button A then button B), use an LRU cache.
**Implementation:**
```typescript
import { LRUCache } from 'lru-cache'
const cache = new LRUCache<string, any>({
max: 1000,
ttl: 5 * 60 * 1000 // 5 minutes
})
export async function getUser(id: string) {
const cached = cache.get(id)
if (cached) return cached
const user = await db.user.findUnique({ where: { id } })
cache.set(id, user)
return user
}
// Request 1: DB query, result cached
// Request 2: cache hit, no DB query
```
Use when sequential user actions hit multiple endpoints needing the same data within seconds.
**With Vercel's [Fluid Compute](https://vercel.com/docs/fluid-compute):** LRU caching is especially effective because multiple concurrent requests can share the same function instance and cache. This means the cache persists across requests without needing external storage like Redis.
**In traditional serverless:** Each invocation runs in isolation, so consider Redis for cross-process caching.
Reference: [https://github.com/isaacs/node-lru-cache](https://github.com/isaacs/node-lru-cache)

View File

@@ -0,0 +1,26 @@
---
title: Per-Request Deduplication with React.cache()
impact: MEDIUM
impactDescription: deduplicates within request
tags: server, cache, react-cache, deduplication
---
## Per-Request Deduplication with React.cache()
Use `React.cache()` for server-side request deduplication. Authentication and database queries benefit most.
**Usage:**
```typescript
import { cache } from 'react'
export const getCurrentUser = cache(async () => {
const session = await auth()
if (!session?.user?.id) return null
return await db.user.findUnique({
where: { id: session.user.id }
})
})
```
Within a single request, multiple calls to `getCurrentUser()` execute the query only once.

View File

@@ -0,0 +1,79 @@
---
title: Parallel Data Fetching with Component Composition
impact: CRITICAL
impactDescription: eliminates server-side waterfalls
tags: server, rsc, parallel-fetching, composition
---
## Parallel Data Fetching with Component Composition
React Server Components execute sequentially within a tree. Restructure with composition to parallelize data fetching.
**Incorrect (Sidebar waits for Page's fetch to complete):**
```tsx
export default async function Page() {
const header = await fetchHeader()
return (
<div>
<div>{header}</div>
<Sidebar />
</div>
)
}
async function Sidebar() {
const items = await fetchSidebarItems()
return <nav>{items.map(renderItem)}</nav>
}
```
**Correct (both fetch simultaneously):**
```tsx
async function Header() {
const data = await fetchHeader()
return <div>{data}</div>
}
async function Sidebar() {
const items = await fetchSidebarItems()
return <nav>{items.map(renderItem)}</nav>
}
export default function Page() {
return (
<div>
<Header />
<Sidebar />
</div>
)
}
```
**Alternative with children prop:**
```tsx
async function Layout({ children }: { children: ReactNode }) {
const header = await fetchHeader()
return (
<div>
<div>{header}</div>
{children}
</div>
)
}
async function Sidebar() {
const items = await fetchSidebarItems()
return <nav>{items.map(renderItem)}</nav>
}
export default function Page() {
return (
<Layout>
<Sidebar />
</Layout>
)
}
```

View File

@@ -0,0 +1,38 @@
---
title: Minimize Serialization at RSC Boundaries
impact: HIGH
impactDescription: reduces data transfer size
tags: server, rsc, serialization, props
---
## Minimize Serialization at RSC Boundaries
The React Server/Client boundary serializes all object properties into strings and embeds them in the HTML response and subsequent RSC requests. This serialized data directly impacts page weight and load time, so **size matters a lot**. Only pass fields that the client actually uses.
**Incorrect (serializes all 50 fields):**
```tsx
async function Page() {
const user = await fetchUser() // 50 fields
return <Profile user={user} />
}
'use client'
function Profile({ user }: { user: User }) {
return <div>{user.name}</div> // uses 1 field
}
```
**Correct (serializes only 1 field):**
```tsx
async function Page() {
const user = await fetchUser()
return <Profile name={user.name} />
}
'use client'
function Profile({ name }: { name: string }) {
return <div>{name}</div>
}
```

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>
```

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version = 1
test_patterns = ["**/*.spec.ts","**/*_test.py","**/*_tests.py","**/test_*.py"]
exclude_patterns = ["classic/**"]
[[analyzers]]
name = "javascript"
[analyzers.meta]
plugins = ["react"]
environment = ["nodejs"]
[[analyzers]]
name = "python"
[analyzers.meta]
runtime_version = "3.x.x"

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# Ignore everything by default, selectively add things to context
*
# Documentation (for embeddings/search)
!docs/
# Platform - Libs
!autogpt_platform/autogpt_libs/
# Platform - Backend
!autogpt_platform/backend/
# Platform - Frontend
!autogpt_platform/frontend/
# Classic - AutoGPT
!classic/original_autogpt/autogpt/
!classic/original_autogpt/pyproject.toml
!classic/original_autogpt/poetry.lock
!classic/original_autogpt/README.md
!classic/original_autogpt/tests/
# Classic - Benchmark
!classic/benchmark/agbenchmark/
!classic/benchmark/pyproject.toml
!classic/benchmark/poetry.lock
!classic/benchmark/README.md
# Classic - Forge
!classic/forge/
!classic/forge/pyproject.toml
!classic/forge/poetry.lock
!classic/forge/README.md
# Classic - Frontend
!classic/frontend/build/web/
# Explicitly re-ignore unwanted files from whitelisted directories
# Note: These patterns MUST come after the whitelist rules to take effect
# Hidden files and directories (but keep frontend .env files needed for build)
**/.*
!autogpt_platform/frontend/.env
!autogpt_platform/frontend/.env.default
!autogpt_platform/frontend/.env.production
# Python artifacts
**/__pycache__/
**/*.pyc
**/*.pyo
**/.venv/
**/.ruff_cache/
**/.pytest_cache/
**/.coverage
**/htmlcov/
# Node artifacts
**/node_modules/
**/.next/
**/storybook-static/
**/playwright-report/
**/test-results/
# Build artifacts
**/dist/
**/build/
!autogpt_platform/frontend/src/**/build/
**/target/
# Logs and temp files
**/*.log
**/*.tmp

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.gitattributes vendored Normal file
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classic/frontend/build/** linguist-generated
**/poetry.lock linguist-generated
docs/_javascript/** linguist-vendored
# Exclude VCR cassettes from stats
classic/forge/tests/vcr_cassettes/**/**.y*ml linguist-generated
* text=auto

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* @Significant-Gravitas/maintainers
.github/workflows/ @Significant-Gravitas/devops
classic/forge/ @Significant-Gravitas/forge-maintainers
classic/benchmark/ @Significant-Gravitas/benchmark-maintainers
classic/frontend/ @Significant-Gravitas/frontend-maintainers
autogpt_platform/infra @Significant-Gravitas/devops
.github/CODEOWNERS @Significant-Gravitas/admins

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name: Bug report 🐛
description: Create a bug report for AutoGPT.
labels: ['status: needs triage']
body:
- type: markdown
attributes:
value: |
### ⚠️ Before you continue
* Check out our [backlog], [roadmap] and join our [discord] to discuss what's going on
* If you need help, you can ask in the [discussions] section or in [#tech-support]
* **Thoroughly search the [existing issues] before creating a new one**
* Read our [wiki page on Contributing]
[backlog]: https://github.com/orgs/Significant-Gravitas/projects/1
[roadmap]: https://github.com/orgs/Significant-Gravitas/projects/2
[discord]: https://discord.gg/autogpt
[discussions]: https://github.com/Significant-Gravitas/AutoGPT/discussions
[#tech-support]: https://discord.com/channels/1092243196446249134/1092275629602394184
[existing issues]: https://github.com/Significant-Gravitas/AutoGPT/issues?q=is%3Aissue
[wiki page on Contributing]: https://github.com/Significant-Gravitas/AutoGPT/wiki/Contributing
- type: checkboxes
attributes:
label: ⚠️ Search for existing issues first ⚠️
description: >
Please [search the history](https://github.com/Significant-Gravitas/AutoGPT/issues)
to see if an issue already exists for the same problem.
options:
- label: I have searched the existing issues, and there is no existing issue for my problem
required: true
- type: markdown
attributes:
value: |
Please confirm that the issue you have is described well and precise in the title above ⬆️.
A good rule of thumb: What would you type if you were searching for the issue?
For example:
BAD - my AutoGPT keeps looping
GOOD - After performing execute_python_file, AutoGPT goes into a loop where it keeps trying to execute the file.
⚠️ SUPER-busy repo, please help the volunteer maintainers.
The less time we spend here, the more time we can spend building AutoGPT.
Please help us help you by following these steps:
- Search for existing issues, adding a comment when you have the same or similar issue is tidier than "new issue" and
newer issues will not be reviewed earlier, this is dependent on the current priorities set by our wonderful team
- Ask on our Discord if your issue is known when you are unsure (https://discord.gg/autogpt)
- Provide relevant info:
- Provide commit-hash (`git rev-parse HEAD` gets it) if possible
- If it's a pip/packages issue, mention this in the title and provide pip version, python version
- If it's a crash, provide traceback and describe the error you got as precise as possible in the title.
- type: dropdown
attributes:
label: Which Operating System are you using?
description: >
Please select the operating system you were using to run AutoGPT when this problem occurred.
options:
- Windows
- Linux
- MacOS
- Docker
- Devcontainer / Codespace
- Windows Subsystem for Linux (WSL)
- Other
validations:
required: true
nested_fields:
- type: text
attributes:
label: Specify the system
description: Please specify the system you are working on.
- type: dropdown
attributes:
label: Which version of AutoGPT are you using?
description: |
Please select which version of AutoGPT you were using when this issue occurred.
If you downloaded the code from the [releases page](https://github.com/Significant-Gravitas/AutoGPT/releases/) make sure you were using the latest code.
**If you weren't please try with the [latest code](https://github.com/Significant-Gravitas/AutoGPT/releases/)**.
If installed with git you can run `git branch` to see which version of AutoGPT you are running.
options:
- Latest Release
- Stable (branch)
- Master (branch)
validations:
required: true
- type: dropdown
attributes:
label: What LLM Provider do you use?
description: >
If you are using AutoGPT with `SMART_LLM=gpt-3.5-turbo`, your problems may be caused by
the [limitations](https://github.com/Significant-Gravitas/AutoGPT/issues?q=is%3Aissue+label%3A%22AI+model+limitation%22) of GPT-3.5.
options:
- Azure
- Groq
- Anthropic
- Llamafile
- Other (detail in issue)
validations:
required: true
- type: dropdown
attributes:
label: Which area covers your issue best?
description: >
Select the area related to the issue you are reporting.
options:
- Installation and setup
- Memory
- Performance
- Prompt
- Commands
- Plugins
- AI Model Limitations
- Challenges
- Documentation
- Logging
- Agents
- Other
validations:
required: true
autolabels: true
nested_fields:
- type: text
attributes:
label: Specify the area
description: Please specify the area you think is best related to the issue.
- type: input
attributes:
label: What commit or version are you using?
description: It is helpful for us to reproduce to know what version of the software you were using when this happened. Please run `git log -n 1 --pretty=format:"%H"` to output the full commit hash.
validations:
required: true
- type: textarea
attributes:
label: Describe your issue.
description: Describe the problem you are experiencing. Try to describe only the issue and phrase it short but clear. ⚠️ Provide NO other data in this field
validations:
required: true
#Following are optional file content uploads
- type: markdown
attributes:
value: |
The following is OPTIONAL, please keep in mind that the log files may contain personal information such as credentials.⚠️
"The log files are located in the folder 'logs' inside the main AutoGPT folder."
- type: textarea
attributes:
label: Upload Activity Log Content
description: |
Upload the activity log content, this can help us understand the issue better.
To do this, go to the folder logs in your main AutoGPT folder, open activity.log and copy/paste the contents to this field.
⚠️ The activity log may contain personal data given to AutoGPT by you in prompt or input as well as
any personal information that AutoGPT collected out of files during last run. Do not add the activity log if you are not comfortable with sharing it. ⚠️
validations:
required: false
- type: textarea
attributes:
label: Upload Error Log Content
description: |
Upload the error log content, this will help us understand the issue better.
To do this, go to the folder logs in your main AutoGPT folder, open error.log and copy/paste the contents to this field.
⚠️ The error log may contain personal data given to AutoGPT by you in prompt or input as well as
any personal information that AutoGPT collected out of files during last run. Do not add the activity log if you are not comfortable with sharing it. ⚠️
validations:
required: false

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name: Feature request 🚀
description: Suggest a new idea for AutoGPT!
labels: ['status: needs triage']
body:
- type: markdown
attributes:
value: |
First, check out our [wiki page on Contributing](https://github.com/Significant-Gravitas/AutoGPT/wiki/Contributing)
Please provide a searchable summary of the issue in the title above ⬆️.
- type: checkboxes
attributes:
label: Duplicates
description: Please [search the history](https://github.com/Significant-Gravitas/AutoGPT/issues) to see if an issue already exists for the same problem.
options:
- label: I have searched the existing issues
required: true
- type: textarea
attributes:
label: Summary 💡
description: Describe how it should work.
- type: textarea
attributes:
label: Examples 🌈
description: Provide a link to other implementations, or screenshots of the expected behavior.
- type: textarea
attributes:
label: Motivation 🔦
description: What are you trying to accomplish? How has the lack of this feature affected you? Providing context helps us come up with a solution that is more useful in the real world.

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### 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 🏗️
<!-- List the key changes. Keep it higher level than the diff but specific enough to highlight what's new/modified. -->
### 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:
<!-- Put your test plan here: -->
- [ ] ...
<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>

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# GitHub Copilot Instructions for AutoGPT
This file provides comprehensive onboarding information for GitHub Copilot coding agent to work efficiently with the AutoGPT repository.
## Repository Overview
**AutoGPT** is a powerful platform for creating, deploying, and managing continuous AI agents that automate complex workflows. This is a large monorepo (~150MB) containing multiple components:
- **AutoGPT Platform** (`autogpt_platform/`) - Main focus: Modern AI agent platform (Polyform Shield License)
- **Classic AutoGPT** (`classic/`) - Legacy agent system (MIT License)
- **Documentation** (`docs/`) - MkDocs-based documentation site
- **Infrastructure** - Docker configurations, CI/CD, and development tools
**Primary Languages & Frameworks:**
- **Backend**: Python 3.10-3.13, FastAPI, Prisma ORM, PostgreSQL, RabbitMQ
- **Frontend**: TypeScript, Next.js 15, React, Tailwind CSS, Radix UI
- **Development**: Docker, Poetry, pnpm, Playwright, Storybook
## Build and Validation Instructions
### Essential Setup Commands
**Always run these commands in the correct directory and in this order:**
1. **Initial Setup** (required once):
```bash
# Clone and enter repository
git clone <repo> && cd AutoGPT
# Start all services (database, redis, rabbitmq, clamav)
cd autogpt_platform && docker compose --profile local up deps --build --detach
```
2. **Backend Setup** (always run before backend development):
```bash
cd autogpt_platform/backend
poetry install # Install dependencies
poetry run prisma migrate dev # Run database migrations
poetry run prisma generate # Generate Prisma client
```
3. **Frontend Setup** (always run before frontend development):
```bash
cd autogpt_platform/frontend
pnpm install # Install dependencies
```
### Runtime Requirements
**Critical:** Always ensure Docker services are running before starting development:
```bash
cd autogpt_platform && docker compose --profile local up deps --build --detach
```
**Python Version:** Use Python 3.11 (required; managed by Poetry via pyproject.toml)
**Node.js Version:** Use Node.js 21+ with pnpm package manager
### Development Commands
**Backend Development:**
```bash
cd autogpt_platform/backend
poetry run serve # Start development server (port 8000)
poetry run test # Run all tests (requires ~5 minutes)
poetry run pytest path/to/test.py # Run specific test
poetry run format # Format code (Black + isort) - always run first
poetry run lint # Lint code (ruff) - run after format
```
**Frontend Development:**
```bash
cd autogpt_platform/frontend
pnpm dev # Start development server (port 3000) - use for active development
pnpm build # Build for production (only needed for E2E tests or deployment)
pnpm test # Run Playwright E2E tests (requires build first)
pnpm test-ui # Run tests with UI
pnpm format # Format and lint code
pnpm storybook # Start component development server
```
### Testing Strategy
**Backend Tests:**
- **Block Tests**: `poetry run pytest backend/blocks/test/test_block.py -xvs` (validates all blocks)
- **Specific Block**: `poetry run pytest 'backend/blocks/test/test_block.py::test_available_blocks[BlockName]' -xvs`
- **Snapshot Tests**: Use `--snapshot-update` when output changes, always review with `git diff`
**Frontend Tests:**
- **E2E Tests**: Always run `pnpm dev` before `pnpm test` (Playwright requires running instance)
- **Component Tests**: Use Storybook for isolated component development
### Critical Validation Steps
**Before committing changes:**
1. Run `poetry run format` (backend) and `pnpm format` (frontend)
2. Ensure all tests pass in modified areas
3. Verify Docker services are still running
4. Check that database migrations apply cleanly
**Common Issues & Workarounds:**
- **Prisma issues**: Run `poetry run prisma generate` after schema changes
- **Permission errors**: Ensure Docker has proper permissions
- **Port conflicts**: Check the `docker-compose.yml` file for the current list of exposed ports. You can list all mapped ports with:
- **Test timeouts**: Backend tests can take 5+ minutes, use `-x` flag to stop on first failure
## Project Layout & Architecture
### Core Architecture
**AutoGPT Platform** (`autogpt_platform/`):
- `backend/` - FastAPI server with async support
- `backend/backend/` - Core API logic
- `backend/blocks/` - Agent execution blocks
- `backend/data/` - Database models and schemas
- `schema.prisma` - Database schema definition
- `frontend/` - Next.js application
- `src/app/` - App Router pages and layouts
- `src/components/` - Reusable React components
- `src/lib/` - Utilities and configurations
- `autogpt_libs/` - Shared Python utilities
- `docker-compose.yml` - Development stack orchestration
**Key Configuration Files:**
- `pyproject.toml` - Python dependencies and tooling
- `package.json` - Node.js dependencies and scripts
- `schema.prisma` - Database schema and migrations
- `next.config.mjs` - Next.js configuration
- `tailwind.config.ts` - Styling configuration
### Security & Middleware
**Cache Protection**: Backend includes middleware preventing sensitive data caching in browsers/proxies
**Authentication**: JWT-based with Supabase integration
**User ID Validation**: All data access requires user ID checks - verify this for any `data/*.py` changes
### Development Workflow
**GitHub Actions**: Multiple CI/CD workflows in `.github/workflows/`
- `platform-backend-ci.yml` - Backend testing and validation
- `platform-frontend-ci.yml` - Frontend testing and validation
- `platform-fullstack-ci.yml` - End-to-end integration tests
**Pre-commit Hooks**: Run linting and formatting checks
**Conventional Commits**: Use format `type(scope): description` (e.g., `feat(backend): add API`)
### Key Source Files
**Backend Entry Points:**
- `backend/backend/api/rest_api.py` - FastAPI application setup
- `backend/backend/data/` - Database models and user management
- `backend/blocks/` - Agent execution blocks and logic
**Frontend Entry Points:**
- `frontend/src/app/layout.tsx` - Root application layout
- `frontend/src/app/page.tsx` - Home page
- `frontend/src/lib/supabase/` - Authentication and database client
**Protected Routes**: Update `frontend/lib/supabase/middleware.ts` when adding protected routes
### Agent Block System
Agents are built using a visual block-based system where each block performs a single action. Blocks are defined in `backend/blocks/` and must include:
- Block definition with input/output schemas
- Execution logic with proper error handling
- Tests validating functionality
### Database & ORM
**Prisma ORM** with PostgreSQL backend including pgvector for embeddings:
- Schema in `schema.prisma`
- Migrations in `backend/migrations/`
- Always run `prisma migrate dev` and `prisma generate` after schema changes
## Environment Configuration
### Configuration Files Priority Order
1. **Backend**: `/backend/.env.default` → `/backend/.env` (user overrides)
2. **Frontend**: `/frontend/.env.default` → `/frontend/.env` (user overrides)
3. **Platform**: `/.env.default` (Supabase/shared) → `/.env` (user overrides)
4. Docker Compose `environment:` sections override file-based config
5. Shell environment variables have highest precedence
### Docker Environment Setup
- All services use hardcoded defaults (no `${VARIABLE}` substitutions)
- The `env_file` directive loads variables INTO containers at runtime
- Backend/Frontend services use YAML anchors for consistent configuration
- Copy `.env.default` files to `.env` for local development customization
## Advanced Development Patterns
### Adding New Blocks
1. Create file in `/backend/backend/blocks/`
2. Inherit from `Block` base class with input/output schemas
3. Implement `run` method with proper error handling
4. Generate block UUID using `uuid.uuid4()`
5. Register in block registry
6. Write tests alongside block implementation
7. Consider how inputs/outputs connect with other blocks in graph editor
### API Development
1. Update routes in `/backend/backend/api/features/`
2. Add/update Pydantic models in same directory
3. Write tests alongside route files
4. For `data/*.py` changes, validate user ID checks
5. Run `poetry run test` to verify changes
### Frontend Development
**📖 Complete Frontend Guide**: See `autogpt_platform/frontend/CONTRIBUTING.md` and `autogpt_platform/frontend/.cursorrules` for comprehensive patterns and conventions.
**Quick Reference:**
**Component Structure:**
- Separate render logic from data/behavior
- Structure: `ComponentName/ComponentName.tsx` + `useComponentName.ts` + `helpers.ts`
- Exception: Small components (3-4 lines of logic) can be inline
- Render-only components can be direct files without folders
**Data Fetching:**
- Use generated API hooks from `@/app/api/__generated__/endpoints/`
- Generated via Orval from backend OpenAPI spec
- Pattern: `use{Method}{Version}{OperationName}`
- Example: `useGetV2ListLibraryAgents`
- Regenerate with: `pnpm generate:api`
- **Never** use deprecated `BackendAPI` or `src/lib/autogpt-server-api/*`
**Code Conventions:**
- Use function declarations for components and handlers (not arrow functions)
- Only arrow functions for small inline lambdas (map, filter, etc.)
- Components: `PascalCase`, Hooks: `camelCase` with `use` prefix
- No barrel files or `index.ts` re-exports
- Minimal comments (code should be self-documenting)
**Styling:**
- Use Tailwind CSS utilities only
- Use design system components from `src/components/` (atoms, molecules, organisms)
- Never use `src/components/__legacy__/*`
- Only use Phosphor Icons (`@phosphor-icons/react`)
- Prefer design tokens over hardcoded values
**Error Handling:**
- Render errors: Use `<ErrorCard />` component
- Mutation errors: Display with toast notifications
- Manual exceptions: Use `Sentry.captureException()`
- Global error boundaries already configured
**Testing:**
- Add/update Storybook stories for UI components (`pnpm storybook`)
- Run Playwright E2E tests with `pnpm test`
- Verify in Chromatic after PR
**Architecture:**
- Default to client components ("use client")
- Server components only for SEO or extreme TTFB needs
- Use React Query for server state (via generated hooks)
- Co-locate UI state in components/hooks
### Security Guidelines
**Cache Protection Middleware** (`/backend/backend/api/middleware/security.py`):
- Default: Disables caching for ALL endpoints with `Cache-Control: no-store, no-cache, must-revalidate, private`
- Uses allow list approach for cacheable paths (static assets, health checks, public pages)
- Prevents sensitive data caching in browsers/proxies
- Add new cacheable endpoints to `CACHEABLE_PATHS`
### CI/CD Alignment
The repository has comprehensive CI workflows that test:
- **Backend**: Python 3.11-3.13, services (Redis/RabbitMQ/ClamAV), Prisma migrations, Poetry lock validation
- **Frontend**: Node.js 21, pnpm, Playwright with Docker Compose stack, API schema validation
- **Integration**: Full-stack type checking and E2E testing
Match these patterns when developing locally - the copilot setup environment mirrors these CI configurations.
## Collaboration with Other AI Assistants
This repository is actively developed with assistance from Claude (via CLAUDE.md files). When working on this codebase:
- Check for existing CLAUDE.md files that provide additional context
- Follow established patterns and conventions already in the codebase
- Maintain consistency with existing code style and architecture
- Consider that changes may be reviewed and extended by both human developers and AI assistants
## Trust These Instructions
These instructions are comprehensive and tested. Only perform additional searches if:
1. Information here is incomplete for your specific task
2. You encounter errors not covered by the workarounds
3. You need to understand implementation details not covered above
For detailed platform development patterns, refer to `autogpt_platform/CLAUDE.md` and `AGENTS.md` in the repository root.

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version: 2
updates:
# autogpt_libs (Poetry project)
- package-ecosystem: "pip"
directory: "autogpt_platform/autogpt_libs"
schedule:
interval: "weekly"
open-pull-requests-limit: 10
target-branch: "dev"
commit-message:
prefix: "chore(libs/deps)"
prefix-development: "chore(libs/deps-dev)"
ignore:
- dependency-name: "poetry"
groups:
production-dependencies:
dependency-type: "production"
update-types:
- "minor"
- "patch"
development-dependencies:
dependency-type: "development"
update-types:
- "minor"
- "patch"
# backend (Poetry project)
- package-ecosystem: "pip"
directory: "autogpt_platform/backend"
schedule:
interval: "weekly"
open-pull-requests-limit: 10
target-branch: "dev"
commit-message:
prefix: "chore(backend/deps)"
prefix-development: "chore(backend/deps-dev)"
ignore:
- dependency-name: "poetry"
groups:
production-dependencies:
dependency-type: "production"
update-types:
- "minor"
- "patch"
development-dependencies:
dependency-type: "development"
update-types:
- "minor"
- "patch"
# frontend (Next.js project)
- package-ecosystem: "npm"
directory: "autogpt_platform/frontend"
schedule:
interval: "weekly"
open-pull-requests-limit: 10
target-branch: "dev"
commit-message:
prefix: "chore(frontend/deps)"
prefix-development: "chore(frontend/deps-dev)"
groups:
production-dependencies:
dependency-type: "production"
update-types:
- "minor"
- "patch"
development-dependencies:
dependency-type: "development"
update-types:
- "minor"
- "patch"
# infra (Terraform)
- package-ecosystem: "terraform"
directory: "autogpt_platform/infra"
schedule:
interval: "weekly"
open-pull-requests-limit: 5
target-branch: "dev"
commit-message:
prefix: "chore(infra/deps)"
prefix-development: "chore(infra/deps-dev)"
groups:
production-dependencies:
dependency-type: "production"
update-types:
- "minor"
- "patch"
development-dependencies:
dependency-type: "development"
update-types:
- "minor"
- "patch"
# GitHub Actions
- package-ecosystem: "github-actions"
directory: "/"
schedule:
interval: "weekly"
open-pull-requests-limit: 5
target-branch: "dev"
groups:
production-dependencies:
dependency-type: "production"
update-types:
- "minor"
- "patch"
development-dependencies:
dependency-type: "development"
update-types:
- "minor"
- "patch"
# Docker
- package-ecosystem: "docker"
directory: "autogpt_platform/"
schedule:
interval: "weekly"
open-pull-requests-limit: 5
target-branch: "dev"
groups:
production-dependencies:
dependency-type: "production"
update-types:
- "minor"
- "patch"
development-dependencies:
dependency-type: "development"
update-types:
- "minor"
- "patch"
# Docs
- package-ecosystem: "pip"
directory: "docs/"
schedule:
interval: "weekly"
open-pull-requests-limit: 1
target-branch: "dev"
commit-message:
prefix: "chore(docs/deps)"
groups:
production-dependencies:
dependency-type: "production"
update-types:
- "minor"
- "patch"
development-dependencies:
dependency-type: "development"
update-types:
- "minor"
- "patch"

33
.github/labeler.yml vendored Normal file
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Classic AutoGPT Agent:
- changed-files:
- any-glob-to-any-file: classic/original_autogpt/**
Classic Benchmark:
- changed-files:
- any-glob-to-any-file: classic/benchmark/**
Classic Frontend:
- changed-files:
- any-glob-to-any-file: classic/frontend/**
Forge:
- changed-files:
- any-glob-to-any-file: classic/forge/**
documentation:
- changed-files:
- any-glob-to-any-file: docs/**
platform/frontend:
- changed-files:
- any-glob-to-any-file: autogpt_platform/frontend/**
platform/backend:
- changed-files:
- all-globs-to-any-file:
- autogpt_platform/backend/**
- '!autogpt_platform/backend/backend/blocks/**'
platform/blocks:
- changed-files:
- any-glob-to-any-file: autogpt_platform/backend/backend/blocks/**

1229
.github/scripts/detect_overlaps.py vendored Normal file

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.github/workflows/classic-autogpt-ci.yml vendored Normal file
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name: Classic - AutoGPT CI
on:
push:
branches: [ master, dev, ci-test* ]
paths:
- '.github/workflows/classic-autogpt-ci.yml'
- 'classic/original_autogpt/**'
pull_request:
branches: [ master, dev, release-* ]
paths:
- '.github/workflows/classic-autogpt-ci.yml'
- 'classic/original_autogpt/**'
concurrency:
group: ${{ format('classic-autogpt-ci-{0}', github.head_ref && format('{0}-{1}', github.event_name, github.event.pull_request.number) || github.sha) }}
cancel-in-progress: ${{ startsWith(github.event_name, 'pull_request') }}
defaults:
run:
shell: bash
working-directory: classic/original_autogpt
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' }}
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'
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: Configure git user Auto-GPT-Bot
run: |
git config --global user.name "Auto-GPT-Bot"
git config --global user.email "github-bot@agpt.co"
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
- id: get_date
name: Get date
run: echo "date=$(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 }}-${{ hashFiles('classic/original_autogpt/poetry.lock') }}
- name: Install Poetry (Unix)
if: runner.os != 'Windows'
run: |
curl -sSL https://install.python-poetry.org | python3 -
if [ "${{ 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=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
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' || '' }}
AWS_ACCESS_KEY_ID: minioadmin
AWS_SECRET_ACCESS_KEY: minioadmin
- 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: ${{ secrets.CODECOV_TOKEN }}
flags: autogpt-agent,${{ runner.os }}
- name: Upload logs to artifact
if: always()
uses: actions/upload-artifact@v4
with:
name: test-logs
path: classic/original_autogpt/logs/

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@@ -0,0 +1,60 @@
name: Classic - Purge Auto-GPT Docker CI cache
on:
schedule:
- cron: 20 4 * * 1,4
env:
BASE_BRANCH: dev
IMAGE_NAME: auto-gpt
jobs:
build:
runs-on: ubuntu-latest
strategy:
matrix:
build-type: [release, dev]
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- id: build
name: Build image
uses: docker/build-push-action@v6
with:
context: classic/
file: classic/Dockerfile.autogpt
build-args: BUILD_TYPE=${{ matrix.build-type }}
load: true # save to docker images
# use GHA cache as read-only
cache-to: type=gha,scope=autogpt-docker-${{ matrix.build-type }},mode=max
- name: Generate build report
env:
event_name: ${{ github.event_name }}
event_ref: ${{ github.event.schedule }}
build_type: ${{ matrix.build-type }}
prod_branch: master
dev_branch: dev
repository: ${{ github.repository }}
base_branch: ${{ github.ref_name != 'master' && github.ref_name != 'dev' && 'dev' || 'master' }}
current_ref: ${{ github.ref_name }}
commit_hash: ${{ github.sha }}
source_url: ${{ format('{0}/tree/{1}', github.event.repository.url, github.sha) }}
push_forced_label:
new_commits_json: ${{ null }}
compare_url_template: ${{ format('/{0}/compare/{{base}}...{{head}}', github.repository) }}
github_context_json: ${{ toJSON(github) }}
job_env_json: ${{ toJSON(env) }}
vars_json: ${{ toJSON(vars) }}
run: .github/workflows/scripts/docker-ci-summary.sh >> $GITHUB_STEP_SUMMARY
continue-on-error: true

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@@ -0,0 +1,166 @@
name: Classic - AutoGPT Docker CI
on:
push:
branches: [master, dev]
paths:
- '.github/workflows/classic-autogpt-docker-ci.yml'
- 'classic/original_autogpt/**'
- 'classic/forge/**'
pull_request:
branches: [ master, dev, release-* ]
paths:
- '.github/workflows/classic-autogpt-docker-ci.yml'
- 'classic/original_autogpt/**'
- 'classic/forge/**'
concurrency:
group: ${{ format('classic-autogpt-docker-ci-{0}', github.head_ref && format('pr-{0}', github.event.pull_request.number) || github.sha) }}
cancel-in-progress: ${{ github.event_name == 'pull_request' }}
defaults:
run:
working-directory: classic/original_autogpt
env:
IMAGE_NAME: auto-gpt
DEPLOY_IMAGE_NAME: ${{ secrets.DOCKER_USER && format('{0}/', secrets.DOCKER_USER) || '' }}auto-gpt
DEV_IMAGE_TAG: latest-dev
jobs:
build:
runs-on: ubuntu-latest
strategy:
matrix:
build-type: [release, dev]
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- if: runner.debug
run: |
ls -al
du -hs *
- id: build
name: Build image
uses: docker/build-push-action@v6
with:
context: classic/
file: classic/Dockerfile.autogpt
build-args: BUILD_TYPE=${{ matrix.build-type }}
tags: ${{ env.IMAGE_NAME }}
labels: GIT_REVISION=${{ github.sha }}
load: true # save to docker images
# cache layers in GitHub Actions cache to speed up builds
cache-from: type=gha,scope=autogpt-docker-${{ matrix.build-type }}
cache-to: type=gha,scope=autogpt-docker-${{ matrix.build-type }},mode=max
- name: Generate build report
env:
event_name: ${{ github.event_name }}
event_ref: ${{ github.event.ref }}
event_ref_type: ${{ github.event.ref}}
build_type: ${{ matrix.build-type }}
prod_branch: master
dev_branch: dev
repository: ${{ github.repository }}
base_branch: ${{ github.ref_name != 'master' && github.ref_name != 'dev' && 'dev' || 'master' }}
current_ref: ${{ github.ref_name }}
commit_hash: ${{ github.event.after }}
source_url: ${{ format('{0}/tree/{1}', github.event.repository.url, github.event.release && github.event.release.tag_name || github.sha) }}
push_forced_label: ${{ github.event.forced && '☢️ forced' || '' }}
new_commits_json: ${{ toJSON(github.event.commits) }}
compare_url_template: ${{ format('/{0}/compare/{{base}}...{{head}}', github.repository) }}
github_context_json: ${{ toJSON(github) }}
job_env_json: ${{ toJSON(env) }}
vars_json: ${{ toJSON(vars) }}
run: .github/workflows/scripts/docker-ci-summary.sh >> $GITHUB_STEP_SUMMARY
continue-on-error: true
test:
runs-on: ubuntu-latest
timeout-minutes: 10
services:
minio:
image: minio/minio:edge-cicd
options: >
--name=minio
--health-interval=10s --health-timeout=5s --health-retries=3
--health-cmd="curl -f http://localhost:9000/minio/health/live"
steps:
- name: Check out repository
uses: actions/checkout@v4
with:
submodules: true
- if: github.event_name == 'push'
name: Log in to Docker hub
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKER_USER }}
password: ${{ secrets.DOCKER_PASSWORD }}
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- id: build
name: Build image
uses: docker/build-push-action@v6
with:
context: classic/
file: classic/Dockerfile.autogpt
build-args: BUILD_TYPE=dev # include pytest
tags: >
${{ env.IMAGE_NAME }},
${{ env.DEPLOY_IMAGE_NAME }}:${{ env.DEV_IMAGE_TAG }}
labels: GIT_REVISION=${{ github.sha }}
load: true # save to docker images
# cache layers in GitHub Actions cache to speed up builds
cache-from: type=gha,scope=autogpt-docker-dev
cache-to: type=gha,scope=autogpt-docker-dev,mode=max
- id: test
name: Run tests
env:
CI: true
PLAIN_OUTPUT: True
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
S3_ENDPOINT_URL: http://minio:9000
AWS_ACCESS_KEY_ID: minioadmin
AWS_SECRET_ACCESS_KEY: minioadmin
run: |
set +e
docker run --env CI --env OPENAI_API_KEY \
--network container:minio \
--env S3_ENDPOINT_URL --env AWS_ACCESS_KEY_ID --env AWS_SECRET_ACCESS_KEY \
--entrypoint poetry ${{ env.IMAGE_NAME }} run \
pytest -v --cov=autogpt --cov-branch --cov-report term-missing \
--numprocesses=4 --durations=10 \
tests/unit tests/integration 2>&1 | tee test_output.txt
test_failure=${PIPESTATUS[0]}
cat << $EOF >> $GITHUB_STEP_SUMMARY
# Tests $([ $test_failure = 0 ] && echo '✅' || echo '❌')
\`\`\`
$(cat test_output.txt)
\`\`\`
$EOF
exit $test_failure
- if: github.event_name == 'push' && github.ref_name == 'master'
name: Push image to Docker Hub
run: docker push ${{ env.DEPLOY_IMAGE_NAME }}:${{ env.DEV_IMAGE_TAG }}

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@@ -0,0 +1,87 @@
name: Classic - AutoGPT Docker Release
on:
release:
types: [published, edited]
workflow_dispatch:
inputs:
no_cache:
type: boolean
description: 'Build from scratch, without using cached layers'
env:
IMAGE_NAME: auto-gpt
DEPLOY_IMAGE_NAME: ${{ secrets.DOCKER_USER }}/auto-gpt
jobs:
build:
if: startsWith(github.ref, 'refs/tags/autogpt-')
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Log in to Docker hub
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKER_USER }}
password: ${{ secrets.DOCKER_PASSWORD }}
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
# slashes are not allowed in image tags, but can appear in git branch or tag names
- id: sanitize_tag
name: Sanitize image tag
run: |
tag=${raw_tag//\//-}
echo tag=${tag#autogpt-} >> $GITHUB_OUTPUT
env:
raw_tag: ${{ github.ref_name }}
- id: build
name: Build image
uses: docker/build-push-action@v6
with:
context: classic/
file: Dockerfile.autogpt
build-args: BUILD_TYPE=release
load: true # save to docker images
# push: true # TODO: uncomment when this issue is fixed: https://github.com/moby/buildkit/issues/1555
tags: >
${{ env.IMAGE_NAME }},
${{ env.DEPLOY_IMAGE_NAME }}:latest,
${{ env.DEPLOY_IMAGE_NAME }}:${{ steps.sanitize_tag.outputs.tag }}
labels: GIT_REVISION=${{ github.sha }}
# cache layers in GitHub Actions cache to speed up builds
cache-from: ${{ !inputs.no_cache && 'type=gha' || '' }},scope=autogpt-docker-release
cache-to: type=gha,scope=autogpt-docker-release,mode=max
- name: Push image to Docker Hub
run: docker push --all-tags ${{ env.DEPLOY_IMAGE_NAME }}
- name: Generate build report
env:
event_name: ${{ github.event_name }}
event_ref: ${{ github.event.ref }}
event_ref_type: ${{ github.event.ref}}
inputs_no_cache: ${{ inputs.no_cache }}
prod_branch: master
dev_branch: dev
repository: ${{ github.repository }}
base_branch: ${{ github.ref_name != 'master' && github.ref_name != 'dev' && 'dev' || 'master' }}
ref_type: ${{ github.ref_type }}
current_ref: ${{ github.ref_name }}
commit_hash: ${{ github.sha }}
source_url: ${{ format('{0}/tree/{1}', github.event.repository.url, github.event.release && github.event.release.tag_name || github.sha) }}
github_context_json: ${{ toJSON(github) }}
job_env_json: ${{ toJSON(env) }}
vars_json: ${{ toJSON(vars) }}
run: .github/workflows/scripts/docker-release-summary.sh >> $GITHUB_STEP_SUMMARY
continue-on-error: true

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@@ -0,0 +1,76 @@
name: Classic - Agent smoke tests
on:
workflow_dispatch:
schedule:
- cron: '0 8 * * *'
push:
branches: [ master, dev, ci-test* ]
paths:
- '.github/workflows/classic-autogpts-ci.yml'
- 'classic/original_autogpt/**'
- 'classic/forge/**'
- 'classic/benchmark/**'
- 'classic/run'
- 'classic/cli.py'
- 'classic/setup.py'
- '!**/*.md'
pull_request:
branches: [ master, dev, release-* ]
paths:
- '.github/workflows/classic-autogpts-ci.yml'
- 'classic/original_autogpt/**'
- 'classic/forge/**'
- 'classic/benchmark/**'
- 'classic/run'
- 'classic/cli.py'
- 'classic/setup.py'
- '!**/*.md'
defaults:
run:
shell: bash
working-directory: classic
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'
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: ${{ env.min-python-version }}
- name: Install Poetry
working-directory: ./classic/${{ matrix.agent-name }}/
run: |
curl -sSL https://install.python-poetry.org | python -
- name: Run regression tests
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
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
AGENT_NAME: ${{ matrix.agent-name }}
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' }}

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@@ -0,0 +1,176 @@
name: Classic - AGBenchmark CI
on:
push:
branches: [ master, dev, ci-test* ]
paths:
- 'classic/benchmark/**'
- '!classic/benchmark/reports/**'
- .github/workflows/classic-benchmark-ci.yml
pull_request:
branches: [ master, dev, release-* ]
paths:
- 'classic/benchmark/**'
- '!classic/benchmark/reports/**'
- .github/workflows/classic-benchmark-ci.yml
concurrency:
group: ${{ format('benchmark-ci-{0}', github.head_ref && format('{0}-{1}', github.event_name, github.event.pull_request.number) || github.sha) }}
cancel-in-progress: ${{ startsWith(github.event_name, 'pull_request') }}
defaults:
run:
shell: bash
env:
min-python-version: '3.10'
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' }}
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
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: Install Poetry
run: |
curl -sSL https://install.python-poetry.org | python -
- 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
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
TELEMETRY_ENVIRONMENT: autogpt-benchmark-ci
TELEMETRY_OPT_IN: ${{ github.ref_name == 'master' }}

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name: Classic - Publish to PyPI
on:
workflow_dispatch:
jobs:
deploy:
runs-on: ubuntu-latest
permissions:
contents: write
steps:
- name: Checkout repository
uses: actions/checkout@v4
with:
submodules: true
fetch-depth: 0
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: 3.8
- name: Install Poetry
working-directory: ./classic/benchmark/
run: |
curl -sSL https://install.python-poetry.org | python3 -
echo "$HOME/.poetry/bin" >> $GITHUB_PATH
- name: Build project for distribution
working-directory: ./classic/benchmark/
run: poetry build
- name: Install dependencies
working-directory: ./classic/benchmark/
run: poetry install
- name: Check Version
working-directory: ./classic/benchmark/
id: check-version
run: |
echo version=$(poetry version --short) >> $GITHUB_OUTPUT
- name: Create Release
uses: ncipollo/release-action@v1
with:
artifacts: "classic/benchmark/dist/*"
token: ${{ secrets.GITHUB_TOKEN }}
draft: false
generateReleaseNotes: false
tag: agbenchmark-v${{ steps.check-version.outputs.version }}
commit: master
- name: Build and publish
working-directory: ./classic/benchmark/
run: poetry publish -u __token__ -p ${{ secrets.PYPI_API_TOKEN }}

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name: Classic - Forge CI
on:
push:
branches: [ master, dev, ci-test* ]
paths:
- '.github/workflows/classic-forge-ci.yml'
- 'classic/forge/**'
- '!classic/forge/tests/vcr_cassettes'
pull_request:
branches: [ master, dev, release-* ]
paths:
- '.github/workflows/classic-forge-ci.yml'
- 'classic/forge/**'
- '!classic/forge/tests/vcr_cassettes'
concurrency:
group: ${{ format('forge-ci-{0}', github.head_ref && format('{0}-{1}', github.event_name, github.event.pull_request.number) || github.sha) }}
cancel-in-progress: ${{ startsWith(github.event_name, 'pull_request') }}
defaults:
run:
shell: bash
working-directory: classic/forge
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' }}
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'
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 }}
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 }}-${{ hashFiles('classic/forge/poetry.lock') }}
- name: Install Poetry (Unix)
if: runner.os != 'Windows'
run: |
curl -sSL https://install.python-poetry.org | python3 -
if [ "${{ 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=forge --cov-branch --cov-report term-missing --cov-report xml \
--durations=10 \
--junitxml=junit.xml -o junit_family=legacy \
forge
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' || '' }}
AWS_ACCESS_KEY_ID: minioadmin
AWS_SECRET_ACCESS_KEY: minioadmin
- 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: ${{ secrets.CODECOV_TOKEN }}
flags: forge,${{ 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
- name: Upload logs to artifact
if: always()
uses: actions/upload-artifact@v4
with:
name: test-logs
path: classic/forge/logs/

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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 }}"

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name: Classic - Python checks
on:
push:
branches: [ master, dev, ci-test* ]
paths:
- '.github/workflows/classic-python-checks-ci.yml'
- 'classic/original_autogpt/**'
- 'classic/forge/**'
- 'classic/benchmark/**'
- '**.py'
- '!classic/forge/tests/vcr_cassettes'
pull_request:
branches: [ master, dev, release-* ]
paths:
- '.github/workflows/classic-python-checks-ci.yml'
- 'classic/original_autogpt/**'
- 'classic/forge/**'
- 'classic/benchmark/**'
- '**.py'
- '!classic/forge/tests/vcr_cassettes'
concurrency:
group: ${{ format('classic-python-checks-ci-{0}', github.head_ref && format('{0}-{1}', github.event_name, github.event.pull_request.number) || github.sha) }}
cancel-in-progress: ${{ startsWith(github.event_name, 'pull_request') }}
defaults:
run:
shell: bash
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
steps:
- name: Checkout repository
uses: actions/checkout@v4
with:
fetch-depth: 0
- 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: ${{ runner.os }}-poetry-${{ hashFiles(format('{0}/poetry.lock', matrix.sub-package)) }}
- name: Install Poetry
run: curl -sSL https://install.python-poetry.org | python3 -
# Install dependencies
- name: Install Python dependencies
run: poetry -C classic/${{ matrix.sub-package }} install
# Lint
- name: Lint (isort)
run: poetry run isort --check .
working-directory: classic/${{ 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
steps:
- name: Checkout repository
uses: actions/checkout@v4
with:
fetch-depth: 0
- 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: ${{ runner.os }}-poetry-${{ hashFiles(format('{0}/poetry.lock', matrix.sub-package)) }}
- name: Install Poetry
run: curl -sSL https://install.python-poetry.org | python3 -
# Install dependencies
- name: Install Python dependencies
run: poetry -C classic/${{ matrix.sub-package }} install
# Typecheck
- name: Typecheck
if: success() || failure()
run: poetry run pyright
working-directory: classic/${{ matrix.sub-package }}

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name: Auto Fix CI Failures
on:
workflow_run:
workflows: ["CI"]
types:
- completed
permissions:
contents: write
pull-requests: write
actions: read
issues: write
id-token: write # Required for OIDC token exchange
jobs:
auto-fix:
if: |
github.event.workflow_run.conclusion == 'failure' &&
github.event.workflow_run.pull_requests[0] &&
!startsWith(github.event.workflow_run.head_branch, 'claude-auto-fix-ci-')
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v6
with:
ref: ${{ github.event.workflow_run.head_branch }}
fetch-depth: 0
token: ${{ secrets.GITHUB_TOKEN }}
- name: Setup git identity
run: |
git config --global user.email "claude[bot]@users.noreply.github.com"
git config --global user.name "claude[bot]"
- name: Create fix branch
id: branch
run: |
BRANCH_NAME="claude-auto-fix-ci-${{ github.event.workflow_run.head_branch }}-${{ github.run_id }}"
git checkout -b "$BRANCH_NAME"
echo "branch_name=$BRANCH_NAME" >> $GITHUB_OUTPUT
# Backend Python/Poetry setup (so Claude can run linting/tests)
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.11"
- name: Set up Python dependency cache
uses: actions/cache@v5
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
- name: Install Poetry
run: |
cd autogpt_platform/backend
HEAD_POETRY_VERSION=$(python3 ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
curl -sSL https://install.python-poetry.org | POETRY_VERSION=$HEAD_POETRY_VERSION python3 -
echo "$HOME/.local/bin" >> $GITHUB_PATH
- name: Install Python dependencies
working-directory: autogpt_platform/backend
run: poetry install
- name: Generate Prisma Client
working-directory: autogpt_platform/backend
run: poetry run prisma generate && poetry run gen-prisma-stub
# Frontend Node.js/pnpm setup (so Claude can run linting/tests)
- name: Enable corepack
run: corepack enable
- name: Set up Node.js
uses: actions/setup-node@v6
with:
node-version: "22"
cache: "pnpm"
cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
- name: Install JavaScript dependencies
working-directory: autogpt_platform/frontend
run: pnpm install --frozen-lockfile
- name: Get CI failure details
id: failure_details
uses: actions/github-script@v8
with:
script: |
const run = await github.rest.actions.getWorkflowRun({
owner: context.repo.owner,
repo: context.repo.repo,
run_id: ${{ github.event.workflow_run.id }}
});
const jobs = await github.rest.actions.listJobsForWorkflowRun({
owner: context.repo.owner,
repo: context.repo.repo,
run_id: ${{ github.event.workflow_run.id }}
});
const failedJobs = jobs.data.jobs.filter(job => job.conclusion === 'failure');
let errorLogs = [];
for (const job of failedJobs) {
const logs = await github.rest.actions.downloadJobLogsForWorkflowRun({
owner: context.repo.owner,
repo: context.repo.repo,
job_id: job.id
});
errorLogs.push({
jobName: job.name,
logs: logs.data
});
}
return {
runUrl: run.data.html_url,
failedJobs: failedJobs.map(j => j.name),
errorLogs: errorLogs
};
- name: Fix CI failures with Claude
id: claude
uses: anthropics/claude-code-action@v1
with:
prompt: |
/fix-ci
Failed CI Run: ${{ fromJSON(steps.failure_details.outputs.result).runUrl }}
Failed Jobs: ${{ join(fromJSON(steps.failure_details.outputs.result).failedJobs, ', ') }}
PR Number: ${{ github.event.workflow_run.pull_requests[0].number }}
Branch Name: ${{ steps.branch.outputs.branch_name }}
Base Branch: ${{ github.event.workflow_run.head_branch }}
Repository: ${{ github.repository }}
Error logs:
${{ toJSON(fromJSON(steps.failure_details.outputs.result).errorLogs) }}
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
claude_args: "--allowedTools 'Edit,MultiEdit,Write,Read,Glob,Grep,LS,Bash(git:*),Bash(bun:*),Bash(npm:*),Bash(npx:*),Bash(gh:*)'"

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# Claude Dependabot PR Review Workflow
#
# This workflow automatically runs Claude analysis on Dependabot PRs to:
# - Identify dependency changes and their versions
# - Look up changelogs for updated packages
# - Assess breaking changes and security impacts
# - Provide actionable recommendations for the development team
#
# Triggered on: Dependabot PRs (opened, synchronize)
# Requirements: CLAUDE_CODE_OAUTH_TOKEN secret must be configured
name: Claude Dependabot PR Review
on:
pull_request:
types: [opened, synchronize]
jobs:
dependabot-review:
# Only run on Dependabot PRs
if: github.actor == 'dependabot[bot]'
runs-on: ubuntu-latest
timeout-minutes: 30
permissions:
contents: write
pull-requests: read
issues: read
id-token: write
actions: read # Required for CI access
steps:
- name: Checkout code
uses: actions/checkout@v6
with:
fetch-depth: 1
# Backend Python/Poetry setup (mirrors platform-backend-ci.yml)
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.11" # Use standard version matching CI
- name: Set up Python dependency cache
uses: actions/cache@v5
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
- name: Install Poetry
run: |
# Extract Poetry version from backend/poetry.lock (matches CI)
cd autogpt_platform/backend
HEAD_POETRY_VERSION=$(python3 ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
echo "Found Poetry version ${HEAD_POETRY_VERSION} in backend/poetry.lock"
# Install Poetry
curl -sSL https://install.python-poetry.org | POETRY_VERSION=$HEAD_POETRY_VERSION python3 -
# Add Poetry to PATH
echo "$HOME/.local/bin" >> $GITHUB_PATH
- name: Check poetry.lock
working-directory: autogpt_platform/backend
run: |
poetry lock
if ! git diff --quiet --ignore-matching-lines="^# " poetry.lock; then
echo "Warning: poetry.lock not up to date, but continuing for setup"
git checkout poetry.lock # Reset for clean setup
fi
- name: Install Python dependencies
working-directory: autogpt_platform/backend
run: poetry install
- name: Generate Prisma Client
working-directory: autogpt_platform/backend
run: poetry run prisma generate && poetry run gen-prisma-stub
# Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
- name: Enable corepack
run: corepack enable
- name: Set up Node.js
uses: actions/setup-node@v6
with:
node-version: "22"
cache: "pnpm"
cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
- name: Install JavaScript dependencies
working-directory: autogpt_platform/frontend
run: pnpm install --frozen-lockfile
# Install Playwright browsers for frontend testing
# NOTE: Disabled to save ~1 minute of setup time. Re-enable if Copilot needs browser automation (e.g., for MCP)
# - name: Install Playwright browsers
# working-directory: autogpt_platform/frontend
# run: pnpm playwright install --with-deps chromium
# Docker setup for development environment
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Copy default environment files
working-directory: autogpt_platform
run: |
# Copy default environment files for development
cp .env.default .env
cp backend/.env.default backend/.env
cp frontend/.env.default frontend/.env
# Phase 1: Cache and load Docker images for faster setup
- name: Set up Docker image cache
id: docker-cache
uses: actions/cache@v5
with:
path: ~/docker-cache
# Use a versioned key for cache invalidation when image list changes
key: docker-images-v2-${{ runner.os }}-${{ hashFiles('.github/workflows/copilot-setup-steps.yml') }}
restore-keys: |
docker-images-v2-${{ runner.os }}-
docker-images-v1-${{ runner.os }}-
- name: Load or pull Docker images
working-directory: autogpt_platform
run: |
mkdir -p ~/docker-cache
# Define image list for easy maintenance
IMAGES=(
"redis:latest"
"rabbitmq:management"
"clamav/clamav-debian:latest"
"busybox:latest"
"kong:2.8.1"
"supabase/gotrue:v2.170.0"
"supabase/postgres:15.8.1.049"
"supabase/postgres-meta:v0.86.1"
"supabase/studio:20250224-d10db0f"
)
# Check if any cached tar files exist (more reliable than cache-hit)
if ls ~/docker-cache/*.tar 1> /dev/null 2>&1; then
echo "Docker cache found, loading images in parallel..."
for image in "${IMAGES[@]}"; do
# Convert image name to filename (replace : and / with -)
filename=$(echo "$image" | tr ':/' '--')
if [ -f ~/docker-cache/${filename}.tar ]; then
echo "Loading $image..."
docker load -i ~/docker-cache/${filename}.tar || echo "Warning: Failed to load $image from cache" &
fi
done
wait
echo "All cached images loaded"
else
echo "No Docker cache found, pulling images in parallel..."
# Pull all images in parallel
for image in "${IMAGES[@]}"; do
docker pull "$image" &
done
wait
# Only save cache on main branches (not PRs) to avoid cache pollution
if [[ "${{ github.ref }}" == "refs/heads/master" ]] || [[ "${{ github.ref }}" == "refs/heads/dev" ]]; then
echo "Saving Docker images to cache in parallel..."
for image in "${IMAGES[@]}"; do
# Convert image name to filename (replace : and / with -)
filename=$(echo "$image" | tr ':/' '--')
echo "Saving $image..."
docker save -o ~/docker-cache/${filename}.tar "$image" || echo "Warning: Failed to save $image" &
done
wait
echo "Docker image cache saved"
else
echo "Skipping cache save for PR/feature branch"
fi
fi
echo "Docker images ready for use"
# Phase 2: Build migrate service with GitHub Actions cache
- name: Build migrate Docker image with cache
working-directory: autogpt_platform
run: |
# Build the migrate image with buildx for GHA caching
docker buildx build \
--cache-from type=gha \
--cache-to type=gha,mode=max \
--target migrate \
--tag autogpt_platform-migrate:latest \
--load \
-f backend/Dockerfile \
..
# Start services using pre-built images
- name: Start Docker services for development
working-directory: autogpt_platform
run: |
# Start essential services (migrate image already built with correct tag)
docker compose --profile local up deps --no-build --detach
echo "Waiting for services to be ready..."
# Wait for database to be ready
echo "Checking database readiness..."
timeout 30 sh -c 'until docker compose exec -T db pg_isready -U postgres 2>/dev/null; do
echo " Waiting for database..."
sleep 2
done' && echo "✅ Database is ready" || echo "⚠️ Database ready check timeout after 30s, continuing..."
# Check migrate service status
echo "Checking migration status..."
docker compose ps migrate || echo " Migrate service not visible in ps output"
# Wait for migrate service to complete
echo "Waiting for migrations to complete..."
timeout 30 bash -c '
ATTEMPTS=0
while [ $ATTEMPTS -lt 15 ]; do
ATTEMPTS=$((ATTEMPTS + 1))
# Check using docker directly (more reliable than docker compose ps)
CONTAINER_STATUS=$(docker ps -a --filter "label=com.docker.compose.service=migrate" --format "{{.Status}}" | head -1)
if [ -z "$CONTAINER_STATUS" ]; then
echo " Attempt $ATTEMPTS: Migrate container not found yet..."
elif echo "$CONTAINER_STATUS" | grep -q "Exited (0)"; then
echo "✅ Migrations completed successfully"
docker compose logs migrate --tail=5 2>/dev/null || true
exit 0
elif echo "$CONTAINER_STATUS" | grep -q "Exited ([1-9]"; then
EXIT_CODE=$(echo "$CONTAINER_STATUS" | grep -oE "Exited \([0-9]+\)" | grep -oE "[0-9]+")
echo "❌ Migrations failed with exit code: $EXIT_CODE"
echo "Migration logs:"
docker compose logs migrate --tail=20 2>/dev/null || true
exit 1
elif echo "$CONTAINER_STATUS" | grep -q "Up"; then
echo " Attempt $ATTEMPTS: Migrate container is running... ($CONTAINER_STATUS)"
else
echo " Attempt $ATTEMPTS: Migrate container status: $CONTAINER_STATUS"
fi
sleep 2
done
echo "⚠️ Timeout: Could not determine migration status after 30 seconds"
echo "Final container check:"
docker ps -a --filter "label=com.docker.compose.service=migrate" || true
echo "Migration logs (if available):"
docker compose logs migrate --tail=10 2>/dev/null || echo " No logs available"
' || echo "⚠️ Migration check completed with warnings, continuing..."
# Brief wait for other services to stabilize
echo "Waiting 5 seconds for other services to stabilize..."
sleep 5
# Verify installations and provide environment info
- name: Verify setup and show environment info
run: |
echo "=== Python Setup ==="
python --version
poetry --version
echo "=== Node.js Setup ==="
node --version
pnpm --version
echo "=== Additional Tools ==="
docker --version
docker compose version
gh --version || true
echo "=== Services Status ==="
cd autogpt_platform
docker compose ps || true
echo "=== Backend Dependencies ==="
cd backend
poetry show | head -10 || true
echo "=== Frontend Dependencies ==="
cd ../frontend
pnpm list --depth=0 | head -10 || true
echo "=== Environment Files ==="
ls -la ../.env* || true
ls -la .env* || true
ls -la ../backend/.env* || true
echo "✅ AutoGPT Platform development environment setup complete!"
echo "🚀 Ready for development with Docker services running"
echo "📝 Backend server: poetry run serve (port 8000)"
echo "🌐 Frontend server: pnpm dev (port 3000)"
- name: Run Claude Dependabot Analysis
id: claude_review
uses: anthropics/claude-code-action@v1
with:
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
allowed_bots: "dependabot[bot]"
claude_args: |
--allowedTools "Bash(npm:*),Bash(pnpm:*),Bash(poetry:*),Bash(git:*),Edit,Replace,NotebookEditCell,mcp__github_inline_comment__create_inline_comment,Bash(gh pr comment:*), Bash(gh pr diff:*), Bash(gh pr view:*)"
prompt: |
You are Claude, an AI assistant specialized in reviewing Dependabot dependency update PRs.
Your primary tasks are:
1. **Analyze the dependency changes** in this Dependabot PR
2. **Look up changelogs** for all updated dependencies to understand what changed
3. **Identify breaking changes** and assess potential impact on the AutoGPT codebase
4. **Provide actionable recommendations** for the development team
## Analysis Process:
1. **Identify Changed Dependencies**:
- Use git diff to see what dependencies were updated
- Parse package.json, poetry.lock, requirements files, etc.
- List all package versions: old → new
2. **Changelog Research**:
- For each updated dependency, look up its changelog/release notes
- Use WebFetch to access GitHub releases, NPM package pages, PyPI project pages. The pr should also have some details
- Focus on versions between the old and new versions
- Identify: breaking changes, deprecations, security fixes, new features
3. **Breaking Change Assessment**:
- Categorize changes: BREAKING, MAJOR, MINOR, PATCH, SECURITY
- Assess impact on AutoGPT's usage patterns
- Check if AutoGPT uses affected APIs/features
- Look for migration guides or upgrade instructions
4. **Codebase Impact Analysis**:
- Search the AutoGPT codebase for usage of changed APIs
- Identify files that might be affected by breaking changes
- Check test files for deprecated usage patterns
- Look for configuration changes needed
## Output Format:
Provide a comprehensive review comment with:
### 🔍 Dependency Analysis Summary
- List of updated packages with version changes
- Overall risk assessment (LOW/MEDIUM/HIGH)
### 📋 Detailed Changelog Review
For each updated dependency:
- **Package**: name (old_version → new_version)
- **Changes**: Summary of key changes
- **Breaking Changes**: List any breaking changes
- **Security Fixes**: Note security improvements
- **Migration Notes**: Any upgrade steps needed
### ⚠️ Impact Assessment
- **Breaking Changes Found**: Yes/No with details
- **Affected Files**: List AutoGPT files that may need updates
- **Test Impact**: Any tests that may need updating
- **Configuration Changes**: Required config updates
### 🛠️ Recommendations
- **Action Required**: What the team should do
- **Testing Focus**: Areas to test thoroughly
- **Follow-up Tasks**: Any additional work needed
- **Merge Recommendation**: APPROVE/REVIEW_NEEDED/HOLD
### 📚 Useful Links
- Links to relevant changelogs, migration guides, documentation
Be thorough but concise. Focus on actionable insights that help the development team make informed decisions about the dependency updates.

319
.github/workflows/claude.yml vendored Normal file
View File

@@ -0,0 +1,319 @@
name: Claude Code
on:
issue_comment:
types: [created]
pull_request_review_comment:
types: [created]
issues:
types: [opened, assigned]
pull_request_review:
types: [submitted]
jobs:
claude:
if: |
(
(github.event_name == 'issue_comment' && contains(github.event.comment.body, '@claude')) ||
(github.event_name == 'pull_request_review_comment' && contains(github.event.comment.body, '@claude')) ||
(github.event_name == 'pull_request_review' && contains(github.event.review.body, '@claude')) ||
(github.event_name == 'issues' && (contains(github.event.issue.body, '@claude') || contains(github.event.issue.title, '@claude')))
) && (
github.event.comment.author_association == 'OWNER' ||
github.event.comment.author_association == 'MEMBER' ||
github.event.comment.author_association == 'COLLABORATOR' ||
github.event.review.author_association == 'OWNER' ||
github.event.review.author_association == 'MEMBER' ||
github.event.review.author_association == 'COLLABORATOR' ||
github.event.issue.author_association == 'OWNER' ||
github.event.issue.author_association == 'MEMBER' ||
github.event.issue.author_association == 'COLLABORATOR'
)
runs-on: ubuntu-latest
timeout-minutes: 45
permissions:
contents: write
pull-requests: read
issues: read
id-token: write
actions: read # Required for CI access
steps:
- name: Checkout code
uses: actions/checkout@v6
with:
fetch-depth: 1
- name: Free Disk Space (Ubuntu)
uses: jlumbroso/free-disk-space@v1.3.1
with:
large-packages: false # slow
docker-images: false # limited benefit
# Backend Python/Poetry setup (mirrors platform-backend-ci.yml)
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.11" # Use standard version matching CI
- name: Set up Python dependency cache
uses: actions/cache@v5
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
- name: Install Poetry
run: |
# Extract Poetry version from backend/poetry.lock (matches CI)
cd autogpt_platform/backend
HEAD_POETRY_VERSION=$(python3 ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
echo "Found Poetry version ${HEAD_POETRY_VERSION} in backend/poetry.lock"
# Install Poetry
curl -sSL https://install.python-poetry.org | POETRY_VERSION=$HEAD_POETRY_VERSION python3 -
# Add Poetry to PATH
echo "$HOME/.local/bin" >> $GITHUB_PATH
- name: Check poetry.lock
working-directory: autogpt_platform/backend
run: |
poetry lock
if ! git diff --quiet --ignore-matching-lines="^# " poetry.lock; then
echo "Warning: poetry.lock not up to date, but continuing for setup"
git checkout poetry.lock # Reset for clean setup
fi
- name: Install Python dependencies
working-directory: autogpt_platform/backend
run: poetry install
- name: Generate Prisma Client
working-directory: autogpt_platform/backend
run: poetry run prisma generate && poetry run gen-prisma-stub
# Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
- name: Enable corepack
run: corepack enable
- name: Set up Node.js
uses: actions/setup-node@v6
with:
node-version: "22"
cache: "pnpm"
cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
- name: Install JavaScript dependencies
working-directory: autogpt_platform/frontend
run: pnpm install --frozen-lockfile
# Install Playwright browsers for frontend testing
# NOTE: Disabled to save ~1 minute of setup time. Re-enable if Copilot needs browser automation (e.g., for MCP)
# - name: Install Playwright browsers
# working-directory: autogpt_platform/frontend
# run: pnpm playwright install --with-deps chromium
# Docker setup for development environment
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Copy default environment files
working-directory: autogpt_platform
run: |
# Copy default environment files for development
cp .env.default .env
cp backend/.env.default backend/.env
cp frontend/.env.default frontend/.env
# Phase 1: Cache and load Docker images for faster setup
- name: Set up Docker image cache
id: docker-cache
uses: actions/cache@v5
with:
path: ~/docker-cache
# Use a versioned key for cache invalidation when image list changes
key: docker-images-v2-${{ runner.os }}-${{ hashFiles('.github/workflows/copilot-setup-steps.yml') }}
restore-keys: |
docker-images-v2-${{ runner.os }}-
docker-images-v1-${{ runner.os }}-
- name: Load or pull Docker images
working-directory: autogpt_platform
run: |
mkdir -p ~/docker-cache
# Define image list for easy maintenance
IMAGES=(
"redis:latest"
"rabbitmq:management"
"clamav/clamav-debian:latest"
"busybox:latest"
"kong:2.8.1"
"supabase/gotrue:v2.170.0"
"supabase/postgres:15.8.1.049"
"supabase/postgres-meta:v0.86.1"
"supabase/studio:20250224-d10db0f"
)
# Check if any cached tar files exist (more reliable than cache-hit)
if ls ~/docker-cache/*.tar 1> /dev/null 2>&1; then
echo "Docker cache found, loading images in parallel..."
for image in "${IMAGES[@]}"; do
# Convert image name to filename (replace : and / with -)
filename=$(echo "$image" | tr ':/' '--')
if [ -f ~/docker-cache/${filename}.tar ]; then
echo "Loading $image..."
docker load -i ~/docker-cache/${filename}.tar || echo "Warning: Failed to load $image from cache" &
fi
done
wait
echo "All cached images loaded"
else
echo "No Docker cache found, pulling images in parallel..."
# Pull all images in parallel
for image in "${IMAGES[@]}"; do
docker pull "$image" &
done
wait
# Only save cache on main branches (not PRs) to avoid cache pollution
if [[ "${{ github.ref }}" == "refs/heads/master" ]] || [[ "${{ github.ref }}" == "refs/heads/dev" ]]; then
echo "Saving Docker images to cache in parallel..."
for image in "${IMAGES[@]}"; do
# Convert image name to filename (replace : and / with -)
filename=$(echo "$image" | tr ':/' '--')
echo "Saving $image..."
docker save -o ~/docker-cache/${filename}.tar "$image" || echo "Warning: Failed to save $image" &
done
wait
echo "Docker image cache saved"
else
echo "Skipping cache save for PR/feature branch"
fi
fi
echo "Docker images ready for use"
# Phase 2: Build migrate service with GitHub Actions cache
- name: Build migrate Docker image with cache
working-directory: autogpt_platform
run: |
# Build the migrate image with buildx for GHA caching
docker buildx build \
--cache-from type=gha \
--cache-to type=gha,mode=max \
--target migrate \
--tag autogpt_platform-migrate:latest \
--load \
-f backend/Dockerfile \
..
# Start services using pre-built images
- name: Start Docker services for development
working-directory: autogpt_platform
run: |
# Start essential services (migrate image already built with correct tag)
docker compose --profile local up deps --no-build --detach
echo "Waiting for services to be ready..."
# Wait for database to be ready
echo "Checking database readiness..."
timeout 30 sh -c 'until docker compose exec -T db pg_isready -U postgres 2>/dev/null; do
echo " Waiting for database..."
sleep 2
done' && echo "✅ Database is ready" || echo "⚠️ Database ready check timeout after 30s, continuing..."
# Check migrate service status
echo "Checking migration status..."
docker compose ps migrate || echo " Migrate service not visible in ps output"
# Wait for migrate service to complete
echo "Waiting for migrations to complete..."
timeout 30 bash -c '
ATTEMPTS=0
while [ $ATTEMPTS -lt 15 ]; do
ATTEMPTS=$((ATTEMPTS + 1))
# Check using docker directly (more reliable than docker compose ps)
CONTAINER_STATUS=$(docker ps -a --filter "label=com.docker.compose.service=migrate" --format "{{.Status}}" | head -1)
if [ -z "$CONTAINER_STATUS" ]; then
echo " Attempt $ATTEMPTS: Migrate container not found yet..."
elif echo "$CONTAINER_STATUS" | grep -q "Exited (0)"; then
echo "✅ Migrations completed successfully"
docker compose logs migrate --tail=5 2>/dev/null || true
exit 0
elif echo "$CONTAINER_STATUS" | grep -q "Exited ([1-9]"; then
EXIT_CODE=$(echo "$CONTAINER_STATUS" | grep -oE "Exited \([0-9]+\)" | grep -oE "[0-9]+")
echo "❌ Migrations failed with exit code: $EXIT_CODE"
echo "Migration logs:"
docker compose logs migrate --tail=20 2>/dev/null || true
exit 1
elif echo "$CONTAINER_STATUS" | grep -q "Up"; then
echo " Attempt $ATTEMPTS: Migrate container is running... ($CONTAINER_STATUS)"
else
echo " Attempt $ATTEMPTS: Migrate container status: $CONTAINER_STATUS"
fi
sleep 2
done
echo "⚠️ Timeout: Could not determine migration status after 30 seconds"
echo "Final container check:"
docker ps -a --filter "label=com.docker.compose.service=migrate" || true
echo "Migration logs (if available):"
docker compose logs migrate --tail=10 2>/dev/null || echo " No logs available"
' || echo "⚠️ Migration check completed with warnings, continuing..."
# Brief wait for other services to stabilize
echo "Waiting 5 seconds for other services to stabilize..."
sleep 5
# Verify installations and provide environment info
- name: Verify setup and show environment info
run: |
echo "=== Python Setup ==="
python --version
poetry --version
echo "=== Node.js Setup ==="
node --version
pnpm --version
echo "=== Additional Tools ==="
docker --version
docker compose version
gh --version || true
echo "=== Services Status ==="
cd autogpt_platform
docker compose ps || true
echo "=== Backend Dependencies ==="
cd backend
poetry show | head -10 || true
echo "=== Frontend Dependencies ==="
cd ../frontend
pnpm list --depth=0 | head -10 || true
echo "=== Environment Files ==="
ls -la ../.env* || true
ls -la .env* || true
ls -la ../backend/.env* || true
echo "✅ AutoGPT Platform development environment setup complete!"
echo "🚀 Ready for development with Docker services running"
echo "📝 Backend server: poetry run serve (port 8000)"
echo "🌐 Frontend server: pnpm dev (port 3000)"
- name: Run Claude Code
id: claude
uses: anthropics/claude-code-action@v1
with:
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
claude_args: |
--allowedTools "Bash(npm:*),Bash(pnpm:*),Bash(poetry:*),Bash(git:*),Edit,Replace,NotebookEditCell,mcp__github_inline_comment__create_inline_comment,Bash(gh pr comment:*), Bash(gh pr diff:*), Bash(gh pr view:*), Bash(gh pr edit:*)"
--model opus
additional_permissions: |
actions: read

98
.github/workflows/codeql.yml vendored Normal file
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@@ -0,0 +1,98 @@
# For most projects, this workflow file will not need changing; you simply need
# to commit it to your repository.
#
# You may wish to alter this file to override the set of languages analyzed,
# or to provide custom queries or build logic.
#
# ******** NOTE ********
# We have attempted to detect the languages in your repository. Please check
# the `language` matrix defined below to confirm you have the correct set of
# supported CodeQL languages.
#
name: "CodeQL"
on:
push:
branches: [ "master", "release-*", "dev" ]
pull_request:
branches: [ "master", "release-*", "dev" ]
merge_group:
schedule:
- cron: '15 4 * * 0'
jobs:
analyze:
name: Analyze (${{ matrix.language }})
# Runner size impacts CodeQL analysis time. To learn more, please see:
# - https://gh.io/recommended-hardware-resources-for-running-codeql
# - https://gh.io/supported-runners-and-hardware-resources
# - https://gh.io/using-larger-runners (GitHub.com only)
# Consider using larger runners or machines with greater resources for possible analysis time improvements.
runs-on: ${{ (matrix.language == 'swift' && 'macos-latest') || 'ubuntu-latest' }}
permissions:
# required for all workflows
security-events: write
# required to fetch internal or private CodeQL packs
packages: read
# only required for workflows in private repositories
actions: read
contents: read
strategy:
fail-fast: false
matrix:
include:
- language: typescript
build-mode: none
- language: python
build-mode: none
# CodeQL supports the following values keywords for 'language': 'c-cpp', 'csharp', 'go', 'java-kotlin', 'javascript-typescript', 'python', 'ruby', 'swift'
# Use `c-cpp` to analyze code written in C, C++ or both
# Use 'java-kotlin' to analyze code written in Java, Kotlin or both
# Use 'javascript-typescript' to analyze code written in JavaScript, TypeScript or both
# To learn more about changing the languages that are analyzed or customizing the build mode for your analysis,
# see https://docs.github.com/en/code-security/code-scanning/creating-an-advanced-setup-for-code-scanning/customizing-your-advanced-setup-for-code-scanning.
# If you are analyzing a compiled language, you can modify the 'build-mode' for that language to customize how
# your codebase is analyzed, see https://docs.github.com/en/code-security/code-scanning/creating-an-advanced-setup-for-code-scanning/codeql-code-scanning-for-compiled-languages
steps:
- name: Checkout repository
uses: actions/checkout@v6
# Initializes the CodeQL tools for scanning.
- name: Initialize CodeQL
uses: github/codeql-action/init@v4
with:
languages: ${{ matrix.language }}
build-mode: ${{ matrix.build-mode }}
# If you wish to specify custom queries, you can do so here or in a config file.
# By default, queries listed here will override any specified in a config file.
# Prefix the list here with "+" to use these queries and those in the config file.
config: |
paths-ignore:
- classic/frontend/build/**
# For more details on CodeQL's query packs, refer to: https://docs.github.com/en/code-security/code-scanning/automatically-scanning-your-code-for-vulnerabilities-and-errors/configuring-code-scanning#using-queries-in-ql-packs
# queries: security-extended,security-and-quality
# If the analyze step fails for one of the languages you are analyzing with
# "We were unable to automatically build your code", modify the matrix above
# to set the build mode to "manual" for that language. Then modify this step
# to build your code.
# Command-line programs to run using the OS shell.
# 📚 See https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions#jobsjob_idstepsrun
- if: matrix.build-mode == 'manual'
shell: bash
run: |
echo 'If you are using a "manual" build mode for one or more of the' \
'languages you are analyzing, replace this with the commands to build' \
'your code, for example:'
echo ' make bootstrap'
echo ' make release'
exit 1
- name: Perform CodeQL Analysis
uses: github/codeql-action/analyze@v4
with:
category: "/language:${{matrix.language}}"

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@@ -0,0 +1,312 @@
name: "Copilot Setup Steps"
# Automatically run the setup steps when they are changed to allow for easy validation, and
# allow manual testing through the repository's "Actions" tab
on:
workflow_dispatch:
push:
paths:
- .github/workflows/copilot-setup-steps.yml
pull_request:
paths:
- .github/workflows/copilot-setup-steps.yml
jobs:
# The job MUST be called `copilot-setup-steps` or it will not be picked up by Copilot.
copilot-setup-steps:
runs-on: ubuntu-latest
timeout-minutes: 45
# Set the permissions to the lowest permissions possible needed for your steps.
# Copilot will be given its own token for its operations.
permissions:
# If you want to clone the repository as part of your setup steps, for example to install dependencies, you'll need the `contents: read` permission. If you don't clone the repository in your setup steps, Copilot will do this for you automatically after the steps complete.
contents: read
# You can define any steps you want, and they will run before the agent starts.
# If you do not check out your code, Copilot will do this for you.
steps:
- name: Checkout code
uses: actions/checkout@v6
with:
fetch-depth: 0
submodules: true
# Backend Python/Poetry setup (mirrors platform-backend-ci.yml)
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.11" # Use standard version matching CI
- name: Set up Python dependency cache
uses: actions/cache@v5
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
- name: Install Poetry
run: |
# Extract Poetry version from backend/poetry.lock (matches CI)
cd autogpt_platform/backend
HEAD_POETRY_VERSION=$(python3 ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
echo "Found Poetry version ${HEAD_POETRY_VERSION} in backend/poetry.lock"
# Install Poetry
curl -sSL https://install.python-poetry.org | POETRY_VERSION=$HEAD_POETRY_VERSION python3 -
# Add Poetry to PATH
echo "$HOME/.local/bin" >> $GITHUB_PATH
- name: Check poetry.lock
working-directory: autogpt_platform/backend
run: |
poetry lock
if ! git diff --quiet --ignore-matching-lines="^# " poetry.lock; then
echo "Warning: poetry.lock not up to date, but continuing for setup"
git checkout poetry.lock # Reset for clean setup
fi
- name: Install Python dependencies
working-directory: autogpt_platform/backend
run: poetry install
- name: Generate Prisma Client
working-directory: autogpt_platform/backend
run: poetry run prisma generate && poetry run gen-prisma-stub
# Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
- name: Set up Node.js
uses: actions/setup-node@v6
with:
node-version: "22"
- name: Enable corepack
run: corepack enable
- name: Set pnpm store directory
run: |
pnpm config set store-dir ~/.pnpm-store
echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
- name: Cache frontend dependencies
uses: actions/cache@v5
with:
path: ~/.pnpm-store
key: ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}
restore-keys: |
${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml') }}
${{ runner.os }}-pnpm-
- name: Install JavaScript dependencies
working-directory: autogpt_platform/frontend
run: pnpm install --frozen-lockfile
# Install Playwright browsers for frontend testing
# NOTE: Disabled to save ~1 minute of setup time. Re-enable if Copilot needs browser automation (e.g., for MCP)
# - name: Install Playwright browsers
# working-directory: autogpt_platform/frontend
# run: pnpm playwright install --with-deps chromium
# Docker setup for development environment
- name: Free up disk space
run: |
# Remove large unused tools to free disk space for Docker builds
sudo rm -rf /usr/share/dotnet
sudo rm -rf /usr/local/lib/android
sudo rm -rf /opt/ghc
sudo rm -rf /opt/hostedtoolcache/CodeQL
sudo docker system prune -af
df -h
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Copy default environment files
working-directory: autogpt_platform
run: |
# Copy default environment files for development
cp .env.default .env
cp backend/.env.default backend/.env
cp frontend/.env.default frontend/.env
# Phase 1: Cache and load Docker images for faster setup
- name: Set up Docker image cache
id: docker-cache
uses: actions/cache@v5
with:
path: ~/docker-cache
# Use a versioned key for cache invalidation when image list changes
key: docker-images-v2-${{ runner.os }}-${{ hashFiles('.github/workflows/copilot-setup-steps.yml') }}
restore-keys: |
docker-images-v2-${{ runner.os }}-
docker-images-v1-${{ runner.os }}-
- name: Load or pull Docker images
working-directory: autogpt_platform
run: |
mkdir -p ~/docker-cache
# Define image list for easy maintenance
IMAGES=(
"redis:latest"
"rabbitmq:management"
"clamav/clamav-debian:latest"
"busybox:latest"
"kong:2.8.1"
"supabase/gotrue:v2.170.0"
"supabase/postgres:15.8.1.049"
"supabase/postgres-meta:v0.86.1"
"supabase/studio:20250224-d10db0f"
)
# Check if any cached tar files exist (more reliable than cache-hit)
if ls ~/docker-cache/*.tar 1> /dev/null 2>&1; then
echo "Docker cache found, loading images in parallel..."
for image in "${IMAGES[@]}"; do
# Convert image name to filename (replace : and / with -)
filename=$(echo "$image" | tr ':/' '--')
if [ -f ~/docker-cache/${filename}.tar ]; then
echo "Loading $image..."
docker load -i ~/docker-cache/${filename}.tar || echo "Warning: Failed to load $image from cache" &
fi
done
wait
echo "All cached images loaded"
else
echo "No Docker cache found, pulling images in parallel..."
# Pull all images in parallel
for image in "${IMAGES[@]}"; do
docker pull "$image" &
done
wait
# Only save cache on main branches (not PRs) to avoid cache pollution
if [[ "${{ github.ref }}" == "refs/heads/master" ]] || [[ "${{ github.ref }}" == "refs/heads/dev" ]]; then
echo "Saving Docker images to cache in parallel..."
for image in "${IMAGES[@]}"; do
# Convert image name to filename (replace : and / with -)
filename=$(echo "$image" | tr ':/' '--')
echo "Saving $image..."
docker save -o ~/docker-cache/${filename}.tar "$image" || echo "Warning: Failed to save $image" &
done
wait
echo "Docker image cache saved"
else
echo "Skipping cache save for PR/feature branch"
fi
fi
echo "Docker images ready for use"
# Phase 2: Build migrate service with GitHub Actions cache
- name: Build migrate Docker image with cache
working-directory: autogpt_platform
run: |
# Build the migrate image with buildx for GHA caching
docker buildx build \
--cache-from type=gha \
--cache-to type=gha,mode=max \
--target migrate \
--tag autogpt_platform-migrate:latest \
--load \
-f backend/Dockerfile \
..
# Start services using pre-built images
- name: Start Docker services for development
working-directory: autogpt_platform
run: |
# Start essential services (migrate image already built with correct tag)
docker compose --profile local up deps --no-build --detach
echo "Waiting for services to be ready..."
# Wait for database to be ready
echo "Checking database readiness..."
timeout 30 sh -c 'until docker compose exec -T db pg_isready -U postgres 2>/dev/null; do
echo " Waiting for database..."
sleep 2
done' && echo "✅ Database is ready" || echo "⚠️ Database ready check timeout after 30s, continuing..."
# Check migrate service status
echo "Checking migration status..."
docker compose ps migrate || echo " Migrate service not visible in ps output"
# Wait for migrate service to complete
echo "Waiting for migrations to complete..."
timeout 30 bash -c '
ATTEMPTS=0
while [ $ATTEMPTS -lt 15 ]; do
ATTEMPTS=$((ATTEMPTS + 1))
# Check using docker directly (more reliable than docker compose ps)
CONTAINER_STATUS=$(docker ps -a --filter "label=com.docker.compose.service=migrate" --format "{{.Status}}" | head -1)
if [ -z "$CONTAINER_STATUS" ]; then
echo " Attempt $ATTEMPTS: Migrate container not found yet..."
elif echo "$CONTAINER_STATUS" | grep -q "Exited (0)"; then
echo "✅ Migrations completed successfully"
docker compose logs migrate --tail=5 2>/dev/null || true
exit 0
elif echo "$CONTAINER_STATUS" | grep -q "Exited ([1-9]"; then
EXIT_CODE=$(echo "$CONTAINER_STATUS" | grep -oE "Exited \([0-9]+\)" | grep -oE "[0-9]+")
echo "❌ Migrations failed with exit code: $EXIT_CODE"
echo "Migration logs:"
docker compose logs migrate --tail=20 2>/dev/null || true
exit 1
elif echo "$CONTAINER_STATUS" | grep -q "Up"; then
echo " Attempt $ATTEMPTS: Migrate container is running... ($CONTAINER_STATUS)"
else
echo " Attempt $ATTEMPTS: Migrate container status: $CONTAINER_STATUS"
fi
sleep 2
done
echo "⚠️ Timeout: Could not determine migration status after 30 seconds"
echo "Final container check:"
docker ps -a --filter "label=com.docker.compose.service=migrate" || true
echo "Migration logs (if available):"
docker compose logs migrate --tail=10 2>/dev/null || echo " No logs available"
' || echo "⚠️ Migration check completed with warnings, continuing..."
# Brief wait for other services to stabilize
echo "Waiting 5 seconds for other services to stabilize..."
sleep 5
# Verify installations and provide environment info
- name: Verify setup and show environment info
run: |
echo "=== Python Setup ==="
python --version
poetry --version
echo "=== Node.js Setup ==="
node --version
pnpm --version
echo "=== Additional Tools ==="
docker --version
docker compose version
gh --version || true
echo "=== Services Status ==="
cd autogpt_platform
docker compose ps || true
echo "=== Backend Dependencies ==="
cd backend
poetry show | head -10 || true
echo "=== Frontend Dependencies ==="
cd ../frontend
pnpm list --depth=0 | head -10 || true
echo "=== Environment Files ==="
ls -la ../.env* || true
ls -la .env* || true
ls -la ../backend/.env* || true
echo "✅ AutoGPT Platform development environment setup complete!"
echo "🚀 Ready for development with Docker services running"
echo "📝 Backend server: poetry run serve (port 8000)"
echo "🌐 Frontend server: pnpm dev (port 3000)"

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name: Block Documentation Sync Check
on:
push:
branches: [master, dev]
paths:
- "autogpt_platform/backend/backend/blocks/**"
- "docs/integrations/**"
- "autogpt_platform/backend/scripts/generate_block_docs.py"
- ".github/workflows/docs-block-sync.yml"
pull_request:
branches: [master, dev]
paths:
- "autogpt_platform/backend/backend/blocks/**"
- "docs/integrations/**"
- "autogpt_platform/backend/scripts/generate_block_docs.py"
- ".github/workflows/docs-block-sync.yml"
jobs:
check-docs-sync:
runs-on: ubuntu-latest
timeout-minutes: 15
steps:
- name: Checkout code
uses: actions/checkout@v6
with:
fetch-depth: 1
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.11"
- name: Set up Python dependency cache
uses: actions/cache@v5
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
restore-keys: |
poetry-${{ runner.os }}-
- name: Install Poetry
run: |
cd autogpt_platform/backend
HEAD_POETRY_VERSION=$(python3 ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
echo "Found Poetry version ${HEAD_POETRY_VERSION} in backend/poetry.lock"
curl -sSL https://install.python-poetry.org | POETRY_VERSION=$HEAD_POETRY_VERSION python3 -
echo "$HOME/.local/bin" >> $GITHUB_PATH
- name: Install dependencies
working-directory: autogpt_platform/backend
run: |
poetry install --only main
poetry run prisma generate
- name: Check block documentation is in sync
working-directory: autogpt_platform/backend
run: |
echo "Checking if block documentation is in sync with code..."
poetry run python scripts/generate_block_docs.py --check
- name: Show diff if out of sync
if: failure()
working-directory: autogpt_platform/backend
run: |
echo "::error::Block documentation is out of sync with code!"
echo ""
echo "To fix this, run the following command locally:"
echo " cd autogpt_platform/backend && poetry run python scripts/generate_block_docs.py"
echo ""
echo "Then commit the updated documentation files."
echo ""
echo "Regenerating docs to show diff..."
poetry run python scripts/generate_block_docs.py
echo ""
echo "Changes detected:"
git diff ../../docs/integrations/ || true

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name: Claude Block Docs Review
on:
pull_request:
types: [opened, synchronize]
paths:
- "docs/integrations/**"
- "autogpt_platform/backend/backend/blocks/**"
concurrency:
group: claude-docs-review-${{ github.event.pull_request.number }}
cancel-in-progress: true
jobs:
claude-review:
# Only run for PRs from members/collaborators
if: |
github.event.pull_request.author_association == 'OWNER' ||
github.event.pull_request.author_association == 'MEMBER' ||
github.event.pull_request.author_association == 'COLLABORATOR'
runs-on: ubuntu-latest
timeout-minutes: 15
permissions:
contents: read
pull-requests: write
id-token: write
steps:
- name: Checkout code
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.11"
- name: Set up Python dependency cache
uses: actions/cache@v5
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
restore-keys: |
poetry-${{ runner.os }}-
- name: Install Poetry
run: |
cd autogpt_platform/backend
HEAD_POETRY_VERSION=$(python3 ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
curl -sSL https://install.python-poetry.org | POETRY_VERSION=$HEAD_POETRY_VERSION python3 -
echo "$HOME/.local/bin" >> $GITHUB_PATH
- name: Install dependencies
working-directory: autogpt_platform/backend
run: |
poetry install --only main
poetry run prisma generate
- name: Run Claude Code Review
uses: anthropics/claude-code-action@v1
with:
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
claude_args: |
--allowedTools "Read,Glob,Grep,Bash(gh pr comment:*),Bash(gh pr diff:*),Bash(gh pr view:*)"
prompt: |
You are reviewing a PR that modifies block documentation or block code for AutoGPT.
## Your Task
Review the changes in this PR and provide constructive feedback. Focus on:
1. **Documentation Accuracy**: For any block code changes, verify that:
- Input/output tables in docs match the actual block schemas
- Description text accurately reflects what the block does
- Any new blocks have corresponding documentation
2. **Manual Content Quality**: Check manual sections (marked with `<!-- MANUAL: -->` markers):
- "How it works" sections should have clear technical explanations
- "Possible use case" sections should have practical, real-world examples
- Content should be helpful for users trying to understand the blocks
3. **Template Compliance**: Ensure docs follow the standard template:
- What it is (brief intro)
- What it does (description)
- How it works (technical explanation)
- Inputs table
- Outputs table
- Possible use case
4. **Cross-references**: Check that links and anchors are correct
## Review Process
1. First, get the PR diff to see what changed: `gh pr diff ${{ github.event.pull_request.number }}`
2. Read any modified block files to understand the implementation
3. Read corresponding documentation files to verify accuracy
4. Provide your feedback as a PR comment
## IMPORTANT: Comment Marker
Start your PR comment with exactly this HTML comment marker on its own line:
<!-- CLAUDE_DOCS_REVIEW -->
This marker is used to identify and replace your comment on subsequent runs.
Be constructive and specific. If everything looks good, say so!
If there are issues, explain what's wrong and suggest how to fix it.
- name: Delete old Claude review comments
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: |
# Get all comment IDs with our marker, sorted by creation date (oldest first)
COMMENT_IDS=$(gh api \
repos/${{ github.repository }}/issues/${{ github.event.pull_request.number }}/comments \
--jq '[.[] | select(.body | contains("<!-- CLAUDE_DOCS_REVIEW -->"))] | sort_by(.created_at) | .[].id')
# Count comments
COMMENT_COUNT=$(echo "$COMMENT_IDS" | grep -c . || true)
if [ "$COMMENT_COUNT" -gt 1 ]; then
# Delete all but the last (newest) comment
echo "$COMMENT_IDS" | head -n -1 | while read -r COMMENT_ID; do
if [ -n "$COMMENT_ID" ]; then
echo "Deleting old review comment: $COMMENT_ID"
gh api -X DELETE repos/${{ github.repository }}/issues/comments/$COMMENT_ID
fi
done
else
echo "No old review comments to clean up"
fi

194
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name: Enhance Block Documentation
on:
workflow_dispatch:
inputs:
block_pattern:
description: 'Block file pattern to enhance (e.g., "google/*.md" or "*" for all blocks)'
required: true
default: '*'
type: string
dry_run:
description: 'Dry run mode - show proposed changes without committing'
type: boolean
default: true
max_blocks:
description: 'Maximum number of blocks to process (0 for unlimited)'
type: number
default: 10
jobs:
enhance-docs:
runs-on: ubuntu-latest
timeout-minutes: 45
permissions:
contents: write
pull-requests: write
id-token: write
steps:
- name: Checkout code
uses: actions/checkout@v6
with:
fetch-depth: 1
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.11"
- name: Set up Python dependency cache
uses: actions/cache@v5
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
restore-keys: |
poetry-${{ runner.os }}-
- name: Install Poetry
run: |
cd autogpt_platform/backend
HEAD_POETRY_VERSION=$(python3 ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
curl -sSL https://install.python-poetry.org | POETRY_VERSION=$HEAD_POETRY_VERSION python3 -
echo "$HOME/.local/bin" >> $GITHUB_PATH
- name: Install dependencies
working-directory: autogpt_platform/backend
run: |
poetry install --only main
poetry run prisma generate
- name: Run Claude Enhancement
uses: anthropics/claude-code-action@v1
with:
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
claude_args: |
--allowedTools "Read,Edit,Glob,Grep,Write,Bash(git:*),Bash(gh:*),Bash(find:*),Bash(ls:*)"
prompt: |
You are enhancing block documentation for AutoGPT. Your task is to improve the MANUAL sections
of block documentation files by reading the actual block implementations and writing helpful content.
## Configuration
- Block pattern: ${{ inputs.block_pattern }}
- Dry run: ${{ inputs.dry_run }}
- Max blocks to process: ${{ inputs.max_blocks }}
## Your Task
1. **Find Documentation Files**
Find block documentation files matching the pattern in `docs/integrations/`
Pattern: ${{ inputs.block_pattern }}
Use: `find docs/integrations -name "*.md" -type f`
2. **For Each Documentation File** (up to ${{ inputs.max_blocks }} files):
a. Read the documentation file
b. Identify which block(s) it documents (look for the block class name)
c. Find and read the corresponding block implementation in `autogpt_platform/backend/backend/blocks/`
d. Improve the MANUAL sections:
**"How it works" section** (within `<!-- MANUAL: how_it_works -->` markers):
- Explain the technical flow of the block
- Describe what APIs or services it connects to
- Note any important configuration or prerequisites
- Keep it concise but informative (2-4 paragraphs)
**"Possible use case" section** (within `<!-- MANUAL: use_case -->` markers):
- Provide 2-3 practical, real-world examples
- Make them specific and actionable
- Show how this block could be used in an automation workflow
3. **Important Rules**
- ONLY modify content within `<!-- MANUAL: -->` and `<!-- END MANUAL -->` markers
- Do NOT modify auto-generated sections (inputs/outputs tables, descriptions)
- Keep content accurate based on the actual block implementation
- Write for users who may not be technical experts
4. **Output**
${{ inputs.dry_run == true && 'DRY RUN MODE: Show proposed changes for each file but do NOT actually edit the files. Describe what you would change.' || 'LIVE MODE: Actually edit the files to improve the documentation.' }}
## Example Improvements
**Before (How it works):**
```
_Add technical explanation here._
```
**After (How it works):**
```
This block connects to the GitHub API to retrieve issue information. When executed,
it authenticates using your GitHub credentials and fetches issue details including
title, body, labels, and assignees.
The block requires a valid GitHub OAuth connection with repository access permissions.
It supports both public and private repositories you have access to.
```
**Before (Possible use case):**
```
_Add practical use case examples here._
```
**After (Possible use case):**
```
**Customer Support Automation**: Monitor a GitHub repository for new issues with
the "bug" label, then automatically create a ticket in your support system and
notify the on-call engineer via Slack.
**Release Notes Generation**: When a new release is published, gather all closed
issues since the last release and generate a summary for your changelog.
```
Begin by finding and listing the documentation files to process.
- name: Create PR with enhanced documentation
if: ${{ inputs.dry_run == false }}
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: |
# Check if there are changes
if git diff --quiet docs/integrations/; then
echo "No changes to commit"
exit 0
fi
# Configure git
git config user.name "github-actions[bot]"
git config user.email "github-actions[bot]@users.noreply.github.com"
# Create branch and commit
BRANCH_NAME="docs/enhance-blocks-$(date +%Y%m%d-%H%M%S)"
git checkout -b "$BRANCH_NAME"
git add docs/integrations/
git commit -m "docs: enhance block documentation with LLM-generated content
Pattern: ${{ inputs.block_pattern }}
Max blocks: ${{ inputs.max_blocks }}
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>"
# Push and create PR
git push -u origin "$BRANCH_NAME"
gh pr create \
--title "docs: LLM-enhanced block documentation" \
--body "## Summary
This PR contains LLM-enhanced documentation for block files matching pattern: \`${{ inputs.block_pattern }}\`
The following manual sections were improved:
- **How it works**: Technical explanations based on block implementations
- **Possible use case**: Practical, real-world examples
## Review Checklist
- [ ] Content is accurate based on block implementations
- [ ] Examples are practical and helpful
- [ ] No auto-generated sections were modified
---
🤖 Generated with [Claude Code](https://claude.com/claude-code)" \
--base dev

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@@ -0,0 +1,60 @@
name: AutoGPT Platform - Deploy Dev Environment
on:
push:
branches: [ dev ]
paths:
- 'autogpt_platform/**'
workflow_dispatch:
inputs:
git_ref:
description: 'Git ref (branch/tag) of AutoGPT to deploy'
required: true
default: 'master'
type: string
permissions:
contents: 'read'
id-token: 'write'
jobs:
migrate:
environment: develop
name: Run migrations for AutoGPT Platform
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v6
with:
ref: ${{ github.event.inputs.git_ref || github.ref_name }}
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Install Python dependencies
run: |
python -m pip install --upgrade pip
pip install prisma
- name: Run Backend Migrations
working-directory: ./autogpt_platform/backend
run: |
python -m prisma migrate deploy
env:
DATABASE_URL: ${{ secrets.BACKEND_DATABASE_URL }}
DIRECT_URL: ${{ secrets.BACKEND_DATABASE_URL }}
trigger:
needs: migrate
runs-on: ubuntu-latest
steps:
- name: Trigger deploy workflow
uses: peter-evans/repository-dispatch@v4
with:
token: ${{ secrets.DEPLOY_TOKEN }}
repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
event-type: build_deploy_dev
client-payload: '{"ref": "${{ github.event.inputs.git_ref || github.ref }}", "repository": "${{ github.repository }}"}'

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@@ -0,0 +1,54 @@
name: AutoGPT Platform - Deploy Prod Environment
on:
release:
types: [published]
workflow_dispatch:
permissions:
contents: 'read'
id-token: 'write'
jobs:
migrate:
environment: production
name: Run migrations for AutoGPT Platform
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v6
with:
ref: ${{ github.ref_name || 'master' }}
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Install Python dependencies
run: |
python -m pip install --upgrade pip
pip install prisma
- name: Run Backend Migrations
working-directory: ./autogpt_platform/backend
run: |
python -m prisma migrate deploy
env:
DATABASE_URL: ${{ secrets.BACKEND_DATABASE_URL }}
DIRECT_URL: ${{ secrets.BACKEND_DATABASE_URL }}
trigger:
needs: migrate
runs-on: ubuntu-latest
steps:
- name: Trigger deploy workflow
uses: peter-evans/repository-dispatch@v4
with:
token: ${{ secrets.DEPLOY_TOKEN }}
repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
event-type: build_deploy_prod
client-payload: |
{"ref": "${{ github.ref_name || 'master' }}", "repository": "${{ github.repository }}"}

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name: AutoGPT Platform - Backend CI
on:
push:
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:
concurrency:
group: ${{ format('backend-ci-{0}', github.head_ref && format('{0}-{1}', github.event_name, github.event.pull_request.number) || github.sha) }}
cancel-in-progress: ${{ startsWith(github.event_name, 'pull_request') }}
defaults:
run:
shell: bash
working-directory: autogpt_platform/backend
jobs:
lint:
permissions:
contents: read
timeout-minutes: 10
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v6
- name: Set up Python 3.12
uses: actions/setup-python@v5
with:
python-version: "3.12"
- name: Set up Python dependency cache
uses: actions/cache@v5
with:
path: ~/.cache/pypoetry
key: poetry-${{ 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: 15
strategy:
fail-fast: false
matrix:
python-version: ["3.11", "3.12", "3.13"]
runs-on: ubuntu-latest
services:
redis:
image: redis:latest
ports:
- 6379:6379
rabbitmq:
image: rabbitmq:4.1.4
ports:
- 5672:5672
env:
RABBITMQ_DEFAULT_USER: ${{ env.RABBITMQ_DEFAULT_USER }}
RABBITMQ_DEFAULT_PASS: ${{ env.RABBITMQ_DEFAULT_PASS }}
options: >-
--health-cmd "rabbitmq-diagnostics -q ping"
--health-interval 30s
--health-timeout 10s
--health-retries 5
--health-start-period 10s
clamav:
image: clamav/clamav-debian:latest
ports:
- 3310:3310
env:
CLAMAV_NO_FRESHCLAMD: false
CLAMD_CONF_StreamMaxLength: 50M
CLAMD_CONF_MaxFileSize: 100M
CLAMD_CONF_MaxScanSize: 100M
CLAMD_CONF_MaxThreads: 4
CLAMD_CONF_ReadTimeout: 300
options: >-
--health-cmd "clamdscan --version || exit 1"
--health-interval 30s
--health-timeout 10s
--health-retries 5
--health-start-period 180s
steps:
- name: Checkout repository
uses: actions/checkout@v6
with:
fetch-depth: 0
submodules: true
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
- name: Setup Supabase
uses: supabase/setup-cli@v1
with:
version: 1.178.1
- id: get_date
name: Get date
run: echo "date=$(date +'%Y-%m-%d')" >> $GITHUB_OUTPUT
- name: Set up Python dependency cache
uses: actions/cache@v5
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-py${{ matrix.python-version }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
- name: Install Poetry
run: |
# Extract Poetry version from backend/poetry.lock
HEAD_POETRY_VERSION=$(python ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
echo "Found Poetry version ${HEAD_POETRY_VERSION} in backend/poetry.lock"
if [ -n "$BASE_REF" ]; then
BASE_BRANCH=${BASE_REF/refs\/heads\//}
BASE_POETRY_VERSION=$((git show "origin/$BASE_BRANCH":./poetry.lock; true) | python ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry -)
echo "Found Poetry version ${BASE_POETRY_VERSION} in backend/poetry.lock on ${BASE_REF}"
POETRY_VERSION=$(printf '%s\n' "$HEAD_POETRY_VERSION" "$BASE_POETRY_VERSION" | sort -V | tail -n1)
else
POETRY_VERSION=$HEAD_POETRY_VERSION
fi
echo "Using Poetry version ${POETRY_VERSION}"
# Install Poetry
curl -sSL https://install.python-poetry.org | POETRY_VERSION=$POETRY_VERSION python3 -
if [ "${{ runner.os }}" = "macOS" ]; then
PATH="$HOME/.local/bin:$PATH"
echo "$HOME/.local/bin" >> $GITHUB_PATH
fi
env:
BASE_REF: ${{ github.base_ref || github.event.merge_group.base_ref }}
- name: Check poetry.lock
run: |
poetry lock
if ! git diff --quiet --ignore-matching-lines="^# " poetry.lock; then
echo "Error: poetry.lock not up to date."
echo
git diff poetry.lock
exit 1
fi
- name: Install Python dependencies
run: poetry install
- name: Generate Prisma Client
run: poetry run prisma generate && poetry run gen-prisma-stub
- id: supabase
name: Start Supabase
working-directory: .
run: |
supabase init
supabase start --exclude postgres-meta,realtime,storage-api,imgproxy,inbucket,studio,edge-runtime,logflare,vector,supavisor
supabase status -o env | sed 's/="/=/; s/"$//' >> $GITHUB_OUTPUT
# outputs:
# DB_URL, API_URL, GRAPHQL_URL, ANON_KEY, SERVICE_ROLE_KEY, JWT_SECRET
- name: Wait for ClamAV to be ready
run: |
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' || {
echo "ClamAV is not responding to PING"
docker logs $(docker ps -q --filter "ancestor=clamav/clamav-debian:latest") 2>&1 | tail -50 || echo "No ClamAV container found"
exit 1
}
- name: Run Database Migrations
run: poetry run prisma migrate deploy
env:
DATABASE_URL: ${{ steps.supabase.outputs.DB_URL }}
DIRECT_URL: ${{ steps.supabase.outputs.DB_URL }}
- name: Run pytest
run: |
if [[ "${{ runner.debug }}" == "1" ]]; then
poetry run pytest -s -vv -o log_cli=true -o log_cli_level=DEBUG
else
poetry run pytest -s -vv
fi
env:
LOG_LEVEL: ${{ runner.debug && 'DEBUG' || 'INFO' }}
DATABASE_URL: ${{ steps.supabase.outputs.DB_URL }}
DIRECT_URL: ${{ steps.supabase.outputs.DB_URL }}
SUPABASE_URL: ${{ steps.supabase.outputs.API_URL }}
SUPABASE_SERVICE_ROLE_KEY: ${{ steps.supabase.outputs.SERVICE_ROLE_KEY }}
JWT_VERIFY_KEY: ${{ steps.supabase.outputs.JWT_SECRET }}
REDIS_HOST: "localhost"
REDIS_PORT: "6379"
ENCRYPTION_KEY: "dvziYgz0KSK8FENhju0ZYi8-fRTfAdlz6YLhdB_jhNw=" # DO NOT USE IN PRODUCTION!!
# - name: Upload coverage reports to Codecov
# uses: codecov/codecov-action@v4
# with:
# token: ${{ secrets.CODECOV_TOKEN }}
# flags: backend,${{ runner.os }}
env:
CI: true
PLAIN_OUTPUT: True
RUN_ENV: local
PORT: 8080
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
# We know these are here, don't report this as a security vulnerability
# This is used as the default credential for the entire system's RabbitMQ instance
# If you want to replace this, you can do so by making our entire system generate
# new credentials for each local user and update the environment variables in
# the backend service, docker composes, and examples
RABBITMQ_DEFAULT_USER: "rabbitmq_user_default"
RABBITMQ_DEFAULT_PASS: "k0VMxyIJF9S35f3x2uaw5IWAl6Y536O7"

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name: AutoGPT Platform - Dev Deploy PR Event Dispatcher
on:
pull_request:
types: [closed]
issue_comment:
types: [created]
permissions:
issues: write
pull-requests: write
jobs:
dispatch:
runs-on: ubuntu-latest
steps:
- name: Check comment permissions and deployment status
id: check_status
if: github.event_name == 'issue_comment' && github.event.issue.pull_request
uses: actions/github-script@v8
with:
script: |
const commentBody = context.payload.comment.body.trim();
const commentUser = context.payload.comment.user.login;
const prAuthor = context.payload.issue.user.login;
const authorAssociation = context.payload.comment.author_association;
// Check permissions
const hasPermission = (
authorAssociation === 'OWNER' ||
authorAssociation === 'MEMBER' ||
authorAssociation === 'COLLABORATOR'
);
core.setOutput('comment_body', commentBody);
core.setOutput('has_permission', hasPermission);
if (!hasPermission && (commentBody === '!deploy' || commentBody === '!undeploy')) {
core.setOutput('permission_denied', 'true');
return;
}
if (commentBody !== '!deploy' && commentBody !== '!undeploy') {
return;
}
// Process deploy command
if (commentBody === '!deploy') {
core.setOutput('should_deploy', 'true');
}
// Process undeploy command
else if (commentBody === '!undeploy') {
core.setOutput('should_undeploy', 'true');
}
- name: Post permission denied comment
if: steps.check_status.outputs.permission_denied == 'true'
uses: actions/github-script@v8
with:
script: |
await github.rest.issues.createComment({
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: context.issue.number,
body: `❌ **Permission denied**: Only the repository owners, members, or collaborators can use deployment commands.`
});
- name: Get PR details for deployment
id: pr_details
if: steps.check_status.outputs.should_deploy == 'true' || steps.check_status.outputs.should_undeploy == 'true'
uses: actions/github-script@v8
with:
script: |
const pr = await github.rest.pulls.get({
owner: context.repo.owner,
repo: context.repo.repo,
pull_number: context.issue.number
});
core.setOutput('pr_number', pr.data.number);
core.setOutput('pr_title', pr.data.title);
core.setOutput('pr_state', pr.data.state);
- name: Dispatch Deploy Event
if: steps.check_status.outputs.should_deploy == 'true'
uses: peter-evans/repository-dispatch@v4
with:
token: ${{ secrets.DISPATCH_TOKEN }}
repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
event-type: pr-event
client-payload: |
{
"action": "deploy",
"pr_number": "${{ steps.pr_details.outputs.pr_number }}",
"pr_title": "${{ steps.pr_details.outputs.pr_title }}",
"pr_state": "${{ steps.pr_details.outputs.pr_state }}",
"repo": "${{ github.repository }}"
}
- name: Post deploy success comment
if: steps.check_status.outputs.should_deploy == 'true'
uses: actions/github-script@v8
with:
script: |
await github.rest.issues.createComment({
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: context.issue.number,
body: `🚀 **Deploying PR #${{ steps.pr_details.outputs.pr_number }}** to development environment...`
});
- name: Dispatch Undeploy Event (from comment)
if: steps.check_status.outputs.should_undeploy == 'true'
uses: peter-evans/repository-dispatch@v4
with:
token: ${{ secrets.DISPATCH_TOKEN }}
repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
event-type: pr-event
client-payload: |
{
"action": "undeploy",
"pr_number": "${{ steps.pr_details.outputs.pr_number }}",
"pr_title": "${{ steps.pr_details.outputs.pr_title }}",
"pr_state": "${{ steps.pr_details.outputs.pr_state }}",
"repo": "${{ github.repository }}"
}
- name: Post undeploy success comment
if: steps.check_status.outputs.should_undeploy == 'true'
uses: actions/github-script@v8
with:
script: |
await github.rest.issues.createComment({
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: context.issue.number,
body: `🗑️ **Undeploying PR #${{ steps.pr_details.outputs.pr_number }}** from development environment...`
});
- name: Check deployment status on PR close
id: check_pr_close
if: github.event_name == 'pull_request' && github.event.action == 'closed'
uses: actions/github-script@v8
with:
script: |
const comments = await github.rest.issues.listComments({
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: context.issue.number
});
let lastDeployIndex = -1;
let lastUndeployIndex = -1;
comments.data.forEach((comment, index) => {
if (comment.body.trim() === '!deploy') {
lastDeployIndex = index;
} else if (comment.body.trim() === '!undeploy') {
lastUndeployIndex = index;
}
});
// Should undeploy if there's a !deploy without a subsequent !undeploy
const shouldUndeploy = lastDeployIndex !== -1 && lastDeployIndex > lastUndeployIndex;
core.setOutput('should_undeploy', shouldUndeploy);
- name: Dispatch Undeploy Event (PR closed with active deployment)
if: >-
github.event_name == 'pull_request' &&
github.event.action == 'closed' &&
steps.check_pr_close.outputs.should_undeploy == 'true'
uses: peter-evans/repository-dispatch@v4
with:
token: ${{ secrets.DISPATCH_TOKEN }}
repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
event-type: pr-event
client-payload: |
{
"action": "undeploy",
"pr_number": "${{ github.event.pull_request.number }}",
"pr_title": "${{ github.event.pull_request.title }}",
"pr_state": "${{ github.event.pull_request.state }}",
"repo": "${{ github.repository }}"
}
- name: Post PR close undeploy comment
if: >-
github.event_name == 'pull_request' &&
github.event.action == 'closed' &&
steps.check_pr_close.outputs.should_undeploy == 'true'
uses: actions/github-script@v8
with:
script: |
await github.rest.issues.createComment({
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: context.issue.number,
body: `🧹 **Auto-undeploying**: PR closed with active deployment. Cleaning up development environment for PR #${{ github.event.pull_request.number }}.`
});

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name: AutoGPT Platform - Frontend CI
on:
push:
branches: [master, dev]
paths:
- ".github/workflows/platform-frontend-ci.yml"
- "autogpt_platform/frontend/**"
- "autogpt_platform/backend/Dockerfile"
- "autogpt_platform/docker-compose.yml"
- "autogpt_platform/docker-compose.platform.yml"
pull_request:
paths:
- ".github/workflows/platform-frontend-ci.yml"
- "autogpt_platform/frontend/**"
- "autogpt_platform/backend/Dockerfile"
- "autogpt_platform/docker-compose.yml"
- "autogpt_platform/docker-compose.platform.yml"
merge_group:
workflow_dispatch:
concurrency:
group: ${{ github.workflow }}-${{ github.event_name == 'merge_group' && format('merge-queue-{0}', github.ref) || format('{0}-{1}', github.ref, github.event.pull_request.number || github.sha) }}
cancel-in-progress: ${{ github.event_name == 'pull_request' }}
defaults:
run:
shell: bash
working-directory: autogpt_platform/frontend
jobs:
setup:
runs-on: ubuntu-latest
outputs:
components-changed: ${{ steps.filter.outputs.components }}
steps:
- name: Checkout repository
uses: actions/checkout@v6
- name: Check for component changes
uses: dorny/paths-filter@v3
id: filter
with:
filters: |
components:
- 'autogpt_platform/frontend/src/components/**'
- name: Enable corepack
run: corepack enable
- name: 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: Install dependencies to populate cache
run: pnpm install --frozen-lockfile
lint:
runs-on: ubuntu-latest
needs: setup
steps:
- name: Checkout repository
uses: actions/checkout@v6
- name: Enable corepack
run: corepack enable
- name: 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: Install dependencies
run: pnpm install --frozen-lockfile
- name: Run lint
run: pnpm lint
chromatic:
runs-on: ubuntu-latest
needs: setup
# Disabled: to re-enable, remove 'false &&' from the condition below
if: >-
false
&& (github.ref == 'refs/heads/dev' || github.base_ref == 'dev')
&& needs.setup.outputs.components-changed == 'true'
steps:
- name: Checkout repository
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Enable corepack
run: corepack enable
- name: 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: Install dependencies
run: pnpm install --frozen-lockfile
- name: Run Chromatic
uses: chromaui/action@latest
with:
projectToken: chpt_9e7c1a76478c9c8
onlyChanged: true
workingDir: autogpt_platform/frontend
token: ${{ secrets.GITHUB_TOKEN }}
exitOnceUploaded: true
integration_test:
runs-on: ubuntu-latest
needs: setup
steps:
- name: Checkout repository
uses: actions/checkout@v6
with:
submodules: recursive
- name: Enable corepack
run: corepack enable
- name: 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: Install dependencies
run: pnpm install --frozen-lockfile
- name: Generate API client
run: pnpm generate:api
- name: Run Integration Tests
run: pnpm test:unit

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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:
concurrency:
group: ${{ github.workflow }}-${{ github.event_name == 'merge_group' && format('merge-queue-{0}', github.ref) || github.head_ref && format('pr-{0}', github.event.pull_request.number) || github.sha }}
cancel-in-progress: ${{ github.event_name == 'pull_request' }}
defaults:
run:
shell: bash
working-directory: autogpt_platform/frontend
jobs:
setup:
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v6
- name: Enable corepack
run: corepack enable
- name: Set up Node
uses: actions/setup-node@v6
with:
node-version: "22.18.0"
cache: "pnpm"
cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
- name: Install dependencies to populate cache
run: pnpm install --frozen-lockfile
check-api-types:
name: check API types
runs-on: ubuntu-latest
needs: setup
steps:
- name: Checkout repository
uses: actions/checkout@v6
with:
submodules: recursive
# ------------------------ Backend setup ------------------------
- name: Set up Backend - Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.12"
- name: Set up Backend - Install Poetry
working-directory: autogpt_platform/backend
run: |
POETRY_VERSION=$(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: Set up Frontend - Install dependencies
run: pnpm install --frozen-lockfile
- 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 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 "\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: 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: ${{ secrets.OPENAI_API_KEY }}
- name: Set up Platform - Set up Docker Buildx
uses: docker/setup-buildx-action@v3
with:
driver: docker-container
driver-opts: network=host
- name: Set up Platform - Expose GHA cache to docker buildx CLI
uses: crazy-max/ghaction-github-runtime@v4
- name: Set up Platform - Build Docker images (with cache)
working-directory: autogpt_platform
run: |
pip install pyyaml
# Resolve extends and generate a flat compose file that bake can understand
docker compose -f docker-compose.yml config > docker-compose.resolved.yml
# Add cache configuration to the resolved compose file
python ../.github/workflows/scripts/docker-ci-fix-compose-build-cache.py \
--source docker-compose.resolved.yml \
--cache-from "type=gha" \
--cache-to "type=gha,mode=max" \
--backend-hash "${{ 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-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: 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: 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

39
.github/workflows/pr-overlap-check.yml vendored Normal file
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name: PR Overlap Detection
on:
pull_request:
types: [opened, synchronize, reopened]
branches:
- dev
- master
permissions:
contents: read
pull-requests: write
jobs:
check-overlaps:
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v4
with:
fetch-depth: 0 # Need full history for merge testing
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Configure git
run: |
git config user.email "github-actions[bot]@users.noreply.github.com"
git config user.name "github-actions[bot]"
- name: Run overlap detection
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Always succeed - this check informs contributors, it shouldn't block merging
continue-on-error: true
run: |
python .github/scripts/detect_overlaps.py ${{ github.event.pull_request.number }}

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name: Repo - Close stale issues
on:
schedule:
- cron: '30 1 * * *'
workflow_dispatch:
permissions:
issues: write
jobs:
stale:
runs-on: ubuntu-latest
steps:
- uses: actions/stale@v10
with:
# operations-per-run: 5000
stale-issue-message: >
This issue has automatically been marked as _stale_ because it has not had
any activity in the last 170 days. You can _unstale_ it by commenting or
removing the label. Otherwise, this issue will be closed in 10 days.
stale-pr-message: >
This pull request has automatically been marked as _stale_ because it has
not had any activity in the last 50 days. You can _unstale_ it by commenting
or removing the label.
close-issue-message: >
This issue was closed automatically because it has been stale for 10 days
with no activity.
days-before-stale: 170
days-before-close: 10
# Do not touch meta issues:
exempt-issue-labels: meta,fridge,project management
# Do not affect pull requests:
days-before-pr-stale: -1
days-before-pr-close: -1

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name: Repo - Enforce dev as base branch
on:
pull_request_target:
branches: [ master ]
types: [ opened ]
jobs:
check_pr_target:
runs-on: ubuntu-latest
permissions:
pull-requests: write
steps:
- name: Check if PR is from dev or hotfix
if: ${{ !(startsWith(github.event.pull_request.head.ref, 'hotfix/') || github.event.pull_request.head.ref == 'dev') }}
run: |
gh pr comment ${{ github.event.number }} --repo "$REPO" \
--body $'This PR targets the `master` branch but does not come from `dev` or a `hotfix/*` branch.\n\nAutomatically setting the base branch to `dev`.'
gh pr edit ${{ github.event.number }} --base dev --repo "$REPO"
env:
GITHUB_TOKEN: ${{ github.token }}
REPO: ${{ github.repository }}

66
.github/workflows/repo-pr-label.yml vendored Normal file
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name: Repo - Pull Request auto-label
on:
# So that PRs touching the same files as the push are updated
push:
branches: [ master, dev, release-* ]
paths-ignore:
- 'classic/forge/tests/vcr_cassettes'
- 'classic/benchmark/reports/**'
# So that the `dirtyLabel` is removed if conflicts are resolve
# We recommend `pull_request_target` so that github secrets are available.
# In `pull_request` we wouldn't be able to change labels of fork PRs
pull_request_target:
types: [ opened, synchronize ]
concurrency:
group: ${{ format('pr-label-{0}', github.event.pull_request.number || github.sha) }}
cancel-in-progress: true
jobs:
conflicts:
runs-on: ubuntu-latest
permissions:
contents: read
pull-requests: write
steps:
- name: Update PRs with conflict labels
uses: eps1lon/actions-label-merge-conflict@releases/2.x
with:
dirtyLabel: "conflicts"
#removeOnDirtyLabel: "PR: ready to ship"
repoToken: "${{ secrets.GITHUB_TOKEN }}"
commentOnDirty: "This pull request has conflicts with the base branch, please resolve those so we can evaluate the pull request."
commentOnClean: "Conflicts have been resolved! 🎉 A maintainer will review the pull request shortly."
size:
if: ${{ github.event_name == 'pull_request_target' }}
permissions:
issues: write
pull-requests: write
runs-on: ubuntu-latest
steps:
- uses: codelytv/pr-size-labeler@v1
with:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
xs_label: 'size/xs'
xs_max_size: 2
s_label: 'size/s'
s_max_size: 10
m_label: 'size/m'
m_max_size: 100
l_label: 'size/l'
l_max_size: 500
xl_label: 'size/xl'
message_if_xl:
scope:
if: ${{ github.event_name == 'pull_request_target' }}
permissions:
contents: read
pull-requests: write
runs-on: ubuntu-latest
steps:
- uses: actions/labeler@v6
with:
sync-labels: true

20
.github/workflows/repo-stats.yml vendored Normal file
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name: Repo - Github Stats
on:
schedule:
# Run this once per day, towards the end of the day for keeping the most
# recent data point most meaningful (hours are interpreted in UTC).
- cron: "0 23 * * *"
workflow_dispatch: # Allow for running this manually.
jobs:
j1:
name: github-repo-stats
runs-on: ubuntu-latest
steps:
- name: run-ghrs
# Use latest release.
uses: jgehrcke/github-repo-stats@HEAD
with:
ghtoken: ${{ secrets.ghrs_github_api_token }}

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name: Repo - PR Status Checker
on:
pull_request:
types: [opened, synchronize, reopened]
merge_group:
jobs:
status-check:
name: Check PR Status
runs-on: ubuntu-latest
steps:
# - name: Wait some time for all actions to start
# run: sleep 30
- uses: actions/checkout@v6
# with:
# fetch-depth: 0
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.10"
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install requests
- name: Check PR Status
run: |
echo "Current directory before running Python script:"
pwd
echo "Attempting to run Python script:"
python .github/workflows/scripts/check_actions_status.py
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

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import json
import os
import requests
import sys
import time
from typing import Dict, List, Tuple
CHECK_INTERVAL = 30
def get_environment_variables() -> Tuple[str, str, str, str, str]:
"""Retrieve and return necessary environment variables."""
try:
with open(os.environ["GITHUB_EVENT_PATH"]) as f:
event = json.load(f)
# Handle both PR and merge group events
if "pull_request" in event:
sha = event["pull_request"]["head"]["sha"]
else:
sha = os.environ["GITHUB_SHA"]
return (
os.environ["GITHUB_API_URL"],
os.environ["GITHUB_REPOSITORY"],
sha,
os.environ["GITHUB_TOKEN"],
os.environ["GITHUB_RUN_ID"],
)
except KeyError as e:
print(f"Error: Missing required environment variable or event data: {e}")
sys.exit(1)
def make_api_request(url: str, headers: Dict[str, str]) -> Dict:
"""Make an API request and return the JSON response."""
try:
print("Making API request to:", url)
response = requests.get(url, headers=headers, timeout=10)
response.raise_for_status()
return response.json()
except requests.RequestException as e:
print(f"Error: API request failed. {e}")
sys.exit(1)
def process_check_runs(check_runs: List[Dict]) -> Tuple[bool, bool]:
"""Process check runs and return their status."""
runs_in_progress = False
all_others_passed = True
for run in check_runs:
if str(run["name"]) != "Check PR Status":
status = run["status"]
conclusion = run["conclusion"]
if status == "completed":
if conclusion not in ["success", "skipped", "neutral"]:
all_others_passed = False
print(
f"Check run {run['name']} (ID: {run['id']}) has conclusion: {conclusion}"
)
else:
runs_in_progress = True
print(f"Check run {run['name']} (ID: {run['id']}) is still {status}.")
all_others_passed = False
else:
print(
f"Skipping check run {run['name']} (ID: {run['id']}) as it is the current run."
)
return runs_in_progress, all_others_passed
def main():
api_url, repo, sha, github_token, current_run_id = get_environment_variables()
endpoint = f"{api_url}/repos/{repo}/commits/{sha}/check-runs"
headers = {
"Accept": "application/vnd.github.v3+json",
}
if github_token:
headers["Authorization"] = f"token {github_token}"
print(f"Current run ID: {current_run_id}")
while True:
data = make_api_request(endpoint, headers)
check_runs = data["check_runs"]
print("Processing check runs...")
print(check_runs)
runs_in_progress, all_others_passed = process_check_runs(check_runs)
if not runs_in_progress:
break
print(
"Some check runs are still in progress. "
f"Waiting {CHECK_INTERVAL} seconds before checking again..."
)
time.sleep(CHECK_INTERVAL)
if all_others_passed:
print("All other completed check runs have passed. This check passes.")
sys.exit(0)
else:
print("Some check runs have failed or have not completed. This check fails.")
sys.exit(1)
if __name__ == "__main__":
main()

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#!/usr/bin/env python3
"""
Add cache configuration to a resolved docker-compose file for all services
that have a build key, and ensure image names match what docker compose expects.
"""
import argparse
import yaml
DEFAULT_BRANCH = "dev"
CACHE_BUILDS_FOR_COMPONENTS = ["backend", "frontend"]
def main():
parser = argparse.ArgumentParser(
description="Add cache config to a resolved compose file"
)
parser.add_argument(
"--source",
required=True,
help="Source compose file to read (should be output of `docker compose config`)",
)
parser.add_argument(
"--cache-from",
default="type=gha",
help="Cache source configuration",
)
parser.add_argument(
"--cache-to",
default="type=gha,mode=max",
help="Cache destination configuration",
)
for component in CACHE_BUILDS_FOR_COMPONENTS:
parser.add_argument(
f"--{component}-hash",
default="",
help=f"Hash for {component} cache scope (e.g., from hashFiles())",
)
parser.add_argument(
"--git-ref",
default="",
help="Git ref for branch-based cache scope (e.g., refs/heads/master)",
)
args = parser.parse_args()
# Normalize git ref to a safe scope name (e.g., refs/heads/master -> master)
git_ref_scope = ""
if args.git_ref:
git_ref_scope = args.git_ref.replace("refs/heads/", "").replace("/", "-")
with open(args.source, "r") as f:
compose = yaml.safe_load(f)
# Get project name from compose file or default
project_name = compose.get("name", "autogpt_platform")
def get_image_name(dockerfile: str, target: str) -> str:
"""Generate image name based on Dockerfile folder and build target."""
dockerfile_parts = dockerfile.replace("\\", "/").split("/")
if len(dockerfile_parts) >= 2:
folder_name = dockerfile_parts[-2] # e.g., "backend" or "frontend"
else:
folder_name = "app"
return f"{project_name}-{folder_name}:{target}"
def get_build_key(dockerfile: str, target: str) -> str:
"""Generate a unique key for a Dockerfile+target combination."""
return f"{dockerfile}:{target}"
def get_component(dockerfile: str) -> str | None:
"""Get component name (frontend/backend) from dockerfile path."""
for component in CACHE_BUILDS_FOR_COMPONENTS:
if component in dockerfile:
return component
return None
# First pass: collect all services with build configs and identify duplicates
# Track which (dockerfile, target) combinations we've seen
build_key_to_first_service: dict[str, str] = {}
services_to_build: list[str] = []
services_to_dedupe: list[str] = []
for service_name, service_config in compose.get("services", {}).items():
if "build" not in service_config:
continue
build_config = service_config["build"]
dockerfile = build_config.get("dockerfile", "Dockerfile")
target = build_config.get("target", "default")
build_key = get_build_key(dockerfile, target)
if build_key not in build_key_to_first_service:
# First service with this build config - it will do the actual build
build_key_to_first_service[build_key] = service_name
services_to_build.append(service_name)
else:
# Duplicate - will just use the image from the first service
services_to_dedupe.append(service_name)
# Second pass: configure builds and deduplicate
modified_services = []
for service_name, service_config in compose.get("services", {}).items():
if "build" not in service_config:
continue
build_config = service_config["build"]
dockerfile = build_config.get("dockerfile", "Dockerfile")
target = build_config.get("target", "latest")
image_name = get_image_name(dockerfile, target)
# Set image name for all services (needed for both builders and deduped)
service_config["image"] = image_name
if service_name in services_to_dedupe:
# Remove build config - this service will use the pre-built image
del service_config["build"]
continue
# This service will do the actual build - add cache config
cache_from_list = []
cache_to_list = []
component = get_component(dockerfile)
if not component:
# Skip services that don't clearly match frontend/backend
continue
# Get the hash for this component
component_hash = getattr(args, f"{component}_hash")
# Scope format: platform-{component}-{target}-{hash|ref}
# Example: platform-backend-server-abc123
if "type=gha" in args.cache_from:
# 1. Primary: exact hash match (most specific)
if component_hash:
hash_scope = f"platform-{component}-{target}-{component_hash}"
cache_from_list.append(f"{args.cache_from},scope={hash_scope}")
# 2. Fallback: branch-based cache
if git_ref_scope:
ref_scope = f"platform-{component}-{target}-{git_ref_scope}"
cache_from_list.append(f"{args.cache_from},scope={ref_scope}")
# 3. Fallback: dev branch cache (for PRs/feature branches)
if git_ref_scope and git_ref_scope != DEFAULT_BRANCH:
master_scope = f"platform-{component}-{target}-{DEFAULT_BRANCH}"
cache_from_list.append(f"{args.cache_from},scope={master_scope}")
if "type=gha" in args.cache_to:
# Write to both hash-based and branch-based scopes
if component_hash:
hash_scope = f"platform-{component}-{target}-{component_hash}"
cache_to_list.append(f"{args.cache_to},scope={hash_scope}")
if git_ref_scope:
ref_scope = f"platform-{component}-{target}-{git_ref_scope}"
cache_to_list.append(f"{args.cache_to},scope={ref_scope}")
# Ensure we have at least one cache source/target
if not cache_from_list:
cache_from_list.append(args.cache_from)
if not cache_to_list:
cache_to_list.append(args.cache_to)
build_config["cache_from"] = cache_from_list
build_config["cache_to"] = cache_to_list
modified_services.append(service_name)
# Write back to the same file
with open(args.source, "w") as f:
yaml.dump(compose, f, default_flow_style=False, sort_keys=False)
print(f"Added cache config to {len(modified_services)} services in {args.source}:")
for svc in modified_services:
svc_config = compose["services"][svc]
build_cfg = svc_config.get("build", {})
cache_from_list = build_cfg.get("cache_from", ["none"])
cache_to_list = build_cfg.get("cache_to", ["none"])
print(f" - {svc}")
print(f" image: {svc_config.get('image', 'N/A')}")
print(f" cache_from: {cache_from_list}")
print(f" cache_to: {cache_to_list}")
if services_to_dedupe:
print(
f"Deduplicated {len(services_to_dedupe)} services (will use pre-built images):"
)
for svc in services_to_dedupe:
print(f" - {svc} -> {compose['services'][svc].get('image', 'N/A')}")
if __name__ == "__main__":
main()

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@@ -0,0 +1,98 @@
#!/bin/bash
meta=$(docker image inspect "$IMAGE_NAME" | jq '.[0]')
head_compare_url=$(sed "s/{base}/$base_branch/; s/{head}/$current_ref/" <<< $compare_url_template)
ref_compare_url=$(sed "s/{base}/$base_branch/; s/{head}/$commit_hash/" <<< $compare_url_template)
EOF=$(dd if=/dev/urandom bs=15 count=1 status=none | base64)
cat << $EOF
# Docker Build summary 🔨
**Source:** branch \`$current_ref\` -> [$repository@\`${commit_hash:0:7}\`]($source_url)
**Build type:** \`$build_type\`
**Image size:** $((`jq -r .Size <<< $meta` / 10**6))MB
## Image details
**Tags:**
$(jq -r '.RepoTags | map("* `\(.)`") | join("\n")' <<< $meta)
<details>
<summary><h3>Layers</h3></summary>
| Age | Size | Created by instruction |
| --------- | ------ | ---------------------- |
$(docker history --no-trunc --format "{{.CreatedSince}}\t{{.Size}}\t\`{{.CreatedBy}}\`\t{{.Comment}}" $IMAGE_NAME \
| grep 'buildkit.dockerfile' `# filter for layers created in this build process`\
| cut -f-3 `# yeet Comment column`\
| sed 's/ ago//' `# fix Layer age`\
| sed 's/ # buildkit//' `# remove buildkit comment from instructions`\
| sed 's/\$/\\$/g' `# escape variable and shell expansions`\
| sed 's/|/\\|/g' `# escape pipes so they don't interfere with column separators`\
| column -t -s$'\t' -o' | ' `# align columns and add separator`\
| sed 's/^/| /; s/$/ |/' `# add table row start and end pipes`)
</details>
<details>
<summary><h3>ENV</h3></summary>
| Variable | Value |
| -------- | -------- |
$(jq -r \
'.Config.Env
| map(
split("=")
| "\(.[0]) | `\(.[1] | gsub("\\s+"; " "))`"
)
| map("| \(.) |")
| .[]' <<< $meta
)
</details>
<details>
<summary>Raw metadata</summary>
\`\`\`JSON
$meta
\`\`\`
</details>
## Build details
**Build trigger:** $push_forced_label $event_name \`$event_ref\`
<details>
<summary><code>github</code> context</summary>
\`\`\`JSON
$github_context_json
\`\`\`
</details>
### Source
**HEAD:** [$repository@\`${commit_hash:0:7}\`]($source_url) on branch [$current_ref]($ref_compare_url)
**Diff with previous HEAD:** $head_compare_url
#### New commits
$(jq -r 'map([
"**Commit [`\(.id[0:7])`](\(.url)) by \(if .author.username then "@"+.author.username else .author.name end):**",
.message,
(if .committer.name != .author.name then "\n> <sub>**Committer:** \(.committer.name) <\(.committer.email)></sub>" else "" end),
"<sub>**Timestamp:** \(.timestamp)</sub>"
] | map("> \(.)\n") | join("")) | join("\n")' <<< $new_commits_json)
### Job environment
#### \`vars\` context:
\`\`\`JSON
$vars_json
\`\`\`
#### \`env\` context:
\`\`\`JSON
$job_env_json
\`\`\`
$EOF

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#!/bin/bash
meta=$(docker image inspect "$IMAGE_NAME" | jq '.[0]')
EOF=$(dd if=/dev/urandom bs=15 count=1 status=none | base64)
cat << $EOF
# Docker Release Build summary 🚀🔨
**Source:** $ref_type \`$current_ref\` -> [$repository@\`${commit_hash:0:7}\`]($source_url)
**Image size:** $((`jq -r .Size <<< $meta` / 10**6))MB
## Image details
**Tags:**
$(jq -r '.RepoTags | map("* `\(.)`") | join("\n")' <<< $meta)
<details>
<summary><h3>Layers</h3></summary>
| Age | Size | Created by instruction |
| --------- | ------ | ---------------------- |
$(docker history --no-trunc --format "{{.CreatedSince}}\t{{.Size}}\t\`{{.CreatedBy}}\`\t{{.Comment}}" $IMAGE_NAME \
| grep 'buildkit.dockerfile' `# filter for layers created in this build process`\
| cut -f-3 `# yeet Comment column`\
| sed 's/ ago//' `# fix Layer age`\
| sed 's/ # buildkit//' `# remove buildkit comment from instructions`\
| sed 's/\$/\\$/g' `# escape variable and shell expansions`\
| sed 's/|/\\|/g' `# escape pipes so they don't interfere with column separators`\
| column -t -s$'\t' -o' | ' `# align columns and add separator`\
| sed 's/^/| /; s/$/ |/' `# add table row start and end pipes`)
</details>
<details>
<summary><h3>ENV</h3></summary>
| Variable | Value |
| -------- | -------- |
$(jq -r \
'.Config.Env
| map(
split("=")
| "\(.[0]) | `\(.[1] | gsub("\\s+"; " "))`"
)
| map("| \(.) |")
| .[]' <<< $meta
)
</details>
<details>
<summary>Raw metadata</summary>
\`\`\`JSON
$meta
\`\`\`
</details>
## Build details
**Build trigger:** $event_name \`$current_ref\`
| Parameter | Value |
| -------------- | ------------ |
| \`no_cache\` | \`$inputs_no_cache\` |
<details>
<summary><code>github</code> context</summary>
\`\`\`JSON
$github_context_json
\`\`\`
</details>
### Job environment
#### \`vars\` context:
\`\`\`JSON
$vars_json
\`\`\`
#### \`env\` context:
\`\`\`JSON
$job_env_json
\`\`\`
$EOF

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