ci: cut Actions spend across PR/push triggers - #12955
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- classic-python-checks: scope path filters to classic/**.py instead of repo-wide **.py so unrelated changes don't trigger the workflow. - platform-backend: drop the 3.11/3.12/3.13 pyright + pytest matrix down to 3.13 (the prod runtime), removing 2/3 of the per-PR runs. - platform-fullstack: add a preflight-e2e gate that waits for backend + frontend CI on the same SHA and skips the big-boi E2E job if upstream failed or didn't run. - repo-pr-label: only fan out on push to master (was master/dev/release-*) since master holds the bulk of open PRs. - repo-workflow-checker: switch from pull_request polling to workflow_run, evaluate once per upstream completion, and post a single "Check PR Status" check-run for branch protection. - check_actions_status.py: rewrite around the workflow_run model (paginated check-runs, brief settle retry, no polling loop). - wait_for_upstream.py: new helper that gates the E2E job on named upstream workflow runs by head SHA. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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🔇 Additional comments (3)
WalkthroughAdds a preflight gating job and polling script to block E2E until upstream CI runs for the same commit are acceptable, pins backend CI to Python 3.13 (removing python-version matrix), and tightens workflow trigger path/branch filters and paths-ignore globs across workflows. (33 words) Changes
Sequence DiagramsequenceDiagram
actor GH as GitHub Actions
participant Preflight as preflight-e2e Job / script
participant API as GitHub REST API
participant Upstream as Upstream CI Workflows
participant E2E as e2e_test Job
GH->>Preflight: start preflight-e2e (job)
Preflight->>API: list workflow runs for HEAD_SHA (paginated)
API->>Upstream: return runs (status, conclusion)
API-->>Preflight: latest runs per workflow
alt Any upstream failed
Preflight->>GH: set output `proceed=false`
GH->>E2E: skip e2e_test (if condition fails)
else All upstream complete (success/neutral/skipped)
Preflight->>GH: set output `proceed=true`
GH->>E2E: run e2e_test
E2E->>E2E: execute E2E steps
else Timeout / API error
Preflight->>GH: set `proceed=false`, exit non‑zero
GH->>E2E: skip e2e_test
end
Estimated code review effort🎯 3 (Moderate) | ⏱️ ~22 minutes Possibly related PRs
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Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## dev #12955 +/- ##
==========================================
+ Coverage 69.52% 69.56% +0.03%
==========================================
Files 2105 2115 +10
Lines 157113 157577 +464
Branches 16200 16233 +33
==========================================
+ Hits 109236 109614 +378
- Misses 44666 44740 +74
- Partials 3211 3223 +12
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Actionable comments posted: 1
🧹 Nitpick comments (1)
.github/workflows/scripts/wait_for_upstream.py (1)
75-76: ⚡ Quick winMake latest-run selection deterministic beyond
run_numberAt Line 75, using only
run_numbercan select the wrong candidate in edge cases (re-runs / mixed run contexts on same SHA). Prefer a stronger ordering key (e.g.,created_at+id, optionallyrun_attempt) when deciding the latest run per workflow name.Proposed patch
- if prev is None or run["run_number"] > prev["run_number"]: + prev_key = ( + prev.get("run_number", -1), + prev.get("run_attempt", -1), + prev.get("id", -1), + ) if prev else (-1, -1, -1) + run_key = ( + run.get("run_number", -1), + run.get("run_attempt", -1), + run.get("id", -1), + ) + if prev is None or run_key > prev_key: by_name[name] = run🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In @.github/workflows/scripts/wait_for_upstream.py around lines 75 - 76, The current selection logic that updates by_name[name] using only run["run_number"] is non-deterministic for reruns; change the comparison to use a deterministic composite key (e.g., (run["created_at"], run.get("run_attempt", run["run_number"]), run["id"]) or similar) so the newest run is chosen unambiguously. In the block that currently checks if prev is None or run["run_number"] > prev["run_number"], compute comparable tuples for both run and prev (referencing variables run, prev, by_name, name) and replace the numeric comparison with tuple comparison to pick the latest run deterministically. Ensure created_at is parsed/used consistently (string ISO timestamps compare lexicographically) and include run["id"] as a final tiebreaker.
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Inline comments:
In @.github/workflows/scripts/wait_for_upstream.py:
- Around line 112-113: fetch_runs call can throw transient requests errors and
currently aborts preflight; modify the polling loop around fetch_runs(env,
headers) so it catches requests.RequestException (or whichever requests
exception type is used), log the error via the existing logger, sleep briefly,
and continue retrying until the MAX_WAIT_SECONDS deadline is reached before
giving up; keep using latest_per_workflow(...) only when fetch_runs succeeds and
ensure the catch uses the same env/headers context so intermittent HTTP/timeouts
don't terminate the job prematurely.
---
Nitpick comments:
In @.github/workflows/scripts/wait_for_upstream.py:
- Around line 75-76: The current selection logic that updates by_name[name]
using only run["run_number"] is non-deterministic for reruns; change the
comparison to use a deterministic composite key (e.g., (run["created_at"],
run.get("run_attempt", run["run_number"]), run["id"]) or similar) so the newest
run is chosen unambiguously. In the block that currently checks if prev is None
or run["run_number"] > prev["run_number"], compute comparable tuples for both
run and prev (referencing variables run, prev, by_name, name) and replace the
numeric comparison with tuple comparison to pick the latest run
deterministically. Ensure created_at is parsed/used consistently (string ISO
timestamps compare lexicographically) and include run["id"] as a final
tiebreaker.
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
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Review profile: CHILL
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- GitHub Check: check API types
- GitHub Check: Wait for upstream CI
- GitHub Check: test
- GitHub Check: type-check
- GitHub Check: Check PR Status
- GitHub Check: Analyze (typescript)
- GitHub Check: Analyze (python)
🧰 Additional context used
🧠 Learnings (3)
📓 Common learnings
Learnt from: CR
Repo: Significant-Gravitas/AutoGPT PR: 0
File: AGENTS.md:0-0
Timestamp: 2026-04-08T17:27:45.740Z
Learning: Use the template in `.github/PULL_REQUEST_TEMPLATE.md` for pull requests, rely on pre-commit checks for linting and formatting, fill out the Changes section and checklist, use conventional commit titles with scope, keep out-of-scope changes under 20% of the PR, ensure PR descriptions are complete, and use linear ticket branch structure
Learnt from: CR
Repo: Significant-Gravitas/AutoGPT PR: 0
File: autogpt_platform/AGENTS.md:0-0
Timestamp: 2026-04-08T17:27:57.501Z
Learning: Split PRs by concern — each PR should have a single clear purpose (e.g., separate PRs for 'usage tracking' and 'credit charging' even if related)
📚 Learning: 2026-04-13T13:11:00.401Z
Learnt from: 0ubbe
Repo: Significant-Gravitas/AutoGPT PR: 12764
File: autogpt_platform/frontend/src/app/(platform)/copilot/components/EmptySession/EmptySession.tsx:41-42
Timestamp: 2026-04-13T13:11:00.401Z
Learning: In Significant-Gravitas/AutoGPT `autogpt_platform/frontend`, unconditional React Query hook calls (e.g. `usePulseChips()` in `EmptySession.tsx`) are intentional when the underlying data is expected to be cached from prior page visits. The team considers the fetch cost acceptable in these cases and does not require `enabled` gating purely for feature-flag-disabled paths. Do not flag unconditional query hooks as wasteful when caching makes the cost negligible.
Applied to files:
.github/workflows/scripts/wait_for_upstream.py
📚 Learning: 2026-03-24T02:05:08.144Z
Learnt from: majdyz
Repo: Significant-Gravitas/AutoGPT PR: 12526
File: autogpt_platform/frontend/src/app/(platform)/copilot/CopilotPage.tsx:0-0
Timestamp: 2026-03-24T02:05:08.144Z
Learning: In `Significant-Gravitas/AutoGPT` (autogpt_platform frontend), when gating logic on a React Query result being available (e.g., `useGetV2GetCopilotUsage`), prefer destructuring `isSuccess` (e.g., `const { data, isSuccess: hasUsage } = useQuery(...)`) over checking `!isLoading`. `isLoading` can be `false` in error/idle states where `data` is still `undefined`, while `isSuccess` guarantees the query completed successfully and `data` is populated. This pattern was established in `CopilotPage.tsx` (PR `#12526`, commit e9dfd1f76).
Applied to files:
.github/workflows/scripts/wait_for_upstream.py
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Actionable comments posted: 2
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Inline comments:
In @.github/workflows/scripts/wait_for_upstream.py:
- Around line 143-164: The current logic in the block using variables missing,
grace_deadline and MISSING_GRACE_SECONDS treats "still missing after grace" as a
pass and calls write_output("proceed", "true"); change this so that if missing
is non-empty after the grace deadline (and in_progress is false) we treat the
upstream as not triggered and do not proceed: call write_output("proceed",
"false") (and update the printed message to reflect a skip/fail decision)
instead of returning success; keep the existing behavior of proceeding only when
the required workflows are present (i.e., when missing is empty) and still log
by_name.keys() when proceeding.
- Around line 67-76: The function latest_per_workflow selects the latest run
using only run_number; change the comparison in latest_per_workflow to consider
both run_number and run_attempt (compare the tuple (run["run_number"],
run.get("run_attempt", 0)) against the stored run's tuple) so that when
run_number is equal the higher run_attempt (more recent attempt) wins; update
the assignment to store the entire run as before and ensure you handle missing
run_attempt by defaulting to 0.
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
ℹ️ Review info
⚙️ Run configuration
Configuration used: Organization UI
Review profile: CHILL
Plan: Pro
Run ID: c520e2c1-006e-4f05-9ef1-710219a35ed8
📒 Files selected for processing (1)
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⏰ Context from checks skipped due to timeout of 90000ms. You can increase the timeout in your CodeRabbit configuration to a maximum of 15 minutes (900000ms). (7)
- GitHub Check: check API types
- GitHub Check: test
- GitHub Check: type-check
- GitHub Check: Wait for upstream CI
- GitHub Check: Check PR Status
- GitHub Check: Analyze (typescript)
- GitHub Check: Analyze (python)
🧰 Additional context used
🧠 Learnings (13)
📓 Common learnings
Learnt from: majdyz
Repo: Significant-Gravitas/AutoGPT PR: 0
File: :0-0
Timestamp: 2026-04-28T03:31:29.696Z
Learning: In Significant-Gravitas/AutoGPT PR `#12933` (`fix/stripe-checkout-link-auth-loop`), the initial approach of pinning `payment_method_types=["card"]` in `top_up_intent` and `create_subscription_checkout` (in `autogpt_platform/backend/backend/data/credit.py`) was reverted in commit `584b43a71` as it patched a symptom. The true root cause was in `update_subscription_tier()` in `v1.py`: a `current_tier_price_id is not None` guard was gating admin-granted DB-tier flips and short-circuiting them when the BUSINESS tier was pruned from the price-id LaunchDarkly flag. Do NOT flag `payment_method_types` absence in these checkout helpers as a Stripe Link bypass issue; the fix lives in the subscription tier update guard logic.
Learnt from: majdyz
Repo: Significant-Gravitas/AutoGPT PR: 0
File: :0-0
Timestamp: 2026-04-25T02:53:53.964Z
Learning: In `autogpt_platform/backend/backend/copilot/sdk/service.py` (PR `#12918`, commit 6576bf561):
- `_flush_unresolved_tool_calls` was renamed to `flush_unresolved_tool_calls` (public); all call sites updated, `# noqa: SLF001` suppressor removed.
- `_flush_orphan_tool_uses_to_session` and `_InterruptedAttempt.finalize` both return `list[StreamBaseResponse]`; the post-loop caller yields those events directly to avoid double-flush and skipped UI cleanup events.
- The three former post-loop blocks (partial restore + redundant re-flush + two separate `yield StreamError` sites) are collapsed into a single block driven by `_classify_final_failure` returning a `_FinalFailure(display_msg, code, retryable)` dataclass, so history marker and SSE yield share one source of truth.
Do NOT flag double-flush risk or mismatched history/SSE marker as issues in the post-loop section of `stream_chat_completion_sdk`.
Learnt from: CR
Repo: Significant-Gravitas/AutoGPT PR: 0
File: AGENTS.md:0-0
Timestamp: 2026-04-08T17:27:45.740Z
Learning: Use the template in `.github/PULL_REQUEST_TEMPLATE.md` for pull requests, rely on pre-commit checks for linting and formatting, fill out the Changes section and checklist, use conventional commit titles with scope, keep out-of-scope changes under 20% of the PR, ensure PR descriptions are complete, and use linear ticket branch structure
📚 Learning: 2026-04-13T13:11:00.401Z
Learnt from: 0ubbe
Repo: Significant-Gravitas/AutoGPT PR: 12764
File: autogpt_platform/frontend/src/app/(platform)/copilot/components/EmptySession/EmptySession.tsx:41-42
Timestamp: 2026-04-13T13:11:00.401Z
Learning: In Significant-Gravitas/AutoGPT `autogpt_platform/frontend`, unconditional React Query hook calls (e.g. `usePulseChips()` in `EmptySession.tsx`) are intentional when the underlying data is expected to be cached from prior page visits. The team considers the fetch cost acceptable in these cases and does not require `enabled` gating purely for feature-flag-disabled paths. Do not flag unconditional query hooks as wasteful when caching makes the cost negligible.
Applied to files:
.github/workflows/scripts/wait_for_upstream.py
📚 Learning: 2026-03-24T02:05:08.144Z
Learnt from: majdyz
Repo: Significant-Gravitas/AutoGPT PR: 12526
File: autogpt_platform/frontend/src/app/(platform)/copilot/CopilotPage.tsx:0-0
Timestamp: 2026-03-24T02:05:08.144Z
Learning: In `Significant-Gravitas/AutoGPT` (autogpt_platform frontend), when gating logic on a React Query result being available (e.g., `useGetV2GetCopilotUsage`), prefer destructuring `isSuccess` (e.g., `const { data, isSuccess: hasUsage } = useQuery(...)`) over checking `!isLoading`. `isLoading` can be `false` in error/idle states where `data` is still `undefined`, while `isSuccess` guarantees the query completed successfully and `data` is populated. This pattern was established in `CopilotPage.tsx` (PR `#12526`, commit e9dfd1f76).
Applied to files:
.github/workflows/scripts/wait_for_upstream.py
📚 Learning: 2026-04-22T05:57:38.198Z
Learnt from: majdyz
Repo: Significant-Gravitas/AutoGPT PR: 12879
File: autogpt_platform/backend/backend/copilot/baseline/service.py:0-0
Timestamp: 2026-04-22T05:57:38.198Z
Learning: In `autogpt_platform/backend/backend/copilot/baseline/service.py`, the approved pattern for `_run_task_subagent` (PR `#12879`, commit 187f0a5) uses a nested `try/except Exception` inside an outer `try/finally`. The outer `finally` block resets `_TASK_DEPTH_VAR` (via `_TASK_DEPTH_VAR.reset(token)`) AND calls `_absorb_inner_usage(parent_state, inner_state)` unconditionally, so both the depth ContextVar and usage roll-up are guaranteed on all exit paths including `CancelledError`/`KeyboardInterrupt`/`SystemExit`. The inner `except Exception` catches and converts failures into a `TaskResponse` error payload that is returned as `StreamToolOutputAvailable`. Do NOT flag missing ContextVar reset or usage roll-up on BaseException paths in this function.
Applied to files:
.github/workflows/scripts/wait_for_upstream.py
📚 Learning: 2026-04-14T06:34:02.835Z
Learnt from: majdyz
Repo: Significant-Gravitas/AutoGPT PR: 12774
File: autogpt_platform/backend/backend/copilot/tools/e2b_sandbox.py:0-0
Timestamp: 2026-04-14T06:34:02.835Z
Learning: In `autogpt_platform/backend/backend/copilot/tools/e2b_sandbox.py`, the `asyncio.wait_for()` retry loop around `AsyncSandbox.create()` (introduced in PR `#12774`) can leak up to `_SANDBOX_CREATE_MAX_RETRIES - 1` (≤2) orphaned E2B sandboxes per hang incident because `wait_for` cancels only the client-side wait while E2B may complete server-side provisioning. With the default `on_timeout="pause"` lifecycle, leaked orphaned sandboxes are **paused** (not killed) when their original `end_at` is reached and persist indefinitely until explicitly killed — there is NO automatic E2B project-level cleanup. Operators must manage these manually or via their own cleanup jobs. The sandbox_id is not accessible from the timed-out coroutine, so recovery via `AsyncSandbox.connect(sandbox_id)` is not possible at timeout. This is an intentionally accepted trade-off; a proper fix is deferred to a follow-up PR. Do NOT flag the retry loop as a blocking issue.
Applied to files:
.github/workflows/scripts/wait_for_upstream.py
📚 Learning: 2026-03-16T16:30:20.657Z
Learnt from: Abhi1992002
Repo: Significant-Gravitas/AutoGPT PR: 12417
File: autogpt_platform/backend/backend/blocks/agent_mail/threads.py:80-102
Timestamp: 2026-03-16T16:30:20.657Z
Learning: In autogpt_platform/backend/backend/blocks/agent_mail/ (and other blocks under autogpt_platform/backend/backend/blocks/), the block executor framework (backend/executor/manager.py lines ~708-733) automatically catches all uncaught exceptions from a block's `run()` method and emits them on the `"error"` output. Explicit try/except blocks within `run()` are therefore not required for standard error propagation — they are only needed when partial output behaviour must be controlled (e.g., preventing some outputs from being yielded on failure, as in attachment blocks). This is the standard pattern across the codebase.
Applied to files:
.github/workflows/scripts/wait_for_upstream.py
📚 Learning: 2026-04-23T00:07:27.130Z
Learnt from: majdyz
Repo: Significant-Gravitas/AutoGPT PR: 0
File: :0-0
Timestamp: 2026-04-23T00:07:27.130Z
Learning: In `autogpt_platform/backend/backend/copilot/sdk/service.py`, background tasks that persist cost or emit Langfuse backfill (e.g. the cost-reconcile task) must be anchored to `_background_tasks` using `_background_tasks.add(task)` and `task.add_done_callback(_background_tasks.discard)`, mirroring the existing pattern at lines 3063 / 4232 / 4256. This prevents the asyncio task from being garbage-collected before persistence or Langfuse emission completes. Do NOT flag the absence of this anchoring as acceptable in this file. Established in PR `#12889` commit 5ce3d0388.
Applied to files:
.github/workflows/scripts/wait_for_upstream.py
📚 Learning: 2026-04-07T18:08:03.548Z
Learnt from: majdyz
Repo: Significant-Gravitas/AutoGPT PR: 12701
File: .claude/skills/orchestrate/scripts/verify-complete.sh:120-121
Timestamp: 2026-04-07T18:08:03.548Z
Learning: In Significant-Gravitas/AutoGPT, verify-complete.sh (`.claude/skills/orchestrate/scripts/verify-complete.sh`) uses `commits[-1].committedDate` (not `updatedAt`) to identify stale CHANGES_REQUESTED reviews. This is intentional: `updatedAt` changes on any PR activity (bot comments, label changes, description edits), which would falsely classify a reviewer's CHANGES_REQUESTED as stale — a silent false negative. The `committedDate` edge case (commit created locally before a review but pushed after) only causes a false positive (unnecessary re-brief), which is the safer failure mode. Do not suggest switching to `updatedAt` for this comparison.
Applied to files:
.github/workflows/scripts/wait_for_upstream.py
📚 Learning: 2026-03-16T16:30:30.764Z
Learnt from: Abhi1992002
Repo: Significant-Gravitas/AutoGPT PR: 12417
File: autogpt_platform/backend/backend/blocks/agent_mail/pods.py:62-74
Timestamp: 2026-03-16T16:30:30.764Z
Learning: In autogpt_platform/backend/backend/blocks/**/*.py, explicit try/except in the `run()` method is NOT required for standard error handling. The block framework's `_execute()` method in `_base.py` catches unhandled exceptions and re-raises them as `BlockExecutionError` or `BlockUnknownError`. Additionally, when a block yields `("error", message)`, `_execute()` immediately raises `BlockExecutionError` — so the `error` output port never propagates downstream. Explicit try/except is only needed when partial output must be controlled (e.g., attachment blocks that must skip yielding `content_base64` on failure).
Applied to files:
.github/workflows/scripts/wait_for_upstream.py
📚 Learning: 2026-03-16T16:32:29.430Z
Learnt from: Abhi1992002
Repo: Significant-Gravitas/AutoGPT PR: 12417
File: autogpt_platform/backend/backend/blocks/agent_mail/pods.py:62-74
Timestamp: 2026-03-16T16:32:29.430Z
Learning: In autogpt_platform/backend/backend/blocks/**/*.py, the Block base class `execute()` method in `backend/blocks/_base.py` already wraps `run()` in a try/except that converts uncaught exceptions into `BlockExecutionError`/`BlockUnknownError`. Therefore, explicit try/except in individual block `run()` methods is redundant and not the established pattern (e.g., Gmail, Slack, Todoist blocks omit it). Exception: blocks like attachment blocks that need to distinguish between success and error yield paths within the generator use explicit try/except for branching control, not for the framework's error routing.
Applied to files:
.github/workflows/scripts/wait_for_upstream.py
📚 Learning: 2026-04-25T02:53:53.964Z
Learnt from: majdyz
Repo: Significant-Gravitas/AutoGPT PR: 0
File: :0-0
Timestamp: 2026-04-25T02:53:53.964Z
Learning: In `autogpt_platform/backend/backend/copilot/sdk/service.py` (PR `#12918`, commit 6576bf561):
- `_flush_unresolved_tool_calls` was renamed to `flush_unresolved_tool_calls` (public); all call sites updated, `# noqa: SLF001` suppressor removed.
- `_flush_orphan_tool_uses_to_session` and `_InterruptedAttempt.finalize` both return `list[StreamBaseResponse]`; the post-loop caller yields those events directly to avoid double-flush and skipped UI cleanup events.
- The three former post-loop blocks (partial restore + redundant re-flush + two separate `yield StreamError` sites) are collapsed into a single block driven by `_classify_final_failure` returning a `_FinalFailure(display_msg, code, retryable)` dataclass, so history marker and SSE yield share one source of truth.
Do NOT flag double-flush risk or mismatched history/SSE marker as issues in the post-loop section of `stream_chat_completion_sdk`.
Applied to files:
.github/workflows/scripts/wait_for_upstream.py
📚 Learning: 2026-04-15T02:06:40.213Z
Learnt from: ntindle
Repo: Significant-Gravitas/AutoGPT PR: 12780
File: autogpt_platform/backend/backend/util/workspace.py:198-221
Timestamp: 2026-04-15T02:06:40.213Z
Learning: In `autogpt_platform/backend/backend/util/workspace.py`, the TOCTOU gap between the `get_workspace_total_size()` pre-check and the subsequent storage write + DB insert in `WorkspaceManager.write_file()` is an accepted trade-off. Reasons: (1) the workspace is single-user-scoped, so a true race requires precise concurrent timing from the same user; (2) the REST upload route (`autogpt_platform/backend/backend/api/features/workspace/routes.py`) already has a post-write quota check with soft-delete rollback as a safety net for that path; (3) adding the same rollback inside `write_file()` would couple the manager to HTTP semantics. The pre-write check catches the overwhelming majority of cases. Do NOT flag this as a blocking TOCTOU issue.
Applied to files:
.github/workflows/scripts/wait_for_upstream.py
📚 Learning: 2026-03-16T17:00:02.827Z
Learnt from: majdyz
Repo: Significant-Gravitas/AutoGPT PR: 12439
File: autogpt_platform/backend/backend/blocks/autogpt_copilot.py:0-0
Timestamp: 2026-03-16T17:00:02.827Z
Learning: In autogpt_platform/backend/backend/blocks/autogpt_copilot.py, the recursion guard uses two module-level ContextVars: `_copilot_recursion_depth` (tracks current nesting depth) and `_copilot_recursion_limit` (stores the chain-wide ceiling). On the first invocation, `_copilot_recursion_limit` is set to `max_recursion_depth`; nested calls use `min(inherited_limit, max_recursion_depth)`, so they can only lower the cap, never raise it. The entry/exit logic is extracted into module-level helper functions. This is the approved pattern for preventing runaway sub-agent recursion in AutogptCopilotBlock (PR `#12439`, commits 348e9f8e2 and 3b70f61b1).
Applied to files:
.github/workflows/scripts/wait_for_upstream.py
Treat workflows still missing after the grace period as not-triggered (proceed=false) so slow webhooks or path-filtered upstreams cannot let the expensive E2E job through. Tie-break latest_per_workflow on (run_number, run_attempt) so the most recent attempt wins. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
ntindle
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discard everything not e2e full stack related
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| - 'classic/original_autogpt/**' | ||
| - 'classic/forge/**' | ||
| - 'classic/direct_benchmark/**' |
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let's keep these rather than classic/**.py;
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| strategy: | ||
| fail-fast: false | ||
| matrix: | ||
| python-version: ["3.11", "3.12", "3.13"] |
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please put this back, it doesn't save us anything and costs cross-version coverage
Pwuts
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This pull request has conflicts with the base branch, please resolve those so we can evaluate the pull request. |
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seems we don't really need this anymore, CI spend has been within bounds the past period |
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Summary
classic/**.py(was repo-wide**.py) so unrelated changes don't trigger the workflow.3.11 / 3.12 / 3.13pyright + pytest matrix down to3.13(the prod runtime), removing 2/3 of the per-PR runs.preflight-e2egate that waits for backend + frontend CI on the same SHA and skips thebig-boiE2E job if upstream failed or didn't run for that SHA.masternow (wasmaster / dev / release-*) sincemasterholds the bulk of open PRs.pull_requestpolling toworkflow_run, evaluates once per upstream completion, and posts a singleCheck PR Statuscheck-run for branch protection.workflow_runmodel (paginated check-runs, brief settle retry, no 30s polling loop).Test plan
Check PR Statusposts on this PR's head SHA after the upstream workflows complete and is required by branch protection.preflight-e2eresolves toproceed=trueonce backend + frontend CI succeed, and that thebig-boie2e_testjob runs.e2e_testis skipped.Classic - Python checksdoes not trigger.dev/ arelease-*branch and confirmrepo-pr-labelno longer fan-outs (onlymastershould trigger it).3.13only.🤖 Generated with Claude Code