* feat: server-side Datadog/LangSmith observability tools + team creds
Add team-wide observability credential settings (Datadog DD_SITE/API/APP
keys, LangSmith API key) stored encrypted server-side, with an admin
dashboard section to connect/disconnect each provider. When connected,
get_agent loads read-only observability tools server-side: Datadog via its
hosted MCP server (langchain-mcp-adapters, toolsets=core) and LangSmith
read tools (langsmith_get_trace, langsmith_list_runs). Credentials live in
the LangGraph server process and are never exposed to the sandbox.
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* fix: address review on observability tools
Address PR review feedback:
- Authorize observability tools per triggering user (admins + the
OBSERVABILITY_AUTHORIZED_EMAILS allowlist) so prompt-injected runs from
untrusted contributors can't reach team Datadog/LangSmith data.
- Use the documented Datadog MCP auth headers DD_API_KEY / DD_APPLICATION_KEY.
- Store each provider's credentials under its own store key to avoid a
read-modify-write race dropping the other provider on concurrent saves.
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* fix: async email resolution in observability authorization gate
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* feat: per-repo custom instructions for the coding agent
Adds per-repository custom instructions for the main coding agent,
mirroring the reviewer's per-repo style prompts. Instructions are stored
in the LangGraph Store, managed via dashboard API + UI (Monaco editor),
and appended to the agent's system prompt for runs targeting that repo.
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* chore: wire agent instructions route into generated route tree
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* fix: enforce repo access on instruction routes
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
The Co-authored-by trailer and bot git identity used
open-swe@users.noreply.github.com, which resolves to the separate
open-swe *user* account rather than the open-swe[bot] GitHub App.
Switch OPEN_SWE_BOT_EMAIL to the bot's noreply address
(215916821+open-swe[bot]@users.noreply.github.com) so co-author credit
and the fallback author identity point at the bot.
Drive the prompt trailer and sandbox git config from the constant
instead of hardcoding the address.
* fix: scope public reviewer tokens
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* refactor: simplify reviewer token wiring; fix push re-scope + red test
- Remove the redundant _check_or_recreate_sandbox_for_proxy /
_refresh_github_proxy_or_recreate_for_proxy wrappers and call the
underlying functions directly (they already default the token to None).
- process_github_push_event: re-scope the GitHub App token when the push
payload lacked repo privacy/id but PR metadata reveals a public repo, so
reviewer.py never proxies a full-installation token for a public PR.
- Clarify the two-token sequence in trigger_pr_review_from_ref.
- Fix pre-existing failing test test_proxy_refresh_failure_recreates_sandbox
and add coverage for _reviewer_token_for_repo + push-event scoping.
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
Add an open_pull_request tool that creates a new PR via the GitHub REST
API using the triggering user's OAuth token (resolved by login from the
dashboard store), so the PR creator is the user rather than open-swe[bot].
Falls back to the GitHub App installation token for GitHub-triggered runs,
unmapped users, and bot-token-only deployments.
The user token never enters the sandbox: clone/push/comments still go
through the bot proxy via gh. The agent is steered to use the tool only
for OPENING a new PR; updates (body edits, mark ready) and pasted/existing
PRs continue to use gh pr edit. Existing-PR (422) returns the open PR's
URL so re-runs don't create duplicates.
* fix: reset stale sandbox creation sentinel
Co-authored-by: Johannes du Plessis <51395795+johannes117@users.noreply.github.com>
* fix: treat SANDBOX_CREATING as a timestamped cross-process lock
Only reset the sentinel when proven stale (older than the creation
timeout); otherwise wait for the worker that holds the lock so a
concurrent run does not create a duplicate sandbox.
* feat(analyzer): outcomes dataset + bootstrap/continual split via skills
Rename the review_style_analyzer graph to `analyzer` and split it into two
modes, plus capture reviewer finding outcomes for continual learning.
- Outcomes dataset: upsert resolved-by-commit (positive), dismissed (false
positive), and GitHub/Slack thumbs findings into a single LangSmith dataset
(openswe-reviewer-outcomes), keyed deterministically per finding+source.
Emit points wired into update_finding, resolve_finding_thread, and the
GitHub/Slack reaction handlers.
- Two playbooks delivered as deepagents skills (bootstrap-repo-analysis,
continual-learning), served as virtual files via a CompositeBackend /skills/
route + StateBackend (seeded into the run files channel at invoke time, never
written to the sandbox). Mode is set by the launcher; continual runs fall
back to the GitHub App installation token.
- Split launcher into start_bootstrap_analysis + start_continual_run; register
a per-repo nightly continual-learning cron when bootstrap completes.
- New read_finding_outcomes tool feeds confirmed/dismissed findings back to the
continual playbook.
Tests for outcome label mapping, skills helper, and cron idempotency.
* fix(analyzer): anchor continual cron runs to a real thread_id
The nightly continual-learning cron is threadless, and get_analyzer
early-returns an empty agent when configurable.thread_id is missing — so
every cron-launched run no-op'd before reading outcomes or saving a refined
prompt. Include the repo's deterministic analyzer thread_id in the continual
run configurable so the run executes; the threadless run carries no message
history, so nightly runs don't accumulate context.
* refactor(analyzer): move cron lifecycle calls out of the review-styles store
Drop the inline `analyzer_cron` imports from review_styles.py (added only to
dodge a circular import) by relocating the cron-trigger calls to the layer
above the store: registration to the save_review_style tool (after a prompt is
saved) and removal to the dashboard delete route. review_styles.py is now a
pure store again with top-level imports only.
* refactor: hoist reviewer_outcomes imports to module level
Move the two inline emit_finding_status_outcome imports introduced in this PR
(update_finding, resolve_finding_thread) to top-level imports. reviewer_outcomes
only depends on langsmith, so there is no circular import to avoid.
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* feat(ui): add Agents chat UI ported from open-swe-app
Introduce a Cursor-style Agents surface separate from the dashboard, with ported chat/diff components and mock thread data until LangGraph APIs land.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(dashboard): wire Agents UI to LangGraph thread APIs
Add dashboard thread list/detail/run/message/stream endpoints with a LangGraph message adapter, dashboard OAuth auth for runs, and TanStack Query hooks replacing mock data.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(dashboard): single agent reply per turn in Agents UI
Use UUID thread IDs LangGraph accepts, skip confirming_completion for
dashboard threads, and merge adapter agent messages so duplicate bubbles
do not render.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(ui): polish Agents UI with floating prompt and layout cleanup
Remove no-op chrome (git panel, headers, sidebar search), port CloudPromptBar
from open-swe-app, and refine chat layout so messages scroll behind the input.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(agent): patch deepagents reducer for None messages on checkpoint replay
LangGraph thread state could 500 when cancelled runs left messages as None.
Apply the reducer guard before graph import, fall back to metadata in the
dashboard API, and adjust Agents prompt bar layout.
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(ui): unify sidebar user menu and clean up Agents UI navigation
Extract SidebarUserMenu so the dashboard and Agents sidebars render the
same profile button, drop the redundant Agents nav row in favor of the
existing Back to Agents link, add the open-swe logo header to the Agents
sidebar, flatten the New Agent button, and cap the home screen run list
to keep the prompt input in view.
* feat(ui): resizable/collapsible sidebar shared across dashboard and Agents
Add a useSidebarLayout hook + SidebarFrame wrapper so both sidebars
share a persisted width (default 260px, drag to resize, 200-420 range)
and a collapse toggle that hides the panel and surfaces a floating
reopen button. Also adds a DELETE /threads/{id} endpoint and an X-on-
hover thread delete control in the Agents sidebar.
* feat(ui): instant user message and busy indicator on Agents transition
Stash submitted prompts in sessionStorage, pre-populate the new thread
detail cache, and merge pending prompts into the rendered message list
so the Agents page renders the user bubble plus the existing thinking
spinner immediately instead of flashing a skeleton and "Agent is
starting" while the run boots.
* feat(ui): token-stream agent replies in the Agents thread view
Opt the LangGraph runs into messages-tuple streaming and forward those
events through the existing SSE channel. The frontend now applies
AIMessageChunk deltas directly to the cached thread (cancelling any
in-flight refetch first so optimistic tokens are not clobbered) and
keeps positional pending prompts so the user bubble stays in the right
place while the agent streams its reply.
* fix(dashboard): await threads.join_stream before iterating
threads.join_stream is async def returning an AsyncIterator, so it must
be awaited before async for. The SSE endpoint was raising
TypeError: 'async for' requires an object with __aiter__ method, got
coroutine on every connection.
* fix(dashboard): drop messages-tuple stream_mode that broke thinking-mode tool turns
Setting stream_mode=["values","messages-tuple","updates"] on
runs.create forces langchain_anthropic into streaming, and on the
second model call (after tool execution) its serialized thinking
blocks come back malformed, so Anthropic rejects the request with
'messages.1.content.0.thinking.thinking: Field required'. Revert to
the default stream_mode so claude-opus thinking + tool use runs to
completion. The frontend keeps the messages-event handler in place
as a no-op fallback for when streaming is re-enabled.
* feat(agents): per-thread model picker wired through to the run
Add optional model_id/effort to the create-thread and send-message
request bodies, forward them as agent_model_id/agent_effort in the
LangGraph run configurable, and record the resolved choice in thread
metadata so the UI can show the model the run is actually using.
get_agent now picks the per-thread override last (highest priority over
team default + profile override) and falls back gracefully when it is
absent or unsupported.
The frontend prompt bar becomes a controlled component fed by a
shared useModelOptions hook (options + profile -> defaultSelection).
AgentsHome seeds the picker from the user's profile default; the
thread view seeds from the thread's recorded model/effort and lets
each follow-up retarget the run.
* refactor(ui): align Agents prompt bar layout with open-swe-app PromptBar
Drop the absolute-positioned send button, restore the original
px-4 py-3.5 min-h-[106px] flex-col container, and move the model
picker into a mt-auto pt-2 footer row so the placeholder text and
the model selector share the same horizontal padding.
* chore: fix lint/format CI failures
Remove unused imports and reformat two files flagged by ruff.
* fix(tests): stop messages-reducer patch tests from polluting the suite
Restore agent modules after reducer patch tests and import LangSmithSandbox
from agent.server in proxy refresh tests so isinstance checks stay valid.
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(dashboard): restructure Open SWE Review tab + wire create_prs
Restructures the dashboard around two related changes the reviewer settings
have been asking for:
- Wire profile.create_prs. Defaults to true (opt-out); when off the system
prompt gets a `Pull Request Policy Override` section telling the agent
to push the branch and notify with the branch URL instead of opening a
PR. Removes the noop Slack Notifications / Allow Artifacts / First Name
/ Last Name controls and their schema fields.
- Repositories opt-in for Open SWE Review. New per-team enabled list
stored in the LangGraph Store (`["enabled_review_repos"]`). Every
reviewer webhook chokepoint now goes through `_is_repo_enabled_for_review`
which AND-combines the existing env allowlist with the dashboard list.
Default is empty (opt-in) — admins enable repos per-installation from
the new Repositories page nested under Open SWE Review.
- Open SWE Review tab now mirrors the Cursor "rules" pattern: main page
shows installation rows + a Rules entry; both drill into nested pages
(/review/repositories/$owner and /review/styles) with a back link.
- Adds the new logo/favicon assets shipped from sidebar + html head.
Tests pass with a new autouse fixture (`tests/conftest.py`) that defaults
`is_review_repo_enabled` to True for existing allowlist tests.
* fix(dashboard): make main content scroll independently of the sidebar
Outer flex container was min-h-svh, so it grew with main's content and the
whole page scrolled — sidebar moved with it. Pin to h-svh + overflow-hidden
so the sidebar stays put and only <main> scrolls.
* fix(dashboard): make disabled repo toggles obviously disabled
Switch's disabled state used opacity-50 against a muted background, so
the not-admin state looked nearly identical to the off state. Bump to
opacity-40 + grayscale, and wrap each repo toggle in a span carrying a
native hover tooltip explaining why it's disabled.
* fix(switch): handle base-ui's data-disabled state
base-ui's Switch.Root sets data-disabled (not the HTML disabled attribute)
when disabled, so Tailwind's disabled: variant never matches and the
button keeps its cursor-pointer + clickable look. Mirror the styling
under the data-[disabled] variant and add pointer-events-none so the
disabled state is both visible and actually unclickable.
* feat(dashboard): paginate per-installation repository list
20 repos per page with Prev / page X of Y / Next controls at the bottom.
Pager only renders when there are more than 20 repos. Page resets to 0
when navigating between installations.
* feat(dashboard): global default model selectors for Agent + Reviewer
Adds team-wide default model + reasoning effort for both agents in the
Admin tab so operators can switch models without redeploying.
Resolution chain:
Agent: hardcoded -> LLM_MODEL_ID env -> team default -> user profile
Reviewer: hardcoded -> LLM_MODEL_ID env -> team default -> per-call configurable
Team defaults live in team_settings and are validated against the
SUPPORTED_MODELS allowlist + the model's supported reasoning efforts.
'Inherit from env' clears the override and falls back to LLM_MODEL_ID.
* refactor(models): drop LLM_MODEL_ID env in favour of the team default
The team default is now the single source of truth for the runtime model
choice; per-user (agent) and per-call configurable (reviewer) selections
still win on top. When no admin has touched the team default, it surfaces
the hardcoded fallback (DEFAULT_MODEL_ID + its default effort), so the
admin UI's dropdown is always pre-populated with a sensible value.
The Admin UI loses the 'Inherit from env' option since there is no longer
an env layer to inherit from.
* chore(models): set hardcoded fallback to gpt-5.5 medium
Decouple the team-default boot value (gpt-5.5 / medium) from each model's
ProfileForm-suggested default_effort so we can change one without nudging
the other. The Opus xhigh default for new user profiles is unchanged.
* feat(dashboard): trigger-mode copy, Coming Soon badges, logout in My Settings
- Rename trigger mode 'ready_for_review' -> 'once_per_pr' with new
description copy that matches the screenshot. Legacy stored values
fall back to 'every_push' on read so the UI never shows an unknown
selection.
- Add a 'Coming soon' badge + greyed-out + disabled state on the
controls that don't have runtime consumers yet: Trigger Mode,
Autofix Mode, Autofix Severity Threshold, and Automatically fix CI
failures. SettingsRow grew a comingSoon prop to keep this consistent.
- My Settings drops the noop PR Preferences section and adds a Sign
Out button. preferred_pr_destination is removed from the profile
schema; old records get the field popped on next write.
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* feat: tune reviewer for precision — web/wiki tools + recalibrated prompt
Reviewer agent now has web_search, fetch_url, and http_request alongside the
finding tools, so it can verify library semantics and consult the DeepWiki
auto-generated wiki for public repos (https://deepwiki.com/<owner>/<repo>)
before flagging cross-file or architectural concerns.
Prompt rewritten to push precision over recall:
- explicit severity ladder pushing reviews toward bimodal high/low instead of
defaulting to medium
- ≤200-char description target (gold set averages ~186 chars; we were at ~436)
- mandatory docs / wiki / code lookup before flagging concurrency, security,
or perf — the three categories that dominated false positives
- "do not flag" list covering compiler/linter-catchable nits, speculative
claims without a concrete attacker/interleaving/scale, style preferences
the codebase doesn't share, and test-quality nits on non-test diffs
- smart file-selection guidance for large PRs (deprioritize generated /
vendored / pure-rename hunks)
Eval config switched to openai:gpt-5.5 + high reasoning effort for the next
benchmark run.
* trim prompt
* subagent prompting
* confidence ratings
* added medium
* enforce confidence threshold
* .
* reviewer: precision-tuned prompt + drop confidence gate
Rewrites the reviewer system prompt around a defensibility bar (anchor +
failure mode + maintainer wouldn't say "not a bug"), an explicit do-not-file
list (style nits, speculation, scope-policing, same-bug fan-out), and a
checklist of 10 bug archetypes drawn from a per-PR audit of the eval golden
set. The audit showed 145 FPs in the last eval split ~28% speculative, ~26%
style-nit, ~31% real-but-unscored (mostly same-archetype fan-out); the new
prompt targets each class directly.
Confidence is still recorded on every finding for post-hoc calibration but
no longer gates publication — the audit showed the gate was a no-op (agent
self-rated 65% of findings "high" regardless), and the prompt's defensibility
bar is the actual discipline. Drops CONFIDENCE_ORDER, CONFIDENCE_THRESHOLD,
the confidence_threshold kwarg on filter_findings_for_publish, the
confidence_filtered score_mode, and the min_confidence kwarg on the eval
target's _extract_comments — all dead once the gate is gone.
Also removes the "informational" severity tier from the Severity enum,
SEVERITY_ORDER, and all validators / tests / docstrings. It was reserved for
FYI observations the dataset never rewards.
* benchmax
* adding google provider
* slight steering
* tuning
* more tuning
* fix
* cleanup
* reducing overfitting
* Add per-repo review style profiles and inject them into the reviewer.
Dashboard users can analyze historical PR review feedback per repository,
edit the resulting style guide, and have it loaded from LangGraph Store at
reviewer runtime (including Martian eval runs) keyed by owner/name.
Co-authored-by: Cursor <cursoragent@cursor.com>
* Fix review style job errors leaking exception details to clients.
Return generic dashboard messages while logging full stack traces server-side.
Co-authored-by: Cursor <cursoragent@cursor.com>
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat: tighten reviewer eval workflow
Require the reviewer to verify and dedupe findings before recording them, and make benchmark runs safe to execute against deployed reviewer graphs without posting GitHub reviews.
* chore: move reviewer eval settings to config
Load reviewer benchmark settings from the default eval config file so deployed eval runs do not require a wide CLI surface.
* feat: allow reviewer eval model overrides
Pass reviewer model and reasoning effort from the eval config into reviewer runs so isolated benchmark deployments can test Opus 4.7 high thinking.
* fix: use adaptive thinking for Opus 4.7
Switch Opus 4.7 model overrides to Anthropic adaptive thinking with effort instead of the deprecated budgeted thinking payload rejected by the API.
* refactor: use latest Anthropic effort API
Remove legacy Anthropic budget-token thinking support and route Anthropic efforts through adaptive thinking plus effort.
* revert prompting
* feat: dashboard backend — GitHub OAuth, profile CRUD, admin endpoints
Adds agent/dashboard/ FastAPI router mounted at /dashboard/api covering:
- GitHub App OAuth login → JWT cookie session (cross-domain ready)
- profile CRUD against LangGraph Store with model+effort validation
- admin gate via CONFIGURED_ADMINS
- /repos via /user/installations using the user's encrypted OAuth token
CORS allowlist on webapp.py is opt-in via DASHBOARD_ALLOWED_ORIGINS so the
Vercel-hosted frontend can call the LangSmith deployment with credentials.
* feat: apply dashboard profile model/effort overrides in get_agent
Look up the triggering user's GitHub login from config (direct field or
GITHUB_USER_EMAIL_MAP reverse lookup), read their profile from the Store,
and apply default_model + reasoning_effort to make_model when both are
valid. Effort 'max' is captured on the profile but not yet wired through —
the OpenAI Reasoning Literal doesn't accept it.
* feat: ui/ TanStack Start dashboard for profile config
Scaffolded with the shadcn b7CScJIjA preset (TanStack Start template,
base-ui primitives, Tailwind v4). Three routes:
- /login — Sign in with GitHub (links to /dashboard/api/auth/login)
- /profile — Edit default model, reasoning effort, default repo
- /admin — Admin-only: list users and edit other profiles
API client (src/lib/api.ts) uses credentials: include so the osw_session
cookie set by the OAuth callback rides cross-origin. VITE_DASHBOARD_API_BASE_URL
points at the LangSmith deployment.
Effort options re-render when the model changes; 'max' on Opus 4.7 is
captured on the profile but ignored downstream until anthropic reasoning
is wired through make_model.
* feat: searchable Combobox for default repo picker
Replaces the Select with a base-ui Combobox so users can filter by typing,
the popup is wider than the trigger so full owner/repo names are readable,
and the list caps at max-h-80 to stay on screen.
* fix: address review comments + wire default_repo and Anthropic thinking
Security/correctness fixes from PR review:
* Open redirect: validate `redirect_to` in `/auth/login` against
`DASHBOARD_BASE_URL` + `DASHBOARD_ALLOWED_ORIGINS` before signing it
into the state JWT. Anything off-allowlist falls back to the dashboard
base URL. (PR #1302 r3250054386)
* Login CSRF: bind the OAuth `state` to the requesting browser. At
`/auth/login` we generate a fresh nonce, set it as a short-lived
HttpOnly SameSite=Lax cookie scoped to `/dashboard/api/auth`, and
embed `hash_state_nonce(nonce)` in the state JWT. At `/auth/callback`
we require the cookie nonce to hash-match the state JWT's nonce_hash
(constant-time compare). (PR #1302 r3250054395)
* RMW race in profile vs token writes: split storage into two
namespaces — `["profiles"]` for user-editable settings and
`["oauth_tokens"]` for the encrypted GitHub token. Each upsert now
only writes its own namespace so an in-flight profile save can no
longer clobber a fresh token from a concurrent re-login (and vice
versa). (PR #1302 r3250054393)
* /repos pagination: follow `Link: rel="next"` for both
`/user/installations` and per-installation `/repositories` with
per_page=100, capped at 1000 items. (PR #1302 r3250054401)
Feature wires:
* default_repo: applied as a fallback in `get_slack_repo_config` (after
explicit-repo / thread metadata, before the env defaults) and in the
Linear webhook (after comment-body extraction, before team mapping).
Both paths resolve the triggering user's GitHub login via
GITHUB_USER_EMAIL_MAP and read the profile's default_repo.
* Anthropic "thinking" effort: `make_model` now accepts a `thinking`
kwarg; `get_agent` maps profile effort {low,medium,high,xhigh,max}
to budget_tokens {1k,4k,12k,32k,60k} when the chosen model is
anthropic. OpenAI path still ignores "max" since the Literal doesn't
accept it.
* feat: TTL and revocation handling for cached GitHub OAuth tokens [closes AB-2322]
Persist github_token_expires_at alongside github_token_encrypted, treat
expired cache entries as missing so we re-resolve before kicking off
runs, and invalidate the cached ciphertext on a downstream 401 so the
next invocation gets a fresh token instead of replaying a revoked one.
Co-authored-by: Johannes du Plessis <51395795+johannes117@users.noreply.github.com>
* webapp: forward installation-token expiry to reviewer cache writes
The three reviewer-thread persist sites in webapp.py were calling
get_github_app_installation_token() (no expiry) and persist_encrypted_github_token
without expires_at, so cached App tokens were treated as never-expiring even
though they actually expire in ~1 hour.
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
Co-authored-by: Johannes du Plessis <51395795+johannes117@users.noreply.github.com>
Co-authored-by: Johannes du Plessis <johannes@langchain.dev>
When the primary model raises a transient provider error (5xx, 429,
connection/timeout) the request is retried once against a fallback
model from the other provider. Anthropic primaries fall back to
OpenAI and vice versa. Also bumps the SDK max_retries from the
default 2 to 6 so quick blips stay on the primary and keep prompt
caching warm.
Triggered by 529 OverloadedError traces that ended runs silently
with no Slack/Linear/PR reply.
* fix: recover from mid-run sandbox death
Recreate dead sandboxes during tool execution and stop repeated unrecoverable timeout loops with a user-facing notification.
* fix: count repeated sandbox recreations
Treat consecutive sandbox recreations as an unrecovered failure streak so outages cannot loop until the model-call limit.
The gh-cli migration removed agent/middleware/open_pr.py and
agent/tools/commit_and_open_pr.py — the only callers of
add_user_coauthor_trailer / add_pr_collaboration_note. Since then the
agent has been driving commits and PRs entirely via gh, with no
attribution back to the Slack/Linear/GitHub user who triggered the run.
Resolve the triggering user's identity in get_agent (reusing the
existing authorship helpers) and inject a Collaborative Attribution
section into the system prompt with the exact trailer and PR-body note
to use. The section is only rendered when an identity is resolvable, so
runs without a known triggering user are unchanged.
* feat: add optional Slack Assistants API typing status indicator
Mirrors OpenClaw's pragmatic approach: instead of rebuilding around
assistant_thread_started events, just opt into assistants.threads.setStatus
to show 'is thinking…' while the agent is working, and clear it when
post_slack_thread_reply lands. Gated behind SLACK_ASSISTANTS_API_ENABLED so
it can be toggled without touching code.
* fix(slack): drop redundant clear, add status heartbeat across model calls
- Slack auto-clears the typing indicator on bot post; remove the explicit
assistants.threads.setStatus("") call from post_slack_thread_reply.
- The indicator expires after ~2 minutes; add a before_model middleware
that refreshes it on every model tick so it stays visible across long
agent runs. Reuses the existing slack_thread.{channel_id,thread_ts}
configurable already plumbed for notify_step_limit.
- chat:write is sufficient on the bot token (assistant:write is on the
way out per Slack docs); no scope or app-config change required.
* feat(slack): contextual status text + rotating loading_messages
- set_slack_assistant_status now accepts an optional loading_messages list
(capped at 10 per Slack's API), surfaced via the assistants.threads.setStatus
payload so Slack rotates through them client-side.
- The heartbeat middleware derives a contextual status from the last
assistant message's tool calls (e.g. "searching the codebase…" after
grep, "running commands…" after execute), falling back to the default
"is thinking…" when no tool calls or unknown tool name.
- Adds a curated DEFAULT_LOADING_MESSAGES list passed alongside the
contextual status on each refresh.
* fix slack assistant status lifecycle
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
Co-authored-by: Johannes du Plessis <johannes@langchain.dev>
* feat: add reviewer graph + eval target wiring
- New `reviewer` graph (`agent/reviewer.py`) registered in langgraph.json
alongside the main `agent` graph. Reuses the same sandbox lifecycle,
GH proxy auth, and middleware primitives from `agent.server`, but with
a narrower tool set, a reviewer-specific system prompt, no
commit/push, and the `task` (subagent) tool stripped via
`_ToolExclusionMiddleware` so review stays in one context.
- New `github_comment` tool: agents call it once per issue with
`(file, line, body, severity)` and the eval scores those calls
against golden comments.
- `ensure_no_empty_msg` middleware (the no_op nudge) is intentionally
*not* on the reviewer's stack — that middleware exists to enforce the
main agent's "always finalize via Slack/Linear/PR" contract, which
the reviewer doesn't have. The main agent's behavior is unchanged.
- `evals/reviewer/target.py`: send PR info as a user message, extract
every `github_comment` tool call (multiple expected per review) into
the run output.
- `evals/reviewer/judge.py`: per-example evaluator now returns a list
of metrics under `{"results": [...]}` so LangSmith averages each
numeric key (f1/precision/recall/tp/fp/fn) across the experiment in
the UI. Dropped the broken `aggregate_pr` summary evaluator that
reached for an attribute that doesn't exist on `RunTree`.
- `evals/reviewer/run_eval.py`: `--limit` now slices the dataset via
`client.list_examples(limit=N)` since `aevaluate` doesn't accept
`max_examples`.
- Makefile: `dev` and `run` targets now use `uv run` so they work
without an activated venv.
* resolve comments
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* fix: re-apply git identity on every agent invocation, source from env
Cached/reconnected sandboxes weren't getting `git config --global` re-applied
(the call was gated on new-sandbox creation), so commits picked up whatever
identity the sandbox happened to have — sometimes an email not associated
with any GitHub account, which Vercel rejects on preview deploys.
Move the git config call out of the new-sandbox branch so it runs on every
get_agent, and source the values from OPEN_SWE_GIT_AUTHOR_NAME /
OPEN_SWE_GIT_AUTHOR_EMAIL env vars (defaulting to the existing bot identity)
so forks can override without code changes.
* cleanup
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* feat: move github workflows to gh cli
Use LangSmith proxy auth to support gh-driven GitHub workflows while removing custom GitHub wrapper tools.
* docker ignore + snapshot and docker image updates
* updated image and instructions
* removing open_pr if needed after agent call
* feat: add edit_pull_request tool for editing PR titles and descriptions
* fix: patch auth flow in open PR middleware tests
* fix: support app token for editing PRs
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
Co-authored-by: Johannes du Plessis <johannes@langchain.dev>
- Root cause: LLM occasionally generates strings like '1, 80' or '170, "limit": 60'
for integer fields, causing a Pydantic ValidationError and wasting an LLM turn
- Change: add SanitizeToolInputsMiddleware in agent/middleware/sanitize_tool_inputs.py
that extracts the leading integer from any string value in offset/limit before
the call reaches Pydantic validation; registered before ToolErrorMiddleware in server.py
- Verified: 14 unit tests covering all three production trace patterns pass
Co-authored-by: LangSmith Forge <forge-agent@langsmith.ai>
Co-authored-by: Johannes du Plessis <johannes@langchain.dev>
* fix: notify users via Slack when agent hits model call step limit
- Root cause: GraphRecursionError at 1000 steps bypassed all @after_agent
middleware including open_pr_if_needed, leaving users with no notification
- Change: Added ModelCallLimitMiddleware(run_limit=60) to intercept gracefully
before the hard recursion limit, and added notify_step_limit_reached
@after_agent middleware to post a Slack thread reply when the limit fires
- Verified: 107 existing tests pass, no regressions
* fix: harden step-limit Slack notification
Ensure the step-limit notification runs after the PR safety net and cover the new middleware behavior with focused unit tests.
---------
Co-authored-by: LangSmith Forge <forge-agent@langsmith.ai>
Co-authored-by: Johannes du Plessis <johannes@langchain.dev>
* feat: add github CI check run tools for shepherding CI
Add get_pr_check_runs and rerun_failed_check_runs tools that authenticate
using the GitHub App installation token so the agent can query and retry
CI status on private repos without relying on GH_TOKEN or unauthenticated
http_request calls.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix: handle paginated GitHub CI results
* refactor(github_ci): address review feedback
- Rename rerun_failed_check_runs -> rerun_failed_workflow_runs and clarify
in docstrings that the tool only retries GitHub Actions workflow runs
(not third-party CI checks surfaced by get_pr_check_runs).
- Skip action_required workflow runs when rerunning; those need manual
approval, not a rerun.
- Run rerun-failed-jobs requests concurrently via asyncio.gather instead
of sequentially.
- Fix latent pagination bug in _fetch_paginated_items where caller-supplied
params could overwrite per_page/page and break the end-of-pagination
check; reserved keys now always win and the threshold uses a PER_PAGE
constant.
- Set an explicit 30s httpx timeout so a hung GitHub call cannot stall
the agent loop.
- Restore alphabetical ordering of tools in agent/tools/__init__.py.
- Add tests for: a 500 surfaced on a later pagination page, and
action_required runs being filtered out of rerun candidates.
---------
Co-authored-by: Claude Agent <agent@anthropic.com>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: Johannes du Plessis <johannes@langchain.dev>
* feat: add get_pr_review_comments tool for authenticated GitHub API access
The agent was asking users to paste PR review comments because it had no
tool to fetch them with auth. This adds get_pr_review_comments, which uses
the GitHub App installation token to fetch all three comment types (thread
comments, inline review comments, review submissions) from private repos.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* u
* u
---------
Co-authored-by: Forge Agent <agent@forge.ai>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: Palash Shah <palash@langchain.dev>
Co-authored-by: Palash Shah <35114859+Palashio@users.noreply.github.com>
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* feat: default to GPT-5.5 medium reasoning
Use OpenAI GPT-5.5 with medium reasoning as the default model and document the completion-token budget semantics for reasoning models.
* fix: use Responses API reasoning config
Pass GPT-5.5 reasoning settings through LangChain's Responses API parameter instead of the Chat Completions-only reasoning_effort field.
* feat: raise GPT-5.5 output budget
Set the default GPT-5.5 output token budget to the model maximum so long-running coding tasks have more room for reasoning and final responses.
* feat: align recursion limit with Deep Agents
Use Deep Agents' default recursion limit so longer coding runs have room to complete without Open SWE imposing a lower cap.
* chore: remove minimal effort level
* chore: reduce max tokens to 64_000
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* fix: add Exa web search tool
* chore: update uv.lock for exa-py dependency
* linting
* chore: remove web_search from system prompt
* chore: drop search_type and category params from web_search
* Add GitHub PR review tools (list, get, create, update, dismiss, submit, list comments) and bind them to the agent
* format n lint
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
Co-authored-by: Aran Yogesh <yogesh.mahendran@langchain.dev>
Adds 6 new agent tools backed by Linear's GraphQL API, with a shared
_graphql_request helper to reduce boilerplate. Refactors existing
comment_on_linear_issue to use the same helper.
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
