* feat: switch model providers to AWS Bedrock (Claude) and Fireworks (non-Claude)
Migrate off direct provider APIs: AWS Bedrock for Anthropic/Claude via the
cross-region inference profile us.anthropic.claude-opus-4-8, Fireworks AI for
all non-Claude models. Drop OpenAI (gpt-5.5) and Google (gemini-3.5-flash)
entirely. DEFAULT_MODEL_ID is now Bedrock Claude; all Fireworks models stay
freely selectable for the agent and reviewer graphs and via team/profile
defaults.
- pyproject: add langchain-aws (ChatBedrockConverse + boto3)
- options.py: Bedrock Claude entry + default; remove openai/google entries
- model.py: bedrock_converse provider_model_kwargs (effort -> thinking budget),
region pin in make_model, bedrock<->fireworks fallback pairing, AWS_REGION/
FIREWORKS_API_KEY local-dev validation
- server.py: provider-aware fallback kwargs build
- sanitize_thinking_blocks: also sanitize ChatBedrockConverse thinking blocks
- model_fallback: treat transient botocore ClientError codes as fallback-worthy
- eval_jobs: repoint hardcoded eval model id to Bedrock Claude
- tests: repoint dropped model ids; drop obsolete google test module
* fix(bedrock): use adaptive thinking + output_config.effort for Opus 4.8
The handoff spec wired Bedrock Converse thinking as
{type: enabled, budget_tokens: N}, but Opus 4.7+ rejects that with a
ValidationException: thinking.type "enabled" is not supported; it requires
thinking.type "adaptive" plus output_config.effort. Verified by live invoke
against us.anthropic.claude-opus-4-8 (account 328440206208, us-east-1):
the enabled+budget shape 400s, adaptive+effort returns normally.
Map profile effort to additional_model_request_fields:
{thinking: {type: adaptive, display: summarized},
output_config: {effort: <low|medium|high|xhigh|max>}}
reusing anthropic_thinking_for/anthropic_effort_for. Update the two
subagent-model tests asserting the old shape.
* fix(deploy): seed Bedrock/Fireworks models, not the dropped anthropic:/openai: ids
Model selection is store-driven, so seed_store.sh's team_settings/default seed is
what runs in prod. It still seeded the removed providers, which would fail at runtime
after the migration:
- agent/builder: anthropic:claude-opus-4-8 -> bedrock_converse:us.anthropic.claude-opus-4-8
- reviewer: openai:gpt-5.5 (dropped) -> bedrock_converse:us.anthropic.claude-opus-4-8
(set SEED_REVIEWER_MODEL to a Fireworks model for a cross-family reviewer)
- fetch-config REQUIRED_PROVIDER_KEYS default ANTHROPIC_API_KEY,OPENAI_API_KEY ->
FIREWORKS_API_KEY (Bedrock auths via host IAM role; dropping the old keys would
otherwise fail-fast at boot)
- docs (DEPLOYMENT/ROTATION/put-config) updated to match.
Surfaced by the cross-family review + verified against deploy/.
* fix(bedrock): security-review NITs — region resolution, error sanitization, reasoning-block strip
From /sh-security-review (all confirmed-low):
- model.py: resolve region from AWS_REGION OR AWS_DEFAULT_REGION (matches
validate_local_dev_llm_config) so the validated region is the one actually used.
- model_fallback.py: sanitize Bedrock AccessDenied/ResourceNotFound errors to the
error code only, so the role ARN + account id in the raw botocore message never
reach logs or the user channel (CWE-209).
- sanitize_thinking_blocks.py: also strip empty Bedrock reasoning_content blocks
(Converse emits reasoning_content, not thinking) so the middleware is not a no-op
on Bedrock; + unit tests. (Empty blocks replay fine today; defensive.)
* deploy(bedrock): grant instance-role Bedrock invoke + repoint LLM_MODEL_ID / eval model ids
Deployment-readiness for the Bedrock migration (PR #62):
- instance-role.ts: least-privilege bedrock:InvokeModel[WithResponseStream] on the
us.anthropic.claude-opus-4-8 inference-profile ARN + the foundation-model ARN in
each routed region (us-east-1/2, us-west-2). The model runs in the server process
on the box, so the EC2 instance role is the principal. Simulator-verified (allowed
for opus-4-8, implicitDeny for other models) and synth-verified. Passed the
mandatory GPT-4.1 IAM cross-review (no blockers, least-privilege confirmed).
- config-store.ts: IaC SSM LLM_MODEL_ID anthropic:claude-opus-4-8 ->
bedrock_converse:us.anthropic.claude-opus-4-8. This SSM value overrides
seed_store.sh's default via pick precedence, so the seed-script fix alone was
insufficient — both sources now point at the supported Bedrock id.
- infra/README.md + evals/reviewer/config.toml: repoint stale anthropic:/google_genai:
ids to the Bedrock id (config.toml's model_id was an active, now-broken value).
AWS_REGION is already wired via user-data.sh (IMDS -> boot.env), so no change needed there.
* chore(secrets): drop OPENAI/GOOGLE/GROQ key shells (revoked, providers removed)
Those three providers were dropped in the Bedrock/Fireworks migration and their keys
revoked; the live Secrets Manager objects (open-swe-{dev,prod}/{OPENAI,GOOGLE,GROQ}_API_KEY)
were deleted (7-day recovery). Remove them from the IaC so a future cdk deploy does not
recreate the shells, and from fetch-config's mirror array so boot stops requesting them:
- config-store.ts SECRET_VARS + descriptions (28 -> 25 shells)
- fetch-config.sh SECRET_VARS array (kept in lockstep)
- put-config.sh: drop the put_secret lines; ANTHROPIC_API_KEY re-labelled optional
(eval judge only — Bedrock builder/reviewer auth via the host IAM role).
REQUIRED_PROVIDER_KEYS is not set in SSM, so it uses the FIREWORKS_API_KEY default.
When a run is cancelled or the sandbox dies mid-tool-call, LangGraph persists
the AIMessage tool_call but never the matching ToolMessage. The next run sends
the provider an orphaned tool_use (Anthropic 400: "tool_use ids were found
without tool_result blocks"), permanently wedging the thread on every retry.
Add RepairOrphanedToolCallsMiddleware, which inserts a synthetic error
ToolMessage immediately after any tool_call lacking a result so the agent can
retry instead of dying. Wired into the agent and reviewer graphs.
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* feat: add plan mode for read-only research and planning
Adds a per-run plan_mode flag that puts the agent in a read-only
research phase: a strong prompt section is injected and mutating tools
are stripped via ExcludeToolsMiddleware so the agent proposes a
reviewable implementation plan before any edits. Surfaced in the
dashboard UI with a Plan toggle (Shift+Tab) wired through the thread API.
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* fix: enforce plan-mode read-only at tool layer and disable subagents
Addresses PR review: plan mode previously relied on prompt text to keep
the shell read-only and left the task subagent (built with its own
write/PR/Linear tools) unrestricted. Now `task` is excluded so research
cannot be delegated to a mutating subagent, and a new
PlanModeShellGuardMiddleware enforces a read-only command allowlist on
`execute`, blocking writes, git state changes, installs, redirection,
and command substitution regardless of model/prompt-injection compliance.
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* fix: harden plan-mode shell guard against wrapped mutations
Block git global options that take values (-C, --git-dir, ...) from being
misread as the subcommand, reject config-injection options (-c,
--config-env, --exec-path), and drop the env command wrapper that could
run arbitrary commands.
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* feat: add plan mode with enter_plan_mode tool, profile/team defaults, Slack commands and approval flow
- enter_plan_mode tool: agent self-activates plan mode via Command(update={'plan_mode': True})
- Plan mode resolution: per-thread > profile default > team default > False
- PLAN_MODE_GUIDANCE_SECTION: always-present prompt section telling agent about the tool
- profile_plan_mode_default and team plan_mode_default settings
- Slack plan on/off/status commands with thread metadata persistence
- slack_thread_reply plan_approval=True renders Approve/Revise/Cancel buttons
- Interactivity handler: approve triggers implementation run, cancel posts confirmation
- Frontend: plan_mode_default in Profile/ProfileUpdate/TeamSettings types and UI toggles
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* test: add tests for enter_plan_mode tool, profile/team defaults, Slack plan commands, approval blocks
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* refactor(plan-mode): drop shell guard, rely on prompt for read-only discipline
Remove PlanModeShellGuardMiddleware and its enforcement of read-only shell
commands during plan mode. Plan mode now relies on the system prompt to
instruct the agent not to run mutating commands; the mutating-tool exclusion
(ExcludeToolsMiddleware) is retained.
* test(open-swe): add Playwright E2E for the Slack → PR → web handoff
Local, secrets-free end-to-end suite that drives the full happy path through mock Slack/GitHub control panels and the real dashboard UI. Only the LLM and external SaaS HTTP boundaries (GitHub/Slack APIs, OAuth token mint) are faked — the real process_slack_mention, get_agent, deepagents loop, tools, middleware, and dashboard authorization all run under `langgraph dev` with a scripted fake chat model and a local temp-dir sandbox.
- full_flow: a Slack mention runs the agent, which implements a change in the sandbox, opens a PR against a fake GitHub remote, and replies with the PR link in the same thread.
- dashboard: clicking the bot's real "Open in Web" link loads the built ui/ app (served same-origin); the thread owner can continue the conversation, while a different user sees the same thread read-only (no composer).
Wired into Agent CI as a `Playwright E2E` job that runs on pull requests.
* fix(open-swe): serve E2E UI assets via explicit route; pin Playwright
The dashboard E2E served the built ui/ SPA's /assets via app.mount(StaticFiles), but LangGraph's custom-app loader serves APIRoutes and drops sub-app Mounts, so /assets 404'd under `langgraph dev` in CI — the React app never booted and the composer/transcript never rendered. Serve assets via an explicit route instead.
Also pin @playwright/test to the latest (1.61.0) for reproducible runs, and make the owner composer assertion tolerant of either hydration state.
* test(open-swe): record Playwright trace + video on every E2E run
Capture a replayable trace (DOM snapshots, network, console, source) and a screen recording for every test, not just retries, plus a screenshot on failure. The CI job already uploads playwright-report/ and test-results/, so each run now has a downloadable replay; documented how to open it.
* feat(plan-mode): collaborative plan review with BlockNote + Yjs
When the agent enters plan mode it writes the plan as a markdown file in the
sandbox (save_plan tool), publishes it, and posts a review link to the source
channel. Reviewers open the plan inside the dashboard (under the /agents shell),
read it rendered in a BlockNote editor, and leave inline comments synced live
over Yjs. Only the thread owner can approve; any reviewer can request changes.
On approve/reject the comments are harvested and handed to the agent for the
follow-up run; the agent never sees comments mid-review.
- agent: enter_plan_mode persists plan state; new save_plan tool; prompt shares
the plan-review link.
- dashboard: Yjs WebSocket collab server (pycrdt-websocket) with store-backed
snapshots; plan content/status store; plan REST API (get/approve/reject,
owner-only approve, client-harvested comments); planStatus on thread summaries.
- ui: BlockNote native comments (CommentsExtension + YjsThreadStore) plan page
mounted under the agents shell, with a "Review plan" banner in the thread view
and a back-link; theme-aware (dark mode) using the dashboard tokens.
- e2e: Playwright coverage of the full Slack -> plan -> review -> approve -> PR
flow, including cross-user comment sync and owner-only approval.
* fix(plan-mode): address review feedback (authz, overrides, leaks, deps)
- plan-collab WS: authorize per-thread before joining a room (same read gate as
the REST API) — previously any logged-in user could join any thread (IDOR).
- plan-collab: tie the snapshot flusher to active connections (refcount) so each
opened plan no longer leaks a permanent 1.5s task on the shared event loop.
- plan decisions: include thread_id in the follow-up run configurable so the run
resumes the existing thread; set plan_mode explicitly so approve forces it off.
- get_agent: an explicit per-thread plan_mode (Slack `plan off`, approved plan,
dashboard toggle) now overrides profile/team defaults instead of falling back.
- plan mode tool gating moved to a state-aware PlanModeMiddleware installed
unconditionally, so a mid-run enter_plan_mode restricts the next model turn;
before_agent resets stale plan_mode so a later run isn't forced back into it.
- exclude write-capable http_request from plan mode.
- pin pycrdt / pycrdt-websocket with upper bounds.
Includes the latest base (#1583): E2E UI assets served via explicit route
(fixes the Playwright CI failure — LangGraph's app loader drops sub-app mounts).
* style: ruff format plan_collab.py
* fix(plan-mode): owner-gate Slack approval + same-origin check on collab WS
- Slack "Approve & Implement" now verifies the clicking user is the plan
requester (owner, via the stored triggering_user_id) before implementing —
matching the dashboard API's owner-only approval. Non-owners are pointed to
Revise / feedback.
- The plan-collab WebSocket validates the handshake Origin against the dashboard
allowlist before accept() (no-op when unconfigured, e.g. local/dev), mirroring
the REST require_same_origin CSRF defense.
* fix(plan-mode): enter plan mode only via the model + local mock dev harness
Plan mode is now entered solely when the model calls enter_plan_mode.
Removed the per-user and team plan_mode_default settings (backend + UI)
and the Slack `plan on/off/status` toggle.
- enter_plan_mode returns a terminating ToolMessage, fixing the missing
ToolMessage error that silently dropped plan mode mid-run.
- PlanReview: defer Yjs provider/doc teardown so React StrictMode's dev
remount doesn't destroy and then reuse the collaboration provider.
- e2e plan_review spec asserts plan_mode actually engages.
- LangSmith trace-url resolution is best-effort: bail before any API
call when the tenant is unset, cache failures, log at debug.
- Add `pnpm run dev:mock`: same-origin Vite HMR harness with a real LLM,
Alice/Bob mock users, and a GitHub login picker.
* docs(plan-mode): drop stale references to removed profile/team defaults
The plan_mode middleware docstring and the approve/reject dispatch comment
still described the profile/team plan_mode_default resolution that no longer
exists; reword to match model-driven entry + the per-thread carry.
* feat(plan-mode): let any reviewer edit the plan, not just comment
Drop the owner/commenter split for the plan document: everyone with read
access edits and comments alike (DefaultThreadStoreAuth "editor" for all,
editor always editable until a decision, anyone seeds the empty doc). This
matches the collab WS, which already relays frames to every readable user.
Plan approval stays owner-gated.
* test(plan-mode): assert plan-mode entry via the tool's success message
plan_mode lives only in run state for tool gating; it is not a persisted
thread-state channel, so the previous `values.plan_mode === true` poll
could never pass. Assert instead that enter_plan_mode's success ToolMessage
("Plan mode is active …") lands in the thread — which only happens when the
tool's Command applies cleanly, the exact regression this guards.
---------
Co-authored-by: Johannes du Plessis <51395795+johannes117@users.noreply.github.com>
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* feat: activate PR babysitting UI toggles for autofix and trigger mode
Remove the "coming soon" gating on the Autofix Mode, Autofix Severity
Threshold, and Trigger Mode controls in the review settings page so
admins can enable CI auto-fix and review-comment resolution on PRs
that Open SWE opens. The backend (ci_autofix.py, webapp.py webhook
routing) was already fully wired — only the UI was disabled.
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* feat: simplify autofix to on/off toggle, remove severity threshold
Replace the four-level AutofixMode (off/low/medium/high) and the
autofix_severity_threshold setting with a single boolean
autofix_enabled toggle. The severity threshold was leftover from the
reviewer finding-severity model and does not apply to CI autofix;
the agent should fix any failing CI and resolve any comments on PRs
it opens.
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* feat: move autofix toggle to per-user profile, remove team-level setting
The autofix toggle is now per-user (auto_fix_ci in the user profile)
instead of team-level (admin-only). This uses the existing auto_fix_ci
field that was already in ProfileUpdate but never wired up.
Changes:
- ci_autofix.py: check per-user auto_fix_ci profile flag after
resolving the agent thread's github_login, instead of checking
team-level autofix_enabled before knowing the PR
- webapp.py: removed early is_autofix_enabled() webhook gates; the
per-user check now happens in ci_autofix.py once the thread is found
- team_settings.py: removed autofix_enabled field, is_autofix_enabled()
- cloud-agents.tsx: enabled the auto_fix_ci toggle (was comingSoon)
- review.tsx: removed the admin-level autofix switch
- Updated tests and AGENTS.md
The agent graph (not the reviewer) is what gets dispatched - this was
already correct in ci_autofix.py line 223: client.runs.create(
thread_id, "agent", ...).
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* feat: batch PR babysitting events
Remove the leftover trigger-mode gate from PR babysitting and batch new CI/review events while an agent run is already active so the running agent can handle the latest PR state before finishing. Also moves review-feedback permission checks behind the per-user opt-out and applies the auto-fix profile gate to merge-conflict babysitting.
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* fix: consume batched babysitting events
Teach the agent queue middleware to turn pending PR babysitting metadata into an injected instruction for the active run, so batched CI/review events are not dropped while still avoiding duplicate run creation.
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* fix: address review findings in PR babysitting batching
- Route batched events through the LangGraph store (read in-process by the
message-queue middleware) instead of a per-model-call threads.get on every
agent thread.
- Only record an attempt / mark the head SHA handled on a real dispatch, not
on a batch, so an event isn't permanently dropped if the in-flight run ends
before consuming it.
- Carry the reviewer's comment through batched review feedback instead of
replacing it with a generic re-check nudge.
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* feat: handle images sent to non-vision models in Slack, Linear, and web UI
Add vision capability checks across all image input paths. When a user
sends images to a text-only model (e.g. GLM 5.2, DeepSeek V4 Pro), the
images are now skipped and a warning is injected into the prompt instead
of sending unsupported content to the model.
- Slack: resolve model at webhook time, skip image fetch + add warning
- Linear: same pattern as Slack
- Queued message middleware: read resolved model from thread metadata,
strip images from queued payloads for text-only models
- Web UI: disable submit + show inline warning when images are attached
to a non-vision model selection
- Shared: resolve_agent_model_id helper + vision_not_supported_warning
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* test: mock resolve_agent_model_id in Slack mention test
The test_process_slack_mention_queues_active_thread_message test was
missing a mock for the new resolve_agent_model_id call added to the
Slack webhook handler, causing a TypeError when image URLs triggered
the model resolution path.
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* fix: include vision warning in queued payload for text-only models
Update the prompt variable (not just content_blocks) before clearing
image_urls so the queued payload also carries the warning text when a
Slack/Linear follow-up arrives while the thread is busy.
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
Remove the hardcoded "call a tool every turn" instruction from the system
prompt and delete the ensure_no_empty_msg middleware that re-injected no_op /
confirming_completion tool calls. The agent now ends its turn naturally when
the model emits a final message with no tool call, which avoids needlessly
extending trajectories (and token spend) on tasks that are already complete.
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* fix: refresh sandbox GitHub proxy token before mid-run expiry
GitHub App installation tokens expire after exactly 1 hour. The LangSmith
sandbox proxy was configured once at run start with a snapshot of that
token, so runs longer than ~1h hit 401s on every gh/git call. Record the
proxy token's expiry per thread and add a before-model hook that
re-configures the proxy with a fresh token when it nears expiry.
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* fix: preserve repo-scoped proxy token on mid-run refresh
Reviewer runs mint a repository-scoped installation token. Record the
repo scope per thread alongside the expiry so the before-model refresh
re-mints a token with the same scope instead of an installation-wide
token, avoiding privilege expansion on long reviewer runs.
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* fix: update passthrough stub for github_proxy_repositories param
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* feat: report Open SWE Review as a PR check run
Auto-review dispatch now creates an in-progress 'Open SWE Review' check run
on the PR head SHA; publish_review completes it (neutral with findings,
success when clean). An after-agent hook fails the check if the run dies
before publishing. Requires the GitHub App's Checks: Read & write permission;
all calls are best-effort so a missing permission never breaks reviews.
* fix: address review feedback on check-run settling
Keep review_check_run_id when the completion PATCH fails so a later
publish or the after-agent hook can retry instead of hanging the check;
count out-of-diff findings toward the check conclusion.
* fix: retry failed check completion with the real publish conclusion
A transient PATCH failure after a successful publish previously left the
check id for the after-agent hook, which settled it as 'failure'. Persist
the intended result as review_check_pending_result and have the hook
prefer it over the generic failure fallback.
---------
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>
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.
* 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>
* 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
* fix: prevent futile retry loop when commit_and_open_pr fails with git/API errors
- Root cause: when git checkout or GitHub PR API fails, the tool returned a generic {"success": false} error with no signal that retrying is futile, causing the agent to loop 9-13+ times until hitting the 1000-step recursion limit
- Change: (1) git_checkout_branch now returns (bool, str) so the actual git error output is surfaced in the tool response; (2) checkout and PR creation failures now include "fatal": true and an explicit "Do not retry" message; (3) prompt.py COMMIT_PR_SECTION adds an explicit instruction to stop on fatal errors
- Verified: 109 unit tests pass, no regressions
* fix: skip PR safety net on fatal commit failures
* style(open_pr): ruff-format fatal retry skip condition
---------
Co-authored-by: LangSmith Forge <forge-agent@langsmith.ai>
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>
* fix: stop agent retrying commit_and_open_pr on 403 permission denied
Detect 403/permission-denied push failures in commit_and_open_pr and
return a PERMANENT_FAILURE message so the LLM stops retrying. Also add
prompt-level guidance to the COMMIT_PR_SECTION reinforcing this. Add
unit tests covering both the 403 and non-403 push failure paths.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix: stop safety net retrying permanent push failures
Skip the after-agent PR fallback when commit_and_open_pr reports a permanent GitHub push authorization failure, while preserving fallback behavior for recoverable failures.
---------
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>
Calling get_github_token() without arguments always invoked LangGraph get_config internally,
which broke tests that only patch agent.middleware.open_pr.get_config and failed outside
runnable context.
Extend get_github_token with an optional runnable config mapping; the middleware passes
the config dict already resolved from get_config(). Request GitHub App installation tokens
only after detecting sandbox/repo changes worth publishing.
Fixes failing Agent unit tests in tests/test_open_pr_middleware.py.
* fix: safety net middleware always skipped due to key-existence check
The open_pr_if_needed after-agent middleware checked `if 'success' in pr_payload`
which evaluates True for BOTH success and failure responses from commit_and_open_pr
(all responses include the 'success' key). This meant the safety net never fired.
Fix: use `pr_payload.get('success')` to check the VALUE instead of key existence.
Evidence: 6+ production traces in last 24h where commit_and_open_pr returned
success=False but the safety net silently skipped (non-fast-forward push failures,
missing GitHub token, workflow permission errors, API 500 errors).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* update
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: Palash Shah <palash@langchain.dev>
* feat: open PRs under user's name and add OpenSWE label
* feat: use user token for PR authorship, add OpenSWE label, and consolidate fallback logic
* linting
* fix: address review nits for PR authorship and labeling
Fix docstring casing, add debug logging for 422 existing-PR search
fallback, tighten test type annotations, and add missing HTTPError
fallback test.
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
* fix: use GitHub App installation token for PR creation instead of user token
* fix: move installation token fetch after no-changes check to avoid unnecessary API call
* fix: skip no_op injection when PR is committed and user is notified
- Root cause: ensure_no_empty_msg Branch 1 (empty AI message) lacked the
same completion checks as Branch 2 (text-only AI message), causing a
spurious no_op injection after commit_and_open_pr + user notification
- Change: add check_if_model_already_called_commit_and_open_pr AND
check_if_model_messaged_user guard to Branch 1 of ensure_no_empty_msg
- Verified: 7/100 production traces no longer get an extra LLM call
* updated
* pass tests
---------
Co-authored-by: Auto Fix Bot <auto-fix@langchain.ai>
Co-authored-by: Palash Shah <palash@langchain.dev>
Co-authored-by: Palash Shah <35114859+Palashio@users.noreply.github.com>
* feat: add GitHub PR comment trigger and reply support
* refactor: improve readability of GitHub integration
* linting
* fix: resolve github token from thread metadata and improve PR trigger flow
* fix: fall back to OAuth for GitHub webhook when no token in thread metadata
* give me commit message github integeration working without a breaking
* auth.py refactor
* fix: validate cached GitHub token before use to handle expiry
* liniting
* ci unitest formatting
* feat: post PR comments as GitHub App bot instead of user OAuth token
* resolved comments
* slack resolveed comments
* Refactor docstring and comments in get_slack_repo_config
Removed unnecessary comments and cleaned up docstring formatting.
* cr
* cr
* cr
* cr
---------
Co-authored-by: bracesproul <braceasproul@gmail.com>
