feat(auth): release-validation pass for 2.0-rc — 12 blockers + simplify follow-ups (#2008)

* feat(auth): introduce backend auth module

Port RFC-001 authentication core from PR #1728:
- JWT token handling (create_access_token, decode_token, TokenPayload)
- Password hashing (bcrypt) with verify_password
- SQLite UserRepository with base interface
- Provider Factory pattern (LocalAuthProvider)
- CLI reset_admin tool
- Auth-specific errors (AuthErrorCode, TokenError, AuthErrorResponse)

Deps:
- bcrypt>=4.0.0
- pyjwt>=2.9.0
- email-validator>=2.0.0
- backend/uv.toml pins public PyPI index

Tests: 12 pure unit tests (test_auth_config.py, test_auth_errors.py).

Scope note: authz.py, test_auth.py, and test_auth_type_system.py are
deferred to commit 2 because they depend on middleware and deps wiring
that is not yet in place. Commit 1 stays "pure new files only" as the
spec mandates.

* feat(auth): wire auth end-to-end (middleware + frontend replacement)

Backend:
- Port auth_middleware, csrf_middleware, langgraph_auth, routers/auth
- Port authz decorator (owner_filter_key defaults to 'owner_id')
- Merge app.py: register AuthMiddleware + CSRFMiddleware + CORS, add
  _ensure_admin_user lifespan hook, _migrate_orphaned_threads helper,
  register auth router
- Merge deps.py: add get_local_provider, get_current_user_from_request,
  get_optional_user_from_request; keep get_current_user as thin str|None
  adapter for feedback router
- langgraph.json: add auth path pointing to langgraph_auth.py:auth
- Rename metadata['user_id'] -> metadata['owner_id'] in langgraph_auth
  (both metadata write and LangGraph filter dict) + test fixtures

Frontend:
- Delete better-auth library and api catch-all route
- Remove better-auth npm dependency and env vars (BETTER_AUTH_SECRET,
  BETTER_AUTH_GITHUB_*) from env.js
- Port frontend/src/core/auth/* (AuthProvider, gateway-config,
  proxy-policy, server-side getServerSideUser, types)
- Port frontend/src/core/api/fetcher.ts
- Port (auth)/layout, (auth)/login, (auth)/setup pages
- Rewrite workspace/layout.tsx as server component that calls
  getServerSideUser and wraps in AuthProvider
- Port workspace/workspace-content.tsx for the client-side sidebar logic

Tests:
- Port 5 auth test files (test_auth, test_auth_middleware,
  test_auth_type_system, test_ensure_admin, test_langgraph_auth)
- 176 auth tests PASS

After this commit: login/logout/registration flow works, but persistence
layer does not yet filter by owner_id. Commit 4 closes that gap.

* feat(auth): account settings page + i18n

- Port account-settings-page.tsx (change password, change email, logout)
- Wire into settings-dialog.tsx as new "account" section with UserIcon,
  rendered first in the section list
- Add i18n keys:
  - en-US/zh-CN: settings.sections.account ("Account" / "账号")
  - en-US/zh-CN: button.logout ("Log out" / "退出登录")
  - types.ts: matching type declarations

* feat(auth): enforce owner_id across 2.0-rc persistence layer

Add request-scoped contextvar-based owner filtering to threads_meta,
runs, run_events, and feedback repositories. Router code is unchanged
— isolation is enforced at the storage layer so that any caller that
forgets to pass owner_id still gets filtered results, and new routes
cannot accidentally leak data.

Core infrastructure
-------------------
- deerflow/runtime/user_context.py (new):
  - ContextVar[CurrentUser | None] with default None
  - runtime_checkable CurrentUser Protocol (structural subtype with .id)
  - set/reset/get/require helpers
  - AUTO sentinel + resolve_owner_id(value, method_name) for sentinel
    three-state resolution: AUTO reads contextvar, explicit str
    overrides, explicit None bypasses the filter (for migration/CLI)

Repository changes
------------------
- ThreadMetaRepository: create/get/search/update_*/delete gain
  owner_id=AUTO kwarg; read paths filter by owner, writes stamp it,
  mutations check ownership before applying
- RunRepository: put/get/list_by_thread/delete gain owner_id=AUTO kwarg
- FeedbackRepository: create/get/list_by_run/list_by_thread/delete
  gain owner_id=AUTO kwarg
- DbRunEventStore: list_messages/list_events/list_messages_by_run/
  count_messages/delete_by_thread/delete_by_run gain owner_id=AUTO
  kwarg. Write paths (put/put_batch) read contextvar softly: when a
  request-scoped user is available, owner_id is stamped; background
  worker writes without a user context pass None which is valid
  (orphan row to be bound by migration)

Schema
------
- persistence/models/run_event.py: RunEventRow.owner_id = Mapped[
  str | None] = mapped_column(String(64), nullable=True, index=True)
- No alembic migration needed: 2.0 ships fresh, Base.metadata.create_all
  picks up the new column automatically

Middleware
----------
- auth_middleware.py: after cookie check, call get_optional_user_from_
  request to load the real User, stamp it into request.state.user AND
  the contextvar via set_current_user, reset in a try/finally. Public
  paths and unauthenticated requests continue without contextvar, and
  @require_auth handles the strict 401 path

Test infrastructure
-------------------
- tests/conftest.py: @pytest.fixture(autouse=True) _auto_user_context
  sets a default SimpleNamespace(id="test-user-autouse") on every test
  unless marked @pytest.mark.no_auto_user. Keeps existing 20+
  persistence tests passing without modification
- pyproject.toml [tool.pytest.ini_options]: register no_auto_user
  marker so pytest does not emit warnings for opt-out tests
- tests/test_user_context.py: 6 tests covering three-state semantics,
  Protocol duck typing, and require/optional APIs
- tests/test_thread_meta_repo.py: one test updated to pass owner_id=
  None explicitly where it was previously relying on the old default

Test results
------------
- test_user_context.py: 6 passed
- test_auth*.py + test_langgraph_auth.py + test_ensure_admin.py: 127
- test_run_event_store / test_run_repository / test_thread_meta_repo
  / test_feedback: 92 passed
- Full backend suite: 1905 passed, 2 failed (both @requires_llm flaky
  integration tests unrelated to auth), 1 skipped

* feat(auth): extend orphan migration to 2.0-rc persistence tables

_ensure_admin_user now runs a three-step pipeline on every boot:

  Step 1 (fatal):     admin user exists / is created / password is reset
  Step 2 (non-fatal): LangGraph store orphan threads → admin
  Step 3 (non-fatal): SQL persistence tables → admin
    - threads_meta
    - runs
    - run_events
    - feedback

Each step is idempotent. The fatal/non-fatal split mirrors PR #1728's
original philosophy: admin creation failure blocks startup (the system
is unusable without an admin), whereas migration failures log a warning
and let the service proceed (a partial migration is recoverable; a
missing admin is not).

Key helpers
-----------
- _iter_store_items(store, namespace, *, page_size=500):
  async generator that cursor-paginates across LangGraph store pages.
  Fixes PR #1728's hardcoded limit=1000 bug that would silently lose
  orphans beyond the first page.

- _migrate_orphaned_threads(store, admin_user_id):
  Rewritten to use _iter_store_items. Returns the migrated count so the
  caller can log it; raises only on unhandled exceptions.

- _migrate_orphan_sql_tables(admin_user_id):
  Imports the 4 ORM models lazily, grabs the shared session factory,
  runs one UPDATE per table in a single transaction, commits once.
  No-op when no persistence backend is configured (in-memory dev).

Tests: test_ensure_admin.py (8 passed)

* test(auth): port AUTH test plan docs + lint/format pass

- Port backend/docs/AUTH_TEST_PLAN.md and AUTH_UPGRADE.md from PR #1728
- Rename metadata.user_id → metadata.owner_id in AUTH_TEST_PLAN.md
  (4 occurrences from the original PR doc)
- ruff auto-fix UP037 in sentinel type annotations: drop quotes around
  "str | None | _AutoSentinel" now that from __future__ import
  annotations makes them implicit string forms
- ruff format: 2 files (app/gateway/app.py, runtime/user_context.py)

Note on test coverage additions:
- conftest.py autouse fixture was already added in commit 4 (had to
  be co-located with the repository changes to keep pre-existing
  persistence tests passing)
- cross-user isolation E2E tests (test_owner_isolation.py) deferred
  — enforcement is already proven by the 98-test repository suite
  via the autouse fixture + explicit _AUTO sentinel exercises
- New test cases (TC-API-17..20, TC-ATK-13, TC-MIG-01..07) listed
  in AUTH_TEST_PLAN.md are deferred to a follow-up PR — they are
  manual-QA test cases rather than pytest code, and the spec-level
  coverage is already met by test_user_context.py + the 98-test
  repository suite.

Final test results:
- Auth suite (test_auth*, test_langgraph_auth, test_ensure_admin,
  test_user_context): 186 passed
- Persistence suite (test_run_event_store, test_run_repository,
  test_thread_meta_repo, test_feedback): 98 passed
- Lint: ruff check + ruff format both clean

* test(auth): add cross-user isolation test suite

10 tests exercising the storage-layer owner filter by manually
switching the user_context contextvar between two users. Verifies
the safety invariant:

  After a repository write with owner_id=A, a subsequent read with
  owner_id=B must not return the row, and vice versa.

Covers all 4 tables that own user-scoped data:

TC-API-17  threads_meta  — read, search, update, delete cross-user
TC-API-18  runs          — get, list_by_thread, delete cross-user
TC-API-19  run_events    — list_messages, list_events, count_messages,
                           delete_by_thread (CRITICAL: raw conversation
                           content leak vector)
TC-API-20  feedback      — get, list_by_run, delete cross-user

Plus two meta-tests verifying the sentinel pattern itself:
- AUTO + unset contextvar raises RuntimeError
- explicit owner_id=None bypasses the filter (migration escape hatch)

Architecture note
-----------------
These tests bypass the HTTP layer by design. The full chain
(cookie → middleware → contextvar → repository) is covered piecewise:

- test_auth_middleware.py: middleware sets contextvar from cookies
- test_owner_isolation.py: repositories enforce isolation when
  contextvar is set to different users

Together they prove the end-to-end safety property without the
ceremony of spinning up a full TestClient + in-memory DB for every
router endpoint.

Tests pass: 231 (full auth + persistence + isolation suite)
Lint: clean

* refactor(auth): migrate user repository to SQLAlchemy ORM

Move the users table into the shared persistence engine so auth
matches the pattern of threads_meta, runs, run_events, and feedback —
one engine, one session factory, one schema init codepath.

New files
---------
- persistence/user/__init__.py, persistence/user/model.py: UserRow
  ORM class with partial unique index on (oauth_provider, oauth_id)
- Registered in persistence/models/__init__.py so
  Base.metadata.create_all() picks it up

Modified
--------
- auth/repositories/sqlite.py: rewritten as async SQLAlchemy,
  identical constructor pattern to the other four repositories
  (def __init__(self, session_factory) + self._sf = session_factory)
- auth/config.py: drop users_db_path field — storage is configured
  through config.database like every other table
- deps.py/get_local_provider: construct SQLiteUserRepository with
  the shared session factory, fail fast if engine is not initialised
- tests/test_auth.py: rewrite test_sqlite_round_trip_new_fields to
  use the shared engine (init_engine + close_engine in a tempdir)
- tests/test_auth_type_system.py: add per-test autouse fixture that
  spins up a scratch engine and resets deps._cached_* singletons

* refactor(auth): remove SQL orphan migration (unused in supported scenarios)

The _migrate_orphan_sql_tables helper existed to bind NULL owner_id
rows in threads_meta, runs, run_events, and feedback to the admin on
first boot. But in every supported upgrade path, it's a no-op:

  1. Fresh install: create_all builds fresh tables, no legacy rows
  2. No-auth → with-auth (no existing persistence DB): persistence
     tables are created fresh by create_all, no legacy rows
  3. No-auth → with-auth (has existing persistence DB from #1930):
     NOT a supported upgrade path — "有 DB 到有 DB" schema evolution
     is out of scope; users wipe DB or run manual ALTER

So the SQL orphan migration never has anything to do in the
supported matrix. Delete the function, simplify _ensure_admin_user
from a 3-step pipeline to a 2-step one (admin creation + LangGraph
store orphan migration only).

LangGraph store orphan migration stays: it serves the real
"no-auth → with-auth" upgrade path where a user's existing LangGraph
thread metadata has no owner_id field and needs to be stamped with
the newly-created admin's id.

Tests: 284 passed (auth + persistence + isolation)
Lint: clean

* security(auth): write initial admin password to 0600 file instead of logs

CodeQL py/clear-text-logging-sensitive-data flagged 3 call sites that
logged the auto-generated admin password to stdout via logger.info().
Production log aggregators (ELK/Splunk/etc) would have captured those
cleartext secrets. Replace with a shared helper that writes to
.deer-flow/admin_initial_credentials.txt with mode 0600, and log only
the path.

New file
--------
- app/gateway/auth/credential_file.py: write_initial_credentials()
  helper. Takes email, password, and a "initial"/"reset" label.
  Creates .deer-flow/ if missing, writes a header comment plus the
  email+password, chmods 0o600, returns the absolute Path.

Modified
--------
- app/gateway/app.py: both _ensure_admin_user paths (fresh creation
  + needs_setup password reset) now write to file and log the path
- app/gateway/auth/reset_admin.py: rewritten to use the shared ORM
  repo (SQLiteUserRepository with session_factory) and the
  credential_file helper. The previous implementation was broken
  after the earlier ORM refactor — it still imported _get_users_conn
  and constructed SQLiteUserRepository() without a session factory.

No tests changed — the three password-log sites are all exercised
via existing test_ensure_admin.py which checks that startup
succeeds, not that a specific string appears in logs.

CodeQL alerts 272, 283, 284: all resolved.

* security(auth): strict JWT validation in middleware (fix junk cookie bypass)

AUTH_TEST_PLAN test 7.5.8 expects junk cookies to be rejected with
401. The previous middleware behaviour was "presence-only": check
that some access_token cookie exists, then pass through. In
combination with my Task-12 decision to skip @require_auth
decorators on routes, this created a gap where a request with any
cookie-shaped string (e.g. access_token=not-a-jwt) would bypass
authentication on routes that do not touch the repository
(/api/models, /api/mcp/config, /api/memory, /api/skills, …).

Fix: middleware now calls get_current_user_from_request() strictly
and catches the resulting HTTPException to render a 401 with the
proper fine-grained error code (token_invalid, token_expired,
user_not_found, …). On success it stamps request.state.user and
the contextvar so repository-layer owner filters work downstream.

The 4 old "_with_cookie_passes" tests in test_auth_middleware.py
were written for the presence-only behaviour; they asserted that
a junk cookie would make the handler return 200. They are renamed
to "_with_junk_cookie_rejected" and their assertions flipped to
401. The negative path (no cookie → 401 not_authenticated)
is unchanged.

Verified:
  no cookie       → 401 not_authenticated
  junk cookie     → 401 token_invalid     (the fixed bug)
  expired cookie  → 401 token_expired

Tests: 284 passed (auth + persistence + isolation)
Lint: clean

* security(auth): wire @require_permission(owner_check=True) on isolation routes

Apply the require_permission decorator to all 28 routes that take a
{thread_id} path parameter. Combined with the strict middleware
(previous commit), this gives the double-layer protection that
AUTH_TEST_PLAN test 7.5.9 documents:

  Layer 1 (AuthMiddleware): cookie + JWT validation, rejects junk
                            cookies and stamps request.state.user
  Layer 2 (@require_permission with owner_check=True): per-resource
                            ownership verification via
                            ThreadMetaStore.check_access — returns
                            404 if a different user owns the thread

The decorator's owner_check branch is rewritten to use the SQL
thread_meta_repo (the 2.0-rc persistence layer) instead of the
LangGraph store path that PR #1728 used (_store_get / get_store
in routers/threads.py). The inject_record convenience is dropped
— no caller in 2.0 needs the LangGraph blob, and the SQL repo has
a different shape.

Routes decorated (28 total):
- threads.py: delete, patch, get, get-state, post-state, post-history
- thread_runs.py: post-runs, post-runs-stream, post-runs-wait,
  list_runs, get_run, cancel_run, join_run, stream_existing_run,
  list_thread_messages, list_run_messages, list_run_events,
  thread_token_usage
- feedback.py: create, list, stats, delete
- uploads.py: upload (added Request param), list, delete
- artifacts.py: get_artifact
- suggestions.py: generate (renamed body parameter to avoid
  conflict with FastAPI Request)

Test fixes:
- test_suggestions_router.py: bypass the decorator via __wrapped__
  (the unit tests cover parsing logic, not auth — no point spinning
  up a thread_meta_repo just to test JSON unwrapping)
- test_auth_middleware.py 4 fake-cookie tests: already updated in
  the previous commit (745bf432)

Tests: 293 passed (auth + persistence + isolation + suggestions)
Lint: clean

* security(auth): defense-in-depth fixes from release validation pass

Eight findings caught while running the AUTH_TEST_PLAN end-to-end against
the deployed sg_dev stack. Each is a pre-condition for shipping
release/2.0-rc that the previous PRs missed.

Backend hardening
- routers/auth.py: rate limiter X-Real-IP now requires AUTH_TRUSTED_PROXIES
  whitelist (CIDR/IP allowlist). Without nginx in front, the previous code
  honored arbitrary X-Real-IP, letting an attacker rotate the header to
  fully bypass the per-IP login lockout.
- routers/auth.py: 36-entry common-password blocklist via Pydantic
  field_validator on RegisterRequest + ChangePasswordRequest. The shared
  _validate_strong_password helper keeps the constraint in one place.
- routers/threads.py: ThreadCreateRequest + ThreadPatchRequest strip
  server-reserved metadata keys (owner_id, user_id) via Pydantic
  field_validator so a forged value can never round-trip back to other
  clients reading the same thread. The actual ownership invariant stays
  on the threads_meta row; this closes the metadata-blob echo gap.
- authz.py + thread_meta/sql.py: require_permission gains a require_existing
  flag plumbed through check_access(require_existing=True). Destructive
  routes (DELETE/PATCH/state-update/runs/feedback) now treat a missing
  thread_meta row as 404 instead of "untracked legacy thread, allow",
  closing the cross-user delete-idempotence gap where any user could
  successfully DELETE another user's deleted thread.
- repositories/sqlite.py + base.py: update_user raises UserNotFoundError
  on a vanished row instead of silently returning the input. Concurrent
  delete during password reset can no longer look like a successful update.
- runtime/user_context.py: resolve_owner_id() coerces User.id (UUID) to
  str at the contextvar boundary so SQLAlchemy String(64) columns can
  bind it. The whole 2.0-rc isolation pipeline was previously broken
  end-to-end (POST /api/threads → 500 "type 'UUID' is not supported").
- persistence/engine.py: SQLAlchemy listener enables PRAGMA journal_mode=WAL,
  synchronous=NORMAL, foreign_keys=ON on every new SQLite connection.
  TC-UPG-06 in the test plan expects WAL; previous code shipped with the
  default 'delete' journal.
- auth_middleware.py: stamp request.state.auth = AuthContext(...) so
  @require_permission's short-circuit fires; previously every isolation
  request did a duplicate JWT decode + users SELECT. Also unifies the
  401 payload through AuthErrorResponse(...).model_dump().
- app.py: _ensure_admin_user restructure removes the noqa F821 scoping
  bug where 'password' was referenced outside the branch that defined it.
  New _announce_credentials helper absorbs the duplicate log block in
  the fresh-admin and reset-admin branches.

* fix(frontend+nginx): rollout CSRF on every state-changing client path

The frontend was 100% broken in gateway-pro mode for any user trying to
open a specific chat thread. Three cumulative bugs each silently
masked the next.

LangGraph SDK CSRF gap (api-client.ts)
- The Client constructor took only apiUrl, no defaultHeaders, no fetch
  interceptor. The SDK's internal fetch never sent X-CSRF-Token, so
  every state-changing /api/langgraph-compat/* call (runs/stream,
  threads/search, threads/{tid}/history, ...) hit CSRFMiddleware and
  got 403 before reaching the auth check. UI symptom: empty thread page
  with no error message; the SPA's hooks swallowed the rejection.
- Fix: pass an onRequest hook that injects X-CSRF-Token from the
  csrf_token cookie per request. Reading the cookie per call (not at
  construction time) handles login / logout / password-change cookie
  rotation transparently. The SDK's prepareFetchOptions calls
  onRequest for both regular requests AND streaming/SSE/reconnect, so
  the same hook covers runs.stream and runs.joinStream.

Raw fetch CSRF gap (7 files)
- Audit: 11 frontend fetch sites, only 2 included CSRF (login/setup +
  account-settings change-password). The other 7 routed through raw
  fetch() with no header — suggestions, memory, agents, mcp, skills,
  uploads, and the local thread cleanup hook all 403'd silently.
- Fix: enhance fetcher.ts:fetchWithAuth to auto-inject X-CSRF-Token on
  POST/PUT/DELETE/PATCH from a single shared readCsrfCookie() helper.
  Convert all 7 raw fetch() callers to fetchWithAuth so the contract
  is centrally enforced. api-client.ts and fetcher.ts share
  readCsrfCookie + STATE_CHANGING_METHODS to avoid drift.

nginx routing + buffering (nginx.local.conf)
- The auth feature shipped without updating the nginx config: per-API
  explicit location blocks but no /api/v1/auth/, /api/feedback, /api/runs.
  The frontend's client-side fetches to /api/v1/auth/login/local 404'd
  from the Next.js side because nginx routed /api/* to the frontend.
- Fix: add catch-all `location /api/` that proxies to the gateway.
  nginx longest-prefix matching keeps the explicit blocks (/api/models,
  /api/threads regex, /api/langgraph/, ...) winning for their paths.
- Fix: disable proxy_buffering + proxy_request_buffering for the
  frontend `location /` block. Without it, nginx tries to spool large
  Next.js chunks into /var/lib/nginx/proxy (root-owned) and fails with
  Permission denied → ERR_INCOMPLETE_CHUNKED_ENCODING → ChunkLoadError.

* test(auth): release-validation test infra and new coverage

Test fixtures and unit tests added during the validation pass.

Router test helpers (NEW: tests/_router_auth_helpers.py)
- make_authed_test_app(): builds a FastAPI test app with a stub
  middleware that stamps request.state.user + request.state.auth and a
  permissive thread_meta_repo mock. TestClient-based router tests
  (test_artifacts_router, test_threads_router) use it instead of bare
  FastAPI() so the new @require_permission(owner_check=True) decorators
  short-circuit cleanly.
- call_unwrapped(): walks the __wrapped__ chain to invoke the underlying
  handler without going through the authz wrappers. Direct-call tests
  (test_uploads_router) use it. Typed with ParamSpec so the wrapped
  signature flows through.

Backend test additions
- test_auth.py: 7 tests for the new _get_client_ip trust model (no
  proxy / trusted proxy / untrusted peer / XFF rejection / invalid
  CIDR / no client). 5 tests for the password blocklist (literal,
  case-insensitive, strong password accepted, change-password binding,
  short-password length-check still fires before blocklist).
  test_update_user_raises_when_row_concurrently_deleted: closes a
  shipped-without-coverage gap on the new UserNotFoundError contract.
- test_thread_meta_repo.py: 4 tests for check_access(require_existing=True)
  — strict missing-row denial, strict owner match, strict owner mismatch,
  strict null-owner still allowed (shared rows survive the tightening).
- test_ensure_admin.py: 3 tests for _migrate_orphaned_threads /
  _iter_store_items pagination, covering the TC-UPG-02 upgrade story
  end-to-end via mock store. Closes the gap where the cursor pagination
  was untested even though the previous PR rewrote it.
- test_threads_router.py: 5 tests for _strip_reserved_metadata
  (owner_id removal, user_id removal, safe-keys passthrough, empty
  input, both-stripped).
- test_auth_type_system.py: replace "password123" fixtures with
  Tr0ub4dor3a / AnotherStr0ngPwd! so the new password blocklist
  doesn't reject the test data.

* docs(auth): refresh TC-DOCKER-05 + document Docker validation gap

- AUTH_TEST_PLAN.md TC-DOCKER-05: the previous expectation
  ("admin password visible in docker logs") was stale after the simplify
  pass that moved credentials to a 0600 file. The grep "Password:" check
  would have silently failed and given a false sense of coverage. New
  expectation matches the actual file-based path: 0600 file in
  DEER_FLOW_HOME, log shows the path (not the secret), reverse-grep
  asserts no leaked password in container logs.
- NEW: docs/AUTH_TEST_DOCKER_GAP.md documents the only un-executed
  block in the test plan (TC-DOCKER-01..06). Reason: sg_dev validation
  host has no Docker daemon installed. The doc maps each Docker case
  to an already-validated bare-metal equivalent (TC-1.1, TC-REENT-01,
  TC-API-02 etc.) so the gap is auditable, and includes pre-flight
  reproduction steps for whoever has Docker available.

---------

Co-authored-by: greatmengqi <chenmengqi.0376@bytedance.com>

.agent/skills/smoke-test/SKILL.md

@@ -0,0 +1,181 @@
+---
+name: smoke-test
+description: End-to-end smoke test skill for DeerFlow. Guides through: 1) Pulling latest code, 2) Docker OR Local installation and deployment (user preference, default to Local if Docker network issues), 3) Service availability verification, 4) Health check, 5) Final test report. Use when the user says "run smoke test", "smoke test deployment", "verify installation", "test service availability", "end-to-end test", or similar.
+---
+
+# DeerFlow Smoke Test Skill
+
+This skill guides the Agent through DeerFlow's full end-to-end smoke test workflow, including code updates, deployment (supporting both Docker and local installation modes), service availability verification, and health checks.
+
+## Deployment Mode Selection
+
+This skill supports two deployment modes:
+- **Local installation mode** (recommended, especially when network issues occur) - Run all services directly on the local machine
+- **Docker mode** - Run all services inside Docker containers
+
+**Selection strategy**:
+- If the user explicitly asks for Docker mode, use Docker
+- If network issues occur (such as slow image pulls), automatically switch to local mode
+- Default to local mode whenever possible
+
+## Structure
+
+```
+smoke-test/
+├── SKILL.md                          ← You are here - core workflow and logic
+├── scripts/
+│   ├── check_docker.sh               ← Check the Docker environment
+│   ├── check_local_env.sh            ← Check local environment dependencies
+│   ├── frontend_check.sh             ← Frontend page smoke check
+│   ├── pull_code.sh                  ← Pull the latest code
+│   ├── deploy_docker.sh              ← Docker deployment
+│   ├── deploy_local.sh               ← Local deployment
+│   └── health_check.sh               ← Service health check
+├── references/
+│   ├── SOP.md                        ← Standard operating procedure
+│   └── troubleshooting.md            ← Troubleshooting guide
+└── templates/
+    ├── report.local.template.md      ← Local mode smoke test report template
+    └── report.docker.template.md     ← Docker mode smoke test report template
+```
+
+## Standard Operating Procedure (SOP)
+
+### Phase 1: Code Update Check
+
+1. **Confirm current directory** - Verify that the current working directory is the DeerFlow project root
+2. **Check Git status** - See whether there are uncommitted changes
+3. **Pull the latest code** - Use `git pull origin main` to get the latest updates
+4. **Confirm code update** - Verify that the latest code was pulled successfully
+
+### Phase 2: Deployment Mode Selection and Environment Check
+
+**Choose deployment mode**:
+- Ask for user preference, or choose automatically based on network conditions
+- Default to local installation mode
+
+**Local mode environment check**:
+1. **Check Node.js version** - Requires 22+
+2. **Check pnpm** - Package manager
+3. **Check uv** - Python package manager
+4. **Check nginx** - Reverse proxy
+5. **Check required ports** - Confirm that ports 2026, 3000, 8001, and 2024 are not occupied
+
+**Docker mode environment check** (if Docker is selected):
+1. **Check whether Docker is installed** - Run `docker --version`
+2. **Check Docker daemon status** - Run `docker info`
+3. **Check Docker Compose availability** - Run `docker compose version`
+4. **Check required ports** - Confirm that port 2026 is not occupied
+
+### Phase 3: Configuration Preparation
+
+1. **Check whether config.yaml exists**
+   - If it does not exist, run `make config` to generate it
+   - If it already exists, check whether it needs an upgrade with `make config-upgrade`
+2. **Check the .env file**
+   - Verify that required environment variables are configured
+   - Especially model API keys such as `OPENAI_API_KEY`
+
+### Phase 4: Deployment Execution
+
+**Local mode deployment**:
+1. **Check dependencies** - Run `make check`
+2. **Install dependencies** - Run `make install`
+3. **(Optional) Pre-pull the sandbox image** - If needed, run `make setup-sandbox`
+4. **Start services** - Run `make dev-daemon` (background mode, recommended) or `make dev` (foreground mode)
+5. **Wait for startup** - Give all services enough time to start completely (90-120 seconds recommended)
+
+**Docker mode deployment** (if Docker is selected):
+1. **Initialize Docker environment** - Run `make docker-init`
+2. **Start Docker services** - Run `make docker-start`
+3. **Wait for startup** - Give all containers enough time to start completely (60 seconds recommended)
+
+### Phase 5: Service Health Check
+
+**Local mode health check**:
+1. **Check process status** - Confirm that LangGraph, Gateway, Frontend, and Nginx processes are all running
+2. **Check frontend service** - Visit `http://localhost:2026` and verify that the page loads
+3. **Check API Gateway** - Verify the `http://localhost:2026/health` endpoint
+4. **Check LangGraph service** - Verify the availability of relevant endpoints
+5. **Frontend route smoke check** - Run `bash .agent/skills/smoke-test/scripts/frontend_check.sh` to verify key routes under `/workspace`
+
+**Docker mode health check** (when using Docker):
+1. **Check container status** - Run `docker ps` and confirm that all containers are running
+2. **Check frontend service** - Visit `http://localhost:2026` and verify that the page loads
+3. **Check API Gateway** - Verify the `http://localhost:2026/health` endpoint
+4. **Check LangGraph service** - Verify the availability of relevant endpoints
+5. **Frontend route smoke check** - Run `bash .agent/skills/smoke-test/scripts/frontend_check.sh` to verify key routes under `/workspace`
+
+### Optional Functional Verification
+
+1. **List available models** - Verify that model configuration loads correctly
+2. **List available skills** - Verify that the skill directory is mounted correctly
+3. **Simple chat test** - Send a simple message to verify the end-to-end flow
+
+### Phase 6: Generate Test Report
+
+1. **Collect all test results** - Summarize execution status for each phase
+2. **Record encountered issues** - If anything fails, record the error details
+3. **Generate the final report** - Use the template that matches the selected deployment mode to create the complete test report, including overall conclusion, detailed key test cases, and explicit frontend page / route results
+4. **Provide follow-up recommendations** - Offer suggestions based on the test results
+
+## Execution Rules
+
+- **Follow the sequence** - Execute strictly in the order described above
+- **Idempotency** - Every step should be safe to repeat
+- **Error handling** - If a step fails, stop and report the issue, then provide troubleshooting suggestions
+- **Detailed logging** - Record the execution result and status of each step
+- **User confirmation** - Ask for confirmation before potentially risky operations such as overwriting config
+- **Mode preference** - Prefer local mode to avoid network-related issues
+- **Template requirement** - The final report must use the matching template under `templates/`; do not output a free-form summary instead of the template-based report
+- **Report clarity** - The execution summary must include the overall pass/fail conclusion plus per-case result explanations, and frontend smoke check results must be listed explicitly in the report
+- **Optional phase handling** - If functional verification is not executed, do not present it as a separate skipped phase in the final report
+
+## Known Acceptable Warnings
+
+The following warnings can appear during smoke testing and do not block a successful result:
+- Feishu/Lark SSL errors in Gateway logs (certificate verification failure) can be ignored if that channel is not enabled
+- Warnings in LangGraph logs about missing methods in the custom checkpointer, such as `adelete_for_runs` or `aprune`, do not affect the core functionality
+
+## Key Tools
+
+Use the following tools during execution:
+
+1. **bash** - Run shell commands
+2. **present_file** - Show generated reports and important files
+3. **task_tool** - Organize complex steps with subtasks when needed
+
+## Success Criteria
+
+Smoke test pass criteria (local mode):
+- [x] Latest code is pulled successfully
+- [x] Local environment check passes (Node.js 22+, pnpm, uv, nginx)
+- [x] Configuration files are set up correctly
+- [x] `make check` passes
+- [x] `make install` completes successfully
+- [x] `make dev` starts successfully
+- [x] All service processes run normally
+- [x] Frontend page is accessible
+- [x] Frontend route smoke check passes (`/workspace` key routes)
+- [x] API Gateway health check passes
+- [x] Test report is generated completely
+
+Smoke test pass criteria (Docker mode):
+- [x] Latest code is pulled successfully
+- [x] Docker environment check passes
+- [x] Configuration files are set up correctly
+- [x] `make docker-init` completes successfully
+- [x] `make docker-start` completes successfully
+- [x] All Docker containers run normally
+- [x] Frontend page is accessible
+- [x] Frontend route smoke check passes (`/workspace` key routes)
+- [x] API Gateway health check passes
+- [x] Test report is generated completely
+
+## Read Reference Files
+
+Before starting execution, read the following reference files:
+1. `references/SOP.md` - Detailed step-by-step operating instructions
+2. `references/troubleshooting.md` - Common issues and solutions
+3. `templates/report.local.template.md` - Local mode test report template
+4. `templates/report.docker.template.md` - Docker mode test report template

.agent/skills/smoke-test/references/SOP.md

@@ -0,0 +1,452 @@
+# DeerFlow Smoke Test Standard Operating Procedure (SOP)
+
+This document describes the detailed operating steps for each phase of the DeerFlow smoke test.
+
+## Phase 1: Code Update Check
+
+### 1.1 Confirm Current Directory
+
+**Objective**: Verify that the current working directory is the DeerFlow project root.
+
+**Steps**:
+1. Run `pwd` to view the current working directory
+2. Check whether the directory contains the following files/directories:
+   - `Makefile`
+   - `backend/`
+   - `frontend/`
+   - `config.example.yaml`
+
+**Success Criteria**: The current directory contains all of the files/directories listed above.
+
+---
+
+### 1.2 Check Git Status
+
+**Objective**: Check whether there are uncommitted changes.
+
+**Steps**:
+1. Run `git status`
+2. Check whether the output includes "Changes not staged for commit" or "Untracked files"
+
+**Notes**:
+- If there are uncommitted changes, recommend that the user commit or stash them first to avoid conflicts while pulling
+- If the user confirms that they want to continue, this step can be skipped
+
+---
+
+### 1.3 Pull the Latest Code
+
+**Objective**: Fetch the latest code updates.
+
+**Steps**:
+1. Run `git fetch origin main`
+2. Run `git pull origin main`
+
+**Success Criteria**:
+- The commands succeed without errors
+- The output shows "Already up to date" or indicates that new commits were pulled successfully
+
+---
+
+### 1.4 Confirm Code Update
+
+**Objective**: Verify that the latest code was pulled successfully.
+
+**Steps**:
+1. Run `git log -1 --oneline` to view the latest commit
+2. Record the commit hash and message
+
+---
+
+## Phase 2: Deployment Mode Selection and Environment Check
+
+### 2.1 Choose Deployment Mode
+
+**Objective**: Decide whether to use local mode or Docker mode.
+
+**Decision Flow**:
+1. Prefer local mode first to avoid network-related issues
+2. If the user explicitly requests Docker, use Docker
+3. If Docker network issues occur, switch to local mode automatically
+
+---
+
+### 2.2 Local Mode Environment Check
+
+**Objective**: Verify that local development environment dependencies are satisfied.
+
+#### 2.2.1 Check Node.js Version
+
+**Steps**:
+1. If nvm is used, run `nvm use 22` to switch to Node 22+
+2. Run `node --version`
+
+**Success Criteria**: Version >= 22.x
+
+**Failure Handling**:
+- If the version is too low, ask the user to install/switch Node.js with nvm:
+  ```bash
+  nvm install 22
+  nvm use 22
+  ```
+- Or install it from the official website: https://nodejs.org/
+
+---
+
+#### 2.2.2 Check pnpm
+
+**Steps**:
+1. Run `pnpm --version`
+
+**Success Criteria**: The command returns pnpm version information.
+
+**Failure Handling**:
+- If pnpm is not installed, ask the user to install it with `npm install -g pnpm`
+
+---
+
+#### 2.2.3 Check uv
+
+**Steps**:
+1. Run `uv --version`
+
+**Success Criteria**: The command returns uv version information.
+
+**Failure Handling**:
+- If uv is not installed, ask the user to install uv
+
+---
+
+#### 2.2.4 Check nginx
+
+**Steps**:
+1. Run `nginx -v`
+
+**Success Criteria**: The command returns nginx version information.
+
+**Failure Handling**:
+- macOS: install with Homebrew using `brew install nginx`
+- Linux: install using the system package manager
+
+---
+
+#### 2.2.5 Check Required Ports
+
+**Steps**:
+1. Run the following commands to check ports:
+   ```bash
+   lsof -i :2026  # Main port
+   lsof -i :3000  # Frontend
+   lsof -i :8001  # Gateway
+   lsof -i :2024  # LangGraph
+   ```
+
+**Success Criteria**: All ports are free, or they are occupied only by DeerFlow-related processes.
+
+**Failure Handling**:
+- If a port is occupied, ask the user to stop the related process
+
+---
+
+### 2.3 Docker Mode Environment Check (If Docker Is Selected)
+
+#### 2.3.1 Check Whether Docker Is Installed
+
+**Steps**:
+1. Run `docker --version`
+
+**Success Criteria**: The command returns Docker version information, such as "Docker version 24.x.x".
+
+---
+
+#### 2.3.2 Check Docker Daemon Status
+
+**Steps**:
+1. Run `docker info`
+
+**Success Criteria**: The command runs successfully and shows Docker system information.
+
+**Failure Handling**:
+- If it fails, ask the user to start Docker Desktop or the Docker service
+
+---
+
+#### 2.3.3 Check Docker Compose Availability
+
+**Steps**:
+1. Run `docker compose version`
+
+**Success Criteria**: The command returns Docker Compose version information.
+
+---
+
+#### 2.3.4 Check Required Ports
+
+**Steps**:
+1. Run `lsof -i :2026` (macOS/Linux) or `netstat -ano | findstr :2026` (Windows)
+
+**Success Criteria**: Port 2026 is free, or it is occupied only by a DeerFlow-related process.
+
+**Failure Handling**:
+- If the port is occupied by another process, ask the user to stop that process or change the configuration
+
+---
+
+## Phase 3: Configuration Preparation
+
+### 3.1 Check config.yaml
+
+**Steps**:
+1. Check whether `config.yaml` exists
+2. If it does not exist, run `make config`
+3. If it already exists, consider running `make config-upgrade` to merge new fields
+
+**Validation**:
+- Check whether at least one model is configured in config.yaml
+- Check whether the model configuration references the correct environment variables
+
+---
+
+### 3.2 Check the .env File
+
+**Steps**:
+1. Check whether the `.env` file exists
+2. If it does not exist, copy it from `.env.example`
+3. Check whether the following environment variables are configured:
+   - `OPENAI_API_KEY` (or other model API keys)
+   - Other required settings
+
+---
+
+## Phase 4: Deployment Execution
+
+### 4.1 Local Mode Deployment
+
+#### 4.1.1 Check Dependencies
+
+**Steps**:
+1. Run `make check`
+
+**Description**: This command validates all required tools (Node.js 22+, pnpm, uv, nginx).
+
+---
+
+#### 4.1.2 Install Dependencies
+
+**Steps**:
+1. Run `make install`
+
+**Description**: This command installs both backend and frontend dependencies.
+
+**Notes**:
+- This step may take some time
+- If network issues cause failures, try using a closer or mirrored package registry
+
+---
+
+#### 4.1.3 (Optional) Pre-pull the Sandbox Image
+
+**Steps**:
+1. If Docker / Container sandbox is used, run `make setup-sandbox`
+
+**Description**: This step is optional and not needed for local sandbox mode.
+
+---
+
+#### 4.1.4 Start Services
+
+**Steps**:
+1. Run `make dev-daemon` (background mode)
+
+**Description**: This command starts all services (LangGraph, Gateway, Frontend, Nginx).
+
+**Notes**:
+- `make dev` runs in the foreground and stops with Ctrl+C
+- `make dev-daemon` runs in the background
+- Use `make stop` to stop services
+
+---
+
+#### 4.1.5 Wait for Services to Start
+
+**Steps**:
+1. Wait 90-120 seconds for all services to start completely
+2. You can monitor startup progress by checking these log files:
+   - `logs/langgraph.log`
+   - `logs/gateway.log`
+   - `logs/frontend.log`
+   - `logs/nginx.log`
+
+---
+
+### 4.2 Docker Mode Deployment (If Docker Is Selected)
+
+#### 4.2.1 Initialize the Docker Environment
+
+**Steps**:
+1. Run `make docker-init`
+
+**Description**: This command pulls the sandbox image if needed.
+
+---
+
+#### 4.2.2 Start Docker Services
+
+**Steps**:
+1. Run `make docker-start`
+
+**Description**: This command builds and starts all required Docker containers.
+
+---
+
+#### 4.2.3 Wait for Services to Start
+
+**Steps**:
+1. Wait 60-90 seconds for all services to start completely
+2. You can run `make docker-logs` to monitor startup progress
+
+---
+
+## Phase 5: Service Health Check
+
+### 5.1 Local Mode Health Check
+
+#### 5.1.1 Check Process Status
+
+**Steps**:
+1. Run the following command to check processes:
+   ```bash
+   ps aux | grep -E "(langgraph|uvicorn|next|nginx)" | grep -v grep
+   ```
+
+**Success Criteria**: Confirm that the following processes are running:
+- LangGraph (`langgraph dev`)
+- Gateway (`uvicorn app.gateway.app:app`)
+- Frontend (`next dev` or `next start`)
+- Nginx (`nginx`)
+
+---
+
+#### 5.1.2 Check Frontend Service
+
+**Steps**:
+1. Use curl or a browser to visit `http://localhost:2026`
+2. Verify that the page loads normally
+
+**Example curl command**:
+```bash
+curl -I http://localhost:2026
+```
+
+**Success Criteria**: Returns an HTTP 200 status code.
+
+---
+
+#### 5.1.3 Check API Gateway
+
+**Steps**:
+1. Visit `http://localhost:2026/health`
+
+**Example curl command**:
+```bash
+curl http://localhost:2026/health
+```
+
+**Success Criteria**: Returns health status JSON.
+
+---
+
+#### 5.1.4 Check LangGraph Service
+
+**Steps**:
+1. Visit relevant LangGraph endpoints to verify availability
+
+---
+
+### 5.2 Docker Mode Health Check (When Using Docker)
+
+#### 5.2.1 Check Container Status
+
+**Steps**:
+1. Run `docker ps`
+2. Confirm that the following containers are running:
+   - `deer-flow-nginx`
+   - `deer-flow-frontend`
+   - `deer-flow-gateway`
+   - `deer-flow-langgraph` (if not in gateway mode)
+
+---
+
+#### 5.2.2 Check Frontend Service
+
+**Steps**:
+1. Use curl or a browser to visit `http://localhost:2026`
+2. Verify that the page loads normally
+
+**Example curl command**:
+```bash
+curl -I http://localhost:2026
+```
+
+**Success Criteria**: Returns an HTTP 200 status code.
+
+---
+
+#### 5.2.3 Check API Gateway
+
+**Steps**:
+1. Visit `http://localhost:2026/health`
+
+**Example curl command**:
+```bash
+curl http://localhost:2026/health
+```
+
+**Success Criteria**: Returns health status JSON.
+
+---
+
+#### 5.2.4 Check LangGraph Service
+
+**Steps**:
+1. Visit relevant LangGraph endpoints to verify availability
+
+---
+
+## Optional Functional Verification
+
+### 6.1 List Available Models
+
+**Steps**: Verify the model list through the API or UI.
+
+---
+
+### 6.2 List Available Skills
+
+**Steps**: Verify the skill list through the API or UI.
+
+---
+
+### 6.3 Simple Chat Test
+
+**Steps**: Send a simple message to test the complete workflow.
+
+---
+
+## Phase 6: Generate the Test Report
+
+### 6.1 Collect Test Results
+
+Summarize the execution status of each phase and record successful and failed items.
+
+### 6.2 Record Issues
+
+If anything fails, record detailed error information.
+
+### 6.3 Generate the Report
+
+Use the template to create a complete test report.
+
+### 6.4 Provide Recommendations
+
+Provide follow-up recommendations based on the test results.

.agent/skills/smoke-test/references/troubleshooting.md

@@ -0,0 +1,612 @@
+# Troubleshooting Guide
+
+This document lists common issues encountered during DeerFlow smoke testing and how to resolve them.
+
+## Code Update Issues
+
+### Issue: `git pull` Fails with a Merge Conflict Warning
+
+**Symptoms**:
+```
+error: Your local changes to the following files would be overwritten by merge
+```
+
+**Solutions**:
+1. Option A: Commit local changes first
+   ```bash
+   git add .
+   git commit -m "Save local changes"
+   git pull origin main
+   ```
+
+2. Option B: Stash local changes
+   ```bash
+   git stash
+   git pull origin main
+   git stash pop  # Restore changes later if needed
+   ```
+
+3. Option C: Discard local changes (use with caution)
+   ```bash
+   git reset --hard HEAD
+   git pull origin main
+   ```
+
+---
+
+## Local Mode Environment Issues
+
+### Issue: Node.js Version Is Too Old
+
+**Symptoms**:
+```
+Node.js version is too old. Requires 22+, got x.x.x
+```
+
+**Solutions**:
+1. Install or upgrade Node.js with nvm:
+   ```bash
+   nvm install 22
+   nvm use 22
+   ```
+
+2. Or download and install it from the official website: https://nodejs.org/
+
+3. Verify the version:
+   ```bash
+   node --version
+   ```
+
+---
+
+### Issue: pnpm Is Not Installed
+
+**Symptoms**:
+```
+command not found: pnpm
+```
+
+**Solutions**:
+1. Install pnpm with npm:
+   ```bash
+   npm install -g pnpm
+   ```
+
+2. Or use the official installation script:
+   ```bash
+   curl -fsSL https://get.pnpm.io/install.sh | sh -
+   ```
+
+3. Verify the installation:
+   ```bash
+   pnpm --version
+   ```
+
+---
+
+### Issue: uv Is Not Installed
+
+**Symptoms**:
+```
+command not found: uv
+```
+
+**Solutions**:
+1. Use the official installation script:
+   ```bash
+   curl -LsSf https://astral.sh/uv/install.sh | sh
+   ```
+
+2. macOS users can also install it with Homebrew:
+   ```bash
+   brew install uv
+   ```
+
+3. Verify the installation:
+   ```bash
+   uv --version
+   ```
+
+---
+
+### Issue: nginx Is Not Installed
+
+**Symptoms**:
+```
+command not found: nginx
+```
+
+**Solutions**:
+1. macOS (Homebrew):
+   ```bash
+   brew install nginx
+   ```
+
+2. Ubuntu/Debian:
+   ```bash
+   sudo apt update
+   sudo apt install nginx
+   ```
+
+3. CentOS/RHEL:
+   ```bash
+   sudo yum install nginx
+   ```
+
+4. Verify the installation:
+   ```bash
+   nginx -v
+   ```
+
+---
+
+### Issue: Port Is Already in Use
+
+**Symptoms**:
+```
+Error: listen EADDRINUSE: address already in use :::2026
+```
+
+**Solutions**:
+1. Find the process using the port:
+   ```bash
+   lsof -i :2026  # macOS/Linux
+   netstat -ano | findstr :2026  # Windows
+   ```
+
+2. Stop that process:
+   ```bash
+   kill -9 <PID>  # macOS/Linux
+   taskkill /PID <PID> /F  # Windows
+   ```
+
+3. Or stop DeerFlow services first:
+   ```bash
+   make stop
+   ```
+
+---
+
+## Local Mode Dependency Installation Issues
+
+### Issue: `make install` Fails Due to Network Timeout
+
+**Symptoms**:
+Network timeouts or connection failures occur during dependency installation.
+
+**Solutions**:
+1. Configure pnpm to use a mirror registry:
+   ```bash
+   pnpm config set registry https://registry.npmmirror.com
+   ```
+
+2. Configure uv to use a mirror registry:
+   ```bash
+   uv pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple
+   ```
+
+3. Retry the installation:
+   ```bash
+   make install
+   ```
+
+---
+
+### Issue: Python Dependency Installation Fails
+
+**Symptoms**:
+Errors occur during `uv sync`.
+
+**Solutions**:
+1. Clean the uv cache:
+   ```bash
+   cd backend
+   uv cache clean
+   ```
+
+2. Resync dependencies:
+   ```bash
+   cd backend
+   uv sync
+   ```
+
+3. View detailed error logs:
+   ```bash
+   cd backend
+   uv sync --verbose
+   ```
+
+---
+
+### Issue: Frontend Dependency Installation Fails
+
+**Symptoms**:
+Errors occur during `pnpm install`.
+
+**Solutions**:
+1. Clean the pnpm cache:
+   ```bash
+   cd frontend
+   pnpm store prune
+   ```
+
+2. Remove node_modules and the lock file:
+   ```bash
+   cd frontend
+   rm -rf node_modules pnpm-lock.yaml
+   ```
+
+3. Reinstall:
+   ```bash
+   cd frontend
+   pnpm install
+   ```
+
+---
+
+## Local Mode Service Startup Issues
+
+### Issue: Services Exit Immediately After Startup
+
+**Symptoms**:
+Processes exit quickly after running `make dev-daemon`.
+
+**Solutions**:
+1. Check log files:
+   ```bash
+   tail -f logs/langgraph.log
+   tail -f logs/gateway.log
+   tail -f logs/frontend.log
+   tail -f logs/nginx.log
+   ```
+
+2. Check whether config.yaml is configured correctly
+3. Check environment variables in the .env file
+4. Confirm that required ports are not occupied
+5. Stop all services and restart:
+   ```bash
+   make stop
+   make dev-daemon
+   ```
+
+---
+
+### Issue: Nginx Fails to Start Because Temp Directories Do Not Exist
+
+**Symptoms**:
+```
+nginx: [emerg] mkdir() "/opt/homebrew/var/run/nginx/client_body_temp" failed (2: No such file or directory)
+```
+
+**Solutions**:
+Add local temp directory configuration to `docker/nginx/nginx.local.conf` so nginx uses the repository's temp directory.
+
+Add the following at the beginning of the `http` block:
+```nginx
+client_body_temp_path temp/client_body_temp;
+proxy_temp_path temp/proxy_temp;
+fastcgi_temp_path temp/fastcgi_temp;
+uwsgi_temp_path temp/uwsgi_temp;
+scgi_temp_path temp/scgi_temp;
+```
+
+Note: The `temp/` directory under the repository root is created automatically by `make dev` or `make dev-daemon`.
+
+---
+
+### Issue: Nginx Fails to Start (General)
+
+**Symptoms**:
+The nginx process fails to start or reports an error.
+
+**Solutions**:
+1. Check the nginx configuration:
+   ```bash
+   nginx -t -c docker/nginx/nginx.local.conf -p .
+   ```
+
+2. Check nginx logs:
+   ```bash
+   tail -f logs/nginx.log
+   ```
+
+3. Ensure no other nginx process is running:
+   ```bash
+   ps aux | grep nginx
+   ```
+
+4. If needed, stop existing nginx processes:
+   ```bash
+   pkill -9 nginx
+   ```
+
+---
+
+### Issue: Frontend Compilation Fails
+
+**Symptoms**:
+Compilation errors appear in `frontend.log`.
+
+**Solutions**:
+1. Check frontend logs:
+   ```bash
+   tail -f logs/frontend.log
+   ```
+
+2. Check whether Node.js version is 22+
+3. Reinstall frontend dependencies:
+   ```bash
+   cd frontend
+   rm -rf node_modules .next
+   pnpm install
+   ```
+
+4. Restart services:
+   ```bash
+   make stop
+   make dev-daemon
+   ```
+
+---
+
+### Issue: Gateway Fails to Start
+
+**Symptoms**:
+Errors appear in `gateway.log`.
+
+**Solutions**:
+1. Check gateway logs:
+   ```bash
+   tail -f logs/gateway.log
+   ```
+
+2. Check whether config.yaml exists and has valid formatting
+3. Check whether Python dependencies are complete:
+   ```bash
+   cd backend
+   uv sync
+   ```
+
+4. Confirm that the LangGraph service is running normally (if not in gateway mode)
+
+---
+
+### Issue: LangGraph Fails to Start
+
+**Symptoms**:
+Errors appear in `langgraph.log`.
+
+**Solutions**:
+1. Check LangGraph logs:
+   ```bash
+   tail -f logs/langgraph.log
+   ```
+
+2. Check config.yaml
+3. Check whether Python dependencies are complete
+4. Confirm that port 2024 is not occupied
+
+---
+
+## Docker-Related Issues
+
+### Issue: Docker Commands Cannot Run
+
+**Symptoms**:
+```
+Cannot connect to the Docker daemon
+```
+
+**Solutions**:
+1. Confirm that Docker Desktop is running
+2. macOS: check whether the Docker icon appears in the top menu bar
+3. Linux: run `sudo systemctl start docker`
+4. Run `docker info` again to verify
+
+---
+
+### Issue: `make docker-init` Fails to Pull the Image
+
+**Symptoms**:
+```
+Error pulling image: connection refused
+```
+
+**Solutions**:
+1. Check network connectivity
+2. Configure a Docker image mirror if needed
+3. Check whether a proxy is required
+4. Switch to local installation mode if necessary (recommended)
+
+---
+
+## Configuration File Issues
+
+### Issue: config.yaml Is Missing or Invalid
+
+**Symptoms**:
+```
+Error: could not read config.yaml
+```
+
+**Solutions**:
+1. Regenerate the configuration file:
+   ```bash
+   make config
+   ```
+
+2. Check YAML syntax:
+   - Make sure indentation is correct (use 2 spaces)
+   - Make sure there are no tab characters
+   - Check that there is a space after each colon
+
+3. Use a YAML validation tool to check the format
+
+---
+
+### Issue: Model API Key Is Not Configured
+
+**Symptoms**:
+After services start, API requests fail with authentication errors.
+
+**Solutions**:
+1. Edit the .env file and add the API key:
+   ```bash
+   OPENAI_API_KEY=your-actual-api-key-here
+   ```
+
+2. Restart services (local mode):
+   ```bash
+   make stop
+   make dev-daemon
+   ```
+
+3. Restart services (Docker mode):
+   ```bash
+   make docker-stop
+   make docker-start
+   ```
+
+4. Confirm that the model configuration in config.yaml references the environment variable correctly
+
+---
+
+## Service Health Check Issues
+
+### Issue: Frontend Page Is Not Accessible
+
+**Symptoms**:
+The browser shows a connection failure when visiting http://localhost:2026.
+
+**Solutions** (local mode):
+1. Confirm that the nginx process is running:
+   ```bash
+   ps aux | grep nginx
+   ```
+
+2. Check nginx logs:
+   ```bash
+   tail -f logs/nginx.log
+   ```
+
+3. Check firewall settings
+
+**Solutions** (Docker mode):
+1. Confirm that the nginx container is running:
+   ```bash
+   docker ps | grep nginx
+   ```
+
+2. Check nginx logs:
+   ```bash
+   cd docker && docker compose -p deer-flow-dev -f docker-compose-dev.yaml logs nginx
+   ```
+
+3. Check firewall settings
+
+---
+
+### Issue: API Gateway Health Check Fails
+
+**Symptoms**:
+Accessing `/health` returns an error or times out.
+
+**Solutions** (local mode):
+1. Check gateway logs:
+   ```bash
+   tail -f logs/gateway.log
+   ```
+
+2. Confirm that config.yaml exists and has valid formatting
+3. Check whether Python dependencies are complete
+4. Confirm that the LangGraph service is running normally
+
+**Solutions** (Docker mode):
+1. Check gateway container logs:
+   ```bash
+   make docker-logs-gateway
+   ```
+
+2. Confirm that config.yaml is mounted correctly
+3. Check whether Python dependencies are complete
+4. Confirm that the LangGraph service is running normally
+
+---
+
+## Common Diagnostic Commands
+
+### Local Mode Diagnostics
+
+#### View All Service Processes
+```bash
+ps aux | grep -E "(langgraph|uvicorn|next|nginx)" | grep -v grep
+```
+
+#### View Service Logs
+```bash
+# View all logs
+tail -f logs/*.log
+
+# View specific service logs
+tail -f logs/langgraph.log
+tail -f logs/gateway.log
+tail -f logs/frontend.log
+tail -f logs/nginx.log
+```
+
+#### Stop All Services
+```bash
+make stop
+```
+
+#### Fully Reset the Local Environment
+```bash
+make stop
+make clean
+make config
+make install
+make dev-daemon
+```
+
+---
+
+### Docker Mode Diagnostics
+
+#### View All Container Status
+```bash
+docker ps -a
+```
+
+#### View Container Resource Usage
+```bash
+docker stats
+```
+
+#### Enter a Container for Debugging
+```bash
+docker exec -it deer-flow-gateway sh
+```
+
+#### Clean Up All DeerFlow-Related Containers and Images
+```bash
+make docker-stop
+cd docker && docker compose -p deer-flow-dev -f docker-compose-dev.yaml down -v
+```
+
+#### Fully Reset the Docker Environment
+```bash
+make docker-stop
+make clean
+make config
+make docker-init
+make docker-start
+```
+
+---
+
+## Get More Help
+
+If the solutions above do not resolve the issue:
+1. Check the GitHub issues for the project: https://github.com/bytedance/deer-flow/issues
+2. Review the project documentation: README.md and the `backend/docs/` directory
+3. Open a new issue and include detailed error logs

.agent/skills/smoke-test/scripts/check_docker.sh

@@ -0,0 +1,80 @@
+#!/usr/bin/env bash
+set -e
+
+echo "=========================================="
+echo "  Checking Docker Environment"
+echo "=========================================="
+echo ""
+
+# Check whether Docker is installed
+if command -v docker >/dev/null 2>&1; then
+    echo "✓ Docker is installed"
+    docker --version
+else
+    echo "✗ Docker is not installed"
+    exit 1
+fi
+echo ""
+
+# Check the Docker daemon
+if docker info >/dev/null 2>&1; then
+    echo "✓ Docker daemon is running normally"
+else
+    echo "✗ Docker daemon is not running"
+    echo "  Please start Docker Desktop or the Docker service"
+    exit 1
+fi
+echo ""
+
+# Check Docker Compose
+if docker compose version >/dev/null 2>&1; then
+    echo "✓ Docker Compose is available"
+    docker compose version
+else
+    echo "✗ Docker Compose is not available"
+    exit 1
+fi
+echo ""
+
+# Check port 2026
+if ! command -v lsof >/dev/null 2>&1; then
+    echo "✗ lsof is required to check whether port 2026 is available"
+    exit 1
+fi
+
+port_2026_usage="$(lsof -nP -iTCP:2026 -sTCP:LISTEN 2>/dev/null || true)"
+if [ -n "$port_2026_usage" ]; then
+    echo "⚠  Port 2026 is already in use"
+    echo "  Occupying process:"
+    echo "$port_2026_usage"
+
+    deerflow_process_found=0
+    while IFS= read -r pid; do
+        if [ -z "$pid" ]; then
+            continue
+        fi
+
+        process_command="$(ps -p "$pid" -o command= 2>/dev/null || true)"
+        case "$process_command" in
+            *[Dd]eer[Ff]low*|*[Dd]eerflow*|*[Nn]ginx*deerflow*|*deerflow/*[Nn]ginx*)
+                deerflow_process_found=1
+                ;;
+        esac
+    done <<EOF
+$(printf '%s\n' "$port_2026_usage" | awk 'NR > 1 {print $2}')
+EOF
+
+    if [ "$deerflow_process_found" -eq 1 ]; then
+        echo "✓ Port 2026 is occupied by DeerFlow"
+    else
+        echo "✗ Port 2026 must be free before starting DeerFlow"
+        exit 1
+    fi
+else
+    echo "✓ Port 2026 is available"
+fi
+echo ""
+
+echo "=========================================="
+echo "  Docker Environment Check Complete"
+echo "=========================================="

.agent/skills/smoke-test/scripts/check_local_env.sh

@@ -0,0 +1,93 @@
+#!/usr/bin/env bash
+set -e
+
+echo "=========================================="
+echo "  Checking Local Development Environment"
+echo "=========================================="
+echo ""
+
+all_passed=true
+
+# Check Node.js
+echo "1. Checking Node.js..."
+if command -v node >/dev/null 2>&1; then
+    NODE_VERSION=$(node --version | sed 's/v//')
+    NODE_MAJOR=$(echo "$NODE_VERSION" | cut -d. -f1)
+    if [ "$NODE_MAJOR" -ge 22 ]; then
+        echo "✓ Node.js is installed (version: $NODE_VERSION)"
+    else
+        echo "✗ Node.js version is too old (current: $NODE_VERSION, required: 22+)"
+        all_passed=false
+    fi
+else
+    echo "✗ Node.js is not installed"
+    all_passed=false
+fi
+echo ""
+
+# Check pnpm
+echo "2. Checking pnpm..."
+if command -v pnpm >/dev/null 2>&1; then
+    echo "✓ pnpm is installed (version: $(pnpm --version))"
+else
+    echo "✗ pnpm is not installed"
+    echo "  Install command: npm install -g pnpm"
+    all_passed=false
+fi
+echo ""
+
+# Check uv
+echo "3. Checking uv..."
+if command -v uv >/dev/null 2>&1; then
+    echo "✓ uv is installed (version: $(uv --version))"
+else
+    echo "✗ uv is not installed"
+    all_passed=false
+fi
+echo ""
+
+# Check nginx
+echo "4. Checking nginx..."
+if command -v nginx >/dev/null 2>&1; then
+    echo "✓ nginx is installed (version: $(nginx -v 2>&1))"
+else
+    echo "✗ nginx is not installed"
+    echo "  macOS: brew install nginx"
+    echo "  Linux: install it with the system package manager"
+    all_passed=false
+fi
+echo ""
+
+# Check ports
+echo "5. Checking ports..."
+if ! command -v lsof >/dev/null 2>&1; then
+    echo "✗ lsof is not installed, so port availability cannot be verified"
+    echo "  Install lsof and rerun this check"
+    all_passed=false
+else
+    for port in 2026 3000 8001 2024; do
+        if lsof -i :$port >/dev/null 2>&1; then
+            echo "⚠  Port $port is already in use:"
+            lsof -i :$port | head -2
+            all_passed=false
+        else
+            echo "✓ Port $port is available"
+        fi
+    done
+fi
+echo ""
+
+# Summary
+echo "=========================================="
+echo "  Environment Check Summary"
+echo "=========================================="
+echo ""
+if [ "$all_passed" = true ]; then
+    echo "✅ All environment checks passed!"
+    echo ""
+    echo "Next step: run make install to install dependencies"
+    exit 0
+else
+    echo "❌ Some checks failed. Please fix the issues above first"
+    exit 1
+fi

.agent/skills/smoke-test/scripts/deploy_docker.sh

@@ -0,0 +1,65 @@
+#!/usr/bin/env bash
+set -e
+
+echo "=========================================="
+echo "  Docker Deployment"
+echo "=========================================="
+echo ""
+
+# Check config.yaml
+if [ ! -f "config.yaml" ]; then
+    echo "config.yaml does not exist. Generating it..."
+    make config
+    echo ""
+    echo "⚠  Please edit config.yaml to configure your models and API keys"
+    echo "  Then run this script again"
+    exit 1
+else
+    echo "✓ config.yaml exists"
+fi
+echo ""
+
+# Check the .env file
+if [ ! -f ".env" ]; then
+    echo ".env does not exist. Copying it from the example..."
+    if [ -f ".env.example" ]; then
+        cp .env.example .env
+        echo "✓ Created the .env file"
+    else
+        echo "⚠  .env.example does not exist. Please create the .env file manually"
+    fi
+else
+    echo "✓ .env file exists"
+fi
+echo ""
+
+# Check the frontend .env file
+if [ ! -f "frontend/.env" ]; then
+    echo "frontend/.env does not exist. Copying it from the example..."
+    if [ -f "frontend/.env.example" ]; then
+        cp frontend/.env.example frontend/.env
+        echo "✓ Created the frontend/.env file"
+    else
+        echo "⚠  frontend/.env.example does not exist. Please create frontend/.env manually"
+    fi
+else
+    echo "✓ frontend/.env file exists"
+fi
+echo ""
+# Initialize the Docker environment
+echo "Initializing the Docker environment..."
+make docker-init
+echo ""
+
+# Start Docker services
+echo "Starting Docker services..."
+make docker-start
+echo ""
+
+echo "=========================================="
+echo "  Deployment Complete"
+echo "=========================================="
+echo ""
+echo "🌐 Access URL: http://localhost:2026"
+echo "📋 View logs: make docker-logs"
+echo "🛑 Stop services: make docker-stop"

.agent/skills/smoke-test/scripts/deploy_local.sh

@@ -0,0 +1,63 @@
+#!/usr/bin/env bash
+set -e
+
+echo "=========================================="
+echo "  Local Mode Deployment"
+echo "=========================================="
+echo ""
+
+# Check config.yaml
+if [ ! -f "config.yaml" ]; then
+    echo "config.yaml does not exist. Generating it..."
+    make config
+    echo ""
+    echo "⚠  Please edit config.yaml to configure your models and API keys"
+    echo "  Then run this script again"
+    exit 1
+else
+    echo "✓ config.yaml exists"
+fi
+echo ""
+
+# Check the .env file
+if [ ! -f ".env" ]; then
+    echo ".env does not exist. Copying it from the example..."
+    if [ -f ".env.example" ]; then
+        cp .env.example .env
+        echo "✓ Created the .env file"
+    else
+        echo "⚠  .env.example does not exist. Please create the .env file manually"
+    fi
+else
+    echo "✓ .env file exists"
+fi
+echo ""
+
+# Check dependencies
+echo "Checking dependencies..."
+make check
+echo ""
+
+# Install dependencies
+echo "Installing dependencies..."
+make install
+echo ""
+
+# Start services
+echo "Starting services (background mode)..."
+make dev-daemon
+echo ""
+
+echo "=========================================="
+echo "  Deployment Complete"
+echo "=========================================="
+echo ""
+echo "🌐 Access URL: http://localhost:2026"
+echo "📋 View logs:"
+echo "   - logs/langgraph.log"
+echo "   - logs/gateway.log"
+echo "   - logs/frontend.log"
+echo "   - logs/nginx.log"
+echo "🛑 Stop services: make stop"
+echo ""
+echo "Please wait 90-120 seconds for all services to start completely, then run the health check"

.agent/skills/smoke-test/scripts/frontend_check.sh

@@ -0,0 +1,70 @@
+#!/usr/bin/env bash
+set +e
+
+echo "=========================================="
+echo "  Frontend Page Smoke Check"
+echo "=========================================="
+echo ""
+
+BASE_URL="${BASE_URL:-http://localhost:2026}"
+DOC_PATH="${DOC_PATH:-/en/docs}"
+
+all_passed=true
+
+check_status() {
+    local name="$1"
+    local url="$2"
+    local expected_re="$3"
+
+    local status
+    status="$(curl -s -o /dev/null -w "%{http_code}" -L "$url")"
+    if echo "$status" | grep -Eq "$expected_re"; then
+        echo "✓ $name ($url) -> $status"
+    else
+        echo "✗ $name ($url) -> $status (expected: $expected_re)"
+        all_passed=false
+    fi
+}
+
+check_final_url() {
+    local name="$1"
+    local url="$2"
+    local expected_path_re="$3"
+
+    local effective
+    effective="$(curl -s -o /dev/null -w "%{url_effective}" -L "$url")"
+    if echo "$effective" | grep -Eq "$expected_path_re"; then
+        echo "✓ $name redirect target -> $effective"
+    else
+        echo "✗ $name redirect target -> $effective (expected path: $expected_path_re)"
+        all_passed=false
+    fi
+}
+
+echo "1. Checking entry pages..."
+check_status "Landing page" "${BASE_URL}/" "200"
+check_status "Workspace redirect" "${BASE_URL}/workspace" "200|301|302|307|308"
+check_final_url "Workspace redirect" "${BASE_URL}/workspace" "/workspace/chats/"
+echo ""
+
+echo "2. Checking key workspace routes..."
+check_status "New chat page" "${BASE_URL}/workspace/chats/new" "200"
+check_status "Chats list page" "${BASE_URL}/workspace/chats" "200"
+check_status "Agents gallery page" "${BASE_URL}/workspace/agents" "200"
+echo ""
+
+echo "3. Checking docs route (optional)..."
+check_status "Docs page" "${BASE_URL}${DOC_PATH}" "200|404"
+echo ""
+
+echo "=========================================="
+echo "  Frontend Smoke Check Summary"
+echo "=========================================="
+echo ""
+if [ "$all_passed" = true ]; then
+    echo "✅ Frontend smoke checks passed!"
+    exit 0
+else
+    echo "❌ Frontend smoke checks failed"
+    exit 1
+fi

.agent/skills/smoke-test/scripts/health_check.sh

@@ -0,0 +1,125 @@
+#!/usr/bin/env bash
+set +e
+
+echo "=========================================="
+echo "  Service Health Check"
+echo "=========================================="
+echo ""
+
+all_passed=true
+mode="${SMOKE_TEST_MODE:-auto}"
+summary_hint="make logs"
+
+print_step() {
+    echo "$1"
+}
+
+check_http_status() {
+    local name="$1"
+    local url="$2"
+    local expected_re="$3"
+    local status
+
+    status="$(curl -s -o /dev/null -w "%{http_code}" "$url" 2>/dev/null)"
+    if echo "$status" | grep -Eq "$expected_re"; then
+        echo "✓ $name is accessible ($url -> $status)"
+    else
+        echo "✗ $name is not accessible ($url -> ${status:-000})"
+        all_passed=false
+    fi
+}
+
+check_listen_port() {
+    local name="$1"
+    local port="$2"
+
+    if lsof -nP -iTCP:"$port" -sTCP:LISTEN >/dev/null 2>&1; then
+        echo "✓ $name is listening on port $port"
+    else
+        echo "✗ $name is not listening on port $port"
+        all_passed=false
+    fi
+}
+
+docker_available() {
+    command -v docker >/dev/null 2>&1 && docker info >/dev/null 2>&1
+}
+
+detect_mode() {
+    case "$mode" in
+        local|docker)
+            echo "$mode"
+            return
+            ;;
+    esac
+
+    if docker_available && docker ps --format "{{.Names}}" | grep -q "deer-flow"; then
+        echo "docker"
+    else
+        echo "local"
+    fi
+}
+
+mode="$(detect_mode)"
+
+echo "Deployment mode: $mode"
+echo ""
+
+if [ "$mode" = "docker" ]; then
+    summary_hint="make docker-logs"
+    print_step "1. Checking container status..."
+    if docker ps --format "{{.Names}}" | grep -q "deer-flow"; then
+        echo "✓ Containers are running:"
+        docker ps --format "  - {{.Names}} ({{.Status}})"
+    else
+        echo "✗ No DeerFlow-related containers are running"
+        all_passed=false
+    fi
+else
+    summary_hint="logs/{langgraph,gateway,frontend,nginx}.log"
+    print_step "1. Checking local service ports..."
+    check_listen_port "Nginx" 2026
+    check_listen_port "Frontend" 3000
+    check_listen_port "Gateway" 8001
+    check_listen_port "LangGraph" 2024
+fi
+echo ""
+
+echo "2. Waiting for services to fully start (30 seconds)..."
+sleep 30
+echo ""
+
+echo "3. Checking frontend service..."
+check_http_status "Frontend service" "http://localhost:2026" "200|301|302|307|308"
+echo ""
+
+echo "4. Checking API Gateway..."
+health_response=$(curl -s http://localhost:2026/health 2>/dev/null)
+if [ $? -eq 0 ] && [ -n "$health_response" ]; then
+    echo "✓ API Gateway health check passed"
+    echo "  Response: $health_response"
+else
+    echo "✗ API Gateway health check failed"
+    all_passed=false
+fi
+echo ""
+
+echo "5. Checking LangGraph service..."
+check_http_status "LangGraph service" "http://localhost:2024/" "200|301|302|307|308|404"
+echo ""
+
+echo "=========================================="
+echo "  Health Check Summary"
+echo "=========================================="
+echo ""
+if [ "$all_passed" = true ]; then
+    echo "✅ All checks passed!"
+    echo ""
+    echo "🌐 Application URL: http://localhost:2026"
+    exit 0
+else
+    echo "❌ Some checks failed"
+    echo ""
+    echo "Please review: $summary_hint"
+    exit 1
+fi

.agent/skills/smoke-test/scripts/pull_code.sh

@@ -0,0 +1,49 @@
+#!/usr/bin/env bash
+set -e
+
+echo "=========================================="
+echo "  Pulling the Latest Code"
+echo "=========================================="
+echo ""
+
+# Check whether the current directory is a Git repository
+if [ ! -d ".git" ]; then
+    echo "✗ The current directory is not a Git repository"
+    exit 1
+fi
+
+# Check Git status
+echo "Checking Git status..."
+if git status --porcelain | grep -q .; then
+    echo "⚠  Uncommitted changes detected:"
+    git status --short
+    echo ""
+    echo "Please commit or stash your changes before continuing"
+    echo "Options:"
+    echo "  1. git add . && git commit -m 'Save changes'"
+    echo "  2. git stash (stash changes and restore them later)"
+    echo "  3. git reset --hard HEAD (discard local changes - use with caution)"
+    exit 1
+else
+    echo "✓ Working tree is clean"
+fi
+echo ""
+
+# Fetch remote updates
+echo "Fetching remote updates..."
+git fetch origin main
+echo ""
+
+# Pull the latest code
+echo "Pulling the latest code..."
+git pull origin main
+echo ""
+
+# Show the latest commit
+echo "Latest commit:"
+git log -1 --oneline
+echo ""
+
+echo "=========================================="
+echo "  Code Update Complete"
+echo "=========================================="

.agent/skills/smoke-test/templates/report.docker.template.md

@@ -0,0 +1,180 @@
+# DeerFlow Smoke Test Report
+
+**Test Date**: {{test_date}}  
+**Test Environment**: {{test_environment}}  
+**Deployment Mode**: Docker  
+**Test Version**: {{git_commit}}
+
+---
+
+## Execution Summary
+
+| Metric | Status |
+|------|------|
+| Total Test Phases | 6 |
+| Passed Phases | {{passed_stages}} |
+| Failed Phases | {{failed_stages}} |
+| Overall Conclusion | **{{overall_status}}** |
+
+### Key Test Cases
+
+| Case | Result | Details |
+|------|--------|---------|
+| Code update check | {{case_code_update}} | {{case_code_update_details}} |
+| Environment check | {{case_env_check}} | {{case_env_check_details}} |
+| Configuration preparation | {{case_config_prep}} | {{case_config_prep_details}} |
+| Deployment | {{case_deploy}} | {{case_deploy_details}} |
+| Health check | {{case_health_check}} | {{case_health_check_details}} |
+| Frontend routes | {{case_frontend_routes_overall}} | {{case_frontend_routes_details}} |
+
+---
+
+## Detailed Test Results
+
+### Phase 1: Code Update Check
+
+- [x] Confirm current directory - {{status_dir_check}}
+- [x] Check Git status - {{status_git_status}}
+- [x] Pull latest code - {{status_git_pull}}
+- [x] Confirm code update - {{status_git_verify}}
+
+**Phase Status**: {{stage1_status}}
+
+---
+
+### Phase 2: Docker Environment Check
+
+- [x] Docker version - {{status_docker_version}}
+- [x] Docker daemon - {{status_docker_daemon}}
+- [x] Docker Compose - {{status_docker_compose}}
+- [x] Port check - {{status_port_check}}
+
+**Phase Status**: {{stage2_status}}
+
+---
+
+### Phase 3: Configuration Preparation
+
+- [x] config.yaml - {{status_config_yaml}}
+- [x] .env file - {{status_env_file}}
+- [x] Model configuration - {{status_model_config}}
+
+**Phase Status**: {{stage3_status}}
+
+---
+
+### Phase 4: Docker Deployment
+
+- [x] docker-init - {{status_docker_init}}
+- [x] docker-start - {{status_docker_start}}
+- [x] Service startup wait - {{status_wait_startup}}
+
+**Phase Status**: {{stage4_status}}
+
+---
+
+### Phase 5: Service Health Check
+
+- [x] Container status - {{status_containers}}
+- [x] Frontend service - {{status_frontend}}
+- [x] API Gateway - {{status_api_gateway}}
+- [x] LangGraph service - {{status_langgraph}}
+
+**Phase Status**: {{stage5_status}}
+
+---
+
+### Frontend Routes Smoke Results
+
+| Route | Status | Details |
+|-------|--------|---------|
+| Landing `/` | {{landing_status}} | {{landing_details}} |
+| Workspace redirect `/workspace` | {{workspace_redirect_status}} | target {{workspace_redirect_target}} |
+| New chat `/workspace/chats/new` | {{new_chat_status}} | {{new_chat_details}} |
+| Chats list `/workspace/chats` | {{chats_list_status}} | {{chats_list_details}} |
+| Agents gallery `/workspace/agents` | {{agents_gallery_status}} | {{agents_gallery_details}} |
+| Docs `{{docs_path}}` | {{docs_status}} | {{docs_details}} |
+
+**Summary**: {{frontend_routes_summary}}
+
+---
+
+### Phase 6: Test Report Generation
+
+- [x] Result summary - {{status_summary}}
+- [x] Issue log - {{status_issues}}
+- [x] Report generation - {{status_report}}
+
+**Phase Status**: {{stage6_status}}
+
+---
+
+## Issue Log
+
+### Issue 1
+**Description**: {{issue1_description}}  
+**Severity**: {{issue1_severity}}  
+**Solution**: {{issue1_solution}}
+
+---
+
+## Environment Information
+
+### Docker Version
+```text
+{{docker_version_output}}
+```
+
+### Git Information
+```text
+Repository: {{git_repo}}
+Branch: {{git_branch}}
+Commit: {{git_commit}}
+Commit Message: {{git_commit_message}}
+```
+
+### Configuration Summary
+- config.yaml exists: {{config_exists}}
+- .env file exists: {{env_exists}}
+- Number of configured models: {{model_count}}
+
+---
+
+## Container Status
+
+| Container Name | Status | Uptime |
+|----------|------|----------|
+| deer-flow-nginx | {{nginx_status}} | {{nginx_uptime}} |
+| deer-flow-frontend | {{frontend_status}} | {{frontend_uptime}} |
+| deer-flow-gateway | {{gateway_status}} | {{gateway_uptime}} |
+| deer-flow-langgraph | {{langgraph_status}} | {{langgraph_uptime}} |
+
+---
+
+## Recommendations and Next Steps
+
+### If the Test Passes
+1. [ ] Visit http://localhost:2026 to start using DeerFlow
+2. [ ] Configure your preferred model if it is not configured yet
+3. [ ] Explore available skills
+4. [ ] Refer to the documentation to learn more features
+
+### If the Test Fails
+1. [ ] Review references/troubleshooting.md for common solutions
+2. [ ] Check Docker logs: `make docker-logs`
+3. [ ] Verify configuration file format and content
+4. [ ] If needed, fully reset the environment: `make clean && make config && make docker-init && make docker-start`
+
+---
+
+## Appendix
+
+### Full Logs
+{{full_logs}}
+
+### Tester
+{{tester_name}}
+
+---
+
+*Report generated at: {{report_time}}*

.agent/skills/smoke-test/templates/report.local.template.md

@@ -0,0 +1,185 @@
+# DeerFlow Smoke Test Report
+
+**Test Date**: {{test_date}}  
+**Test Environment**: {{test_environment}}  
+**Deployment Mode**: Local  
+**Test Version**: {{git_commit}}
+
+---
+
+## Execution Summary
+
+| Metric | Status |
+|------|------|
+| Total Test Phases | 6 |
+| Passed Phases | {{passed_stages}} |
+| Failed Phases | {{failed_stages}} |
+| Overall Conclusion | **{{overall_status}}** |
+
+### Key Test Cases
+
+| Case | Result | Details |
+|------|--------|---------|
+| Code update check | {{case_code_update}} | {{case_code_update_details}} |
+| Environment check | {{case_env_check}} | {{case_env_check_details}} |
+| Configuration preparation | {{case_config_prep}} | {{case_config_prep_details}} |
+| Deployment | {{case_deploy}} | {{case_deploy_details}} |
+| Health check | {{case_health_check}} | {{case_health_check_details}} |
+| Frontend routes | {{case_frontend_routes_overall}} | {{case_frontend_routes_details}} |
+
+---
+
+## Detailed Test Results
+
+### Phase 1: Code Update Check
+
+- [x] Confirm current directory - {{status_dir_check}}
+- [x] Check Git status - {{status_git_status}}
+- [x] Pull latest code - {{status_git_pull}}
+- [x] Confirm code update - {{status_git_verify}}
+
+**Phase Status**: {{stage1_status}}
+
+---
+
+### Phase 2: Local Environment Check
+
+- [x] Node.js version - {{status_node_version}}
+- [x] pnpm - {{status_pnpm}}
+- [x] uv - {{status_uv}}
+- [x] nginx - {{status_nginx}}
+- [x] Port check - {{status_port_check}}
+
+**Phase Status**: {{stage2_status}}
+
+---
+
+### Phase 3: Configuration Preparation
+
+- [x] config.yaml - {{status_config_yaml}}
+- [x] .env file - {{status_env_file}}
+- [x] Model configuration - {{status_model_config}}
+
+**Phase Status**: {{stage3_status}}
+
+---
+
+### Phase 4: Local Deployment
+
+- [x] make check - {{status_make_check}}
+- [x] make install - {{status_make_install}}
+- [x] make dev-daemon / make dev - {{status_local_start}}
+- [x] Service startup wait - {{status_wait_startup}}
+
+**Phase Status**: {{stage4_status}}
+
+---
+
+### Phase 5: Service Health Check
+
+- [x] Process status - {{status_processes}}
+- [x] Frontend service - {{status_frontend}}
+- [x] API Gateway - {{status_api_gateway}}
+- [x] LangGraph service - {{status_langgraph}}
+
+**Phase Status**: {{stage5_status}}
+
+---
+
+### Frontend Routes Smoke Results
+
+| Route | Status | Details |
+|-------|--------|---------|
+| Landing `/` | {{landing_status}} | {{landing_details}} |
+| Workspace redirect `/workspace` | {{workspace_redirect_status}} | target {{workspace_redirect_target}} |
+| New chat `/workspace/chats/new` | {{new_chat_status}} | {{new_chat_details}} |
+| Chats list `/workspace/chats` | {{chats_list_status}} | {{chats_list_details}} |
+| Agents gallery `/workspace/agents` | {{agents_gallery_status}} | {{agents_gallery_details}} |
+| Docs `{{docs_path}}` | {{docs_status}} | {{docs_details}} |
+
+**Summary**: {{frontend_routes_summary}}
+
+---
+
+### Phase 6: Test Report Generation
+
+- [x] Result summary - {{status_summary}}
+- [x] Issue log - {{status_issues}}
+- [x] Report generation - {{status_report}}
+
+**Phase Status**: {{stage6_status}}
+
+---
+
+## Issue Log
+
+### Issue 1
+**Description**: {{issue1_description}}  
+**Severity**: {{issue1_severity}}  
+**Solution**: {{issue1_solution}}
+
+---
+
+## Environment Information
+
+### Local Dependency Versions
+```text
+Node.js: {{node_version_output}}
+pnpm: {{pnpm_version_output}}
+uv: {{uv_version_output}}
+nginx: {{nginx_version_output}}
+```
+
+### Git Information
+```text
+Repository: {{git_repo}}
+Branch: {{git_branch}}
+Commit: {{git_commit}}
+Commit Message: {{git_commit_message}}
+```
+
+### Configuration Summary
+- config.yaml exists: {{config_exists}}
+- .env file exists: {{env_exists}}
+- Number of configured models: {{model_count}}
+
+---
+
+## Local Service Status
+
+| Service | Status | Endpoint |
+|---------|--------|----------|
+| Nginx | {{nginx_status}} | {{nginx_endpoint}} |
+| Frontend | {{frontend_status}} | {{frontend_endpoint}} |
+| Gateway | {{gateway_status}} | {{gateway_endpoint}} |
+| LangGraph | {{langgraph_status}} | {{langgraph_endpoint}} |
+
+---
+
+## Recommendations and Next Steps
+
+### If the Test Passes
+1. [ ] Visit http://localhost:2026 to start using DeerFlow
+2. [ ] Configure your preferred model if it is not configured yet
+3. [ ] Explore available skills
+4. [ ] Refer to the documentation to learn more features
+
+### If the Test Fails
+1. [ ] Review references/troubleshooting.md for common solutions
+2. [ ] Check local logs: `logs/{langgraph,gateway,frontend,nginx}.log`
+3. [ ] Verify configuration file format and content
+4. [ ] If needed, fully reset the environment: `make stop && make clean && make install && make dev-daemon`
+
+---
+
+## Appendix
+
+### Full Logs
+{{full_logs}}
+
+### Tester
+{{tester_name}}
+
+---
+
+*Report generated at: {{report_time}}*

.env.example

@@ -6,11 +6,6 @@ JINA_API_KEY=your-jina-api-key
 
 # InfoQuest API Key
 INFOQUEST_API_KEY=your-infoquest-api-key
-# Authentication — JWT secret for session signing
-# If not set, an ephemeral secret is auto-generated (sessions lost on restart)
-# Generate with: python -c "import secrets; print(secrets.token_urlsafe(32))"
-# AUTH_JWT_SECRET=your-secure-jwt-secret-here
-
 # CORS Origins (comma-separated) - e.g., http://localhost:3000,http://localhost:3001
 # CORS_ORIGINS=http://localhost:3000
 
@@ -22,6 +17,7 @@ INFOQUEST_API_KEY=your-infoquest-api-key
 # DEEPSEEK_API_KEY=your-deepseek-api-key
 # NOVITA_API_KEY=your-novita-api-key  # OpenAI-compatible, see https://novita.ai
 # MINIMAX_API_KEY=your-minimax-api-key  # OpenAI-compatible, see https://platform.minimax.io
+# VLLM_API_KEY=your-vllm-api-key  # OpenAI-compatible
 # FEISHU_APP_ID=your-feishu-app-id
 # FEISHU_APP_SECRET=your-feishu-app-secret
 
@@ -37,5 +33,9 @@ INFOQUEST_API_KEY=your-infoquest-api-key
 
 # GitHub API Token
 # GITHUB_TOKEN=your-github-token
+
+# Database (only needed when config.yaml has database.backend: postgres)
+# DATABASE_URL=postgresql://deerflow:password@localhost:5432/deerflow
+#
 # WECOM_BOT_ID=your-wecom-bot-id
 # WECOM_BOT_SECRET=your-wecom-bot-secret

.gitignore

@@ -54,4 +54,6 @@ web/
 # Deployment artifacts
 backend/Dockerfile.langgraph
 config.yaml.bak
+.playwright-mcp
 .gstack/
+.worktrees

CODE_OF_CONDUCT.md

@@ -0,0 +1,128 @@
+# Contributor Covenant Code of Conduct
+
+## Our Pledge
+
+We as members, contributors, and leaders pledge to make participation in our
+community a harassment-free experience for everyone, regardless of age, body
+size, visible or invisible disability, ethnicity, sex characteristics, gender
+identity and expression, level of experience, education, socio-economic status,
+nationality, personal appearance, race, religion, or sexual identity
+and orientation.
+
+We pledge to act and interact in ways that contribute to an open, welcoming,
+diverse, inclusive, and healthy community.
+
+## Our Standards
+
+Examples of behavior that contributes to a positive environment for our
+community include:
+
+* Demonstrating empathy and kindness toward other people
+* Being respectful of differing opinions, viewpoints, and experiences
+* Giving and gracefully accepting constructive feedback
+* Accepting responsibility and apologizing to those affected by our mistakes,
+  and learning from the experience
+* Focusing on what is best not just for us as individuals, but for the
+  overall community
+
+Examples of unacceptable behavior include:
+
+* The use of sexualized language or imagery, and sexual attention or
+  advances of any kind
+* Trolling, insulting or derogatory comments, and personal or political attacks
+* Public or private harassment
+* Publishing others' private information, such as a physical or email
+  address, without their explicit permission
+* Other conduct which could reasonably be considered inappropriate in a
+  professional setting
+
+## Enforcement Responsibilities
+
+Community leaders are responsible for clarifying and enforcing our standards of
+acceptable behavior and will take appropriate and fair corrective action in
+response to any behavior that they deem inappropriate, threatening, offensive,
+or harmful.
+
+Community leaders have the right and responsibility to remove, edit, or reject
+comments, commits, code, wiki edits, issues, and other contributions that are
+not aligned to this Code of Conduct, and will communicate reasons for moderation
+decisions when appropriate.
+
+## Scope
+
+This Code of Conduct applies within all community spaces, and also applies when
+an individual is officially representing the community in public spaces.
+Examples of representing our community include using an official e-mail address,
+posting via an official social media account, or acting as an appointed
+representative at an online or offline event.
+
+## Enforcement
+
+Instances of abusive, harassing, or otherwise unacceptable behavior may be
+reported to the community leaders responsible for enforcement at
+willem.jiang@gmail.com.
+All complaints will be reviewed and investigated promptly and fairly.
+
+All community leaders are obligated to respect the privacy and security of the
+reporter of any incident.
+
+## Enforcement Guidelines
+
+Community leaders will follow these Community Impact Guidelines in determining
+the consequences for any action they deem in violation of this Code of Conduct:
+
+### 1. Correction
+
+**Community Impact**: Use of inappropriate language or other behavior deemed
+unprofessional or unwelcome in the community.
+
+**Consequence**: A private, written warning from community leaders, providing
+clarity around the nature of the violation and an explanation of why the
+behavior was inappropriate. A public apology may be requested.
+
+### 2. Warning
+
+**Community Impact**: A violation through a single incident or series
+of actions.
+
+**Consequence**: A warning with consequences for continued behavior. No
+interaction with the people involved, including unsolicited interaction with
+those enforcing the Code of Conduct, for a specified period of time. This
+includes avoiding interactions in community spaces as well as external channels
+like social media. Violating these terms may lead to a temporary or
+permanent ban.
+
+### 3. Temporary Ban
+
+**Community Impact**: A serious violation of community standards, including
+sustained inappropriate behavior.
+
+**Consequence**: A temporary ban from any sort of interaction or public
+communication with the community for a specified period of time. No public or
+private interaction with the people involved, including unsolicited interaction
+with those enforcing the Code of Conduct, is allowed during this period.
+Violating these terms may lead to a permanent ban.
+
+### 4. Permanent Ban
+
+**Community Impact**: Demonstrating a pattern of violation of community
+standards, including sustained inappropriate behavior,  harassment of an
+individual, or aggression toward or disparagement of classes of individuals.
+
+**Consequence**: A permanent ban from any sort of public interaction within
+the community.
+
+## Attribution
+
+This Code of Conduct is adapted from the [Contributor Covenant][homepage],
+version 2.0, available at
+https://www.contributor-covenant.org/version/2/0/code_of_conduct.html.
+
+Community Impact Guidelines were inspired by [Mozilla's code of conduct
+enforcement ladder](https://github.com/mozilla/diversity).
+
+[homepage]: https://www.contributor-covenant.org
+
+For answers to common questions about this code of conduct, see the FAQ at
+https://www.contributor-covenant.org/faq. Translations are available at
+https://www.contributor-covenant.org/translations.

CONTRIBUTING.md

@@ -77,6 +77,18 @@ export UV_INDEX_URL=https://pypi.org/simple
 export NPM_REGISTRY=https://registry.npmjs.org
 ```
 
+#### Recommended host resources
+
+Use these as practical starting points for development and review environments:
+
+| Scenario | Starting point | Recommended | Notes |
+|---------|-----------|------------|-------|
+| `make dev` on one machine | 4 vCPU, 8 GB RAM | 8 vCPU, 16 GB RAM | Best when DeerFlow uses hosted model APIs. |
+| `make docker-start` review environment | 4 vCPU, 8 GB RAM | 8 vCPU, 16 GB RAM | Docker image builds and sandbox containers need extra headroom. |
+| Shared Linux test server | 8 vCPU, 16 GB RAM | 16 vCPU, 32 GB RAM | Prefer this for heavier multi-agent runs or multiple reviewers. |
+
+`2 vCPU / 4 GB` environments often fail to start reliably or become unresponsive under normal DeerFlow workloads.
+
 #### Linux: Docker daemon permission denied
 
 If `make docker-init`, `make docker-start`, or `make docker-stop` fails on Linux with an error like below, your current user likely does not have permission to access the Docker daemon socket:

Makefile

@@ -1,19 +1,25 @@
 # DeerFlow - Unified Development Environment
 
-.PHONY: help config config-upgrade check install dev dev-pro dev-daemon dev-daemon-pro start start-pro start-daemon start-daemon-pro stop up up-pro down clean docker-init docker-start docker-start-pro docker-stop docker-logs docker-logs-frontend docker-logs-gateway
+.PHONY: help config config-upgrade check install setup doctor dev dev-pro dev-daemon dev-daemon-pro start start-pro start-daemon start-daemon-pro stop up up-pro down clean docker-init docker-start docker-start-pro docker-stop docker-logs docker-logs-frontend docker-logs-gateway
 
 BASH ?= bash
+BACKEND_UV_RUN = cd backend && uv run
 
 # Detect OS for Windows compatibility
 ifeq ($(OS),Windows_NT)
     SHELL := cmd.exe
     PYTHON ?= python
+    # Run repo shell scripts through Git Bash when Make is launched from cmd.exe / PowerShell.
+    RUN_WITH_GIT_BASH = call scripts\run-with-git-bash.cmd
 else
     PYTHON ?= python3
+    RUN_WITH_GIT_BASH =
 endif
 
 help:
 	@echo "DeerFlow Development Commands:"
+	@echo "  make setup           - Interactive setup wizard (recommended for new users)"
+	@echo "  make doctor          - Check configuration and system requirements"
 	@echo "  make config          - Generate local config files (aborts if config already exists)"
 	@echo "  make config-upgrade  - Merge new fields from config.example.yaml into config.yaml"
 	@echo "  make check           - Check if all required tools are installed"
@@ -44,11 +50,18 @@ help:
 	@echo "  make docker-logs-frontend - View Docker frontend logs"
 	@echo "  make docker-logs-gateway - View Docker gateway logs"
 
+## Setup & Diagnosis
+setup:
+	@$(BACKEND_UV_RUN) python ../scripts/setup_wizard.py
+
+doctor:
+	@$(BACKEND_UV_RUN) python ../scripts/doctor.py
+
 config:
 	@$(PYTHON) ./scripts/configure.py
 
 config-upgrade:
-	@./scripts/config-upgrade.sh
+	@$(RUN_WITH_GIT_BASH) ./scripts/config-upgrade.sh
 
 # Check required tools
 check:
@@ -106,78 +119,46 @@ setup-sandbox:
 # Start all services in development mode (with hot-reloading)
 dev:
 	@$(PYTHON) ./scripts/check.py
-ifeq ($(OS),Windows_NT)
-	@call scripts\run-with-git-bash.cmd ./scripts/serve.sh --dev
-else
-	@./scripts/serve.sh --dev
-endif
+	@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --dev
 
 # Start all services in dev + Gateway mode (experimental: agent runtime embedded in Gateway)
 dev-pro:
 	@$(PYTHON) ./scripts/check.py
-ifeq ($(OS),Windows_NT)
-	@call scripts\run-with-git-bash.cmd ./scripts/serve.sh --dev --gateway
-else
-	@./scripts/serve.sh --dev --gateway
-endif
+	@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --dev --gateway
 
 # Start all services in production mode (with optimizations)
 start:
 	@$(PYTHON) ./scripts/check.py
-ifeq ($(OS),Windows_NT)
-	@call scripts\run-with-git-bash.cmd ./scripts/serve.sh --prod
-else
-	@./scripts/serve.sh --prod
-endif
+	@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --prod
 
 # Start all services in prod + Gateway mode (experimental)
 start-pro:
 	@$(PYTHON) ./scripts/check.py
-ifeq ($(OS),Windows_NT)
-	@call scripts\run-with-git-bash.cmd ./scripts/serve.sh --prod --gateway
-else
-	@./scripts/serve.sh --prod --gateway
-endif
+	@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --prod --gateway
 
 # Start all services in daemon mode (background)
 dev-daemon:
 	@$(PYTHON) ./scripts/check.py
-ifeq ($(OS),Windows_NT)
-	@call scripts\run-with-git-bash.cmd ./scripts/serve.sh --dev --daemon
-else
-	@./scripts/serve.sh --dev --daemon
-endif
+	@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --dev --daemon
 
 # Start daemon + Gateway mode (experimental)
 dev-daemon-pro:
 	@$(PYTHON) ./scripts/check.py
-ifeq ($(OS),Windows_NT)
-	@call scripts\run-with-git-bash.cmd ./scripts/serve.sh --dev --gateway --daemon
-else
-	@./scripts/serve.sh --dev --gateway --daemon
-endif
+	@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --dev --gateway --daemon
 
 # Start prod services in daemon mode (background)
 start-daemon:
 	@$(PYTHON) ./scripts/check.py
-ifeq ($(OS),Windows_NT)
-	@call scripts\run-with-git-bash.cmd ./scripts/serve.sh --prod --daemon
-else
-	@./scripts/serve.sh --prod --daemon
-endif
+	@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --prod --daemon
 
 # Start prod daemon + Gateway mode (experimental)
 start-daemon-pro:
 	@$(PYTHON) ./scripts/check.py
-ifeq ($(OS),Windows_NT)
-	@call scripts\run-with-git-bash.cmd ./scripts/serve.sh --prod --gateway --daemon
-else
-	@./scripts/serve.sh --prod --gateway --daemon
-endif
+	@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --prod --gateway --daemon
 
 # Stop all services
 stop:
-	@./scripts/serve.sh --stop
+	@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --stop
 
 # Clean up
 clean: stop
@@ -193,29 +174,29 @@ clean: stop
 
 # Initialize Docker containers and install dependencies
 docker-init:
-	@./scripts/docker.sh init
+	@$(RUN_WITH_GIT_BASH) ./scripts/docker.sh init
 
 # Start Docker development environment
 docker-start:
-	@./scripts/docker.sh start
+	@$(RUN_WITH_GIT_BASH) ./scripts/docker.sh start
 
 # Start Docker in Gateway mode (experimental)
 docker-start-pro:
-	@./scripts/docker.sh start --gateway
+	@$(RUN_WITH_GIT_BASH) ./scripts/docker.sh start --gateway
 
 # Stop Docker development environment
 docker-stop:
-	@./scripts/docker.sh stop
+	@$(RUN_WITH_GIT_BASH) ./scripts/docker.sh stop
 
 # View Docker development logs
 docker-logs:
-	@./scripts/docker.sh logs
+	@$(RUN_WITH_GIT_BASH) ./scripts/docker.sh logs
 
 # View Docker development logs
 docker-logs-frontend:
-	@./scripts/docker.sh logs --frontend
+	@$(RUN_WITH_GIT_BASH) ./scripts/docker.sh logs --frontend
 docker-logs-gateway:
-	@./scripts/docker.sh logs --gateway
+	@$(RUN_WITH_GIT_BASH) ./scripts/docker.sh logs --gateway
 
 # ==========================================
 # Production Docker Commands
@@ -223,12 +204,12 @@ docker-logs-gateway:
 
 # Build and start production services
 up:
-	@./scripts/deploy.sh
+	@$(RUN_WITH_GIT_BASH) ./scripts/deploy.sh
 
 # Build and start production services in Gateway mode
 up-pro:
-	@./scripts/deploy.sh --gateway
+	@$(RUN_WITH_GIT_BASH) ./scripts/deploy.sh --gateway
 
 # Stop and remove production containers
 down:
-	@./scripts/deploy.sh down
+	@$(RUN_WITH_GIT_BASH) ./scripts/deploy.sh down

README.md

@@ -53,6 +53,7 @@ DeerFlow has newly integrated the intelligent search and crawling toolset indepe
   - [Quick Start](#quick-start)
     - [Configuration](#configuration)
     - [Running the Application](#running-the-application)
+      - [Deployment Sizing](#deployment-sizing)
       - [Option 1: Docker (Recommended)](#option-1-docker-recommended)
       - [Option 2: Local Development](#option-2-local-development)
     - [Advanced](#advanced)
@@ -103,35 +104,38 @@ That prompt is intended for coding agents. It tells the agent to clone the repo
    cd deer-flow
    ```
 
-2. **Generate local configuration files**
+2. **Run the setup wizard**
 
    From the project root directory (`deer-flow/`), run:
 
    ```bash
-   make config
+   make setup
    ```
 
-   This command creates local configuration files based on the provided example templates.
+   This launches an interactive wizard that guides you through choosing an LLM provider, optional web search, and execution/safety preferences such as sandbox mode, bash access, and file-write tools. It generates a minimal `config.yaml` and writes your keys to `.env`. Takes about 2 minutes.
 
-3. **Configure your preferred model(s)**
+   The wizard also lets you configure an optional web search provider, or skip it for now.
 
-   Edit `config.yaml` and define at least one model:
+   Run `make doctor` at any time to verify your setup and get actionable fix hints.
+
+   > **Advanced / manual configuration**: If you prefer to edit `config.yaml` directly, run `make config` instead to copy the full template. See `config.example.yaml` for the complete reference including CLI-backed providers (Codex CLI, Claude Code OAuth), OpenRouter, Responses API, and more.
+
+   <details>
+   <summary>Manual model configuration examples</summary>
 
    ```yaml
    models:
-     - name: gpt-4                       # Internal identifier
-       display_name: GPT-4               # Human-readable name
-       use: langchain_openai:ChatOpenAI  # LangChain class path
-       model: gpt-4                      # Model identifier for API
-       api_key: $OPENAI_API_KEY          # API key (recommended: use env var)
-       max_tokens: 4096                  # Maximum tokens per request
-       temperature: 0.7                  # Sampling temperature
+     - name: gpt-4o
+       display_name: GPT-4o
+       use: langchain_openai:ChatOpenAI
+       model: gpt-4o
+       api_key: $OPENAI_API_KEY
 
      - name: openrouter-gemini-2.5-flash
        display_name: Gemini 2.5 Flash (OpenRouter)
        use: langchain_openai:ChatOpenAI
        model: google/gemini-2.5-flash-preview
-       api_key: $OPENAI_API_KEY          # OpenRouter still uses the OpenAI-compatible field name here
+       api_key: $OPENROUTER_API_KEY
        base_url: https://openrouter.ai/api/v1
 
      - name: gpt-5-responses
@@ -141,12 +145,26 @@ That prompt is intended for coding agents. It tells the agent to clone the repo
        api_key: $OPENAI_API_KEY
        use_responses_api: true
        output_version: responses/v1
+
+     - name: qwen3-32b-vllm
+       display_name: Qwen3 32B (vLLM)
+       use: deerflow.models.vllm_provider:VllmChatModel
+       model: Qwen/Qwen3-32B
+       api_key: $VLLM_API_KEY
+       base_url: http://localhost:8000/v1
+       supports_thinking: true
+       when_thinking_enabled:
+         extra_body:
+           chat_template_kwargs:
+             enable_thinking: true
    ```
 
    OpenRouter and similar OpenAI-compatible gateways should be configured with `langchain_openai:ChatOpenAI` plus `base_url`. If you prefer a provider-specific environment variable name, point `api_key` at that variable explicitly (for example `api_key: $OPENROUTER_API_KEY`).
 
    To route OpenAI models through `/v1/responses`, keep using `langchain_openai:ChatOpenAI` and set `use_responses_api: true` with `output_version: responses/v1`.
 
+   For vLLM 0.19.0, use `deerflow.models.vllm_provider:VllmChatModel`. For Qwen-style reasoning models, DeerFlow toggles reasoning with `extra_body.chat_template_kwargs.enable_thinking` and preserves vLLM's non-standard `reasoning` field across multi-turn tool-call conversations. Legacy `thinking` configs are normalized automatically for backward compatibility. Reasoning models may also require the server to be started with `--reasoning-parser ...`. If your local vLLM deployment accepts any non-empty API key, you can still set `VLLM_API_KEY` to a placeholder value.
+
    CLI-backed provider examples:
 
    ```yaml
@@ -167,50 +185,39 @@ That prompt is intended for coding agents. It tells the agent to clone the repo
    ```
 
    - Codex CLI reads `~/.codex/auth.json`
-   - The Codex Responses endpoint currently rejects `max_tokens` and `max_output_tokens`, so `CodexChatModel` does not expose a request-level token cap
-   - Claude Code accepts `CLAUDE_CODE_OAUTH_TOKEN`, `ANTHROPIC_AUTH_TOKEN`, `CLAUDE_CODE_OAUTH_TOKEN_FILE_DESCRIPTOR`, `CLAUDE_CODE_CREDENTIALS_PATH`, or plaintext `~/.claude/.credentials.json`
-   - ACP agent entries are separate from model providers. If you configure `acp_agents.codex`, point it at a Codex ACP adapter such as `npx -y @zed-industries/codex-acp`; the standard `codex` CLI binary is not ACP-compatible by itself
-   - On macOS, DeerFlow does not probe Keychain automatically. Export Claude Code auth explicitly if needed:
+   - Claude Code accepts `CLAUDE_CODE_OAUTH_TOKEN`, `ANTHROPIC_AUTH_TOKEN`, `CLAUDE_CODE_CREDENTIALS_PATH`, or `~/.claude/.credentials.json`
+   - ACP agent entries are separate from model providers — if you configure `acp_agents.codex`, point it at a Codex ACP adapter such as `npx -y @zed-industries/codex-acp`
+   - On macOS, export Claude Code auth explicitly if needed:
 
    ```bash
    eval "$(python3 scripts/export_claude_code_oauth.py --print-export)"
    ```
-   
-4. **Set API keys for your configured model(s)**
-
-   Choose one of the following methods:
-
-- Option A: Edit the `.env` file in the project root (Recommended)
 
+   API keys can also be set manually in `.env` (recommended) or exported in your shell:
 
    ```bash
-   TAVILY_API_KEY=your-tavily-api-key
    OPENAI_API_KEY=your-openai-api-key
-   # OpenRouter also uses OPENAI_API_KEY when your config uses langchain_openai:ChatOpenAI + base_url.
-   # Add other provider keys as needed
-   INFOQUEST_API_KEY=your-infoquest-api-key
+   TAVILY_API_KEY=your-tavily-api-key
    ```
 
-- Option B: Export environment variables in your shell
-
-   ```bash
-   export OPENAI_API_KEY=your-openai-api-key
-   ```
-
-   For CLI-backed providers:
-   - Codex CLI: `~/.codex/auth.json`
-   - Claude Code OAuth: explicit env/file handoff or `~/.claude/.credentials.json`
-
-- Option C: Edit `config.yaml` directly (Not recommended for production)
-
-   ```yaml
-   models:
-     - name: gpt-4
-       api_key: your-actual-api-key-here  # Replace placeholder
-   ```
+   </details>
 
 ### Running the Application
 
+#### Deployment Sizing
+
+Use the table below as a practical starting point when choosing how to run DeerFlow:
+
+| Deployment target | Starting point | Recommended | Notes |
+|---------|-----------|------------|-------|
+| Local evaluation / `make dev` | 4 vCPU, 8 GB RAM, 20 GB free SSD | 8 vCPU, 16 GB RAM | Good for one developer or one light session with hosted model APIs. `2 vCPU / 4 GB` is usually not enough. |
+| Docker development / `make docker-start` | 4 vCPU, 8 GB RAM, 25 GB free SSD | 8 vCPU, 16 GB RAM | Image builds, bind mounts, and sandbox containers need more headroom than pure local dev. |
+| Long-running server / `make up` | 8 vCPU, 16 GB RAM, 40 GB free SSD | 16 vCPU, 32 GB RAM | Preferred for shared use, multi-agent runs, report generation, or heavier sandbox workloads. |
+
+- These numbers cover DeerFlow itself. If you also host a local LLM, size that service separately.
+- Linux plus Docker is the recommended deployment target for a persistent server. macOS and Windows are best treated as development or evaluation environments.
+- If CPU or memory usage stays pinned, reduce concurrent runs first, then move to the next sizing tier.
+
 #### Option 1: Docker (Recommended)
 
 **Development** (hot-reload, source mounts):
@@ -247,7 +254,7 @@ See [CONTRIBUTING.md](CONTRIBUTING.md) for detailed Docker development guide.
 
 If you prefer running services locally:
 
-Prerequisite: complete the "Configuration" steps above first (`make config` and model API keys). `make dev` requires a valid configuration file (defaults to `config.yaml` in the project root; can be overridden via `DEER_FLOW_CONFIG_PATH`).
+Prerequisite: complete the "Configuration" steps above first (`make setup`). `make dev` requires a valid `config.yaml` in the project root (can be overridden via `DEER_FLOW_CONFIG_PATH`). Run `make doctor` to verify your setup before starting.
 On Windows, run the local development flow from Git Bash. Native `cmd.exe` and PowerShell shells are not supported for the bash-based service scripts, and WSL is not guaranteed because some scripts rely on Git for Windows utilities such as `cygpath`.
 
 1. **Check prerequisites**:
@@ -361,6 +368,7 @@ DeerFlow supports receiving tasks from messaging apps. Channels auto-start when
 | Telegram | Bot API (long-polling) | Easy |
 | Slack | Socket Mode | Moderate |
 | Feishu / Lark | WebSocket | Moderate |
+| WeChat | Tencent iLink (long-polling) | Moderate |
 | WeCom | WebSocket | Moderate |
 
 **Configuration in `config.yaml`:**
@@ -405,6 +413,19 @@ channels:
     bot_token: $TELEGRAM_BOT_TOKEN
     allowed_users: []               # empty = allow all
 
+  wechat:
+    enabled: false
+    bot_token: $WECHAT_BOT_TOKEN
+    ilink_bot_id: $WECHAT_ILINK_BOT_ID
+    qrcode_login_enabled: true      # optional: allow first-time QR bootstrap when bot_token is absent
+    allowed_users: []               # empty = allow all
+    polling_timeout: 35
+    state_dir: ./.deer-flow/wechat/state
+    max_inbound_image_bytes: 20971520
+    max_outbound_image_bytes: 20971520
+    max_inbound_file_bytes: 52428800
+    max_outbound_file_bytes: 52428800
+
     # Optional: per-channel / per-user session settings
     session:
       assistant_id: mobile-agent  # custom agent names are also supported here
@@ -438,6 +459,10 @@ SLACK_APP_TOKEN=xapp-...
 FEISHU_APP_ID=cli_xxxx
 FEISHU_APP_SECRET=your_app_secret
 
+# WeChat iLink
+WECHAT_BOT_TOKEN=your_ilink_bot_token
+WECHAT_ILINK_BOT_ID=your_ilink_bot_id
+
 # WeCom
 WECOM_BOT_ID=your_bot_id
 WECOM_BOT_SECRET=your_bot_secret
@@ -463,6 +488,14 @@ WECOM_BOT_SECRET=your_bot_secret
 3. Under **Events**, subscribe to `im.message.receive_v1` and select **Long Connection** mode.
 4. Copy the App ID and App Secret. Set `FEISHU_APP_ID` and `FEISHU_APP_SECRET` in `.env` and enable the channel in `config.yaml`.
 
+**WeChat Setup**
+
+1. Enable the `wechat` channel in `config.yaml`.
+2. Either set `WECHAT_BOT_TOKEN` in `.env`, or set `qrcode_login_enabled: true` for first-time QR bootstrap.
+3. When `bot_token` is absent and QR bootstrap is enabled, watch backend logs for the QR content returned by iLink and complete the binding flow.
+4. After the QR flow succeeds, DeerFlow persists the acquired token under `state_dir` for later restarts.
+5. For Docker Compose deployments, keep `state_dir` on a persistent volume so the `get_updates_buf` cursor and saved auth state survive restarts.
+
 **WeCom Setup**
 
 1. Create a bot on the WeCom AI Bot platform and obtain the `bot_id` and `bot_secret`.

README_zh.md

@@ -40,6 +40,7 @@ https://github.com/user-attachments/assets/a8bcadc4-e040-4cf2-8fda-dd768b999c18
   - [快速开始](#快速开始)
     - [配置](#配置)
     - [运行应用](#运行应用)
+      - [部署建议与资源规划](#部署建议与资源规划)
       - [方式一：Docker（推荐）](#方式一docker推荐)
       - [方式二：本地开发](#方式二本地开发)
     - [进阶配置](#进阶配置)
@@ -150,6 +151,20 @@ https://github.com/user-attachments/assets/a8bcadc4-e040-4cf2-8fda-dd768b999c18
 
 ### 运行应用
 
+#### 部署建议与资源规划
+
+可以先按下面的资源档位来选择 DeerFlow 的运行方式：
+
+| 部署场景 | 起步配置 | 推荐配置 | 说明 |
+|---------|-----------|------------|-------|
+| 本地体验 / `make dev` | 4 vCPU、8 GB 内存、20 GB SSD 可用空间 | 8 vCPU、16 GB 内存 | 适合单个开发者或单个轻量会话，且模型走外部 API。`2 核 / 4 GB` 通常跑不稳。 |
+| Docker 开发 / `make docker-start` | 4 vCPU、8 GB 内存、25 GB SSD 可用空间 | 8 vCPU、16 GB 内存 | 镜像构建、源码挂载和 sandbox 容器都会比纯本地模式更吃资源。 |
+| 长期运行服务 / `make up` | 8 vCPU、16 GB 内存、40 GB SSD 可用空间 | 16 vCPU、32 GB 内存 | 更适合共享环境、多 agent 任务、报告生成或更重的 sandbox 负载。 |
+
+- 上面的配置只覆盖 DeerFlow 本身；如果你还要本机部署本地大模型，请单独为模型服务预留资源。
+- 持续运行的服务更推荐使用 Linux + Docker。macOS 和 Windows 更适合作为开发机或体验环境。
+- 如果 CPU 或内存长期打满，先降低并发会话或重任务数量，再考虑升级到更高一档配置。
+
 #### 方式一：Docker（推荐）
 
 **开发模式**（支持热更新，挂载源码）：

backend/CLAUDE.md

@@ -293,10 +293,17 @@ Proxied through nginx: `/api/langgraph/*` → LangGraph, all other `/api/*` →
 
 - `create_chat_model(name, thinking_enabled)` instantiates LLM from config via reflection
 - Supports `thinking_enabled` flag with per-model `when_thinking_enabled` overrides
+- Supports vLLM-style thinking toggles via `when_thinking_enabled.extra_body.chat_template_kwargs.enable_thinking` for Qwen reasoning models, while normalizing legacy `thinking` configs for backward compatibility
 - Supports `supports_vision` flag for image understanding models
 - Config values starting with `$` resolved as environment variables
 - Missing provider modules surface actionable install hints from reflection resolvers (for example `uv add langchain-google-genai`)
 
+### vLLM Provider (`packages/harness/deerflow/models/vllm_provider.py`)
+
+- `VllmChatModel` subclasses `langchain_openai:ChatOpenAI` for vLLM 0.19.0 OpenAI-compatible endpoints
+- Preserves vLLM's non-standard assistant `reasoning` field on full responses, streaming deltas, and follow-up tool-call turns
+- Designed for configs that enable thinking through `extra_body.chat_template_kwargs.enable_thinking` on vLLM 0.19.0 Qwen reasoning models, while accepting the older `thinking` alias
+
 ### IM Channels System (`app/channels/`)
 
 Bridges external messaging platforms (Feishu, Slack, Telegram) to the DeerFlow agent via the LangGraph Server.
@@ -365,6 +372,7 @@ Focused regression coverage for the updater lives in `backend/tests/test_memory_
 
 **`config.yaml`** key sections:
 - `models[]` - LLM configs with `use` class path, `supports_thinking`, `supports_vision`, provider-specific fields
+- vLLM reasoning models should use `deerflow.models.vllm_provider:VllmChatModel`; for Qwen-style parsers prefer `when_thinking_enabled.extra_body.chat_template_kwargs.enable_thinking`, and DeerFlow will also normalize the older `thinking` alias
 - `tools[]` - Tool configs with `use` variable path and `group`
 - `tool_groups[]` - Logical groupings for tools
 - `sandbox.use` - Sandbox provider class path
@@ -387,14 +395,16 @@ Both can be modified at runtime via Gateway API endpoints or `DeerFlowClient` me
 **Architecture**: Imports the same `deerflow` modules that LangGraph Server and Gateway API use. Shares the same config files and data directories. No FastAPI dependency.
 
 **Agent Conversation** (replaces LangGraph Server):
-- `chat(message, thread_id)` — synchronous, returns final text
-- `stream(message, thread_id)` — yields `StreamEvent` aligned with LangGraph SSE protocol:
-  - `"values"` — full state snapshot (title, messages, artifacts)
-  - `"messages-tuple"` — per-message update (AI text, tool calls, tool results)
-  - `"end"` — stream finished
+- `chat(message, thread_id)` — synchronous, accumulates streaming deltas per message-id and returns the final AI text
+- `stream(message, thread_id)` — subscribes to LangGraph `stream_mode=["values", "messages", "custom"]` and yields `StreamEvent`:
+  - `"values"` — full state snapshot (title, messages, artifacts); AI text already delivered via `messages` mode is **not** re-synthesized here to avoid duplicate deliveries
+  - `"messages-tuple"` — per-chunk update: for AI text this is a **delta** (concat per `id` to rebuild the full message); tool calls and tool results are emitted once each
+  - `"custom"` — forwarded from `StreamWriter`
+  - `"end"` — stream finished (carries cumulative `usage` counted once per message id)
 - Agent created lazily via `create_agent()` + `_build_middlewares()`, same as `make_lead_agent`
 - Supports `checkpointer` parameter for state persistence across turns
 - `reset_agent()` forces agent recreation (e.g. after memory or skill changes)
+- See [docs/STREAMING.md](docs/STREAMING.md) for the full design: why Gateway and DeerFlowClient are parallel paths, LangGraph's `stream_mode` semantics, the per-id dedup invariants, and regression testing strategy
 
 **Gateway Equivalent Methods** (replaces Gateway API):
 

backend/Dockerfile

@@ -11,39 +11,29 @@ FROM ${UV_IMAGE} AS uv-source
 FROM python:3.12-slim-bookworm AS builder
 
 ARG NODE_MAJOR=22
-ARG NODE_VERSION=22.16.0
 ARG APT_MIRROR
 ARG UV_INDEX_URL
-ARG NODE_DIST_URL
+# Optional extras to install (e.g. "postgres" for PostgreSQL support)
+# Usage: docker build --build-arg UV_EXTRAS=postgres ...
+ARG UV_EXTRAS
 
-# Optionally override apt mirror for restricted networks (e.g. APT_MIRROR=mirrors.byted.org)
+# Optionally override apt mirror for restricted networks (e.g. APT_MIRROR=mirrors.aliyun.com)
 RUN if [ -n "${APT_MIRROR}" ]; then \
       sed -i "s|deb.debian.org|${APT_MIRROR}|g" /etc/apt/sources.list.d/debian.sources 2>/dev/null || true; \
       sed -i "s|deb.debian.org|${APT_MIRROR}|g" /etc/apt/sources.list 2>/dev/null || true; \
     fi
 
 # Install build tools + Node.js (build-essential needed for native Python extensions)
-# NODE_DIST_URL: base URL for Node.js binary tarballs in restricted networks.
-#   npmmirror: https://registry.npmmirror.com/-/binary/node
-#   official:  https://nodejs.org/dist  (default, via nodesource apt)
 RUN apt-get update && apt-get install -y \
     curl \
     build-essential \
     gnupg \
     ca-certificates \
-    xz-utils \
-    && if [ -n "${NODE_DIST_URL}" ]; then \
-         curl -fsSL "${NODE_DIST_URL}/v${NODE_VERSION}/node-v${NODE_VERSION}-linux-x64.tar.xz" \
-           | tar -xJ --strip-components=1 -C /usr/local \
-         && ln -sf /usr/local/bin/node /usr/bin/node \
-         && ln -sf /usr/local/lib/node_modules /usr/lib/node_modules; \
-       else \
-         mkdir -p /etc/apt/keyrings \
-         && curl -fsSL https://deb.nodesource.com/gpgkey/nodesource-repo.gpg.key | gpg --dearmor -o /etc/apt/keyrings/nodesource.gpg \
-         && echo "deb [signed-by=/etc/apt/keyrings/nodesource.gpg] https://deb.nodesource.com/node_${NODE_MAJOR}.x nodistro main" > /etc/apt/sources.list.d/nodesource.list \
-         && apt-get update \
-         && apt-get install -y nodejs; \
-       fi \
+    && mkdir -p /etc/apt/keyrings \
+    && curl -fsSL https://deb.nodesource.com/gpgkey/nodesource-repo.gpg.key | gpg --dearmor -o /etc/apt/keyrings/nodesource.gpg \
+    && echo "deb [signed-by=/etc/apt/keyrings/nodesource.gpg] https://deb.nodesource.com/node_${NODE_MAJOR}.x nodistro main" > /etc/apt/sources.list.d/nodesource.list \
+    && apt-get update \
+    && apt-get install -y nodejs \
     && rm -rf /var/lib/apt/lists/*
 
 # Install uv (source image overridable via UV_IMAGE build arg)
@@ -56,8 +46,9 @@ WORKDIR /app
 COPY backend ./backend
 
 # Install dependencies with cache mount
+# When UV_EXTRAS is set (e.g. "postgres"), installs optional dependencies.
 RUN --mount=type=cache,target=/root/.cache/uv \
-    sh -c "cd backend && UV_INDEX_URL=${UV_INDEX_URL:-https://pypi.org/simple} uv sync"
+    sh -c "cd backend && UV_INDEX_URL=${UV_INDEX_URL:-https://pypi.org/simple} uv sync ${UV_EXTRAS:+--extra $UV_EXTRAS}"
 
 # ── Stage 2: Dev ──────────────────────────────────────────────────────────────
 # Retains compiler toolchain from builder so startup-time `uv sync` can build
@@ -97,4 +88,4 @@ COPY --from=builder /app/backend ./backend
 EXPOSE 8001 2024
 
 # Default command (can be overridden in docker-compose)
-CMD ["sh", "-c", "cd backend && PYTHONPATH=. uv run uvicorn app.gateway.app:app --host 0.0.0.0 --port 8001"]
+CMD ["sh", "-c", "cd backend && PYTHONPATH=. uv run --no-sync uvicorn app.gateway.app:app --host 0.0.0.0 --port 8001"]

backend/app/channels/base.py

@@ -106,3 +106,21 @@ class Channel(ABC):
                         logger.warning("[%s] file upload skipped for %s", self.name, attachment.filename)
                 except Exception:
                     logger.exception("[%s] failed to upload file %s", self.name, attachment.filename)
+
+    async def receive_file(self, msg: InboundMessage, thread_id: str) -> InboundMessage:
+        """
+        Optionally process and materialize inbound file attachments for this channel.
+
+        By default, this method does nothing and simply returns the original message.
+        Subclasses (e.g. FeishuChannel) may override this to download files (images, documents, etc)
+        referenced in msg.files, save them to the sandbox, and update msg.text to include
+        the sandbox file paths for downstream model consumption.
+
+        Args:
+            msg: The inbound message, possibly containing file metadata in msg.files.
+            thread_id: The resolved DeerFlow thread ID for sandbox path context.
+
+        Returns:
+            The (possibly modified) InboundMessage, with text and/or files updated as needed.
+        """
+        return msg

backend/app/channels/feishu.py

@@ -5,12 +5,15 @@ from __future__ import annotations
 import asyncio
 import json
 import logging
+import re
 import threading
-from typing import Any
+from typing import Any, Literal
 
 from app.channels.base import Channel
 from app.channels.commands import KNOWN_CHANNEL_COMMANDS
-from app.channels.message_bus import InboundMessageType, MessageBus, OutboundMessage, ResolvedAttachment
+from app.channels.message_bus import InboundMessage, InboundMessageType, MessageBus, OutboundMessage, ResolvedAttachment
+from deerflow.config.paths import VIRTUAL_PATH_PREFIX, get_paths
+from deerflow.sandbox.sandbox_provider import get_sandbox_provider
 
 logger = logging.getLogger(__name__)
 
@@ -56,6 +59,8 @@ class FeishuChannel(Channel):
         self._CreateFileRequestBody = None
         self._CreateImageRequest = None
         self._CreateImageRequestBody = None
+        self._GetMessageResourceRequest = None
+        self._thread_lock = threading.Lock()
 
     async def start(self) -> None:
         if self._running:
@@ -73,6 +78,7 @@ class FeishuChannel(Channel):
                 CreateMessageRequest,
                 CreateMessageRequestBody,
                 Emoji,
+                GetMessageResourceRequest,
                 PatchMessageRequest,
                 PatchMessageRequestBody,
                 ReplyMessageRequest,
@@ -96,6 +102,7 @@ class FeishuChannel(Channel):
         self._CreateFileRequestBody = CreateFileRequestBody
         self._CreateImageRequest = CreateImageRequest
         self._CreateImageRequestBody = CreateImageRequestBody
+        self._GetMessageResourceRequest = GetMessageResourceRequest
 
         app_id = self.config.get("app_id", "")
         app_secret = self.config.get("app_secret", "")
@@ -275,6 +282,112 @@ class FeishuChannel(Channel):
             raise RuntimeError(f"Feishu file upload failed: code={response.code}, msg={response.msg}")
         return response.data.file_key
 
+    async def receive_file(self, msg: InboundMessage, thread_id: str) -> InboundMessage:
+        """Download a Feishu file into the thread uploads directory.
+
+        Returns the sandbox virtual path when the image is persisted successfully.
+        """
+        if not msg.thread_ts:
+            logger.warning("[Feishu] received file message without thread_ts, cannot associate with conversation: %s", msg)
+            return msg
+        files = msg.files
+        if not files:
+            logger.warning("[Feishu] received message with no files: %s", msg)
+            return msg
+        text = msg.text
+        for file in files:
+            if file.get("image_key"):
+                virtual_path = await self._receive_single_file(msg.thread_ts, file["image_key"], "image", thread_id)
+                text = text.replace("[image]", virtual_path, 1)
+            elif file.get("file_key"):
+                virtual_path = await self._receive_single_file(msg.thread_ts, file["file_key"], "file", thread_id)
+                text = text.replace("[file]", virtual_path, 1)
+        msg.text = text
+        return msg
+
+    async def _receive_single_file(self, message_id: str, file_key: str, type: Literal["image", "file"], thread_id: str) -> str:
+        request = self._GetMessageResourceRequest.builder().message_id(message_id).file_key(file_key).type(type).build()
+
+        def inner():
+            return self._api_client.im.v1.message_resource.get(request)
+
+        try:
+            response = await asyncio.to_thread(inner)
+        except Exception:
+            logger.exception("[Feishu] resource get request failed for resource_key=%s type=%s", file_key, type)
+            return f"Failed to obtain the [{type}]"
+
+        if not response.success():
+            logger.warning(
+                "[Feishu] resource get failed: resource_key=%s, type=%s, code=%s, msg=%s, log_id=%s ",
+                file_key,
+                type,
+                response.code,
+                response.msg,
+                response.get_log_id(),
+            )
+            return f"Failed to obtain the [{type}]"
+
+        image_stream = getattr(response, "file", None)
+        if image_stream is None:
+            logger.warning("[Feishu] resource get returned no file stream: resource_key=%s, type=%s", file_key, type)
+            return f"Failed to obtain the [{type}]"
+
+        try:
+            content: bytes = await asyncio.to_thread(image_stream.read)
+        except Exception:
+            logger.exception("[Feishu] failed to read resource stream: resource_key=%s, type=%s", file_key, type)
+            return f"Failed to obtain the [{type}]"
+
+        if not content:
+            logger.warning("[Feishu] empty resource content: resource_key=%s, type=%s", file_key, type)
+            return f"Failed to obtain the [{type}]"
+
+        paths = get_paths()
+        paths.ensure_thread_dirs(thread_id)
+        uploads_dir = paths.sandbox_uploads_dir(thread_id).resolve()
+
+        ext = "png" if type == "image" else "bin"
+        raw_filename = getattr(response, "file_name", "") or f"feishu_{file_key[-12:]}.{ext}"
+
+        # Sanitize filename: preserve extension, replace path chars in name part
+        if "." in raw_filename:
+            name_part, ext = raw_filename.rsplit(".", 1)
+            name_part = re.sub(r"[./\\]", "_", name_part)
+            filename = f"{name_part}.{ext}"
+        else:
+            filename = re.sub(r"[./\\]", "_", raw_filename)
+        resolved_target = uploads_dir / filename
+
+        def down_load():
+            # use thread_lock to avoid filename conflicts when writing
+            with self._thread_lock:
+                resolved_target.write_bytes(content)
+
+        try:
+            await asyncio.to_thread(down_load)
+        except Exception:
+            logger.exception("[Feishu] failed to persist downloaded resource: %s, type=%s", resolved_target, type)
+            return f"Failed to obtain the [{type}]"
+
+        virtual_path = f"{VIRTUAL_PATH_PREFIX}/uploads/{resolved_target.name}"
+
+        try:
+            sandbox_provider = get_sandbox_provider()
+            sandbox_id = sandbox_provider.acquire(thread_id)
+            if sandbox_id != "local":
+                sandbox = sandbox_provider.get(sandbox_id)
+                if sandbox is None:
+                    logger.warning("[Feishu] sandbox not found for thread_id=%s", thread_id)
+                    return f"Failed to obtain the [{type}]"
+                sandbox.update_file(virtual_path, content)
+        except Exception:
+            logger.exception("[Feishu] failed to sync resource into non-local sandbox: %s", virtual_path)
+            return f"Failed to obtain the [{type}]"
+
+        logger.info("[Feishu] downloaded resource mapped: file_key=%s -> %s", file_key, virtual_path)
+        return virtual_path
+
     # -- message formatting ------------------------------------------------
 
     @staticmethod
@@ -479,9 +592,28 @@ class FeishuChannel(Channel):
             # Parse message content
             content = json.loads(message.content)
 
+            # files_list store the any-file-key in feishu messages, which can be used to download the file content later
+            # In Feishu channel, image_keys are independent of file_keys.
+            # The file_key includes files, videos, and audio, but does not include stickers.
+            files_list = []
+
             if "text" in content:
                 # Handle plain text messages
                 text = content["text"]
+            elif "file_key" in content:
+                file_key = content.get("file_key")
+                if isinstance(file_key, str) and file_key:
+                    files_list.append({"file_key": file_key})
+                    text = "[file]"
+                else:
+                    text = ""
+            elif "image_key" in content:
+                image_key = content.get("image_key")
+                if isinstance(image_key, str) and image_key:
+                    files_list.append({"image_key": image_key})
+                    text = "[image]"
+                else:
+                    text = ""
             elif "content" in content and isinstance(content["content"], list):
                 # Handle rich-text messages with a top-level "content" list (e.g., topic groups/posts)
                 text_paragraphs: list[str] = []
@@ -495,6 +627,16 @@ class FeishuChannel(Channel):
                                     text_value = element.get("text", "")
                                     if text_value:
                                         paragraph_text_parts.append(text_value)
+                                elif element.get("tag") == "img":
+                                    image_key = element.get("image_key")
+                                    if isinstance(image_key, str) and image_key:
+                                        files_list.append({"image_key": image_key})
+                                        paragraph_text_parts.append("[image]")
+                                elif element.get("tag") in ("file", "media"):
+                                    file_key = element.get("file_key")
+                                    if isinstance(file_key, str) and file_key:
+                                        files_list.append({"file_key": file_key})
+                                        paragraph_text_parts.append("[file]")
                         if paragraph_text_parts:
                             # Join text segments within a paragraph with spaces to avoid "helloworld"
                             text_paragraphs.append(" ".join(paragraph_text_parts))
@@ -514,7 +656,7 @@ class FeishuChannel(Channel):
                 text[:100] if text else "",
             )
 
-            if not text:
+            if not (text or files_list):
                 logger.info("[Feishu] empty text, ignoring message")
                 return
 
@@ -534,6 +676,7 @@ class FeishuChannel(Channel):
                 text=text,
                 msg_type=msg_type,
                 thread_ts=msg_id,
+                files=files_list,
                 metadata={"message_id": msg_id, "root_id": root_id},
             )
             inbound.topic_id = topic_id

backend/app/channels/manager.py

@@ -8,6 +8,7 @@ import mimetypes
 import re
 import time
 from collections.abc import Awaitable, Callable, Mapping
+from pathlib import Path
 from typing import Any
 
 import httpx
@@ -37,6 +38,7 @@ CHANNEL_CAPABILITIES = {
     "feishu": {"supports_streaming": True},
     "slack": {"supports_streaming": False},
     "telegram": {"supports_streaming": False},
+    "wechat": {"supports_streaming": False},
     "wecom": {"supports_streaming": True},
 }
 
@@ -78,7 +80,24 @@ async def _read_wecom_inbound_file(file_info: dict[str, Any], client: httpx.Asyn
     return decrypt_file(data, aeskey)
 
 
+async def _read_wechat_inbound_file(file_info: dict[str, Any], client: httpx.AsyncClient) -> bytes | None:
+    raw_path = file_info.get("path")
+    if isinstance(raw_path, str) and raw_path.strip():
+        try:
+            return await asyncio.to_thread(Path(raw_path).read_bytes)
+        except OSError:
+            logger.exception("[Manager] failed to read WeChat inbound file from local path: %s", raw_path)
+            return None
+
+    full_url = file_info.get("full_url")
+    if isinstance(full_url, str) and full_url.strip():
+        return await _read_http_inbound_file({"url": full_url}, client)
+
+    return None
+
+
 register_inbound_file_reader("wecom", _read_wecom_inbound_file)
+register_inbound_file_reader("wechat", _read_wechat_inbound_file)
 
 
 class InvalidChannelSessionConfigError(ValueError):
@@ -675,6 +694,18 @@ class ChannelManager:
             thread_id = await self._create_thread(client, msg)
 
         assistant_id, run_config, run_context = self._resolve_run_params(msg, thread_id)
+
+        # If the inbound message contains file attachments, let the channel
+        # materialize (download) them and update msg.text to include sandbox file paths.
+        # This enables downstream models to access user-uploaded files by path.
+        # Channels that do not support file download will simply return the original message.
+        if msg.files:
+            from .service import get_channel_service
+
+            service = get_channel_service()
+            channel = service.get_channel(msg.channel_name) if service else None
+            logger.info("[Manager] preparing receive file context for %d attachments", len(msg.files))
+            msg = await channel.receive_file(msg, thread_id) if channel else msg
         if extra_context:
             run_context.update(extra_context)
 

backend/app/channels/service.py

@@ -6,6 +6,7 @@ import logging
 import os
 from typing import Any
 
+from app.channels.base import Channel
 from app.channels.manager import DEFAULT_GATEWAY_URL, DEFAULT_LANGGRAPH_URL, ChannelManager
 from app.channels.message_bus import MessageBus
 from app.channels.store import ChannelStore
@@ -17,6 +18,7 @@ _CHANNEL_REGISTRY: dict[str, str] = {
     "feishu": "app.channels.feishu:FeishuChannel",
     "slack": "app.channels.slack:SlackChannel",
     "telegram": "app.channels.telegram:TelegramChannel",
+    "wechat": "app.channels.wechat:WechatChannel",
     "wecom": "app.channels.wecom:WeComChannel",
 }
 
@@ -164,6 +166,10 @@ class ChannelService:
             "channels": channels_status,
         }
 
+    def get_channel(self, name: str) -> Channel | None:
+        """Return a running channel instance by name when available."""
+        return self._channels.get(name)
+
 
 # -- singleton access -------------------------------------------------------
 

backend/app/gateway/app.py

@@ -17,6 +17,7 @@ from app.gateway.routers import (
     assistants_compat,
     auth,
     channels,
+    feedback,
     mcp,
     memory,
     models,
@@ -42,83 +43,120 @@ logger = logging.getLogger(__name__)
 async def _ensure_admin_user(app: FastAPI) -> None:
     """Auto-create the admin user on first boot if no users exist.
 
-    Prints the generated password to stdout so the operator can log in.
-    On subsequent boots, warns if any user still needs setup.
+    After admin creation, migrate orphan threads from the LangGraph
+    store (metadata.owner_id unset) to the admin account. This is the
+    "no-auth → with-auth" upgrade path: users who ran DeerFlow without
+    authentication have existing LangGraph thread data that needs an
+    owner assigned.
 
-    Multi-worker safe: relies on SQLite UNIQUE constraint to resolve races.
-    Only the worker that successfully creates/updates the admin prints the
-    password; losers silently skip.
+    No SQL persistence migration is needed: the four owner_id columns
+    (threads_meta, runs, run_events, feedback) only come into existence
+    alongside the auth module via create_all, so freshly created tables
+    never contain NULL-owner rows. "Existing persistence DB + new auth"
+    is not a supported upgrade path — fresh install or wipe-and-retry.
+
+    Multi-worker safe: relies on SQLite UNIQUE constraint to resolve
+    races during admin creation. Only the worker that successfully
+    creates/updates the admin prints the password; losers silently skip.
     """
     import secrets
 
+    from app.gateway.auth.credential_file import write_initial_credentials
     from app.gateway.deps import get_local_provider
 
+    def _announce_credentials(email: str, password: str, *, label: str, headline: str) -> None:
+        """Write the password to a 0600 file and log the path (never the secret)."""
+        cred_path = write_initial_credentials(email, password, label=label)
+        logger.info("=" * 60)
+        logger.info("  %s", headline)
+        logger.info("  Credentials written to: %s (mode 0600)", cred_path)
+        logger.info("  Change it after login: Settings -> Account")
+        logger.info("=" * 60)
+
     provider = get_local_provider()
     user_count = await provider.count_users()
 
+    admin = None
+
     if user_count == 0:
         password = secrets.token_urlsafe(16)
         try:
             admin = await provider.create_user(email="admin@deerflow.dev", password=password, system_role="admin", needs_setup=True)
         except ValueError:
             return  # Another worker already created the admin.
+        _announce_credentials(admin.email, password, label="initial", headline="Admin account created on first boot")
+    else:
+        # Admin exists but setup never completed — reset password so operator
+        # can always find it in the console without needing the CLI.
+        # Multi-worker guard: if admin was created less than 30s ago, another
+        # worker just created it and will print the password — skip reset.
+        admin = await provider.get_user_by_email("admin@deerflow.dev")
+        if admin and admin.needs_setup:
+            import time
 
-        # Migrate orphaned threads (no user_id) to this admin
-        store = getattr(app.state, "store", None)
-        if store is not None:
-            await _migrate_orphaned_threads(store, str(admin.id))
+            age = time.time() - admin.created_at.replace(tzinfo=UTC).timestamp()
+            if age >= 30:
+                from app.gateway.auth.password import hash_password_async
 
-        logger.info("=" * 60)
-        logger.info("  Admin account created on first boot")
-        logger.info("  Email:    %s", admin.email)
-        logger.info("  Password: %s", password)
-        logger.info("  Change it after login: Settings -> Account")
-        logger.info("=" * 60)
-        return
+                password = secrets.token_urlsafe(16)
+                admin.password_hash = await hash_password_async(password)
+                admin.token_version += 1
+                await provider.update_user(admin)
+                _announce_credentials(admin.email, password, label="reset", headline="Admin account setup incomplete — password reset")
 
-    # Admin exists but setup never completed — reset password so operator
-    # can always find it in the console without needing the CLI.
-    # Multi-worker guard: if admin was created less than 5s ago, another
-    # worker just created it and will print the password — skip reset.
-    admin = await provider.get_user_by_email("admin@deerflow.dev")
-    if admin and admin.needs_setup:
-        import time
+    if admin is None:
+        return  # Nothing to bind orphans to.
 
-        age = time.time() - admin.created_at.replace(tzinfo=UTC).timestamp()
-        if age < 30:
-            return  # Just created by another worker in this startup; its password is still valid.
+    admin_id = str(admin.id)
 
-        from app.gateway.auth.password import hash_password_async
-
-        password = secrets.token_urlsafe(16)
-        admin.password_hash = await hash_password_async(password)
-        admin.token_version += 1
-        await provider.update_user(admin)
-
-        logger.info("=" * 60)
-        logger.info("  Admin account setup incomplete — password reset")
-        logger.info("  Email:    %s", admin.email)
-        logger.info("  Password: %s", password)
-        logger.info("  Change it after login: Settings -> Account")
-        logger.info("=" * 60)
+    # LangGraph store orphan migration — non-fatal.
+    # This covers the "no-auth → with-auth" upgrade path for users
+    # whose existing LangGraph thread metadata has no owner_id set.
+    store = getattr(app.state, "store", None)
+    if store is not None:
+        try:
+            migrated = await _migrate_orphaned_threads(store, admin_id)
+            if migrated:
+                logger.info("Migrated %d orphan LangGraph thread(s) to admin", migrated)
+        except Exception:
+            logger.exception("LangGraph thread migration failed (non-fatal)")
 
 
-async def _migrate_orphaned_threads(store, admin_user_id: str) -> None:
-    """Migrate threads with no user_id to the given admin."""
-    try:
-        migrated = 0
-        results = await store.asearch(("threads",), limit=1000)
-        for item in results:
-            metadata = item.value.get("metadata", {})
-            if not metadata.get("user_id"):
-                metadata["user_id"] = admin_user_id
-                item.value["metadata"] = metadata
-                await store.aput(("threads",), item.key, item.value)
-                migrated += 1
-        if migrated:
-            logger.info("Migrated %d orphaned thread(s) to admin", migrated)
-    except Exception:
-        logger.exception("Thread migration failed (non-fatal)")
+async def _iter_store_items(store, namespace, *, page_size: int = 500):
+    """Paginated async iterator over a LangGraph store namespace.
+
+    Replaces the old hardcoded ``limit=1000`` call with a cursor-style
+    loop so that environments with more than one page of orphans do
+    not silently lose data. Terminates when a page is empty OR when a
+    short page arrives (indicating the last page).
+    """
+    offset = 0
+    while True:
+        batch = await store.asearch(namespace, limit=page_size, offset=offset)
+        if not batch:
+            return
+        for item in batch:
+            yield item
+        if len(batch) < page_size:
+            return
+        offset += page_size
+
+
+async def _migrate_orphaned_threads(store, admin_user_id: str) -> int:
+    """Migrate LangGraph store threads with no owner_id to the given admin.
+
+    Uses cursor pagination so all orphans are migrated regardless of
+    count. Returns the number of rows migrated.
+    """
+    migrated = 0
+    async for item in _iter_store_items(store, ("threads",)):
+        metadata = item.value.get("metadata", {})
+        if not metadata.get("owner_id"):
+            metadata["owner_id"] = admin_user_id
+            item.value["metadata"] = metadata
+            await store.aput(("threads",), item.key, item.value)
+            migrated += 1
+    return migrated
 
 
 @asynccontextmanager
@@ -261,7 +299,8 @@ This gateway provides custom endpoints for models, MCP configuration, skills, an
     # CSRF: Double Submit Cookie pattern for state-changing requests
     app.add_middleware(CSRFMiddleware)
 
-    # CORS: when GATEWAY_CORS_ORIGINS is set (dev without nginx), add CORS middleware
+    # CORS: when GATEWAY_CORS_ORIGINS is set (dev without nginx), add CORS middleware.
+    # In production, nginx handles CORS and no middleware is needed.
     cors_origins_env = os.environ.get("GATEWAY_CORS_ORIGINS", "")
     if cors_origins_env:
         cors_origins = [o.strip() for o in cors_origins_env.split(",") if o.strip()]
@@ -317,6 +356,9 @@ This gateway provides custom endpoints for models, MCP configuration, skills, an
     # Auth API is mounted at /api/v1/auth
     app.include_router(auth.router)
 
+    # Feedback API is mounted at /api/threads/{thread_id}/runs/{run_id}/feedback
+    app.include_router(feedback.router)
+
     # Thread Runs API (LangGraph Platform-compatible runs lifecycle)
     app.include_router(thread_runs.router)
 

backend/app/gateway/auth/config.py

@@ -13,17 +13,19 @@ logger = logging.getLogger(__name__)
 
 
 class AuthConfig(BaseModel):
-    """JWT and auth-related configuration. Parsed once at startup."""
+    """JWT and auth-related configuration. Parsed once at startup.
+
+    Note: the ``users`` table now lives in the shared persistence
+    database managed by ``deerflow.persistence.engine``. The old
+    ``users_db_path`` config key has been removed — user storage is
+    configured through ``config.database`` like every other table.
+    """
 
     jwt_secret: str = Field(
         ...,
         description="Secret key for JWT signing. MUST be set via AUTH_JWT_SECRET.",
     )
     token_expiry_days: int = Field(default=7, ge=1, le=30)
-    users_db_path: str | None = Field(
-        default=None,
-        description="Path to users SQLite DB. Defaults to .deer-flow/users.db",
-    )
     oauth_github_client_id: str | None = Field(default=None)
     oauth_github_client_secret: str | None = Field(default=None)
 

backend/app/gateway/auth/credential_file.py

@@ -0,0 +1,48 @@
+"""Write initial admin credentials to a restricted file instead of logs.
+
+Logging secrets to stdout/stderr is a well-known CodeQL finding
+(py/clear-text-logging-sensitive-data) — in production those logs
+get collected into ELK/Splunk/etc and become a secret sprawl
+source. This helper writes the credential to a 0600 file that only
+the process user can read, and returns the path so the caller can
+log **the path** (not the password) for the operator to pick up.
+"""
+
+from __future__ import annotations
+
+import os
+from pathlib import Path
+
+from deerflow.config.paths import get_paths
+
+_CREDENTIAL_FILENAME = "admin_initial_credentials.txt"
+
+
+def write_initial_credentials(email: str, password: str, *, label: str = "initial") -> Path:
+    """Write the admin email + password to ``{base_dir}/admin_initial_credentials.txt``.
+
+    The file is created **atomically** with mode 0600 via ``os.open``
+    so the password is never world-readable, even for the single syscall
+    window between ``write_text`` and ``chmod``.
+
+    ``label`` distinguishes "initial" (fresh creation) from "reset"
+    (password reset) in the file header so an operator picking up the
+    file after a restart can tell which event produced it.
+
+    Returns the absolute :class:`Path` to the file.
+    """
+    target = get_paths().base_dir / _CREDENTIAL_FILENAME
+    target.parent.mkdir(parents=True, exist_ok=True)
+
+    content = (
+        f"# DeerFlow admin {label} credentials\n# This file is generated on first boot or password reset.\n# Change the password after login via Settings -> Account,\n# then delete this file.\n#\nemail: {email}\npassword: {password}\n"
+    )
+
+    # Atomic 0600 create-or-truncate. O_TRUNC (not O_EXCL) so the
+    # reset-password path can rewrite an existing file without a
+    # separate unlink-then-create dance.
+    fd = os.open(target, os.O_WRONLY | os.O_CREAT | os.O_TRUNC, 0o600)
+    with os.fdopen(fd, "w", encoding="utf-8") as fh:
+        fh.write(content)
+
+    return target.resolve()

backend/app/gateway/auth/repositories/base.py

@@ -5,6 +5,16 @@ from abc import ABC, abstractmethod
 from app.gateway.auth.models import User
 
 
+class UserNotFoundError(LookupError):
+    """Raised when a user repository operation targets a non-existent row.
+
+    Subclass of :class:`LookupError` so callers that already catch
+    ``LookupError`` for "missing entity" can keep working unchanged,
+    while specific call sites can pin to this class to distinguish
+    "concurrent delete during update" from other lookups.
+    """
+
+
 class UserRepository(ABC):
     """Abstract interface for user data storage.
 
@@ -60,6 +70,11 @@ class UserRepository(ABC):
 
         Returns:
             Updated User
+
+        Raises:
+            UserNotFoundError: If no row exists for ``user.id``. This is
+                a hard failure (not a no-op) so callers cannot mistake a
+                concurrent-delete race for a successful update.
         """
         ...
 

backend/app/gateway/auth/repositories/sqlite.py

@@ -1,196 +1,122 @@
-"""SQLite implementation of UserRepository."""
+"""SQLAlchemy-backed UserRepository implementation.
 
-import asyncio
-import sqlite3
-from contextlib import contextmanager
-from datetime import UTC, datetime
-from pathlib import Path
-from typing import Any
+Uses the shared async session factory from
+``deerflow.persistence.engine`` — the ``users`` table lives in the
+same database as ``threads_meta``, ``runs``, ``run_events``, and
+``feedback``.
+
+Constructor takes the session factory directly (same pattern as the
+other four repositories in ``deerflow.persistence.*``). Callers
+construct this after ``init_engine_from_config()`` has run.
+"""
+
+from __future__ import annotations
+
+from datetime import UTC
 from uuid import UUID
 
-from app.gateway.auth.config import get_auth_config
+from sqlalchemy import func, select
+from sqlalchemy.exc import IntegrityError
+from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker
+
 from app.gateway.auth.models import User
-from app.gateway.auth.repositories.base import UserRepository
-
-_resolved_db_path: Path | None = None
-_table_initialized: bool = False
-
-
-def _get_users_db_path() -> Path:
-    """Get the users database path (resolved and cached once)."""
-    global _resolved_db_path
-    if _resolved_db_path is not None:
-        return _resolved_db_path
-    config = get_auth_config()
-    if config.users_db_path:
-        _resolved_db_path = Path(config.users_db_path)
-    else:
-        _resolved_db_path = Path(".deer-flow/users.db")
-    _resolved_db_path.parent.mkdir(parents=True, exist_ok=True)
-    return _resolved_db_path
-
-
-def _get_connection() -> sqlite3.Connection:
-    """Get a SQLite connection for the users database."""
-    db_path = _get_users_db_path()
-    conn = sqlite3.connect(str(db_path))
-    conn.row_factory = sqlite3.Row
-    return conn
-
-
-def _init_users_table(conn: sqlite3.Connection) -> None:
-    """Initialize the users table if it doesn't exist."""
-    conn.execute("PRAGMA journal_mode=WAL")
-    conn.execute(
-        """
-        CREATE TABLE IF NOT EXISTS users (
-            id TEXT PRIMARY KEY,
-            email TEXT UNIQUE NOT NULL,
-            password_hash TEXT,
-            system_role TEXT NOT NULL DEFAULT 'user',
-            created_at REAL NOT NULL,
-            oauth_provider TEXT,
-            oauth_id TEXT,
-            needs_setup INTEGER NOT NULL DEFAULT 0,
-            token_version INTEGER NOT NULL DEFAULT 0
-        )
-    """
-    )
-    # Add unique constraint for OAuth identity to prevent duplicate social logins
-    conn.execute(
-        """
-        CREATE UNIQUE INDEX IF NOT EXISTS idx_users_oauth_identity
-        ON users(oauth_provider, oauth_id)
-        WHERE oauth_provider IS NOT NULL AND oauth_id IS NOT NULL
-    """
-    )
-    conn.commit()
-
-
-@contextmanager
-def _get_users_conn():
-    """Context manager for users database connection."""
-    global _table_initialized
-    conn = _get_connection()
-    try:
-        if not _table_initialized:
-            _init_users_table(conn)
-            _table_initialized = True
-        yield conn
-    finally:
-        conn.close()
+from app.gateway.auth.repositories.base import UserNotFoundError, UserRepository
+from deerflow.persistence.user.model import UserRow
 
 
 class SQLiteUserRepository(UserRepository):
-    """SQLite implementation of UserRepository."""
+    """Async user repository backed by the shared SQLAlchemy engine."""
+
+    def __init__(self, session_factory: async_sessionmaker[AsyncSession]) -> None:
+        self._sf = session_factory
+
+    # ── Converters ────────────────────────────────────────────────────
+
+    @staticmethod
+    def _row_to_user(row: UserRow) -> User:
+        return User(
+            id=UUID(row.id),
+            email=row.email,
+            password_hash=row.password_hash,
+            system_role=row.system_role,  # type: ignore[arg-type]
+            # SQLite loses tzinfo on read; reattach UTC so downstream
+            # code can compare timestamps reliably.
+            created_at=row.created_at if row.created_at.tzinfo else row.created_at.replace(tzinfo=UTC),
+            oauth_provider=row.oauth_provider,
+            oauth_id=row.oauth_id,
+            needs_setup=row.needs_setup,
+            token_version=row.token_version,
+        )
+
+    @staticmethod
+    def _user_to_row(user: User) -> UserRow:
+        return UserRow(
+            id=str(user.id),
+            email=user.email,
+            password_hash=user.password_hash,
+            system_role=user.system_role,
+            created_at=user.created_at,
+            oauth_provider=user.oauth_provider,
+            oauth_id=user.oauth_id,
+            needs_setup=user.needs_setup,
+            token_version=user.token_version,
+        )
+
+    # ── CRUD ──────────────────────────────────────────────────────────
 
     async def create_user(self, user: User) -> User:
-        """Create a new user in SQLite."""
-        return await asyncio.to_thread(self._create_user_sync, user)
-
-    def _create_user_sync(self, user: User) -> User:
-        """Synchronous user creation (runs in thread pool)."""
-        with _get_users_conn() as conn:
+        """Insert a new user. Raises ``ValueError`` on duplicate email."""
+        row = self._user_to_row(user)
+        async with self._sf() as session:
+            session.add(row)
             try:
-                conn.execute(
-                    """
-                    INSERT INTO users (id, email, password_hash, system_role, created_at, oauth_provider, oauth_id, needs_setup, token_version)
-                    VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)
-                    """,
-                    (
-                        str(user.id),
-                        user.email,
-                        user.password_hash,
-                        user.system_role,
-                        datetime.now(UTC).timestamp(),
-                        user.oauth_provider,
-                        user.oauth_id,
-                        int(user.needs_setup),
-                        user.token_version,
-                    ),
-                )
-                conn.commit()
-            except sqlite3.IntegrityError as e:
-                if "UNIQUE constraint failed: users.email" in str(e):
-                    raise ValueError(f"Email already registered: {user.email}") from e
-                raise
+                await session.commit()
+            except IntegrityError as exc:
+                await session.rollback()
+                raise ValueError(f"Email already registered: {user.email}") from exc
         return user
 
     async def get_user_by_id(self, user_id: str) -> User | None:
-        """Get user by ID from SQLite."""
-        return await asyncio.to_thread(self._get_user_by_id_sync, user_id)
-
-    def _get_user_by_id_sync(self, user_id: str) -> User | None:
-        """Synchronous get by ID (runs in thread pool)."""
-        with _get_users_conn() as conn:
-            cursor = conn.execute("SELECT * FROM users WHERE id = ?", (user_id,))
-            row = cursor.fetchone()
-            if row is None:
-                return None
-            return self._row_to_user(dict(row))
+        async with self._sf() as session:
+            row = await session.get(UserRow, user_id)
+            return self._row_to_user(row) if row is not None else None
 
     async def get_user_by_email(self, email: str) -> User | None:
-        """Get user by email from SQLite."""
-        return await asyncio.to_thread(self._get_user_by_email_sync, email)
-
-    def _get_user_by_email_sync(self, email: str) -> User | None:
-        """Synchronous get by email (runs in thread pool)."""
-        with _get_users_conn() as conn:
-            cursor = conn.execute("SELECT * FROM users WHERE email = ?", (email,))
-            row = cursor.fetchone()
-            if row is None:
-                return None
-            return self._row_to_user(dict(row))
+        stmt = select(UserRow).where(UserRow.email == email)
+        async with self._sf() as session:
+            result = await session.execute(stmt)
+            row = result.scalar_one_or_none()
+            return self._row_to_user(row) if row is not None else None
 
     async def update_user(self, user: User) -> User:
-        """Update an existing user in SQLite."""
-        return await asyncio.to_thread(self._update_user_sync, user)
-
-    def _update_user_sync(self, user: User) -> User:
-        with _get_users_conn() as conn:
-            conn.execute(
-                "UPDATE users SET email = ?, password_hash = ?, system_role = ?, oauth_provider = ?, oauth_id = ?, needs_setup = ?, token_version = ? WHERE id = ?",
-                (user.email, user.password_hash, user.system_role, user.oauth_provider, user.oauth_id, int(user.needs_setup), user.token_version, str(user.id)),
-            )
-            conn.commit()
+        async with self._sf() as session:
+            row = await session.get(UserRow, str(user.id))
+            if row is None:
+                # Hard fail on concurrent delete: callers (reset_admin,
+                # password change handlers, _ensure_admin_user) all
+                # fetched the user just before this call, so a missing
+                # row here means the row vanished underneath us. Silent
+                # success would let the caller log "password reset" for
+                # a row that no longer exists.
+                raise UserNotFoundError(f"User {user.id} no longer exists")
+            row.email = user.email
+            row.password_hash = user.password_hash
+            row.system_role = user.system_role
+            row.oauth_provider = user.oauth_provider
+            row.oauth_id = user.oauth_id
+            row.needs_setup = user.needs_setup
+            row.token_version = user.token_version
+            await session.commit()
         return user
 
     async def count_users(self) -> int:
-        """Return total number of registered users."""
-        return await asyncio.to_thread(self._count_users_sync)
-
-    def _count_users_sync(self) -> int:
-        with _get_users_conn() as conn:
-            cursor = conn.execute("SELECT COUNT(*) FROM users")
-            return cursor.fetchone()[0]
+        stmt = select(func.count()).select_from(UserRow)
+        async with self._sf() as session:
+            return await session.scalar(stmt) or 0
 
     async def get_user_by_oauth(self, provider: str, oauth_id: str) -> User | None:
-        """Get user by OAuth provider and ID from SQLite."""
-        return await asyncio.to_thread(self._get_user_by_oauth_sync, provider, oauth_id)
-
-    def _get_user_by_oauth_sync(self, provider: str, oauth_id: str) -> User | None:
-        """Synchronous get by OAuth (runs in thread pool)."""
-        with _get_users_conn() as conn:
-            cursor = conn.execute(
-                "SELECT * FROM users WHERE oauth_provider = ? AND oauth_id = ?",
-                (provider, oauth_id),
-            )
-            row = cursor.fetchone()
-            if row is None:
-                return None
-            return self._row_to_user(dict(row))
-
-    @staticmethod
-    def _row_to_user(row: dict[str, Any]) -> User:
-        """Convert a database row to a User model."""
-        return User(
-            id=UUID(row["id"]),
-            email=row["email"],
-            password_hash=row["password_hash"],
-            system_role=row["system_role"],
-            created_at=datetime.fromtimestamp(row["created_at"], tz=UTC),
-            oauth_provider=row.get("oauth_provider"),
-            oauth_id=row.get("oauth_id"),
-            needs_setup=bool(row["needs_setup"]),
-            token_version=int(row["token_version"]),
-        )
+        stmt = select(UserRow).where(UserRow.oauth_provider == provider, UserRow.oauth_id == oauth_id)
+        async with self._sf() as session:
+            result = await session.execute(stmt)
+            row = result.scalar_one_or_none()
+            return self._row_to_user(row) if row is not None else None

backend/app/gateway/auth/reset_admin.py

@@ -1,16 +1,81 @@
-"""CLI tool to reset admin password.
+"""CLI tool to reset an admin password.
 
 Usage:
     python -m app.gateway.auth.reset_admin
     python -m app.gateway.auth.reset_admin --email admin@example.com
+
+Writes the new password to ``.deer-flow/admin_initial_credentials.txt``
+(mode 0600) instead of printing it, so CI / log aggregators never see
+the cleartext secret.
 """
 
+from __future__ import annotations
+
 import argparse
+import asyncio
 import secrets
 import sys
 
+from sqlalchemy import select
+
+from app.gateway.auth.credential_file import write_initial_credentials
 from app.gateway.auth.password import hash_password
 from app.gateway.auth.repositories.sqlite import SQLiteUserRepository
+from deerflow.persistence.user.model import UserRow
+
+
+async def _run(email: str | None) -> int:
+    from deerflow.config import get_app_config
+    from deerflow.persistence.engine import (
+        close_engine,
+        get_session_factory,
+        init_engine_from_config,
+    )
+
+    config = get_app_config()
+    await init_engine_from_config(config.database)
+    try:
+        sf = get_session_factory()
+        if sf is None:
+            print("Error: persistence engine not available (check config.database).", file=sys.stderr)
+            return 1
+
+        repo = SQLiteUserRepository(sf)
+
+        if email:
+            user = await repo.get_user_by_email(email)
+        else:
+            # Find first admin via direct SELECT — repository does not
+            # expose a "first admin" helper and we do not want to add
+            # one just for this CLI.
+            async with sf() as session:
+                stmt = select(UserRow).where(UserRow.system_role == "admin").limit(1)
+                row = (await session.execute(stmt)).scalar_one_or_none()
+            if row is None:
+                user = None
+            else:
+                user = await repo.get_user_by_id(row.id)
+
+        if user is None:
+            if email:
+                print(f"Error: user '{email}' not found.", file=sys.stderr)
+            else:
+                print("Error: no admin user found.", file=sys.stderr)
+            return 1
+
+        new_password = secrets.token_urlsafe(16)
+        user.password_hash = hash_password(new_password)
+        user.token_version += 1
+        user.needs_setup = True
+        await repo.update_user(user)
+
+        cred_path = write_initial_credentials(user.email, new_password, label="reset")
+        print(f"Password reset for: {user.email}")
+        print(f"Credentials written to: {cred_path} (mode 0600)")
+        print("Next login will require setup (new email + password).")
+        return 0
+    finally:
+        await close_engine()
 
 
 def main() -> None:
@@ -18,48 +83,8 @@ def main() -> None:
     parser.add_argument("--email", help="Admin email (default: first admin found)")
     args = parser.parse_args()
 
-    repo = SQLiteUserRepository()
-
-    # Find admin user synchronously (CLI context, no event loop)
-    import asyncio
-
-    user = asyncio.run(_find_admin(repo, args.email))
-    if user is None:
-        if args.email:
-            print(f"Error: user '{args.email}' not found.", file=sys.stderr)
-        else:
-            print("Error: no admin user found.", file=sys.stderr)
-        sys.exit(1)
-
-    new_password = secrets.token_urlsafe(16)
-    user.password_hash = hash_password(new_password)
-    user.token_version += 1
-    user.needs_setup = True
-    asyncio.run(repo.update_user(user))
-
-    print(f"Password reset for: {user.email}")
-    print(f"New password: {new_password}")
-    print("Next login will require setup (new email + password).")
-
-
-async def _find_admin(repo: SQLiteUserRepository, email: str | None):
-    if email:
-        return await repo.get_user_by_email(email)
-    # Find first admin
-    import asyncio
-
-    from app.gateway.auth.repositories.sqlite import _get_users_conn
-
-    def _find_sync():
-        with _get_users_conn() as conn:
-            cursor = conn.execute("SELECT id FROM users WHERE system_role = 'admin' LIMIT 1")
-            row = cursor.fetchone()
-            return dict(row)["id"] if row else None
-
-    admin_id = await asyncio.to_thread(_find_sync)
-    if admin_id:
-        return await repo.get_user_by_id(admin_id)
-    return None
+    exit_code = asyncio.run(_run(args.email))
+    sys.exit(exit_code)
 
 
 if __name__ == "__main__":

backend/app/gateway/auth_middleware.py

@@ -1,17 +1,24 @@
 """Global authentication middleware — fail-closed safety net.
 
-Rejects unauthenticated requests to non-public paths with 401.
+Rejects unauthenticated requests to non-public paths with 401. When a
+request passes the cookie check, resolves the JWT payload to a real
+``User`` object and stamps it into both ``request.state.user`` and the
+``deerflow.runtime.user_context`` contextvar so that repository-layer
+owner filtering works automatically via the sentinel pattern.
+
 Fine-grained permission checks remain in authz.py decorators.
 """
 
 from collections.abc import Callable
 
-from fastapi import Request, Response
+from fastapi import HTTPException, Request, Response
 from starlette.middleware.base import BaseHTTPMiddleware
 from starlette.responses import JSONResponse
 from starlette.types import ASGIApp
 
-from app.gateway.auth.errors import AuthErrorCode
+from app.gateway.auth.errors import AuthErrorCode, AuthErrorResponse
+from app.gateway.authz import _ALL_PERMISSIONS, AuthContext
+from deerflow.runtime.user_context import reset_current_user, set_current_user
 
 # Paths that never require authentication.
 _PUBLIC_PATH_PREFIXES: tuple[str, ...] = (
@@ -41,12 +48,23 @@ def _is_public(path: str) -> bool:
 
 
 class AuthMiddleware(BaseHTTPMiddleware):
-    """Coarse-grained auth gate: reject requests without a valid session cookie.
+    """Strict auth gate: reject requests without a valid session.
 
-    This does NOT verify JWT signature or user existence — that is the job of
-    ``get_current_user_from_request`` in deps.py (called by ``@require_auth``).
-    The middleware only checks *presence* of the cookie so that new endpoints
-    that forget ``@require_auth`` are not completely exposed.
+    Two-stage check for non-public paths:
+
+    1. Cookie presence — return 401 NOT_AUTHENTICATED if missing
+    2. JWT validation via ``get_optional_user_from_request`` — return 401
+       TOKEN_INVALID if the token is absent, malformed, expired, or the
+       signed user does not exist / is stale
+
+    On success, stamps ``request.state.user`` and the
+    ``deerflow.runtime.user_context`` contextvar so that repository-layer
+    owner filters work downstream without every route needing a
+    ``@require_auth`` decorator. Routes that need per-resource
+    authorization (e.g. "user A cannot read user B's thread by guessing
+    the URL") should additionally use ``@require_permission(...,
+    owner_check=True)`` for explicit enforcement — but authentication
+    itself is fully handled here.
     """
 
     def __init__(self, app: ASGIApp) -> None:
@@ -61,11 +79,39 @@ class AuthMiddleware(BaseHTTPMiddleware):
             return JSONResponse(
                 status_code=401,
                 content={
-                    "detail": {
-                        "code": AuthErrorCode.NOT_AUTHENTICATED,
-                        "message": "Authentication required",
-                    }
+                    "detail": AuthErrorResponse(
+                        code=AuthErrorCode.NOT_AUTHENTICATED,
+                        message="Authentication required",
+                    ).model_dump()
                 },
             )
 
-        return await call_next(request)
+        # Strict JWT validation: reject junk/expired tokens with 401
+        # right here instead of silently passing through. This closes
+        # the "junk cookie bypass" gap (AUTH_TEST_PLAN test 7.5.8):
+        # without this, non-isolation routes like /api/models would
+        # accept any cookie-shaped string as authentication.
+        #
+        # We call the *strict* resolver so that fine-grained error
+        # codes (token_expired, token_invalid, user_not_found, …)
+        # propagate from AuthErrorCode, not get flattened into one
+        # generic code. BaseHTTPMiddleware doesn't let HTTPException
+        # bubble up, so we catch and render it as JSONResponse here.
+        from app.gateway.deps import get_current_user_from_request
+
+        try:
+            user = await get_current_user_from_request(request)
+        except HTTPException as exc:
+            return JSONResponse(status_code=exc.status_code, content={"detail": exc.detail})
+
+        # Stamp both request.state.user (for the contextvar pattern)
+        # and request.state.auth (so @require_permission's "auth is
+        # None" branch short-circuits instead of running the entire
+        # JWT-decode + DB-lookup pipeline a second time per request).
+        request.state.user = user
+        request.state.auth = AuthContext(user=user, permissions=_ALL_PERMISSIONS)
+        token = set_current_user(user)
+        try:
+            return await call_next(request)
+        finally:
+            reset_current_user(token)

backend/app/gateway/authz.py

@@ -169,8 +169,7 @@ def require_permission(
     resource: str,
     action: str,
     owner_check: bool = False,
-    owner_filter_key: str = "user_id",
-    inject_record: bool = False,
+    require_existing: bool = False,
 ) -> Callable[[Callable[P, T]], Callable[P, T]]:
     """Decorator that checks permission for resource:action.
 
@@ -181,27 +180,24 @@ def require_permission(
         action: Action name (e.g., "read", "write", "delete")
         owner_check: If True, validates that the current user owns the resource.
                      Requires 'thread_id' path parameter and performs ownership check.
-        owner_filter_key: Field name for ownership filter (default: "user_id")
-        inject_record: If True and owner_check is True, injects the thread record
-                      into kwargs['thread_record'] for use in the handler.
+        require_existing: Only meaningful with ``owner_check=True``. If True, a
+                          missing ``threads_meta`` row counts as a denial (404)
+                          instead of "untracked legacy thread, allow". Use on
+                          **destructive / mutating** routes (DELETE, PATCH,
+                          state-update) so a deleted thread can't be re-targeted
+                          by another user via the missing-row code path.
 
     Usage:
-        # Simple permission check
-        @require_permission("threads", "read")
+        # Read-style: legacy untracked threads are allowed
+        @require_permission("threads", "read", owner_check=True)
         async def get_thread(thread_id: str, request: Request):
             ...
 
-        # With ownership check (for /threads/{thread_id} endpoints)
-        @require_permission("threads", "delete", owner_check=True)
+        # Destructive: thread row MUST exist and be owned by caller
+        @require_permission("threads", "delete", owner_check=True, require_existing=True)
         async def delete_thread(thread_id: str, request: Request):
             ...
 
-        # With ownership check and record injection
-        @require_permission("threads", "delete", owner_check=True, inject_record=True)
-        async def delete_thread(thread_id: str, request: Request, thread_record: dict = None):
-            # thread_record is injected if found
-            ...
-
     Raises:
         HTTPException 401: If authentication required but user is anonymous
         HTTPException 403: If user lacks permission
@@ -231,28 +227,33 @@ def require_permission(
                     detail=f"Permission denied: {resource}:{action}",
                 )
 
-            # Owner check for thread-specific resources
+            # Owner check for thread-specific resources.
+            #
+            # 2.0-rc moved thread metadata into the SQL persistence layer
+            # (``threads_meta`` table). We verify ownership via
+            # ``ThreadMetaStore.check_access``: it returns True for
+            # missing rows (untracked legacy thread) and for rows whose
+            # ``owner_id`` is NULL (shared / pre-auth data), so this is
+            # strict-deny rather than strict-allow — only an *existing*
+            # row with a *different* owner_id triggers 404.
             if owner_check:
                 thread_id = kwargs.get("thread_id")
                 if thread_id is None:
                     raise ValueError("require_permission with owner_check=True requires 'thread_id' parameter")
 
-                # Get thread and verify ownership
-                from app.gateway.routers.threads import _store_get, get_store
+                from app.gateway.deps import get_thread_meta_repo
 
-                store = get_store(request)
-                if store is not None:
-                    record = await _store_get(store, thread_id)
-                    if record:
-                        owner_id = record.get("metadata", {}).get(owner_filter_key)
-                        if owner_id and owner_id != str(auth.user.id):
-                            raise HTTPException(
-                                status_code=404,
-                                detail=f"Thread {thread_id} not found",
-                            )
-                        # Inject record if requested
-                        if inject_record:
-                            kwargs["thread_record"] = record
+                thread_meta_repo = get_thread_meta_repo(request)
+                allowed = await thread_meta_repo.check_access(
+                    thread_id,
+                    str(auth.user.id),
+                    require_existing=require_existing,
+                )
+                if not allowed:
+                    raise HTTPException(
+                        status_code=404,
+                        detail=f"Thread {thread_id} not found",
+                    )
 
             return await func(*args, **kwargs)
 

backend/app/gateway/deps.py

@@ -1,9 +1,10 @@
 """Centralized accessors for singleton objects stored on ``app.state``.
 
 **Getters** (used by routers): raise 503 when a required dependency is
-missing, except ``get_store`` which returns ``None``.
+missing, except ``get_store`` and ``get_thread_meta_repo`` which return
+``None``.
 
-Initialization is handled directly in ``app.py`` via :class:`AsyncExitStack``.
+Initialization is handled directly in ``app.py`` via :class:`AsyncExitStack`.
 """
 
 from __future__ import annotations
@@ -14,39 +15,94 @@ from typing import TYPE_CHECKING
 
 from fastapi import FastAPI, HTTPException, Request
 
-from deerflow.runtime import RunManager, StreamBridge
+from deerflow.runtime import RunContext, RunManager
 
 if TYPE_CHECKING:
     from app.gateway.auth.local_provider import LocalAuthProvider
     from app.gateway.auth.repositories.sqlite import SQLiteUserRepository
 
+
+@asynccontextmanager
+async def langgraph_runtime(app: FastAPI) -> AsyncGenerator[None, None]:
+    """Bootstrap and tear down all LangGraph runtime singletons.
+
+    Usage in ``app.py``::
+
+        async with langgraph_runtime(app):
+            yield
+    """
+    from deerflow.agents.checkpointer.async_provider import make_checkpointer
+    from deerflow.config import get_app_config
+    from deerflow.persistence.engine import close_engine, get_session_factory, init_engine_from_config
+    from deerflow.runtime import make_store, make_stream_bridge
+    from deerflow.runtime.events.store import make_run_event_store
+
+    async with AsyncExitStack() as stack:
+        app.state.stream_bridge = await stack.enter_async_context(make_stream_bridge())
+
+        # Initialize persistence engine BEFORE checkpointer so that
+        # auto-create-database logic runs first (postgres backend).
+        config = get_app_config()
+        await init_engine_from_config(config.database)
+
+        app.state.checkpointer = await stack.enter_async_context(make_checkpointer())
+        app.state.store = await stack.enter_async_context(make_store())
+
+        # Initialize repositories — one get_session_factory() call for all.
+        sf = get_session_factory()
+        if sf is not None:
+            from deerflow.persistence.feedback import FeedbackRepository
+            from deerflow.persistence.run import RunRepository
+            from deerflow.persistence.thread_meta import ThreadMetaRepository
+
+            app.state.run_store = RunRepository(sf)
+            app.state.feedback_repo = FeedbackRepository(sf)
+            app.state.thread_meta_repo = ThreadMetaRepository(sf)
+        else:
+            from deerflow.persistence.thread_meta import MemoryThreadMetaStore
+            from deerflow.runtime.runs.store.memory import MemoryRunStore
+
+            app.state.run_store = MemoryRunStore()
+            app.state.feedback_repo = None
+            app.state.thread_meta_repo = MemoryThreadMetaStore(app.state.store)
+
+        # Run event store (has its own factory with config-driven backend selection)
+        run_events_config = getattr(config, "run_events", None)
+        app.state.run_event_store = make_run_event_store(run_events_config)
+
+        # RunManager with store backing for persistence
+        app.state.run_manager = RunManager(store=app.state.run_store)
+
+        try:
+            yield
+        finally:
+            await close_engine()
+
+
 # ---------------------------------------------------------------------------
-# Getters – called by routers per-request
+# Getters -- called by routers per-request
 # ---------------------------------------------------------------------------
 
 
-def get_stream_bridge(request: Request) -> StreamBridge:
-    """Return the global :class:`StreamBridge`, or 503."""
-    bridge = getattr(request.app.state, "stream_bridge", None)
-    if bridge is None:
-        raise HTTPException(status_code=503, detail="Stream bridge not available")
-    return bridge
+def _require(attr: str, label: str):
+    """Create a FastAPI dependency that returns ``app.state.<attr>`` or 503."""
+
+    def dep(request: Request):
+        val = getattr(request.app.state, attr, None)
+        if val is None:
+            raise HTTPException(status_code=503, detail=f"{label} not available")
+        return val
+
+    dep.__name__ = dep.__qualname__ = f"get_{attr}"
+    return dep
 
 
-def get_run_manager(request: Request) -> RunManager:
-    """Return the global :class:`RunManager`, or 503."""
-    mgr = getattr(request.app.state, "run_manager", None)
-    if mgr is None:
-        raise HTTPException(status_code=503, detail="Run manager not available")
-    return mgr
-
-
-def get_checkpointer(request: Request):
-    """Return the global checkpointer, or 503."""
-    cp = getattr(request.app.state, "checkpointer", None)
-    if cp is None:
-        raise HTTPException(status_code=503, detail="Checkpointer not available")
-    return cp
+get_stream_bridge = _require("stream_bridge", "Stream bridge")
+get_run_manager = _require("run_manager", "Run manager")
+get_checkpointer = _require("checkpointer", "Checkpointer")
+get_run_event_store = _require("run_event_store", "Run event store")
+get_feedback_repo = _require("feedback_repo", "Feedback")
+get_run_store = _require("run_store", "Run store")
 
 
 def get_store(request: Request):
@@ -54,8 +110,30 @@ def get_store(request: Request):
     return getattr(request.app.state, "store", None)
 
 
+get_thread_meta_repo = _require("thread_meta_repo", "Thread metadata store")
+
+
+def get_run_context(request: Request) -> RunContext:
+    """Build a :class:`RunContext` from ``app.state`` singletons.
+
+    Returns a *base* context with infrastructure dependencies.  Callers that
+    need per-run fields (e.g. ``follow_up_to_run_id``) should use
+    ``dataclasses.replace(ctx, follow_up_to_run_id=...)`` before passing it
+    to :func:`run_agent`.
+    """
+    from deerflow.config import get_app_config
+
+    return RunContext(
+        checkpointer=get_checkpointer(request),
+        store=get_store(request),
+        event_store=get_run_event_store(request),
+        run_events_config=getattr(get_app_config(), "run_events", None),
+        thread_meta_repo=get_thread_meta_repo(request),
+    )
+
+
 # ---------------------------------------------------------------------------
-# Auth helpers (used by authz.py)
+# Auth helpers (used by authz.py and auth middleware)
 # ---------------------------------------------------------------------------
 
 # Cached singletons to avoid repeated instantiation per request
@@ -64,12 +142,20 @@ _cached_repo: SQLiteUserRepository | None = None
 
 
 def get_local_provider() -> LocalAuthProvider:
-    """Get or create the cached LocalAuthProvider singleton."""
+    """Get or create the cached LocalAuthProvider singleton.
+
+    Must be called after ``init_engine_from_config()`` — the shared
+    session factory is required to construct the user repository.
+    """
     global _cached_local_provider, _cached_repo
     if _cached_repo is None:
         from app.gateway.auth.repositories.sqlite import SQLiteUserRepository
+        from deerflow.persistence.engine import get_session_factory
 
-        _cached_repo = SQLiteUserRepository()
+        sf = get_session_factory()
+        if sf is None:
+            raise RuntimeError("get_local_provider() called before init_engine_from_config(); cannot access users table")
+        _cached_repo = SQLiteUserRepository(sf)
     if _cached_local_provider is None:
         from app.gateway.auth.local_provider import LocalAuthProvider
 
@@ -128,26 +214,12 @@ async def get_optional_user_from_request(request: Request):
         return None
 
 
-# ---------------------------------------------------------------------------
-# Runtime bootstrap
-# ---------------------------------------------------------------------------
+async def get_current_user(request: Request) -> str | None:
+    """Extract user_id from request cookie, or None if not authenticated.
 
-
-@asynccontextmanager
-async def langgraph_runtime(app: FastAPI) -> AsyncGenerator[None, None]:
-    """Bootstrap and tear down all LangGraph runtime singletons.
-
-    Usage in ``app.py``::
-
-        async with langgraph_runtime(app):
-            yield
+    Thin adapter that returns the string id for callers that only need
+    identification (e.g., ``feedback.py``). Full-user callers should use
+    ``get_current_user_from_request`` or ``get_optional_user_from_request``.
     """
-    from deerflow.agents.checkpointer.async_provider import make_checkpointer
-    from deerflow.runtime import make_store, make_stream_bridge
-
-    async with AsyncExitStack() as stack:
-        app.state.stream_bridge = await stack.enter_async_context(make_stream_bridge())
-        app.state.checkpointer = await stack.enter_async_context(make_checkpointer())
-        app.state.store = await stack.enter_async_context(make_store())
-        app.state.run_manager = RunManager()
-        yield
+    user = await get_optional_user_from_request(request)
+    return str(user.id) if user else None

backend/app/gateway/langgraph_auth.py

@@ -93,14 +93,14 @@ async def authenticate(request):
 
 @auth.on
 async def add_owner_filter(ctx: Auth.types.AuthContext, value: dict):
-    """Inject user_id metadata on writes; filter by user_id on reads.
+    """Inject owner_id metadata on writes; filter by owner_id on reads.
 
-    Gateway stores thread ownership as ``metadata.user_id``.
+    Gateway stores thread ownership as ``metadata.owner_id``.
     This handler ensures LangGraph Server enforces the same isolation.
     """
-    # On create/update: stamp user_id into metadata
+    # On create/update: stamp owner_id into metadata
     metadata = value.setdefault("metadata", {})
-    metadata["user_id"] = ctx.user.identity
+    metadata["owner_id"] = ctx.user.identity
 
     # Return filter dict — LangGraph applies it to search/read/delete
-    return {"user_id": ctx.user.identity}
+    return {"owner_id": ctx.user.identity}

backend/app/gateway/routers/__init__.py

@@ -1,3 +1,3 @@
-from . import artifacts, assistants_compat, auth, mcp, models, skills, suggestions, thread_runs, threads, uploads
+from . import artifacts, assistants_compat, mcp, models, skills, suggestions, thread_runs, threads, uploads
 
-__all__ = ["artifacts", "assistants_compat", "auth", "mcp", "models", "skills", "suggestions", "threads", "thread_runs", "uploads"]
+__all__ = ["artifacts", "assistants_compat", "mcp", "models", "skills", "suggestions", "threads", "thread_runs", "uploads"]

backend/app/gateway/routers/artifacts.py

@@ -7,6 +7,7 @@ from urllib.parse import quote
 from fastapi import APIRouter, HTTPException, Request
 from fastapi.responses import FileResponse, PlainTextResponse, Response
 
+from app.gateway.authz import require_permission
 from app.gateway.path_utils import resolve_thread_virtual_path
 
 logger = logging.getLogger(__name__)
@@ -81,6 +82,7 @@ def _extract_file_from_skill_archive(zip_path: Path, internal_path: str) -> byte
     summary="Get Artifact File",
     description="Retrieve an artifact file generated by the AI agent. Text and binary files can be viewed inline, while active web content is always downloaded.",
 )
+@require_permission("threads", "read", owner_check=True)
 async def get_artifact(thread_id: str, path: str, request: Request, download: bool = False) -> Response:
     """Get an artifact file by its path.
 

backend/app/gateway/routers/auth.py

@@ -1,11 +1,13 @@
 """Authentication endpoints."""
 
 import logging
+import os
 import time
+from ipaddress import ip_address, ip_network
 
 from fastapi import APIRouter, Depends, HTTPException, Request, Response, status
 from fastapi.security import OAuth2PasswordRequestForm
-from pydantic import BaseModel, EmailStr, Field
+from pydantic import BaseModel, EmailStr, Field, field_validator
 
 from app.gateway.auth import (
     UserResponse,
@@ -31,12 +33,84 @@ class LoginResponse(BaseModel):
     needs_setup: bool = False
 
 
+# Top common-password blocklist. Drawn from the public SecLists "10k worst
+# passwords" set, lowercased + length>=8 only (shorter ones already fail
+# the min_length check). Kept tight on purpose: this is the **lower bound**
+# defense, not a full HIBP / passlib check, and runs in-process per request.
+_COMMON_PASSWORDS: frozenset[str] = frozenset(
+    {
+        "password",
+        "password1",
+        "password12",
+        "password123",
+        "password1234",
+        "12345678",
+        "123456789",
+        "1234567890",
+        "qwerty12",
+        "qwertyui",
+        "qwerty123",
+        "abc12345",
+        "abcd1234",
+        "iloveyou",
+        "letmein1",
+        "welcome1",
+        "welcome123",
+        "admin123",
+        "administrator",
+        "passw0rd",
+        "p@ssw0rd",
+        "monkey12",
+        "trustno1",
+        "sunshine",
+        "princess",
+        "football",
+        "baseball",
+        "superman",
+        "batman123",
+        "starwars",
+        "dragon123",
+        "master123",
+        "shadow12",
+        "michael1",
+        "jennifer",
+        "computer",
+    }
+)
+
+
+def _password_is_common(password: str) -> bool:
+    """Case-insensitive blocklist check.
+
+    Lowercases the input so trivial mutations like ``Password`` /
+    ``PASSWORD`` are also rejected. Does not normalize digit substitutions
+    (``p@ssw0rd`` is included as a literal entry instead) — keeping the
+    rule cheap and predictable.
+    """
+    return password.lower() in _COMMON_PASSWORDS
+
+
+def _validate_strong_password(value: str) -> str:
+    """Pydantic field-validator body shared by Register + ChangePassword.
+
+    Constraint = function, not type-level mixin. The two request models
+    have no "is-a" relationship; they only share the password-strength
+    rule. Lifting it into a free function lets each model bind it via
+    ``@field_validator(field_name)`` without inheritance gymnastics.
+    """
+    if _password_is_common(value):
+        raise ValueError("Password is too common; choose a stronger password.")
+    return value
+
+
 class RegisterRequest(BaseModel):
     """Request model for user registration."""
 
     email: EmailStr
     password: str = Field(..., min_length=8)
 
+    _strong_password = field_validator("password")(classmethod(lambda cls, v: _validate_strong_password(v)))
+
 
 class ChangePasswordRequest(BaseModel):
     """Request model for password change (also handles setup flow)."""
@@ -45,6 +119,8 @@ class ChangePasswordRequest(BaseModel):
     new_password: str = Field(..., min_length=8)
     new_email: EmailStr | None = None
 
+    _strong_password = field_validator("new_password")(classmethod(lambda cls, v: _validate_strong_password(v)))
+
 
 class MessageResponse(BaseModel):
     """Generic message response."""
@@ -79,26 +155,65 @@ _LOCKOUT_SECONDS = 300  # 5 minutes
 _login_attempts: dict[str, tuple[int, float]] = {}
 
 
+def _trusted_proxies() -> list:
+    """Parse ``AUTH_TRUSTED_PROXIES`` env var into a list of ip_network objects.
+
+    Comma-separated CIDR or single-IP entries. Empty / unset = no proxy is
+    trusted (direct mode). Invalid entries are skipped with a logger warning.
+    Read live so env-var overrides take effect immediately and tests can
+    ``monkeypatch.setenv`` without poking a module-level cache.
+    """
+    raw = os.getenv("AUTH_TRUSTED_PROXIES", "").strip()
+    if not raw:
+        return []
+    nets = []
+    for entry in raw.split(","):
+        entry = entry.strip()
+        if not entry:
+            continue
+        try:
+            nets.append(ip_network(entry, strict=False))
+        except ValueError:
+            logger.warning("AUTH_TRUSTED_PROXIES: ignoring invalid entry %r", entry)
+    return nets
+
+
 def _get_client_ip(request: Request) -> str:
     """Extract the real client IP for rate limiting.
 
-    Uses ``X-Real-IP`` header set by nginx (``proxy_set_header X-Real-IP
-    $remote_addr``).  Nginx unconditionally overwrites any client-supplied
-    ``X-Real-IP``, so the value seen by Gateway is always the TCP peer IP
-    that nginx observed — it cannot be spoofed by the client.
+    Trust model:
 
-    ``request.client.host`` is NOT reliable because uvicorn's default
-    ``proxy_headers=True`` replaces it with the *first* entry from
-    ``X-Forwarded-For``, which IS client-spoofable.
+    - The TCP peer (``request.client.host``) is always the baseline. It is
+      whatever the kernel reports as the connecting socket — unforgeable
+      by the client itself.
+    - ``X-Real-IP`` is **only** honored if the TCP peer is in the
+      ``AUTH_TRUSTED_PROXIES`` allowlist (set via env var, comma-separated
+      CIDR or single IPs). When set, the gateway is assumed to be behind a
+      reverse proxy (nginx, Cloudflare, ALB, …) that overwrites
+      ``X-Real-IP`` with the original client address.
+    - With no ``AUTH_TRUSTED_PROXIES`` set, ``X-Real-IP`` is silently
+      ignored — closing the bypass where any client could rotate the
+      header to dodge per-IP rate limits in dev / direct-gateway mode.
 
-    ``X-Forwarded-For`` is intentionally NOT used for the same reason.
+    ``X-Forwarded-For`` is intentionally NOT used because it is naturally
+    client-controlled at the *first* hop and the trust chain is harder to
+    audit per-request.
     """
-    real_ip = request.headers.get("x-real-ip", "").strip()
-    if real_ip:
-        return real_ip
+    peer_host = request.client.host if request.client else None
 
-    # Fallback: direct connection without nginx (e.g. unit tests, dev).
-    return request.client.host if request.client else "unknown"
+    trusted = _trusted_proxies()
+    if trusted and peer_host:
+        try:
+            peer_ip = ip_address(peer_host)
+            if any(peer_ip in net for net in trusted):
+                real_ip = request.headers.get("x-real-ip", "").strip()
+                if real_ip:
+                    return real_ip
+        except ValueError:
+            # peer_host wasn't a parseable IP (e.g. "unknown") — fall through
+            pass
+
+    return peer_host or "unknown"
 
 
 def _check_rate_limit(ip: str) -> None:

backend/app/gateway/routers/feedback.py

@@ -0,0 +1,132 @@
+"""Feedback endpoints — create, list, stats, delete.
+
+Allows users to submit thumbs-up/down feedback on runs,
+optionally scoped to a specific message.
+"""
+
+from __future__ import annotations
+
+import logging
+from typing import Any
+
+from fastapi import APIRouter, HTTPException, Request
+from pydantic import BaseModel, Field
+
+from app.gateway.authz import require_permission
+from app.gateway.deps import get_current_user, get_feedback_repo, get_run_store
+
+logger = logging.getLogger(__name__)
+router = APIRouter(prefix="/api/threads", tags=["feedback"])
+
+
+# ---------------------------------------------------------------------------
+# Request / response models
+# ---------------------------------------------------------------------------
+
+
+class FeedbackCreateRequest(BaseModel):
+    rating: int = Field(..., description="Feedback rating: +1 (positive) or -1 (negative)")
+    comment: str | None = Field(default=None, description="Optional text feedback")
+    message_id: str | None = Field(default=None, description="Optional: scope feedback to a specific message")
+
+
+class FeedbackResponse(BaseModel):
+    feedback_id: str
+    run_id: str
+    thread_id: str
+    owner_id: str | None = None
+    message_id: str | None = None
+    rating: int
+    comment: str | None = None
+    created_at: str = ""
+
+
+class FeedbackStatsResponse(BaseModel):
+    run_id: str
+    total: int = 0
+    positive: int = 0
+    negative: int = 0
+
+
+# ---------------------------------------------------------------------------
+# Endpoints
+# ---------------------------------------------------------------------------
+
+
+@router.post("/{thread_id}/runs/{run_id}/feedback", response_model=FeedbackResponse)
+@require_permission("threads", "write", owner_check=True, require_existing=True)
+async def create_feedback(
+    thread_id: str,
+    run_id: str,
+    body: FeedbackCreateRequest,
+    request: Request,
+) -> dict[str, Any]:
+    """Submit feedback (thumbs-up/down) for a run."""
+    if body.rating not in (1, -1):
+        raise HTTPException(status_code=400, detail="rating must be +1 or -1")
+
+    user_id = await get_current_user(request)
+
+    # Validate run exists and belongs to thread
+    run_store = get_run_store(request)
+    run = await run_store.get(run_id)
+    if run is None:
+        raise HTTPException(status_code=404, detail=f"Run {run_id} not found")
+    if run.get("thread_id") != thread_id:
+        raise HTTPException(status_code=404, detail=f"Run {run_id} not found in thread {thread_id}")
+
+    feedback_repo = get_feedback_repo(request)
+    return await feedback_repo.create(
+        run_id=run_id,
+        thread_id=thread_id,
+        rating=body.rating,
+        owner_id=user_id,
+        message_id=body.message_id,
+        comment=body.comment,
+    )
+
+
+@router.get("/{thread_id}/runs/{run_id}/feedback", response_model=list[FeedbackResponse])
+@require_permission("threads", "read", owner_check=True)
+async def list_feedback(
+    thread_id: str,
+    run_id: str,
+    request: Request,
+) -> list[dict[str, Any]]:
+    """List all feedback for a run."""
+    feedback_repo = get_feedback_repo(request)
+    return await feedback_repo.list_by_run(thread_id, run_id)
+
+
+@router.get("/{thread_id}/runs/{run_id}/feedback/stats", response_model=FeedbackStatsResponse)
+@require_permission("threads", "read", owner_check=True)
+async def feedback_stats(
+    thread_id: str,
+    run_id: str,
+    request: Request,
+) -> dict[str, Any]:
+    """Get aggregated feedback stats (positive/negative counts) for a run."""
+    feedback_repo = get_feedback_repo(request)
+    return await feedback_repo.aggregate_by_run(thread_id, run_id)
+
+
+@router.delete("/{thread_id}/runs/{run_id}/feedback/{feedback_id}")
+@require_permission("threads", "delete", owner_check=True, require_existing=True)
+async def delete_feedback(
+    thread_id: str,
+    run_id: str,
+    feedback_id: str,
+    request: Request,
+) -> dict[str, bool]:
+    """Delete a feedback record."""
+    feedback_repo = get_feedback_repo(request)
+    # Verify feedback belongs to the specified thread/run before deleting
+    existing = await feedback_repo.get(feedback_id)
+    if existing is None:
+        raise HTTPException(status_code=404, detail=f"Feedback {feedback_id} not found")
+    if existing.get("thread_id") != thread_id or existing.get("run_id") != run_id:
+        raise HTTPException(status_code=404, detail=f"Feedback {feedback_id} not found in run {run_id}")
+    deleted = await feedback_repo.delete(feedback_id)
+    if not deleted:
+        raise HTTPException(status_code=404, detail=f"Feedback {feedback_id} not found")
+    return {"success": True}

backend/app/gateway/routers/runs.py

@@ -51,6 +51,7 @@ async def stateless_stream(body: RunCreateRequest, request: Request) -> Streamin
             "Cache-Control": "no-cache",
             "Connection": "keep-alive",
             "X-Accel-Buffering": "no",
+            "Content-Location": f"/api/threads/{thread_id}/runs/{record.run_id}",
         },
     )
 

backend/app/gateway/routers/skills.py

@@ -1,14 +1,29 @@
 import json
 import logging
+import shutil
 from pathlib import Path
 
 from fastapi import APIRouter, HTTPException
 from pydantic import BaseModel, Field
 
 from app.gateway.path_utils import resolve_thread_virtual_path
+from deerflow.agents.lead_agent.prompt import refresh_skills_system_prompt_cache_async
 from deerflow.config.extensions_config import ExtensionsConfig, SkillStateConfig, get_extensions_config, reload_extensions_config
 from deerflow.skills import Skill, load_skills
 from deerflow.skills.installer import SkillAlreadyExistsError, install_skill_from_archive
+from deerflow.skills.manager import (
+    append_history,
+    atomic_write,
+    custom_skill_exists,
+    ensure_custom_skill_is_editable,
+    get_custom_skill_dir,
+    get_custom_skill_file,
+    get_skill_history_file,
+    read_custom_skill_content,
+    read_history,
+    validate_skill_markdown_content,
+)
+from deerflow.skills.security_scanner import scan_skill_content
 
 logger = logging.getLogger(__name__)
 
@@ -52,6 +67,22 @@ class SkillInstallResponse(BaseModel):
     message: str = Field(..., description="Installation result message")
 
 
+class CustomSkillContentResponse(SkillResponse):
+    content: str = Field(..., description="Raw SKILL.md content")
+
+
+class CustomSkillUpdateRequest(BaseModel):
+    content: str = Field(..., description="Replacement SKILL.md content")
+
+
+class CustomSkillHistoryResponse(BaseModel):
+    history: list[dict]
+
+
+class SkillRollbackRequest(BaseModel):
+    history_index: int = Field(default=-1, description="History entry index to restore from, defaulting to the latest change.")
+
+
 def _skill_to_response(skill: Skill) -> SkillResponse:
     """Convert a Skill object to a SkillResponse."""
     return SkillResponse(
@@ -78,6 +109,181 @@ async def list_skills() -> SkillsListResponse:
         raise HTTPException(status_code=500, detail=f"Failed to load skills: {str(e)}")
 
 
+@router.post(
+    "/skills/install",
+    response_model=SkillInstallResponse,
+    summary="Install Skill",
+    description="Install a skill from a .skill file (ZIP archive) located in the thread's user-data directory.",
+)
+async def install_skill(request: SkillInstallRequest) -> SkillInstallResponse:
+    try:
+        skill_file_path = resolve_thread_virtual_path(request.thread_id, request.path)
+        result = install_skill_from_archive(skill_file_path)
+        await refresh_skills_system_prompt_cache_async()
+        return SkillInstallResponse(**result)
+    except FileNotFoundError as e:
+        raise HTTPException(status_code=404, detail=str(e))
+    except SkillAlreadyExistsError as e:
+        raise HTTPException(status_code=409, detail=str(e))
+    except ValueError as e:
+        raise HTTPException(status_code=400, detail=str(e))
+    except HTTPException:
+        raise
+    except Exception as e:
+        logger.error(f"Failed to install skill: {e}", exc_info=True)
+        raise HTTPException(status_code=500, detail=f"Failed to install skill: {str(e)}")
+
+
+@router.get("/skills/custom", response_model=SkillsListResponse, summary="List Custom Skills")
+async def list_custom_skills() -> SkillsListResponse:
+    try:
+        skills = [skill for skill in load_skills(enabled_only=False) if skill.category == "custom"]
+        return SkillsListResponse(skills=[_skill_to_response(skill) for skill in skills])
+    except Exception as e:
+        logger.error("Failed to list custom skills: %s", e, exc_info=True)
+        raise HTTPException(status_code=500, detail=f"Failed to list custom skills: {str(e)}")
+
+
+@router.get("/skills/custom/{skill_name}", response_model=CustomSkillContentResponse, summary="Get Custom Skill Content")
+async def get_custom_skill(skill_name: str) -> CustomSkillContentResponse:
+    try:
+        skills = load_skills(enabled_only=False)
+        skill = next((s for s in skills if s.name == skill_name and s.category == "custom"), None)
+        if skill is None:
+            raise HTTPException(status_code=404, detail=f"Custom skill '{skill_name}' not found")
+        return CustomSkillContentResponse(**_skill_to_response(skill).model_dump(), content=read_custom_skill_content(skill_name))
+    except HTTPException:
+        raise
+    except Exception as e:
+        logger.error("Failed to get custom skill %s: %s", skill_name, e, exc_info=True)
+        raise HTTPException(status_code=500, detail=f"Failed to get custom skill: {str(e)}")
+
+
+@router.put("/skills/custom/{skill_name}", response_model=CustomSkillContentResponse, summary="Edit Custom Skill")
+async def update_custom_skill(skill_name: str, request: CustomSkillUpdateRequest) -> CustomSkillContentResponse:
+    try:
+        ensure_custom_skill_is_editable(skill_name)
+        validate_skill_markdown_content(skill_name, request.content)
+        scan = await scan_skill_content(request.content, executable=False, location=f"{skill_name}/SKILL.md")
+        if scan.decision == "block":
+            raise HTTPException(status_code=400, detail=f"Security scan blocked the edit: {scan.reason}")
+        skill_file = get_custom_skill_dir(skill_name) / "SKILL.md"
+        prev_content = skill_file.read_text(encoding="utf-8")
+        atomic_write(skill_file, request.content)
+        append_history(
+            skill_name,
+            {
+                "action": "human_edit",
+                "author": "human",
+                "thread_id": None,
+                "file_path": "SKILL.md",
+                "prev_content": prev_content,
+                "new_content": request.content,
+                "scanner": {"decision": scan.decision, "reason": scan.reason},
+            },
+        )
+        await refresh_skills_system_prompt_cache_async()
+        return await get_custom_skill(skill_name)
+    except HTTPException:
+        raise
+    except FileNotFoundError as e:
+        raise HTTPException(status_code=404, detail=str(e))
+    except ValueError as e:
+        raise HTTPException(status_code=400, detail=str(e))
+    except Exception as e:
+        logger.error("Failed to update custom skill %s: %s", skill_name, e, exc_info=True)
+        raise HTTPException(status_code=500, detail=f"Failed to update custom skill: {str(e)}")
+
+
+@router.delete("/skills/custom/{skill_name}", summary="Delete Custom Skill")
+async def delete_custom_skill(skill_name: str) -> dict[str, bool]:
+    try:
+        ensure_custom_skill_is_editable(skill_name)
+        skill_dir = get_custom_skill_dir(skill_name)
+        prev_content = read_custom_skill_content(skill_name)
+        append_history(
+            skill_name,
+            {
+                "action": "human_delete",
+                "author": "human",
+                "thread_id": None,
+                "file_path": "SKILL.md",
+                "prev_content": prev_content,
+                "new_content": None,
+                "scanner": {"decision": "allow", "reason": "Deletion requested."},
+            },
+        )
+        shutil.rmtree(skill_dir)
+        await refresh_skills_system_prompt_cache_async()
+        return {"success": True}
+    except FileNotFoundError as e:
+        raise HTTPException(status_code=404, detail=str(e))
+    except ValueError as e:
+        raise HTTPException(status_code=400, detail=str(e))
+    except Exception as e:
+        logger.error("Failed to delete custom skill %s: %s", skill_name, e, exc_info=True)
+        raise HTTPException(status_code=500, detail=f"Failed to delete custom skill: {str(e)}")
+
+
+@router.get("/skills/custom/{skill_name}/history", response_model=CustomSkillHistoryResponse, summary="Get Custom Skill History")
+async def get_custom_skill_history(skill_name: str) -> CustomSkillHistoryResponse:
+    try:
+        if not custom_skill_exists(skill_name) and not get_skill_history_file(skill_name).exists():
+            raise HTTPException(status_code=404, detail=f"Custom skill '{skill_name}' not found")
+        return CustomSkillHistoryResponse(history=read_history(skill_name))
+    except HTTPException:
+        raise
+    except Exception as e:
+        logger.error("Failed to read history for %s: %s", skill_name, e, exc_info=True)
+        raise HTTPException(status_code=500, detail=f"Failed to read history: {str(e)}")
+
+
+@router.post("/skills/custom/{skill_name}/rollback", response_model=CustomSkillContentResponse, summary="Rollback Custom Skill")
+async def rollback_custom_skill(skill_name: str, request: SkillRollbackRequest) -> CustomSkillContentResponse:
+    try:
+        if not custom_skill_exists(skill_name) and not get_skill_history_file(skill_name).exists():
+            raise HTTPException(status_code=404, detail=f"Custom skill '{skill_name}' not found")
+        history = read_history(skill_name)
+        if not history:
+            raise HTTPException(status_code=400, detail=f"Custom skill '{skill_name}' has no history")
+        record = history[request.history_index]
+        target_content = record.get("prev_content")
+        if target_content is None:
+            raise HTTPException(status_code=400, detail="Selected history entry has no previous content to roll back to")
+        validate_skill_markdown_content(skill_name, target_content)
+        scan = await scan_skill_content(target_content, executable=False, location=f"{skill_name}/SKILL.md")
+        skill_file = get_custom_skill_file(skill_name)
+        current_content = skill_file.read_text(encoding="utf-8") if skill_file.exists() else None
+        history_entry = {
+            "action": "rollback",
+            "author": "human",
+            "thread_id": None,
+            "file_path": "SKILL.md",
+            "prev_content": current_content,
+            "new_content": target_content,
+            "rollback_from_ts": record.get("ts"),
+            "scanner": {"decision": scan.decision, "reason": scan.reason},
+        }
+        if scan.decision == "block":
+            append_history(skill_name, history_entry)
+            raise HTTPException(status_code=400, detail=f"Rollback blocked by security scanner: {scan.reason}")
+        atomic_write(skill_file, target_content)
+        append_history(skill_name, history_entry)
+        await refresh_skills_system_prompt_cache_async()
+        return await get_custom_skill(skill_name)
+    except HTTPException:
+        raise
+    except IndexError:
+        raise HTTPException(status_code=400, detail="history_index is out of range")
+    except FileNotFoundError as e:
+        raise HTTPException(status_code=404, detail=str(e))
+    except ValueError as e:
+        raise HTTPException(status_code=400, detail=str(e))
+    except Exception as e:
+        logger.error("Failed to roll back custom skill %s: %s", skill_name, e, exc_info=True)
+        raise HTTPException(status_code=500, detail=f"Failed to roll back custom skill: {str(e)}")
+
+
 @router.get(
     "/skills/{skill_name}",
     response_model=SkillResponse,
@@ -132,6 +338,7 @@ async def update_skill(skill_name: str, request: SkillUpdateRequest) -> SkillRes
 
         logger.info(f"Skills configuration updated and saved to: {config_path}")
         reload_extensions_config()
+        await refresh_skills_system_prompt_cache_async()
 
         skills = load_skills(enabled_only=False)
         updated_skill = next((s for s in skills if s.name == skill_name), None)
@@ -147,27 +354,3 @@ async def update_skill(skill_name: str, request: SkillUpdateRequest) -> SkillRes
     except Exception as e:
         logger.error(f"Failed to update skill {skill_name}: {e}", exc_info=True)
         raise HTTPException(status_code=500, detail=f"Failed to update skill: {str(e)}")
-
-
-@router.post(
-    "/skills/install",
-    response_model=SkillInstallResponse,
-    summary="Install Skill",
-    description="Install a skill from a .skill file (ZIP archive) located in the thread's user-data directory.",
-)
-async def install_skill(request: SkillInstallRequest) -> SkillInstallResponse:
-    try:
-        skill_file_path = resolve_thread_virtual_path(request.thread_id, request.path)
-        result = install_skill_from_archive(skill_file_path)
-        return SkillInstallResponse(**result)
-    except FileNotFoundError as e:
-        raise HTTPException(status_code=404, detail=str(e))
-    except SkillAlreadyExistsError as e:
-        raise HTTPException(status_code=409, detail=str(e))
-    except ValueError as e:
-        raise HTTPException(status_code=400, detail=str(e))
-    except HTTPException:
-        raise
-    except Exception as e:
-        logger.error(f"Failed to install skill: {e}", exc_info=True)
-        raise HTTPException(status_code=500, detail=f"Failed to install skill: {str(e)}")

backend/app/gateway/routers/suggestions.py

@@ -1,10 +1,11 @@
 import json
 import logging
 
-from fastapi import APIRouter
+from fastapi import APIRouter, Request
 from langchain_core.messages import HumanMessage, SystemMessage
 from pydantic import BaseModel, Field
 
+from app.gateway.authz import require_permission
 from deerflow.models import create_chat_model
 
 logger = logging.getLogger(__name__)
@@ -98,12 +99,13 @@ def _format_conversation(messages: list[SuggestionMessage]) -> str:
     summary="Generate Follow-up Questions",
     description="Generate short follow-up questions a user might ask next, based on recent conversation context.",
 )
-async def generate_suggestions(thread_id: str, request: SuggestionsRequest) -> SuggestionsResponse:
-    if not request.messages:
+@require_permission("threads", "read", owner_check=True)
+async def generate_suggestions(thread_id: str, body: SuggestionsRequest, request: Request) -> SuggestionsResponse:
+    if not body.messages:
         return SuggestionsResponse(suggestions=[])
 
-    n = request.n
-    conversation = _format_conversation(request.messages)
+    n = body.n
+    conversation = _format_conversation(body.messages)
     if not conversation:
         return SuggestionsResponse(suggestions=[])
 
@@ -120,7 +122,7 @@ async def generate_suggestions(thread_id: str, request: SuggestionsRequest) -> S
     user_content = f"Conversation Context:\n{conversation}\n\nGenerate {n} follow-up questions"
 
     try:
-        model = create_chat_model(name=request.model_name, thinking_enabled=False)
+        model = create_chat_model(name=body.model_name, thinking_enabled=False)
         response = await model.ainvoke([SystemMessage(content=system_instruction), HumanMessage(content=user_content)])
         raw = _extract_response_text(response.content)
         suggestions = _parse_json_string_list(raw) or []

backend/app/gateway/routers/thread_runs.py

@@ -19,8 +19,8 @@ from fastapi import APIRouter, HTTPException, Query, Request
 from fastapi.responses import Response, StreamingResponse
 from pydantic import BaseModel, Field
 
-from app.gateway.authz import require_auth, require_permission
-from app.gateway.deps import get_checkpointer, get_run_manager, get_stream_bridge
+from app.gateway.authz import require_permission
+from app.gateway.deps import get_checkpointer, get_run_event_store, get_run_manager, get_run_store, get_stream_bridge
 from app.gateway.services import sse_consumer, start_run
 from deerflow.runtime import RunRecord, serialize_channel_values
 
@@ -54,6 +54,7 @@ class RunCreateRequest(BaseModel):
     after_seconds: float | None = Field(default=None, description="Delayed execution")
     if_not_exists: Literal["reject", "create"] = Field(default="create", description="Thread creation policy")
     feedback_keys: list[str] | None = Field(default=None, description="LangSmith feedback keys")
+    follow_up_to_run_id: str | None = Field(default=None, description="Run ID this message follows up on. Auto-detected from latest successful run if not provided.")
 
 
 class RunResponse(BaseModel):
@@ -93,28 +94,21 @@ def _record_to_response(record: RunRecord) -> RunResponse:
 
 
 @router.post("/{thread_id}/runs", response_model=RunResponse)
-@require_auth
-@require_permission("runs", "create", owner_check=True)
+@require_permission("runs", "create", owner_check=True, require_existing=True)
 async def create_run(thread_id: str, body: RunCreateRequest, request: Request) -> RunResponse:
-    """Create a background run (returns immediately).
-
-    Multi-tenant isolation: only the thread owner can create runs.
-    """
+    """Create a background run (returns immediately)."""
     record = await start_run(body, thread_id, request)
     return _record_to_response(record)
 
 
 @router.post("/{thread_id}/runs/stream")
-@require_auth
-@require_permission("runs", "create", owner_check=True)
+@require_permission("runs", "create", owner_check=True, require_existing=True)
 async def stream_run(thread_id: str, body: RunCreateRequest, request: Request) -> StreamingResponse:
     """Create a run and stream events via SSE.
 
     The response includes a ``Content-Location`` header with the run's
     resource URL, matching the LangGraph Platform protocol.  The
     ``useStream`` React hook uses this to extract run metadata.
-
-    Multi-tenant isolation: only the thread owner can stream runs.
     """
     bridge = get_stream_bridge(request)
     run_mgr = get_run_manager(request)
@@ -128,20 +122,17 @@ async def stream_run(thread_id: str, body: RunCreateRequest, request: Request) -
             "Connection": "keep-alive",
             "X-Accel-Buffering": "no",
             # LangGraph Platform includes run metadata in this header.
-            # The SDK's _get_run_metadata_from_response() parses it.
-            "Content-Location": (f"/api/threads/{thread_id}/runs/{record.run_id}/stream?thread_id={thread_id}&run_id={record.run_id}"),
+            # The SDK uses a greedy regex to extract the run id from this path,
+            # so it must point at the canonical run resource without extra suffixes.
+            "Content-Location": f"/api/threads/{thread_id}/runs/{record.run_id}",
         },
     )
 
 
 @router.post("/{thread_id}/runs/wait", response_model=dict)
-@require_auth
-@require_permission("runs", "create", owner_check=True)
+@require_permission("runs", "create", owner_check=True, require_existing=True)
 async def wait_run(thread_id: str, body: RunCreateRequest, request: Request) -> dict:
-    """Create a run and block until it completes, returning the final state.
-
-    Multi-tenant isolation: only the thread owner can wait for runs.
-    """
+    """Create a run and block until it completes, returning the final state."""
     record = await start_run(body, thread_id, request)
 
     if record.task is not None:
@@ -165,26 +156,18 @@ async def wait_run(thread_id: str, body: RunCreateRequest, request: Request) ->
 
 
 @router.get("/{thread_id}/runs", response_model=list[RunResponse])
-@require_auth
 @require_permission("runs", "read", owner_check=True)
 async def list_runs(thread_id: str, request: Request) -> list[RunResponse]:
-    """List all runs for a thread.
-
-    Multi-tenant isolation: only the thread owner can list runs.
-    """
+    """List all runs for a thread."""
     run_mgr = get_run_manager(request)
     records = await run_mgr.list_by_thread(thread_id)
     return [_record_to_response(r) for r in records]
 
 
 @router.get("/{thread_id}/runs/{run_id}", response_model=RunResponse)
-@require_auth
 @require_permission("runs", "read", owner_check=True)
 async def get_run(thread_id: str, run_id: str, request: Request) -> RunResponse:
-    """Get details of a specific run.
-
-    Multi-tenant isolation: only the thread owner can get runs.
-    """
+    """Get details of a specific run."""
     run_mgr = get_run_manager(request)
     record = run_mgr.get(run_id)
     if record is None or record.thread_id != thread_id:
@@ -193,8 +176,7 @@ async def get_run(thread_id: str, run_id: str, request: Request) -> RunResponse:
 
 
 @router.post("/{thread_id}/runs/{run_id}/cancel")
-@require_auth
-@require_permission("runs", "cancel", owner_check=True)
+@require_permission("runs", "cancel", owner_check=True, require_existing=True)
 async def cancel_run(
     thread_id: str,
     run_id: str,
@@ -208,8 +190,6 @@ async def cancel_run(
     - action=rollback: Stop execution, revert to pre-run checkpoint state
     - wait=true: Block until the run fully stops, return 204
     - wait=false: Return immediately with 202
-
-    Multi-tenant isolation: only the thread owner can cancel runs.
     """
     run_mgr = get_run_manager(request)
     record = run_mgr.get(run_id)
@@ -234,13 +214,9 @@ async def cancel_run(
 
 
 @router.get("/{thread_id}/runs/{run_id}/join")
-@require_auth
 @require_permission("runs", "read", owner_check=True)
 async def join_run(thread_id: str, run_id: str, request: Request) -> StreamingResponse:
-    """Join an existing run's SSE stream.
-
-    Multi-tenant isolation: only the thread owner can join runs.
-    """
+    """Join an existing run's SSE stream."""
     bridge = get_stream_bridge(request)
     run_mgr = get_run_manager(request)
     record = run_mgr.get(run_id)
@@ -259,6 +235,7 @@ async def join_run(thread_id: str, run_id: str, request: Request) -> StreamingRe
 
 
 @router.api_route("/{thread_id}/runs/{run_id}/stream", methods=["GET", "POST"], response_model=None)
+@require_permission("runs", "read", owner_check=True)
 async def stream_existing_run(
     thread_id: str,
     run_id: str,
@@ -298,3 +275,54 @@ async def stream_existing_run(
             "X-Accel-Buffering": "no",
         },
     )
+
+
+# ---------------------------------------------------------------------------
+# Messages / Events / Token usage endpoints
+# ---------------------------------------------------------------------------
+
+
+@router.get("/{thread_id}/messages")
+@require_permission("runs", "read", owner_check=True)
+async def list_thread_messages(
+    thread_id: str,
+    request: Request,
+    limit: int = Query(default=50, le=200),
+    before_seq: int | None = Query(default=None),
+    after_seq: int | None = Query(default=None),
+) -> list[dict]:
+    """Return displayable messages for a thread (across all runs)."""
+    event_store = get_run_event_store(request)
+    return await event_store.list_messages(thread_id, limit=limit, before_seq=before_seq, after_seq=after_seq)
+
+
+@router.get("/{thread_id}/runs/{run_id}/messages")
+@require_permission("runs", "read", owner_check=True)
+async def list_run_messages(thread_id: str, run_id: str, request: Request) -> list[dict]:
+    """Return displayable messages for a specific run."""
+    event_store = get_run_event_store(request)
+    return await event_store.list_messages_by_run(thread_id, run_id)
+
+
+@router.get("/{thread_id}/runs/{run_id}/events")
+@require_permission("runs", "read", owner_check=True)
+async def list_run_events(
+    thread_id: str,
+    run_id: str,
+    request: Request,
+    event_types: str | None = Query(default=None),
+    limit: int = Query(default=500, le=2000),
+) -> list[dict]:
+    """Return the full event stream for a run (debug/audit)."""
+    event_store = get_run_event_store(request)
+    types = event_types.split(",") if event_types else None
+    return await event_store.list_events(thread_id, run_id, event_types=types, limit=limit)
+
+
+@router.get("/{thread_id}/token-usage")
+@require_permission("threads", "read", owner_check=True)
+async def thread_token_usage(thread_id: str, request: Request) -> dict:
+    """Thread-level token usage aggregation."""
+    run_store = get_run_store(request)
+    agg = await run_store.aggregate_tokens_by_thread(thread_id)
+    return {"thread_id": thread_id, **agg}

backend/app/gateway/routers/threads.py

@@ -13,37 +13,39 @@ matching the LangGraph Platform wire format expected by the
 from __future__ import annotations
 
 import logging
-import re
 import time
 import uuid
-from typing import Annotated, Any
+from typing import Any
 
-from fastapi import APIRouter, HTTPException, Path, Request
+from fastapi import APIRouter, HTTPException, Request
 from pydantic import BaseModel, Field, field_validator
 
-from app.gateway.authz import require_auth, require_permission
-from app.gateway.deps import get_checkpointer, get_store
+from app.gateway.authz import require_permission
+from app.gateway.deps import get_checkpointer
+from app.gateway.utils import sanitize_log_param
 from deerflow.config.paths import Paths, get_paths
 from deerflow.runtime import serialize_channel_values
 
-# ---------------------------------------------------------------------------
-# Thread ID validation (prevents log-injection via control characters)
-# ---------------------------------------------------------------------------
-
-_UUID_RE = re.compile(r"^[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{12}$")
-ThreadId = Annotated[str, Path(description="Thread UUID", pattern=_UUID_RE.pattern)]
-
-# ---------------------------------------------------------------------------
-# Store namespace
-# ---------------------------------------------------------------------------
-
-THREADS_NS: tuple[str, ...] = ("threads",)
-"""Namespace used by the Store for thread metadata records."""
-
 logger = logging.getLogger(__name__)
 router = APIRouter(prefix="/api/threads", tags=["threads"])
 
 
+# Metadata keys that the server controls; clients are not allowed to set
+# them. Pydantic ``@field_validator("metadata")`` strips them on every
+# inbound model below so a malicious client cannot reflect a forged
+# owner identity through the API surface. Defense-in-depth — the
+# row-level invariant is still ``threads_meta.owner_id`` populated from
+# the auth contextvar; this list closes the metadata-blob echo gap.
+_SERVER_RESERVED_METADATA_KEYS: frozenset[str] = frozenset({"owner_id", "user_id"})
+
+
+def _strip_reserved_metadata(metadata: dict[str, Any] | None) -> dict[str, Any]:
+    """Return ``metadata`` with server-controlled keys removed."""
+    if not metadata:
+        return metadata or {}
+    return {k: v for k, v in metadata.items() if k not in _SERVER_RESERVED_METADATA_KEYS}
+
+
 # ---------------------------------------------------------------------------
 # Response / request models
 # ---------------------------------------------------------------------------
@@ -72,14 +74,10 @@ class ThreadCreateRequest(BaseModel):
     """Request body for creating a thread."""
 
     thread_id: str | None = Field(default=None, description="Optional thread ID (auto-generated if omitted)")
+    assistant_id: str | None = Field(default=None, description="Associate thread with an assistant")
     metadata: dict[str, Any] = Field(default_factory=dict, description="Initial metadata")
 
-    @field_validator("thread_id")
-    @classmethod
-    def _validate_uuid(cls, v: str | None) -> str | None:
-        if v is not None and not _UUID_RE.match(v):
-            raise ValueError("thread_id must be a valid UUID")
-        return v
+    _strip_reserved = field_validator("metadata")(classmethod(lambda cls, v: _strip_reserved_metadata(v)))
 
 
 class ThreadSearchRequest(BaseModel):
@@ -109,6 +107,8 @@ class ThreadPatchRequest(BaseModel):
 
     metadata: dict[str, Any] = Field(default_factory=dict, description="Metadata to merge")
 
+    _strip_reserved = field_validator("metadata")(classmethod(lambda cls, v: _strip_reserved_metadata(v)))
+
 
 class ThreadStateUpdateRequest(BaseModel):
     """Request body for updating thread state (human-in-the-loop resume)."""
@@ -151,61 +151,16 @@ def _delete_thread_data(thread_id: str, paths: Paths | None = None) -> ThreadDel
         raise HTTPException(status_code=422, detail=str(exc)) from exc
     except FileNotFoundError:
         # Not critical — thread data may not exist on disk
-        logger.debug("No local thread data to delete for %s", thread_id)
+        logger.debug("No local thread data to delete for %s", sanitize_log_param(thread_id))
         return ThreadDeleteResponse(success=True, message=f"No local data for {thread_id}")
     except Exception as exc:
-        logger.exception("Failed to delete thread data for %s", thread_id)
+        logger.exception("Failed to delete thread data for %s", sanitize_log_param(thread_id))
         raise HTTPException(status_code=500, detail="Failed to delete local thread data.") from exc
 
-    logger.info("Deleted local thread data for %s", thread_id)
+    logger.info("Deleted local thread data for %s", sanitize_log_param(thread_id))
     return ThreadDeleteResponse(success=True, message=f"Deleted local thread data for {thread_id}")
 
 
-async def _store_get(store, thread_id: str) -> dict | None:
-    """Fetch a thread record from the Store; returns ``None`` if absent."""
-    item = await store.aget(THREADS_NS, thread_id)
-    return item.value if item is not None else None
-
-
-async def _store_put(store, record: dict) -> None:
-    """Write a thread record to the Store."""
-    await store.aput(THREADS_NS, record["thread_id"], record)
-
-
-async def _store_upsert(store, thread_id: str, *, metadata: dict | None = None, values: dict | None = None) -> None:
-    """Create or refresh a thread record in the Store.
-
-    On creation the record is written with ``status="idle"``.  On update only
-    ``updated_at`` (and optionally ``metadata`` / ``values``) are changed so
-    that existing fields are preserved.
-
-    ``values`` carries the agent-state snapshot exposed to the frontend
-    (currently just ``{"title": "..."}``).
-    """
-    now = time.time()
-    existing = await _store_get(store, thread_id)
-    if existing is None:
-        await _store_put(
-            store,
-            {
-                "thread_id": thread_id,
-                "status": "idle",
-                "created_at": now,
-                "updated_at": now,
-                "metadata": metadata or {},
-                "values": values or {},
-            },
-        )
-    else:
-        val = dict(existing)
-        val["updated_at"] = now
-        if metadata:
-            val.setdefault("metadata", {}).update(metadata)
-        if values:
-            val.setdefault("values", {}).update(values)
-        await _store_put(store, val)
-
-
 def _derive_thread_status(checkpoint_tuple) -> str:
     """Derive thread status from checkpoint metadata."""
     if checkpoint_tuple is None:
@@ -231,36 +186,35 @@ def _derive_thread_status(checkpoint_tuple) -> str:
 
 
 @router.delete("/{thread_id}", response_model=ThreadDeleteResponse)
-@require_auth
-@require_permission("threads", "delete", owner_check=True)
-async def delete_thread_data(thread_id: ThreadId, request: Request) -> ThreadDeleteResponse:
+@require_permission("threads", "delete", owner_check=True, require_existing=True)
+async def delete_thread_data(thread_id: str, request: Request) -> ThreadDeleteResponse:
     """Delete local persisted filesystem data for a thread.
 
     Cleans DeerFlow-managed thread directories, removes checkpoint data,
-    and removes the thread record from the Store.
-
-    Multi-tenant isolation: only the thread owner can delete their thread.
+    and removes the thread_meta row from the configured ThreadMetaStore
+    (sqlite or memory).
     """
-    store = get_store(request)
-    checkpointer = get_checkpointer(request)
+    from app.gateway.deps import get_thread_meta_repo
 
     # Clean local filesystem
     response = _delete_thread_data(thread_id)
 
-    # Remove from Store (best-effort)
-    if store is not None:
-        try:
-            await store.adelete(THREADS_NS, thread_id)
-        except Exception:
-            logger.debug("Could not delete store record for thread %s (not critical)", thread_id)
-
     # Remove checkpoints (best-effort)
+    checkpointer = getattr(request.app.state, "checkpointer", None)
     if checkpointer is not None:
         try:
             if hasattr(checkpointer, "adelete_thread"):
                 await checkpointer.adelete_thread(thread_id)
         except Exception:
-            logger.debug("Could not delete checkpoints for thread %s (not critical)", thread_id)
+            logger.debug("Could not delete checkpoints for thread %s (not critical)", sanitize_log_param(thread_id))
+
+    # Remove thread_meta row (best-effort) — required for sqlite backend
+    # so the deleted thread no longer appears in /threads/search.
+    try:
+        thread_meta_repo = get_thread_meta_repo(request)
+        await thread_meta_repo.delete(thread_id)
+    except Exception:
+        logger.debug("Could not delete thread_meta for %s (not critical)", sanitize_log_param(thread_id))
 
     return response
 
@@ -269,54 +223,40 @@ async def delete_thread_data(thread_id: ThreadId, request: Request) -> ThreadDel
 async def create_thread(body: ThreadCreateRequest, request: Request) -> ThreadResponse:
     """Create a new thread.
 
-    The thread record is written to the Store (for fast listing) and an
-    empty checkpoint is written to the checkpointer (for state reads).
+    Writes a thread_meta record (so the thread appears in /threads/search)
+    and an empty checkpoint (so state endpoints work immediately).
     Idempotent: returns the existing record when ``thread_id`` already exists.
-
-    If authenticated, the user's ID is injected into the thread metadata
-    for multi-tenant isolation.
     """
-    store = get_store(request)
+    from app.gateway.deps import get_thread_meta_repo
+
     checkpointer = get_checkpointer(request)
+    thread_meta_repo = get_thread_meta_repo(request)
     thread_id = body.thread_id or str(uuid.uuid4())
     now = time.time()
+    # ``body.metadata`` is already stripped of server-reserved keys by
+    # ``ThreadCreateRequest._strip_reserved`` — see the model definition.
 
-    from app.gateway.deps import get_optional_user_from_request
+    # Idempotency: return existing record when already present
+    existing_record = await thread_meta_repo.get(thread_id)
+    if existing_record is not None:
+        return ThreadResponse(
+            thread_id=thread_id,
+            status=existing_record.get("status", "idle"),
+            created_at=str(existing_record.get("created_at", "")),
+            updated_at=str(existing_record.get("updated_at", "")),
+            metadata=existing_record.get("metadata", {}),
+        )
 
-    user = await get_optional_user_from_request(request)
-
-    thread_metadata = dict(body.metadata)
-    if user:
-        thread_metadata["user_id"] = str(user.id)
-
-    # Idempotency: return existing record from Store when already present
-    if store is not None:
-        existing_record = await _store_get(store, thread_id)
-        if existing_record is not None:
-            return ThreadResponse(
-                thread_id=thread_id,
-                status=existing_record.get("status", "idle"),
-                created_at=str(existing_record.get("created_at", "")),
-                updated_at=str(existing_record.get("updated_at", "")),
-                metadata=existing_record.get("metadata", {}),
-            )
-
-    # Write thread record to Store
-    if store is not None:
-        try:
-            await _store_put(
-                store,
-                {
-                    "thread_id": thread_id,
-                    "status": "idle",
-                    "created_at": now,
-                    "updated_at": now,
-                    "metadata": thread_metadata,
-                },
-            )
-        except Exception:
-            logger.exception("Failed to write thread %s to store", thread_id)
-            raise HTTPException(status_code=500, detail="Failed to create thread")
+    # Write thread_meta so the thread appears in /threads/search immediately
+    try:
+        await thread_meta_repo.create(
+            thread_id,
+            assistant_id=getattr(body, "assistant_id", None),
+            metadata=body.metadata,
+        )
+    except Exception:
+        logger.exception("Failed to write thread_meta for %s", sanitize_log_param(thread_id))
+        raise HTTPException(status_code=500, detail="Failed to create thread")
 
     # Write an empty checkpoint so state endpoints work immediately
     config = {"configurable": {"thread_id": thread_id, "checkpoint_ns": ""}}
@@ -328,21 +268,21 @@ async def create_thread(body: ThreadCreateRequest, request: Request) -> ThreadRe
             "source": "input",
             "writes": None,
             "parents": {},
-            **thread_metadata,
+            **body.metadata,
             "created_at": now,
         }
         await checkpointer.aput(config, empty_checkpoint(), ckpt_metadata, {})
     except Exception:
-        logger.exception("Failed to create checkpoint for thread %s", thread_id)
+        logger.exception("Failed to create checkpoint for thread %s", sanitize_log_param(thread_id))
         raise HTTPException(status_code=500, detail="Failed to create thread")
 
-    logger.info("Thread created: %s (user_id=%s)", thread_id, thread_metadata.get("user_id"))
+    logger.info("Thread created: %s", sanitize_log_param(thread_id))
     return ThreadResponse(
         thread_id=thread_id,
         status="idle",
         created_at=str(now),
         updated_at=str(now),
-        metadata=thread_metadata,
+        metadata=body.metadata,
     )
 
 
@@ -350,190 +290,91 @@ async def create_thread(body: ThreadCreateRequest, request: Request) -> ThreadRe
 async def search_threads(body: ThreadSearchRequest, request: Request) -> list[ThreadResponse]:
     """Search and list threads.
 
-    Two-phase approach:
-
-    **Phase 1 — Store (fast path, O(threads))**: returns threads that were
-    created or run through this Gateway.  Store records are tiny metadata
-    dicts so fetching all of them at once is cheap.
-
-    **Phase 2 — Checkpointer supplement (lazy migration)**: threads that
-    were created directly by LangGraph Server (and therefore absent from the
-    Store) are discovered here by iterating the shared checkpointer.  Any
-    newly found thread is immediately written to the Store so that the next
-    search skips Phase 2 for that thread — the Store converges to a full
-    index over time without a one-shot migration job.
-
-    If authenticated, only threads belonging to the current user are returned
-    (enforced by user_id metadata filter for multi-tenant isolation).
+    Delegates to the configured ThreadMetaStore implementation
+    (SQL-backed for sqlite/postgres, Store-backed for memory mode).
     """
-    store = get_store(request)
-    checkpointer = get_checkpointer(request)
+    from app.gateway.deps import get_thread_meta_repo
 
-    from app.gateway.deps import get_optional_user_from_request
-
-    user = await get_optional_user_from_request(request)
-    user_id = str(user.id) if user else None
-
-    # -----------------------------------------------------------------------
-    # Phase 1: Store
-    # -----------------------------------------------------------------------
-    merged: dict[str, ThreadResponse] = {}
-
-    if store is not None:
-        try:
-            items = await store.asearch(THREADS_NS, limit=10_000)
-        except Exception:
-            logger.warning("Store search failed — falling back to checkpointer only", exc_info=True)
-            items = []
-
-        for item in items:
-            val = item.value
-            merged[val["thread_id"]] = ThreadResponse(
-                thread_id=val["thread_id"],
-                status=val.get("status", "idle"),
-                created_at=str(val.get("created_at", "")),
-                updated_at=str(val.get("updated_at", "")),
-                metadata=val.get("metadata", {}),
-                values=val.get("values", {}),
-            )
-
-    # -----------------------------------------------------------------------
-    # Phase 2: Checkpointer supplement
-    # Discovers threads not yet in the Store (e.g. created by LangGraph
-    # Server) and lazily migrates them so future searches skip this phase.
-    # -----------------------------------------------------------------------
-    try:
-        async for checkpoint_tuple in checkpointer.alist(None):
-            cfg = getattr(checkpoint_tuple, "config", {})
-            thread_id = cfg.get("configurable", {}).get("thread_id")
-            if not thread_id or thread_id in merged:
-                continue
-
-            # Skip sub-graph checkpoints (checkpoint_ns is non-empty for those)
-            if cfg.get("configurable", {}).get("checkpoint_ns", ""):
-                continue
-
-            ckpt_meta = getattr(checkpoint_tuple, "metadata", {}) or {}
-            # Strip LangGraph internal keys from the user-visible metadata dict
-            user_meta = {k: v for k, v in ckpt_meta.items() if k not in ("created_at", "updated_at", "step", "source", "writes", "parents")}
-
-            # Extract state values (title) from the checkpoint's channel_values
-            checkpoint_data = getattr(checkpoint_tuple, "checkpoint", {}) or {}
-            channel_values = checkpoint_data.get("channel_values", {})
-            ckpt_values = {}
-            if title := channel_values.get("title"):
-                ckpt_values["title"] = title
-
-            thread_resp = ThreadResponse(
-                thread_id=thread_id,
-                status=_derive_thread_status(checkpoint_tuple),
-                created_at=str(ckpt_meta.get("created_at", "")),
-                updated_at=str(ckpt_meta.get("updated_at", ckpt_meta.get("created_at", ""))),
-                metadata=user_meta,
-                values=ckpt_values,
-            )
-            merged[thread_id] = thread_resp
-
-            # Lazy migration — write to Store so the next search finds it there
-            if store is not None:
-                try:
-                    await _store_upsert(store, thread_id, metadata=user_meta, values=ckpt_values or None)
-                except Exception:
-                    logger.debug("Failed to migrate thread %s to store (non-fatal)", thread_id)
-    except Exception:
-        logger.exception("Checkpointer scan failed during thread search")
-        # Don't raise — return whatever was collected from Store + partial scan
-
-    # -----------------------------------------------------------------------
-    # Phase 3: Filter → sort → paginate
-    # -----------------------------------------------------------------------
-    results = list(merged.values())
-
-    # Multi-tenant isolation: filter by user_id if authenticated
-    if user_id:
-        results = [r for r in results if r.metadata.get("user_id") == user_id]
-
-    if body.metadata:
-        results = [r for r in results if all(r.metadata.get(k) == v for k, v in body.metadata.items())]
-
-    if body.status:
-        results = [r for r in results if r.status == body.status]
-
-    results.sort(key=lambda r: r.updated_at, reverse=True)
-    return results[body.offset : body.offset + body.limit]
+    repo = get_thread_meta_repo(request)
+    rows = await repo.search(
+        metadata=body.metadata or None,
+        status=body.status,
+        limit=body.limit,
+        offset=body.offset,
+    )
+    return [
+        ThreadResponse(
+            thread_id=r["thread_id"],
+            status=r.get("status", "idle"),
+            created_at=r.get("created_at", ""),
+            updated_at=r.get("updated_at", ""),
+            metadata=r.get("metadata", {}),
+            values={"title": r["display_name"]} if r.get("display_name") else {},
+            interrupts={},
+        )
+        for r in rows
+    ]
 
 
 @router.patch("/{thread_id}", response_model=ThreadResponse)
-@require_auth
-@require_permission("threads", "write", owner_check=True, inject_record=True)
-async def patch_thread(thread_id: ThreadId, request: Request, body: ThreadPatchRequest, thread_record: dict = None) -> ThreadResponse:
-    """Merge metadata into a thread record.
+@require_permission("threads", "write", owner_check=True, require_existing=True)
+async def patch_thread(thread_id: str, body: ThreadPatchRequest, request: Request) -> ThreadResponse:
+    """Merge metadata into a thread record."""
+    from app.gateway.deps import get_thread_meta_repo
 
-    Multi-tenant isolation: only the thread owner can patch their thread.
-    """
-    store = get_store(request)
-    if store is None:
-        raise HTTPException(status_code=503, detail="Store not available")
-
-    record = thread_record
-    if record is None:
-        record = await _store_get(store, thread_id)
+    thread_meta_repo = get_thread_meta_repo(request)
+    record = await thread_meta_repo.get(thread_id)
     if record is None:
         raise HTTPException(status_code=404, detail=f"Thread {thread_id} not found")
 
-    now = time.time()
-    updated = dict(record)
-    updated.setdefault("metadata", {}).update(body.metadata)
-    updated["updated_at"] = now
-
+    # ``body.metadata`` already stripped by ``ThreadPatchRequest._strip_reserved``.
     try:
-        await _store_put(store, updated)
+        await thread_meta_repo.update_metadata(thread_id, body.metadata)
     except Exception:
-        logger.exception("Failed to patch thread %s", thread_id)
+        logger.exception("Failed to patch thread %s", sanitize_log_param(thread_id))
         raise HTTPException(status_code=500, detail="Failed to update thread")
 
+    # Re-read to get the merged metadata + refreshed updated_at
+    record = await thread_meta_repo.get(thread_id) or record
     return ThreadResponse(
         thread_id=thread_id,
-        status=updated.get("status", "idle"),
-        created_at=str(updated.get("created_at", "")),
-        updated_at=str(now),
-        metadata=updated.get("metadata", {}),
+        status=record.get("status", "idle"),
+        created_at=str(record.get("created_at", "")),
+        updated_at=str(record.get("updated_at", "")),
+        metadata=record.get("metadata", {}),
     )
 
 
 @router.get("/{thread_id}", response_model=ThreadResponse)
-@require_auth
 @require_permission("threads", "read", owner_check=True)
-async def get_thread(thread_id: ThreadId, request: Request) -> ThreadResponse:
+async def get_thread(thread_id: str, request: Request) -> ThreadResponse:
     """Get thread info.
 
-    Reads metadata from the Store and derives the accurate execution
-    status from the checkpointer.  Falls back to the checkpointer alone
-    for threads that pre-date Store adoption (backward compat).
-
-    Multi-tenant isolation: returns 404 if the thread does not belong to
-    the authenticated user.
+    Reads metadata from the ThreadMetaStore and derives the accurate
+    execution status from the checkpointer.  Falls back to the checkpointer
+    alone for threads that pre-date ThreadMetaStore adoption (backward compat).
     """
-    store = get_store(request)
+    from app.gateway.deps import get_thread_meta_repo
+
+    thread_meta_repo = get_thread_meta_repo(request)
     checkpointer = get_checkpointer(request)
 
-    record: dict | None = None
-    if store is not None:
-        record = await _store_get(store, thread_id)
+    record: dict | None = await thread_meta_repo.get(thread_id)
 
     # Derive accurate status from the checkpointer
     config = {"configurable": {"thread_id": thread_id, "checkpoint_ns": ""}}
     try:
         checkpoint_tuple = await checkpointer.aget_tuple(config)
     except Exception:
-        logger.exception("Failed to get checkpoint for thread %s", thread_id)
+        logger.exception("Failed to get checkpoint for thread %s", sanitize_log_param(thread_id))
         raise HTTPException(status_code=500, detail="Failed to get thread")
 
     if record is None and checkpoint_tuple is None:
         raise HTTPException(status_code=404, detail=f"Thread {thread_id} not found")
 
-    # If the thread exists in the checkpointer but not the store (e.g. legacy
-    # data), synthesize a minimal store record from the checkpoint metadata.
+    # If the thread exists in the checkpointer but not in thread_meta (e.g.
+    # legacy data created before thread_meta adoption), synthesize a minimal
+    # record from the checkpoint metadata.
     if record is None and checkpoint_tuple is not None:
         ckpt_meta = getattr(checkpoint_tuple, "metadata", {}) or {}
         record = {
@@ -562,15 +403,12 @@ async def get_thread(thread_id: ThreadId, request: Request) -> ThreadResponse:
 
 
 @router.get("/{thread_id}/state", response_model=ThreadStateResponse)
-@require_auth
 @require_permission("threads", "read", owner_check=True)
-async def get_thread_state(thread_id: ThreadId, request: Request) -> ThreadStateResponse:
+async def get_thread_state(thread_id: str, request: Request) -> ThreadStateResponse:
     """Get the latest state snapshot for a thread.
 
     Channel values are serialized to ensure LangChain message objects
     are converted to JSON-safe dicts.
-
-    Multi-tenant isolation: returns 404 if thread does not belong to user.
     """
     checkpointer = get_checkpointer(request)
 
@@ -578,7 +416,7 @@ async def get_thread_state(thread_id: ThreadId, request: Request) -> ThreadState
     try:
         checkpoint_tuple = await checkpointer.aget_tuple(config)
     except Exception:
-        logger.exception("Failed to get state for thread %s", thread_id)
+        logger.exception("Failed to get state for thread %s", sanitize_log_param(thread_id))
         raise HTTPException(status_code=500, detail="Failed to get thread state")
 
     if checkpoint_tuple is None:
@@ -615,19 +453,19 @@ async def get_thread_state(thread_id: ThreadId, request: Request) -> ThreadState
 
 
 @router.post("/{thread_id}/state", response_model=ThreadStateResponse)
-@require_auth
-@require_permission("threads", "write", owner_check=True)
-async def update_thread_state(thread_id: ThreadId, body: ThreadStateUpdateRequest, request: Request) -> ThreadStateResponse:
+@require_permission("threads", "write", owner_check=True, require_existing=True)
+async def update_thread_state(thread_id: str, body: ThreadStateUpdateRequest, request: Request) -> ThreadStateResponse:
     """Update thread state (e.g. for human-in-the-loop resume or title rename).
 
     Writes a new checkpoint that merges *body.values* into the latest
-    channel values, then syncs any updated ``title`` field back to the Store
-    so that ``/threads/search`` reflects the change immediately.
-
-    Multi-tenant isolation: only the thread owner can update their thread.
+    channel values, then syncs any updated ``title`` field through the
+    ThreadMetaStore abstraction so that ``/threads/search`` reflects the
+    change immediately in both sqlite and memory backends.
     """
+    from app.gateway.deps import get_thread_meta_repo
+
     checkpointer = get_checkpointer(request)
-    store = get_store(request)
+    thread_meta_repo = get_thread_meta_repo(request)
 
     # checkpoint_ns must be present in the config for aput — default to ""
     # (the root graph namespace).  checkpoint_id is optional; omitting it
@@ -644,7 +482,7 @@ async def update_thread_state(thread_id: ThreadId, body: ThreadStateUpdateReques
     try:
         checkpoint_tuple = await checkpointer.aget_tuple(read_config)
     except Exception:
-        logger.exception("Failed to get state for thread %s", thread_id)
+        logger.exception("Failed to get state for thread %s", sanitize_log_param(thread_id))
         raise HTTPException(status_code=500, detail="Failed to get thread state")
 
     if checkpoint_tuple is None:
@@ -678,19 +516,22 @@ async def update_thread_state(thread_id: ThreadId, body: ThreadStateUpdateReques
     try:
         new_config = await checkpointer.aput(write_config, checkpoint, metadata, {})
     except Exception:
-        logger.exception("Failed to update state for thread %s", thread_id)
+        logger.exception("Failed to update state for thread %s", sanitize_log_param(thread_id))
         raise HTTPException(status_code=500, detail="Failed to update thread state")
 
     new_checkpoint_id: str | None = None
     if isinstance(new_config, dict):
         new_checkpoint_id = new_config.get("configurable", {}).get("checkpoint_id")
 
-    # Sync title changes to the Store so /threads/search reflects them immediately.
-    if store is not None and body.values and "title" in body.values:
-        try:
-            await _store_upsert(store, thread_id, values={"title": body.values["title"]})
-        except Exception:
-            logger.debug("Failed to sync title to store for thread %s (non-fatal)", thread_id)
+    # Sync title changes through the ThreadMetaStore abstraction so /threads/search
+    # reflects them immediately in both sqlite and memory backends.
+    if body.values and "title" in body.values:
+        new_title = body.values["title"]
+        if new_title:  # Skip empty strings and None
+            try:
+                await thread_meta_repo.update_display_name(thread_id, new_title)
+            except Exception:
+                logger.debug("Failed to sync title to thread_meta for %s (non-fatal)", sanitize_log_param(thread_id))
 
     return ThreadStateResponse(
         values=serialize_channel_values(channel_values),
@@ -702,12 +543,15 @@ async def update_thread_state(thread_id: ThreadId, body: ThreadStateUpdateReques
 
 
 @router.post("/{thread_id}/history", response_model=list[HistoryEntry])
-@require_auth
 @require_permission("threads", "read", owner_check=True)
-async def get_thread_history(thread_id: ThreadId, body: ThreadHistoryRequest, request: Request) -> list[HistoryEntry]:
+async def get_thread_history(thread_id: str, body: ThreadHistoryRequest, request: Request) -> list[HistoryEntry]:
     """Get checkpoint history for a thread.
 
-    Multi-tenant isolation: returns 404 if thread does not belong to user.
+    Messages are read from the checkpointer's channel values (the
+    authoritative source) and serialized via
+    :func:`~deerflow.runtime.serialization.serialize_channel_values`.
+    Only the latest (first) checkpoint carries the ``messages`` key to
+    avoid duplicating them across every entry.
     """
     checkpointer = get_checkpointer(request)
 
@@ -716,6 +560,7 @@ async def get_thread_history(thread_id: ThreadId, body: ThreadHistoryRequest, re
         config["configurable"]["checkpoint_id"] = body.before
 
     entries: list[HistoryEntry] = []
+    is_latest_checkpoint = True
     try:
         async for checkpoint_tuple in checkpointer.alist(config, limit=body.limit):
             ckpt_config = getattr(checkpoint_tuple, "config", {})
@@ -730,22 +575,42 @@ async def get_thread_history(thread_id: ThreadId, body: ThreadHistoryRequest, re
 
             channel_values = checkpoint.get("channel_values", {})
 
+            # Build values from checkpoint channel_values
+            values: dict[str, Any] = {}
+            if title := channel_values.get("title"):
+                values["title"] = title
+            if thread_data := channel_values.get("thread_data"):
+                values["thread_data"] = thread_data
+
+            # Attach messages from checkpointer only for the latest checkpoint
+            if is_latest_checkpoint:
+                messages = channel_values.get("messages")
+                if messages:
+                    values["messages"] = serialize_channel_values({"messages": messages}).get("messages", [])
+            is_latest_checkpoint = False
+
             # Derive next tasks
             tasks_raw = getattr(checkpoint_tuple, "tasks", []) or []
             next_tasks = [t.name for t in tasks_raw if hasattr(t, "name")]
 
+            # Strip LangGraph internal keys from metadata
+            user_meta = {k: v for k, v in metadata.items() if k not in ("created_at", "updated_at", "step", "source", "writes", "parents")}
+            # Keep step for ordering context
+            if "step" in metadata:
+                user_meta["step"] = metadata["step"]
+
             entries.append(
                 HistoryEntry(
                     checkpoint_id=checkpoint_id,
                     parent_checkpoint_id=parent_id,
-                    metadata=metadata,
-                    values=serialize_channel_values(channel_values),
+                    metadata=user_meta,
+                    values=values,
                     created_at=str(metadata.get("created_at", "")),
                     next=next_tasks,
                 )
             )
     except Exception:
-        logger.exception("Failed to get history for thread %s", thread_id)
+        logger.exception("Failed to get history for thread %s", sanitize_log_param(thread_id))
         raise HTTPException(status_code=500, detail="Failed to get thread history")
 
     return entries

backend/app/gateway/routers/uploads.py

@@ -4,9 +4,10 @@ import logging
 import os
 import stat
 
-from fastapi import APIRouter, File, HTTPException, UploadFile
+from fastapi import APIRouter, File, HTTPException, Request, UploadFile
 from pydantic import BaseModel
 
+from app.gateway.authz import require_permission
 from deerflow.config.paths import get_paths
 from deerflow.sandbox.sandbox_provider import get_sandbox_provider
 from deerflow.uploads.manager import (
@@ -54,8 +55,10 @@ def _make_file_sandbox_writable(file_path: os.PathLike[str] | str) -> None:
 
 
 @router.post("", response_model=UploadResponse)
+@require_permission("threads", "write", owner_check=True, require_existing=True)
 async def upload_files(
     thread_id: str,
+    request: Request,
     files: list[UploadFile] = File(...),
 ) -> UploadResponse:
     """Upload multiple files to a thread's uploads directory."""
@@ -133,7 +136,8 @@ async def upload_files(
 
 
 @router.get("/list", response_model=dict)
-async def list_uploaded_files(thread_id: str) -> dict:
+@require_permission("threads", "read", owner_check=True)
+async def list_uploaded_files(thread_id: str, request: Request) -> dict:
     """List all files in a thread's uploads directory."""
     try:
         uploads_dir = get_uploads_dir(thread_id)
@@ -151,7 +155,8 @@ async def list_uploaded_files(thread_id: str) -> dict:
 
 
 @router.delete("/{filename}")
-async def delete_uploaded_file(thread_id: str, filename: str) -> dict:
+@require_permission("threads", "delete", owner_check=True, require_existing=True)
+async def delete_uploaded_file(thread_id: str, filename: str, request: Request) -> dict:
     """Delete a file from a thread's uploads directory."""
     try:
         uploads_dir = get_uploads_dir(thread_id)

backend/app/gateway/services.py

@@ -8,16 +8,17 @@ frames, and consuming stream bridge events.  Router modules
 from __future__ import annotations
 
 import asyncio
+import dataclasses
 import json
 import logging
 import re
-import time
 from typing import Any
 
 from fastapi import HTTPException, Request
 from langchain_core.messages import HumanMessage
 
-from app.gateway.deps import get_checkpointer, get_run_manager, get_store, get_stream_bridge
+from app.gateway.deps import get_run_context, get_run_manager, get_run_store, get_stream_bridge
+from app.gateway.utils import sanitize_log_param
 from deerflow.runtime import (
     END_SENTINEL,
     HEARTBEAT_SENTINEL,
@@ -116,7 +117,6 @@ def build_run_config(
     metadata: dict[str, Any] | None,
     *,
     assistant_id: str | None = None,
-    user_id: str | None = None,
 ) -> dict[str, Any]:
     """Build a RunnableConfig dict for the agent.
 
@@ -129,9 +129,6 @@ def build_run_config(
     This mirrors the channel manager's ``_resolve_run_params`` logic so that
     the LangGraph Platform-compatible HTTP API and the IM channel path behave
     identically.
-
-    If *user_id* is provided, it is injected into the config metadata for
-    multi-tenant isolation.
     """
     config: dict[str, Any] = {"recursion_limit": 100}
     if request_config:
@@ -165,11 +162,6 @@ def build_run_config(
             if not normalized or not re.fullmatch(r"[a-z0-9-]+", normalized):
                 raise ValueError(f"Invalid assistant_id {assistant_id!r}: must contain only letters, digits, and hyphens after normalization.")
             config["configurable"]["agent_name"] = normalized
-
-    # Multi-tenant isolation: inject user_id into metadata
-    if user_id:
-        config.setdefault("metadata", {})["user_id"] = user_id
-
     if metadata:
         config.setdefault("metadata", {}).update(metadata)
     return config
@@ -180,71 +172,6 @@ def build_run_config(
 # ---------------------------------------------------------------------------
 
 
-async def _upsert_thread_in_store(store, thread_id: str, metadata: dict | None) -> None:
-    """Create or refresh the thread record in the Store.
-
-    Called from :func:`start_run` so that threads created via the stateless
-    ``/runs/stream`` endpoint (which never calls ``POST /threads``) still
-    appear in ``/threads/search`` results.
-    """
-    # Deferred import to avoid circular import with the threads router module.
-    from app.gateway.routers.threads import _store_upsert
-
-    try:
-        await _store_upsert(store, thread_id, metadata=metadata)
-    except Exception:
-        logger.warning("Failed to upsert thread %s in store (non-fatal)", thread_id)
-
-
-async def _sync_thread_title_after_run(
-    run_task: asyncio.Task,
-    thread_id: str,
-    checkpointer: Any,
-    store: Any,
-) -> None:
-    """Wait for *run_task* to finish, then persist the generated title to the Store.
-
-    TitleMiddleware writes the generated title to the LangGraph agent state
-    (checkpointer) but the Gateway's Store record is not updated automatically.
-    This coroutine closes that gap by reading the final checkpoint after the
-    run completes and syncing ``values.title`` into the Store record so that
-    subsequent ``/threads/search`` responses include the correct title.
-
-    Runs as a fire-and-forget :func:`asyncio.create_task`; failures are
-    logged at DEBUG level and never propagate.
-    """
-    # Wait for the background run task to complete (any outcome).
-    # asyncio.wait does not propagate task exceptions — it just returns
-    # when the task is done, cancelled, or failed.
-    await asyncio.wait({run_task})
-
-    # Deferred import to avoid circular import with the threads router module.
-    from app.gateway.routers.threads import _store_get, _store_put
-
-    try:
-        ckpt_config = {"configurable": {"thread_id": thread_id, "checkpoint_ns": ""}}
-        ckpt_tuple = await checkpointer.aget_tuple(ckpt_config)
-        if ckpt_tuple is None:
-            return
-
-        channel_values = ckpt_tuple.checkpoint.get("channel_values", {})
-        title = channel_values.get("title")
-        if not title:
-            return
-
-        existing = await _store_get(store, thread_id)
-        if existing is None:
-            return
-
-        updated = dict(existing)
-        updated.setdefault("values", {})["title"] = title
-        updated["updated_at"] = time.time()
-        await _store_put(store, updated)
-        logger.debug("Synced title %r for thread %s", title, thread_id)
-    except Exception:
-        logger.debug("Failed to sync title for thread %s (non-fatal)", thread_id, exc_info=True)
-
-
 async def start_run(
     body: Any,
     thread_id: str,
@@ -264,14 +191,24 @@ async def start_run(
     """
     bridge = get_stream_bridge(request)
     run_mgr = get_run_manager(request)
-    checkpointer = get_checkpointer(request)
-    store = get_store(request)
+    run_ctx = get_run_context(request)
 
     disconnect = DisconnectMode.cancel if body.on_disconnect == "cancel" else DisconnectMode.continue_
 
-    # Reuse auth context set by @require_auth decorator to avoid redundant DB lookup
-    auth = getattr(request.state, "auth", None)
-    user_id = str(auth.user.id) if auth and auth.user else None
+    # Resolve follow_up_to_run_id: explicit from request, or auto-detect from latest successful run
+    follow_up_to_run_id = getattr(body, "follow_up_to_run_id", None)
+    if follow_up_to_run_id is None:
+        run_store = get_run_store(request)
+        try:
+            recent_runs = await run_store.list_by_thread(thread_id, limit=1)
+            if recent_runs and recent_runs[0].get("status") == "success":
+                follow_up_to_run_id = recent_runs[0]["run_id"]
+        except Exception:
+            pass  # Don't block run creation
+
+    # Enrich base context with per-run field
+    if follow_up_to_run_id:
+        run_ctx = dataclasses.replace(run_ctx, follow_up_to_run_id=follow_up_to_run_id)
 
     try:
         record = await run_mgr.create_or_reject(
@@ -281,27 +218,32 @@ async def start_run(
             metadata=body.metadata or {},
             kwargs={"input": body.input, "config": body.config},
             multitask_strategy=body.multitask_strategy,
+            follow_up_to_run_id=follow_up_to_run_id,
         )
     except ConflictError as exc:
         raise HTTPException(status_code=409, detail=str(exc)) from exc
     except UnsupportedStrategyError as exc:
         raise HTTPException(status_code=501, detail=str(exc)) from exc
 
-    # Ensure the thread is visible in /threads/search, even for threads that
-    # were never explicitly created via POST /threads (e.g. stateless runs).
-    store = get_store(request)
-    if store is not None:
-        await _upsert_thread_in_store(store, thread_id, body.metadata)
+    # Upsert thread metadata so the thread appears in /threads/search,
+    # even for threads that were never explicitly created via POST /threads
+    # (e.g. stateless runs).
+    try:
+        existing = await run_ctx.thread_meta_repo.get(thread_id)
+        if existing is None:
+            await run_ctx.thread_meta_repo.create(
+                thread_id,
+                assistant_id=body.assistant_id,
+                metadata=body.metadata,
+            )
+        else:
+            await run_ctx.thread_meta_repo.update_status(thread_id, "running")
+    except Exception:
+        logger.warning("Failed to upsert thread_meta for %s (non-fatal)", sanitize_log_param(thread_id))
 
     agent_factory = resolve_agent_factory(body.assistant_id)
     graph_input = normalize_input(body.input)
-    config = build_run_config(
-        thread_id,
-        body.config,
-        body.metadata,
-        assistant_id=body.assistant_id,
-        user_id=user_id,
-    )
+    config = build_run_config(thread_id, body.config, body.metadata, assistant_id=body.assistant_id)
 
     # Merge DeerFlow-specific context overrides into configurable.
     # The ``context`` field is a custom extension for the langgraph-compat layer
@@ -330,8 +272,7 @@ async def start_run(
             bridge,
             run_mgr,
             record,
-            checkpointer=checkpointer,
-            store=store,
+            ctx=run_ctx,
             agent_factory=agent_factory,
             graph_input=graph_input,
             config=config,
@@ -343,11 +284,9 @@ async def start_run(
     )
     record.task = task
 
-    # After the run completes, sync the title generated by TitleMiddleware from
-    # the checkpointer into the Store record so that /threads/search returns the
-    # correct title instead of an empty values dict.
-    if store is not None:
-        asyncio.create_task(_sync_thread_title_after_run(task, thread_id, checkpointer, store))
+    # Title sync is handled by worker.py's finally block which reads the
+    # title from the checkpoint and calls thread_meta_repo.update_display_name
+    # after the run completes.
 
     return record
 
@@ -364,8 +303,9 @@ async def sse_consumer(
     - ``cancel``: abort the background task on client disconnect.
     - ``continue``: let the task run; events are discarded.
     """
+    last_event_id = request.headers.get("Last-Event-ID")
     try:
-        async for entry in bridge.subscribe(record.run_id):
+        async for entry in bridge.subscribe(record.run_id, last_event_id=last_event_id):
             if await request.is_disconnected():
                 break
 

backend/app/gateway/utils.py

@@ -0,0 +1,6 @@
+"""Shared utility helpers for the Gateway layer."""
+
+
+def sanitize_log_param(value: str) -> str:
+    """Strip control characters to prevent log injection."""
+    return value.replace("\n", "").replace("\r", "").replace("\x00", "")

backend/docs/API.md

@@ -86,6 +86,7 @@ Content-Type: application/json
     ]
   },
   "config": {
+    "recursion_limit": 100,
     "configurable": {
       "model_name": "gpt-4",
       "thinking_enabled": false,
@@ -100,6 +101,21 @@ Content-Type: application/json
 - Use: `values`, `messages-tuple`, `custom`, `updates`, `events`, `debug`, `tasks`, `checkpoints`
 - Do not use: `tools` (deprecated/invalid in current `langgraph-api` and will trigger schema validation errors)
 
+**Recursion Limit:**
+
+`config.recursion_limit` caps the number of graph steps LangGraph will execute
+in a single run. The `/api/langgraph/*` endpoints go straight to the LangGraph
+server and therefore inherit LangGraph's native default of **25**, which is
+too low for plan-mode or subagent-heavy runs — the agent typically errors out
+with `GraphRecursionError` after the first round of subagent results comes
+back, before the lead agent can synthesize the final answer.
+
+DeerFlow's own Gateway and IM-channel paths mitigate this by defaulting to
+`100` in `build_run_config` (see `backend/app/gateway/services.py`), but
+clients calling the LangGraph API directly must set `recursion_limit`
+explicitly in the request body. `100` matches the Gateway default and is a
+safe starting point; increase it if you run deeply nested subagent graphs.
+
 **Configurable Options:**
 - `model_name` (string): Override the default model
 - `thinking_enabled` (boolean): Enable extended thinking for supported models
@@ -626,6 +642,14 @@ curl -X POST http://localhost:2026/api/langgraph/threads/abc123/runs \
   -H "Content-Type: application/json" \
   -d '{
     "input": {"messages": [{"role": "user", "content": "Hello"}]},
-    "config": {"configurable": {"model_name": "gpt-4"}}
+    "config": {
+      "recursion_limit": 100,
+      "configurable": {"model_name": "gpt-4"}
+    }
   }'
 ```
+
+> The `/api/langgraph/*` endpoints bypass DeerFlow's Gateway and inherit
+> LangGraph's native `recursion_limit` default of 25, which is too low for
+> plan-mode or subagent runs. Set `config.recursion_limit` explicitly — see
+> the [Create Run](#create-run) section for details.

backend/docs/AUTH_TEST_DOCKER_GAP.md

@@ -0,0 +1,77 @@
+# Docker Test Gap (Section 七 7.4)
+
+This file documents the only **un-executed** test cases from
+`backend/docs/AUTH_TEST_PLAN.md` after the full release validation pass.
+
+## Why this gap exists
+
+The release validation environment (sg_dev: `10.251.229.92`) **does not have
+a Docker daemon installed**. The TC-DOCKER cases are container-runtime
+behavior tests that need an actual Docker engine to spin up
+`docker/docker-compose.yaml` services.
+
+```bash
+$ ssh sg_dev "which docker; docker --version"
+# (empty)
+# bash: docker: command not found
+```
+
+All other test plan sections were executed against either:
+- The local dev box (Mac, all services running locally), or
+- The deployed sg_dev instance (gateway + frontend + nginx via SSH tunnel)
+
+## Cases not executed
+
+| Case | Title | What it covers | Why not run |
+|---|---|---|---|
+| TC-DOCKER-01 | `users.db` volume persistence | Verify the `DEER_FLOW_HOME` bind mount survives container restart | needs `docker compose up` |
+| TC-DOCKER-02 | Session persistence across container restart | `AUTH_JWT_SECRET` env var keeps cookies valid after `docker compose down && up` | needs `docker compose down/up` |
+| TC-DOCKER-03 | Per-worker rate limiter divergence | Confirms in-process `_login_attempts` dict doesn't share state across `gunicorn` workers (4 by default in the compose file); known limitation, documented | needs multi-worker container |
+| TC-DOCKER-04 | IM channels skip AuthMiddleware | Verify Feishu/Slack/Telegram dispatchers run in-container against `http://langgraph:2024` without going through nginx | needs `docker logs` |
+| TC-DOCKER-05 | Admin credentials surfacing | **Updated post-simplify** — was "log scrape", now "0600 credential file in `DEER_FLOW_HOME`". The file-based behavior is already validated by TC-1.1 + TC-UPG-13 on sg_dev (non-Docker), so the only Docker-specific gap is verifying the volume mount carries the file out to the host | needs container + host volume |
+| TC-DOCKER-06 | Gateway-mode Docker deploy | `./scripts/deploy.sh --gateway` produces a 3-container topology (no `langgraph` container); same auth flow as standard mode | needs `docker compose --profile gateway` |
+
+## Coverage already provided by non-Docker tests
+
+The **auth-relevant** behavior in each Docker case is already exercised by
+the test cases that ran on sg_dev or local:
+
+| Docker case | Auth behavior covered by |
+|---|---|
+| TC-DOCKER-01 (volume persistence) | TC-REENT-01 on sg_dev (admin row survives gateway restart) — same SQLite file, just no container layer between |
+| TC-DOCKER-02 (session persistence) | TC-API-02/03/06 (cookie roundtrip), plus TC-REENT-04 (multi-cookie) — JWT verification is process-state-free, container restart is equivalent to `pkill uvicorn && uv run uvicorn` |
+| TC-DOCKER-03 (per-worker rate limit) | TC-GW-04 + TC-REENT-09 (single-worker rate limit + 5min expiry). The cross-worker divergence is an architectural property of the in-memory dict; no auth code path differs |
+| TC-DOCKER-04 (IM channels skip auth) | Code-level only: `app/channels/manager.py` uses `langgraph_sdk` directly with no cookie handling. The langgraph_auth handler is bypassed by going through SDK, not HTTP |
+| TC-DOCKER-05 (credential surfacing) | TC-1.1 on sg_dev (file at `~/deer-flow/backend/.deer-flow/admin_initial_credentials.txt`, mode 0600, password 22 chars) — the only Docker-unique step is whether the bind mount projects this path onto the host, which is a `docker compose` config check, not a runtime behavior change |
+| TC-DOCKER-06 (gateway-mode container) | Section 七 7.2 covered by TC-GW-01..05 + Section 二 (gateway-mode auth flow on sg_dev) — same Gateway code, container is just a packaging change |
+
+## Reproduction steps when Docker becomes available
+
+Anyone with `docker` + `docker compose` installed can reproduce the gap by
+running the test plan section verbatim. Pre-flight:
+
+```bash
+# Required on the host
+docker --version           # >=24.x
+docker compose version     # plugin >=2.x
+
+# Required env var (otherwise sessions reset on every container restart)
+echo "AUTH_JWT_SECRET=$(python3 -c 'import secrets; print(secrets.token_urlsafe(32))')" \
+  >> .env
+
+# Optional: pin DEER_FLOW_HOME to a stable host path
+echo "DEER_FLOW_HOME=$HOME/deer-flow-data" >> .env
+```
+
+Then run TC-DOCKER-01..06 from the test plan as written.
+
+## Decision log
+
+- **Not blocking the release.** The auth-relevant behavior in every Docker
+  case has an already-validated equivalent on bare metal. The gap is purely
+  about *container packaging* details (bind mounts, multi-worker, log
+  collection), not about whether the auth code paths work.
+- **TC-DOCKER-05 was updated in place** in `AUTH_TEST_PLAN.md` to reflect
+  the post-simplify reality (credentials file → 0600 file, no log leak).
+  The old "grep 'Password:' in docker logs" expectation would have failed
+  silently and given a false sense of coverage.

backend/docs/AUTH_TEST_PLAN.md

@@ -671,7 +671,7 @@ curl -s -X POST http://localhost:2026/api/threads/search \
 **预期：**
 - [ ] 返回的 thread 数量 ≥ 旧版创建的数量
 - [ ] 控制台日志有 `Migrated N orphaned thread(s) to admin`
-- [ ] 每个 thread 的 `metadata.user_id` 都已被设为 admin 的 ID
+- [ ] 每个 thread 的 `metadata.owner_id` 都已被设为 admin 的 ID
 
 #### TC-UPG-03: 旧 Thread 内容完整
 
@@ -683,7 +683,7 @@ curl -s http://localhost:2026/api/threads/<old-thread-id> \
 
 **预期：**
 - [ ] `metadata.title` 保留原值（如 `old-thread-1`）
-- [ ] `metadata.user_id` 已填充
+- [ ] `metadata.owner_id` 已填充
 
 #### TC-UPG-04: 新用户看不到旧 Thread
 
@@ -1478,13 +1478,28 @@ docker logs deer-flow-gateway 2>&1 | grep -E "ChannelManager|channel" | head -10
 
 **预期：** 无 auth 相关错误。渠道通过 `langgraph-sdk` 直连 LangGraph Server（`http://langgraph:2024`），不走 auth 层。
 
-#### TC-DOCKER-05: admin 密码在容器日志中可见
+#### TC-DOCKER-05: admin 密码写入 0600 凭证文件（不再走日志）
 
 ```bash
-docker logs deer-flow-gateway 2>&1 | grep "Password:"
+# 凭证文件写在挂载到宿主机的 DEER_FLOW_HOME 下
+ls -la ${DEER_FLOW_HOME:-backend/.deer-flow}/admin_initial_credentials.txt
+# 预期文件权限: -rw------- (0600)
+
+cat ${DEER_FLOW_HOME:-backend/.deer-flow}/admin_initial_credentials.txt
+# 预期内容: email + password 行
+
+# 容器日志只输出文件路径，不输出密码本身
+docker logs deer-flow-gateway 2>&1 | grep -E "Credentials written to|Admin account"
+# 预期看到: "Credentials written to: /...../admin_initial_credentials.txt (mode 0600)"
+
+# 反向验证: 日志里 NEVER 出现明文密码
+docker logs deer-flow-gateway 2>&1 | grep -iE "Password: .{15,}" && echo "FAIL: leaked" || echo "OK: not leaked"
 ```
 
-**预期：** 首次启动时输出 admin 密码，运维可通过 `docker logs` 获取。
+**预期：**
+- 凭证文件存在于 `DEER_FLOW_HOME` 下，权限 `0600`
+- 容器日志输出**路径**（不是密码本身），符合 CodeQL `py/clear-text-logging-sensitive-data` 规则
+- `grep "Password:"` 在日志中**应当无匹配**（旧行为已废弃，simplify pass 移除了日志泄露路径）
 
 #### TC-DOCKER-06: Gateway 模式 Docker 部署
 
@@ -1697,10 +1712,10 @@ curl -s -X POST $BASE/api/threads \
   -b cookies.txt \
   -H "Content-Type: application/json" \
   -H "X-CSRF-Token: $CSRF" \
-  -d '{"metadata":{"user_id":"victim-user-id"}}' | jq .metadata.user_id
+  -d '{"metadata":{"owner_id":"victim-user-id"}}' | jq .metadata.owner_id
 ```
 
-**预期：** 返回的 `metadata.user_id` 应为当前登录用户的 ID，不是请求中注入的 `victim-user-id`。服务端应覆盖客户端提供的 `user_id`。
+**预期：** 返回的 `metadata.owner_id` 应为当前登录用户的 ID，不是请求中注入的 `victim-user-id`。服务端应覆盖客户端提供的 `user_id`。
 
 #### 7.5.6 HTTP Method 探测
 

backend/docs/CONFIGURATION.md

@@ -192,8 +192,8 @@ tools:
 ```
 
 **Built-in Tools**:
-- `web_search` - Search the web (Tavily)
-- `web_fetch` - Fetch web pages (Jina AI)
+- `web_search` - Search the web (DuckDuckGo, Tavily, Exa, InfoQuest, Firecrawl)
+- `web_fetch` - Fetch web pages (Jina AI, Exa, InfoQuest, Firecrawl)
 - `ls` - List directory contents
 - `read_file` - Read file contents
 - `write_file` - Write file contents

backend/docs/README.md

@@ -15,6 +15,7 @@ This directory contains detailed documentation for the DeerFlow backend.
 
 | Document | Description |
 |----------|-------------|
+| [STREAMING.md](STREAMING.md) | Token-level streaming design: Gateway vs DeerFlowClient paths, `stream_mode` semantics, per-id dedup |
 | [FILE_UPLOAD.md](FILE_UPLOAD.md) | File upload functionality |
 | [PATH_EXAMPLES.md](PATH_EXAMPLES.md) | Path types and usage examples |
 | [summarization.md](summarization.md) | Context summarization feature |
@@ -47,6 +48,7 @@ docs/
 ├── PATH_EXAMPLES.md           # Path usage examples
 ├── summarization.md           # Summarization feature
 ├── plan_mode_usage.md         # Plan mode feature
+├── STREAMING.md               # Token-level streaming design
 ├── AUTO_TITLE_GENERATION.md   # Title generation
 ├── TITLE_GENERATION_IMPLEMENTATION.md  # Title implementation details
 └── TODO.md                    # Roadmap and issues

backend/docs/STREAMING.md

@@ -0,0 +1,351 @@
+# DeerFlow 流式输出设计
+
+本文档解释 DeerFlow 是如何把 LangGraph agent 的事件流端到端送到两类消费者（HTTP 客户端、嵌入式 Python 调用方）的：两条路径为什么**必须**并存、它们各自的契约是什么、以及设计里那些 non-obvious 的不变式。
+
+---
+
+## TL;DR
+
+- DeerFlow 有**两条并行**的流式路径：**Gateway 路径**（async / HTTP SSE / JSON 序列化）服务浏览器和 IM 渠道；**DeerFlowClient 路径**（sync / in-process / 原生 LangChain 对象）服务 Jupyter、脚本、测试。它们**无法合并**——消费者模型不同。
+- 两条路径都从 `create_agent()` 工厂出发，核心都是订阅 LangGraph 的 `stream_mode=["values", "messages", "custom"]`。`values` 是节点级 state 快照，`messages` 是 LLM token 级 delta，`custom` 是显式 `StreamWriter` 事件。**这三种模式不是详细程度的梯度，是三个独立的事件源**，要 token 流就必须显式订阅 `messages`。
+- 嵌入式 client 为每个 `stream()` 调用维护三个 `set[str]`：`seen_ids` / `streamed_ids` / `counted_usage_ids`。三者看起来相似但管理**三个独立的不变式**，不能合并。
+
+---
+
+## 为什么有两条流式路径
+
+两条路径服务的消费者模型根本不同：
+
+| 维度 | Gateway 路径 | DeerFlowClient 路径 |
+|---|---|---|
+| 入口 | FastAPI `/runs/stream` endpoint | `DeerFlowClient.stream(message)` |
+| 触发层 | `runtime/runs/worker.py::run_agent` | `packages/harness/deerflow/client.py::DeerFlowClient.stream` |
+| 执行模型 | `async def` + `agent.astream()` | sync generator + `agent.stream()` |
+| 事件传输 | `StreamBridge`（asyncio Queue）+ `sse_consumer` | 直接 `yield` |
+| 序列化 | `serialize(chunk)` → 纯 JSON dict，匹配 LangGraph Platform wire 格式 | `StreamEvent.data`，携带原生 LangChain 对象 |
+| 消费者 | 前端 `useStream` React hook、飞书/Slack/Telegram channel、LangGraph SDK 客户端 | Jupyter notebook、集成测试、内部 Python 脚本 |
+| 生命周期管理 | `RunManager`：run_id 跟踪、disconnect 语义、multitask 策略、heartbeat | 无；函数返回即结束 |
+| 断连恢复 | `Last-Event-ID` SSE 重连 | 无需要 |
+
+**两条路径的存在是 DRY 的刻意妥协**：Gateway 的全部基础设施（async + Queue + JSON + RunManager）**都是为了跨网络边界把事件送给 HTTP 消费者**。当生产者（agent）和消费者（Python 调用栈）在同一个进程时，这整套东西都是纯开销。
+
+### 为什么不能让 DeerFlowClient 复用 Gateway
+
+曾经考虑过三种复用方案，都被否决：
+
+1. **让 `client.stream()` 变成 `async def client.astream()`**  
+   breaking change。用户用不上的 `async for` / `asyncio.run()` 要硬塞进 Jupyter notebook 和同步脚本。DeerFlowClient 的一大卖点（"把 agent 当普通函数调用"）直接消失。
+
+2. **在 `client.stream()` 内部起一个独立事件循环线程，用 `StreamBridge` 在 sync/async 之间做桥接**  
+   引入线程池、队列、信号量。为了"消除重复"，把**复杂度**代替代码行数引进来。是典型的"wrong abstraction"——开销高于复用收益。
+
+3. **让 `run_agent` 自己兼容 sync mode**  
+   给 Gateway 加一条用不到的死分支，污染 worker.py 的焦点。
+
+所以两条路径的事件处理逻辑会**相似但不共享**。这是刻意设计，不是疏忽。
+
+---
+
+## LangGraph `stream_mode` 三层语义
+
+LangGraph 的 `agent.stream(stream_mode=[...])` 是**多路复用**接口：一次订阅多个 mode，每个 mode 是一个独立的事件源。三种核心 mode：
+
+```mermaid
+flowchart LR
+    classDef values fill:#B8C5D1,stroke:#5A6B7A,color:#2C3E50
+    classDef messages fill:#C9B8A8,stroke:#7A6B5A,color:#2C3E50
+    classDef custom fill:#B5C4B1,stroke:#5A7A5A,color:#2C3E50
+
+    subgraph LG["LangGraph agent graph"]
+        direction TB
+        Node1["node: LLM call"]
+        Node2["node: tool call"]
+        Node3["node: reducer"]
+    end
+
+    LG -->|"每个节点完成后"| V["values: 完整 state 快照"]
+    Node1 -->|"LLM 每产生一个 token"| M["messages: (AIMessageChunk, meta)"]
+    Node1 -->|"StreamWriter.write()"| C["custom: 任意 dict"]
+
+    class V values
+    class M messages
+    class C custom
+```
+
+| Mode | 发射时机 | Payload | 粒度 |
+|---|---|---|---|
+| `values` | 每个 graph 节点完成后 | 完整 state dict（title、messages、artifacts）| 节点级 |
+| `messages` | LLM 每次 yield 一个 chunk；tool 节点完成时 | `(AIMessageChunk \| ToolMessage, metadata_dict)` | token 级 |
+| `custom` | 用户代码显式调用 `StreamWriter.write()` | 任意 dict | 应用定义 |
+
+### 两套命名的由来
+
+同一件事在**三个协议层**有三个名字：
+
+```
+Application                    HTTP / SSE                    LangGraph Graph
+┌──────────────┐               ┌──────────────┐              ┌──────────────┐
+│ frontend     │               │ LangGraph    │              │ agent.astream│
+│ useStream    │──"messages-   │ Platform SDK │──"messages"──│ graph.astream│
+│ Feishu IM    │   tuple"──────│ HTTP wire    │              │              │
+└──────────────┘               └──────────────┘              └──────────────┘
+```
+
+- **Graph 层**（`agent.stream` / `agent.astream`）：LangGraph Python 直接 API，mode 叫 **`"messages"`**。
+- **Platform SDK 层**（`langgraph-sdk` HTTP client）：跨进程 HTTP 契约，mode 叫 **`"messages-tuple"`**。
+- **Gateway worker** 显式做翻译：`if m == "messages-tuple": lg_modes.append("messages")`（`runtime/runs/worker.py:117-121`）。
+
+**后果**：`DeerFlowClient.stream()` 直接调 `agent.stream()`（Graph 层），所以必须传 `"messages"`。`app/channels/manager.py` 通过 `langgraph-sdk` 走 HTTP SDK，所以传 `"messages-tuple"`。**这两个字符串不能互相替代**，也不能抽成"一个共享常量"——它们是不同协议层的 type alias，共享只会让某一层说不是它母语的话。
+
+---
+
+## Gateway 路径：async + HTTP SSE
+
+```mermaid
+sequenceDiagram
+    participant Client as HTTP Client
+    participant API as FastAPI<br/>thread_runs.py
+    participant Svc as services.py<br/>start_run
+    participant Worker as worker.py<br/>run_agent (async)
+    participant Bridge as StreamBridge<br/>(asyncio.Queue)
+    participant Agent as LangGraph<br/>agent.astream
+    participant SSE as sse_consumer
+
+    Client->>API: POST /runs/stream
+    API->>Svc: start_run(body)
+    Svc->>Bridge: create bridge
+    Svc->>Worker: asyncio.create_task(run_agent(...))
+    Svc-->>API: StreamingResponse(sse_consumer)
+    API-->>Client: event-stream opens
+
+    par worker (producer)
+        Worker->>Agent: astream(stream_mode=lg_modes)
+        loop 每个 chunk
+            Agent-->>Worker: (mode, chunk)
+            Worker->>Bridge: publish(run_id, event, serialize(chunk))
+        end
+        Worker->>Bridge: publish_end(run_id)
+    and sse_consumer (consumer)
+        SSE->>Bridge: subscribe(run_id)
+        loop 每个 event
+            Bridge-->>SSE: StreamEvent
+            SSE-->>Client: "event: <name>\ndata: <json>\n\n"
+        end
+    end
+```
+
+关键组件：
+
+- `runtime/runs/worker.py::run_agent` — 在 `asyncio.Task` 里跑 `agent.astream()`，把每个 chunk 通过 `serialize(chunk, mode=mode)` 转成 JSON，再 `bridge.publish()`。
+- `runtime/stream_bridge` — 抽象 Queue。`publish/subscribe` 解耦生产者和消费者，支持 `Last-Event-ID` 重连、心跳、多订阅者 fan-out。
+- `app/gateway/services.py::sse_consumer` — 从 bridge 订阅，格式化为 SSE wire 帧。
+- `runtime/serialization.py::serialize` — mode-aware 序列化；`messages` mode 下 `serialize_messages_tuple` 把 `(chunk, metadata)` 转成 `[chunk.model_dump(), metadata]`。
+
+**`StreamBridge` 的存在价值**：当生产者（`run_agent` 任务）和消费者（HTTP 连接）在不同的 asyncio task 里运行时，需要一个可以跨 task 传递事件的中介。Queue 同时还承担断连重连的 buffer 和多订阅者的 fan-out。
+
+---
+
+## DeerFlowClient 路径：sync + in-process
+
+```mermaid
+sequenceDiagram
+    participant User as Python caller
+    participant Client as DeerFlowClient.stream
+    participant Agent as LangGraph<br/>agent.stream (sync)
+
+    User->>Client: for event in client.stream("hi"):
+    Client->>Agent: stream(stream_mode=["values","messages","custom"])
+    loop 每个 chunk
+        Agent-->>Client: (mode, chunk)
+        Client->>Client: 分发 mode<br/>构建 StreamEvent
+        Client-->>User: yield StreamEvent
+    end
+    Client-->>User: yield StreamEvent(type="end")
+```
+
+对比之下，sync 路径的每个环节都是显著更少的移动部件：
+
+- 没有 `RunManager` —— 一次 `stream()` 调用对应一次生命周期，无需 run_id。
+- 没有 `StreamBridge` —— 直接 `yield`，生产和消费在同一个 Python 调用栈，不需要跨 task 中介。
+- 没有 JSON 序列化 —— `StreamEvent.data` 直接装原生 LangChain 对象（`AIMessage.content`、`usage_metadata` 的 `UsageMetadata` TypedDict）。Jupyter 用户拿到的是真正的类型，不是匿名 dict。
+- 没有 asyncio —— 调用者可以直接 `for event in ...`，不必写 `async for`。
+
+---
+
+## 消费语义：delta vs cumulative
+
+LangGraph `messages` mode 给出的是 **delta**：每个 `AIMessageChunk.content` 只包含这一次新 yield 的 token，**不是**从头的累计文本。
+
+这个语义和 LangChain 的 `fs2 Stream` 风格一致：**上游发增量，下游负责累加**。Gateway 路径里前端 `useStream` React hook 自己维护累加器；DeerFlowClient 路径里 `chat()` 方法替调用者做累加。
+
+### `DeerFlowClient.chat()` 的 O(n) 累加器
+
+```python
+chunks: dict[str, list[str]] = {}
+last_id: str = ""
+for event in self.stream(message, thread_id=thread_id, **kwargs):
+    if event.type == "messages-tuple" and event.data.get("type") == "ai":
+        msg_id = event.data.get("id") or ""
+        delta = event.data.get("content", "")
+        if delta:
+            chunks.setdefault(msg_id, []).append(delta)
+            last_id = msg_id
+return "".join(chunks.get(last_id, ()))
+```
+
+**为什么不是 `buffers[id] = buffers.get(id,"") + delta`**：CPython 的字符串 in-place concat 优化仅在 refcount=1 且 LHS 是 local name 时生效；这里字符串存在 dict 里被 reassign，优化失效，每次都是 O(n) 拷贝 → 总体 O(n²)。实测 50 KB / 5000 chunk 的回复要 100-300ms 纯拷贝开销。用 `list` + `"".join()` 是 O(n)。
+
+---
+
+## 三个 id set 为什么不能合并
+
+`DeerFlowClient.stream()` 在一次调用生命周期内维护三个 `set[str]`：
+
+```python
+seen_ids: set[str] = set()           # values 路径内部 dedup
+streamed_ids: set[str] = set()       # messages → values 跨模式 dedup
+counted_usage_ids: set[str] = set()  # usage_metadata 幂等计数
+```
+
+乍看像是"三份几乎一样的东西"，实际每个管**不同的不变式**。
+
+| Set | 负责的不变式 | 被谁填充 | 被谁查询 |
+|---|---|---|---|
+| `seen_ids` | 连续两个 `values` 快照里同一条 message 只生成一个 `messages-tuple` 事件 | values 分支每处理一条消息就加入 | values 分支处理下一条消息前检查 |
+| `streamed_ids` | 如果一条消息已经通过 `messages` 模式 token 级流过，values 快照到达时**不要**再合成一次完整 `messages-tuple` | messages 分支每发一个 AI/tool 事件就加入 | values 分支看到消息时检查 |
+| `counted_usage_ids` | 同一个 `usage_metadata` 在 messages 末尾 chunk 和 values 快照的 final AIMessage 里各带一份，**累计总量只算一次** | `_account_usage()` 每次接受 usage 就加入 | `_account_usage()` 每次调用时检查 |
+
+### 为什么不能只用一个 set
+
+关键观察：**同一个 message id 在这三个 set 里的加入时机不同**。
+
+```mermaid
+sequenceDiagram
+    participant M as messages mode
+    participant V as values mode
+    participant SS as streamed_ids
+    participant SU as counted_usage_ids
+    participant SE as seen_ids
+
+    Note over M: 第一个 AI text chunk 到达
+    M->>SS: add(msg_id)
+    Note over M: 最后一个 chunk 带 usage
+    M->>SU: add(msg_id)
+    Note over V: snapshot 到达，包含同一条 AI message
+    V->>SE: add(msg_id)
+    V->>SS: 查询 → 已存在，跳过文本合成
+    V->>SU: 查询 → 已存在，不重复计数
+```
+
+- `seen_ids` **永远在 values 快照到达时**加入，所以它是 "values 已处理" 的标记。一条只出现在 messages 流里的消息（罕见但可能），`seen_ids` 里永远没有它。
+- `streamed_ids` **在 messages 流的第一个有效事件时**加入。一条只通过 values 快照到达的非 AI 消息（HumanMessage、被 truncate 的 tool 消息），`streamed_ids` 里永远没有它。
+- `counted_usage_ids` **只在看到非空 `usage_metadata` 时**加入。一条完全没有 usage 的消息（tool message、错误消息）永远不会进去。
+
+**集合包含关系**：`counted_usage_ids ⊆ (streamed_ids ∪ seen_ids)` 大致成立，但**不是严格子集**，因为一条消息可以在 messages 模式流完 text 但**在最后那个带 usage 的 chunk 之前**就被 values snapshot 赶上——此时它已经在 `streamed_ids` 里，但还不在 `counted_usage_ids` 里。把它们合并成一个 dict-of-flags 会让这个微妙的时序依赖**从类型系统里消失**，变成注释里的一句话。三个独立的 set 把不变式显式化了：每个 set 名对应一个可以口头回答的问题。
+
+---
+
+## 端到端：一次真实对话的事件时序
+
+假设调用 `client.stream("Count from 1 to 15")`，LLM 给出 "one\ntwo\n...\nfifteen"（88 字符），tokenizer 把它拆成 ~35 个 BPE chunk。下面是事件到达序列的精简版：
+
+```mermaid
+sequenceDiagram
+    participant U as User
+    participant C as DeerFlowClient
+    participant A as LangGraph<br/>agent.stream
+
+    U->>C: stream("Count ... 15")
+    C->>A: stream(mode=["values","messages","custom"])
+
+    A-->>C: ("values", {messages: [HumanMessage]})
+    C-->>U: StreamEvent(type="values", ...)
+
+    Note over A,C: LLM 开始 yield token
+    loop 35 次，约 476ms
+        A-->>C: ("messages", (AIMessageChunk(content="ele"), meta))
+        C->>C: streamed_ids.add(ai-1)
+        C-->>U: StreamEvent(type="messages-tuple",<br/>data={type:ai, content:"ele", id:ai-1})
+    end
+
+    Note over A: LLM finish_reason=stop，最后一个 chunk 带 usage
+    A-->>C: ("messages", (AIMessageChunk(content="", usage_metadata={...}), meta))
+    C->>C: counted_usage_ids.add(ai-1)<br/>(无文本，不 yield)
+
+    A-->>C: ("values", {messages: [..., AIMessage(complete)]})
+    C->>C: ai-1 in streamed_ids → 跳过合成
+    C->>C: 捕获 usage (已在 counted_usage_ids，no-op)
+    C-->>U: StreamEvent(type="values", ...)
+
+    C-->>U: StreamEvent(type="end", data={usage:{...}})
+```
+
+关键观察：
+
+1. 用户看到 **35 个 messages-tuple 事件**，跨越约 476ms，每个事件带一个 token delta 和同一个 `id=ai-1`。
+2. 最后一个 `values` 快照里的 `AIMessage` **不会**再触发一个完整的 `messages-tuple` 事件——因为 `ai-1 in streamed_ids` 跳过了合成。
+3. `end` 事件里的 `usage` 正好等于那一份 cumulative usage，**不是它的两倍**——`counted_usage_ids` 在 messages 末尾 chunk 上已经吸收了，values 分支的重复访问是 no-op。
+4. 消费者拿到的 `content` 是**增量**："ele" 只包含 3 个字符，不是 "one\ntwo\n...ele"。想要完整文本要按 `id` 累加，`chat()` 已经帮你做了。
+
+---
+
+## 为什么这个设计容易出 bug，以及测试策略
+
+本文档的直接起因是 bytedance/deer-flow#1969：`DeerFlowClient.stream()` 原本只订阅 `["values", "custom"]`，**漏了 `"messages"`**。结果 `client.stream("hello")` 等价于一次性返回，视觉上和 `chat()` 没区别。
+
+这类 bug 有三个结构性原因：
+
+1. **多协议层命名**：`messages` / `messages-tuple` / HTTP SSE `messages` 是同一概念的三个名字。在其中一层出错不会在另外两层报错。
+2. **多消费者模型**：Gateway 和 DeerFlowClient 是两套独立实现，**没有单一的"订阅哪些 mode"的 single source of truth**。前者订阅对了不代表后者也订阅对了。
+3. **mock 测试绕开了真实路径**：老测试用 `agent.stream.return_value = iter([dict_chunk, ...])` 喂 values 形状的 dict 模拟 state 快照。这样构造的输入**永远不会进入 `messages` mode 分支**，所以即使 `stream_mode` 里少一个元素，CI 依然全绿。
+
+### 防御手段
+
+真正的防线是**显式断言 "messages" mode 被订阅 + 用真实 chunk shape mock**：
+
+```python
+# tests/test_client.py::test_messages_mode_emits_token_deltas
+agent.stream.return_value = iter([
+    ("messages", (AIMessageChunk(content="Hel", id="ai-1"), {})),
+    ("messages", (AIMessageChunk(content="lo ", id="ai-1"), {})),
+    ("messages", (AIMessageChunk(content="world!", id="ai-1"), {})),
+    ("values", {"messages": [HumanMessage(...), AIMessage(content="Hello world!", id="ai-1")]}),
+])
+# ...
+assert [e.data["content"] for e in ai_text_events] == ["Hel", "lo ", "world!"]
+assert len(ai_text_events) == 3  # values snapshot must NOT re-synthesize
+assert "messages" in agent.stream.call_args.kwargs["stream_mode"]
+```
+
+**为什么这比"抽一个共享常量"更有效**：共享常量只能保证"用它的人写对字符串"，但新增消费者的人可能根本不知道常量在哪。行为断言强制任何改动都要穿过**实际执行路径**，改回 `["values", "custom"]` 会立刻让 `assert "messages" in ...` 失败。
+
+### 活体信号：BPE 子词边界
+
+回归的最终验证是让真实 LLM 数 1-15，然后看是否能在输出里看到 tokenizer 的子词切分：
+
+```
+[5.460s] 'ele' / 'ven'      eleven 被拆成两个 token
+[5.508s] 'tw'  / 'elve'     twelve 拆两个
+[5.568s] 'th'  / 'irteen'   thirteen 拆两个
+[5.623s] 'four'/ 'teen'     fourteen 拆两个
+[5.677s] 'f'   / 'if' / 'teen'  fifteen 拆三个
+```
+
+子词切分是 tokenizer 的外部事实，**无法伪造**。能看到它就说明数据流**逐 chunk** 地穿过了整条管道，没有被任何中间层缓冲成整段。这种"活体信号"在流式系统里是比单元测试更高置信度的证据。
+
+---
+
+## 相关源码定位
+
+| 关心什么 | 看这里 |
+|---|---|
+| DeerFlowClient 嵌入式流 | `packages/harness/deerflow/client.py::DeerFlowClient.stream` |
+| `chat()` 的 delta 累加器 | `packages/harness/deerflow/client.py::DeerFlowClient.chat` |
+| Gateway async 流 | `packages/harness/deerflow/runtime/runs/worker.py::run_agent` |
+| HTTP SSE 帧输出 | `app/gateway/services.py::sse_consumer` / `format_sse` |
+| 序列化到 wire 格式 | `packages/harness/deerflow/runtime/serialization.py` |
+| LangGraph mode 命名翻译 | `packages/harness/deerflow/runtime/runs/worker.py:117-121` |
+| 飞书渠道的增量卡片更新 | `app/channels/manager.py::_handle_streaming_chat` |
+| Channels 自带的 delta/cumulative 防御性累加 | `app/channels/manager.py::_merge_stream_text` |
+| Frontend useStream 支持的 mode 集合 | `frontend/src/core/api/stream-mode.ts` |
+| 核心回归测试 | `backend/tests/test_client.py::TestStream::test_messages_mode_emits_token_deltas` |

backend/packages/harness/deerflow/agents/__init__.py

@@ -2,8 +2,14 @@ from .checkpointer import get_checkpointer, make_checkpointer, reset_checkpointe
 from .factory import create_deerflow_agent
 from .features import Next, Prev, RuntimeFeatures
 from .lead_agent import make_lead_agent
+from .lead_agent.prompt import prime_enabled_skills_cache
 from .thread_state import SandboxState, ThreadState
 
+# LangGraph imports deerflow.agents when registering the graph. Prime the
+# enabled-skills cache here so the request path can usually read a warm cache
+# without forcing synchronous filesystem work during prompt module import.
+prime_enabled_skills_cache()
+
 __all__ = [
     "create_deerflow_agent",
     "RuntimeFeatures",

backend/packages/harness/deerflow/agents/checkpointer/async_provider.py

@@ -17,6 +17,7 @@ For sync usage see :mod:`deerflow.agents.checkpointer.provider`.
 
 from __future__ import annotations
 
+import asyncio
 import contextlib
 import logging
 from collections.abc import AsyncIterator
@@ -54,7 +55,7 @@ async def _async_checkpointer(config) -> AsyncIterator[Checkpointer]:
             raise ImportError(SQLITE_INSTALL) from exc
 
         conn_str = resolve_sqlite_conn_str(config.connection_string or "store.db")
-        ensure_sqlite_parent_dir(conn_str)
+        await asyncio.to_thread(ensure_sqlite_parent_dir, conn_str)
         async with AsyncSqliteSaver.from_conn_string(conn_str) as saver:
             await saver.setup()
             yield saver
@@ -83,23 +84,76 @@ async def _async_checkpointer(config) -> AsyncIterator[Checkpointer]:
 
 
 @contextlib.asynccontextmanager
-async def make_checkpointer() -> AsyncIterator[Checkpointer]:
-    """Async context manager that yields a checkpointer for the caller's lifetime.
-    Resources are opened on enter and closed on exit — no global state::
-
-        async with make_checkpointer() as checkpointer:
-            app.state.checkpointer = checkpointer
-
-    Yields an ``InMemorySaver`` when no checkpointer is configured in *config.yaml*.
-    """
-
-    config = get_app_config()
-
-    if config.checkpointer is None:
+async def _async_checkpointer_from_database(db_config) -> AsyncIterator[Checkpointer]:
+    """Async context manager that constructs a checkpointer from unified DatabaseConfig."""
+    if db_config.backend == "memory":
         from langgraph.checkpoint.memory import InMemorySaver
 
         yield InMemorySaver()
         return
 
-    async with _async_checkpointer(config.checkpointer) as saver:
-        yield saver
+    if db_config.backend == "sqlite":
+        try:
+            from langgraph.checkpoint.sqlite.aio import AsyncSqliteSaver
+        except ImportError as exc:
+            raise ImportError(SQLITE_INSTALL) from exc
+
+        conn_str = db_config.checkpointer_sqlite_path
+        ensure_sqlite_parent_dir(conn_str)
+        async with AsyncSqliteSaver.from_conn_string(conn_str) as saver:
+            await saver.setup()
+            yield saver
+        return
+
+    if db_config.backend == "postgres":
+        try:
+            from langgraph.checkpoint.postgres.aio import AsyncPostgresSaver
+        except ImportError as exc:
+            raise ImportError(POSTGRES_INSTALL) from exc
+
+        if not db_config.postgres_url:
+            raise ValueError("database.postgres_url is required for the postgres backend")
+
+        async with AsyncPostgresSaver.from_conn_string(db_config.postgres_url) as saver:
+            await saver.setup()
+            yield saver
+        return
+
+    raise ValueError(f"Unknown database backend: {db_config.backend!r}")
+
+
+@contextlib.asynccontextmanager
+async def make_checkpointer() -> AsyncIterator[Checkpointer]:
+    """Async context manager that yields a checkpointer for the caller's lifetime.
+    Resources are opened on enter and closed on exit -- no global state::
+
+        async with make_checkpointer() as checkpointer:
+            app.state.checkpointer = checkpointer
+
+    Yields an ``InMemorySaver`` when no checkpointer is configured in *config.yaml*.
+
+    Priority:
+    1. Legacy ``checkpointer:`` config section (backward compatible)
+    2. Unified ``database:`` config section
+    3. Default InMemorySaver
+    """
+
+    config = get_app_config()
+
+    # Legacy: standalone checkpointer config takes precedence
+    if config.checkpointer is not None:
+        async with _async_checkpointer(config.checkpointer) as saver:
+            yield saver
+            return
+
+    # Unified database config
+    db_config = getattr(config, "database", None)
+    if db_config is not None and db_config.backend != "memory":
+        async with _async_checkpointer_from_database(db_config) as saver:
+            yield saver
+            return
+
+    # Default: in-memory
+    from langgraph.checkpoint.memory import InMemorySaver
+
+    yield InMemorySaver()

backend/packages/harness/deerflow/agents/lead_agent/agent.py

@@ -56,13 +56,15 @@ def _create_summarization_middleware() -> SummarizationMiddleware | None:
     # Prepare keep parameter
     keep = config.keep.to_tuple()
 
-    # Prepare model parameter
+    # Prepare model parameter.
+    # Bind "middleware:summarize" tag so RunJournal identifies these LLM calls
+    # as middleware rather than lead_agent (SummarizationMiddleware is a
+    # LangChain built-in, so we tag the model at creation time).
     if config.model_name:
         model = create_chat_model(name=config.model_name, thinking_enabled=False)
     else:
-        # Use a lightweight model for summarization to save costs
-        # Falls back to default model if not explicitly specified
         model = create_chat_model(thinking_enabled=False)
+    model = model.with_config(tags=["middleware:summarize"])
 
     # Prepare kwargs
     kwargs = {
@@ -287,14 +289,14 @@ def make_lead_agent(config: RunnableConfig):
     agent_name = cfg.get("agent_name")
 
     agent_config = load_agent_config(agent_name) if not is_bootstrap else None
-    # Custom agent model or fallback to global/default model resolution
-    agent_model_name = agent_config.model if agent_config and agent_config.model else _resolve_model_name()
+    # Custom agent model from agent config (if any), or None to let _resolve_model_name pick the default
+    agent_model_name = agent_config.model if agent_config and agent_config.model else None
 
-    # Final model name resolution with request override, then agent config, then global default
-    model_name = requested_model_name or agent_model_name
+    # Final model name resolution: request → agent config → global default, with fallback for unknown names
+    model_name = _resolve_model_name(requested_model_name or agent_model_name)
 
     app_config = get_app_config()
-    model_config = app_config.get_model_config(model_name) if model_name else None
+    model_config = app_config.get_model_config(model_name)
 
     if model_config is None:
         raise ValueError("No chat model could be resolved. Please configure at least one model in config.yaml or provide a valid 'model_name'/'model' in the request.")

backend/packages/harness/deerflow/agents/lead_agent/prompt.py

@@ -1,19 +1,191 @@
+import asyncio
 import logging
+import threading
 from datetime import datetime
+from functools import lru_cache
 
 from deerflow.config.agents_config import load_agent_soul
 from deerflow.skills import load_skills
+from deerflow.skills.types import Skill
 from deerflow.subagents import get_available_subagent_names
 
 logger = logging.getLogger(__name__)
 
+_ENABLED_SKILLS_REFRESH_WAIT_TIMEOUT_SECONDS = 5.0
+_enabled_skills_lock = threading.Lock()
+_enabled_skills_cache: list[Skill] | None = None
+_enabled_skills_refresh_active = False
+_enabled_skills_refresh_version = 0
+_enabled_skills_refresh_event = threading.Event()
+
+
+def _load_enabled_skills_sync() -> list[Skill]:
+    return list(load_skills(enabled_only=True))
+
+
+def _start_enabled_skills_refresh_thread() -> None:
+    threading.Thread(
+        target=_refresh_enabled_skills_cache_worker,
+        name="deerflow-enabled-skills-loader",
+        daemon=True,
+    ).start()
+
+
+def _refresh_enabled_skills_cache_worker() -> None:
+    global _enabled_skills_cache, _enabled_skills_refresh_active
+
+    while True:
+        with _enabled_skills_lock:
+            target_version = _enabled_skills_refresh_version
+
+        try:
+            skills = _load_enabled_skills_sync()
+        except Exception:
+            logger.exception("Failed to load enabled skills for prompt injection")
+            skills = []
+
+        with _enabled_skills_lock:
+            if _enabled_skills_refresh_version == target_version:
+                _enabled_skills_cache = skills
+                _enabled_skills_refresh_active = False
+                _enabled_skills_refresh_event.set()
+                return
+
+            # A newer invalidation happened while loading. Keep the worker alive
+            # and loop again so the cache always converges on the latest version.
+            _enabled_skills_cache = None
+
+
+def _ensure_enabled_skills_cache() -> threading.Event:
+    global _enabled_skills_refresh_active
+
+    with _enabled_skills_lock:
+        if _enabled_skills_cache is not None:
+            _enabled_skills_refresh_event.set()
+            return _enabled_skills_refresh_event
+        if _enabled_skills_refresh_active:
+            return _enabled_skills_refresh_event
+        _enabled_skills_refresh_active = True
+        _enabled_skills_refresh_event.clear()
+
+    _start_enabled_skills_refresh_thread()
+    return _enabled_skills_refresh_event
+
+
+def _invalidate_enabled_skills_cache() -> threading.Event:
+    global _enabled_skills_cache, _enabled_skills_refresh_active, _enabled_skills_refresh_version
+
+    _get_cached_skills_prompt_section.cache_clear()
+    with _enabled_skills_lock:
+        _enabled_skills_cache = None
+        _enabled_skills_refresh_version += 1
+        _enabled_skills_refresh_event.clear()
+        if _enabled_skills_refresh_active:
+            return _enabled_skills_refresh_event
+        _enabled_skills_refresh_active = True
+
+    _start_enabled_skills_refresh_thread()
+    return _enabled_skills_refresh_event
+
+
+def prime_enabled_skills_cache() -> None:
+    _ensure_enabled_skills_cache()
+
+
+def warm_enabled_skills_cache(timeout_seconds: float = _ENABLED_SKILLS_REFRESH_WAIT_TIMEOUT_SECONDS) -> bool:
+    if _ensure_enabled_skills_cache().wait(timeout=timeout_seconds):
+        return True
+
+    logger.warning("Timed out waiting %.1fs for enabled skills cache warm-up", timeout_seconds)
+    return False
+
 
 def _get_enabled_skills():
+    with _enabled_skills_lock:
+        cached = _enabled_skills_cache
+
+    if cached is not None:
+        return list(cached)
+
+    _ensure_enabled_skills_cache()
+    return []
+
+
+def _skill_mutability_label(category: str) -> str:
+    return "[custom, editable]" if category == "custom" else "[built-in]"
+
+
+def clear_skills_system_prompt_cache() -> None:
+    _invalidate_enabled_skills_cache()
+
+
+async def refresh_skills_system_prompt_cache_async() -> None:
+    await asyncio.to_thread(_invalidate_enabled_skills_cache().wait)
+
+
+def _reset_skills_system_prompt_cache_state() -> None:
+    global _enabled_skills_cache, _enabled_skills_refresh_active, _enabled_skills_refresh_version
+
+    _get_cached_skills_prompt_section.cache_clear()
+    with _enabled_skills_lock:
+        _enabled_skills_cache = None
+        _enabled_skills_refresh_active = False
+        _enabled_skills_refresh_version = 0
+        _enabled_skills_refresh_event.clear()
+
+
+def _refresh_enabled_skills_cache() -> None:
+    """Backward-compatible test helper for direct synchronous reload."""
     try:
-        return list(load_skills(enabled_only=True))
+        skills = _load_enabled_skills_sync()
     except Exception:
         logger.exception("Failed to load enabled skills for prompt injection")
-        return []
+        skills = []
+
+    with _enabled_skills_lock:
+        _enabled_skills_cache = skills
+        _enabled_skills_refresh_active = False
+        _enabled_skills_refresh_event.set()
+
+
+def _build_skill_evolution_section(skill_evolution_enabled: bool) -> str:
+    if not skill_evolution_enabled:
+        return ""
+    return """
+## Skill Self-Evolution
+After completing a task, consider creating or updating a skill when:
+- The task required 5+ tool calls to resolve
+- You overcame non-obvious errors or pitfalls
+- The user corrected your approach and the corrected version worked
+- You discovered a non-trivial, recurring workflow
+If you used a skill and encountered issues not covered by it, patch it immediately.
+Prefer patch over edit. Before creating a new skill, confirm with the user first.
+Skip simple one-off tasks.
+"""
+
+
+def _skill_mutability_label(category: str) -> str:
+    return "[custom, editable]" if category == "custom" else "[built-in]"
+
+
+def clear_skills_system_prompt_cache() -> None:
+    _get_cached_skills_prompt_section.cache_clear()
+
+
+def _build_skill_evolution_section(skill_evolution_enabled: bool) -> str:
+    if not skill_evolution_enabled:
+        return ""
+    return """
+## Skill Self-Evolution
+After completing a task, consider creating or updating a skill when:
+- The task required 5+ tool calls to resolve
+- You overcame non-obvious errors or pitfalls
+- The user corrected your approach and the corrected version worked
+- You discovered a non-trivial, recurring workflow
+If you used a skill and encountered issues not covered by it, patch it immediately.
+Prefer patch over edit. Before creating a new skill, confirm with the user first.
+Skip simple one-off tasks.
+"""
 
 
 def _build_subagent_section(max_concurrent: int) -> str:
@@ -269,6 +441,9 @@ You: "Deploying to staging..." [proceed]
 - Use `read_file` tool to read uploaded files using their paths from the list
 - For PDF, PPT, Excel, and Word files, converted Markdown versions (*.md) are available alongside originals
 - All temporary work happens in `/mnt/user-data/workspace`
+- Treat `/mnt/user-data/workspace` as your default current working directory for coding and file-editing tasks
+- When writing scripts or commands that create/read files from the workspace, prefer relative paths such as `hello.txt`, `../uploads/data.csv`, and `../outputs/report.md`
+- Avoid hardcoding `/mnt/user-data/...` inside generated scripts when a relative path from the workspace is enough
 - Final deliverables must be copied to `/mnt/user-data/outputs` and presented using `present_file` tool
 {acp_section}
 </working_directory>
@@ -388,37 +563,21 @@ def _get_memory_context(agent_name: str | None = None) -> str:
         return ""
 
 
-def get_skills_prompt_section(available_skills: set[str] | None = None) -> str:
-    """Generate the skills prompt section with available skills list.
-
-    Returns the <skill_system>...</skill_system> block listing all enabled skills,
-    suitable for injection into any agent's system prompt.
-    """
-    skills = _get_enabled_skills()
-
-    try:
-        from deerflow.config import get_app_config
-
-        config = get_app_config()
-        container_base_path = config.skills.container_path
-    except Exception:
-        container_base_path = "/mnt/skills"
-
-    if not skills:
-        return ""
-
-    if available_skills is not None:
-        skills = [skill for skill in skills if skill.name in available_skills]
-
-    # Check again after filtering
-    if not skills:
-        return ""
-
-    skill_items = "\n".join(
-        f"    <skill>\n        <name>{skill.name}</name>\n        <description>{skill.description}</description>\n        <location>{skill.get_container_file_path(container_base_path)}</location>\n    </skill>" for skill in skills
-    )
-    skills_list = f"<available_skills>\n{skill_items}\n</available_skills>"
-
+@lru_cache(maxsize=32)
+def _get_cached_skills_prompt_section(
+    skill_signature: tuple[tuple[str, str, str, str], ...],
+    available_skills_key: tuple[str, ...] | None,
+    container_base_path: str,
+    skill_evolution_section: str,
+) -> str:
+    filtered = [(name, description, category, location) for name, description, category, location in skill_signature if available_skills_key is None or name in available_skills_key]
+    skills_list = ""
+    if filtered:
+        skill_items = "\n".join(
+            f"    <skill>\n        <name>{name}</name>\n        <description>{description} {_skill_mutability_label(category)}</description>\n        <location>{location}</location>\n    </skill>"
+            for name, description, category, location in filtered
+        )
+        skills_list = f"<available_skills>\n{skill_items}\n</available_skills>"
     return f"""<skill_system>
 You have access to skills that provide optimized workflows for specific tasks. Each skill contains best practices, frameworks, and references to additional resources.
 
@@ -430,12 +589,40 @@ You have access to skills that provide optimized workflows for specific tasks. E
 5. Follow the skill's instructions precisely
 
 **Skills are located at:** {container_base_path}
-
+{skill_evolution_section}
 {skills_list}
 
 </skill_system>"""
 
 
+def get_skills_prompt_section(available_skills: set[str] | None = None) -> str:
+    """Generate the skills prompt section with available skills list."""
+    skills = _get_enabled_skills()
+
+    try:
+        from deerflow.config import get_app_config
+
+        config = get_app_config()
+        container_base_path = config.skills.container_path
+        skill_evolution_enabled = config.skill_evolution.enabled
+    except Exception:
+        container_base_path = "/mnt/skills"
+        skill_evolution_enabled = False
+
+    if not skills and not skill_evolution_enabled:
+        return ""
+
+    if available_skills is not None and not any(skill.name in available_skills for skill in skills):
+        return ""
+
+    skill_signature = tuple((skill.name, skill.description, skill.category, skill.get_container_file_path(container_base_path)) for skill in skills)
+    available_key = tuple(sorted(available_skills)) if available_skills is not None else None
+    if not skill_signature and available_key is not None:
+        return ""
+    skill_evolution_section = _build_skill_evolution_section(skill_evolution_enabled)
+    return _get_cached_skills_prompt_section(skill_signature, available_key, container_base_path, skill_evolution_section)
+
+
 def get_agent_soul(agent_name: str | None) -> str:
     # Append SOUL.md (agent personality) if present
     soul = load_agent_soul(agent_name)

backend/packages/harness/deerflow/agents/memory/queue.py

@@ -4,7 +4,7 @@ import logging
 import threading
 import time
 from dataclasses import dataclass, field
-from datetime import datetime
+from datetime import UTC, datetime
 from typing import Any
 
 from deerflow.config.memory_config import get_memory_config
@@ -18,7 +18,7 @@ class ConversationContext:
 
     thread_id: str
     messages: list[Any]
-    timestamp: datetime = field(default_factory=datetime.utcnow)
+    timestamp: datetime = field(default_factory=lambda: datetime.now(UTC))
     agent_name: str | None = None
     correction_detected: bool = False
     reinforcement_detected: bool = False

backend/packages/harness/deerflow/agents/memory/storage.py

@@ -4,7 +4,7 @@ import abc
 import json
 import logging
 import threading
-from datetime import datetime
+from datetime import UTC, datetime
 from pathlib import Path
 from typing import Any
 
@@ -15,11 +15,16 @@ from deerflow.config.paths import get_paths
 logger = logging.getLogger(__name__)
 
 
+def utc_now_iso_z() -> str:
+    """Current UTC time as ISO-8601 with ``Z`` suffix (matches prior naive-UTC output)."""
+    return datetime.now(UTC).isoformat().removesuffix("+00:00") + "Z"
+
+
 def create_empty_memory() -> dict[str, Any]:
     """Create an empty memory structure."""
     return {
         "version": "1.0",
-        "lastUpdated": datetime.utcnow().isoformat() + "Z",
+        "lastUpdated": utc_now_iso_z(),
         "user": {
             "workContext": {"summary": "", "updatedAt": ""},
             "personalContext": {"summary": "", "updatedAt": ""},
@@ -137,7 +142,7 @@ class FileMemoryStorage(MemoryStorage):
 
         try:
             file_path.parent.mkdir(parents=True, exist_ok=True)
-            memory_data["lastUpdated"] = datetime.utcnow().isoformat() + "Z"
+            memory_data["lastUpdated"] = utc_now_iso_z()
 
             temp_path = file_path.with_suffix(".tmp")
             with open(temp_path, "w", encoding="utf-8") as f:

backend/packages/harness/deerflow/agents/memory/updater.py

@@ -5,14 +5,17 @@ import logging
 import math
 import re
 import uuid
-from datetime import datetime
 from typing import Any
 
 from deerflow.agents.memory.prompt import (
     MEMORY_UPDATE_PROMPT,
     format_conversation_for_update,
 )
-from deerflow.agents.memory.storage import create_empty_memory, get_memory_storage
+from deerflow.agents.memory.storage import (
+    create_empty_memory,
+    get_memory_storage,
+    utc_now_iso_z,
+)
 from deerflow.config.memory_config import get_memory_config
 from deerflow.models import create_chat_model
 
@@ -86,7 +89,7 @@ def create_memory_fact(
 
     normalized_category = category.strip() or "context"
     validated_confidence = _validate_confidence(confidence)
-    now = datetime.utcnow().isoformat() + "Z"
+    now = utc_now_iso_z()
     memory_data = get_memory_data(agent_name)
     updated_memory = dict(memory_data)
     facts = list(memory_data.get("facts", []))
@@ -376,7 +379,7 @@ class MemoryUpdater:
             Updated memory data.
         """
         config = get_memory_config()
-        now = datetime.utcnow().isoformat() + "Z"
+        now = utc_now_iso_z()
 
         # Update user sections
         user_updates = update_data.get("user", {})

backend/packages/harness/deerflow/agents/middlewares/clarification_middleware.py

@@ -1,5 +1,6 @@
 """Middleware for intercepting clarification requests and presenting them to the user."""
 
+import json
 import logging
 from collections.abc import Callable
 from typing import override
@@ -60,6 +61,20 @@ class ClarificationMiddleware(AgentMiddleware[ClarificationMiddlewareState]):
         context = args.get("context")
         options = args.get("options", [])
 
+        # Some models (e.g. Qwen3-Max) serialize array parameters as JSON strings
+        # instead of native arrays. Deserialize and normalize so `options`
+        # is always a list for the rendering logic below.
+        if isinstance(options, str):
+            try:
+                options = json.loads(options)
+            except (json.JSONDecodeError, TypeError):
+                options = [options]
+
+        if options is None:
+            options = []
+        elif not isinstance(options, list):
+            options = [options]
+
         # Type-specific icons
         type_icons = {
             "missing_info": "❓",

backend/packages/harness/deerflow/agents/middlewares/loop_detection_middleware.py

@@ -33,30 +33,92 @@ _DEFAULT_WINDOW_SIZE = 20  # track last N tool calls
 _DEFAULT_MAX_TRACKED_THREADS = 100  # LRU eviction limit
 
 
+def _normalize_tool_call_args(raw_args: object) -> tuple[dict, str | None]:
+    """Normalize tool call args to a dict plus an optional fallback key.
+
+    Some providers serialize ``args`` as a JSON string instead of a dict.
+    We defensively parse those cases so loop detection does not crash while
+    still preserving a stable fallback key for non-dict payloads.
+    """
+    if isinstance(raw_args, dict):
+        return raw_args, None
+
+    if isinstance(raw_args, str):
+        try:
+            parsed = json.loads(raw_args)
+        except (TypeError, ValueError, json.JSONDecodeError):
+            return {}, raw_args
+
+        if isinstance(parsed, dict):
+            return parsed, None
+        return {}, json.dumps(parsed, sort_keys=True, default=str)
+
+    if raw_args is None:
+        return {}, None
+
+    return {}, json.dumps(raw_args, sort_keys=True, default=str)
+
+
+def _stable_tool_key(name: str, args: dict, fallback_key: str | None) -> str:
+    """Derive a stable key from salient args without overfitting to noise."""
+    if name == "read_file" and fallback_key is None:
+        path = args.get("path") or ""
+        start_line = args.get("start_line")
+        end_line = args.get("end_line")
+
+        bucket_size = 200
+        try:
+            start_line = int(start_line) if start_line is not None else 1
+        except (TypeError, ValueError):
+            start_line = 1
+        try:
+            end_line = int(end_line) if end_line is not None else start_line
+        except (TypeError, ValueError):
+            end_line = start_line
+
+        start_line, end_line = sorted((start_line, end_line))
+        bucket_start = max(start_line, 1)
+        bucket_end = max(end_line, 1)
+        bucket_start = (bucket_start - 1) // bucket_size
+        bucket_end = (bucket_end - 1) // bucket_size
+        return f"{path}:{bucket_start}-{bucket_end}"
+
+    # write_file / str_replace are content-sensitive: same path may be updated
+    # with different payloads during iteration. Using only salient fields (path)
+    # can collapse distinct calls, so we hash full args to reduce false positives.
+    if name in {"write_file", "str_replace"}:
+        if fallback_key is not None:
+            return fallback_key
+        return json.dumps(args, sort_keys=True, default=str)
+
+    salient_fields = ("path", "url", "query", "command", "pattern", "glob", "cmd")
+    stable_args = {field: args[field] for field in salient_fields if args.get(field) is not None}
+    if stable_args:
+        return json.dumps(stable_args, sort_keys=True, default=str)
+
+    if fallback_key is not None:
+        return fallback_key
+
+    return json.dumps(args, sort_keys=True, default=str)
+
+
 def _hash_tool_calls(tool_calls: list[dict]) -> str:
-    """Deterministic hash of a set of tool calls (name + args).
+    """Deterministic hash of a set of tool calls (name + stable key).
 
     This is intended to be order-independent: the same multiset of tool calls
     should always produce the same hash, regardless of their input order.
     """
-    # First normalize each tool call to a minimal (name, args) structure.
-    normalized: list[dict] = []
+    # Normalize each tool call to a stable (name, key) structure.
+    normalized: list[str] = []
     for tc in tool_calls:
-        normalized.append(
-            {
-                "name": tc.get("name", ""),
-                "args": tc.get("args", {}),
-            }
-        )
+        name = tc.get("name", "")
+        args, fallback_key = _normalize_tool_call_args(tc.get("args", {}))
+        key = _stable_tool_key(name, args, fallback_key)
 
-    # Sort by both name and a deterministic serialization of args so that
-    # permutations of the same multiset of calls yield the same ordering.
-    normalized.sort(
-        key=lambda tc: (
-            tc["name"],
-            json.dumps(tc["args"], sort_keys=True, default=str),
-        )
-    )
+        normalized.append(f"{name}:{key}")
+
+    # Sort so permutations of the same multiset of calls yield the same ordering.
+    normalized.sort()
     blob = json.dumps(normalized, sort_keys=True, default=str)
     return hashlib.md5(blob.encode()).hexdigest()[:12]
 

backend/packages/harness/deerflow/agents/middlewares/sandbox_audit_middleware.py

@@ -23,25 +23,119 @@ logger = logging.getLogger(__name__)
 
 # Each pattern is compiled once at import time.
 _HIGH_RISK_PATTERNS: list[re.Pattern[str]] = [
-    re.compile(r"rm\s+-[^\s]*r[^\s]*\s+(/\*?|~/?\*?|/home\b|/root\b)\s*$"),  # rm -rf / /* ~ /home /root
-    re.compile(r"(curl|wget).+\|\s*(ba)?sh"),  # curl|sh, wget|sh
+    # --- original rules (retained) ---
+    re.compile(r"rm\s+-[^\s]*r[^\s]*\s+(/\*?|~/?\*?|/home\b|/root\b)\s*$"),
     re.compile(r"dd\s+if="),
     re.compile(r"mkfs"),
     re.compile(r"cat\s+/etc/shadow"),
-    re.compile(r">\s*/etc/"),  # overwrite /etc/ files
+    re.compile(r">+\s*/etc/"),
+    # --- pipe to sh/bash (generalised, replaces old curl|sh rule) ---
+    re.compile(r"\|\s*(ba)?sh\b"),
+    # --- command substitution (targeted – only dangerous executables) ---
+    re.compile(r"[`$]\(?\s*(curl|wget|bash|sh|python|ruby|perl|base64)"),
+    # --- base64 decode piped to execution ---
+    re.compile(r"base64\s+.*-d.*\|"),
+    # --- overwrite system binaries ---
+    re.compile(r">+\s*(/usr/bin/|/bin/|/sbin/)"),
+    # --- overwrite shell startup files ---
+    re.compile(r">+\s*~/?\.(bashrc|profile|zshrc|bash_profile)"),
+    # --- process environment leakage ---
+    re.compile(r"/proc/[^/]+/environ"),
+    # --- dynamic linker hijack (one-step escalation) ---
+    re.compile(r"\b(LD_PRELOAD|LD_LIBRARY_PATH)\s*="),
+    # --- bash built-in networking (bypasses tool allowlists) ---
+    re.compile(r"/dev/tcp/"),
+    # --- fork bomb ---
+    re.compile(r"\S+\(\)\s*\{[^}]*\|\s*\S+\s*&"),  # :(){ :|:& };:
+    re.compile(r"while\s+true.*&\s*done"),  # while true; do bash & done
 ]
 
 _MEDIUM_RISK_PATTERNS: list[re.Pattern[str]] = [
-    re.compile(r"chmod\s+777"),  # overly permissive, but reversible
-    re.compile(r"pip\s+install"),
-    re.compile(r"pip3\s+install"),
+    re.compile(r"chmod\s+777"),
+    re.compile(r"pip3?\s+install"),
     re.compile(r"apt(-get)?\s+install"),
+    # sudo/su: no-op under Docker root; warn so LLM is aware
+    re.compile(r"\b(sudo|su)\b"),
+    # PATH modification: long attack chain, warn rather than block
+    re.compile(r"\bPATH\s*="),
 ]
 
 
-def _classify_command(command: str) -> str:
-    """Return 'block', 'warn', or 'pass'."""
-    # Normalize for matching (collapse whitespace)
+def _split_compound_command(command: str) -> list[str]:
+    """Split a compound command into sub-commands (quote-aware).
+
+    Scans the raw command string so unquoted shell control operators are
+    recognised even when they are not surrounded by whitespace
+    (e.g. ``safe;rm -rf /`` or ``rm -rf /&&echo ok``). Operators inside
+    quotes are ignored. If the command ends with an unclosed quote or a
+    dangling escape, return the whole command unchanged (fail-closed —
+    safer to classify the unsplit string than silently drop parts).
+    """
+    parts: list[str] = []
+    current: list[str] = []
+    in_single_quote = False
+    in_double_quote = False
+    escaping = False
+    index = 0
+
+    while index < len(command):
+        char = command[index]
+
+        if escaping:
+            current.append(char)
+            escaping = False
+            index += 1
+            continue
+
+        if char == "\\" and not in_single_quote:
+            current.append(char)
+            escaping = True
+            index += 1
+            continue
+
+        if char == "'" and not in_double_quote:
+            in_single_quote = not in_single_quote
+            current.append(char)
+            index += 1
+            continue
+
+        if char == '"' and not in_single_quote:
+            in_double_quote = not in_double_quote
+            current.append(char)
+            index += 1
+            continue
+
+        if not in_single_quote and not in_double_quote:
+            if command.startswith("&&", index) or command.startswith("||", index):
+                part = "".join(current).strip()
+                if part:
+                    parts.append(part)
+                current = []
+                index += 2
+                continue
+            if char == ";":
+                part = "".join(current).strip()
+                if part:
+                    parts.append(part)
+                current = []
+                index += 1
+                continue
+
+        current.append(char)
+        index += 1
+
+    # Unclosed quote or dangling escape → fail-closed, return whole command
+    if in_single_quote or in_double_quote or escaping:
+        return [command]
+
+    part = "".join(current).strip()
+    if part:
+        parts.append(part)
+    return parts if parts else [command]
+
+
+def _classify_single_command(command: str) -> str:
+    """Classify a single (non-compound) command. Return 'block', 'warn', or 'pass'."""
     normalized = " ".join(command.split())
 
     for pattern in _HIGH_RISK_PATTERNS:
@@ -66,6 +160,35 @@ def _classify_command(command: str) -> str:
     return "pass"
 
 
+def _classify_command(command: str) -> str:
+    """Return 'block', 'warn', or 'pass'.
+
+    Strategy:
+    1. First scan the *whole* raw command against high-risk patterns. This
+       catches structural attacks like ``while true; do bash & done`` or
+       ``:(){ :|:& };:`` that span multiple shell statements — splitting them
+       on ``;`` would destroy the pattern context.
+    2. Then split compound commands (e.g. ``cmd1 && cmd2 ; cmd3``) and
+       classify each sub-command independently. The most severe verdict wins.
+    """
+    # Pass 1: whole-command high-risk scan (catches multi-statement patterns)
+    normalized = " ".join(command.split())
+    for pattern in _HIGH_RISK_PATTERNS:
+        if pattern.search(normalized):
+            return "block"
+
+    # Pass 2: per-sub-command classification
+    sub_commands = _split_compound_command(command)
+    worst = "pass"
+    for sub in sub_commands:
+        verdict = _classify_single_command(sub)
+        if verdict == "block":
+            return "block"  # short-circuit: can't get worse
+        if verdict == "warn":
+            worst = "warn"
+    return worst
+
+
 # ---------------------------------------------------------------------------
 # Middleware
 # ---------------------------------------------------------------------------
@@ -105,11 +228,16 @@ class SandboxAuditMiddleware(AgentMiddleware[ThreadState]):
             thread_id = cfg.get("configurable", {}).get("thread_id")
         return thread_id
 
-    def _write_audit(self, thread_id: str | None, command: str, verdict: str) -> None:
+    _AUDIT_COMMAND_LIMIT = 200
+
+    def _write_audit(self, thread_id: str | None, command: str, verdict: str, *, truncate: bool = False) -> None:
+        audited_command = command
+        if truncate and len(command) > self._AUDIT_COMMAND_LIMIT:
+            audited_command = f"{command[: self._AUDIT_COMMAND_LIMIT]}... ({len(command)} chars)"
         record = {
             "timestamp": datetime.now(UTC).isoformat(),
             "thread_id": thread_id or "unknown",
-            "command": command,
+            "command": audited_command,
             "verdict": verdict,
         }
         logger.info("[SandboxAudit] %s", json.dumps(record, ensure_ascii=False))
@@ -139,23 +267,52 @@ class SandboxAuditMiddleware(AgentMiddleware[ThreadState]):
             status=result.status,
         )
 
+    # ------------------------------------------------------------------
+    # Input sanitisation
+    # ------------------------------------------------------------------
+
+    # Normal bash commands rarely exceed a few hundred characters.  10 000 is
+    # well above any legitimate use case yet a tiny fraction of Linux ARG_MAX.
+    # Anything longer is almost certainly a payload injection or base64-encoded
+    # attack string.
+    _MAX_COMMAND_LENGTH = 10_000
+
+    def _validate_input(self, command: str) -> str | None:
+        """Return ``None`` if *command* is acceptable, else a rejection reason."""
+        if not command.strip():
+            return "empty command"
+        if len(command) > self._MAX_COMMAND_LENGTH:
+            return "command too long"
+        if "\x00" in command:
+            return "null byte detected"
+        return None
+
     # ------------------------------------------------------------------
     # Core logic (shared between sync and async paths)
     # ------------------------------------------------------------------
 
-    def _pre_process(self, request: ToolCallRequest) -> tuple[str, str | None, str]:
+    def _pre_process(self, request: ToolCallRequest) -> tuple[str, str | None, str, str | None]:
         """
-        Returns (command, thread_id, verdict).
+        Returns (command, thread_id, verdict, reject_reason).
         verdict is 'block', 'warn', or 'pass'.
+        reject_reason is non-None only for input sanitisation rejections.
         """
         args = request.tool_call.get("args", {})
-        command: str = args.get("command", "")
+        raw_command = args.get("command")
+        command = raw_command if isinstance(raw_command, str) else ""
         thread_id = self._get_thread_id(request)
 
-        # ① classify command
+        # ① input sanitisation — reject malformed input before regex analysis
+        reject_reason = self._validate_input(command)
+        if reject_reason:
+            self._write_audit(thread_id, command, "block", truncate=True)
+            logger.warning("[SandboxAudit] INVALID INPUT thread=%s reason=%s", thread_id, reject_reason)
+            return command, thread_id, "block", reject_reason
+
+        # ② classify command
         verdict = _classify_command(command)
 
-        # ② audit log
+        # ③ audit log
         self._write_audit(thread_id, command, verdict)
 
         if verdict == "block":
@@ -163,7 +320,7 @@ class SandboxAuditMiddleware(AgentMiddleware[ThreadState]):
         elif verdict == "warn":
             logger.warning("[SandboxAudit] WARN (medium-risk) thread=%s cmd=%r", thread_id, command)
 
-        return command, thread_id, verdict
+        return command, thread_id, verdict, None
 
     # ------------------------------------------------------------------
     # wrap_tool_call hooks
@@ -178,9 +335,10 @@ class SandboxAuditMiddleware(AgentMiddleware[ThreadState]):
         if request.tool_call.get("name") != "bash":
             return handler(request)
 
-        command, _, verdict = self._pre_process(request)
+        command, _, verdict, reject_reason = self._pre_process(request)
         if verdict == "block":
-            return self._build_block_message(request, "security violation detected")
+            reason = reject_reason or "security violation detected"
+            return self._build_block_message(request, reason)
         result = handler(request)
         if verdict == "warn":
             result = self._append_warn_to_result(result, command)
@@ -195,9 +353,10 @@ class SandboxAuditMiddleware(AgentMiddleware[ThreadState]):
         if request.tool_call.get("name") != "bash":
             return await handler(request)
 
-        command, _, verdict = self._pre_process(request)
+        command, _, verdict, reject_reason = self._pre_process(request)
         if verdict == "block":
-            return self._build_block_message(request, "security violation detected")
+            reason = reject_reason or "security violation detected"
+            return self._build_block_message(request, reason)
         result = await handler(request)
         if verdict == "warn":
             result = self._append_warn_to_result(result, command)

backend/packages/harness/deerflow/agents/middlewares/title_middleware.py

@@ -1,10 +1,11 @@
 """Middleware for automatic thread title generation."""
 
 import logging
-from typing import NotRequired, override
+from typing import Any, NotRequired, override
 
 from langchain.agents import AgentState
 from langchain.agents.middleware import AgentMiddleware
+from langgraph.config import get_config
 from langgraph.runtime import Runtime
 
 from deerflow.config.title_config import get_title_config
@@ -100,6 +101,20 @@ class TitleMiddleware(AgentMiddleware[TitleMiddlewareState]):
             return user_msg[:fallback_chars].rstrip() + "..."
         return user_msg if user_msg else "New Conversation"
 
+    def _get_runnable_config(self) -> dict[str, Any]:
+        """Inherit the parent RunnableConfig and add middleware tag.
+
+        This ensures RunJournal identifies LLM calls from this middleware
+        as ``middleware:title`` instead of ``lead_agent``.
+        """
+        try:
+            parent = get_config()
+        except Exception:
+            parent = {}
+        config = {**parent}
+        config["tags"] = [*(config.get("tags") or []), "middleware:title"]
+        return config
+
     def _generate_title_result(self, state: TitleMiddlewareState) -> dict | None:
         """Generate a local fallback title without blocking on an LLM call."""
         if not self._should_generate_title(state):
@@ -121,7 +136,7 @@ class TitleMiddleware(AgentMiddleware[TitleMiddlewareState]):
                 model = create_chat_model(name=config.model_name, thinking_enabled=False)
             else:
                 model = create_chat_model(thinking_enabled=False)
-            response = await model.ainvoke(prompt)
+            response = await model.ainvoke(prompt, config=self._get_runnable_config())
             title = self._parse_title(response.content)
             if title:
                 return {"title": title}

backend/packages/harness/deerflow/agents/middlewares/view_image_middleware.py

@@ -1,22 +1,19 @@
 """Middleware for injecting image details into conversation before LLM call."""
 
 import logging
-from typing import NotRequired, override
+from typing import override
 
-from langchain.agents import AgentState
 from langchain.agents.middleware import AgentMiddleware
 from langchain_core.messages import AIMessage, HumanMessage, ToolMessage
 from langgraph.runtime import Runtime
 
-from deerflow.agents.thread_state import ViewedImageData
+from deerflow.agents.thread_state import ThreadState
 
 logger = logging.getLogger(__name__)
 
 
-class ViewImageMiddlewareState(AgentState):
-    """Compatible with the `ThreadState` schema."""
-
-    viewed_images: NotRequired[dict[str, ViewedImageData] | None]
+class ViewImageMiddlewareState(ThreadState):
+    """Reuse the thread state so reducer-backed keys keep their annotations."""
 
 
 class ViewImageMiddleware(AgentMiddleware[ViewImageMiddlewareState]):

backend/packages/harness/deerflow/client.py

@@ -25,7 +25,7 @@ import uuid
 from collections.abc import Generator, Sequence
 from dataclasses import dataclass, field
 from pathlib import Path
-from typing import Any
+from typing import Any, Literal
 
 from langchain.agents import create_agent
 from langchain.agents.middleware import AgentMiddleware
@@ -55,6 +55,9 @@ from deerflow.uploads.manager import (
 logger = logging.getLogger(__name__)
 
 
+StreamEventType = Literal["values", "messages-tuple", "custom", "end"]
+
+
 @dataclass
 class StreamEvent:
     """A single event from the streaming agent response.
@@ -69,7 +72,7 @@ class StreamEvent:
         data: Event payload. Contents vary by type.
     """
 
-    type: str
+    type: StreamEventType
     data: dict[str, Any] = field(default_factory=dict)
 
 
@@ -254,13 +257,53 @@ class DeerFlowClient:
 
         return get_available_tools(model_name=model_name, subagent_enabled=subagent_enabled)
 
+    @staticmethod
+    def _serialize_tool_calls(tool_calls) -> list[dict]:
+        """Reshape LangChain tool_calls into the wire format used in events."""
+        return [{"name": tc["name"], "args": tc["args"], "id": tc.get("id")} for tc in tool_calls]
+
+    @staticmethod
+    def _ai_text_event(msg_id: str | None, text: str, usage: dict | None) -> "StreamEvent":
+        """Build a ``messages-tuple`` AI text event, attaching usage when present."""
+        data: dict[str, Any] = {"type": "ai", "content": text, "id": msg_id}
+        if usage:
+            data["usage_metadata"] = usage
+        return StreamEvent(type="messages-tuple", data=data)
+
+    @staticmethod
+    def _ai_tool_calls_event(msg_id: str | None, tool_calls) -> "StreamEvent":
+        """Build a ``messages-tuple`` AI tool-calls event."""
+        return StreamEvent(
+            type="messages-tuple",
+            data={
+                "type": "ai",
+                "content": "",
+                "id": msg_id,
+                "tool_calls": DeerFlowClient._serialize_tool_calls(tool_calls),
+            },
+        )
+
+    @staticmethod
+    def _tool_message_event(msg: ToolMessage) -> "StreamEvent":
+        """Build a ``messages-tuple`` tool-result event from a ToolMessage."""
+        return StreamEvent(
+            type="messages-tuple",
+            data={
+                "type": "tool",
+                "content": DeerFlowClient._extract_text(msg.content),
+                "name": msg.name,
+                "tool_call_id": msg.tool_call_id,
+                "id": msg.id,
+            },
+        )
+
     @staticmethod
     def _serialize_message(msg) -> dict:
         """Serialize a LangChain message to a plain dict for values events."""
         if isinstance(msg, AIMessage):
             d: dict[str, Any] = {"type": "ai", "content": msg.content, "id": getattr(msg, "id", None)}
             if msg.tool_calls:
-                d["tool_calls"] = [{"name": tc["name"], "args": tc["args"], "id": tc.get("id")} for tc in msg.tool_calls]
+                d["tool_calls"] = DeerFlowClient._serialize_tool_calls(msg.tool_calls)
             if getattr(msg, "usage_metadata", None):
                 d["usage_metadata"] = msg.usage_metadata
             return d
@@ -315,6 +358,108 @@ class DeerFlowClient:
             return "\n".join(pieces) if pieces else ""
         return str(content)
 
+    # ------------------------------------------------------------------
+    # Public API — threads
+    # ------------------------------------------------------------------
+
+    def list_threads(self, limit: int = 10) -> dict:
+        """List the recent N threads.
+
+        Args:
+            limit: Maximum number of threads to return. Default is 10.
+
+        Returns:
+            Dict with "thread_list" key containing list of thread info dicts,
+            sorted by thread creation time descending.
+        """
+        checkpointer = self._checkpointer
+        if checkpointer is None:
+            from deerflow.agents.checkpointer.provider import get_checkpointer
+
+            checkpointer = get_checkpointer()
+
+        thread_info_map = {}
+
+        for cp in checkpointer.list(config=None, limit=limit):
+            cfg = cp.config.get("configurable", {})
+            thread_id = cfg.get("thread_id")
+            if not thread_id:
+                continue
+
+            ts = cp.checkpoint.get("ts")
+            checkpoint_id = cfg.get("checkpoint_id")
+
+            if thread_id not in thread_info_map:
+                channel_values = cp.checkpoint.get("channel_values", {})
+                thread_info_map[thread_id] = {
+                    "thread_id": thread_id,
+                    "created_at": ts,
+                    "updated_at": ts,
+                    "latest_checkpoint_id": checkpoint_id,
+                    "title": channel_values.get("title"),
+                }
+            else:
+                # Explicitly compare timestamps to ensure accuracy when iterating over unordered namespaces.
+                # Treat None as "missing" and only compare when existing values are non-None.
+                if ts is not None:
+                    current_created = thread_info_map[thread_id]["created_at"]
+                    if current_created is None or ts < current_created:
+                        thread_info_map[thread_id]["created_at"] = ts
+
+                    current_updated = thread_info_map[thread_id]["updated_at"]
+                    if current_updated is None or ts > current_updated:
+                        thread_info_map[thread_id]["updated_at"] = ts
+                        thread_info_map[thread_id]["latest_checkpoint_id"] = checkpoint_id
+                        channel_values = cp.checkpoint.get("channel_values", {})
+                        thread_info_map[thread_id]["title"] = channel_values.get("title")
+
+        threads = list(thread_info_map.values())
+        threads.sort(key=lambda x: x.get("created_at") or "", reverse=True)
+
+        return {"thread_list": threads[:limit]}
+
+    def get_thread(self, thread_id: str) -> dict:
+        """Get the complete thread record, including all node execution records.
+
+        Args:
+            thread_id: Thread ID.
+
+        Returns:
+            Dict containing the thread's full checkpoint history.
+        """
+        checkpointer = self._checkpointer
+        if checkpointer is None:
+            from deerflow.agents.checkpointer.provider import get_checkpointer
+
+            checkpointer = get_checkpointer()
+
+        config = {"configurable": {"thread_id": thread_id}}
+        checkpoints = []
+
+        for cp in checkpointer.list(config):
+            channel_values = dict(cp.checkpoint.get("channel_values", {}))
+            if "messages" in channel_values:
+                channel_values["messages"] = [self._serialize_message(m) if hasattr(m, "content") else m for m in channel_values["messages"]]
+
+            cfg = cp.config.get("configurable", {})
+            parent_cfg = cp.parent_config.get("configurable", {}) if cp.parent_config else {}
+
+            checkpoints.append(
+                {
+                    "checkpoint_id": cfg.get("checkpoint_id"),
+                    "parent_checkpoint_id": parent_cfg.get("checkpoint_id"),
+                    "ts": cp.checkpoint.get("ts"),
+                    "metadata": cp.metadata,
+                    "values": channel_values,
+                    "pending_writes": [{"task_id": w[0], "channel": w[1], "value": w[2]} for w in getattr(cp, "pending_writes", [])],
+                }
+            )
+
+        # Sort globally by timestamp to prevent partial ordering issues caused by different namespaces (e.g., subgraphs)
+        checkpoints.sort(key=lambda x: x["ts"] if x["ts"] else "")
+
+        return {"thread_id": thread_id, "checkpoints": checkpoints}
+
     # ------------------------------------------------------------------
     # Public API — conversation
     # ------------------------------------------------------------------
@@ -336,6 +481,53 @@ class DeerFlowClient:
         consumers can switch between HTTP streaming and embedded mode
         without changing their event-handling logic.
 
+        Token-level streaming
+        ~~~~~~~~~~~~~~~~~~~~~
+        This method subscribes to LangGraph's ``messages`` stream mode, so
+        ``messages-tuple`` events for AI text are emitted as **deltas** as
+        the model generates tokens, not as one cumulative dump at node
+        completion.  Each delta carries a stable ``id`` — consumers that
+        want the full text must accumulate ``content`` per ``id``.
+        ``chat()`` already does this for you.
+
+        Tool calls and tool results are still emitted once per logical
+        message.  ``values`` events continue to carry full state snapshots
+        after each graph node finishes; AI text already delivered via the
+        ``messages`` stream is **not** re-synthesized from the snapshot to
+        avoid duplicate deliveries.
+
+        Why not reuse Gateway's ``run_agent``?
+        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+        Gateway (``runtime/runs/worker.py``) has a complete streaming
+        pipeline: ``run_agent`` → ``StreamBridge`` → ``sse_consumer``.  It
+        looks like this client duplicates that work, but the two paths
+        serve different audiences and **cannot** share execution:
+
+        * ``run_agent`` is ``async def`` and uses ``agent.astream()``;
+          this method is a sync generator using ``agent.stream()`` so
+          callers can write ``for event in client.stream(...)`` without
+          touching asyncio.  Bridging the two would require spinning up
+          an event loop + thread per call.
+        * Gateway events are JSON-serialized by ``serialize()`` for SSE
+          wire transmission.  This client yields in-process stream event
+          payloads directly as Python data structures (``StreamEvent``
+          with ``data`` as a plain ``dict``), without the extra
+          JSON/SSE serialization layer used for HTTP delivery.
+        * ``StreamBridge`` is an asyncio-queue decoupling producers from
+          consumers across an HTTP boundary (``Last-Event-ID`` replay,
+          heartbeats, multi-subscriber fan-out).  A single in-process
+          caller with a direct iterator needs none of that.
+
+        So ``DeerFlowClient.stream()`` is a parallel, sync, in-process
+        consumer of the same ``create_agent()`` factory — not a wrapper
+        around Gateway.  The two paths **should** stay in sync on which
+        LangGraph stream modes they subscribe to; that invariant is
+        enforced by ``tests/test_client.py::test_messages_mode_emits_token_deltas``
+        rather than by a shared constant, because the three layers
+        (Graph, Platform SDK, HTTP) each use their own naming
+        (``messages`` vs ``messages-tuple``) and cannot literally share
+        a string.
+
         Args:
             message: User message text.
             thread_id: Thread ID for conversation context. Auto-generated if None.
@@ -345,8 +537,9 @@ class DeerFlowClient:
         Yields:
             StreamEvent with one of:
             - type="values"          data={"title": str|None, "messages": [...], "artifacts": [...]}
-            - type="messages-tuple"  data={"type": "ai", "content": str, "id": str}
-            - type="messages-tuple"  data={"type": "ai", "content": str, "id": str, "usage_metadata": {...}}
+            - type="custom"          data={...}
+            - type="messages-tuple"  data={"type": "ai", "content": <delta>, "id": str}
+            - type="messages-tuple"  data={"type": "ai", "content": <delta>, "id": str, "usage_metadata": {...}}
             - type="messages-tuple"  data={"type": "ai", "content": "", "id": str, "tool_calls": [...]}
             - type="messages-tuple"  data={"type": "tool", "content": str, "name": str, "tool_call_id": str, "id": str}
             - type="end"             data={"usage": {"input_tokens": int, "output_tokens": int, "total_tokens": int}}
@@ -363,9 +556,88 @@ class DeerFlowClient:
             context["agent_name"] = self._agent_name
 
         seen_ids: set[str] = set()
+        # Cross-mode handoff: ids already streamed via LangGraph ``messages``
+        # mode so the ``values`` path skips re-synthesis of the same message.
+        streamed_ids: set[str] = set()
+        # The same message id carries identical cumulative ``usage_metadata``
+        # in both the final ``messages`` chunk and the values snapshot —
+        # count it only on whichever arrives first.
+        counted_usage_ids: set[str] = set()
         cumulative_usage: dict[str, int] = {"input_tokens": 0, "output_tokens": 0, "total_tokens": 0}
 
-        for chunk in self._agent.stream(state, config=config, context=context, stream_mode="values"):
+        def _account_usage(msg_id: str | None, usage: Any) -> dict | None:
+            """Add *usage* to cumulative totals if this id has not been counted.
+
+            ``usage`` is a ``langchain_core.messages.UsageMetadata`` TypedDict
+            or ``None``; typed as ``Any`` because TypedDicts are not
+            structurally assignable to plain ``dict`` under strict type
+            checking.  Returns the normalized usage dict (for attaching
+            to an event) when we accepted it, otherwise ``None``.
+            """
+            if not usage:
+                return None
+            if msg_id and msg_id in counted_usage_ids:
+                return None
+            if msg_id:
+                counted_usage_ids.add(msg_id)
+            input_tokens = usage.get("input_tokens", 0) or 0
+            output_tokens = usage.get("output_tokens", 0) or 0
+            total_tokens = usage.get("total_tokens", 0) or 0
+            cumulative_usage["input_tokens"] += input_tokens
+            cumulative_usage["output_tokens"] += output_tokens
+            cumulative_usage["total_tokens"] += total_tokens
+            return {
+                "input_tokens": input_tokens,
+                "output_tokens": output_tokens,
+                "total_tokens": total_tokens,
+            }
+
+        for item in self._agent.stream(
+            state,
+            config=config,
+            context=context,
+            stream_mode=["values", "messages", "custom"],
+        ):
+            if isinstance(item, tuple) and len(item) == 2:
+                mode, chunk = item
+                mode = str(mode)
+            else:
+                mode, chunk = "values", item
+
+            if mode == "custom":
+                yield StreamEvent(type="custom", data=chunk)
+                continue
+
+            if mode == "messages":
+                # LangGraph ``messages`` mode emits ``(message_chunk, metadata)``.
+                if isinstance(chunk, tuple) and len(chunk) == 2:
+                    msg_chunk, _metadata = chunk
+                else:
+                    msg_chunk = chunk
+
+                msg_id = getattr(msg_chunk, "id", None)
+
+                if isinstance(msg_chunk, AIMessage):
+                    text = self._extract_text(msg_chunk.content)
+                    counted_usage = _account_usage(msg_id, msg_chunk.usage_metadata)
+
+                    if text:
+                        if msg_id:
+                            streamed_ids.add(msg_id)
+                        yield self._ai_text_event(msg_id, text, counted_usage)
+
+                    if msg_chunk.tool_calls:
+                        if msg_id:
+                            streamed_ids.add(msg_id)
+                        yield self._ai_tool_calls_event(msg_id, msg_chunk.tool_calls)
+
+                elif isinstance(msg_chunk, ToolMessage):
+                    if msg_id:
+                        streamed_ids.add(msg_id)
+                    yield self._tool_message_event(msg_chunk)
+                continue
+
+            # mode == "values"
             messages = chunk.get("messages", [])
 
             for msg in messages:
@@ -375,47 +647,25 @@ class DeerFlowClient:
                 if msg_id:
                     seen_ids.add(msg_id)
 
+                # Already streamed via ``messages`` mode; only (defensively)
+                # capture usage here and skip re-synthesizing the event.
+                if msg_id and msg_id in streamed_ids:
+                    if isinstance(msg, AIMessage):
+                        _account_usage(msg_id, getattr(msg, "usage_metadata", None))
+                    continue
+
                 if isinstance(msg, AIMessage):
-                    # Track token usage from AI messages
-                    usage = getattr(msg, "usage_metadata", None)
-                    if usage:
-                        cumulative_usage["input_tokens"] += usage.get("input_tokens", 0) or 0
-                        cumulative_usage["output_tokens"] += usage.get("output_tokens", 0) or 0
-                        cumulative_usage["total_tokens"] += usage.get("total_tokens", 0) or 0
+                    counted_usage = _account_usage(msg_id, msg.usage_metadata)
 
                     if msg.tool_calls:
-                        yield StreamEvent(
-                            type="messages-tuple",
-                            data={
-                                "type": "ai",
-                                "content": "",
-                                "id": msg_id,
-                                "tool_calls": [{"name": tc["name"], "args": tc["args"], "id": tc.get("id")} for tc in msg.tool_calls],
-                            },
-                        )
+                        yield self._ai_tool_calls_event(msg_id, msg.tool_calls)
 
                     text = self._extract_text(msg.content)
                     if text:
-                        event_data: dict[str, Any] = {"type": "ai", "content": text, "id": msg_id}
-                        if usage:
-                            event_data["usage_metadata"] = {
-                                "input_tokens": usage.get("input_tokens", 0) or 0,
-                                "output_tokens": usage.get("output_tokens", 0) or 0,
-                                "total_tokens": usage.get("total_tokens", 0) or 0,
-                            }
-                        yield StreamEvent(type="messages-tuple", data=event_data)
+                        yield self._ai_text_event(msg_id, text, counted_usage)
 
                 elif isinstance(msg, ToolMessage):
-                    yield StreamEvent(
-                        type="messages-tuple",
-                        data={
-                            "type": "tool",
-                            "content": self._extract_text(msg.content),
-                            "name": getattr(msg, "name", None),
-                            "tool_call_id": getattr(msg, "tool_call_id", None),
-                            "id": msg_id,
-                        },
-                    )
+                    yield self._tool_message_event(msg)
 
             # Emit a values event for each state snapshot
             yield StreamEvent(
@@ -432,10 +682,12 @@ class DeerFlowClient:
     def chat(self, message: str, *, thread_id: str | None = None, **kwargs) -> str:
         """Send a message and return the final text response.
 
-        Convenience wrapper around :meth:`stream` that returns only the
-        **last** AI text from ``messages-tuple`` events. If the agent emits
-        multiple text segments in one turn, intermediate segments are
-        discarded. Use :meth:`stream` directly to capture all events.
+        Convenience wrapper around :meth:`stream` that accumulates delta
+        ``messages-tuple`` events per ``id`` and returns the text of the
+        **last** AI message to complete.  Intermediate AI messages (e.g.
+        planner drafts) are discarded — only the final id's accumulated
+        text is returned.  Use :meth:`stream` directly if you need every
+        delta as it arrives.
 
         Args:
             message: User message text.
@@ -443,15 +695,21 @@ class DeerFlowClient:
             **kwargs: Override client defaults (same as stream()).
 
         Returns:
-            The last AI message text, or empty string if no response.
+            The accumulated text of the last AI message, or empty string
+            if no AI text was produced.
         """
-        last_text = ""
+        # Per-id delta lists joined once at the end — avoids the O(n²) cost
+        # of repeated ``str + str`` on a growing buffer for long responses.
+        chunks: dict[str, list[str]] = {}
+        last_id: str = ""
         for event in self.stream(message, thread_id=thread_id, **kwargs):
             if event.type == "messages-tuple" and event.data.get("type") == "ai":
-                content = event.data.get("content", "")
-                if content:
-                    last_text = content
-        return last_text
+                msg_id = event.data.get("id") or ""
+                delta = event.data.get("content", "")
+                if delta:
+                    chunks.setdefault(msg_id, []).append(delta)
+                    last_id = msg_id
+        return "".join(chunks.get(last_id, ()))
 
     # ------------------------------------------------------------------
     # Public API — configuration queries

backend/packages/harness/deerflow/community/aio_sandbox/aio_sandbox_provider.py

@@ -112,6 +112,9 @@ class AioSandboxProvider(SandboxProvider):
         atexit.register(self.shutdown)
         self._register_signal_handlers()
 
+        # Reconcile orphaned containers from previous process lifecycles
+        self._reconcile_orphans()
+
         # Start idle checker if enabled
         if self._config.get("idle_timeout", DEFAULT_IDLE_TIMEOUT) > 0:
             self._start_idle_checker()
@@ -175,6 +178,51 @@ class AioSandboxProvider(SandboxProvider):
                 resolved[key] = str(value)
         return resolved
 
+    # ── Startup reconciliation ────────────────────────────────────────────
+
+    def _reconcile_orphans(self) -> None:
+        """Reconcile orphaned containers left by previous process lifecycles.
+
+        On startup, enumerate all running containers matching our prefix
+        and adopt them all into the warm pool.  The idle checker will reclaim
+        containers that nobody re-acquires within ``idle_timeout``.
+
+        All containers are adopted unconditionally because we cannot
+        distinguish "orphaned" from "actively used by another process"
+        based on age alone — ``idle_timeout`` represents inactivity, not
+        uptime.  Adopting into the warm pool and letting the idle checker
+        decide avoids destroying containers that a concurrent process may
+        still be using.
+
+        This closes the fundamental gap where in-memory state loss (process
+        restart, crash, SIGKILL) leaves Docker containers running forever.
+        """
+        try:
+            running = self._backend.list_running()
+        except Exception as e:
+            logger.warning(f"Failed to enumerate running containers during startup reconciliation: {e}")
+            return
+
+        if not running:
+            return
+
+        current_time = time.time()
+        adopted = 0
+
+        for info in running:
+            age = current_time - info.created_at if info.created_at > 0 else float("inf")
+            # Single lock acquisition per container: atomic check-and-insert.
+            # Avoids a TOCTOU window between the "already tracked?" check and
+            # the warm-pool insert.
+            with self._lock:
+                if info.sandbox_id in self._sandboxes or info.sandbox_id in self._warm_pool:
+                    continue
+                self._warm_pool[info.sandbox_id] = (info, current_time)
+            adopted += 1
+            logger.info(f"Adopted container {info.sandbox_id} into warm pool (age: {age:.0f}s)")
+
+        logger.info(f"Startup reconciliation complete: {adopted} adopted into warm pool, {len(running)} total found")
+
     # ── Deterministic ID ─────────────────────────────────────────────────
 
     @staticmethod
@@ -316,13 +364,23 @@ class AioSandboxProvider(SandboxProvider):
     # ── Signal handling ──────────────────────────────────────────────────
 
     def _register_signal_handlers(self) -> None:
-        """Register signal handlers for graceful shutdown."""
+        """Register signal handlers for graceful shutdown.
+
+        Handles SIGTERM, SIGINT, and SIGHUP (terminal close) to ensure
+        sandbox containers are cleaned up even when the user closes the terminal.
+        """
         self._original_sigterm = signal.getsignal(signal.SIGTERM)
         self._original_sigint = signal.getsignal(signal.SIGINT)
+        self._original_sighup = signal.getsignal(signal.SIGHUP) if hasattr(signal, "SIGHUP") else None
 
         def signal_handler(signum, frame):
             self.shutdown()
-            original = self._original_sigterm if signum == signal.SIGTERM else self._original_sigint
+            if signum == signal.SIGTERM:
+                original = self._original_sigterm
+            elif hasattr(signal, "SIGHUP") and signum == signal.SIGHUP:
+                original = self._original_sighup
+            else:
+                original = self._original_sigint
             if callable(original):
                 original(signum, frame)
             elif original == signal.SIG_DFL:
@@ -332,6 +390,8 @@ class AioSandboxProvider(SandboxProvider):
         try:
             signal.signal(signal.SIGTERM, signal_handler)
             signal.signal(signal.SIGINT, signal_handler)
+            if hasattr(signal, "SIGHUP"):
+                signal.signal(signal.SIGHUP, signal_handler)
         except ValueError:
             logger.debug("Could not register signal handlers (not main thread)")
 

backend/packages/harness/deerflow/community/aio_sandbox/backend.py

@@ -96,3 +96,19 @@ class SandboxBackend(ABC):
             SandboxInfo if found and healthy, None otherwise.
         """
         ...
+
+    def list_running(self) -> list[SandboxInfo]:
+        """Enumerate all running sandboxes managed by this backend.
+
+        Used for startup reconciliation: when the process restarts, it needs
+        to discover containers started by previous processes so they can be
+        adopted into the warm pool or destroyed if idle too long.
+
+        The default implementation returns an empty list, which is correct
+        for backends that don't manage local containers (e.g., RemoteSandboxBackend
+        delegates lifecycle to the provisioner which handles its own cleanup).
+
+        Returns:
+            A list of SandboxInfo for all currently running sandboxes.
+        """
+        return []

backend/packages/harness/deerflow/community/aio_sandbox/local_backend.py

@@ -6,9 +6,11 @@ Handles container lifecycle, port allocation, and cross-process container discov
 
 from __future__ import annotations
 
+import json
 import logging
 import os
 import subprocess
+from datetime import datetime
 
 from deerflow.utils.network import get_free_port, release_port
 
@@ -18,6 +20,52 @@ from .sandbox_info import SandboxInfo
 logger = logging.getLogger(__name__)
 
 
+def _parse_docker_timestamp(raw: str) -> float:
+    """Parse Docker's ISO 8601 timestamp into a Unix epoch float.
+
+    Docker returns timestamps with nanosecond precision and a trailing ``Z``
+    (e.g. ``2026-04-08T01:22:50.123456789Z``).  Python's ``fromisoformat``
+    accepts at most microseconds and (pre-3.11) does not accept ``Z``, so the
+    string is normalized before parsing.  Returns ``0.0`` on empty input or
+    parse failure so callers can use ``0.0`` as a sentinel for "unknown age".
+    """
+    if not raw:
+        return 0.0
+    try:
+        s = raw.strip()
+        if "." in s:
+            dot_pos = s.index(".")
+            tz_start = dot_pos + 1
+            while tz_start < len(s) and s[tz_start].isdigit():
+                tz_start += 1
+            frac = s[dot_pos + 1 : tz_start][:6]  # truncate to microseconds
+            tz_suffix = s[tz_start:]
+            s = s[: dot_pos + 1] + frac + tz_suffix
+        if s.endswith("Z"):
+            s = s[:-1] + "+00:00"
+        return datetime.fromisoformat(s).timestamp()
+    except (ValueError, TypeError) as e:
+        logger.debug(f"Could not parse docker timestamp {raw!r}: {e}")
+        return 0.0
+
+
+def _extract_host_port(inspect_entry: dict, container_port: int) -> int | None:
+    """Extract the host port mapped to ``container_port/tcp`` from a docker inspect entry.
+
+    Returns None if the container has no port mapping for that port.
+    """
+    try:
+        ports = (inspect_entry.get("NetworkSettings") or {}).get("Ports") or {}
+        bindings = ports.get(f"{container_port}/tcp") or []
+        if bindings:
+            host_port = bindings[0].get("HostPort")
+            if host_port:
+                return int(host_port)
+    except (ValueError, TypeError, AttributeError):
+        pass
+    return None
+
+
 def _format_container_mount(runtime: str, host_path: str, container_path: str, read_only: bool) -> list[str]:
     """Format a bind-mount argument for the selected runtime.
 
@@ -172,8 +220,12 @@ class LocalContainerBackend(SandboxBackend):
 
     def destroy(self, info: SandboxInfo) -> None:
         """Stop the container and release its port."""
-        if info.container_id:
-            self._stop_container(info.container_id)
+        # Prefer container_id, fall back to container_name (both accepted by docker stop).
+        # This ensures containers discovered via list_running() (which only has the name)
+        # can also be stopped.
+        stop_target = info.container_id or info.container_name
+        if stop_target:
+            self._stop_container(stop_target)
         # Extract port from sandbox_url for release
         try:
             from urllib.parse import urlparse
@@ -222,6 +274,129 @@ class LocalContainerBackend(SandboxBackend):
             container_name=container_name,
         )
 
+    def list_running(self) -> list[SandboxInfo]:
+        """Enumerate all running containers matching the configured prefix.
+
+        Uses a single ``docker ps`` call to list container names, then a
+        single batched ``docker inspect`` call to retrieve creation timestamp
+        and port mapping for all containers at once.  Total subprocess calls:
+        2 (down from 2N+1 in the naive per-container approach).
+
+        Note: Docker's ``--filter name=`` performs *substring* matching,
+        so a secondary ``startswith`` check is applied to ensure only
+        containers with the exact prefix are included.
+
+        Containers without port mappings are still included (with empty
+        sandbox_url) so that startup reconciliation can adopt orphans
+        regardless of their port state.
+        """
+        # Step 1: enumerate container names via docker ps
+        try:
+            result = subprocess.run(
+                [
+                    self._runtime,
+                    "ps",
+                    "--filter",
+                    f"name={self._container_prefix}-",
+                    "--format",
+                    "{{.Names}}",
+                ],
+                capture_output=True,
+                text=True,
+                timeout=10,
+            )
+            if result.returncode != 0:
+                stderr = (result.stderr or "").strip()
+                logger.warning(
+                    "Failed to list running containers with %s ps (returncode=%s, stderr=%s)",
+                    self._runtime,
+                    result.returncode,
+                    stderr or "<empty>",
+                )
+                return []
+            if not result.stdout.strip():
+                return []
+        except (subprocess.CalledProcessError, subprocess.TimeoutExpired, FileNotFoundError, OSError) as e:
+            logger.warning(f"Failed to list running containers: {e}")
+            return []
+
+        # Filter to names matching our exact prefix (docker filter is substring-based)
+        container_names = [name.strip() for name in result.stdout.strip().splitlines() if name.strip().startswith(self._container_prefix + "-")]
+        if not container_names:
+            return []
+
+        # Step 2: batched docker inspect — single subprocess call for all containers
+        inspections = self._batch_inspect(container_names)
+
+        infos: list[SandboxInfo] = []
+        sandbox_host = os.environ.get("DEER_FLOW_SANDBOX_HOST", "localhost")
+        for container_name in container_names:
+            data = inspections.get(container_name)
+            if data is None:
+                # Container disappeared between ps and inspect, or inspect failed
+                continue
+            created_at, host_port = data
+            sandbox_id = container_name[len(self._container_prefix) + 1 :]
+            sandbox_url = f"http://{sandbox_host}:{host_port}" if host_port else ""
+
+            infos.append(
+                SandboxInfo(
+                    sandbox_id=sandbox_id,
+                    sandbox_url=sandbox_url,
+                    container_name=container_name,
+                    created_at=created_at,
+                )
+            )
+
+        logger.info(f"Found {len(infos)} running sandbox container(s)")
+        return infos
+
+    def _batch_inspect(self, container_names: list[str]) -> dict[str, tuple[float, int | None]]:
+        """Batch-inspect containers in a single subprocess call.
+
+        Returns a mapping of ``container_name -> (created_at, host_port)``.
+        Missing containers or parse failures are silently dropped from the result.
+        """
+        if not container_names:
+            return {}
+        try:
+            result = subprocess.run(
+                [self._runtime, "inspect", *container_names],
+                capture_output=True,
+                text=True,
+                timeout=15,
+            )
+        except (subprocess.CalledProcessError, subprocess.TimeoutExpired, FileNotFoundError, OSError) as e:
+            logger.warning(f"Failed to batch-inspect containers: {e}")
+            return {}
+
+        if result.returncode != 0:
+            stderr = (result.stderr or "").strip()
+            logger.warning(
+                "Failed to batch-inspect containers with %s inspect (returncode=%s, stderr=%s)",
+                self._runtime,
+                result.returncode,
+                stderr or "<empty>",
+            )
+            return {}
+
+        try:
+            payload = json.loads(result.stdout or "[]")
+        except json.JSONDecodeError as e:
+            logger.warning(f"Failed to parse docker inspect output as JSON: {e}")
+            return {}
+
+        out: dict[str, tuple[float, int | None]] = {}
+        for entry in payload:
+            # ``Name`` is prefixed with ``/`` in the docker inspect response
+            name = (entry.get("Name") or "").lstrip("/")
+            if not name:
+                continue
+            created_at = _parse_docker_timestamp(entry.get("Created", ""))
+            host_port = _extract_host_port(entry, 8080)
+            out[name] = (created_at, host_port)
+        return out
+
     # ── Container operations ─────────────────────────────────────────────
 
     def _start_container(

backend/packages/harness/deerflow/community/exa/tools.py

@@ -0,0 +1,79 @@
+import json
+
+from exa_py import Exa
+from langchain.tools import tool
+
+from deerflow.config import get_app_config
+
+
+def _get_exa_client(tool_name: str = "web_search") -> Exa:
+    config = get_app_config().get_tool_config(tool_name)
+    api_key = None
+    if config is not None and "api_key" in config.model_extra:
+        api_key = config.model_extra.get("api_key")
+    return Exa(api_key=api_key)
+
+
+@tool("web_search", parse_docstring=True)
+def web_search_tool(query: str) -> str:
+    """Search the web.
+
+    Args:
+        query: The query to search for.
+    """
+    try:
+        config = get_app_config().get_tool_config("web_search")
+        max_results = 5
+        search_type = "auto"
+        contents_max_characters = 1000
+        if config is not None:
+            max_results = config.model_extra.get("max_results", max_results)
+            search_type = config.model_extra.get("search_type", search_type)
+            contents_max_characters = config.model_extra.get("contents_max_characters", contents_max_characters)
+
+        client = _get_exa_client()
+        res = client.search(
+            query,
+            type=search_type,
+            num_results=max_results,
+            contents={"highlights": {"max_characters": contents_max_characters}},
+        )
+
+        normalized_results = [
+            {
+                "title": result.title or "",
+                "url": result.url or "",
+                "snippet": "\n".join(result.highlights) if result.highlights else "",
+            }
+            for result in res.results
+        ]
+        json_results = json.dumps(normalized_results, indent=2, ensure_ascii=False)
+        return json_results
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+
+@tool("web_fetch", parse_docstring=True)
+def web_fetch_tool(url: str) -> str:
+    """Fetch the contents of a web page at a given URL.
+    Only fetch EXACT URLs that have been provided directly by the user or have been returned in results from the web_search and web_fetch tools.
+    This tool can NOT access content that requires authentication, such as private Google Docs or pages behind login walls.
+    Do NOT add www. to URLs that do NOT have them.
+    URLs must include the schema: https://example.com is a valid URL while example.com is an invalid URL.
+
+    Args:
+        url: The URL to fetch the contents of.
+    """
+    try:
+        client = _get_exa_client("web_fetch")
+        res = client.get_contents([url], text={"max_characters": 4096})
+
+        if res.results:
+            result = res.results[0]
+            title = result.title or "Untitled"
+            text = result.text or ""
+            return f"# {title}\n\n{text[:4096]}"
+        else:
+            return "Error: No results found"
+    except Exception as e:
+        return f"Error: {str(e)}"

backend/packages/harness/deerflow/community/firecrawl/tools.py

@@ -6,10 +6,10 @@ from langchain.tools import tool
 from deerflow.config import get_app_config
 
 
-def _get_firecrawl_client() -> FirecrawlApp:
-    config = get_app_config().get_tool_config("web_search")
+def _get_firecrawl_client(tool_name: str = "web_search") -> FirecrawlApp:
+    config = get_app_config().get_tool_config(tool_name)
     api_key = None
-    if config is not None:
+    if config is not None and "api_key" in config.model_extra:
         api_key = config.model_extra.get("api_key")
     return FirecrawlApp(api_key=api_key)  # type: ignore[arg-type]
 
@@ -27,7 +27,7 @@ def web_search_tool(query: str) -> str:
         if config is not None:
             max_results = config.model_extra.get("max_results", max_results)
 
-        client = _get_firecrawl_client()
+        client = _get_firecrawl_client("web_search")
         result = client.search(query, limit=max_results)
 
         # result.web contains list of SearchResultWeb objects
@@ -58,7 +58,7 @@ def web_fetch_tool(url: str) -> str:
         url: The URL to fetch the contents of.
     """
     try:
-        client = _get_firecrawl_client()
+        client = _get_firecrawl_client("web_fetch")
         result = client.scrape(url, formats=["markdown"])
 
         markdown_content = result.markdown or ""

backend/packages/harness/deerflow/config/__init__.py

@@ -2,6 +2,7 @@ from .app_config import get_app_config
 from .extensions_config import ExtensionsConfig, get_extensions_config
 from .memory_config import MemoryConfig, get_memory_config
 from .paths import Paths, get_paths
+from .skill_evolution_config import SkillEvolutionConfig
 from .skills_config import SkillsConfig
 from .tracing_config import (
     get_enabled_tracing_providers,
@@ -13,6 +14,7 @@ from .tracing_config import (
 
 __all__ = [
     "get_app_config",
+    "SkillEvolutionConfig",
     "Paths",
     "get_paths",
     "SkillsConfig",

backend/packages/harness/deerflow/config/app_config.py

@@ -10,11 +10,14 @@ from pydantic import BaseModel, ConfigDict, Field
 
 from deerflow.config.acp_config import load_acp_config_from_dict
 from deerflow.config.checkpointer_config import CheckpointerConfig, load_checkpointer_config_from_dict
+from deerflow.config.database_config import DatabaseConfig
 from deerflow.config.extensions_config import ExtensionsConfig
 from deerflow.config.guardrails_config import GuardrailsConfig, load_guardrails_config_from_dict
 from deerflow.config.memory_config import MemoryConfig, load_memory_config_from_dict
 from deerflow.config.model_config import ModelConfig
+from deerflow.config.run_events_config import RunEventsConfig
 from deerflow.config.sandbox_config import SandboxConfig
+from deerflow.config.skill_evolution_config import SkillEvolutionConfig
 from deerflow.config.skills_config import SkillsConfig
 from deerflow.config.stream_bridge_config import StreamBridgeConfig, load_stream_bridge_config_from_dict
 from deerflow.config.subagents_config import SubagentsAppConfig, load_subagents_config_from_dict
@@ -46,6 +49,7 @@ class AppConfig(BaseModel):
     tools: list[ToolConfig] = Field(default_factory=list, description="Available tools")
     tool_groups: list[ToolGroupConfig] = Field(default_factory=list, description="Available tool groups")
     skills: SkillsConfig = Field(default_factory=SkillsConfig, description="Skills configuration")
+    skill_evolution: SkillEvolutionConfig = Field(default_factory=SkillEvolutionConfig, description="Agent-managed skill evolution configuration")
     extensions: ExtensionsConfig = Field(default_factory=ExtensionsConfig, description="Extensions configuration (MCP servers and skills state)")
     tool_search: ToolSearchConfig = Field(default_factory=ToolSearchConfig, description="Tool search / deferred loading configuration")
     title: TitleConfig = Field(default_factory=TitleConfig, description="Automatic title generation configuration")
@@ -54,6 +58,8 @@ class AppConfig(BaseModel):
     subagents: SubagentsAppConfig = Field(default_factory=SubagentsAppConfig, description="Subagent runtime configuration")
     guardrails: GuardrailsConfig = Field(default_factory=GuardrailsConfig, description="Guardrail middleware configuration")
     model_config = ConfigDict(extra="allow", frozen=False)
+    database: DatabaseConfig = Field(default_factory=DatabaseConfig, description="Unified database backend configuration")
+    run_events: RunEventsConfig = Field(default_factory=RunEventsConfig, description="Run event storage configuration")
     checkpointer: CheckpointerConfig | None = Field(default=None, description="Checkpointer configuration")
     stream_bridge: StreamBridgeConfig | None = Field(default=None, description="Stream bridge configuration")
 

backend/packages/harness/deerflow/config/database_config.py

@@ -0,0 +1,92 @@
+"""Unified database backend configuration.
+
+Controls BOTH the LangGraph checkpointer and the DeerFlow application
+persistence layer (runs, threads metadata, users, etc.). The user
+configures one backend; the system handles physical separation details.
+
+SQLite mode: checkpointer and app use different .db files in the same
+directory to avoid write-lock contention. This is automatic.
+
+Postgres mode: both use the same database URL but maintain independent
+connection pools with different lifecycles.
+
+Memory mode: checkpointer uses MemorySaver, app uses in-memory stores.
+No database is initialized.
+
+Sensitive values (postgres_url) should use $VAR syntax in config.yaml
+to reference environment variables from .env:
+
+    database:
+      backend: postgres
+      postgres_url: $DATABASE_URL
+
+The $VAR resolution is handled by AppConfig.resolve_env_variables()
+before this config is instantiated -- DatabaseConfig itself does not
+need to do any environment variable processing.
+"""
+
+from __future__ import annotations
+
+import os
+from typing import Literal
+
+from pydantic import BaseModel, Field
+
+
+class DatabaseConfig(BaseModel):
+    backend: Literal["memory", "sqlite", "postgres"] = Field(
+        default="memory",
+        description=("Storage backend for both checkpointer and application data. 'memory' for development (no persistence across restarts), 'sqlite' for single-node deployment, 'postgres' for production multi-node deployment."),
+    )
+    sqlite_dir: str = Field(
+        default=".deer-flow/data",
+        description=("Directory for SQLite database files. Checkpointer uses {sqlite_dir}/checkpoints.db, application data uses {sqlite_dir}/app.db."),
+    )
+    postgres_url: str = Field(
+        default="",
+        description=(
+            "PostgreSQL connection URL, shared by checkpointer and app. "
+            "Use $DATABASE_URL in config.yaml to reference .env. "
+            "Example: postgresql://user:pass@host:5432/deerflow "
+            "(the +asyncpg driver suffix is added automatically where needed)."
+        ),
+    )
+    echo_sql: bool = Field(
+        default=False,
+        description="Echo all SQL statements to log (debug only).",
+    )
+    pool_size: int = Field(
+        default=5,
+        description="Connection pool size for the app ORM engine (postgres only).",
+    )
+
+    # -- Derived helpers (not user-configured) --
+
+    @property
+    def _resolved_sqlite_dir(self) -> str:
+        """Resolve sqlite_dir to an absolute path (relative to CWD)."""
+        from pathlib import Path
+
+        return str(Path(self.sqlite_dir).resolve())
+
+    @property
+    def checkpointer_sqlite_path(self) -> str:
+        """SQLite file path for the LangGraph checkpointer."""
+        return os.path.join(self._resolved_sqlite_dir, "checkpoints.db")
+
+    @property
+    def app_sqlite_path(self) -> str:
+        """SQLite file path for application ORM data."""
+        return os.path.join(self._resolved_sqlite_dir, "app.db")
+
+    @property
+    def app_sqlalchemy_url(self) -> str:
+        """SQLAlchemy async URL for the application ORM engine."""
+        if self.backend == "sqlite":
+            return f"sqlite+aiosqlite:///{self.app_sqlite_path}"
+        if self.backend == "postgres":
+            url = self.postgres_url
+            if url.startswith("postgresql://"):
+                url = url.replace("postgresql://", "postgresql+asyncpg://", 1)
+            return url
+        raise ValueError(f"No SQLAlchemy URL for backend={self.backend!r}")

backend/packages/harness/deerflow/config/model_config.py

@@ -27,6 +27,10 @@ class ModelConfig(BaseModel):
         default_factory=lambda: None,
         description="Extra settings to be passed to the model when thinking is enabled",
     )
+    when_thinking_disabled: dict | None = Field(
+        default_factory=lambda: None,
+        description="Extra settings to be passed to the model when thinking is disabled",
+    )
     supports_vision: bool = Field(default_factory=lambda: False, description="Whether the model supports vision/image inputs")
     thinking: dict | None = Field(
         default_factory=lambda: None,

backend/packages/harness/deerflow/config/run_events_config.py

@@ -0,0 +1,33 @@
+"""Run event storage configuration.
+
+Controls where run events (messages + execution traces) are persisted.
+
+Backends:
+- memory: In-memory storage, data lost on restart. Suitable for
+  development and testing.
+- db: SQL database via SQLAlchemy ORM. Provides full query capability.
+  Suitable for production deployments.
+- jsonl: Append-only JSONL files. Lightweight alternative for
+  single-node deployments that need persistence without a database.
+"""
+
+from __future__ import annotations
+
+from typing import Literal
+
+from pydantic import BaseModel, Field
+
+
+class RunEventsConfig(BaseModel):
+    backend: Literal["memory", "db", "jsonl"] = Field(
+        default="memory",
+        description="Storage backend for run events. 'memory' for development (no persistence), 'db' for production (SQL queries), 'jsonl' for lightweight single-node persistence.",
+    )
+    max_trace_content: int = Field(
+        default=10240,
+        description="Maximum trace content size in bytes before truncation (db backend only).",
+    )
+    track_token_usage: bool = Field(
+        default=True,
+        description="Whether RunJournal should accumulate token counts to RunRow.",
+    )

backend/packages/harness/deerflow/config/sandbox_config.py

@@ -74,5 +74,10 @@ class SandboxConfig(BaseModel):
         ge=0,
         description="Maximum characters to keep from read_file tool output. Output exceeding this limit is head-truncated. Set to 0 to disable truncation.",
     )
+    ls_output_max_chars: int = Field(
+        default=20000,
+        ge=0,
+        description="Maximum characters to keep from ls tool output. Output exceeding this limit is head-truncated. Set to 0 to disable truncation.",
+    )
 
     model_config = ConfigDict(extra="allow")

backend/packages/harness/deerflow/config/skill_evolution_config.py

@@ -0,0 +1,14 @@
+from pydantic import BaseModel, Field
+
+
+class SkillEvolutionConfig(BaseModel):
+    """Configuration for agent-managed skill evolution."""
+
+    enabled: bool = Field(
+        default=False,
+        description="Whether the agent can create and modify skills under skills/custom.",
+    )
+    moderation_model_name: str | None = Field(
+        default=None,
+        description="Optional model name for skill security moderation. Defaults to the primary chat model.",
+    )

backend/packages/harness/deerflow/models/factory.py

@@ -9,6 +9,27 @@ from deerflow.tracing import build_tracing_callbacks
 logger = logging.getLogger(__name__)
 
 
+def _deep_merge_dicts(base: dict | None, override: dict) -> dict:
+    """Recursively merge two dictionaries without mutating the inputs."""
+    merged = dict(base or {})
+    for key, value in override.items():
+        if isinstance(value, dict) and isinstance(merged.get(key), dict):
+            merged[key] = _deep_merge_dicts(merged[key], value)
+        else:
+            merged[key] = value
+    return merged
+
+
+def _vllm_disable_chat_template_kwargs(chat_template_kwargs: dict) -> dict:
+    """Build the disable payload for vLLM/Qwen chat template kwargs."""
+    disable_kwargs: dict[str, bool] = {}
+    if "thinking" in chat_template_kwargs:
+        disable_kwargs["thinking"] = False
+    if "enable_thinking" in chat_template_kwargs:
+        disable_kwargs["enable_thinking"] = False
+    return disable_kwargs
+
+
 def create_chat_model(name: str | None = None, thinking_enabled: bool = False, **kwargs) -> BaseChatModel:
     """Create a chat model instance from the config.
 
@@ -35,6 +56,7 @@ def create_chat_model(name: str | None = None, thinking_enabled: bool = False, *
             "supports_thinking",
             "supports_reasoning_effort",
             "when_thinking_enabled",
+            "when_thinking_disabled",
             "thinking",
             "supports_vision",
         },
@@ -51,16 +73,29 @@ def create_chat_model(name: str | None = None, thinking_enabled: bool = False, *
             raise ValueError(f"Model {name} does not support thinking. Set `supports_thinking` to true in the `config.yaml` to enable thinking.") from None
         if effective_wte:
             model_settings_from_config.update(effective_wte)
-    if not thinking_enabled and has_thinking_settings:
-        if effective_wte.get("extra_body", {}).get("thinking", {}).get("type"):
+    if not thinking_enabled:
+        if model_config.when_thinking_disabled is not None:
+            # User-provided disable settings take full precedence
+            model_settings_from_config.update(model_config.when_thinking_disabled)
+        elif has_thinking_settings and effective_wte.get("extra_body", {}).get("thinking", {}).get("type"):
             # OpenAI-compatible gateway: thinking is nested under extra_body
-            kwargs.update({"extra_body": {"thinking": {"type": "disabled"}}})
-            kwargs.update({"reasoning_effort": "minimal"})
-        elif effective_wte.get("thinking", {}).get("type"):
+            model_settings_from_config["extra_body"] = _deep_merge_dicts(
+                model_settings_from_config.get("extra_body"),
+                {"thinking": {"type": "disabled"}},
+            )
+            model_settings_from_config["reasoning_effort"] = "minimal"
+        elif has_thinking_settings and (disable_chat_template_kwargs := _vllm_disable_chat_template_kwargs(effective_wte.get("extra_body", {}).get("chat_template_kwargs") or {})):
+            # vLLM uses chat template kwargs to switch thinking on/off.
+            model_settings_from_config["extra_body"] = _deep_merge_dicts(
+                model_settings_from_config.get("extra_body"),
+                {"chat_template_kwargs": disable_chat_template_kwargs},
+            )
+        elif has_thinking_settings and effective_wte.get("thinking", {}).get("type"):
             # Native langchain_anthropic: thinking is a direct constructor parameter
-            kwargs.update({"thinking": {"type": "disabled"}})
-    if not model_config.supports_reasoning_effort and "reasoning_effort" in kwargs:
-        del kwargs["reasoning_effort"]
+            model_settings_from_config["thinking"] = {"type": "disabled"}
+    if not model_config.supports_reasoning_effort:
+        kwargs.pop("reasoning_effort", None)
+        model_settings_from_config.pop("reasoning_effort", None)
 
     # For Codex Responses API models: map thinking mode to reasoning_effort
     from deerflow.models.openai_codex_provider import CodexChatModel
@@ -78,6 +113,15 @@ def create_chat_model(name: str | None = None, thinking_enabled: bool = False, *
         elif "reasoning_effort" not in model_settings_from_config:
             model_settings_from_config["reasoning_effort"] = "medium"
 
+    # Ensure stream_usage is enabled so that token usage metadata is available
+    # in streaming responses.  LangChain's BaseChatOpenAI only defaults
+    # stream_usage=True when no custom base_url/api_base is set, so models
+    # hitting third-party endpoints (e.g. doubao, deepseek) silently lose
+    # usage data.  We default it to True unless explicitly configured.
+    if "stream_usage" not in model_settings_from_config and "stream_usage" not in kwargs:
+        if "stream_usage" in getattr(model_class, "model_fields", {}):
+            model_settings_from_config["stream_usage"] = True
+
     model_instance = model_class(**kwargs, **model_settings_from_config)
 
     callbacks = build_tracing_callbacks()

backend/packages/harness/deerflow/models/openai_codex_provider.py

@@ -48,6 +48,10 @@ class CodexChatModel(BaseChatModel):
 
     model_config = {"arbitrary_types_allowed": True}
 
+    @classmethod
+    def is_lc_serializable(cls) -> bool:
+        return True
+
     @property
     def _llm_type(self) -> str:
         return "codex-responses"
@@ -216,18 +220,48 @@ class CodexChatModel(BaseChatModel):
     def _stream_response(self, headers: dict, payload: dict) -> dict:
         """Stream SSE from Codex API and collect the final response."""
         completed_response = None
+        streamed_output_items: dict[int, dict[str, Any]] = {}
 
         with httpx.Client(timeout=300) as client:
             with client.stream("POST", f"{CODEX_BASE_URL}/responses", headers=headers, json=payload) as resp:
                 resp.raise_for_status()
                 for line in resp.iter_lines():
                     data = self._parse_sse_data_line(line)
-                    if data and data.get("type") == "response.completed":
+                    if not data:
+                        continue
+
+                    event_type = data.get("type")
+                    if event_type == "response.output_item.done":
+                        output_index = data.get("output_index")
+                        output_item = data.get("item")
+                        if isinstance(output_index, int) and isinstance(output_item, dict):
+                            streamed_output_items[output_index] = output_item
+                    elif event_type == "response.completed":
                         completed_response = data["response"]
 
         if not completed_response:
             raise RuntimeError("Codex API stream ended without response.completed event")
 
+        # ChatGPT Codex can emit the final assistant content only in stream events.
+        # When response.completed arrives, response.output may still be empty.
+        if streamed_output_items:
+            merged_output = []
+            response_output = completed_response.get("output")
+            if isinstance(response_output, list):
+                merged_output = list(response_output)
+
+            max_index = max(max(streamed_output_items), len(merged_output) - 1)
+            if max_index >= 0 and len(merged_output) <= max_index:
+                merged_output.extend([None] * (max_index + 1 - len(merged_output)))
+
+            for output_index, output_item in streamed_output_items.items():
+                existing_item = merged_output[output_index]
+                if not isinstance(existing_item, dict):
+                    merged_output[output_index] = output_item
+
+            completed_response = dict(completed_response)
+            completed_response["output"] = [item for item in merged_output if isinstance(item, dict)]
+
         return completed_response
 
     @staticmethod

backend/packages/harness/deerflow/models/patched_deepseek.py

@@ -23,6 +23,14 @@ class PatchedChatDeepSeek(ChatDeepSeek):
     request payload.
     """
 
+    @classmethod
+    def is_lc_serializable(cls) -> bool:
+        return True
+
+    @property
+    def lc_secrets(self) -> dict[str, str]:
+        return {"api_key": "DEEPSEEK_API_KEY", "openai_api_key": "DEEPSEEK_API_KEY"}
+
     def _get_request_payload(
         self,
         input_: LanguageModelInput,

backend/packages/harness/deerflow/models/vllm_provider.py

@@ -0,0 +1,258 @@
+"""Custom vLLM provider built on top of LangChain ChatOpenAI.
+
+vLLM 0.19.0 exposes reasoning models through an OpenAI-compatible API, but
+LangChain's default OpenAI adapter drops the non-standard ``reasoning`` field
+from assistant messages and streaming deltas. That breaks interleaved
+thinking/tool-call flows because vLLM expects the assistant's prior reasoning to
+be echoed back on subsequent turns.
+
+This provider preserves ``reasoning`` on:
+- non-streaming responses
+- streaming deltas
+- multi-turn request payloads
+"""
+
+from __future__ import annotations
+
+import json
+from collections.abc import Mapping
+from typing import Any, cast
+
+import openai
+from langchain_core.language_models import LanguageModelInput
+from langchain_core.messages import (
+    AIMessage,
+    AIMessageChunk,
+    BaseMessageChunk,
+    ChatMessageChunk,
+    FunctionMessageChunk,
+    HumanMessageChunk,
+    SystemMessageChunk,
+    ToolMessageChunk,
+)
+from langchain_core.messages.tool import tool_call_chunk
+from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
+from langchain_openai import ChatOpenAI
+from langchain_openai.chat_models.base import _create_usage_metadata
+
+
+def _normalize_vllm_chat_template_kwargs(payload: dict[str, Any]) -> None:
+    """Map DeerFlow's legacy ``thinking`` toggle to vLLM/Qwen's ``enable_thinking``.
+
+    DeerFlow originally documented ``extra_body.chat_template_kwargs.thinking``
+    for vLLM, but vLLM 0.19.0's Qwen reasoning parser reads
+    ``chat_template_kwargs.enable_thinking``. Normalize the payload just before
+    it is sent so existing configs keep working and flash mode can truly
+    disable reasoning.
+    """
+    extra_body = payload.get("extra_body")
+    if not isinstance(extra_body, dict):
+        return
+
+    chat_template_kwargs = extra_body.get("chat_template_kwargs")
+    if not isinstance(chat_template_kwargs, dict):
+        return
+
+    if "thinking" not in chat_template_kwargs:
+        return
+
+    normalized_chat_template_kwargs = dict(chat_template_kwargs)
+    normalized_chat_template_kwargs.setdefault("enable_thinking", normalized_chat_template_kwargs["thinking"])
+    normalized_chat_template_kwargs.pop("thinking", None)
+    extra_body["chat_template_kwargs"] = normalized_chat_template_kwargs
+
+
+def _reasoning_to_text(reasoning: Any) -> str:
+    """Best-effort extraction of readable reasoning text from vLLM payloads."""
+    if isinstance(reasoning, str):
+        return reasoning
+
+    if isinstance(reasoning, list):
+        parts = [_reasoning_to_text(item) for item in reasoning]
+        return "".join(part for part in parts if part)
+
+    if isinstance(reasoning, dict):
+        for key in ("text", "content", "reasoning"):
+            value = reasoning.get(key)
+            if isinstance(value, str):
+                return value
+            if value is not None:
+                text = _reasoning_to_text(value)
+                if text:
+                    return text
+        try:
+            return json.dumps(reasoning, ensure_ascii=False)
+        except TypeError:
+            return str(reasoning)
+
+    try:
+        return json.dumps(reasoning, ensure_ascii=False)
+    except TypeError:
+        return str(reasoning)
+
+
+def _convert_delta_to_message_chunk_with_reasoning(_dict: Mapping[str, Any], default_class: type[BaseMessageChunk]) -> BaseMessageChunk:
+    """Convert a streaming delta to a LangChain message chunk while preserving reasoning."""
+    id_ = _dict.get("id")
+    role = cast(str, _dict.get("role"))
+    content = cast(str, _dict.get("content") or "")
+    additional_kwargs: dict[str, Any] = {}
+
+    if _dict.get("function_call"):
+        function_call = dict(_dict["function_call"])
+        if "name" in function_call and function_call["name"] is None:
+            function_call["name"] = ""
+        additional_kwargs["function_call"] = function_call
+
+    reasoning = _dict.get("reasoning")
+    if reasoning is not None:
+        additional_kwargs["reasoning"] = reasoning
+        reasoning_text = _reasoning_to_text(reasoning)
+        if reasoning_text:
+            additional_kwargs["reasoning_content"] = reasoning_text
+
+    tool_call_chunks = []
+    if raw_tool_calls := _dict.get("tool_calls"):
+        try:
+            tool_call_chunks = [
+                tool_call_chunk(
+                    name=rtc["function"].get("name"),
+                    args=rtc["function"].get("arguments"),
+                    id=rtc.get("id"),
+                    index=rtc["index"],
+                )
+                for rtc in raw_tool_calls
+            ]
+        except KeyError:
+            pass
+
+    if role == "user" or default_class == HumanMessageChunk:
+        return HumanMessageChunk(content=content, id=id_)
+    if role == "assistant" or default_class == AIMessageChunk:
+        return AIMessageChunk(
+            content=content,
+            additional_kwargs=additional_kwargs,
+            id=id_,
+            tool_call_chunks=tool_call_chunks,  # type: ignore[arg-type]
+        )
+    if role in ("system", "developer") or default_class == SystemMessageChunk:
+        role_kwargs = {"__openai_role__": "developer"} if role == "developer" else {}
+        return SystemMessageChunk(content=content, id=id_, additional_kwargs=role_kwargs)
+    if role == "function" or default_class == FunctionMessageChunk:
+        return FunctionMessageChunk(content=content, name=_dict["name"], id=id_)
+    if role == "tool" or default_class == ToolMessageChunk:
+        return ToolMessageChunk(content=content, tool_call_id=_dict["tool_call_id"], id=id_)
+    if role or default_class == ChatMessageChunk:
+        return ChatMessageChunk(content=content, role=role, id=id_)  # type: ignore[arg-type]
+    return default_class(content=content, id=id_)  # type: ignore[call-arg]
+
+
+def _restore_reasoning_field(payload_msg: dict[str, Any], orig_msg: AIMessage) -> None:
+    """Re-inject vLLM reasoning onto outgoing assistant messages."""
+    reasoning = orig_msg.additional_kwargs.get("reasoning")
+    if reasoning is None:
+        reasoning = orig_msg.additional_kwargs.get("reasoning_content")
+    if reasoning is not None:
+        payload_msg["reasoning"] = reasoning
+
+
+class VllmChatModel(ChatOpenAI):
+    """ChatOpenAI variant that preserves vLLM reasoning fields across turns."""
+
+    model_config = {"arbitrary_types_allowed": True}
+
+    @property
+    def _llm_type(self) -> str:
+        return "vllm-openai-compatible"
+
+    def _get_request_payload(
+        self,
+        input_: LanguageModelInput,
+        *,
+        stop: list[str] | None = None,
+        **kwargs: Any,
+    ) -> dict[str, Any]:
+        """Restore assistant reasoning in request payloads for interleaved thinking."""
+        original_messages = self._convert_input(input_).to_messages()
+        payload = super()._get_request_payload(input_, stop=stop, **kwargs)
+        _normalize_vllm_chat_template_kwargs(payload)
+        payload_messages = payload.get("messages", [])
+
+        if len(payload_messages) == len(original_messages):
+            for payload_msg, orig_msg in zip(payload_messages, original_messages):
+                if payload_msg.get("role") == "assistant" and isinstance(orig_msg, AIMessage):
+                    _restore_reasoning_field(payload_msg, orig_msg)
+        else:
+            ai_messages = [message for message in original_messages if isinstance(message, AIMessage)]
+            assistant_payloads = [message for message in payload_messages if message.get("role") == "assistant"]
+            for payload_msg, ai_msg in zip(assistant_payloads, ai_messages):
+                _restore_reasoning_field(payload_msg, ai_msg)
+
+        return payload
+
+    def _create_chat_result(self, response: dict | openai.BaseModel, generation_info: dict | None = None) -> ChatResult:
+        """Preserve vLLM reasoning on non-streaming responses."""
+        result = super()._create_chat_result(response, generation_info=generation_info)
+        response_dict = response if isinstance(response, dict) else response.model_dump()
+
+        for generation, choice in zip(result.generations, response_dict.get("choices", [])):
+            if not isinstance(generation, ChatGeneration):
+                continue
+            message = generation.message
+            if not isinstance(message, AIMessage):
+                continue
+            reasoning = choice.get("message", {}).get("reasoning")
+            if reasoning is None:
+                continue
+            message.additional_kwargs["reasoning"] = reasoning
+            reasoning_text = _reasoning_to_text(reasoning)
+            if reasoning_text:
+                message.additional_kwargs["reasoning_content"] = reasoning_text
+
+        return result
+
+    def _convert_chunk_to_generation_chunk(
+        self,
+        chunk: dict,
+        default_chunk_class: type,
+        base_generation_info: dict | None,
+    ) -> ChatGenerationChunk | None:
+        """Preserve vLLM reasoning on streaming deltas."""
+        if chunk.get("type") == "content.delta":
+            return None
+
+        token_usage = chunk.get("usage")
+        choices = chunk.get("choices", []) or chunk.get("chunk", {}).get("choices", [])
+        usage_metadata = _create_usage_metadata(token_usage, chunk.get("service_tier")) if token_usage else None
+
+        if len(choices) == 0:
+            generation_chunk = ChatGenerationChunk(message=default_chunk_class(content="", usage_metadata=usage_metadata), generation_info=base_generation_info)
+            if self.output_version == "v1":
+                generation_chunk.message.content = []
+                generation_chunk.message.response_metadata["output_version"] = "v1"
+            return generation_chunk
+
+        choice = choices[0]
+        if choice["delta"] is None:
+            return None
+
+        message_chunk = _convert_delta_to_message_chunk_with_reasoning(choice["delta"], default_chunk_class)
+        generation_info = {**base_generation_info} if base_generation_info else {}
+
+        if finish_reason := choice.get("finish_reason"):
+            generation_info["finish_reason"] = finish_reason
+            if model_name := chunk.get("model"):
+                generation_info["model_name"] = model_name
+            if system_fingerprint := chunk.get("system_fingerprint"):
+                generation_info["system_fingerprint"] = system_fingerprint
+            if service_tier := chunk.get("service_tier"):
+                generation_info["service_tier"] = service_tier
+
+        if logprobs := choice.get("logprobs"):
+            generation_info["logprobs"] = logprobs
+
+        if usage_metadata and isinstance(message_chunk, AIMessageChunk):
+            message_chunk.usage_metadata = usage_metadata
+
+        message_chunk.response_metadata["model_provider"] = "openai"
+        return ChatGenerationChunk(message=message_chunk, generation_info=generation_info or None)

backend/packages/harness/deerflow/persistence/__init__.py

@@ -0,0 +1,13 @@
+"""DeerFlow application persistence layer (SQLAlchemy 2.0 async ORM).
+
+This module manages DeerFlow's own application data -- runs metadata,
+thread ownership, cron jobs, users. It is completely separate from
+LangGraph's checkpointer, which manages graph execution state.
+
+Usage:
+    from deerflow.persistence import init_engine, close_engine, get_session_factory
+"""
+
+from deerflow.persistence.engine import close_engine, get_engine, get_session_factory, init_engine
+
+__all__ = ["close_engine", "get_engine", "get_session_factory", "init_engine"]

backend/packages/harness/deerflow/persistence/base.py

@@ -0,0 +1,40 @@
+"""SQLAlchemy declarative base with automatic to_dict support.
+
+All DeerFlow ORM models inherit from this Base. It provides a generic
+to_dict() method via SQLAlchemy's inspect() so individual models don't
+need to write their own serialization logic.
+
+LangGraph's checkpointer tables are NOT managed by this Base.
+"""
+
+from __future__ import annotations
+
+from sqlalchemy import inspect as sa_inspect
+from sqlalchemy.orm import DeclarativeBase
+
+
+class Base(DeclarativeBase):
+    """Base class for all DeerFlow ORM models.
+
+    Provides:
+    - Automatic to_dict() via SQLAlchemy column inspection.
+    - Standard __repr__() showing all column values.
+    """
+
+    def to_dict(self, *, exclude: set[str] | None = None) -> dict:
+        """Convert ORM instance to plain dict.
+
+        Uses SQLAlchemy's inspect() to iterate mapped column attributes.
+
+        Args:
+            exclude: Optional set of column keys to omit.
+
+        Returns:
+            Dict of {column_key: value} for all mapped columns.
+        """
+        exclude = exclude or set()
+        return {c.key: getattr(self, c.key) for c in sa_inspect(type(self)).mapper.column_attrs if c.key not in exclude}
+
+    def __repr__(self) -> str:
+        cols = ", ".join(f"{c.key}={getattr(self, c.key)!r}" for c in sa_inspect(type(self)).mapper.column_attrs)
+        return f"{type(self).__name__}({cols})"

backend/packages/harness/deerflow/persistence/engine.py

@@ -0,0 +1,185 @@
+"""Async SQLAlchemy engine lifecycle management.
+
+Initializes at Gateway startup, provides session factory for
+repositories, disposes at shutdown.
+
+When database.backend="memory", init_engine is a no-op and
+get_session_factory() returns None. Repositories must check for
+None and fall back to in-memory implementations.
+"""
+
+from __future__ import annotations
+
+import json
+import logging
+
+from sqlalchemy.ext.asyncio import AsyncEngine, AsyncSession, async_sessionmaker, create_async_engine
+
+
+def _json_serializer(obj: object) -> str:
+    """JSON serializer with ensure_ascii=False for Chinese character support."""
+    return json.dumps(obj, ensure_ascii=False)
+
+
+logger = logging.getLogger(__name__)
+
+_engine: AsyncEngine | None = None
+_session_factory: async_sessionmaker[AsyncSession] | None = None
+
+
+async def _auto_create_postgres_db(url: str) -> None:
+    """Connect to the ``postgres`` maintenance DB and CREATE DATABASE.
+
+    The target database name is extracted from *url*.  The connection is
+    made to the default ``postgres`` database on the same server using
+    ``AUTOCOMMIT`` isolation (CREATE DATABASE cannot run inside a
+    transaction).
+    """
+    from sqlalchemy import text
+    from sqlalchemy.engine.url import make_url
+
+    parsed = make_url(url)
+    db_name = parsed.database
+    if not db_name:
+        raise ValueError("Cannot auto-create database: no database name in URL")
+
+    # Connect to the default 'postgres' database to issue CREATE DATABASE
+    maint_url = parsed.set(database="postgres")
+    maint_engine = create_async_engine(maint_url, isolation_level="AUTOCOMMIT")
+    try:
+        async with maint_engine.connect() as conn:
+            await conn.execute(text(f'CREATE DATABASE "{db_name}"'))
+        logger.info("Auto-created PostgreSQL database: %s", db_name)
+    finally:
+        await maint_engine.dispose()
+
+
+async def init_engine(
+    backend: str,
+    *,
+    url: str = "",
+    echo: bool = False,
+    pool_size: int = 5,
+    sqlite_dir: str = "",
+) -> None:
+    """Create the async engine and session factory, then auto-create tables.
+
+    Args:
+        backend: "memory", "sqlite", or "postgres".
+        url: SQLAlchemy async URL (for sqlite/postgres).
+        echo: Echo SQL to log.
+        pool_size: Postgres connection pool size.
+        sqlite_dir: Directory to create for SQLite (ensured to exist).
+    """
+    global _engine, _session_factory
+
+    if backend == "memory":
+        logger.info("Persistence backend=memory -- ORM engine not initialized")
+        return
+
+    if backend == "postgres":
+        try:
+            import asyncpg  # noqa: F401
+        except ImportError:
+            raise ImportError("database.backend is set to 'postgres' but asyncpg is not installed.\nInstall it with:\n    uv sync --extra postgres\nOr switch to backend: sqlite in config.yaml for single-node deployment.") from None
+
+    if backend == "sqlite":
+        import os
+
+        from sqlalchemy import event
+
+        os.makedirs(sqlite_dir or ".", exist_ok=True)
+        _engine = create_async_engine(url, echo=echo, json_serializer=_json_serializer)
+
+        # Enable WAL on every new connection. SQLite PRAGMA settings are
+        # per-connection, so we wire the listener instead of running PRAGMA
+        # once at startup. WAL gives concurrent reads + writers without
+        # blocking and is the standard recommendation for any production
+        # SQLite deployment (TC-UPG-06 in AUTH_TEST_PLAN.md). The companion
+        # ``synchronous=NORMAL`` is the safe-and-fast pairing — fsync only
+        # at WAL checkpoint boundaries instead of every commit.
+        @event.listens_for(_engine.sync_engine, "connect")
+        def _enable_sqlite_wal(dbapi_conn, _record):  # noqa: ARG001 — SQLAlchemy contract
+            cursor = dbapi_conn.cursor()
+            try:
+                cursor.execute("PRAGMA journal_mode=WAL;")
+                cursor.execute("PRAGMA synchronous=NORMAL;")
+                cursor.execute("PRAGMA foreign_keys=ON;")
+            finally:
+                cursor.close()
+    elif backend == "postgres":
+        _engine = create_async_engine(
+            url,
+            echo=echo,
+            pool_size=pool_size,
+            pool_pre_ping=True,
+            json_serializer=_json_serializer,
+        )
+    else:
+        raise ValueError(f"Unknown persistence backend: {backend!r}")
+
+    _session_factory = async_sessionmaker(_engine, expire_on_commit=False)
+
+    # Auto-create tables (dev convenience). Production should use Alembic.
+    from deerflow.persistence.base import Base
+
+    # Import all models so Base.metadata discovers them.
+    # When no models exist yet (scaffolding phase), this is a no-op.
+    try:
+        import deerflow.persistence.models  # noqa: F401
+    except ImportError:
+        # Models package not yet available — tables won't be auto-created.
+        # This is expected during initial scaffolding or minimal installs.
+        logger.debug("deerflow.persistence.models not found; skipping auto-create tables")
+
+    try:
+        async with _engine.begin() as conn:
+            await conn.run_sync(Base.metadata.create_all)
+    except Exception as exc:
+        if backend == "postgres" and "does not exist" in str(exc):
+            # Database not yet created — attempt to auto-create it, then retry.
+            await _auto_create_postgres_db(url)
+            # Rebuild engine against the now-existing database
+            await _engine.dispose()
+            _engine = create_async_engine(url, echo=echo, pool_size=pool_size, pool_pre_ping=True, json_serializer=_json_serializer)
+            _session_factory = async_sessionmaker(_engine, expire_on_commit=False)
+            async with _engine.begin() as conn:
+                await conn.run_sync(Base.metadata.create_all)
+        else:
+            raise
+
+    logger.info("Persistence engine initialized: backend=%s", backend)
+
+
+async def init_engine_from_config(config) -> None:
+    """Convenience: init engine from a DatabaseConfig object."""
+    if config.backend == "memory":
+        await init_engine("memory")
+        return
+    await init_engine(
+        backend=config.backend,
+        url=config.app_sqlalchemy_url,
+        echo=config.echo_sql,
+        pool_size=config.pool_size,
+        sqlite_dir=config.sqlite_dir if config.backend == "sqlite" else "",
+    )
+
+
+def get_session_factory() -> async_sessionmaker[AsyncSession] | None:
+    """Return the async session factory, or None if backend=memory."""
+    return _session_factory
+
+
+def get_engine() -> AsyncEngine | None:
+    """Return the async engine, or None if not initialized."""
+    return _engine
+
+
+async def close_engine() -> None:
+    """Dispose the engine, release all connections."""
+    global _engine, _session_factory
+    if _engine is not None:
+        await _engine.dispose()
+        logger.info("Persistence engine closed")
+    _engine = None
+    _session_factory = None

backend/packages/harness/deerflow/persistence/feedback/__init__.py

@@ -0,0 +1,6 @@
+"""Feedback persistence — ORM and SQL repository."""
+
+from deerflow.persistence.feedback.model import FeedbackRow
+from deerflow.persistence.feedback.sql import FeedbackRepository
+
+__all__ = ["FeedbackRepository", "FeedbackRow"]

backend/packages/harness/deerflow/persistence/feedback/model.py

@@ -0,0 +1,30 @@
+"""ORM model for user feedback on runs."""
+
+from __future__ import annotations
+
+from datetime import UTC, datetime
+
+from sqlalchemy import DateTime, String, Text
+from sqlalchemy.orm import Mapped, mapped_column
+
+from deerflow.persistence.base import Base
+
+
+class FeedbackRow(Base):
+    __tablename__ = "feedback"
+
+    feedback_id: Mapped[str] = mapped_column(String(64), primary_key=True)
+    run_id: Mapped[str] = mapped_column(String(64), nullable=False, index=True)
+    thread_id: Mapped[str] = mapped_column(String(64), nullable=False, index=True)
+    owner_id: Mapped[str | None] = mapped_column(String(64), index=True)
+    message_id: Mapped[str | None] = mapped_column(String(64))
+    # message_id is an optional RunEventStore event identifier —
+    # allows feedback to target a specific message or the entire run
+
+    rating: Mapped[int] = mapped_column(nullable=False)
+    # +1 (thumbs-up) or -1 (thumbs-down)
+
+    comment: Mapped[str | None] = mapped_column(Text)
+    # Optional text feedback from the user
+
+    created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=lambda: datetime.now(UTC))

backend/packages/harness/deerflow/persistence/feedback/sql.py

@@ -0,0 +1,139 @@
+"""SQLAlchemy-backed feedback storage.
+
+Each method acquires its own short-lived session.
+"""
+
+from __future__ import annotations
+
+import uuid
+from datetime import UTC, datetime
+
+from sqlalchemy import case, func, select
+from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker
+
+from deerflow.persistence.feedback.model import FeedbackRow
+from deerflow.runtime.user_context import AUTO, _AutoSentinel, resolve_owner_id
+
+
+class FeedbackRepository:
+    def __init__(self, session_factory: async_sessionmaker[AsyncSession]) -> None:
+        self._sf = session_factory
+
+    @staticmethod
+    def _row_to_dict(row: FeedbackRow) -> dict:
+        d = row.to_dict()
+        val = d.get("created_at")
+        if isinstance(val, datetime):
+            d["created_at"] = val.isoformat()
+        return d
+
+    async def create(
+        self,
+        *,
+        run_id: str,
+        thread_id: str,
+        rating: int,
+        owner_id: str | None | _AutoSentinel = AUTO,
+        message_id: str | None = None,
+        comment: str | None = None,
+    ) -> dict:
+        """Create a feedback record. rating must be +1 or -1."""
+        if rating not in (1, -1):
+            raise ValueError(f"rating must be +1 or -1, got {rating}")
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="FeedbackRepository.create")
+        row = FeedbackRow(
+            feedback_id=str(uuid.uuid4()),
+            run_id=run_id,
+            thread_id=thread_id,
+            owner_id=resolved_owner_id,
+            message_id=message_id,
+            rating=rating,
+            comment=comment,
+            created_at=datetime.now(UTC),
+        )
+        async with self._sf() as session:
+            session.add(row)
+            await session.commit()
+            await session.refresh(row)
+            return self._row_to_dict(row)
+
+    async def get(
+        self,
+        feedback_id: str,
+        *,
+        owner_id: str | None | _AutoSentinel = AUTO,
+    ) -> dict | None:
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="FeedbackRepository.get")
+        async with self._sf() as session:
+            row = await session.get(FeedbackRow, feedback_id)
+            if row is None:
+                return None
+            if resolved_owner_id is not None and row.owner_id != resolved_owner_id:
+                return None
+            return self._row_to_dict(row)
+
+    async def list_by_run(
+        self,
+        thread_id: str,
+        run_id: str,
+        *,
+        limit: int = 100,
+        owner_id: str | None | _AutoSentinel = AUTO,
+    ) -> list[dict]:
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="FeedbackRepository.list_by_run")
+        stmt = select(FeedbackRow).where(FeedbackRow.thread_id == thread_id, FeedbackRow.run_id == run_id)
+        if resolved_owner_id is not None:
+            stmt = stmt.where(FeedbackRow.owner_id == resolved_owner_id)
+        stmt = stmt.order_by(FeedbackRow.created_at.asc()).limit(limit)
+        async with self._sf() as session:
+            result = await session.execute(stmt)
+            return [self._row_to_dict(r) for r in result.scalars()]
+
+    async def list_by_thread(
+        self,
+        thread_id: str,
+        *,
+        limit: int = 100,
+        owner_id: str | None | _AutoSentinel = AUTO,
+    ) -> list[dict]:
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="FeedbackRepository.list_by_thread")
+        stmt = select(FeedbackRow).where(FeedbackRow.thread_id == thread_id)
+        if resolved_owner_id is not None:
+            stmt = stmt.where(FeedbackRow.owner_id == resolved_owner_id)
+        stmt = stmt.order_by(FeedbackRow.created_at.asc()).limit(limit)
+        async with self._sf() as session:
+            result = await session.execute(stmt)
+            return [self._row_to_dict(r) for r in result.scalars()]
+
+    async def delete(
+        self,
+        feedback_id: str,
+        *,
+        owner_id: str | None | _AutoSentinel = AUTO,
+    ) -> bool:
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="FeedbackRepository.delete")
+        async with self._sf() as session:
+            row = await session.get(FeedbackRow, feedback_id)
+            if row is None:
+                return False
+            if resolved_owner_id is not None and row.owner_id != resolved_owner_id:
+                return False
+            await session.delete(row)
+            await session.commit()
+            return True
+
+    async def aggregate_by_run(self, thread_id: str, run_id: str) -> dict:
+        """Aggregate feedback stats for a run using database-side counting."""
+        stmt = select(
+            func.count().label("total"),
+            func.coalesce(func.sum(case((FeedbackRow.rating == 1, 1), else_=0)), 0).label("positive"),
+            func.coalesce(func.sum(case((FeedbackRow.rating == -1, 1), else_=0)), 0).label("negative"),
+        ).where(FeedbackRow.thread_id == thread_id, FeedbackRow.run_id == run_id)
+        async with self._sf() as session:
+            row = (await session.execute(stmt)).one()
+            return {
+                "run_id": run_id,
+                "total": row.total,
+                "positive": row.positive,
+                "negative": row.negative,
+            }

backend/packages/harness/deerflow/persistence/migrations/alembic.ini

@@ -0,0 +1,38 @@
+[alembic]
+script_location = %(here)s
+# Default URL for offline mode / autogenerate.
+# Runtime uses engine from DeerFlow config.
+sqlalchemy.url = sqlite+aiosqlite:///./data/app.db
+
+[loggers]
+keys = root,sqlalchemy,alembic
+
+[handlers]
+keys = console
+
+[formatters]
+keys = generic
+
+[logger_root]
+level = WARN
+handlers = console
+
+[logger_sqlalchemy]
+level = WARN
+handlers =
+qualname = sqlalchemy.engine
+
+[logger_alembic]
+level = INFO
+handlers =
+qualname = alembic
+
+[handler_console]
+class = StreamHandler
+args = (sys.stderr,)
+level = NOTSET
+formatter = generic
+
+[formatter_generic]
+format = %(levelname)-5.5s [%(name)s] %(message)s
+datefmt = %H:%M:%S

backend/packages/harness/deerflow/persistence/migrations/env.py

@@ -0,0 +1,65 @@
+"""Alembic environment for DeerFlow application tables.
+
+ONLY manages DeerFlow's tables (runs, threads_meta, cron_jobs, users).
+LangGraph's checkpointer tables are managed by LangGraph itself -- they
+have their own schema lifecycle and must not be touched by Alembic.
+"""
+
+from __future__ import annotations
+
+import asyncio
+import logging
+from logging.config import fileConfig
+
+from alembic import context
+from sqlalchemy.ext.asyncio import create_async_engine
+
+from deerflow.persistence.base import Base
+
+# Import all models so metadata is populated.
+try:
+    import deerflow.persistence.models  # noqa: F401 — register ORM models with Base.metadata
+except ImportError:
+    # Models not available — migration will work with existing metadata only.
+    logging.getLogger(__name__).warning("Could not import deerflow.persistence.models; Alembic may not detect all tables")
+
+config = context.config
+if config.config_file_name is not None:
+    fileConfig(config.config_file_name)
+
+target_metadata = Base.metadata
+
+
+def run_migrations_offline() -> None:
+    url = config.get_main_option("sqlalchemy.url")
+    context.configure(
+        url=url,
+        target_metadata=target_metadata,
+        literal_binds=True,
+        render_as_batch=True,
+    )
+    with context.begin_transaction():
+        context.run_migrations()
+
+
+def do_run_migrations(connection):
+    context.configure(
+        connection=connection,
+        target_metadata=target_metadata,
+        render_as_batch=True,  # Required for SQLite ALTER TABLE support
+    )
+    with context.begin_transaction():
+        context.run_migrations()
+
+
+async def run_migrations_online() -> None:
+    connectable = create_async_engine(config.get_main_option("sqlalchemy.url"))
+    async with connectable.connect() as connection:
+        await connection.run_sync(do_run_migrations)
+    await connectable.dispose()
+
+
+if context.is_offline_mode():
+    run_migrations_offline()
+else:
+    asyncio.run(run_migrations_online())

backend/packages/harness/deerflow/persistence/models/__init__.py

@@ -0,0 +1,23 @@
+"""ORM model registration entry point.
+
+Importing this module ensures all ORM models are registered with
+``Base.metadata`` so Alembic autogenerate detects every table.
+
+The actual ORM classes have moved to entity-specific subpackages:
+- ``deerflow.persistence.thread_meta``
+- ``deerflow.persistence.run``
+- ``deerflow.persistence.feedback``
+- ``deerflow.persistence.user``
+
+``RunEventRow`` remains in ``deerflow.persistence.models.run_event`` because
+its storage implementation lives in ``deerflow.runtime.events.store.db`` and
+there is no matching entity directory.
+"""
+
+from deerflow.persistence.feedback.model import FeedbackRow
+from deerflow.persistence.models.run_event import RunEventRow
+from deerflow.persistence.run.model import RunRow
+from deerflow.persistence.thread_meta.model import ThreadMetaRow
+from deerflow.persistence.user.model import UserRow
+
+__all__ = ["FeedbackRow", "RunEventRow", "RunRow", "ThreadMetaRow", "UserRow"]

backend/packages/harness/deerflow/persistence/models/run_event.py

@@ -0,0 +1,35 @@
+"""ORM model for run events."""
+
+from __future__ import annotations
+
+from datetime import UTC, datetime
+
+from sqlalchemy import JSON, DateTime, Index, String, Text, UniqueConstraint
+from sqlalchemy.orm import Mapped, mapped_column
+
+from deerflow.persistence.base import Base
+
+
+class RunEventRow(Base):
+    __tablename__ = "run_events"
+
+    id: Mapped[int] = mapped_column(primary_key=True, autoincrement=True)
+    thread_id: Mapped[str] = mapped_column(String(64), nullable=False)
+    run_id: Mapped[str] = mapped_column(String(64), nullable=False)
+    # Owner of the conversation this event belongs to. Nullable for data
+    # created before auth was introduced; populated by auth middleware on
+    # new writes and by the boot-time orphan migration on existing rows.
+    owner_id: Mapped[str | None] = mapped_column(String(64), nullable=True, index=True)
+    event_type: Mapped[str] = mapped_column(String(32), nullable=False)
+    category: Mapped[str] = mapped_column(String(16), nullable=False)
+    # "message" | "trace" | "lifecycle"
+    content: Mapped[str] = mapped_column(Text, default="")
+    event_metadata: Mapped[dict] = mapped_column(JSON, default=dict)
+    seq: Mapped[int] = mapped_column(nullable=False)
+    created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=lambda: datetime.now(UTC))
+
+    __table_args__ = (
+        UniqueConstraint("thread_id", "seq", name="uq_events_thread_seq"),
+        Index("ix_events_thread_cat_seq", "thread_id", "category", "seq"),
+        Index("ix_events_run", "thread_id", "run_id", "seq"),
+    )

backend/packages/harness/deerflow/persistence/run/__init__.py

@@ -0,0 +1,6 @@
+"""Run metadata persistence — ORM and SQL repository."""
+
+from deerflow.persistence.run.model import RunRow
+from deerflow.persistence.run.sql import RunRepository
+
+__all__ = ["RunRepository", "RunRow"]

backend/packages/harness/deerflow/persistence/run/model.py

@@ -0,0 +1,49 @@
+"""ORM model for run metadata."""
+
+from __future__ import annotations
+
+from datetime import UTC, datetime
+
+from sqlalchemy import JSON, DateTime, Index, String, Text
+from sqlalchemy.orm import Mapped, mapped_column
+
+from deerflow.persistence.base import Base
+
+
+class RunRow(Base):
+    __tablename__ = "runs"
+
+    run_id: Mapped[str] = mapped_column(String(64), primary_key=True)
+    thread_id: Mapped[str] = mapped_column(String(64), nullable=False, index=True)
+    assistant_id: Mapped[str | None] = mapped_column(String(128))
+    owner_id: Mapped[str | None] = mapped_column(String(64), index=True)
+    status: Mapped[str] = mapped_column(String(20), default="pending")
+    # "pending" | "running" | "success" | "error" | "timeout" | "interrupted"
+
+    model_name: Mapped[str | None] = mapped_column(String(128))
+    multitask_strategy: Mapped[str] = mapped_column(String(20), default="reject")
+    metadata_json: Mapped[dict] = mapped_column(JSON, default=dict)
+    kwargs_json: Mapped[dict] = mapped_column(JSON, default=dict)
+    error: Mapped[str | None] = mapped_column(Text)
+
+    # Convenience fields (for listing pages without querying RunEventStore)
+    message_count: Mapped[int] = mapped_column(default=0)
+    first_human_message: Mapped[str | None] = mapped_column(Text)
+    last_ai_message: Mapped[str | None] = mapped_column(Text)
+
+    # Token usage (accumulated in-memory by RunJournal, written on run completion)
+    total_input_tokens: Mapped[int] = mapped_column(default=0)
+    total_output_tokens: Mapped[int] = mapped_column(default=0)
+    total_tokens: Mapped[int] = mapped_column(default=0)
+    llm_call_count: Mapped[int] = mapped_column(default=0)
+    lead_agent_tokens: Mapped[int] = mapped_column(default=0)
+    subagent_tokens: Mapped[int] = mapped_column(default=0)
+    middleware_tokens: Mapped[int] = mapped_column(default=0)
+
+    # Follow-up association
+    follow_up_to_run_id: Mapped[str | None] = mapped_column(String(64))
+
+    created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=lambda: datetime.now(UTC))
+    updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=lambda: datetime.now(UTC), onupdate=lambda: datetime.now(UTC))
+
+    __table_args__ = (Index("ix_runs_thread_status", "thread_id", "status"),)

backend/packages/harness/deerflow/persistence/run/sql.py

@@ -0,0 +1,255 @@
+"""SQLAlchemy-backed RunStore implementation.
+
+Each method acquires and releases its own short-lived session.
+Run status updates happen from background workers that may live
+minutes -- we don't hold connections across long execution.
+"""
+
+from __future__ import annotations
+
+import json
+from datetime import UTC, datetime
+from typing import Any
+
+from sqlalchemy import func, select, update
+from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker
+
+from deerflow.persistence.run.model import RunRow
+from deerflow.runtime.runs.store.base import RunStore
+from deerflow.runtime.user_context import AUTO, _AutoSentinel, resolve_owner_id
+
+
+class RunRepository(RunStore):
+    def __init__(self, session_factory: async_sessionmaker[AsyncSession]) -> None:
+        self._sf = session_factory
+
+    @staticmethod
+    def _safe_json(obj: Any) -> Any:
+        """Ensure obj is JSON-serializable. Falls back to model_dump() or str()."""
+        if obj is None:
+            return None
+        if isinstance(obj, (str, int, float, bool)):
+            return obj
+        if isinstance(obj, dict):
+            return {k: RunRepository._safe_json(v) for k, v in obj.items()}
+        if isinstance(obj, (list, tuple)):
+            return [RunRepository._safe_json(v) for v in obj]
+        if hasattr(obj, "model_dump"):
+            try:
+                return obj.model_dump()
+            except Exception:
+                pass
+        if hasattr(obj, "dict"):
+            try:
+                return obj.dict()
+            except Exception:
+                pass
+        try:
+            json.dumps(obj)
+            return obj
+        except (TypeError, ValueError):
+            return str(obj)
+
+    @staticmethod
+    def _row_to_dict(row: RunRow) -> dict[str, Any]:
+        d = row.to_dict()
+        # Remap JSON columns to match RunStore interface
+        d["metadata"] = d.pop("metadata_json", {})
+        d["kwargs"] = d.pop("kwargs_json", {})
+        # Convert datetime to ISO string for consistency with MemoryRunStore
+        for key in ("created_at", "updated_at"):
+            val = d.get(key)
+            if isinstance(val, datetime):
+                d[key] = val.isoformat()
+        return d
+
+    async def put(
+        self,
+        run_id,
+        *,
+        thread_id,
+        assistant_id=None,
+        owner_id: str | None | _AutoSentinel = AUTO,
+        status="pending",
+        multitask_strategy="reject",
+        metadata=None,
+        kwargs=None,
+        error=None,
+        created_at=None,
+        follow_up_to_run_id=None,
+    ):
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="RunRepository.put")
+        now = datetime.now(UTC)
+        row = RunRow(
+            run_id=run_id,
+            thread_id=thread_id,
+            assistant_id=assistant_id,
+            owner_id=resolved_owner_id,
+            status=status,
+            multitask_strategy=multitask_strategy,
+            metadata_json=self._safe_json(metadata) or {},
+            kwargs_json=self._safe_json(kwargs) or {},
+            error=error,
+            follow_up_to_run_id=follow_up_to_run_id,
+            created_at=datetime.fromisoformat(created_at) if created_at else now,
+            updated_at=now,
+        )
+        async with self._sf() as session:
+            session.add(row)
+            await session.commit()
+
+    async def get(
+        self,
+        run_id,
+        *,
+        owner_id: str | None | _AutoSentinel = AUTO,
+    ):
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="RunRepository.get")
+        async with self._sf() as session:
+            row = await session.get(RunRow, run_id)
+            if row is None:
+                return None
+            if resolved_owner_id is not None and row.owner_id != resolved_owner_id:
+                return None
+            return self._row_to_dict(row)
+
+    async def list_by_thread(
+        self,
+        thread_id,
+        *,
+        owner_id: str | None | _AutoSentinel = AUTO,
+        limit=100,
+    ):
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="RunRepository.list_by_thread")
+        stmt = select(RunRow).where(RunRow.thread_id == thread_id)
+        if resolved_owner_id is not None:
+            stmt = stmt.where(RunRow.owner_id == resolved_owner_id)
+        stmt = stmt.order_by(RunRow.created_at.desc()).limit(limit)
+        async with self._sf() as session:
+            result = await session.execute(stmt)
+            return [self._row_to_dict(r) for r in result.scalars()]
+
+    async def update_status(self, run_id, status, *, error=None):
+        values: dict[str, Any] = {"status": status, "updated_at": datetime.now(UTC)}
+        if error is not None:
+            values["error"] = error
+        async with self._sf() as session:
+            await session.execute(update(RunRow).where(RunRow.run_id == run_id).values(**values))
+            await session.commit()
+
+    async def delete(
+        self,
+        run_id,
+        *,
+        owner_id: str | None | _AutoSentinel = AUTO,
+    ):
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="RunRepository.delete")
+        async with self._sf() as session:
+            row = await session.get(RunRow, run_id)
+            if row is None:
+                return
+            if resolved_owner_id is not None and row.owner_id != resolved_owner_id:
+                return
+            await session.delete(row)
+            await session.commit()
+
+    async def list_pending(self, *, before=None):
+        if before is None:
+            before_dt = datetime.now(UTC)
+        elif isinstance(before, datetime):
+            before_dt = before
+        else:
+            before_dt = datetime.fromisoformat(before)
+        stmt = select(RunRow).where(RunRow.status == "pending", RunRow.created_at <= before_dt).order_by(RunRow.created_at.asc())
+        async with self._sf() as session:
+            result = await session.execute(stmt)
+            return [self._row_to_dict(r) for r in result.scalars()]
+
+    async def update_run_completion(
+        self,
+        run_id: str,
+        *,
+        status: str,
+        total_input_tokens: int = 0,
+        total_output_tokens: int = 0,
+        total_tokens: int = 0,
+        llm_call_count: int = 0,
+        lead_agent_tokens: int = 0,
+        subagent_tokens: int = 0,
+        middleware_tokens: int = 0,
+        message_count: int = 0,
+        last_ai_message: str | None = None,
+        first_human_message: str | None = None,
+        error: str | None = None,
+    ) -> None:
+        """Update status + token usage + convenience fields on run completion."""
+        values: dict[str, Any] = {
+            "status": status,
+            "total_input_tokens": total_input_tokens,
+            "total_output_tokens": total_output_tokens,
+            "total_tokens": total_tokens,
+            "llm_call_count": llm_call_count,
+            "lead_agent_tokens": lead_agent_tokens,
+            "subagent_tokens": subagent_tokens,
+            "middleware_tokens": middleware_tokens,
+            "message_count": message_count,
+            "updated_at": datetime.now(UTC),
+        }
+        if last_ai_message is not None:
+            values["last_ai_message"] = last_ai_message[:2000]
+        if first_human_message is not None:
+            values["first_human_message"] = first_human_message[:2000]
+        if error is not None:
+            values["error"] = error
+        async with self._sf() as session:
+            await session.execute(update(RunRow).where(RunRow.run_id == run_id).values(**values))
+            await session.commit()
+
+    async def aggregate_tokens_by_thread(self, thread_id: str) -> dict[str, Any]:
+        """Aggregate token usage via a single SQL GROUP BY query."""
+        _completed = RunRow.status.in_(("success", "error"))
+        _thread = RunRow.thread_id == thread_id
+
+        stmt = (
+            select(
+                func.coalesce(RunRow.model_name, "unknown").label("model"),
+                func.count().label("runs"),
+                func.coalesce(func.sum(RunRow.total_tokens), 0).label("total_tokens"),
+                func.coalesce(func.sum(RunRow.total_input_tokens), 0).label("total_input_tokens"),
+                func.coalesce(func.sum(RunRow.total_output_tokens), 0).label("total_output_tokens"),
+                func.coalesce(func.sum(RunRow.lead_agent_tokens), 0).label("lead_agent"),
+                func.coalesce(func.sum(RunRow.subagent_tokens), 0).label("subagent"),
+                func.coalesce(func.sum(RunRow.middleware_tokens), 0).label("middleware"),
+            )
+            .where(_thread, _completed)
+            .group_by(func.coalesce(RunRow.model_name, "unknown"))
+        )
+
+        async with self._sf() as session:
+            rows = (await session.execute(stmt)).all()
+
+        total_tokens = total_input = total_output = total_runs = 0
+        lead_agent = subagent = middleware = 0
+        by_model: dict[str, dict] = {}
+        for r in rows:
+            by_model[r.model] = {"tokens": r.total_tokens, "runs": r.runs}
+            total_tokens += r.total_tokens
+            total_input += r.total_input_tokens
+            total_output += r.total_output_tokens
+            total_runs += r.runs
+            lead_agent += r.lead_agent
+            subagent += r.subagent
+            middleware += r.middleware
+
+        return {
+            "total_tokens": total_tokens,
+            "total_input_tokens": total_input,
+            "total_output_tokens": total_output,
+            "total_runs": total_runs,
+            "by_model": by_model,
+            "by_caller": {
+                "lead_agent": lead_agent,
+                "subagent": subagent,
+                "middleware": middleware,
+            },
+        }

backend/packages/harness/deerflow/persistence/thread_meta/__init__.py

@@ -0,0 +1,13 @@
+"""Thread metadata persistence — ORM, abstract store, and concrete implementations."""
+
+from deerflow.persistence.thread_meta.base import ThreadMetaStore
+from deerflow.persistence.thread_meta.memory import MemoryThreadMetaStore
+from deerflow.persistence.thread_meta.model import ThreadMetaRow
+from deerflow.persistence.thread_meta.sql import ThreadMetaRepository
+
+__all__ = [
+    "MemoryThreadMetaStore",
+    "ThreadMetaRepository",
+    "ThreadMetaRow",
+    "ThreadMetaStore",
+]

backend/packages/harness/deerflow/persistence/thread_meta/base.py

@@ -0,0 +1,60 @@
+"""Abstract interface for thread metadata storage.
+
+Implementations:
+- ThreadMetaRepository: SQL-backed (sqlite / postgres via SQLAlchemy)
+- MemoryThreadMetaStore: wraps LangGraph BaseStore (memory mode)
+"""
+
+from __future__ import annotations
+
+import abc
+
+
+class ThreadMetaStore(abc.ABC):
+    @abc.abstractmethod
+    async def create(
+        self,
+        thread_id: str,
+        *,
+        assistant_id: str | None = None,
+        owner_id: str | None = None,
+        display_name: str | None = None,
+        metadata: dict | None = None,
+    ) -> dict:
+        pass
+
+    @abc.abstractmethod
+    async def get(self, thread_id: str) -> dict | None:
+        pass
+
+    @abc.abstractmethod
+    async def search(
+        self,
+        *,
+        metadata: dict | None = None,
+        status: str | None = None,
+        limit: int = 100,
+        offset: int = 0,
+    ) -> list[dict]:
+        pass
+
+    @abc.abstractmethod
+    async def update_display_name(self, thread_id: str, display_name: str) -> None:
+        pass
+
+    @abc.abstractmethod
+    async def update_status(self, thread_id: str, status: str) -> None:
+        pass
+
+    @abc.abstractmethod
+    async def update_metadata(self, thread_id: str, metadata: dict) -> None:
+        """Merge ``metadata`` into the thread's metadata field.
+
+        Existing keys are overwritten by the new values; keys absent from
+        ``metadata`` are preserved. No-op if the thread does not exist.
+        """
+        pass
+
+    @abc.abstractmethod
+    async def delete(self, thread_id: str) -> None:
+        pass

backend/packages/harness/deerflow/persistence/thread_meta/memory.py

@@ -0,0 +1,120 @@
+"""In-memory ThreadMetaStore backed by LangGraph BaseStore.
+
+Used when database.backend=memory. Delegates to the LangGraph Store's
+``("threads",)`` namespace — the same namespace used by the Gateway
+router for thread records.
+"""
+
+from __future__ import annotations
+
+import time
+from typing import Any
+
+from langgraph.store.base import BaseStore
+
+from deerflow.persistence.thread_meta.base import ThreadMetaStore
+
+THREADS_NS: tuple[str, ...] = ("threads",)
+
+
+class MemoryThreadMetaStore(ThreadMetaStore):
+    def __init__(self, store: BaseStore) -> None:
+        self._store = store
+
+    async def create(
+        self,
+        thread_id: str,
+        *,
+        assistant_id: str | None = None,
+        owner_id: str | None = None,
+        display_name: str | None = None,
+        metadata: dict | None = None,
+    ) -> dict:
+        now = time.time()
+        record: dict[str, Any] = {
+            "thread_id": thread_id,
+            "assistant_id": assistant_id,
+            "owner_id": owner_id,
+            "display_name": display_name,
+            "status": "idle",
+            "metadata": metadata or {},
+            "values": {},
+            "created_at": now,
+            "updated_at": now,
+        }
+        await self._store.aput(THREADS_NS, thread_id, record)
+        return record
+
+    async def get(self, thread_id: str) -> dict | None:
+        item = await self._store.aget(THREADS_NS, thread_id)
+        return item.value if item is not None else None
+
+    async def search(
+        self,
+        *,
+        metadata: dict | None = None,
+        status: str | None = None,
+        limit: int = 100,
+        offset: int = 0,
+    ) -> list[dict]:
+        filter_dict: dict[str, Any] = {}
+        if metadata:
+            filter_dict.update(metadata)
+        if status:
+            filter_dict["status"] = status
+
+        items = await self._store.asearch(
+            THREADS_NS,
+            filter=filter_dict or None,
+            limit=limit,
+            offset=offset,
+        )
+        return [self._item_to_dict(item) for item in items]
+
+    async def update_display_name(self, thread_id: str, display_name: str) -> None:
+        item = await self._store.aget(THREADS_NS, thread_id)
+        if item is None:
+            return
+        record = dict(item.value)
+        record["display_name"] = display_name
+        record["updated_at"] = time.time()
+        await self._store.aput(THREADS_NS, thread_id, record)
+
+    async def update_status(self, thread_id: str, status: str) -> None:
+        item = await self._store.aget(THREADS_NS, thread_id)
+        if item is None:
+            return
+        record = dict(item.value)
+        record["status"] = status
+        record["updated_at"] = time.time()
+        await self._store.aput(THREADS_NS, thread_id, record)
+
+    async def update_metadata(self, thread_id: str, metadata: dict) -> None:
+        """Merge ``metadata`` into the in-memory record. No-op if absent."""
+        item = await self._store.aget(THREADS_NS, thread_id)
+        if item is None:
+            return
+        record = dict(item.value)
+        merged = dict(record.get("metadata") or {})
+        merged.update(metadata)
+        record["metadata"] = merged
+        record["updated_at"] = time.time()
+        await self._store.aput(THREADS_NS, thread_id, record)
+
+    async def delete(self, thread_id: str) -> None:
+        await self._store.adelete(THREADS_NS, thread_id)
+
+    @staticmethod
+    def _item_to_dict(item) -> dict[str, Any]:
+        """Convert a Store SearchItem to the dict format expected by callers."""
+        val = item.value
+        return {
+            "thread_id": item.key,
+            "assistant_id": val.get("assistant_id"),
+            "owner_id": val.get("owner_id"),
+            "display_name": val.get("display_name"),
+            "status": val.get("status", "idle"),
+            "metadata": val.get("metadata", {}),
+            "created_at": str(val.get("created_at", "")),
+            "updated_at": str(val.get("updated_at", "")),
+        }