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greatmengqi e75a2ff29a 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>
2026-04-11 11:25:38 +08:00
rayhpeng 185f5649dd feat(persistence): add unified persistence layer with event store, token tracking, and feedback (#1930)
* feat(persistence): add SQLAlchemy 2.0 async ORM scaffold

Introduce a unified database configuration (DatabaseConfig) that
controls both the LangGraph checkpointer and the DeerFlow application
persistence layer from a single `database:` config section.

New modules:
- deerflow.config.database_config — Pydantic config with memory/sqlite/postgres backends
- deerflow.persistence — async engine lifecycle, DeclarativeBase with to_dict mixin, Alembic skeleton
- deerflow.runtime.runs.store — RunStore ABC + MemoryRunStore implementation

Gateway integration initializes/tears down the persistence engine in
the existing langgraph_runtime() context manager. Legacy checkpointer
config is preserved for backward compatibility.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* feat(persistence): add RunEventStore ABC + MemoryRunEventStore

Phase 2-A prerequisite for event storage: adds the unified run event
stream interface (RunEventStore) with an in-memory implementation,
RunEventsConfig, gateway integration, and comprehensive tests (27 cases).

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* feat(persistence): add ORM models, repositories, DB/JSONL event stores, RunJournal, and API endpoints

Phase 2-B: run persistence + event storage + token tracking.

- ORM models: RunRow (with token fields), ThreadMetaRow, RunEventRow
- RunRepository implements RunStore ABC via SQLAlchemy ORM
- ThreadMetaRepository with owner access control
- DbRunEventStore with trace content truncation and cursor pagination
- JsonlRunEventStore with per-run files and seq recovery from disk
- RunJournal (BaseCallbackHandler) captures LLM/tool/lifecycle events,
  accumulates token usage by caller type, buffers and flushes to store
- RunManager now accepts optional RunStore for persistent backing
- Worker creates RunJournal, writes human_message, injects callbacks
- Gateway deps use factory functions (RunRepository when DB available)
- New endpoints: messages, run messages, run events, token-usage
- ThreadCreateRequest gains assistant_id field
- 92 tests pass (33 new), zero regressions

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* feat(persistence): add user feedback + follow-up run association

Phase 2-C: feedback and follow-up tracking.

- FeedbackRow ORM model (rating +1/-1, optional message_id, comment)
- FeedbackRepository with CRUD, list_by_run/thread, aggregate stats
- Feedback API endpoints: create, list, stats, delete
- follow_up_to_run_id in RunCreateRequest (explicit or auto-detected
  from latest successful run on the thread)
- Worker writes follow_up_to_run_id into human_message event metadata
- Gateway deps: feedback_repo factory + getter
- 17 new tests (14 FeedbackRepository + 3 follow-up association)
- 109 total tests pass, zero regressions

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* test+config: comprehensive Phase 2 test coverage + deprecate checkpointer config

- config.example.yaml: deprecate standalone checkpointer section, activate
  unified database:sqlite as default (drives both checkpointer + app data)
- New: test_thread_meta_repo.py (14 tests) — full ThreadMetaRepository coverage
  including check_access owner logic, list_by_owner pagination
- Extended test_run_repository.py (+4 tests) — completion preserves fields,
  list ordering desc, limit, owner_none returns all
- Extended test_run_journal.py (+8 tests) — on_chain_error, track_tokens=false,
  middleware no ai_message, unknown caller tokens, convenience fields,
  tool_error, non-summarization custom event
- Extended test_run_event_store.py (+7 tests) — DB batch seq continuity,
  make_run_event_store factory (memory/db/jsonl/fallback/unknown)
- Extended test_phase2b_integration.py (+4 tests) — create_or_reject persists,
  follow-up metadata, summarization in history, full DB-backed lifecycle
- Fixed DB integration test to use proper fake objects (not MagicMock)
  for JSON-serializable metadata
- 157 total Phase 2 tests pass, zero regressions

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* config: move default sqlite_dir to .deer-flow/data

Keep SQLite databases alongside other DeerFlow-managed data
(threads, memory) under the .deer-flow/ directory instead of a
top-level ./data folder.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* refactor(persistence): remove UTFJSON, use engine-level json_serializer + datetime.now()

- Replace custom UTFJSON type with standard sqlalchemy.JSON in all ORM
  models. Add json_serializer=json.dumps(ensure_ascii=False) to all
  create_async_engine calls so non-ASCII text (Chinese etc.) is stored
  as-is in both SQLite and Postgres.
- Change ORM datetime defaults from datetime.now(UTC) to datetime.now(),
  remove UTC imports.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* refactor(gateway): simplify deps.py with getter factory + inline repos

- Replace 6 identical getter functions with _require() factory.
- Inline 3 _make_*_repo() factories into langgraph_runtime(), call
  get_session_factory() once instead of 3 times.
- Add thread_meta upsert in start_run (services.py).

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* feat(docker): add UV_EXTRAS build arg for optional dependencies

Support installing optional dependency groups (e.g. postgres) at
Docker build time via UV_EXTRAS build arg:
  UV_EXTRAS=postgres docker compose build

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* refactor(journal): fix flush, token tracking, and consolidate tests

RunJournal fixes:
- _flush_sync: retain events in buffer when no event loop instead of
  dropping them; worker's finally block flushes via async flush().
- on_llm_end: add tool_calls filter and caller=="lead_agent" guard for
  ai_message events; mark message IDs for dedup with record_llm_usage.
- worker.py: persist completion data (tokens, message count) to RunStore
  in finally block.

Model factory:
- Auto-inject stream_usage=True for BaseChatOpenAI subclasses with
  custom api_base, so usage_metadata is populated in streaming responses.

Test consolidation:
- Delete test_phase2b_integration.py (redundant with existing tests).
- Move DB-backed lifecycle test into test_run_journal.py.
- Add tests for stream_usage injection in test_model_factory.py.
- Clean up executor/task_tool dead journal references.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* feat(events): widen content type to str|dict in all store backends

Allow event content to be a dict (for structured OpenAI-format messages)
in addition to plain strings. Dict values are JSON-serialized for the DB
backend and deserialized on read; memory and JSONL backends handle dicts
natively. Trace truncation now serializes dicts to JSON before measuring.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* fix(events): use metadata flag instead of heuristic for dict content detection

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* feat(converters): add LangChain-to-OpenAI message format converters

Pure functions langchain_to_openai_message, langchain_to_openai_completion,
langchain_messages_to_openai, and _infer_finish_reason for converting
LangChain BaseMessage objects to OpenAI Chat Completions format, used by
RunJournal for event storage. 15 unit tests added.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* fix(converters): handle empty list content as null, clean up test

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* feat(events): human_message content uses OpenAI user message format

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* feat(events): ai_message uses OpenAI format, add ai_tool_call message event

- ai_message content now uses {"role": "assistant", "content": "..."} format
- New ai_tool_call message event emitted when lead_agent LLM responds with tool_calls
- ai_tool_call uses langchain_to_openai_message converter for consistent format
- Both events include finish_reason in metadata ("stop" or "tool_calls")

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* feat(events): add tool_result message event with OpenAI tool message format

Cache tool_call_id from on_tool_start keyed by run_id as fallback for on_tool_end,
then emit a tool_result message event (role=tool, tool_call_id, content) after each
successful tool completion.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* feat(events): summary content uses OpenAI system message format

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* feat(events): replace llm_start/llm_end with llm_request/llm_response in OpenAI format

Add on_chat_model_start to capture structured prompt messages as llm_request events.
Replace llm_end trace events with llm_response using OpenAI Chat Completions format.
Track llm_call_index to pair request/response events.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* feat(events): add record_middleware method for middleware trace events

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* test(events): add full run sequence integration test for OpenAI content format

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* feat(events): align message events with checkpoint format and add middleware tag injection

- Message events (ai_message, ai_tool_call, tool_result, human_message) now use
  BaseMessage.model_dump() format, matching LangGraph checkpoint values.messages
- on_tool_end extracts tool_call_id/name/status from ToolMessage objects
- on_tool_error now emits tool_result message events with error status
- record_middleware uses middleware:{tag} event_type and middleware category
- Summarization custom events use middleware:summarize category
- TitleMiddleware injects middleware:title tag via get_config() inheritance
- SummarizationMiddleware model bound with middleware:summarize tag
- Worker writes human_message using HumanMessage.model_dump()

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* feat(threads): switch search endpoint to threads_meta table and sync title

- POST /api/threads/search now queries threads_meta table directly,
  removing the two-phase Store + Checkpointer scan approach
- Add ThreadMetaRepository.search() with metadata/status filters
- Add ThreadMetaRepository.update_display_name() for title sync
- Worker syncs checkpoint title to threads_meta.display_name on run completion
- Map display_name to values.title in search response for API compatibility

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* feat(threads): history endpoint reads messages from event store

- POST /api/threads/{thread_id}/history now combines two data sources:
  checkpointer for checkpoint_id, metadata, title, thread_data;
  event store for messages (complete history, not truncated by summarization)
- Strip internal LangGraph metadata keys from response
- Remove full channel_values serialization in favor of selective fields

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* fix: remove duplicate optional-dependencies header in pyproject.toml

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* fix(middleware): pass tagged config to TitleMiddleware ainvoke call

Without the config, the middleware:title tag was not injected,
causing the LLM response to be recorded as a lead_agent ai_message
in run_events.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* fix: resolve merge conflict in .env.example

Keep both DATABASE_URL (from persistence-scaffold) and WECOM
credentials (from main) after the merge.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* fix(persistence): address review feedback on PR #1851

- Fix naive datetime.now() → datetime.now(UTC) in all ORM models
- Fix seq race condition in DbRunEventStore.put() with FOR UPDATE
  and UNIQUE(thread_id, seq) constraint
- Encapsulate _store access in RunManager.update_run_completion()
- Deduplicate _store.put() logic in RunManager via _persist_to_store()
- Add update_run_completion to RunStore ABC + MemoryRunStore
- Wire follow_up_to_run_id through the full create path
- Add error recovery to RunJournal._flush_sync() lost-event scenario
- Add migration note for search_threads breaking change
- Fix test_checkpointer_none_fix mock to set database=None

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* chore: update uv.lock

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* fix(persistence): address 22 review comments from CodeQL, Copilot, and Code Quality

Bug fixes:
- Sanitize log params to prevent log injection (CodeQL)
- Reset threads_meta.status to idle/error when run completes
- Attach messages only to latest checkpoint in /history response
- Write threads_meta on POST /threads so new threads appear in search

Lint fixes:
- Remove unused imports (journal.py, migrations/env.py, test_converters.py)
- Convert lambda to named function (engine.py, Ruff E731)
- Remove unused logger definitions in repos (Ruff F841)
- Add logging to JSONL decode errors and empty except blocks
- Separate assert side-effects in tests (CodeQL)
- Remove unused local variables in tests (Ruff F841)
- Fix max_trace_content truncation to use byte length, not char length

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* style: apply ruff format to persistence and runtime files

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* Potential fix for pull request finding 'Statement has no effect'

Co-authored-by: Copilot Autofix powered by AI <223894421+github-code-quality[bot]@users.noreply.github.com>

* refactor(runtime): introduce RunContext to reduce run_agent parameter bloat

Extract checkpointer, store, event_store, run_events_config, thread_meta_repo,
and follow_up_to_run_id into a frozen RunContext dataclass. Add get_run_context()
in deps.py to build the base context from app.state singletons. start_run() uses
dataclasses.replace() to enrich per-run fields before passing ctx to run_agent.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* refactor(gateway): move sanitize_log_param to app/gateway/utils.py

Extract the log-injection sanitizer from routers/threads.py into a shared
utils module and rename to sanitize_log_param (public API). Eliminates the
reverse service → router import in services.py.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* perf: use SQL aggregation for feedback stats and thread token usage

Replace Python-side counting in FeedbackRepository.aggregate_by_run with
a single SELECT COUNT/SUM query. Add RunStore.aggregate_tokens_by_thread
abstract method with SQL GROUP BY implementation in RunRepository and
Python fallback in MemoryRunStore. Simplify the thread_token_usage
endpoint to delegate to the new method, eliminating the limit=10000
truncation risk.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* docs: annotate DbRunEventStore.put() as low-frequency path

Add docstring clarifying that put() opens a per-call transaction with
FOR UPDATE and should only be used for infrequent writes (currently
just the initial human_message event). High-throughput callers should
use put_batch() instead.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* fix(threads): fall back to Store search when ThreadMetaRepository is unavailable

When database.backend=memory (default) or no SQL session factory is
configured, search_threads now queries the LangGraph Store instead of
returning 503. Returns empty list if neither Store nor repo is available.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* refactor(persistence): introduce ThreadMetaStore ABC for backend-agnostic thread metadata

Add ThreadMetaStore abstract base class with create/get/search/update/delete
interface. ThreadMetaRepository (SQL) now inherits from it. New
MemoryThreadMetaStore wraps LangGraph BaseStore for memory-mode deployments.

deps.py now always provides a non-None thread_meta_repo, eliminating all
`if thread_meta_repo is not None` guards in services.py, worker.py, and
routers/threads.py. search_threads no longer needs a Store fallback branch.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* refactor(history): read messages from checkpointer instead of RunEventStore

The /history endpoint now reads messages directly from the
checkpointer's channel_values (the authoritative source) instead of
querying RunEventStore.list_messages(). The RunEventStore API is
preserved for other consumers.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* fix(persistence): address new Copilot review comments

- feedback.py: validate thread_id/run_id before deleting feedback
- jsonl.py: add path traversal protection with ID validation
- run_repo.py: parse `before` to datetime for PostgreSQL compat
- thread_meta_repo.py: fix pagination when metadata filter is active
- database_config.py: use resolve_path for sqlite_dir consistency

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* Implement skill self-evolution and skill_manage flow (#1874)

* chore: ignore .worktrees directory

* Add skill_manage self-evolution flow

* Fix CI regressions for skill_manage

* Address PR review feedback for skill evolution

* fix(skill-evolution): preserve history on delete

* fix(skill-evolution): tighten scanner fallbacks

* docs: add skill_manage e2e evidence screenshot

* fix(skill-manage): avoid blocking fs ops in session runtime

---------

Co-authored-by: Willem Jiang <willem.jiang@gmail.com>

* fix(config): resolve sqlite_dir relative to CWD, not Paths.base_dir

resolve_path() resolves relative to Paths.base_dir (.deer-flow),
which double-nested the path to .deer-flow/.deer-flow/data/app.db.
Use Path.resolve() (CWD-relative) instead.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* Feature/feishu receive file (#1608)

* feat(feishu): add channel file materialization hook for inbound messages

- Introduce Channel.receive_file(msg, thread_id) as a base method for file materialization; default is no-op.
- Implement FeishuChannel.receive_file to download files/images from Feishu messages, save to sandbox, and inject virtual paths into msg.text.
- Update ChannelManager to call receive_file for any channel if msg.files is present, enabling downstream model access to user-uploaded files.
- No impact on Slack/Telegram or other channels (they inherit the default no-op).

* style(backend): format code with ruff for lint compliance

- Auto-formatted packages/harness/deerflow/agents/factory.py and tests/test_create_deerflow_agent.py using `ruff format`
- Ensured both files conform to project linting standards
- Fixes CI lint check failures caused by code style issues

* fix(feishu): handle file write operation asynchronously to prevent blocking

* fix(feishu): rename GetMessageResourceRequest to _GetMessageResourceRequest and remove redundant code

* test(feishu): add tests for receive_file method and placeholder replacement

* fix(manager): remove unnecessary type casting for channel retrieval

* fix(feishu): update logging messages to reflect resource handling instead of image

* fix(feishu): sanitize filename by replacing invalid characters in file uploads

* fix(feishu): improve filename sanitization and reorder image key handling in message processing

* fix(feishu): add thread lock to prevent filename conflicts during file downloads

* fix(test): correct bad merge in test_feishu_parser.py

* chore: run ruff and apply formatting cleanup
fix(feishu): preserve rich-text attachment order and improve fallback filename handling

* fix(docker): restore gateway env vars and fix langgraph empty arg issue (#1915)

Two production docker-compose.yaml bugs prevent `make up` from working:

1. Gateway missing DEER_FLOW_CONFIG_PATH and DEER_FLOW_EXTENSIONS_CONFIG_PATH
   environment overrides. Added in fb2d99f (#1836) but accidentally reverted
   by ca2fb95 (#1847). Without them, gateway reads host paths from .env via
   env_file, causing FileNotFoundError inside the container.

2. Langgraph command fails when LANGGRAPH_ALLOW_BLOCKING is unset (default).
   Empty $${allow_blocking} inserts a bare space between flags, causing
   ' --no-reload' to be parsed as unexpected extra argument. Fix by building
   args string first and conditionally appending --allow-blocking.

Co-authored-by: cooper <cooperfu@tencent.com>

* fix(frontend): resolve invalid HTML nesting and tabnabbing vulnerabilities (#1904)

* fix(frontend): resolve invalid HTML nesting and tabnabbing vulnerabilities

Fix `<button>` inside `<a>` invalid HTML in artifact components and add
missing `noopener,noreferrer` to `window.open` calls to prevent reverse
tabnabbing.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix(frontend): address Copilot review on tabnabbing and double-tab-open

Remove redundant parent onClick on web_fetch ChainOfThoughtStep to
prevent opening two tabs on link click, and explicitly null out
window.opener after window.open() for defensive tabnabbing hardening.

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>

* refactor(persistence): organize entities into per-entity directories

Restructure the persistence layer from horizontal "models/ + repositories/"
split into vertical entity-aligned directories. Each entity (thread_meta,
run, feedback) now owns its ORM model, abstract interface (where applicable),
and concrete implementations under a single directory with an aggregating
__init__.py for one-line imports.

Layout:
  persistence/thread_meta/{base,model,sql,memory}.py
  persistence/run/{model,sql}.py
  persistence/feedback/{model,sql}.py

models/__init__.py is kept as a facade so Alembic autogenerate continues to
discover all ORM tables via Base.metadata. RunEventRow remains under
models/run_event.py because its storage implementation lives in
runtime/events/store/db.py and has no matching repository directory.

The repositories/ directory is removed entirely. All call sites in
gateway/deps.py and tests are updated to import from the new entity
packages, e.g.:

    from deerflow.persistence.thread_meta import ThreadMetaRepository
    from deerflow.persistence.run import RunRepository
    from deerflow.persistence.feedback import FeedbackRepository

Full test suite passes (1690 passed, 14 skipped).

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* fix(gateway): sync thread rename and delete through ThreadMetaStore

The POST /threads/{id}/state endpoint previously synced title changes
only to the LangGraph Store via _store_upsert. In sqlite mode the search
endpoint reads from the ThreadMetaRepository SQL table, so renames never
appeared in /threads/search until the next agent run completed (worker.py
syncs title from checkpoint to thread_meta in its finally block).

Likewise the DELETE /threads/{id} endpoint cleaned up the filesystem,
Store, and checkpointer but left the threads_meta row orphaned in sqlite,
so deleted threads kept appearing in /threads/search.

Fix both endpoints by routing through the ThreadMetaStore abstraction
which already has the correct sqlite/memory implementations wired up by
deps.py. The rename path now calls update_display_name() and the delete
path calls delete() — both work uniformly across backends.

Verified end-to-end with curl in gateway mode against sqlite backend.
Existing test suite (1690 passed) and focused router/repo tests pass.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* refactor(gateway): route all thread metadata access through ThreadMetaStore

Following the rename/delete bug fix in PR1, migrate the remaining direct
LangGraph Store reads/writes in the threads router and services to the
ThreadMetaStore abstraction so that the sqlite and memory backends behave
identically and the legacy dual-write paths can be removed.

Migrated endpoints (threads.py):
- create_thread: idempotency check + write now use thread_meta_repo.get/create
  instead of dual-writing the LangGraph Store and the SQL row.
- get_thread: reads from thread_meta_repo.get; the checkpoint-only fallback
  for legacy threads is preserved.
- patch_thread: replaced _store_get/_store_put with thread_meta_repo.update_metadata.
- delete_thread_data: dropped the legacy store.adelete; thread_meta_repo.delete
  already covers it.

Removed dead code (services.py):
- _upsert_thread_in_store — redundant with the immediately following
  thread_meta_repo.create() call.
- _sync_thread_title_after_run — worker.py's finally block already syncs
  the title via thread_meta_repo.update_display_name() after each run.

Removed dead code (threads.py):
- _store_get / _store_put / _store_upsert helpers (no remaining callers).
- THREADS_NS constant.
- get_store import (router no longer touches the LangGraph Store directly).

New abstract method:
- ThreadMetaStore.update_metadata(thread_id, metadata) merges metadata into
  the thread's metadata field. Implemented in both ThreadMetaRepository (SQL,
  read-modify-write inside one session) and MemoryThreadMetaStore. Three new
  unit tests cover merge / empty / nonexistent behaviour.

Net change: -134 lines. Full test suite: 1693 passed, 14 skipped.
Verified end-to-end with curl in gateway mode against sqlite backend
(create / patch / get / rename / search / delete).

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: Copilot Autofix powered by AI <223894421+github-code-quality[bot]@users.noreply.github.com>
Co-authored-by: DanielWalnut <45447813+hetaoBackend@users.noreply.github.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
Co-authored-by: JilongSun <965640067@qq.com>
Co-authored-by: jie <49781832+stan-fu@users.noreply.github.com>
Co-authored-by: cooper <cooperfu@tencent.com>
Co-authored-by: yangzheli <43645580+yangzheli@users.noreply.github.com>
2026-04-11 11:23:39 +08:00
681 changed files with 10120 additions and 80349 deletions
+5 -5
View File
@@ -59,7 +59,7 @@ smoke-test/
2. **Check pnpm** - Package manager 2. **Check pnpm** - Package manager
3. **Check uv** - Python package manager 3. **Check uv** - Python package manager
4. **Check nginx** - Reverse proxy 4. **Check nginx** - Reverse proxy
5. **Check required ports** - Confirm that ports 2026, 3000, and 8001 are not occupied 5. **Check required ports** - Confirm that ports 2026, 3000, 8001, and 2024 are not occupied
**Docker mode environment check** (if Docker is selected): **Docker mode environment check** (if Docker is selected):
1. **Check whether Docker is installed** - Run `docker --version` 1. **Check whether Docker is installed** - Run `docker --version`
@@ -93,17 +93,17 @@ smoke-test/
### Phase 5: Service Health Check ### Phase 5: Service Health Check
**Local mode health check**: **Local mode health check**:
1. **Check process status** - Confirm that Gateway, Frontend, and Nginx processes are all running 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 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 3. **Check API Gateway** - Verify the `http://localhost:2026/health` endpoint
4. **Check LangGraph-compatible API** - Verify the `/api/langgraph/*` route exposed by Gateway 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` 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): **Docker mode health check** (when using Docker):
1. **Check container status** - Run `docker ps` and confirm that all containers are running 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 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 3. **Check API Gateway** - Verify the `http://localhost:2026/health` endpoint
4. **Check LangGraph-compatible API** - Verify the `/api/langgraph/*` route exposed by Gateway 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` 5. **Frontend route smoke check** - Run `bash .agent/skills/smoke-test/scripts/frontend_check.sh` to verify key routes under `/workspace`
### Optional Functional Verification ### Optional Functional Verification
@@ -135,7 +135,7 @@ smoke-test/
The following warnings can appear during smoke testing and do not block a successful result: 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 - Feishu/Lark SSL errors in Gateway logs (certificate verification failure) can be ignored if that channel is not enabled
- Warnings in Gateway logs about missing methods in the custom checkpointer, such as `adelete_for_runs` or `aprune`, do not affect the core functionality - 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 ## Key Tools
+10 -8
View File
@@ -138,6 +138,7 @@ This document describes the detailed operating steps for each phase of the DeerF
lsof -i :2026 # Main port lsof -i :2026 # Main port
lsof -i :3000 # Frontend lsof -i :3000 # Frontend
lsof -i :8001 # Gateway lsof -i :8001 # Gateway
lsof -i :2024 # LangGraph
``` ```
**Success Criteria**: All ports are free, or they are occupied only by DeerFlow-related processes. **Success Criteria**: All ports are free, or they are occupied only by DeerFlow-related processes.
@@ -257,7 +258,7 @@ This document describes the detailed operating steps for each phase of the DeerF
**Steps**: **Steps**:
1. Run `make dev-daemon` (background mode) 1. Run `make dev-daemon` (background mode)
**Description**: This command starts all services (Gateway embedded runtime, Frontend, Nginx). **Description**: This command starts all services (LangGraph, Gateway, Frontend, Nginx).
**Notes**: **Notes**:
- `make dev` runs in the foreground and stops with Ctrl+C - `make dev` runs in the foreground and stops with Ctrl+C
@@ -271,6 +272,7 @@ This document describes the detailed operating steps for each phase of the DeerF
**Steps**: **Steps**:
1. Wait 90-120 seconds for all services to start completely 1. Wait 90-120 seconds for all services to start completely
2. You can monitor startup progress by checking these log files: 2. You can monitor startup progress by checking these log files:
- `logs/langgraph.log`
- `logs/gateway.log` - `logs/gateway.log`
- `logs/frontend.log` - `logs/frontend.log`
- `logs/nginx.log` - `logs/nginx.log`
@@ -314,10 +316,11 @@ This document describes the detailed operating steps for each phase of the DeerF
**Steps**: **Steps**:
1. Run the following command to check processes: 1. Run the following command to check processes:
```bash ```bash
ps aux | grep -E "(uvicorn|next|nginx)" | grep -v grep ps aux | grep -E "(langgraph|uvicorn|next|nginx)" | grep -v grep
``` ```
**Success Criteria**: Confirm that the following processes are running: **Success Criteria**: Confirm that the following processes are running:
- LangGraph (`langgraph dev`)
- Gateway (`uvicorn app.gateway.app:app`) - Gateway (`uvicorn app.gateway.app:app`)
- Frontend (`next dev` or `next start`) - Frontend (`next dev` or `next start`)
- Nginx (`nginx`) - Nginx (`nginx`)
@@ -353,11 +356,10 @@ curl http://localhost:2026/health
--- ---
#### 5.1.4 Check LangGraph-compatible API #### 5.1.4 Check LangGraph Service
**Steps**: **Steps**:
1. Visit `http://localhost:2026/api/langgraph/assistants/lead_agent` to verify Gateway's LangGraph-compatible API route is reachable. 1. Visit relevant LangGraph endpoints to verify availability
2. A `401` response is acceptable when authentication is enabled and no session cookie is provided.
--- ---
@@ -371,6 +373,7 @@ curl http://localhost:2026/health
- `deer-flow-nginx` - `deer-flow-nginx`
- `deer-flow-frontend` - `deer-flow-frontend`
- `deer-flow-gateway` - `deer-flow-gateway`
- `deer-flow-langgraph` (if not in gateway mode)
--- ---
@@ -403,11 +406,10 @@ curl http://localhost:2026/health
--- ---
#### 5.2.4 Check LangGraph-compatible API #### 5.2.4 Check LangGraph Service
**Steps**: **Steps**:
1. Visit `http://localhost:2026/api/langgraph/assistants/lead_agent` to verify Gateway's LangGraph-compatible API route is reachable. 1. Visit relevant LangGraph endpoints to verify availability
2. A `401` response is acceptable when authentication is enabled and no session cookie is provided.
--- ---
@@ -254,6 +254,7 @@ Processes exit quickly after running `make dev-daemon`.
**Solutions**: **Solutions**:
1. Check log files: 1. Check log files:
```bash ```bash
tail -f logs/langgraph.log
tail -f logs/gateway.log tail -f logs/gateway.log
tail -f logs/frontend.log tail -f logs/frontend.log
tail -f logs/nginx.log tail -f logs/nginx.log
@@ -366,7 +367,24 @@ Errors appear in `gateway.log`.
uv sync uv sync
``` ```
4. Confirm that the Gateway process is running normally. 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
--- ---
@@ -501,7 +519,7 @@ Accessing `/health` returns an error or times out.
2. Confirm that config.yaml exists and has valid formatting 2. Confirm that config.yaml exists and has valid formatting
3. Check whether Python dependencies are complete 3. Check whether Python dependencies are complete
4. Confirm that the Gateway process is running normally. 4. Confirm that the LangGraph service is running normally
**Solutions** (Docker mode): **Solutions** (Docker mode):
1. Check gateway container logs: 1. Check gateway container logs:
@@ -511,7 +529,7 @@ Accessing `/health` returns an error or times out.
2. Confirm that config.yaml is mounted correctly 2. Confirm that config.yaml is mounted correctly
3. Check whether Python dependencies are complete 3. Check whether Python dependencies are complete
4. Confirm that the Gateway process is running normally. 4. Confirm that the LangGraph service is running normally
--- ---
@@ -521,7 +539,7 @@ Accessing `/health` returns an error or times out.
#### View All Service Processes #### View All Service Processes
```bash ```bash
ps aux | grep -E "(uvicorn|next|nginx)" | grep -v grep ps aux | grep -E "(langgraph|uvicorn|next|nginx)" | grep -v grep
``` ```
#### View Service Logs #### View Service Logs
@@ -530,6 +548,7 @@ ps aux | grep -E "(uvicorn|next|nginx)" | grep -v grep
tail -f logs/*.log tail -f logs/*.log
# View specific service logs # View specific service logs
tail -f logs/langgraph.log
tail -f logs/gateway.log tail -f logs/gateway.log
tail -f logs/frontend.log tail -f logs/frontend.log
tail -f logs/nginx.log tail -f logs/nginx.log
@@ -65,7 +65,7 @@ if ! command -v lsof >/dev/null 2>&1; then
echo " Install lsof and rerun this check" echo " Install lsof and rerun this check"
all_passed=false all_passed=false
else else
for port in 2026 3000 8001; do for port in 2026 3000 8001 2024; do
if lsof -i :$port >/dev/null 2>&1; then if lsof -i :$port >/dev/null 2>&1; then
echo "⚠ Port $port is already in use:" echo "⚠ Port $port is already in use:"
lsof -i :$port | head -2 lsof -i :$port | head -2
@@ -54,6 +54,7 @@ echo "=========================================="
echo "" echo ""
echo "🌐 Access URL: http://localhost:2026" echo "🌐 Access URL: http://localhost:2026"
echo "📋 View logs:" echo "📋 View logs:"
echo " - logs/langgraph.log"
echo " - logs/gateway.log" echo " - logs/gateway.log"
echo " - logs/frontend.log" echo " - logs/frontend.log"
echo " - logs/nginx.log" echo " - logs/nginx.log"
@@ -76,11 +76,12 @@ if [ "$mode" = "docker" ]; then
all_passed=false all_passed=false
fi fi
else else
summary_hint="logs/{gateway,frontend,nginx}.log" summary_hint="logs/{langgraph,gateway,frontend,nginx}.log"
print_step "1. Checking local service ports..." print_step "1. Checking local service ports..."
check_listen_port "Nginx" 2026 check_listen_port "Nginx" 2026
check_listen_port "Frontend" 3000 check_listen_port "Frontend" 3000
check_listen_port "Gateway" 8001 check_listen_port "Gateway" 8001
check_listen_port "LangGraph" 2024
fi fi
echo "" echo ""
@@ -103,8 +104,8 @@ else
fi fi
echo "" echo ""
echo "5. Checking LangGraph-compatible Gateway API..." echo "5. Checking LangGraph service..."
check_http_status "LangGraph-compatible Gateway API" "http://localhost:2026/api/langgraph/assistants/lead_agent" "200|401" check_http_status "LangGraph service" "http://localhost:2024/" "200|301|302|307|308|404"
echo "" echo ""
echo "==========================================" echo "=========================================="
@@ -78,7 +78,7 @@
- [x] Container status - {{status_containers}} - [x] Container status - {{status_containers}}
- [x] Frontend service - {{status_frontend}} - [x] Frontend service - {{status_frontend}}
- [x] API Gateway - {{status_api_gateway}} - [x] API Gateway - {{status_api_gateway}}
- [x] LangGraph-compatible Gateway API - {{status_langgraph}} - [x] LangGraph service - {{status_langgraph}}
**Phase Status**: {{stage5_status}} **Phase Status**: {{stage5_status}}
@@ -147,6 +147,7 @@ Commit Message: {{git_commit_message}}
| deer-flow-nginx | {{nginx_status}} | {{nginx_uptime}} | | deer-flow-nginx | {{nginx_status}} | {{nginx_uptime}} |
| deer-flow-frontend | {{frontend_status}} | {{frontend_uptime}} | | deer-flow-frontend | {{frontend_status}} | {{frontend_uptime}} |
| deer-flow-gateway | {{gateway_status}} | {{gateway_uptime}} | | deer-flow-gateway | {{gateway_status}} | {{gateway_uptime}} |
| deer-flow-langgraph | {{langgraph_status}} | {{langgraph_uptime}} |
--- ---
@@ -80,7 +80,7 @@
- [x] Process status - {{status_processes}} - [x] Process status - {{status_processes}}
- [x] Frontend service - {{status_frontend}} - [x] Frontend service - {{status_frontend}}
- [x] API Gateway - {{status_api_gateway}} - [x] API Gateway - {{status_api_gateway}}
- [x] LangGraph-compatible Gateway API - {{status_langgraph}} - [x] LangGraph service - {{status_langgraph}}
**Phase Status**: {{stage5_status}} **Phase Status**: {{stage5_status}}
@@ -152,7 +152,7 @@ Commit Message: {{git_commit_message}}
| Nginx | {{nginx_status}} | {{nginx_endpoint}} | | Nginx | {{nginx_status}} | {{nginx_endpoint}} |
| Frontend | {{frontend_status}} | {{frontend_endpoint}} | | Frontend | {{frontend_status}} | {{frontend_endpoint}} |
| Gateway | {{gateway_status}} | {{gateway_endpoint}} | | Gateway | {{gateway_status}} | {{gateway_endpoint}} |
| Gateway LangGraph API | {{langgraph_status}} | {{langgraph_endpoint}} | | LangGraph | {{langgraph_status}} | {{langgraph_endpoint}} |
--- ---
@@ -166,7 +166,7 @@ Commit Message: {{git_commit_message}}
### If the Test Fails ### If the Test Fails
1. [ ] Review references/troubleshooting.md for common solutions 1. [ ] Review references/troubleshooting.md for common solutions
2. [ ] Check local logs: `logs/{gateway,frontend,nginx}.log` 2. [ ] Check local logs: `logs/{langgraph,gateway,frontend,nginx}.log`
3. [ ] Verify configuration file format and content 3. [ ] Verify configuration file format and content
4. [ ] If needed, fully reset the environment: `make stop && make clean && make install && make dev-daemon` 4. [ ] If needed, fully reset the environment: `make stop && make clean && make install && make dev-daemon`
+2 -28
View File
@@ -1,6 +1,3 @@
# Serper API Key (Google Search) - https://serper.dev
SERPER_API_KEY=your-serper-api-key
# TAVILY API Key # TAVILY API Key
TAVILY_API_KEY=your-tavily-api-key TAVILY_API_KEY=your-tavily-api-key
@@ -9,9 +6,8 @@ JINA_API_KEY=your-jina-api-key
# InfoQuest API Key # InfoQuest API Key
INFOQUEST_API_KEY=your-infoquest-api-key INFOQUEST_API_KEY=your-infoquest-api-key
# Browser CORS allowlist for split-origin or port-forwarded deployments (comma-separated exact origins). # CORS Origins (comma-separated) - e.g., http://localhost:3000,http://localhost:3001
# Leave unset when using the unified nginx endpoint, e.g. http://localhost:2026. # CORS_ORIGINS=http://localhost:3000
# GATEWAY_CORS_ORIGINS=http://localhost:3000,http://127.0.0.1:3000
# Optional: # Optional:
# FIRECRAWL_API_KEY=your-firecrawl-api-key # FIRECRAWL_API_KEY=your-firecrawl-api-key
@@ -28,7 +24,6 @@ INFOQUEST_API_KEY=your-infoquest-api-key
# SLACK_BOT_TOKEN=your-slack-bot-token # SLACK_BOT_TOKEN=your-slack-bot-token
# SLACK_APP_TOKEN=your-slack-app-token # SLACK_APP_TOKEN=your-slack-app-token
# TELEGRAM_BOT_TOKEN=your-telegram-bot-token # TELEGRAM_BOT_TOKEN=your-telegram-bot-token
# DISCORD_BOT_TOKEN=your-discord-bot-token
# Enable LangSmith to monitor and debug your LLM calls, agent runs, and tool executions. # Enable LangSmith to monitor and debug your LLM calls, agent runs, and tool executions.
# LANGSMITH_TRACING=true # LANGSMITH_TRACING=true
@@ -44,24 +39,3 @@ INFOQUEST_API_KEY=your-infoquest-api-key
# #
# WECOM_BOT_ID=your-wecom-bot-id # WECOM_BOT_ID=your-wecom-bot-id
# WECOM_BOT_SECRET=your-wecom-bot-secret # WECOM_BOT_SECRET=your-wecom-bot-secret
# DINGTALK_CLIENT_ID=your-dingtalk-client-id
# DINGTALK_CLIENT_SECRET=your-dingtalk-client-secret
# Set to "false" to disable Swagger UI, ReDoc, and OpenAPI schema in production
# GATEWAY_ENABLE_DOCS=false
# Shared internal Gateway auth token for multi-worker deployments.
# `make up` generates and persists this automatically; set it manually only
# when you run Gateway workers outside the bundled deploy script.
# DEER_FLOW_INTERNAL_AUTH_TOKEN=your-shared-internal-token
# ── Frontend SSR → Gateway wiring ─────────────────────────────────────────────
# The Next.js server uses these to reach the Gateway during SSR (auth checks,
# /api/* rewrites). They default to localhost values that match `make dev` and
# `make start`, so most local users do not need to set them.
#
# Override only when the Gateway is not on localhost:8001 (e.g. when the
# frontend and gateway run on different hosts, in containers with a service
# alias, or behind a different port). docker-compose already sets these.
# DEER_FLOW_INTERNAL_GATEWAY_BASE_URL=http://localhost:8001
# DEER_FLOW_TRUSTED_ORIGINS=http://localhost:3000,http://localhost:2026
-159
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@@ -1,159 +0,0 @@
name: 🐛 Bug report
description: Report something that isn't working so maintainers can reproduce and fix it.
title: "[bug] "
labels: ["bug"]
body:
- type: markdown
attributes:
value: |
Thanks for taking the time to file a bug. A clear, reproducible report is the
single biggest factor in how fast it gets fixed.
Please fill in every required field — especially **reproduction steps** and **logs**.
- type: checkboxes
id: preflight
attributes:
label: Before you start
options:
- label: I searched [existing issues](https://github.com/bytedance/deer-flow/issues?q=is%3Aissue) and this is not a duplicate.
required: true
- label: I can reproduce this on the latest `main`.
required: false
- type: input
id: summary
attributes:
label: Problem summary
description: One sentence describing the bug.
placeholder: e.g. make dev fails to start the gateway service
validations:
required: true
- type: dropdown
id: areas
attributes:
label: Affected area(s)
description: Which part of DeerFlow does this touch? Select all that apply.
multiple: true
options:
- Frontend (UI / Next.js)
- Backend API (gateway / endpoints / SSE)
- Agents / LangGraph (graph, prompts, langgraph.json)
- Sandbox / Docker
- Skills
- MCP
- Config / setup (make, config.yaml, env)
- Docs
- Not sure
validations:
required: true
- type: textarea
id: actual
attributes:
label: What happened?
description: The actual behavior. Include the key error lines verbatim.
placeholder: When I do X, I expected Y but I got Z.
validations:
required: true
- type: textarea
id: expected
attributes:
label: Expected behavior
placeholder: What did you expect to happen instead?
validations:
required: true
- type: textarea
id: reproduce
attributes:
label: Steps to reproduce
description: Exact commands and sequence. Minimal steps that reliably reproduce the problem.
placeholder: |
1. make check
2. make install
3. make dev
4. ...
validations:
required: true
- type: textarea
id: logs
attributes:
label: Relevant logs
description: Paste key lines from logs (for example `logs/gateway.log`, `logs/frontend.log`). Redact secrets.
render: shell
validations:
required: true
- type: dropdown
id: run_mode
attributes:
label: How are you running DeerFlow?
options:
- Local (make dev)
- Docker (make docker-start)
- CI
- Other
validations:
required: true
- type: dropdown
id: os
attributes:
label: Operating system
options:
- macOS
- Linux
- Windows
- Other
validations:
required: true
- type: input
id: platform_details
attributes:
label: Platform details
description: Architecture and shell, if relevant.
placeholder: e.g. arm64, zsh
- type: input
id: python_version
attributes:
label: Python version
placeholder: e.g. Python 3.12.9
- type: input
id: node_version
attributes:
label: Node.js version
placeholder: e.g. v22.11.0
- type: input
id: pnpm_version
attributes:
label: pnpm version
placeholder: e.g. 10.26.2
- type: input
id: uv_version
attributes:
label: uv version
placeholder: e.g. 0.7.20
- type: textarea
id: git_info
attributes:
label: Git state
description: Output of `git branch --show-current` and the latest commit SHA.
placeholder: |
branch: feature/my-branch
commit: abcdef1
- type: textarea
id: additional
attributes:
label: Additional context
description: Screenshots, related issues, config snippets (redacted), or anything else that helps triage.
-11
View File
@@ -1,11 +0,0 @@
blank_issues_enabled: false
contact_links:
- name: 💬 Questions & usage help
url: https://github.com/bytedance/deer-flow/discussions/categories/q-a
about: "How do I use X? Why does Y behave like that? Ask in Discussions — it gets answered faster and stays searchable."
- name: 💡 Ideas & proposals
url: https://github.com/bytedance/deer-flow/discussions/categories/ideas
about: Have a half-formed idea? Float it in Discussions before opening a formal feature request.
- name: 🔒 Report a security vulnerability
url: https://github.com/bytedance/deer-flow/security/policy
about: Do not open a public issue for security problems. Follow the security policy instead.
@@ -1,67 +0,0 @@
name: 💡 Feature request
description: Propose a new capability or an improvement to an existing one.
title: "[feat] "
labels: ["enhancement"]
body:
- type: markdown
attributes:
value: |
Thanks for the suggestion. For non-trivial features, please open a
[Discussion](https://github.com/bytedance/deer-flow/discussions/categories/ideas)
first to align on scope before writing code.
- type: checkboxes
id: preflight
attributes:
label: Before you start
options:
- label: I searched [existing issues](https://github.com/bytedance/deer-flow/issues?q=is%3Aissue) and this is not a duplicate.
required: true
- type: textarea
id: problem
attributes:
label: Problem / motivation
description: What problem does this solve? What is painful today, or what does it unblock?
placeholder: "I'm always frustrated when ..."
validations:
required: true
- type: textarea
id: solution
attributes:
label: Proposed solution
description: Describe the change from a user's / caller's perspective.
validations:
required: true
- type: dropdown
id: areas
attributes:
label: Affected area(s)
description: Which part of DeerFlow would this touch? Select all that apply.
multiple: true
options:
- Frontend (UI / Next.js)
- Backend API (gateway / endpoints / SSE)
- Agents / LangGraph (graph, prompts, langgraph.json)
- Sandbox / Docker
- Skills
- MCP
- Config / setup
- Docs
- Not sure
validations:
required: true
- type: textarea
id: alternatives
attributes:
label: Alternatives considered
description: Other approaches you weighed and why you discarded them.
- type: textarea
id: additional
attributes:
label: Additional context
description: Mockups, links, related issues, or anything else that helps.
@@ -0,0 +1,128 @@
name: Runtime Information
description: Report runtime/environment details to help reproduce an issue.
title: "[runtime] "
labels:
- needs-triage
body:
- type: markdown
attributes:
value: |
Thanks for sharing runtime details.
Complete this form so maintainers can quickly reproduce and diagnose the problem.
- type: input
id: summary
attributes:
label: Problem summary
description: Short summary of the issue.
placeholder: e.g. make dev fails to start gateway service
validations:
required: true
- type: textarea
id: expected
attributes:
label: Expected behavior
placeholder: What did you expect to happen?
validations:
required: true
- type: textarea
id: actual
attributes:
label: Actual behavior
placeholder: What happened instead? Include key error lines.
validations:
required: true
- type: dropdown
id: os
attributes:
label: Operating system
options:
- macOS
- Linux
- Windows
- Other
validations:
required: true
- type: input
id: platform_details
attributes:
label: Platform details
description: Add architecture and shell if relevant.
placeholder: e.g. arm64, zsh
- type: input
id: python_version
attributes:
label: Python version
placeholder: e.g. Python 3.12.9
- type: input
id: node_version
attributes:
label: Node.js version
placeholder: e.g. v23.11.0
- type: input
id: pnpm_version
attributes:
label: pnpm version
placeholder: e.g. 10.26.2
- type: input
id: uv_version
attributes:
label: uv version
placeholder: e.g. 0.7.20
- type: dropdown
id: run_mode
attributes:
label: How are you running DeerFlow?
options:
- Local (make dev)
- Docker (make docker-dev)
- CI
- Other
validations:
required: true
- type: textarea
id: reproduce
attributes:
label: Reproduction steps
description: Provide exact commands and sequence.
placeholder: |
1. make check
2. make install
3. make dev
4. ...
validations:
required: true
- type: textarea
id: logs
attributes:
label: Relevant logs
description: Paste key lines from logs (for example logs/gateway.log, logs/frontend.log).
render: shell
validations:
required: true
- type: textarea
id: git_info
attributes:
label: Git state
description: Share output of git branch and latest commit SHA.
placeholder: |
branch: feature/my-branch
commit: abcdef1
- type: textarea
id: additional
attributes:
label: Additional context
description: Add anything else that might help triage.
-72
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@@ -1,72 +0,0 @@
# Path-based PR auto-labeling config for actions/labeler@v5.
# Each key is a label (must exist — see .github/labels.yml); the globs decide
# when it is applied. A PR can match several areas, which is expected.
"area:frontend":
- changed-files:
- any-glob-to-any-file:
- "frontend/**"
"area:backend":
- changed-files:
- any-glob-to-any-file:
- "backend/app/**"
- "backend/packages/harness/deerflow/runtime/**"
- "backend/packages/harness/deerflow/persistence/**"
- "backend/packages/harness/deerflow/config/**"
- "backend/packages/harness/deerflow/tools/**"
- "backend/packages/harness/deerflow/guardrails/**"
- "backend/packages/harness/deerflow/tracing/**"
- "backend/packages/harness/deerflow/models/**"
- "backend/packages/harness/deerflow/utils/**"
- "backend/packages/harness/deerflow/uploads/**"
"area:agents":
- changed-files:
- any-glob-to-any-file:
- "backend/packages/harness/deerflow/agents/**"
- "backend/packages/harness/deerflow/subagents/**"
- "backend/packages/harness/deerflow/reflection/**"
- "backend/langgraph.json"
- "backend/**/prompts/**"
"area:sandbox":
- changed-files:
- any-glob-to-any-file:
- "docker/**"
- "backend/packages/harness/deerflow/sandbox/**"
- "backend/Dockerfile"
- "frontend/Dockerfile"
"area:skills":
- changed-files:
- any-glob-to-any-file:
- "skills/**"
- "backend/packages/harness/deerflow/skills/**"
- "frontend/src/core/skills/**"
"area:mcp":
- changed-files:
- any-glob-to-any-file:
- "backend/packages/harness/deerflow/mcp/**"
- "frontend/src/core/mcp/**"
"area:ci":
- changed-files:
- any-glob-to-any-file:
- ".github/**"
- "scripts/**"
"area:docs":
- changed-files:
- any-glob-to-any-file:
- "docs/**"
- "**/*.md"
"area:deps":
- changed-files:
- any-glob-to-any-file:
- "backend/pyproject.toml"
- "backend/uv.lock"
- "frontend/package.json"
- "frontend/pnpm-lock.yaml"
-119
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@@ -1,119 +0,0 @@
# Declarative label source of truth for DeerFlow.
#
# This file is the single source of truth for repository labels used by the
# auto-labeling workflows (.github/workflows/pr-labeler.yml, pr-triage.yml,
# issue-triage.yml). Auto-labelers can only apply labels that already exist,
# so every label referenced by a workflow MUST be declared here.
#
# Apply with: uv run --with pyyaml python scripts/sync_labels.py [--repo OWNER/NAME]
# CI keeps it in sync via .github/workflows/label-sync.yml (runs on changes here).
#
# Sync is additive/update-only: it creates or updates the labels listed below
# and never deletes labels that are not listed.
#
# Color = 6-digit hex without the leading '#'.
labels:
# ── Type ─────────────────────────────────────────────────────────────────
# Mostly GitHub defaults; declared here so colors/descriptions stay stable
# and so issue templates can rely on them existing.
- name: bug
color: d73a4a
description: Something isn't working
- name: enhancement
color: a2eeef
description: New feature or request
- name: documentation
color: 0075ca
description: Improvements or additions to documentation
- name: question
color: d876e3
description: Further information is requested
# ── Area (auto, by changed paths — see .github/labeler.yml) ───────────────
# Mirrors the "Surface area" section of the pull request template.
- name: "area:frontend"
color: c5def5
description: Next.js frontend under frontend/
- name: "area:backend"
color: c5def5
description: Gateway / runtime / core backend under backend/
- name: "area:agents"
color: c5def5
description: Agents, subagents, graph wiring, prompts, langgraph.json
- name: "area:sandbox"
color: c5def5
description: Sandboxed execution and docker/
- name: "area:skills"
color: c5def5
description: Skills under skills/ or the skills harness
- name: "area:mcp"
color: c5def5
description: Model Context Protocol integration
- name: "area:ci"
color: c5def5
description: GitHub Actions, CI config, repo tooling
- name: "area:docs"
color: c5def5
description: Documentation and Markdown only
- name: "area:deps"
color: c5def5
description: Dependency manifests / lockfiles
# ── Size (auto, by additions + deletions — see pr-triage.yml) ─────────────
- name: "size/XS"
color: "009900"
description: PR changes < 20 lines
- name: "size/S"
color: 77bb00
description: PR changes 20-100 lines
- name: "size/M"
color: eebb00
description: PR changes 100-300 lines
- name: "size/L"
color: ee9900
description: PR changes 300-700 lines
- name: "size/XL"
color: ee5500
description: PR changes 700+ lines
# ── Risk (auto, by changed paths — see pr-triage.yml) ─────────────────────
- name: "risk:low"
color: 0e8a16
description: "Low risk: docs / i18n / assets only"
- name: "risk:medium"
color: fbca04
description: "Medium risk: regular code changes"
- name: "risk:high"
color: b60205
description: "High risk: backend API, agents, sandbox, auth, deps, CI"
# ── Priority (manual) ─────────────────────────────────────────────────────
- name: P0
color: b60205
description: Critical priority
- name: P1
color: d93f0b
description: Major priority
- name: P2
color: e99695
description: Normal priority
# ── Status (auto + manual) ────────────────────────────────────────────────
- name: needs-triage
color: fef2c0
description: Awaiting maintainer triage
- name: needs-validation
color: d4c5f9
description: Touches front/back contract surface; needs real-path validation
- name: skip-validation
color: cccccc
description: "Maintainer override: do not auto-add needs-validation on this PR"
- name: reviewing
color: 5319e7
description: A maintainer is reviewing this PR
# ── Contributor ───────────────────────────────────────────────────────────
- name: first-time-contributor
color: c2e0c6
description: First contribution to this repository — be welcoming
-75
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@@ -1,75 +0,0 @@
<!-- Reference a related issue with #123. Use Fixes / Closes / Resolves to
auto-close it on merge. Delete this line if the PR doesn't reference an issue. -->
Fixes #
## Why
<!-- Why are you opening this PR? Cover two things:
- The trigger — what made you write this? A bug you hit, a feature you need,
tech debt, or a prod issue?
- The pain being addressed — user-facing problem, or what it unblocks.
For non-trivial features, please open an issue/discussion first to align on
scope before writing code. -->
## What changed
<!-- Describe the change from a user's / caller's perspective, not as a code diff. e.g.:
- "Settings now has a 'Custom endpoint' field, off by default"
- "Backend /api/chat gains a `stream` flag, defaults to false"
- "Default model changed from X to Y — existing users notice on first run" -->
## Surface area
<!-- Check every box that applies. Reviewers use this to scope the review. -->
- [ ] **Frontend UI** — page / component / setting / interaction under `frontend/`
- [ ] **Backend API** — endpoint / SSE event / request-response shape under `backend/app`
- [ ] **Agents / LangGraph** — agent node, graph wiring, `langgraph.json`, or prompt change
- [ ] **Sandbox**`docker/` or sandboxed execution
- [ ] **Skills** — change under `skills/`
- [ ] **Dependencies** — new/upgraded entry in `backend/pyproject.toml` or `frontend/package.json` (say what it buys us)
- [ ] **Default behavior change** — changes existing behavior without the user opting in (default model, default setting, data shape)
- [ ] **Docs / tests / CI only** — no runtime behavior change
## Screenshots / Recording
<!-- If you checked "Frontend UI", attach screenshots showing the entry point —
where users discover the change — not just the feature in isolation.
Before/after is best for behavior changes. Short GIFs welcome. -->
## Bug fix verification
<!-- Skip (delete) this section if this PR is not a bug fix.
Bugs should be encoded as a failing test that goes red before the fix.
Confirm:
- Test path that reproduces the bug:
- Did it go red on `main` and green on this branch? (yes / no)
- If a red test wasn't cheap to write, explain why and what you did instead. -->
## Validation
<!-- What you actually ran. Run at least the checks for the area you changed:
Backend: cd backend && make lint && make test
Frontend: cd frontend && pnpm format && pnpm lint && pnpm typecheck && BETTER_AUTH_SECRET=local-dev-secret pnpm build && make test
Frontend E2E (if you touched frontend/): cd frontend && make test-e2e -->
## AI assistance
<!-- DeerFlow is an AI project — most PRs here use AI coding tools, and that's
welcome. Disclosing it just helps reviewers calibrate how closely to read the
diff. Please fill all three; don't delete the section. -->
**Tool(s) used:** <!-- e.g. Claude Code, Cursor, GitHub Copilot, Codex, Windsurf, or "none" -->
**How you used it:** <!-- e.g. "generated the module from a spec", "autocomplete only",
"AI wrote tests, I wrote the impl". A prompt or conversation link is great too. -->
- [ ] I've read and understand every line of this change and take responsibility for it — it's not unreviewed AI output.
@@ -1,46 +0,0 @@
name: Backend Blocking IO
on:
push:
branches: ["main"]
paths:
- "backend/**"
- ".github/workflows/backend-blocking-io-tests.yml"
pull_request:
types: [opened, synchronize, reopened, ready_for_review]
paths:
- "backend/**"
- ".github/workflows/backend-blocking-io-tests.yml"
concurrency:
group: blocking-io-${{ github.event.pull_request.number || github.ref }}
cancel-in-progress: true
permissions:
contents: read
jobs:
backend-blocking-io:
if: github.event_name != 'pull_request' || github.event.pull_request.draft == false
runs-on: ubuntu-latest
timeout-minutes: 10
steps:
- name: Checkout
uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.12"
- name: Install uv
uses: astral-sh/setup-uv@v3
- name: Install backend dependencies
working-directory: backend
run: uv sync --group dev
- name: Run blocking IO regression tests
working-directory: backend
run: make test-blocking-io
-101
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@@ -1,101 +0,0 @@
name: Publish Containers
on:
push:
tags:
- "v*"
jobs:
backend-container:
runs-on: ubuntu-latest
permissions:
contents: read
packages: write
attestations: write
id-token: write
env:
REGISTRY: ghcr.io
IMAGE_NAME: ${{ github.repository }}-backend
steps:
- name: Checkout repository
uses: actions/checkout@v6
- name: Log in to the Container registry
uses: docker/login-action@74a5d142397b4f367a81961eba4e8cd7edddf772 #v3.4.0
with:
registry: ${{ env.REGISTRY }}
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Extract metadata (tags, labels) for Docker
id: meta
uses: docker/metadata-action@902fa8ec7d6ecbf8d84d538b9b233a880e428804 #v5.7.0
with:
images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
tags: |
type=ref,event=tag
type=ref,event=branch
type=sha
type=raw,value=latest,enable={{is_default_branch}}
- name: Build and push Docker image
id: push
uses: docker/build-push-action@263435318d21b8e681c14492fe198d362a7d2c83 #v6.18.0
with:
context: .
file: backend/Dockerfile
push: true
tags: ${{ steps.meta.outputs.tags }}
labels: ${{ steps.meta.outputs.labels }}
- name: Generate artifact attestation
uses: actions/attest-build-provenance@v2
with:
subject-name: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME}}
subject-digest: ${{ steps.push.outputs.digest }}
push-to-registry: true
frontend-container:
runs-on: ubuntu-latest
permissions:
contents: read
packages: write
attestations: write
id-token: write
env:
REGISTRY: ghcr.io
IMAGE_NAME: ${{ github.repository }}-frontend
steps:
- name: Checkout repository
uses: actions/checkout@v6
- name: Log in to the Container registry
uses: docker/login-action@74a5d142397b4f367a81961eba4e8cd7edddf772 #v3.4.0
with:
registry: ${{ env.REGISTRY }}
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Extract metadata (tags, labels) for Docker
id: meta
uses: docker/metadata-action@902fa8ec7d6ecbf8d84d538b9b233a880e428804 #v5.7.0
with:
images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
tags: |
type=ref,event=tag
type=ref,event=branch
type=sha
type=raw,value=latest,enable={{is_default_branch}}
- name: Build and push Docker image
id: push
uses: docker/build-push-action@263435318d21b8e681c14492fe198d362a7d2c83 #v6.18.0
with:
context: .
file: frontend/Dockerfile
push: true
tags: ${{ steps.meta.outputs.tags }}
labels: ${{ steps.meta.outputs.labels }}
- name: Generate artifact attestation
uses: actions/attest-build-provenance@v2
with:
subject-name: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME}}
subject-digest: ${{ steps.push.outputs.digest }}
push-to-registry: true
-63
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@@ -1,63 +0,0 @@
name: E2E Tests
on:
push:
branches: [ 'main' ]
paths:
- 'frontend/**'
- '.github/workflows/e2e-tests.yml'
pull_request:
types: [opened, synchronize, reopened, ready_for_review]
paths:
- 'frontend/**'
- '.github/workflows/e2e-tests.yml'
concurrency:
group: e2e-tests-${{ github.event.pull_request.number || github.ref }}
cancel-in-progress: true
permissions:
contents: read
jobs:
e2e-tests:
if: ${{ github.event_name != 'pull_request' || github.event.pull_request.draft == false }}
runs-on: ubuntu-latest
timeout-minutes: 15
steps:
- name: Checkout
uses: actions/checkout@v6
- name: Setup Node.js
uses: actions/setup-node@v4
with:
node-version: '22'
- name: Enable Corepack
run: corepack enable
- name: Use pinned pnpm version
run: corepack prepare pnpm@10.26.2 --activate
- name: Install frontend dependencies
working-directory: frontend
run: pnpm install --frozen-lockfile
- name: Install Playwright Chromium
working-directory: frontend
run: npx playwright install chromium --with-deps
- name: Run E2E tests
working-directory: frontend
run: pnpm exec playwright test
env:
SKIP_ENV_VALIDATION: '1'
- name: Upload Playwright report
uses: actions/upload-artifact@v4
if: ${{ !cancelled() }}
with:
name: playwright-report
path: frontend/playwright-report/
retention-days: 7
-43
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@@ -1,43 +0,0 @@
name: Frontend Unit Tests
on:
push:
branches: [ 'main' ]
pull_request:
types: [opened, synchronize, reopened, ready_for_review]
concurrency:
group: frontend-unit-tests-${{ github.event.pull_request.number || github.ref }}
cancel-in-progress: true
permissions:
contents: read
jobs:
frontend-unit-tests:
if: github.event.pull_request.draft == false
runs-on: ubuntu-latest
timeout-minutes: 15
steps:
- name: Checkout
uses: actions/checkout@v6
- name: Setup Node.js
uses: actions/setup-node@v4
with:
node-version: '22'
- name: Enable Corepack
run: corepack enable
- name: Use pinned pnpm version
run: corepack prepare pnpm@10.26.2 --activate
- name: Install frontend dependencies
working-directory: frontend
run: pnpm install --frozen-lockfile
- name: Run unit tests of frontend
working-directory: frontend
run: make test
-44
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@@ -1,44 +0,0 @@
name: Issue Triage
# Ensures every newly opened issue carries `needs-triage`, even blank or
# API-created ones that bypass the issue templates. Creates the label if it is
# somehow missing, so the workflow is self-healing.
on:
issues:
types: [opened]
permissions:
issues: write
jobs:
needs-triage:
runs-on: ubuntu-latest
steps:
- name: Add needs-triage label
uses: actions/github-script@v7
with:
script: |
const { owner, repo } = context.repo;
const issue_number = context.payload.issue.number;
const current = (context.payload.issue.labels || []).map(l => l.name);
if (current.includes('needs-triage')) {
core.info('Issue already has needs-triage; nothing to do.');
return;
}
// Self-heal: create the label if it does not exist yet.
try {
await github.rest.issues.createLabel({
owner, repo, name: 'needs-triage', color: 'fef2c0',
description: 'Awaiting maintainer triage',
});
} catch (e) {
if (e.status !== 422) throw e; // 422 = already exists
}
await github.rest.issues.addLabels({
owner, repo, issue_number, labels: ['needs-triage'],
});
core.info(`Added needs-triage to #${issue_number}.`);
-38
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@@ -1,38 +0,0 @@
name: Label Sync
# Keeps repository labels in sync with the declarative source of truth
# (.github/labels.yml). Runs whenever that file changes on main, and can be
# triggered manually. Additive/update-only — never deletes labels.
on:
push:
branches: [main]
paths:
- ".github/labels.yml"
- "scripts/sync_labels.py"
- ".github/workflows/label-sync.yml"
workflow_dispatch:
permissions:
contents: read
issues: write
concurrency:
group: label-sync
cancel-in-progress: false
jobs:
sync:
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v6
- name: Install uv
uses: astral-sh/setup-uv@v7
- name: Sync labels
run: uv run --with pyyaml python scripts/sync_labels.py
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
GH_REPO: ${{ github.repository }}
-28
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@@ -1,28 +0,0 @@
name: PR Labeler
# Applies area:* labels based on which files a PR changes (see .github/labeler.yml).
# Uses pull_request_target so it also works on fork PRs. SAFE: actions/labeler
# only reads the changed-file list via the API — it never checks out or runs PR code.
on:
pull_request_target:
types: [opened, synchronize, reopened, ready_for_review]
permissions:
contents: read
pull-requests: write
concurrency:
group: pr-labeler-${{ github.event.pull_request.number }}
cancel-in-progress: true
jobs:
label:
if: github.event.pull_request.draft == false
runs-on: ubuntu-latest
steps:
- name: Apply area labels
uses: actions/labeler@v5
with:
configuration-path: .github/labeler.yml
sync-labels: true
-164
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@@ -1,164 +0,0 @@
name: PR Triage
# Two responsibilities, both pure-metadata (no PR code is checked out or run):
# 1. On open/sync: apply size/* + risk:* labels, and needs-validation when the
# PR touches the front/back contract surface (backend API, SSE, agents, or
# the frontend streaming client). A `skip-validation` label opts out.
# 2. On maintainer review: apply the `reviewing` label.
#
# All labels are managed within their own namespace — labels outside size/*,
# risk:*, needs-validation and reviewing are never touched here.
on:
pull_request_target:
types: [opened, synchronize, reopened, ready_for_review]
pull_request_review:
types: [submitted]
permissions:
contents: read
pull-requests: write
concurrency:
group: pr-triage-${{ github.event.pull_request.number }}
cancel-in-progress: false
jobs:
size-and-risk:
if: github.event_name == 'pull_request_target' && github.event.pull_request.draft == false
runs-on: ubuntu-latest
steps:
- name: Label size, risk and validation need
uses: actions/github-script@v7
with:
script: |
const pr = context.payload.pull_request;
const { owner, repo } = context.repo;
const prNumber = pr.number;
// ---- size, from additions + deletions ----
const churn = (pr.additions || 0) + (pr.deletions || 0);
const sizeLabel =
churn < 20 ? 'size/XS' :
churn < 100 ? 'size/S' :
churn < 300 ? 'size/M' :
churn < 700 ? 'size/L' : 'size/XL';
// ---- changed paths ----
const files = await github.paginate(github.rest.pulls.listFiles, {
owner, repo, pull_number: prNumber, per_page: 100,
});
const paths = files.map(f => f.filename);
const matches = (re) => paths.some(p => re.test(p));
const docsOnly = paths.length > 0 && paths.every(p =>
/\.(md|mdx|txt)$/i.test(p) || p.startsWith('docs/') ||
/\.(png|jpe?g|gif|svg|webp|ico)$/i.test(p));
const highRisk = matches(
/^backend\/app\/gateway\//) || matches(
/^backend\/packages\/harness\/deerflow\/(agents|subagents|sandbox)\//) || matches(
/(^|\/)langgraph\.json$/) || matches(
/(^|\/)(auth|authz|security)/i) || matches(
/(pyproject\.toml|uv\.lock|package\.json|pnpm-lock\.yaml)$/) || matches(
/^docker\//) || matches(
/^\.github\/workflows\//);
const riskLabel = docsOnly ? 'risk:low' : (highRisk ? 'risk:high' : 'risk:medium');
// needs-validation: front/back contract surface
const contractSurface =
matches(/^backend\/app\/gateway\//) ||
matches(/^backend\/packages\/harness\/deerflow\/(agents|subagents)\//) ||
matches(/(^|\/)langgraph\.json$/) ||
matches(/^frontend\/src\/core\/(api|threads|messages)\//);
const current = (pr.labels || []).map(l => l.name);
const hasSkip = current.includes('skip-validation');
const desired = [sizeLabel, riskLabel];
if (contractSurface && !hasSkip) desired.push('needs-validation');
const managed = (name) =>
name.startsWith('size/') || name.startsWith('risk:') || name === 'needs-validation';
const toRemove = current.filter(l => managed(l) && !desired.includes(l));
const toAdd = desired.filter(l => !current.includes(l));
for (const name of toRemove) {
try {
await github.rest.issues.removeLabel({ owner, repo, issue_number: prNumber, name });
} catch (e) {
if (e.status !== 404) throw e;
}
}
if (toAdd.length) {
await github.rest.issues.addLabels({ owner, repo, issue_number: prNumber, labels: toAdd });
}
core.info(`size=${sizeLabel} risk=${riskLabel} churn=${churn} ` +
`validation=${desired.includes('needs-validation')} ` +
`(+${toAdd.join(',') || '-'} / -${toRemove.join(',') || '-'})`);
first-time:
if: github.event_name == 'pull_request_target' && github.event.action == 'opened'
runs-on: ubuntu-latest
steps:
- name: Label first-time contributors
uses: actions/github-script@v7
with:
script: |
const pr = context.payload.pull_request;
const { owner, repo } = context.repo;
const assoc = pr.author_association;
const isBot = pr.user.type === 'Bot';
core.info(`author=${pr.user.login} association=${assoc} bot=${isBot}`);
// FIRST_TIME_CONTRIBUTOR = no prior merged commit to this repo;
// FIRST_TIMER = no prior commit anywhere on GitHub. Either counts.
if (isBot || !['FIRST_TIME_CONTRIBUTOR', 'FIRST_TIMER'].includes(assoc)) {
core.info('Not a first-time contributor; skipping.');
return;
}
await github.rest.issues.addLabels({
owner, repo, issue_number: pr.number, labels: ['first-time-contributor'],
});
core.info(`Added first-time-contributor to #${pr.number}.`);
reviewing:
if: github.event_name == 'pull_request_review'
runs-on: ubuntu-latest
steps:
- name: Add reviewing label for maintainer reviews
uses: actions/github-script@v7
with:
script: |
const { owner, repo } = context.repo;
const prNumber = context.payload.pull_request.number;
const reviewer = context.payload.review.user.login;
const { data: perm } = await github.rest.repos.getCollaboratorPermissionLevel({
owner, repo, username: reviewer,
});
if (!['admin', 'write', 'maintain'].includes(perm.permission)) {
core.info(`Reviewer ${reviewer} (${perm.permission}) is not a maintainer; skipping.`);
return;
}
const { data: labels } = await github.rest.issues.listLabelsOnIssue({
owner, repo, issue_number: prNumber,
});
if (labels.some(l => l.name === 'reviewing')) {
core.info('Already labeled reviewing; skipping.');
return;
}
try {
await github.rest.issues.addLabels({
owner, repo, issue_number: prNumber, labels: ['reviewing'],
});
core.info(`Added "reviewing" (reviewer ${reviewer}).`);
} catch (e) {
// 403 is expected for review events on some fork PR contexts.
if (e.status === 403) core.info('No permission to label (expected on some fork PRs).');
else throw e;
}
-3
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@@ -40,7 +40,6 @@ coverage/
skills/custom/* skills/custom/*
logs/ logs/
log/ log/
debug.log
# Local git hooks (keep only on this machine, do not push) # Local git hooks (keep only on this machine, do not push)
.githooks/ .githooks/
@@ -56,7 +55,5 @@ web/
backend/Dockerfile.langgraph backend/Dockerfile.langgraph
config.yaml.bak config.yaml.bak
.playwright-mcp .playwright-mcp
/frontend/test-results/
/frontend/playwright-report/
.gstack/ .gstack/
.worktrees .worktrees
-33
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@@ -1,33 +0,0 @@
repos:
# Backend: ruff lint + format via uv (uses the same ruff version as backend deps)
- repo: local
hooks:
- id: ruff
name: ruff lint
entry: bash -c 'cd backend && uv run ruff check --fix "${@/#backend\//}"' --
language: system
types_or: [python]
files: ^backend/
- id: ruff-format
name: ruff format
entry: bash -c 'cd backend && uv run ruff format "${@/#backend\//}"' --
language: system
types_or: [python]
files: ^backend/
# Frontend: eslint + prettier (must run from frontend/ for node_modules resolution)
- repo: local
hooks:
- id: frontend-eslint
name: eslint (frontend)
entry: bash -c 'cd frontend && npx eslint --fix "${@/#frontend\//}"' --
language: system
types_or: [javascript, tsx, ts]
files: ^frontend/
- id: frontend-prettier
name: prettier (frontend)
entry: bash -c 'cd frontend && npx prettier --write "${@/#frontend\//}"' --
language: system
files: ^frontend/
types_or: [javascript, tsx, ts, json, css]
+26 -40
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@@ -46,12 +46,12 @@ Docker provides a consistent, isolated environment with all dependencies pre-con
All services will start with hot-reload enabled: All services will start with hot-reload enabled:
- Frontend changes are automatically reloaded - Frontend changes are automatically reloaded
- Backend changes trigger automatic restart - Backend changes trigger automatic restart
- Gateway-hosted LangGraph-compatible runtime supports hot-reload - LangGraph server supports hot-reload
4. **Access the application**: 4. **Access the application**:
- Web Interface: http://localhost:2026 - Web Interface: http://localhost:2026
- API Gateway: http://localhost:2026/api/* - API Gateway: http://localhost:2026/api/*
- LangGraph-compatible API: http://localhost:2026/api/langgraph/* - LangGraph: http://localhost:2026/api/langgraph/*
#### Docker Commands #### Docker Commands
@@ -94,7 +94,7 @@ Use these as practical starting points for development and review environments:
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: 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:
```text ```text
unable to get image 'deer-flow-gateway': permission denied while trying to connect to the Docker daemon socket at unix:///var/run/docker.sock unable to get image 'deer-flow-dev-langgraph': permission denied while trying to connect to the Docker daemon socket at unix:///var/run/docker.sock
``` ```
Recommended fix: add your current user to the `docker` group so Docker commands work without `sudo`. Recommended fix: add your current user to the `docker` group so Docker commands work without `sudo`.
@@ -131,8 +131,9 @@ Host Machine
Docker Compose (deer-flow-dev) Docker Compose (deer-flow-dev)
├→ nginx (port 2026) ← Reverse proxy ├→ nginx (port 2026) ← Reverse proxy
├→ web (port 3000) ← Frontend with hot-reload ├→ web (port 3000) ← Frontend with hot-reload
├→ gateway (port 8001) ← Gateway API + LangGraph-compatible runtime with hot-reload ├→ api (port 8001) ← Gateway API with hot-reload
└→ provisioner (optional, port 8002) ← Started only in provisioner/K8s sandbox mode ├→ langgraph (port 2024) ← LangGraph server with hot-reload
└→ provisioner (optional, port 8002) ← Started only in provisioner/K8s sandbox mode
``` ```
**Benefits of Docker Development**: **Benefits of Docker Development**:
@@ -165,7 +166,7 @@ Required tools:
1. **Configure the application** (same as Docker setup above) 1. **Configure the application** (same as Docker setup above)
2. **Install dependencies** (this also sets up pre-commit hooks): 2. **Install dependencies**:
```bash ```bash
make install make install
``` ```
@@ -183,13 +184,17 @@ Required tools:
If you need to start services individually: If you need to start services individually:
1. **Start backend service**: 1. **Start backend services**:
```bash ```bash
# Terminal 1: Start Gateway API + embedded agent runtime (port 8001) # Terminal 1: Start LangGraph Server (port 2024)
cd backend cd backend
make dev make dev
# Terminal 2: Start Frontend (port 3000) # Terminal 2: Start Gateway API (port 8001)
cd backend
make gateway
# Terminal 3: Start Frontend (port 3000)
cd frontend cd frontend
pnpm dev pnpm dev
``` ```
@@ -207,10 +212,10 @@ If you need to start services individually:
The nginx configuration provides: The nginx configuration provides:
- Unified entry point on port 2026 - Unified entry point on port 2026
- Rewrites `/api/langgraph/*` to Gateway's LangGraph-compatible API (8001) - Routes `/api/langgraph/*` to LangGraph Server (2024)
- Routes other `/api/*` endpoints to Gateway API (8001) - Routes other `/api/*` endpoints to Gateway API (8001)
- Routes non-API requests to Frontend (3000) - Routes non-API requests to Frontend (3000)
- Same-origin API routing; split-origin or port-forwarded browser clients should use the Gateway `GATEWAY_CORS_ORIGINS` allowlist - Centralized CORS handling
- SSE/streaming support for real-time agent responses - SSE/streaming support for real-time agent responses
- Optimized timeouts for long-running operations - Optimized timeouts for long-running operations
@@ -230,8 +235,8 @@ deer-flow/
│ └── nginx.local.conf # Nginx config for local dev │ └── nginx.local.conf # Nginx config for local dev
├── backend/ # Backend application ├── backend/ # Backend application
│ ├── src/ │ ├── src/
│ │ ├── gateway/ # Gateway API and LangGraph-compatible runtime (port 8001) │ │ ├── gateway/ # Gateway API (port 8001)
│ │ ├── agents/ # LangGraph agent runtime used by Gateway │ │ ├── agents/ # LangGraph agents (port 2024)
│ │ ├── mcp/ # Model Context Protocol integration │ │ ├── mcp/ # Model Context Protocol integration
│ │ ├── skills/ # Skills system │ │ ├── skills/ # Skills system
│ │ └── sandbox/ # Sandbox execution │ │ └── sandbox/ # Sandbox execution
@@ -251,7 +256,8 @@ Browser
Nginx (port 2026) ← Unified entry point Nginx (port 2026) ← Unified entry point
├→ Frontend (port 3000) ← / (non-API requests) ├→ Frontend (port 3000) ← / (non-API requests)
→ Gateway API (port 8001) ← /api/* and /api/langgraph/* (LangGraph-compatible agent interactions) → Gateway API (port 8001) ← /api/models, /api/mcp, /api/skills, /api/threads/*/artifacts
└→ LangGraph Server (port 2024) ← /api/langgraph/* (agent interactions)
``` ```
## Development Workflow ## Development Workflow
@@ -287,44 +293,24 @@ Nginx (port 2026) ← Unified entry point
git push origin feature/your-feature-name git push origin feature/your-feature-name
``` ```
## AI assistance disclosure
DeerFlow is an AI project and we welcome AI-assisted contributions. To help
reviewers calibrate how closely to read a change, **every pull request must
complete the "AI assistance" section of the
[PR template](.github/pull_request_template.md)**:
- which tool(s) you used (or `none`),
- how you used them, and
- a confirmation that a human has read, understands, and takes responsibility
for the change.
Please don't delete the section. PRs that ignore it may be asked to fill it in
before review.
## Testing ## Testing
```bash ```bash
# Backend tests # Backend tests
cd backend cd backend
make test uv run pytest
# Frontend unit tests # Frontend checks
cd frontend cd frontend
make test pnpm check
# Frontend E2E tests (requires Chromium; builds and auto-starts the Next.js production server)
cd frontend
make test-e2e
``` ```
### PR Regression Checks ### PR Regression Checks
Every pull request triggers the following CI workflows: Every pull request runs the backend regression workflow at [.github/workflows/backend-unit-tests.yml](.github/workflows/backend-unit-tests.yml), including:
- **Backend unit tests** — [.github/workflows/backend-unit-tests.yml](.github/workflows/backend-unit-tests.yml) - `tests/test_provisioner_kubeconfig.py`
- **Frontend unit tests** — [.github/workflows/frontend-unit-tests.yml](.github/workflows/frontend-unit-tests.yml) - `tests/test_docker_sandbox_mode_detection.py`
- **Frontend E2E tests** — [.github/workflows/e2e-tests.yml](.github/workflows/e2e-tests.yml) (triggered only when `frontend/` files change)
## Code Style ## Code Style
+67 -13
View File
@@ -1,6 +1,6 @@
# DeerFlow - Unified Development Environment # DeerFlow - Unified Development Environment
.PHONY: help config config-upgrade check install setup doctor detect-thread-boundaries detect-blocking-io dev dev-daemon start start-daemon stop up down clean docker-init docker-start 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 BASH ?= bash
BACKEND_UV_RUN = cd backend && uv run BACKEND_UV_RUN = cd backend && uv run
@@ -23,24 +23,28 @@ help:
@echo " make config - Generate local config files (aborts if config already exists)" @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 config-upgrade - Merge new fields from config.example.yaml into config.yaml"
@echo " make check - Check if all required tools are installed" @echo " make check - Check if all required tools are installed"
@echo " make detect-thread-boundaries - Inventory async/thread boundary points" @echo " make install - Install all dependencies (frontend + backend)"
@echo " make detect-blocking-io - Inventory blocking IO that may block the backend event loop"
@echo " make install - Install all dependencies (frontend + backend + pre-commit hooks)"
@echo " make setup-sandbox - Pre-pull sandbox container image (recommended)" @echo " make setup-sandbox - Pre-pull sandbox container image (recommended)"
@echo " make dev - Start all services in development mode (with hot-reloading)" @echo " make dev - Start all services in development mode (with hot-reloading)"
@echo " make dev-pro - Start in dev + Gateway mode (experimental, no LangGraph server)"
@echo " make dev-daemon - Start dev services in background (daemon mode)" @echo " make dev-daemon - Start dev services in background (daemon mode)"
@echo " make dev-daemon-pro - Start dev daemon + Gateway mode (experimental)"
@echo " make start - Start all services in production mode (optimized, no hot-reloading)" @echo " make start - Start all services in production mode (optimized, no hot-reloading)"
@echo " make start-pro - Start in prod + Gateway mode (experimental)"
@echo " make start-daemon - Start prod services in background (daemon mode)" @echo " make start-daemon - Start prod services in background (daemon mode)"
@echo " make start-daemon-pro - Start prod daemon + Gateway mode (experimental)"
@echo " make stop - Stop all running services" @echo " make stop - Stop all running services"
@echo " make clean - Clean up processes and temporary files" @echo " make clean - Clean up processes and temporary files"
@echo "" @echo ""
@echo "Docker Production Commands:" @echo "Docker Production Commands:"
@echo " make up - Build and start production Docker services (localhost:2026)" @echo " make up - Build and start production Docker services (localhost:2026)"
@echo " make up-pro - Build and start production Docker in Gateway mode (experimental)"
@echo " make down - Stop and remove production Docker containers" @echo " make down - Stop and remove production Docker containers"
@echo "" @echo ""
@echo "Docker Development Commands:" @echo "Docker Development Commands:"
@echo " make docker-init - Pull the sandbox image" @echo " make docker-init - Pull the sandbox image"
@echo " make docker-start - Start Docker services (mode-aware from config.yaml, localhost:2026)" @echo " make docker-start - Start Docker services (mode-aware from config.yaml, localhost:2026)"
@echo " make docker-start-pro - Start Docker in Gateway mode (experimental, no LangGraph container)"
@echo " make docker-stop - Stop Docker development services" @echo " make docker-stop - Stop Docker development services"
@echo " make docker-logs - View Docker development logs" @echo " make docker-logs - View Docker development logs"
@echo " make docker-logs-frontend - View Docker frontend logs" @echo " make docker-logs-frontend - View Docker frontend logs"
@@ -53,12 +57,6 @@ setup:
doctor: doctor:
@$(BACKEND_UV_RUN) python ../scripts/doctor.py @$(BACKEND_UV_RUN) python ../scripts/doctor.py
detect-thread-boundaries:
@$(PYTHON) ./scripts/detect_thread_boundaries.py
detect-blocking-io:
@$(MAKE) -C backend detect-blocking-io
config: config:
@$(PYTHON) ./scripts/configure.py @$(PYTHON) ./scripts/configure.py
@@ -75,8 +73,6 @@ install:
@cd backend && uv sync @cd backend && uv sync
@echo "Installing frontend dependencies..." @echo "Installing frontend dependencies..."
@cd frontend && pnpm install @cd frontend && pnpm install
@echo "Installing pre-commit hooks..."
@$(BACKEND_UV_RUN) --with pre-commit pre-commit install
@echo "✓ All dependencies installed" @echo "✓ All dependencies installed"
@echo "" @echo ""
@echo "==========================================" @echo "=========================================="
@@ -89,28 +85,77 @@ install:
# Pre-pull sandbox Docker image (optional but recommended) # Pre-pull sandbox Docker image (optional but recommended)
setup-sandbox: setup-sandbox:
@$(RUN_WITH_GIT_BASH) ./scripts/setup-sandbox.sh @echo "=========================================="
@echo " Pre-pulling Sandbox Container Image"
@echo "=========================================="
@echo ""
@IMAGE=$$(grep -A 20 "# sandbox:" config.yaml 2>/dev/null | grep "image:" | awk '{print $$2}' | head -1); \
if [ -z "$$IMAGE" ]; then \
IMAGE="enterprise-public-cn-beijing.cr.volces.com/vefaas-public/all-in-one-sandbox:latest"; \
echo "Using default image: $$IMAGE"; \
else \
echo "Using configured image: $$IMAGE"; \
fi; \
echo ""; \
if command -v container >/dev/null 2>&1 && [ "$$(uname)" = "Darwin" ]; then \
echo "Detected Apple Container on macOS, pulling image..."; \
container pull "$$IMAGE" || echo "⚠ Apple Container pull failed, will try Docker"; \
fi; \
if command -v docker >/dev/null 2>&1; then \
echo "Pulling image using Docker..."; \
if docker pull "$$IMAGE"; then \
echo ""; \
echo "✓ Sandbox image pulled successfully"; \
else \
echo ""; \
echo "⚠ Failed to pull sandbox image (this is OK for local sandbox mode)"; \
fi; \
else \
echo "✗ Neither Docker nor Apple Container is available"; \
echo " Please install Docker: https://docs.docker.com/get-docker/"; \
exit 1; \
fi
# Start all services in development mode (with hot-reloading) # Start all services in development mode (with hot-reloading)
dev: dev:
@$(PYTHON) ./scripts/check.py @$(PYTHON) ./scripts/check.py
@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --dev @$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --dev
# Start all services in dev + Gateway mode (experimental: agent runtime embedded in Gateway)
dev-pro:
@$(PYTHON) ./scripts/check.py
@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --dev --gateway
# Start all services in production mode (with optimizations) # Start all services in production mode (with optimizations)
start: start:
@$(PYTHON) ./scripts/check.py @$(PYTHON) ./scripts/check.py
@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --prod @$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --prod
# Start all services in prod + Gateway mode (experimental)
start-pro:
@$(PYTHON) ./scripts/check.py
@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --prod --gateway
# Start all services in daemon mode (background) # Start all services in daemon mode (background)
dev-daemon: dev-daemon:
@$(PYTHON) ./scripts/check.py @$(PYTHON) ./scripts/check.py
@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --dev --daemon @$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --dev --daemon
# Start daemon + Gateway mode (experimental)
dev-daemon-pro:
@$(PYTHON) ./scripts/check.py
@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --dev --gateway --daemon
# Start prod services in daemon mode (background) # Start prod services in daemon mode (background)
start-daemon: start-daemon:
@$(PYTHON) ./scripts/check.py @$(PYTHON) ./scripts/check.py
@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --prod --daemon @$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --prod --daemon
# Start prod daemon + Gateway mode (experimental)
start-daemon-pro:
@$(PYTHON) ./scripts/check.py
@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --prod --gateway --daemon
# Stop all services # Stop all services
stop: stop:
@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --stop @$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --stop
@@ -119,6 +164,7 @@ stop:
clean: stop clean: stop
@echo "Cleaning up..." @echo "Cleaning up..."
@-rm -rf backend/.deer-flow 2>/dev/null || true @-rm -rf backend/.deer-flow 2>/dev/null || true
@-rm -rf backend/.langgraph_api 2>/dev/null || true
@-rm -rf logs/*.log 2>/dev/null || true @-rm -rf logs/*.log 2>/dev/null || true
@echo "✓ Cleanup complete" @echo "✓ Cleanup complete"
@@ -134,6 +180,10 @@ docker-init:
docker-start: docker-start:
@$(RUN_WITH_GIT_BASH) ./scripts/docker.sh start @$(RUN_WITH_GIT_BASH) ./scripts/docker.sh start
# Start Docker in Gateway mode (experimental)
docker-start-pro:
@$(RUN_WITH_GIT_BASH) ./scripts/docker.sh start --gateway
# Stop Docker development environment # Stop Docker development environment
docker-stop: docker-stop:
@$(RUN_WITH_GIT_BASH) ./scripts/docker.sh stop @$(RUN_WITH_GIT_BASH) ./scripts/docker.sh stop
@@ -156,6 +206,10 @@ docker-logs-gateway:
up: up:
@$(RUN_WITH_GIT_BASH) ./scripts/deploy.sh @$(RUN_WITH_GIT_BASH) ./scripts/deploy.sh
# Build and start production services in Gateway mode
up-pro:
@$(RUN_WITH_GIT_BASH) ./scripts/deploy.sh --gateway
# Stop and remove production containers # Stop and remove production containers
down: down:
@$(RUN_WITH_GIT_BASH) ./scripts/deploy.sh down @$(RUN_WITH_GIT_BASH) ./scripts/deploy.sh down
+37 -52
View File
@@ -243,9 +243,10 @@ make up # Build images and start all production services
make down # Stop and remove containers make down # Stop and remove containers
``` ```
Access: http://localhost:2026 > [!NOTE]
> The LangGraph agent server currently runs via `langgraph dev` (the open-source CLI server).
The unified nginx endpoint is same-origin by default and does not emit browser CORS headers. If you run a split-origin or port-forwarded browser client, set `GATEWAY_CORS_ORIGINS` to comma-separated exact origins such as `http://localhost:3000`; the Gateway then applies the CORS allowlist and matching CSRF origin checks. Access: http://localhost:2026
See [CONTRIBUTING.md](CONTRIBUTING.md) for detailed Docker development guide. See [CONTRIBUTING.md](CONTRIBUTING.md) for detailed Docker development guide.
@@ -253,7 +254,7 @@ See [CONTRIBUTING.md](CONTRIBUTING.md) for detailed Docker development guide.
If you prefer running services locally: If you prefer running services locally:
Prerequisite: complete the "Configuration" steps above first (`make setup`). `make dev` requires a valid `config.yaml` in the project root. Set `DEER_FLOW_PROJECT_ROOT` to define that root explicitly, or `DEER_FLOW_CONFIG_PATH` to point at a specific config file. Runtime state defaults to `.deer-flow` under the project root and can be moved with `DEER_FLOW_HOME`; skills default to `skills/` under the project root and can be moved with `DEER_FLOW_SKILLS_PATH`. Run `make doctor` to verify your setup before starting. 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`. 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**: 1. **Check prerequisites**:
@@ -263,7 +264,7 @@ On Windows, run the local development flow from Git Bash. Native `cmd.exe` and P
2. **Install dependencies**: 2. **Install dependencies**:
```bash ```bash
make install # Install backend + frontend dependencies + pre-commit hooks make install # Install backend + frontend dependencies
``` ```
3. **(Optional) Pre-pull sandbox image**: 3. **(Optional) Pre-pull sandbox image**:
@@ -288,31 +289,53 @@ On Windows, run the local development flow from Git Bash. Native `cmd.exe` and P
#### Startup Modes #### Startup Modes
DeerFlow runs the agent runtime inside the Gateway API. Development mode enables hot-reload; production mode uses a pre-built frontend. DeerFlow supports multiple startup modes across two dimensions:
- **Dev / Prod** — dev enables hot-reload; prod uses pre-built frontend
- **Standard / Gateway** — standard uses a separate LangGraph server (4 processes); Gateway mode (experimental) embeds the agent runtime in the Gateway API (3 processes)
| | **Local Foreground** | **Local Daemon** | **Docker Dev** | **Docker Prod** | | | **Local Foreground** | **Local Daemon** | **Docker Dev** | **Docker Prod** |
|---|---|---|---|---| |---|---|---|---|---|
| **Dev** | `./scripts/serve.sh --dev`<br/>`make dev` | `./scripts/serve.sh --dev --daemon`<br/>`make dev-daemon` | `./scripts/docker.sh start`<br/>`make docker-start` | — | | **Dev** | `./scripts/serve.sh --dev`<br/>`make dev` | `./scripts/serve.sh --dev --daemon`<br/>`make dev-daemon` | `./scripts/docker.sh start`<br/>`make docker-start` | — |
| **Dev + Gateway** | `./scripts/serve.sh --dev --gateway`<br/>`make dev-pro` | `./scripts/serve.sh --dev --gateway --daemon`<br/>`make dev-daemon-pro` | `./scripts/docker.sh start --gateway`<br/>`make docker-start-pro` | — |
| **Prod** | `./scripts/serve.sh --prod`<br/>`make start` | `./scripts/serve.sh --prod --daemon`<br/>`make start-daemon` | — | `./scripts/deploy.sh`<br/>`make up` | | **Prod** | `./scripts/serve.sh --prod`<br/>`make start` | `./scripts/serve.sh --prod --daemon`<br/>`make start-daemon` | — | `./scripts/deploy.sh`<br/>`make up` |
| **Prod + Gateway** | `./scripts/serve.sh --prod --gateway`<br/>`make start-pro` | `./scripts/serve.sh --prod --gateway --daemon`<br/>`make start-daemon-pro` | — | `./scripts/deploy.sh --gateway`<br/>`make up-pro` |
| Action | Local | Docker Dev | Docker Prod | | Action | Local | Docker Dev | Docker Prod |
|---|---|---|---| |---|---|---|---|
| **Stop** | `./scripts/serve.sh --stop`<br/>`make stop` | `./scripts/docker.sh stop`<br/>`make docker-stop` | `./scripts/deploy.sh down`<br/>`make down` | | **Stop** | `./scripts/serve.sh --stop`<br/>`make stop` | `./scripts/docker.sh stop`<br/>`make docker-stop` | `./scripts/deploy.sh down`<br/>`make down` |
| **Restart** | `./scripts/serve.sh --restart [flags]` | `./scripts/docker.sh restart` | — | | **Restart** | `./scripts/serve.sh --restart [flags]` | `./scripts/docker.sh restart` | — |
Gateway owns `/api/langgraph/*` and translates those public LangGraph-compatible paths to its native `/api/*` routers behind nginx. > **Gateway mode** eliminates the LangGraph server process — the Gateway API handles agent execution directly via async tasks, managing its own concurrency.
#### Why Gateway Mode?
In standard mode, DeerFlow runs a dedicated [LangGraph Platform](https://langchain-ai.github.io/langgraph/) server alongside the Gateway API. This architecture works well but has trade-offs:
| | Standard Mode | Gateway Mode |
|---|---|---|
| **Architecture** | Gateway (REST API) + LangGraph (agent runtime) | Gateway embeds agent runtime |
| **Concurrency** | `--n-jobs-per-worker` per worker (requires license) | `--workers` × async tasks (no per-worker cap) |
| **Containers / Processes** | 4 (frontend, gateway, langgraph, nginx) | 3 (frontend, gateway, nginx) |
| **Resource usage** | Higher (two Python runtimes) | Lower (single Python runtime) |
| **LangGraph Platform license** | Required for production images | Not required |
| **Cold start** | Slower (two services to initialize) | Faster |
Both modes are functionally equivalent — the same agents, tools, and skills work in either mode.
#### Docker Production Deployment #### Docker Production Deployment
`deploy.sh` supports building and starting separately: `deploy.sh` supports building and starting separately. Images are mode-agnostic — runtime mode is selected at start time:
```bash ```bash
# One-step (build + start) # One-step (build + start)
deploy.sh deploy.sh # standard mode (default)
deploy.sh --gateway # gateway mode
# Two-step (build once, start later) # Two-step (build once, start with any mode)
deploy.sh build # build all images deploy.sh build # build all images
deploy.sh start # start pre-built images deploy.sh start # start in standard mode
deploy.sh start --gateway # start in gateway mode
# Stop # Stop
deploy.sh down deploy.sh down
@@ -347,14 +370,13 @@ DeerFlow supports receiving tasks from messaging apps. Channels auto-start when
| Feishu / Lark | WebSocket | Moderate | | Feishu / Lark | WebSocket | Moderate |
| WeChat | Tencent iLink (long-polling) | Moderate | | WeChat | Tencent iLink (long-polling) | Moderate |
| WeCom | WebSocket | Moderate | | WeCom | WebSocket | Moderate |
| DingTalk | Stream Push (WebSocket) | Moderate |
**Configuration in `config.yaml`:** **Configuration in `config.yaml`:**
```yaml ```yaml
channels: channels:
# LangGraph-compatible Gateway API base URL (default: http://localhost:8001/api) # LangGraph Server URL (default: http://localhost:2024)
langgraph_url: http://localhost:8001/api langgraph_url: http://localhost:2024
# Gateway API URL (default: http://localhost:8001) # Gateway API URL (default: http://localhost:8001)
gateway_url: http://localhost:8001 gateway_url: http://localhost:8001
@@ -417,19 +439,11 @@ channels:
context: context:
thinking_enabled: true thinking_enabled: true
subagent_enabled: true subagent_enabled: true
dingtalk:
enabled: true
client_id: $DINGTALK_CLIENT_ID # Client ID of your DingTalk application
client_secret: $DINGTALK_CLIENT_SECRET # Client Secret of your DingTalk application
allowed_users: [] # empty = allow all
card_template_id: "" # Optional: AI Card template ID for streaming typewriter effect
``` ```
Notes: Notes:
- `assistant_id: lead_agent` calls the default LangGraph assistant directly. - `assistant_id: lead_agent` calls the default LangGraph assistant directly.
- If `assistant_id` is set to a custom agent name, DeerFlow still routes through `lead_agent` and injects that value as `agent_name`, so the custom agent's SOUL/config takes effect for IM channels. - If `assistant_id` is set to a custom agent name, DeerFlow still routes through `lead_agent` and injects that value as `agent_name`, so the custom agent's SOUL/config takes effect for IM channels.
- IM channel workers call Gateway's LangGraph-compatible API internally and automatically attach process-local internal auth plus the CSRF cookie/header pair required for thread and run creation.
Set the corresponding API keys in your `.env` file: Set the corresponding API keys in your `.env` file:
@@ -452,10 +466,6 @@ WECHAT_ILINK_BOT_ID=your_ilink_bot_id
# WeCom # WeCom
WECOM_BOT_ID=your_bot_id WECOM_BOT_ID=your_bot_id
WECOM_BOT_SECRET=your_bot_secret WECOM_BOT_SECRET=your_bot_secret
# DingTalk
DINGTALK_CLIENT_ID=your_client_id
DINGTALK_CLIENT_SECRET=your_client_secret
``` ```
**Telegram Setup** **Telegram Setup**
@@ -494,15 +504,7 @@ DINGTALK_CLIENT_SECRET=your_client_secret
4. Make sure backend dependencies include `wecom-aibot-python-sdk`. The channel uses a WebSocket long connection and does not require a public callback URL. 4. Make sure backend dependencies include `wecom-aibot-python-sdk`. The channel uses a WebSocket long connection and does not require a public callback URL.
5. The current integration supports inbound text, image, and file messages. Final images/files generated by the agent are also sent back to the WeCom conversation. 5. The current integration supports inbound text, image, and file messages. Final images/files generated by the agent are also sent back to the WeCom conversation.
**DingTalk Setup** When DeerFlow runs in Docker Compose, IM channels execute inside the `gateway` container. In that case, do not point `channels.langgraph_url` or `channels.gateway_url` at `localhost`; use container service names such as `http://langgraph:2024` and `http://gateway:8001`, or set `DEER_FLOW_CHANNELS_LANGGRAPH_URL` and `DEER_FLOW_CHANNELS_GATEWAY_URL`.
1. Create a DingTalk application in the [DingTalk Developer Console](https://open.dingtalk.com/) and enable **Robot** capability.
2. Set the message receiving mode to **Stream Mode** in the robot configuration page.
3. Copy the `Client ID` and `Client Secret`, set `DINGTALK_CLIENT_ID` and `DINGTALK_CLIENT_SECRET` in `.env`, and enable the channel in `config.yaml`.
4. *(Optional)* To enable streaming AI Card replies (typewriter effect), create an **AI Card** template on the [DingTalk Card Platform](https://open.dingtalk.com/document/dingstart/typewriter-effect-streaming-ai-card), then set `card_template_id` in `config.yaml` to the template ID. You also need to apply for the `Card.Streaming.Write` and `Card.Instance.Write` permissions.
When DeerFlow runs in Docker Compose, IM channels execute inside the `gateway` container. In that case, do not point `channels.langgraph_url` or `channels.gateway_url` at `localhost`; use container service names such as `http://gateway:8001/api` and `http://gateway:8001`, or set `DEER_FLOW_CHANNELS_LANGGRAPH_URL` and `DEER_FLOW_CHANNELS_GATEWAY_URL`.
**Commands** **Commands**
@@ -546,15 +548,6 @@ LANGFUSE_BASE_URL=https://cloud.langfuse.com
If you are using a self-hosted Langfuse instance, set `LANGFUSE_BASE_URL` to your deployment URL. If you are using a self-hosted Langfuse instance, set `LANGFUSE_BASE_URL` to your deployment URL.
**Trace correlation fields.** Every agent run is annotated with Langfuse's reserved trace attributes so the Sessions and Users pages light up automatically:
- `session_id` = LangGraph `thread_id` — groups every trace of the same conversation
- `user_id` = effective user from `get_effective_user_id()` (falls back to `default` in no-auth mode)
- `trace_name` = assistant id (defaults to `lead-agent`)
- `tags` = `[env:<DEER_FLOW_ENV>, model:<model_name>]` (omitted when not set)
These are injected into `RunnableConfig.metadata` at the graph invocation root for both the gateway path (`runtime/runs/worker.py::run_agent`) and the embedded path (`client.py::DeerFlowClient.stream`), so any LangChain-compatible callback can read them. Set `DEER_FLOW_ENV` (or `ENVIRONMENT`) to tag traces by deployment environment.
#### Using Both Providers #### Using Both Providers
If both LangSmith and Langfuse are enabled, DeerFlow attaches both tracing callbacks and reports the same model activity to both systems. If both LangSmith and Langfuse are enabled, DeerFlow attaches both tracing callbacks and reports the same model activity to both systems.
@@ -637,7 +630,7 @@ See [`skills/public/claude-to-deerflow/SKILL.md`](skills/public/claude-to-deerfl
Complex tasks rarely fit in a single pass. DeerFlow decomposes them. Complex tasks rarely fit in a single pass. DeerFlow decomposes them.
The lead agent can spawn sub-agents on the fly — each with its own scoped context, tools, and termination conditions. Sub-agents run in parallel when possible, report back structured results, and the lead agent synthesizes everything into a coherent output. When token usage tracking is enabled, completed sub-agent usage is attributed back to the dispatching step. The lead agent can spawn sub-agents on the fly — each with its own scoped context, tools, and termination conditions. Sub-agents run in parallel when possible, report back structured results, and the lead agent synthesizes everything into a coherent output.
This is how DeerFlow handles tasks that take minutes to hours: a research task might fan out into a dozen sub-agents, each exploring a different angle, then converge into a single report — or a website — or a slide deck with generated visuals. One harness, many hands. This is how DeerFlow handles tasks that take minutes to hours: a research task might fan out into a dozen sub-agents, each exploring a different angle, then converge into a single report — or a website — or a slide deck with generated visuals. One harness, many hands.
@@ -665,8 +658,6 @@ This is the difference between a chatbot with tool access and an agent with an a
**Summarization**: Within a session, DeerFlow manages context aggressively — summarizing completed sub-tasks, offloading intermediate results to the filesystem, compressing what's no longer immediately relevant. This lets it stay sharp across long, multi-step tasks without blowing the context window. **Summarization**: Within a session, DeerFlow manages context aggressively — summarizing completed sub-tasks, offloading intermediate results to the filesystem, compressing what's no longer immediately relevant. This lets it stay sharp across long, multi-step tasks without blowing the context window.
**Strict Tool-Call Recovery**: When a provider or middleware interrupts a tool-call loop, DeerFlow now strips provider-level raw tool-call metadata on forced-stop assistant messages and injects placeholder tool results for dangling calls before the next model invocation. This keeps OpenAI-compatible reasoning models that strictly validate `tool_call_id` sequences from failing with malformed history errors.
### Long-Term Memory ### Long-Term Memory
Most agents forget everything the moment a conversation ends. DeerFlow remembers. Most agents forget everything the moment a conversation ends. DeerFlow remembers.
@@ -740,12 +731,6 @@ DeerFlow has key high-privilege capabilities including **system command executio
We welcome contributions! Please see [CONTRIBUTING.md](CONTRIBUTING.md) for development setup, workflow, and guidelines. We welcome contributions! Please see [CONTRIBUTING.md](CONTRIBUTING.md) for development setup, workflow, and guidelines.
Regression coverage includes Docker sandbox mode detection and provisioner kubeconfig-path handling tests in `backend/tests/`. Regression coverage includes Docker sandbox mode detection and provisioner kubeconfig-path handling tests in `backend/tests/`.
Backend blocking-IO diagnostics are available from the repository root with
`make detect-blocking-io`: it statically scans backend business code for
blocking IO that may run on the backend event loop, prints a concise summary,
and writes complete JSON findings to `.deer-flow/blocking-io-findings.json`.
The JSON includes compact review records with `priority`, `location`,
`blocking_call`, `event_loop_exposure`, `reason`, and `code`.
Gateway artifact serving now forces active web content types (`text/html`, `application/xhtml+xml`, `image/svg+xml`) to download as attachments instead of inline rendering, reducing XSS risk for generated artifacts. Gateway artifact serving now forces active web content types (`text/html`, `application/xhtml+xml`, `image/svg+xml`) to download as attachments instead of inline rendering, reducing XSS risk for generated artifacts.
## License ## License
+3 -22
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@@ -228,7 +228,7 @@ make down # Stop and remove containers
``` ```
> [!NOTE] > [!NOTE]
> Le runtime d'agent s'exécute actuellement dans la Gateway. nginx réécrit `/api/langgraph/*` vers l'API compatible LangGraph servie par la Gateway. > Le serveur d'agents LangGraph fonctionne actuellement via `langgraph dev` (le serveur CLI open source).
Accès : http://localhost:2026 Accès : http://localhost:2026
@@ -290,14 +290,13 @@ DeerFlow peut recevoir des tâches depuis des applications de messagerie. Les ca
| Telegram | Bot API (long-polling) | Facile | | Telegram | Bot API (long-polling) | Facile |
| Slack | Socket Mode | Modérée | | Slack | Socket Mode | Modérée |
| Feishu / Lark | WebSocket | Modérée | | Feishu / Lark | WebSocket | Modérée |
| DingTalk | Stream Push (WebSocket) | Modérée |
**Configuration dans `config.yaml` :** **Configuration dans `config.yaml` :**
```yaml ```yaml
channels: channels:
# LangGraph-compatible Gateway API base URL (default: http://localhost:8001/api) # LangGraph Server URL (default: http://localhost:2024)
langgraph_url: http://localhost:8001/api langgraph_url: http://localhost:2024
# Gateway API URL (default: http://localhost:8001) # Gateway API URL (default: http://localhost:8001)
gateway_url: http://localhost:8001 gateway_url: http://localhost:8001
@@ -342,13 +341,6 @@ channels:
context: context:
thinking_enabled: true thinking_enabled: true
subagent_enabled: true subagent_enabled: true
dingtalk:
enabled: true
client_id: $DINGTALK_CLIENT_ID # ClientId depuis DingTalk Open Platform
client_secret: $DINGTALK_CLIENT_SECRET # ClientSecret depuis DingTalk Open Platform
allowed_users: [] # vide = tout le monde autorisé
card_template_id: "" # Optionnel : ID de modèle AI Card pour l'effet machine à écrire en streaming
``` ```
Définissez les clés API correspondantes dans votre fichier `.env` : Définissez les clés API correspondantes dans votre fichier `.env` :
@@ -364,10 +356,6 @@ SLACK_APP_TOKEN=xapp-...
# Feishu / Lark # Feishu / Lark
FEISHU_APP_ID=cli_xxxx FEISHU_APP_ID=cli_xxxx
FEISHU_APP_SECRET=your_app_secret FEISHU_APP_SECRET=your_app_secret
# DingTalk
DINGTALK_CLIENT_ID=your_client_id
DINGTALK_CLIENT_SECRET=your_client_secret
``` ```
**Configuration Telegram** **Configuration Telegram**
@@ -390,13 +378,6 @@ DINGTALK_CLIENT_SECRET=your_client_secret
3. Dans **Events**, abonnez-vous à `im.message.receive_v1` et sélectionnez le mode **Long Connection**. 3. Dans **Events**, abonnez-vous à `im.message.receive_v1` et sélectionnez le mode **Long Connection**.
4. Copiez l'App ID et l'App Secret. Définissez `FEISHU_APP_ID` et `FEISHU_APP_SECRET` dans `.env` et activez le canal dans `config.yaml`. 4. Copiez l'App ID et l'App Secret. Définissez `FEISHU_APP_ID` et `FEISHU_APP_SECRET` dans `.env` et activez le canal dans `config.yaml`.
**Configuration DingTalk**
1. Créez une application sur [DingTalk Open Platform](https://open.dingtalk.com/) et activez la capacité **Robot**.
2. Dans la page de configuration du robot, définissez le mode de réception des messages sur **Stream**.
3. Copiez le `Client ID` et le `Client Secret`. Définissez `DINGTALK_CLIENT_ID` et `DINGTALK_CLIENT_SECRET` dans `.env` et activez le canal dans `config.yaml`.
4. *(Optionnel)* Pour activer les réponses en streaming AI Card (effet machine à écrire), créez un modèle **AI Card** sur la [plateforme de cartes DingTalk](https://open.dingtalk.com/document/dingstart/typewriter-effect-streaming-ai-card), puis définissez `card_template_id` dans `config.yaml` avec l'ID du modèle. Vous devez également demander les permissions `Card.Streaming.Write` et `Card.Instance.Write`.
**Commandes** **Commandes**
Une fois un canal connecté, vous pouvez interagir avec DeerFlow directement depuis le chat : Une fois un canal connecté, vous pouvez interagir avec DeerFlow directement depuis le chat :
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@@ -181,7 +181,7 @@ make down # コンテナを停止して削除
``` ```
> [!NOTE] > [!NOTE]
> Agentランタイムは現在Gateway内で実行されます。`/api/langgraph/*`はnginxによってGatewayのLangGraph-compatible APIへ書き換えられます。 > LangGraphエージェントサーバーは現在`langgraph dev`(オープンソースCLIサーバー)経由で実行されます。
アクセス: http://localhost:2026 アクセス: http://localhost:2026
@@ -243,14 +243,13 @@ DeerFlowはメッセージングアプリからのタスク受信をサポート
| Telegram | Bot API(ロングポーリング) | 簡単 | | Telegram | Bot API(ロングポーリング) | 簡単 |
| Slack | Socket Mode | 中程度 | | Slack | Socket Mode | 中程度 |
| Feishu / Lark | WebSocket | 中程度 | | Feishu / Lark | WebSocket | 中程度 |
| DingTalk | Stream PushWebSocket | 中程度 |
**`config.yaml`での設定:** **`config.yaml`での設定:**
```yaml ```yaml
channels: channels:
# LangGraph-compatible Gateway API base URL(デフォルト: http://localhost:8001/api # LangGraphサーバーURL(デフォルト: http://localhost:2024
langgraph_url: http://localhost:8001/api langgraph_url: http://localhost:2024
# Gateway API URL(デフォルト: http://localhost:8001 # Gateway API URL(デフォルト: http://localhost:8001
gateway_url: http://localhost:8001 gateway_url: http://localhost:8001
@@ -295,13 +294,6 @@ channels:
context: context:
thinking_enabled: true thinking_enabled: true
subagent_enabled: true subagent_enabled: true
dingtalk:
enabled: true
client_id: $DINGTALK_CLIENT_ID # DingTalk Open PlatformのClientId
client_secret: $DINGTALK_CLIENT_SECRET # DingTalk Open PlatformのClientSecret
allowed_users: [] # 空 = 全員許可
card_template_id: "" # オプション:ストリーミングタイプライター効果用のAIカードテンプレートID
``` ```
対応するAPIキーを`.env`ファイルに設定します: 対応するAPIキーを`.env`ファイルに設定します:
@@ -317,10 +309,6 @@ SLACK_APP_TOKEN=xapp-...
# Feishu / Lark # Feishu / Lark
FEISHU_APP_ID=cli_xxxx FEISHU_APP_ID=cli_xxxx
FEISHU_APP_SECRET=your_app_secret FEISHU_APP_SECRET=your_app_secret
# DingTalk
DINGTALK_CLIENT_ID=your_client_id
DINGTALK_CLIENT_SECRET=your_client_secret
``` ```
**Telegramのセットアップ** **Telegramのセットアップ**
@@ -343,13 +331,6 @@ DINGTALK_CLIENT_SECRET=your_client_secret
3. **イベント**で`im.message.receive_v1`を購読し、**ロングコネクション**モードを選択。 3. **イベント**で`im.message.receive_v1`を購読し、**ロングコネクション**モードを選択。
4. App IDとApp Secretをコピー。`.env`に`FEISHU_APP_ID`と`FEISHU_APP_SECRET`を設定し、`config.yaml`でチャネルを有効にします。 4. App IDとApp Secretをコピー。`.env`に`FEISHU_APP_ID`と`FEISHU_APP_SECRET`を設定し、`config.yaml`でチャネルを有効にします。
**DingTalkのセットアップ**
1. [DingTalk Open Platform](https://open.dingtalk.com/)でアプリを作成し、**ロボット**機能を有効化します。
2. ロボット設定ページでメッセージ受信モードを**Streamモード**に設定します。
3. `Client ID`と`Client Secret`をコピー。`.env`に`DINGTALK_CLIENT_ID`と`DINGTALK_CLIENT_SECRET`を設定し、`config.yaml`でチャネルを有効にします。
4. *(オプション)* ストリーミングAIカード返信(タイプライター効果)を有効にするには、[DingTalkカードプラットフォーム](https://open.dingtalk.com/document/dingstart/typewriter-effect-streaming-ai-card)で**AIカード**テンプレートを作成し、`config.yaml`の`card_template_id`にテンプレートIDを設定します。`Card.Streaming.Write` および `Card.Instance.Write` 権限の申請も必要です。
**コマンド** **コマンド**
チャネル接続後、チャットから直接DeerFlowと対話できます: チャネル接続後、チャットから直接DeerFlowと対話できます:
-15
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@@ -256,7 +256,6 @@ DeerFlow принимает задачи прямо из мессенджеро
| Telegram | Bot API (long-polling) | Просто | | Telegram | Bot API (long-polling) | Просто |
| Slack | Socket Mode | Средне | | Slack | Socket Mode | Средне |
| Feishu / Lark | WebSocket | Средне | | Feishu / Lark | WebSocket | Средне |
| DingTalk | Stream Push (WebSocket) | Средне |
**Конфигурация в `config.yaml`:** **Конфигурация в `config.yaml`:**
@@ -279,13 +278,6 @@ channels:
enabled: true enabled: true
bot_token: $TELEGRAM_BOT_TOKEN bot_token: $TELEGRAM_BOT_TOKEN
allowed_users: [] allowed_users: []
dingtalk:
enabled: true
client_id: $DINGTALK_CLIENT_ID # ClientId с DingTalk Open Platform
client_secret: $DINGTALK_CLIENT_SECRET # ClientSecret с DingTalk Open Platform
allowed_users: [] # пусто = разрешить всем
card_template_id: "" # Опционально: ID шаблона AI Card для потокового эффекта печатной машинки
``` ```
**Настройка Telegram** **Настройка Telegram**
@@ -293,13 +285,6 @@ channels:
1. Напишите [@BotFather](https://t.me/BotFather), отправьте `/newbot` и скопируйте HTTP API-токен. 1. Напишите [@BotFather](https://t.me/BotFather), отправьте `/newbot` и скопируйте HTTP API-токен.
2. Укажите `TELEGRAM_BOT_TOKEN` в `.env` и включите канал в `config.yaml`. 2. Укажите `TELEGRAM_BOT_TOKEN` в `.env` и включите канал в `config.yaml`.
**Настройка DingTalk**
1. Создайте приложение на [DingTalk Open Platform](https://open.dingtalk.com/) и включите возможность **Робот**.
2. На странице настроек робота установите режим приёма сообщений на **Stream**.
3. Скопируйте `Client ID` и `Client Secret`. Укажите `DINGTALK_CLIENT_ID` и `DINGTALK_CLIENT_SECRET` в `.env` и включите канал в `config.yaml`.
4. *(Опционально)* Для включения потоковых ответов AI Card (эффект печатной машинки) создайте шаблон **AI Card** на [платформе карточек DingTalk](https://open.dingtalk.com/document/dingstart/typewriter-effect-streaming-ai-card), затем укажите `card_template_id` в `config.yaml` с ID шаблона. Также необходимо запросить разрешения `Card.Streaming.Write` и `Card.Instance.Write`.
**Доступные команды** **Доступные команды**
| Команда | Описание | | Команда | Описание |
+4 -23
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@@ -184,7 +184,7 @@ make down # 停止并移除容器
``` ```
> [!NOTE] > [!NOTE]
> 当前 Agent 运行时嵌入在 Gateway 中运行,`/api/langgraph/*` 会由 nginx 重写到 Gateway 的 LangGraph-compatible API > 当前 LangGraph agent server 通过开源 CLI 服务 `langgraph dev` 运行
访问地址:http://localhost:2026 访问地址:http://localhost:2026
@@ -194,7 +194,7 @@ make down # 停止并移除容器
如果你更希望直接在本地启动各个服务: 如果你更希望直接在本地启动各个服务:
前提:先完成上面的“配置”步骤(`make config` 和模型 API key 配置)。`make dev` 需要有效配置文件,默认读取项目根目录下的 `config.yaml`。可以用 `DEER_FLOW_PROJECT_ROOT` 显式指定项目根目录,也可以 `DEER_FLOW_CONFIG_PATH` 指向某个具体配置文件。运行期状态默认写到项目根目录下的 `.deer-flow`,可用 `DEER_FLOW_HOME` 覆盖;skills 默认读取项目根目录下的 `skills/`,可用 `DEER_FLOW_SKILLS_PATH` 覆盖。 前提:先完成上面的“配置”步骤(`make config` 和模型 API key 配置)。`make dev` 需要有效配置文件,默认读取项目根目录下的 `config.yaml`,也可以通过 `DEER_FLOW_CONFIG_PATH` 覆盖。
在 Windows 上,请使用 Git Bash 运行本地开发流程。基于 bash 的服务脚本不支持直接在原生 `cmd.exe` 或 PowerShell 中执行,且 WSL 也不保证可用,因为部分脚本依赖 Git for Windows 的 `cygpath` 等工具。 在 Windows 上,请使用 Git Bash 运行本地开发流程。基于 bash 的服务脚本不支持直接在原生 `cmd.exe` 或 PowerShell 中执行,且 WSL 也不保证可用,因为部分脚本依赖 Git for Windows 的 `cygpath` 等工具。
1. **检查依赖环境** 1. **检查依赖环境**
@@ -248,14 +248,13 @@ DeerFlow 支持从即时通讯应用接收任务。只要配置完成,对应
| Slack | Socket Mode | 中等 | | Slack | Socket Mode | 中等 |
| Feishu / Lark | WebSocket | 中等 | | Feishu / Lark | WebSocket | 中等 |
| 企业微信智能机器人 | WebSocket | 中等 | | 企业微信智能机器人 | WebSocket | 中等 |
| 钉钉 | Stream PushWebSocket | 中等 |
**`config.yaml` 中的配置示例:** **`config.yaml` 中的配置示例:**
```yaml ```yaml
channels: channels:
# LangGraph-compatible Gateway API base URL(默认:http://localhost:8001/api # LangGraph Server URL(默认:http://localhost:2024
langgraph_url: http://localhost:8001/api langgraph_url: http://localhost:2024
# Gateway API URL(默认:http://localhost:8001 # Gateway API URL(默认:http://localhost:8001
gateway_url: http://localhost:8001 gateway_url: http://localhost:8001
@@ -305,13 +304,6 @@ channels:
context: context:
thinking_enabled: true thinking_enabled: true
subagent_enabled: true subagent_enabled: true
dingtalk:
enabled: true
client_id: $DINGTALK_CLIENT_ID # 钉钉开放平台 ClientId
client_secret: $DINGTALK_CLIENT_SECRET # 钉钉开放平台 ClientSecret
allowed_users: [] # 留空表示允许所有人
card_template_id: "" # 可选:AI 卡片模板 ID,用于流式打字机效果
``` ```
说明: 说明:
@@ -335,10 +327,6 @@ FEISHU_APP_SECRET=your_app_secret
# 企业微信智能机器人 # 企业微信智能机器人
WECOM_BOT_ID=your_bot_id WECOM_BOT_ID=your_bot_id
WECOM_BOT_SECRET=your_bot_secret WECOM_BOT_SECRET=your_bot_secret
# 钉钉
DINGTALK_CLIENT_ID=your_client_id
DINGTALK_CLIENT_SECRET=your_client_secret
``` ```
**Telegram 配置** **Telegram 配置**
@@ -369,13 +357,6 @@ DINGTALK_CLIENT_SECRET=your_client_secret
4. 安装后端依赖时确保包含 `wecom-aibot-python-sdk`,渠道会通过 WebSocket 长连接接收消息,无需公网回调地址。 4. 安装后端依赖时确保包含 `wecom-aibot-python-sdk`,渠道会通过 WebSocket 长连接接收消息,无需公网回调地址。
5. 当前支持文本、图片和文件入站消息;agent 生成的最终图片/文件也会回传到企业微信会话中。 5. 当前支持文本、图片和文件入站消息;agent 生成的最终图片/文件也会回传到企业微信会话中。
**钉钉配置**
1. 在 [钉钉开放平台](https://open.dingtalk.com/) 创建应用,并启用 **机器人** 能力。
2. 在机器人配置页面设置消息接收模式为 **Stream模式**。
3. 复制 `Client ID` 和 `Client Secret`,在 `.env` 中设置 `DINGTALK_CLIENT_ID` 和 `DINGTALK_CLIENT_SECRET`,并在 `config.yaml` 中启用该渠道。
4. *(可选)* 如需开启流式 AI 卡片回复(打字机效果),请在[钉钉卡片平台](https://open.dingtalk.com/document/dingstart/typewriter-effect-streaming-ai-card)创建 **AI 卡片**模板,然后在 `config.yaml` 中将 `card_template_id` 设为该模板 ID。同时需要申请 `Card.Streaming.Write` 和 `Card.Instance.Write` 权限。
**命令** **命令**
渠道连接完成后,你可以直接在聊天窗口里和 DeerFlow 交互: 渠道连接完成后,你可以直接在聊天窗口里和 DeerFlow 交互:
+65 -148
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@@ -7,13 +7,15 @@ This file provides guidance to Claude Code (claude.ai/code) when working with co
DeerFlow is a LangGraph-based AI super agent system with a full-stack architecture. The backend provides a "super agent" with sandbox execution, persistent memory, subagent delegation, and extensible tool integration - all operating in per-thread isolated environments. DeerFlow is a LangGraph-based AI super agent system with a full-stack architecture. The backend provides a "super agent" with sandbox execution, persistent memory, subagent delegation, and extensible tool integration - all operating in per-thread isolated environments.
**Architecture**: **Architecture**:
- **Gateway API** (port 8001): REST API plus embedded LangGraph-compatible agent runtime - **LangGraph Server** (port 2024): Agent runtime and workflow execution
- **Gateway API** (port 8001): REST API for models, MCP, skills, memory, artifacts, uploads, and local thread cleanup
- **Frontend** (port 3000): Next.js web interface - **Frontend** (port 3000): Next.js web interface
- **Nginx** (port 2026): Unified reverse proxy entry point - **Nginx** (port 2026): Unified reverse proxy entry point
- **Provisioner** (port 8002, optional in Docker dev): Started only when sandbox is configured for provisioner/Kubernetes mode - **Provisioner** (port 8002, optional in Docker dev): Started only when sandbox is configured for provisioner/Kubernetes mode
**Runtime**: **Runtime Modes**:
- `make dev`, Docker dev, and production all run the agent runtime in Gateway via `RunManager` + `run_agent()` + `StreamBridge` (`packages/harness/deerflow/runtime/`). Nginx exposes that runtime at `/api/langgraph/*` and rewrites it to Gateway's native `/api/*` routers. - **Standard mode** (`make dev`): LangGraph Server handles agent execution as a separate process. 4 processes total.
- **Gateway mode** (`make dev-pro`, experimental): Agent runtime embedded in Gateway via `RunManager` + `run_agent()` + `StreamBridge` (`packages/harness/deerflow/runtime/`). Service manages its own concurrency via async tasks. 3 processes total, no LangGraph Server.
**Project Structure**: **Project Structure**:
``` ```
@@ -23,7 +25,7 @@ deer-flow/
├── extensions_config.json # MCP servers and skills configuration ├── extensions_config.json # MCP servers and skills configuration
├── backend/ # Backend application (this directory) ├── backend/ # Backend application (this directory)
│ ├── Makefile # Backend-only commands (dev, gateway, lint) │ ├── Makefile # Backend-only commands (dev, gateway, lint)
│ ├── langgraph.json # LangGraph Studio graph configuration │ ├── langgraph.json # LangGraph server configuration
│ ├── packages/ │ ├── packages/
│ │ └── harness/ # deerflow-harness package (import: deerflow.*) │ │ └── harness/ # deerflow-harness package (import: deerflow.*)
│ │ ├── pyproject.toml │ │ ├── pyproject.toml
@@ -81,64 +83,26 @@ When making code changes, you MUST update the relevant documentation:
```bash ```bash
make check # Check system requirements make check # Check system requirements
make install # Install all dependencies (frontend + backend) make install # Install all dependencies (frontend + backend)
make dev # Start all services (Gateway + Frontend + Nginx), with config.yaml preflight make dev # Start all services (LangGraph + Gateway + Frontend + Nginx), with config.yaml preflight
make start # Start production services locally make dev-pro # Gateway mode (experimental): skip LangGraph, agent runtime embedded in Gateway
make start-pro # Production + Gateway mode (experimental)
make stop # Stop all services make stop # Stop all services
``` ```
**Backend directory** (for backend development only): **Backend directory** (for backend development only):
```bash ```bash
make install # Install backend dependencies make install # Install backend dependencies
make dev # Run Gateway API with reload (port 8001) make dev # Run LangGraph server only (port 2024)
make gateway # Run Gateway API only (port 8001) make gateway # Run Gateway API only (port 8001)
make test # Run all backend tests make test # Run all backend tests
make test-blocking-io # Run strict Blockbuster runtime gate on tests/blocking_io/ make lint # Lint with ruff
make lint # Lint with ruff make format # Format code with ruff
make format # Format code with ruff
``` ```
The `detect-blocking-io` target parses `app/`, `packages/harness/deerflow/`,
and `scripts/` with AST. By default it reports only blocking IO candidates that
are inside async code, reachable from async code in the same file, or reachable
from sync-only `AgentMiddleware` before/after hooks that LangGraph can execute
on the async graph path. It prints a concise summary and writes complete JSON
findings to `.deer-flow/blocking-io-findings.json` at the repository root
(both `make detect-blocking-io` from the repo root and `cd backend && make
detect-blocking-io` resolve to the same repo-root path). JSON findings include
`priority`, `location`, `blocking_call`, `event_loop_exposure`, `reason`, and
`code` for model-assisted or manual review. `priority` is a deterministic
review ordering from operation type, not proof of a bug. Bare-name same-file
calls are resolved by function name, so duplicate helper names in one file can
conservatively over-report async reachability. It is intentionally
informational and is not run from CI in this round.
Regression tests related to Docker/provisioner behavior: Regression tests related to Docker/provisioner behavior:
- `tests/test_docker_sandbox_mode_detection.py` (mode detection from `config.yaml`) - `tests/test_docker_sandbox_mode_detection.py` (mode detection from `config.yaml`)
- `tests/test_provisioner_kubeconfig.py` (kubeconfig file/directory handling) - `tests/test_provisioner_kubeconfig.py` (kubeconfig file/directory handling)
Blocking-IO runtime gate (`tests/blocking_io/`):
- Wraps every item under `tests/blocking_io/` with a strict Blockbuster
context scoped to `app.*` and `deerflow.*` (see
`tests/support/detectors/blocking_io_runtime.py`). Any sync blocking IO
call whose stack passes through DeerFlow business code while running on
the asyncio event loop raises `BlockingError` and fails the test.
- Regression anchors live there: `test_skills_load.py` (locks the
`asyncio.to_thread` offload around `LocalSkillStorage.load_skills`, fix
for #1917); `test_sqlite_lifespan.py` (locks the offload around
SQLite path resolution plus `ensure_sqlite_parent_dir`, fix for #1912);
`test_jsonl_run_event_store.py` (locks `JsonlRunEventStore`'s async
API offloading its file IO via `asyncio.to_thread`, fix #3084); and
`test_uploads_middleware.py` (locks `UploadsMiddleware.abefore_agent`
offloading the uploads-directory scan off the event loop).
- `test_gate_smoke.py` is a meta-test asserting the gate actually catches
unoffloaded blocking IO and that the `@pytest.mark.allow_blocking_io`
opt-out works.
- Coverage boundary: the gate only sees code that test execution actually
touches. Static AST coverage is a separate concern (out of scope for
this PR).
- CI: runs on every PR via `.github/workflows/backend-blocking-io-tests.yml`,
hard-fail.
Boundary check (harness → app import firewall): Boundary check (harness → app import firewall):
- `tests/test_harness_boundary.py` — ensures `packages/harness/deerflow/` never imports from `app.*` - `tests/test_harness_boundary.py` — ensures `packages/harness/deerflow/` never imports from `app.*`
@@ -151,7 +115,7 @@ CI runs these regression tests for every pull request via [.github/workflows/bac
The backend is split into two layers with a strict dependency direction: The backend is split into two layers with a strict dependency direction:
- **Harness** (`packages/harness/deerflow/`): Publishable agent framework package (`deerflow-harness`). Import prefix: `deerflow.*`. Contains agent orchestration, tools, sandbox, models, MCP, skills, config — everything needed to build and run agents. - **Harness** (`packages/harness/deerflow/`): Publishable agent framework package (`deerflow-harness`). Import prefix: `deerflow.*`. Contains agent orchestration, tools, sandbox, models, MCP, skills, config — everything needed to build and run agents.
- **App** (`app/`): Unpublished application code. Import prefix: `app.*`. Contains the FastAPI Gateway API and IM channel integrations (Feishu, Slack, Telegram, DingTalk). - **App** (`app/`): Unpublished application code. Import prefix: `app.*`. Contains the FastAPI Gateway API and IM channel integrations (Feishu, Slack, Telegram).
**Dependency rule**: App imports deerflow, but deerflow never imports app. This boundary is enforced by `tests/test_harness_boundary.py` which runs in CI. **Dependency rule**: App imports deerflow, but deerflow never imports app. This boundary is enforced by `tests/test_harness_boundary.py` which runs in CI.
@@ -192,26 +156,20 @@ from deerflow.config import get_app_config
### Middleware Chain ### Middleware Chain
Lead-agent middlewares are assembled in strict append order across `packages/harness/deerflow/agents/middlewares/tool_error_handling_middleware.py` (`build_lead_runtime_middlewares`) and `packages/harness/deerflow/agents/lead_agent/agent.py` (`_build_middlewares`): Middlewares execute in strict order in `packages/harness/deerflow/agents/lead_agent/agent.py`:
1. **ThreadDataMiddleware** - Creates per-thread directories under the user's isolation scope (`backend/.deer-flow/users/{user_id}/threads/{thread_id}/user-data/{workspace,uploads,outputs}`); resolves `user_id` via `get_effective_user_id()` (falls back to `"default"` in no-auth mode); Web UI thread deletion now follows LangGraph thread removal with Gateway cleanup of the local thread directory 1. **ThreadDataMiddleware** - Creates per-thread directories (`backend/.deer-flow/threads/{thread_id}/user-data/{workspace,uploads,outputs}`); Web UI thread deletion now follows LangGraph thread removal with Gateway cleanup of the local `.deer-flow/threads/{thread_id}` directory
2. **UploadsMiddleware** - Tracks and injects newly uploaded files into conversation 2. **UploadsMiddleware** - Tracks and injects newly uploaded files into conversation
3. **SandboxMiddleware** - Acquires sandbox, stores `sandbox_id` in state 3. **SandboxMiddleware** - Acquires sandbox, stores `sandbox_id` in state
4. **DanglingToolCallMiddleware** - Injects placeholder ToolMessages for AIMessage tool_calls that lack responses (e.g., due to user interruption), including raw provider tool-call payloads preserved only in `additional_kwargs["tool_calls"]` 4. **DanglingToolCallMiddleware** - Injects placeholder ToolMessages for AIMessage tool_calls that lack responses (e.g., due to user interruption)
5. **LLMErrorHandlingMiddleware** - Normalizes provider/model invocation failures into recoverable assistant-facing errors before later middleware/tool stages run 5. **GuardrailMiddleware** - Pre-tool-call authorization via pluggable `GuardrailProvider` protocol (optional, if `guardrails.enabled` in config). Evaluates each tool call and returns error ToolMessage on deny. Three provider options: built-in `AllowlistProvider` (zero deps), OAP policy providers (e.g. `aport-agent-guardrails`), or custom providers. See [docs/GUARDRAILS.md](docs/GUARDRAILS.md) for setup, usage, and how to implement a provider.
6. **GuardrailMiddleware** - Pre-tool-call authorization via pluggable `GuardrailProvider` protocol (optional, if `guardrails.enabled` in config). Evaluates each tool call and returns error ToolMessage on deny. Three provider options: built-in `AllowlistProvider` (zero deps), OAP policy providers (e.g. `aport-agent-guardrails`), or custom providers. See [docs/GUARDRAILS.md](docs/GUARDRAILS.md) for setup, usage, and how to implement a provider. 6. **SummarizationMiddleware** - Context reduction when approaching token limits (optional, if enabled)
7. **SandboxAuditMiddleware** - Audits sandboxed shell/file operations for security logging before tool execution continues 7. **TodoListMiddleware** - Task tracking with `write_todos` tool (optional, if plan_mode)
8. **ToolErrorHandlingMiddleware** - Converts tool exceptions into error `ToolMessage`s so the run can continue instead of aborting 8. **TitleMiddleware** - Auto-generates thread title after first complete exchange and normalizes structured message content before prompting the title model
9. **SummarizationMiddleware** - Context reduction when approaching token limits (optional, if enabled) 9. **MemoryMiddleware** - Queues conversations for async memory update (filters to user + final AI responses)
10. **TodoListMiddleware** - Task tracking with `write_todos` tool (optional, if plan_mode) 10. **ViewImageMiddleware** - Injects base64 image data before LLM call (conditional on vision support)
11. **TokenUsageMiddleware** - Records token usage metrics when token tracking is enabled (optional); subagent usage is cached by `tool_call_id` only while token usage is enabled and merged back into the dispatching AIMessage by message position rather than message id 11. **SubagentLimitMiddleware** - Truncates excess `task` tool calls from model response to enforce `MAX_CONCURRENT_SUBAGENTS` limit (optional, if subagent_enabled)
12. **TitleMiddleware** - Auto-generates thread title after first complete exchange and normalizes structured message content before prompting the title model 12. **ClarificationMiddleware** - Intercepts `ask_clarification` tool calls, interrupts via `Command(goto=END)` (must be last)
13. **MemoryMiddleware** - Queues conversations for async memory update (filters to user + final AI responses)
14. **ViewImageMiddleware** - Injects base64 image data before LLM call (conditional on vision support)
15. **DeferredToolFilterMiddleware** - Hides deferred (MCP) tool schemas from the bound model using a build-time deferred-name set + catalog hash, reading per-thread promotions from `ThreadState.promoted` (hash-scoped, no ContextVar); a tool becomes bound on subsequent turns after `tool_search` returns its schema (optional, if `tool_search.enabled`)
16. **SubagentLimitMiddleware** - Truncates excess `task` tool calls from model response to enforce `MAX_CONCURRENT_SUBAGENTS` limit (optional, if `subagent_enabled`)
17. **LoopDetectionMiddleware** - Detects repeated tool-call loops; hard-stop responses clear both structured `tool_calls` and raw provider tool-call metadata before forcing a final text answer
18. **ClarificationMiddleware** - Intercepts `ask_clarification` tool calls, interrupts via `Command(goto=END)` (must be last)
### Configuration System ### Configuration System
@@ -223,10 +181,6 @@ Setup: Copy `config.example.yaml` to `config.yaml` in the **project root** direc
**Config Caching**: `get_app_config()` caches the parsed config, but automatically reloads it when the resolved config path changes or the file's mtime increases. This keeps Gateway and LangGraph reads aligned with `config.yaml` edits without requiring a manual process restart. **Config Caching**: `get_app_config()` caches the parsed config, but automatically reloads it when the resolved config path changes or the file's mtime increases. This keeps Gateway and LangGraph reads aligned with `config.yaml` edits without requiring a manual process restart.
**Config Hot-Reload Boundary**: Gateway dependencies route through `get_app_config()` on every request, so per-run fields like `models[*].max_tokens`, `summarization.*`, `title.*`, `memory.*`, `subagents.*`, `tools[*]`, and the agent system prompt pick up `config.yaml` edits on the next message. `AppConfig` is intentionally **not** cached on `app.state``lifespan()` keeps a local `startup_config` variable for one-shot bootstrap work and passes it to `langgraph_runtime(app, startup_config)`.
Infrastructure fields are **restart-required**. The authoritative list lives in `packages/harness/deerflow/config/reload_boundary.py::STARTUP_ONLY_FIELDS` and is mirrored by the standardised `"startup-only:"` prefix on the corresponding `Field(description=...)` in `AppConfig`, so IDE hover on those fields surfaces the reason inline (no need to context-switch into this table). Currently registered: `database`, `checkpointer`, `run_events`, `stream_bridge`, `sandbox`, `log_level`, `channels`. Adding a new restart-required field requires updating the registry; drift is pinned by `tests/test_reload_boundary.py`.
Configuration priority: Configuration priority:
1. Explicit `config_path` argument 1. Explicit `config_path` argument
2. `DEER_FLOW_CONFIG_PATH` environment variable 2. `DEER_FLOW_CONFIG_PATH` environment variable
@@ -248,9 +202,7 @@ Configuration priority:
### Gateway API (`app/gateway/`) ### Gateway API (`app/gateway/`)
FastAPI application on port 8001 with health check at `GET /health`. Set `GATEWAY_ENABLE_DOCS=false` to disable `/docs`, `/redoc`, and `/openapi.json` in production (default: enabled). FastAPI application on port 8001 with health check at `GET /health`.
CORS is same-origin by default when requests enter through nginx on port 2026. Split-origin or port-forwarded browser clients must opt in with `GATEWAY_CORS_ORIGINS` (comma-separated exact origins); Gateway `CORSMiddleware` and `CSRFMiddleware` both read that variable so browser CORS and auth-origin checks stay aligned.
**Routers**: **Routers**:
@@ -264,38 +216,28 @@ CORS is same-origin by default when requests enter through nginx on port 2026. S
| **Threads** (`/api/threads/{id}`) | `DELETE /` - remove DeerFlow-managed local thread data after LangGraph thread deletion; unexpected failures are logged server-side and return a generic 500 detail | | **Threads** (`/api/threads/{id}`) | `DELETE /` - remove DeerFlow-managed local thread data after LangGraph thread deletion; unexpected failures are logged server-side and return a generic 500 detail |
| **Artifacts** (`/api/threads/{id}/artifacts`) | `GET /{path}` - serve artifacts; active content types (`text/html`, `application/xhtml+xml`, `image/svg+xml`) are always forced as download attachments to reduce XSS risk; `?download=true` still forces download for other file types | | **Artifacts** (`/api/threads/{id}/artifacts`) | `GET /{path}` - serve artifacts; active content types (`text/html`, `application/xhtml+xml`, `image/svg+xml`) are always forced as download attachments to reduce XSS risk; `?download=true` still forces download for other file types |
| **Suggestions** (`/api/threads/{id}/suggestions`) | `POST /` - generate follow-up questions; rich list/block model content is normalized before JSON parsing | | **Suggestions** (`/api/threads/{id}/suggestions`) | `POST /` - generate follow-up questions; rich list/block model content is normalized before JSON parsing |
| **Thread Runs** (`/api/threads/{id}/runs`) | `POST /` - create background run; `POST /stream` - create + SSE stream; `POST /wait` - create + block; `GET /` - list runs; `GET /{rid}` - run details; `POST /{rid}/cancel` - cancel; `GET /{rid}/join` - join SSE; `GET /{rid}/messages` - paginated messages `{data, has_more}`; `GET /{rid}/events` - full event stream; `GET /../messages` - thread messages with feedback; `GET /../token-usage` - aggregate tokens |
| **Feedback** (`/api/threads/{id}/runs/{rid}/feedback`) | `PUT /` - upsert feedback; `DELETE /` - delete user feedback; `POST /` - create feedback; `GET /` - list feedback; `GET /stats` - aggregate stats; `DELETE /{fid}` - delete specific |
| **Runs** (`/api/runs`) | `POST /stream` - stateless run + SSE; `POST /wait` - stateless run + block; `GET /{rid}/messages` - paginated messages by run_id `{data, has_more}` (cursor: `after_seq`/`before_seq`); `GET /{rid}/feedback` - list feedback by run_id |
**RunManager / RunStore contract**: Proxied through nginx: `/api/langgraph/*` → LangGraph, all other `/api/*` → Gateway.
- `RunManager.get()` is async; direct callers must `await` it.
- When a persistent `RunStore` is configured, `get()` and `list_by_thread()` hydrate historical runs from the store. In-memory records win for the same `run_id` so task, abort, and stream-control state stays attached to active local runs.
- `cancel()` and `create_or_reject(..., multitask_strategy="interrupt"|"rollback")` persist interrupted status through `RunStore.update_status()`, matching normal `set_status()` transitions.
- Store-only hydrated runs are readable history. If the current worker has no in-memory task/control state for that run, cancellation APIs can return 409 because this worker cannot stop the task.
- `POST /wait` (both thread-scoped and `/api/runs/wait`) drains the stream bridge via `wait_for_run_completion()` instead of bare `await record.task`, so it honours the run's `on_disconnect` setting and cancels the background run on real client disconnect rather than returning a stale checkpoint (issue #3265).
Proxied through nginx: `/api/langgraph/*` → Gateway LangGraph-compatible runtime, all other `/api/*` → Gateway REST APIs.
### Sandbox System (`packages/harness/deerflow/sandbox/`) ### Sandbox System (`packages/harness/deerflow/sandbox/`)
**Interface**: Abstract `Sandbox` with `execute_command`, `read_file`, `write_file`, `list_dir` **Interface**: Abstract `Sandbox` with `execute_command`, `read_file`, `write_file`, `list_dir`
**Provider Pattern**: `SandboxProvider` with `acquire`, `acquire_async`, `get`, `release` lifecycle. Async agent/tool paths call async sandbox lifecycle hooks so Docker sandbox creation, discovery, cross-process locking, readiness polling, and release stay off the event loop. **Provider Pattern**: `SandboxProvider` with `acquire`, `get`, `release` lifecycle
**Implementations**: **Implementations**:
- `LocalSandboxProvider` - Local filesystem execution. `acquire(thread_id)` returns a per-thread `LocalSandbox` (id `local:{thread_id}`) whose `path_mappings` resolve `/mnt/user-data/{workspace,uploads,outputs}` and `/mnt/acp-workspace` to that thread's host directories, so the public `Sandbox` API honours the `/mnt/user-data` contract uniformly with AIO. `acquire()` / `acquire(None)` keeps the legacy generic singleton (id `local`) for callers without a thread context. Per-thread sandboxes are held in an LRU cache (default 256 entries) guarded by a `threading.Lock`. - `LocalSandboxProvider` - Singleton local filesystem execution with path mappings
- `AioSandboxProvider` (`packages/harness/deerflow/community/`) - Docker-based isolation - `AioSandboxProvider` (`packages/harness/deerflow/community/`) - Docker-based isolation
**Virtual Path System**: **Virtual Path System**:
- Agent sees: `/mnt/user-data/{workspace,uploads,outputs}`, `/mnt/skills` - Agent sees: `/mnt/user-data/{workspace,uploads,outputs}`, `/mnt/skills`
- Physical: `backend/.deer-flow/users/{user_id}/threads/{thread_id}/user-data/...`, `deer-flow/skills/` - Physical: `backend/.deer-flow/threads/{thread_id}/user-data/...`, `deer-flow/skills/`
- Translation: `LocalSandboxProvider` builds per-thread `PathMapping`s for the user-data prefixes at acquire time; `tools.py` keeps `replace_virtual_path()` / `replace_virtual_paths_in_command()` as a defense-in-depth layer (and for path validation). AIO has the directories volume-mounted at the same virtual paths inside its container, so both implementations accept `/mnt/user-data/...` natively. - Translation: `replace_virtual_path()` / `replace_virtual_paths_in_command()`
- Detection: `is_local_sandbox()` accepts both `sandbox_id == "local"` (legacy / no-thread) and `sandbox_id.startswith("local:")` (per-thread) - Detection: `is_local_sandbox()` checks `sandbox_id == "local"`
**Sandbox Tools** (in `packages/harness/deerflow/sandbox/tools.py`): **Sandbox Tools** (in `packages/harness/deerflow/sandbox/tools.py`):
- `bash` - Execute commands with path translation and error handling - `bash` - Execute commands with path translation and error handling
- `ls` - Directory listing (tree format, max 2 levels) - `ls` - Directory listing (tree format, max 2 levels)
- `read_file` - Read file contents with optional line range - `read_file` - Read file contents with optional line range
- `write_file` - Write/append to files, creates directories; overwrites by default and exposes the `append` argument in the model-facing schema for end-of-file writes - `write_file` - Write/append to files, creates directories
- `str_replace` - Substring replacement (single or all occurrences); same-path serialization is scoped to `(sandbox.id, path)` so isolated sandboxes do not contend on identical virtual paths inside one process - `str_replace` - Substring replacement (single or all occurrences); same-path serialization is scoped to `(sandbox.id, path)` so isolated sandboxes do not contend on identical virtual paths inside one process
### Subagent System (`packages/harness/deerflow/subagents/`) ### Subagent System (`packages/harness/deerflow/subagents/`)
@@ -315,10 +257,8 @@ Proxied through nginx: `/api/langgraph/*` → Gateway LangGraph-compatible runti
- `present_files` - Make output files visible to user (only `/mnt/user-data/outputs`) - `present_files` - Make output files visible to user (only `/mnt/user-data/outputs`)
- `ask_clarification` - Request clarification (intercepted by ClarificationMiddleware → interrupts) - `ask_clarification` - Request clarification (intercepted by ClarificationMiddleware → interrupts)
- `view_image` - Read image as base64 (added only if model supports vision) - `view_image` - Read image as base64 (added only if model supports vision)
- `setup_agent` - Bootstrap-only: persist a brand-new custom agent's `SOUL.md` and `config.yaml`. Bound only when `is_bootstrap=True`.
- `update_agent` - Custom-agent-only: persist self-updates to the current agent's `SOUL.md` / `config.yaml` from inside a normal chat (partial update + atomic write). Bound when `agent_name` is set and `is_bootstrap=False`.
4. **Subagent tool** (if enabled): 4. **Subagent tool** (if enabled):
- `task` - Delegate to subagent (description, prompt, subagent_type) - `task` - Delegate to subagent (description, prompt, subagent_type, max_turns)
**Community tools** (`packages/harness/deerflow/community/`): **Community tools** (`packages/harness/deerflow/community/`):
- `tavily/` - Web search (5 results default) and web fetch (4KB limit) - `tavily/` - Web search (5 results default) and web fetch (4KB limit)
@@ -329,7 +269,7 @@ Proxied through nginx: `/api/langgraph/*` → Gateway LangGraph-compatible runti
- `invoke_acp_agent` - Invokes external ACP-compatible agents from `config.yaml` - `invoke_acp_agent` - Invokes external ACP-compatible agents from `config.yaml`
- ACP launchers must be real ACP adapters. The standard `codex` CLI is not ACP-compatible by itself; configure a wrapper such as `npx -y @zed-industries/codex-acp` or an installed `codex-acp` binary - ACP launchers must be real ACP adapters. The standard `codex` CLI is not ACP-compatible by itself; configure a wrapper such as `npx -y @zed-industries/codex-acp` or an installed `codex-acp` binary
- Missing ACP executables now return an actionable error message instead of a raw `[Errno 2]` - Missing ACP executables now return an actionable error message instead of a raw `[Errno 2]`
- Each ACP agent uses a per-thread workspace at `{base_dir}/users/{user_id}/threads/{thread_id}/acp-workspace/`. The workspace is accessible to the lead agent via the virtual path `/mnt/acp-workspace/` (read-only). In docker sandbox mode, the directory is volume-mounted into the container at `/mnt/acp-workspace` (read-only); in local sandbox mode, path translation is handled by `tools.py` - Each ACP agent uses a per-thread workspace at `{base_dir}/threads/{thread_id}/acp-workspace/`. The workspace is accessible to the lead agent via the virtual path `/mnt/acp-workspace/` (read-only). In docker sandbox mode, the directory is volume-mounted into the container at `/mnt/acp-workspace` (read-only); in local sandbox mode, path translation is handled by `tools.py`
- `image_search/` - Image search via DuckDuckGo - `image_search/` - Image search via DuckDuckGo
### MCP System (`packages/harness/deerflow/mcp/`) ### MCP System (`packages/harness/deerflow/mcp/`)
@@ -339,7 +279,7 @@ Proxied through nginx: `/api/langgraph/*` → Gateway LangGraph-compatible runti
- **Cache invalidation**: Detects config file changes via mtime comparison - **Cache invalidation**: Detects config file changes via mtime comparison
- **Transports**: stdio (command-based), SSE, HTTP - **Transports**: stdio (command-based), SSE, HTTP
- **OAuth (HTTP/SSE)**: Supports token endpoint flows (`client_credentials`, `refresh_token`) with automatic token refresh + Authorization header injection - **OAuth (HTTP/SSE)**: Supports token endpoint flows (`client_credentials`, `refresh_token`) with automatic token refresh + Authorization header injection
- **Runtime updates**: Gateway API saves to extensions_config.json; the Gateway-embedded runtime detects changes via mtime - **Runtime updates**: Gateway API saves to extensions_config.json; LangGraph detects via mtime
### Skills System (`packages/harness/deerflow/skills/`) ### Skills System (`packages/harness/deerflow/skills/`)
@@ -366,10 +306,9 @@ Proxied through nginx: `/api/langgraph/*` → Gateway LangGraph-compatible runti
### IM Channels System (`app/channels/`) ### IM Channels System (`app/channels/`)
Bridges external messaging platforms (Feishu, Slack, Telegram, DingTalk) to the DeerFlow agent via Gateway's LangGraph-compatible API. Bridges external messaging platforms (Feishu, Slack, Telegram) to the DeerFlow agent via the LangGraph Server.
**Architecture**: Channels communicate with the LangGraph Server through `langgraph-sdk` HTTP client (same as the frontend), ensuring threads are created and managed server-side.
**Architecture**: Channels communicate with Gateway through the `langgraph-sdk` HTTP client (same as the frontend), ensuring threads are created and managed server-side. The internal SDK client injects process-local internal auth plus a matching CSRF cookie/header pair so Gateway accepts state-changing thread/run requests from channel workers without relying on browser session cookies.
**Components**: **Components**:
- `message_bus.py` - Async pub/sub hub (`InboundMessage` → queue → dispatcher; `OutboundMessage` → callbacks → channels) - `message_bus.py` - Async pub/sub hub (`InboundMessage` → queue → dispatcher; `OutboundMessage` → callbacks → channels)
@@ -377,52 +316,40 @@ Bridges external messaging platforms (Feishu, Slack, Telegram, DingTalk) to the
- `manager.py` - Core dispatcher: creates threads via `client.threads.create()`, routes commands, keeps Slack/Telegram on `client.runs.wait()`, and uses `client.runs.stream(["messages-tuple", "values"])` for Feishu incremental outbound updates - `manager.py` - Core dispatcher: creates threads via `client.threads.create()`, routes commands, keeps Slack/Telegram on `client.runs.wait()`, and uses `client.runs.stream(["messages-tuple", "values"])` for Feishu incremental outbound updates
- `base.py` - Abstract `Channel` base class (start/stop/send lifecycle) - `base.py` - Abstract `Channel` base class (start/stop/send lifecycle)
- `service.py` - Manages lifecycle of all configured channels from `config.yaml` - `service.py` - Manages lifecycle of all configured channels from `config.yaml`
- `slack.py` / `feishu.py` / `telegram.py` / `dingtalk.py` - Platform-specific implementations (`feishu.py` tracks the running card `message_id` in memory and patches the same card in place; `dingtalk.py` optionally uses AI Card streaming for in-place updates when `card_template_id` is configured) - `slack.py` / `feishu.py` / `telegram.py` - Platform-specific implementations (`feishu.py` tracks the running card `message_id` in memory and patches the same card in place)
**Message Flow**: **Message Flow**:
1. External platform -> Channel impl -> `MessageBus.publish_inbound()` 1. External platform -> Channel impl -> `MessageBus.publish_inbound()`
2. `ChannelManager._dispatch_loop()` consumes from queue 2. `ChannelManager._dispatch_loop()` consumes from queue
3. For chat: look up/create thread through Gateway's LangGraph-compatible API 3. For chat: look up/create thread on LangGraph Server
4. Feishu chat: `runs.stream()` → accumulate AI text → publish multiple outbound updates (`is_final=False`) → publish final outbound (`is_final=True`) 4. Feishu chat: `runs.stream()` → accumulate AI text → publish multiple outbound updates (`is_final=False`) → publish final outbound (`is_final=True`)
5. Slack/Telegram chat: `runs.wait()` → extract final response → publish outbound 5. Slack/Telegram chat: `runs.wait()` → extract final response → publish outbound
6. Feishu channel sends one running reply card up front, then patches the same card for each outbound update (card JSON sets `config.update_multi=true` for Feishu's patch API requirement) 6. Feishu channel sends one running reply card up front, then patches the same card for each outbound update (card JSON sets `config.update_multi=true` for Feishu's patch API requirement)
7. DingTalk AI Card mode (when `card_template_id` configured): `runs.stream()` → create card with initial text → stream updates via `PUT /v1.0/card/streaming` → finalize on `is_final=True`. Falls back to `sampleMarkdown` if card creation or streaming fails 7. For commands (`/new`, `/status`, `/models`, `/memory`, `/help`): handle locally or query Gateway API
8. For commands (`/new`, `/status`, `/models`, `/memory`, `/help`): handle locally or query Gateway API 8. Outbound → channel callbacks → platform reply
9. Outbound → channel callbacks → platform reply
**Configuration** (`config.yaml` -> `channels`): **Configuration** (`config.yaml` -> `channels`):
- `langgraph_url` - LangGraph-compatible Gateway API base URL (default: `http://localhost:8001/api`) - `langgraph_url` - LangGraph Server URL (default: `http://localhost:2024`)
- `gateway_url` - Gateway API URL for auxiliary commands (default: `http://localhost:8001`) - `gateway_url` - Gateway API URL for auxiliary commands (default: `http://localhost:8001`)
- In Docker Compose, IM channels run inside the `gateway` container, so `localhost` points back to that container. Use `http://gateway:8001/api` for `langgraph_url` and `http://gateway:8001` for `gateway_url`, or set `DEER_FLOW_CHANNELS_LANGGRAPH_URL` / `DEER_FLOW_CHANNELS_GATEWAY_URL`. - In Docker Compose, IM channels run inside the `gateway` container, so `localhost` points back to that container. Use `http://langgraph:2024` / `http://gateway:8001`, or set `DEER_FLOW_CHANNELS_LANGGRAPH_URL` / `DEER_FLOW_CHANNELS_GATEWAY_URL`.
- Per-channel configs: `feishu` (app_id, app_secret), `slack` (bot_token, app_token), `telegram` (bot_token), `dingtalk` (client_id, client_secret, optional `card_template_id` for AI Card streaming) - Per-channel configs: `feishu` (app_id, app_secret), `slack` (bot_token, app_token), `telegram` (bot_token)
### Memory System (`packages/harness/deerflow/agents/memory/`) ### Memory System (`packages/harness/deerflow/agents/memory/`)
**Components**: **Components**:
- `updater.py` - LLM-based memory updates with fact extraction, whitespace-normalized fact deduplication (trims leading/trailing whitespace before comparing), and atomic file I/O - `updater.py` - LLM-based memory updates with fact extraction, whitespace-normalized fact deduplication (trims leading/trailing whitespace before comparing), and atomic file I/O
- `queue.py` - Debounced update queue (per-thread deduplication, configurable wait time); captures `user_id` at enqueue time so it survives the `threading.Timer` boundary - `queue.py` - Debounced update queue (per-thread deduplication, configurable wait time)
- `prompt.py` - Prompt templates for memory updates - `prompt.py` - Prompt templates for memory updates
- `storage.py` - File-based storage with per-user isolation; cache keyed by `(user_id, agent_name)` tuple
**Per-User Isolation**: **Data Structure** (stored in `backend/.deer-flow/memory.json`):
- Memory is stored per-user at `{base_dir}/users/{user_id}/memory.json`
- Per-agent per-user memory at `{base_dir}/users/{user_id}/agents/{agent_name}/memory.json`
- Custom agent definitions (`SOUL.md` + `config.yaml`) are also per-user at `{base_dir}/users/{user_id}/agents/{agent_name}/`. The legacy shared layout `{base_dir}/agents/{agent_name}/` remains read-only fallback for unmigrated installations
- `user_id` is resolved via `get_effective_user_id()` from `deerflow.runtime.user_context`
- In no-auth mode, `user_id` defaults to `"default"` (constant `DEFAULT_USER_ID`)
- Absolute `storage_path` in config opts out of per-user isolation
- **Migration**: Run `PYTHONPATH=. python scripts/migrate_user_isolation.py` to move legacy `memory.json`, `threads/`, and `agents/` into per-user layout. Supports `--dry-run` (preview changes) and `--user-id USER_ID` (assign unowned legacy data to a user, defaults to `default`).
**Data Structure** (stored in `{base_dir}/users/{user_id}/memory.json`):
- **User Context**: `workContext`, `personalContext`, `topOfMind` (1-3 sentence summaries) - **User Context**: `workContext`, `personalContext`, `topOfMind` (1-3 sentence summaries)
- **History**: `recentMonths`, `earlierContext`, `longTermBackground` - **History**: `recentMonths`, `earlierContext`, `longTermBackground`
- **Facts**: Discrete facts with `id`, `content`, `category` (preference/knowledge/context/behavior/goal), `confidence` (0-1), `createdAt`, `source` - **Facts**: Discrete facts with `id`, `content`, `category` (preference/knowledge/context/behavior/goal), `confidence` (0-1), `createdAt`, `source`
**Workflow**: **Workflow**:
1. `MemoryMiddleware` filters messages (user inputs + final AI responses), captures `user_id` via `get_effective_user_id()`, and queues conversation with the captured `user_id` 1. `MemoryMiddleware` filters messages (user inputs + final AI responses) and queues conversation
2. Queue debounces (30s default), batches updates, deduplicates per-thread 2. Queue debounces (30s default), batches updates, deduplicates per-thread
3. Background thread invokes LLM to extract context updates and facts, using the stored `user_id` (not the contextvar, which is unavailable on timer threads) 3. Background thread invokes LLM to extract context updates and facts
4. Applies updates atomically (temp file + rename) with cache invalidation, skipping duplicate fact content before append 4. Applies updates atomically (temp file + rename) with cache invalidation, skipping duplicate fact content before append
5. Next interaction injects top 15 facts + context into `<memory>` tags in system prompt 5. Next interaction injects top 15 facts + context into `<memory>` tags in system prompt
@@ -430,7 +357,7 @@ Focused regression coverage for the updater lives in `backend/tests/test_memory_
**Configuration** (`config.yaml``memory`): **Configuration** (`config.yaml``memory`):
- `enabled` / `injection_enabled` - Master switches - `enabled` / `injection_enabled` - Master switches
- `storage_path` - Path to memory.json (absolute path opts out of per-user isolation) - `storage_path` - Path to memory.json
- `debounce_seconds` - Wait time before processing (default: 30) - `debounce_seconds` - Wait time before processing (default: 30)
- `model_name` - LLM for updates (null = default model) - `model_name` - LLM for updates (null = default model)
- `max_facts` / `fact_confidence_threshold` - Fact storage limits (100 / 0.7) - `max_facts` / `fact_confidence_threshold` - Fact storage limits (100 / 0.7)
@@ -441,24 +368,6 @@ Focused regression coverage for the updater lives in `backend/tests/test_memory_
- `resolve_variable(path)` - Import module and return variable (e.g., `module.path:variable_name`) - `resolve_variable(path)` - Import module and return variable (e.g., `module.path:variable_name`)
- `resolve_class(path, base_class)` - Import and validate class against base class - `resolve_class(path, base_class)` - Import and validate class against base class
### Tracing System (`packages/harness/deerflow/tracing/`)
LangSmith and Langfuse are both supported. The wiring lives in two layers:
- `factory.py::build_tracing_callbacks()` — returns the LangChain `CallbackHandler` list for the providers currently enabled via env vars (`LANGSMITH_TRACING`, `LANGFUSE_TRACING`, etc.). The handlers are attached at the **graph invocation root** for in-graph runs (`make_lead_agent` and `DeerFlowClient.stream` both append them to `config["callbacks"]` before invoking the graph) so a single run produces one trace with all node / LLM / tool calls as child spans. Standalone callers — anything that invokes a model outside such a graph (e.g. `MemoryUpdater`) — keep `create_chat_model`'s default `attach_tracing=True`, which falls back to model-level callback attachment.
- `metadata.py::build_langfuse_trace_metadata()` — builds the Langfuse-reserved trace attributes for `RunnableConfig.metadata`. The Langfuse v4 `langchain.CallbackHandler` lifts these onto the root trace (see its `_parse_langfuse_trace_attributes`), but only when it sees `on_chain_start(parent_run_id=None)` — which is why the callbacks have to live at the graph root, not the model.
**Trace-attribute injection points**: both `runtime/runs/worker.py::run_agent` (gateway path) and `client.py::DeerFlowClient.stream` (embedded path) merge the metadata into `config["metadata"]` right before constructing the graph. Caller-supplied keys win via `setdefault`, so an external `session_id` override is preserved. Field mapping:
| Langfuse field | Source |
|-----------------------|----------------------------------------------|
| `langfuse_session_id` | LangGraph `thread_id` |
| `langfuse_user_id` | `get_effective_user_id()` (`default` in no-auth) |
| `langfuse_trace_name` | `RunRecord.assistant_id` / client `agent_name` (defaults to `lead-agent`) |
| `langfuse_tags` | `env:<DEER_FLOW_ENV>` + `model:<model_name>` |
Returns `{}` when Langfuse is not in the enabled providers — LangSmith-only deployments are unaffected. Set `DEER_FLOW_ENV` (or `ENVIRONMENT`) to tag traces by deployment environment. Tests live in `tests/test_tracing_factory.py`, `tests/test_tracing_metadata.py`, `tests/test_worker_langfuse_metadata.py`, and `tests/test_client_langfuse_metadata.py`.
### Config Schema ### Config Schema
**`config.yaml`** key sections: **`config.yaml`** key sections:
@@ -483,9 +392,9 @@ Both can be modified at runtime via Gateway API endpoints or `DeerFlowClient` me
`DeerFlowClient` provides direct in-process access to all DeerFlow capabilities without HTTP services. All return types align with the Gateway API response schemas, so consumer code works identically in HTTP and embedded modes. `DeerFlowClient` provides direct in-process access to all DeerFlow capabilities without HTTP services. All return types align with the Gateway API response schemas, so consumer code works identically in HTTP and embedded modes.
**Architecture**: Imports the same `deerflow` modules that Gateway API uses. Shares the same config files and data directories. No FastAPI dependency. **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**: **Agent Conversation** (replaces LangGraph Server):
- `chat(message, thread_id)` — synchronous, accumulates streaming deltas per message-id and returns the final AI text - `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`: - `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 - `"values"` — full state snapshot (title, messages, artifacts); AI text already delivered via `messages` mode is **not** re-synthesized here to avoid duplicate deliveries
@@ -548,15 +457,20 @@ This starts all services and makes the application available at `http://localhos
| | **Local Foreground** | **Local Daemon** | **Docker Dev** | **Docker Prod** | | | **Local Foreground** | **Local Daemon** | **Docker Dev** | **Docker Prod** |
|---|---|---|---|---| |---|---|---|---|---|
| **Dev** | `./scripts/serve.sh --dev`<br/>`make dev` | `./scripts/serve.sh --dev --daemon`<br/>`make dev-daemon` | `./scripts/docker.sh start`<br/>`make docker-start` | — | | **Dev** | `./scripts/serve.sh --dev`<br/>`make dev` | `./scripts/serve.sh --dev --daemon`<br/>`make dev-daemon` | `./scripts/docker.sh start`<br/>`make docker-start` | — |
| **Dev + Gateway** | `./scripts/serve.sh --dev --gateway`<br/>`make dev-pro` | `./scripts/serve.sh --dev --gateway --daemon`<br/>`make dev-daemon-pro` | `./scripts/docker.sh start --gateway`<br/>`make docker-start-pro` | — |
| **Prod** | `./scripts/serve.sh --prod`<br/>`make start` | `./scripts/serve.sh --prod --daemon`<br/>`make start-daemon` | — | `./scripts/deploy.sh`<br/>`make up` | | **Prod** | `./scripts/serve.sh --prod`<br/>`make start` | `./scripts/serve.sh --prod --daemon`<br/>`make start-daemon` | — | `./scripts/deploy.sh`<br/>`make up` |
| **Prod + Gateway** | `./scripts/serve.sh --prod --gateway`<br/>`make start-pro` | `./scripts/serve.sh --prod --gateway --daemon`<br/>`make start-daemon-pro` | — | `./scripts/deploy.sh --gateway`<br/>`make up-pro` |
| Action | Local | Docker Dev | Docker Prod | | Action | Local | Docker Dev | Docker Prod |
|---|---|---|---| |---|---|---|---|
| **Stop** | `./scripts/serve.sh --stop`<br/>`make stop` | `./scripts/docker.sh stop`<br/>`make docker-stop` | `./scripts/deploy.sh down`<br/>`make down` | | **Stop** | `./scripts/serve.sh --stop`<br/>`make stop` | `./scripts/docker.sh stop`<br/>`make docker-stop` | `./scripts/deploy.sh down`<br/>`make down` |
| **Restart** | `./scripts/serve.sh --restart [flags]` | `./scripts/docker.sh restart` | — | | **Restart** | `./scripts/serve.sh --restart [flags]` | `./scripts/docker.sh restart` | — |
Gateway mode embeds the agent runtime in Gateway, no LangGraph server.
**Nginx routing**: **Nginx routing**:
- `/api/langgraph/*`Gateway embedded runtime (8001), rewritten to `/api/*` - Standard mode: `/api/langgraph/*`LangGraph Server (2024)
- Gateway mode: `/api/langgraph/*` → Gateway embedded runtime (8001) (via envsubst)
- `/api/*` (other) → Gateway API (8001) - `/api/*` (other) → Gateway API (8001)
- `/` (non-API) → Frontend (3000) - `/` (non-API) → Frontend (3000)
@@ -565,11 +479,15 @@ This starts all services and makes the application available at `http://localhos
From the **backend** directory: From the **backend** directory:
```bash ```bash
# Gateway API # Terminal 1: LangGraph server
make dev
# Terminal 2: Gateway API
make gateway make gateway
``` ```
Direct access (without nginx): Direct access (without nginx):
- LangGraph: `http://localhost:2024`
- Gateway: `http://localhost:8001` - Gateway: `http://localhost:8001`
### Frontend Configuration ### Frontend Configuration
@@ -590,7 +508,6 @@ Multi-file upload with automatic document conversion:
- Rejects directory inputs before copying so uploads stay all-or-nothing - Rejects directory inputs before copying so uploads stay all-or-nothing
- Reuses one conversion worker per request when called from an active event loop - Reuses one conversion worker per request when called from an active event loop
- Files stored in thread-isolated directories - Files stored in thread-isolated directories
- Duplicate filenames in a single upload request are auto-renamed with `_N` suffixes so later files do not truncate earlier files
- Agent receives uploaded file list via `UploadsMiddleware` - Agent receives uploaded file list via `UploadsMiddleware`
See [docs/FILE_UPLOAD.md](docs/FILE_UPLOAD.md) for details. See [docs/FILE_UPLOAD.md](docs/FILE_UPLOAD.md) for details.
+4 -1
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@@ -56,8 +56,11 @@ export OPENAI_API_KEY="your-api-key"
### Run the Development Server ### Run the Development Server
```bash ```bash
# Gateway API + embedded agent runtime # Terminal 1: LangGraph server
make dev make dev
# Terminal 2: Gateway API
make gateway
``` ```
## Project Structure ## Project Structure
+3 -13
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@@ -50,12 +50,6 @@ COPY backend ./backend
RUN --mount=type=cache,target=/root/.cache/uv \ RUN --mount=type=cache,target=/root/.cache/uv \
sh -c "cd backend && UV_INDEX_URL=${UV_INDEX_URL:-https://pypi.org/simple} uv sync ${UV_EXTRAS:+--extra $UV_EXTRAS}" sh -c "cd backend && UV_INDEX_URL=${UV_INDEX_URL:-https://pypi.org/simple} uv sync ${UV_EXTRAS:+--extra $UV_EXTRAS}"
# UTF-8 locale prevents UnicodeEncodeError on Chinese/emoji content in minimal
# containers where locale configuration may be missing and the default encoding is not UTF-8.
ENV LANG=C.UTF-8
ENV LC_ALL=C.UTF-8
ENV PYTHONIOENCODING=utf-8
# ── Stage 2: Dev ────────────────────────────────────────────────────────────── # ── Stage 2: Dev ──────────────────────────────────────────────────────────────
# Retains compiler toolchain from builder so startup-time `uv sync` can build # Retains compiler toolchain from builder so startup-time `uv sync` can build
# source distributions in development containers. # source distributions in development containers.
@@ -64,7 +58,7 @@ FROM builder AS dev
# Install Docker CLI (for DooD: allows starting sandbox containers via host Docker socket) # Install Docker CLI (for DooD: allows starting sandbox containers via host Docker socket)
COPY --from=docker:cli /usr/local/bin/docker /usr/local/bin/docker COPY --from=docker:cli /usr/local/bin/docker /usr/local/bin/docker
EXPOSE 8001 EXPOSE 8001 2024
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 uvicorn app.gateway.app:app --host 0.0.0.0 --port 8001"]
@@ -72,10 +66,6 @@ CMD ["sh", "-c", "cd backend && PYTHONPATH=. uv run uvicorn app.gateway.app:app
# Clean image without build-essential — reduces size (~200 MB) and attack surface. # Clean image without build-essential — reduces size (~200 MB) and attack surface.
FROM python:3.12-slim-bookworm FROM python:3.12-slim-bookworm
ENV LANG=C.UTF-8
ENV LC_ALL=C.UTF-8
ENV PYTHONIOENCODING=utf-8
# Copy Node.js runtime from builder (provides npx for MCP servers) # Copy Node.js runtime from builder (provides npx for MCP servers)
COPY --from=builder /usr/bin/node /usr/bin/node COPY --from=builder /usr/bin/node /usr/bin/node
COPY --from=builder /usr/lib/node_modules /usr/lib/node_modules COPY --from=builder /usr/lib/node_modules /usr/lib/node_modules
@@ -94,8 +84,8 @@ WORKDIR /app
# Copy backend with pre-built virtualenv from builder # Copy backend with pre-built virtualenv from builder
COPY --from=builder /app/backend ./backend COPY --from=builder /app/backend ./backend
# Expose Gateway API port. # Expose ports (gateway: 8001, langgraph: 2024)
EXPOSE 8001 EXPOSE 8001 2024
# Default command (can be overridden in docker-compose) # Default command (can be overridden in docker-compose)
CMD ["sh", "-c", "cd backend && PYTHONPATH=. uv run --no-sync 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"]
+3 -9
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@@ -2,16 +2,13 @@ install:
uv sync uv sync
dev: dev:
PYTHONPATH=. PYTHONIOENCODING=utf-8 PYTHONUTF8=1 uv run uvicorn app.gateway.app:app --host 0.0.0.0 --port 8001 --reload uv run langgraph dev --no-browser --no-reload --n-jobs-per-worker 10
gateway: gateway:
PYTHONPATH=. PYTHONIOENCODING=utf-8 PYTHONUTF8=1 uv run uvicorn app.gateway.app:app --host 0.0.0.0 --port 8001 PYTHONPATH=. uv run uvicorn app.gateway.app:app --host 0.0.0.0 --port 8001
test: test:
PYTHONPATH=. PYTHONIOENCODING=utf-8 PYTHONUTF8=1 uv run pytest tests/ -v PYTHONPATH=. uv run pytest tests/ -v
test-blocking-io:
PYTHONPATH=. PYTHONIOENCODING=utf-8 PYTHONUTF8=1 uv run pytest tests/blocking_io -q --tb=short
lint: lint:
uvx ruff check . uvx ruff check .
@@ -19,6 +16,3 @@ lint:
format: format:
uvx ruff check . --fix && uvx ruff format . uvx ruff check . --fix && uvx ruff format .
detect-blocking-io:
@PYTHONPATH=. PYTHONIOENCODING=utf-8 PYTHONUTF8=1 uv run python ../scripts/detect_blocking_io_static.py --output ../.deer-flow/blocking-io-findings.json
+34 -43
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@@ -11,26 +11,31 @@ DeerFlow is a LangGraph-based AI super agent with sandbox execution, persistent
│ Nginx (Port 2026) │ │ Nginx (Port 2026) │
│ Unified reverse proxy │ │ Unified reverse proxy │
└───────┬──────────────────┬───────────┘ └───────┬──────────────────┬───────────┘
/api/langgraph/* │ /api/* (other) /api/langgraph/* │ /api/* (other)
rewritten to /api/* │ ▼ ▼
┌────────────────────┐ ┌────────────────────────┐
┌────────────────────────────────────────┐ │ LangGraph Server │ │ Gateway API (8001) │
Gateway API (8001) (Port 2024) │ FastAPI REST
FastAPI REST + agent runtime │ │
┌────────────────┐ │ │ Models, MCP, Skills,
Models, MCP, Skills, Memory, Uploads, │ │ Lead Agent │ │ │ Memory, Uploads,
Artifacts, Threads, Runs, Streaming │ ┌──────────┐ │ │ │ Artifacts
│ │Middleware│ │ │ └────────────────────────┘
┌────────────────────────────────────┐ │ │ Chain │ │
│ │ Lead Agent │ │ │ │ └──────────┘ │ │
│ │ Middleware Chain, Tools, Subagents │ │ │ │ ┌──────────┐ │ │
└────────────────────────────────────┘ │ │ Tools │ │
└──────────────────────────────────────── │ │ └──────────┘ │ │
│ │ ┌──────────┐ │ │
│ │ │Subagents │ │ │
│ │ └──────────┘ │ │
│ └────────────────┘ │
└────────────────────┘
``` ```
**Request Routing** (via Nginx): **Request Routing** (via Nginx):
- `/api/langgraph/*` Gateway LangGraph-compatible API - agent interactions, threads, streaming - `/api/langgraph/*` → LangGraph Server - agent interactions, threads, streaming
- `/api/*` (other) → Gateway API - models, MCP, skills, memory, artifacts, uploads, thread-local cleanup - `/api/*` (other) → Gateway API - models, MCP, skills, memory, artifacts, uploads, thread-local cleanup
- `/` (non-API) → Frontend - Next.js web interface - `/` (non-API) → Frontend - Next.js web interface
@@ -69,12 +74,12 @@ Middlewares execute in strict order, each handling a specific concern:
Per-thread isolated execution with virtual path translation: Per-thread isolated execution with virtual path translation:
- **Abstract interface**: `execute_command`, `read_file`, `write_file`, `list_dir` - **Abstract interface**: `execute_command`, `read_file`, `write_file`, `list_dir`
- **Providers**: `LocalSandboxProvider` (filesystem) and `AioSandboxProvider` (Docker, in community/). Async runtime paths use async sandbox lifecycle hooks so startup, readiness polling, and release do not block the event loop. - **Providers**: `LocalSandboxProvider` (filesystem) and `AioSandboxProvider` (Docker, in community/)
- **Virtual paths**: `/mnt/user-data/{workspace,uploads,outputs}` → thread-specific physical directories - **Virtual paths**: `/mnt/user-data/{workspace,uploads,outputs}` → thread-specific physical directories
- **Skills path**: `/mnt/skills``deer-flow/skills/` directory - **Skills path**: `/mnt/skills``deer-flow/skills/` directory
- **Skills loading**: Recursively discovers nested `SKILL.md` files under `skills/{public,custom}` and preserves nested container paths - **Skills loading**: Recursively discovers nested `SKILL.md` files under `skills/{public,custom}` and preserves nested container paths
- **File-write safety**: `str_replace` serializes read-modify-write per `(sandbox.id, path)` so isolated sandboxes keep concurrency even when virtual paths match - **File-write safety**: `str_replace` serializes read-modify-write per `(sandbox.id, path)` so isolated sandboxes keep concurrency even when virtual paths match
- **Tools**: `bash`, `ls`, `read_file`, `write_file`, `str_replace` (`write_file` overwrites by default and exposes `append` for end-of-file writes; `bash` is disabled by default when using `LocalSandboxProvider`; use `AioSandboxProvider` for isolated shell access) - **Tools**: `bash`, `ls`, `read_file`, `write_file`, `str_replace` (`bash` is disabled by default when using `LocalSandboxProvider`; use `AioSandboxProvider` for isolated shell access)
### Subagent System ### Subagent System
@@ -119,7 +124,7 @@ FastAPI application providing REST endpoints for frontend integration:
| `POST /api/memory/reload` | Force memory reload | | `POST /api/memory/reload` | Force memory reload |
| `GET /api/memory/config` | Memory configuration | | `GET /api/memory/config` | Memory configuration |
| `GET /api/memory/status` | Combined config + data | | `GET /api/memory/status` | Combined config + data |
| `POST /api/threads/{id}/uploads` | Upload files (auto-converts PDF/PPT/Excel/Word to Markdown, rejects directory paths, auto-renames duplicate filenames in one request) | | `POST /api/threads/{id}/uploads` | Upload files (auto-converts PDF/PPT/Excel/Word to Markdown, rejects directory paths) |
| `GET /api/threads/{id}/uploads/list` | List uploaded files | | `GET /api/threads/{id}/uploads/list` | List uploaded files |
| `DELETE /api/threads/{id}` | Delete DeerFlow-managed local thread data after LangGraph thread deletion; unexpected failures are logged server-side and return a generic 500 detail | | `DELETE /api/threads/{id}` | Delete DeerFlow-managed local thread data after LangGraph thread deletion; unexpected failures are logged server-side and return a generic 500 detail |
| `GET /api/threads/{id}/artifacts/{path}` | Serve generated artifacts | | `GET /api/threads/{id}/artifacts/{path}` | Serve generated artifacts |
@@ -188,7 +193,7 @@ export OPENAI_API_KEY="your-api-key-here"
**Full Application** (from project root): **Full Application** (from project root):
```bash ```bash
make dev # Starts Gateway + Frontend + Nginx make dev # Starts LangGraph + Gateway + Frontend + Nginx
``` ```
Access at: http://localhost:2026 Access at: http://localhost:2026
@@ -196,11 +201,14 @@ Access at: http://localhost:2026
**Backend Only** (from backend directory): **Backend Only** (from backend directory):
```bash ```bash
# Gateway API + embedded agent runtime # Terminal 1: LangGraph server
make dev make dev
# Terminal 2: Gateway API
make gateway
``` ```
Direct access: Gateway at http://localhost:8001 Direct access: LangGraph at http://localhost:2024, Gateway at http://localhost:8001
--- ---
@@ -236,16 +244,12 @@ backend/
│ └── utils/ # Utilities │ └── utils/ # Utilities
├── docs/ # Documentation ├── docs/ # Documentation
├── tests/ # Test suite ├── tests/ # Test suite
├── langgraph.json # LangGraph graph registry for tooling/Studio compatibility ├── langgraph.json # LangGraph server configuration
├── pyproject.toml # Python dependencies ├── pyproject.toml # Python dependencies
├── Makefile # Development commands ├── Makefile # Development commands
└── Dockerfile # Container build └── Dockerfile # Container build
``` ```
`langgraph.json` is not the default service entrypoint. The scripts and Docker
deployments run the Gateway embedded runtime; the file is kept for LangGraph
tooling, Studio, or direct LangGraph Server compatibility.
--- ---
## Configuration ## Configuration
@@ -358,11 +362,10 @@ If a provider is explicitly enabled but required credentials are missing, or the
```bash ```bash
make install # Install dependencies make install # Install dependencies
make dev # Run Gateway API + embedded agent runtime (port 8001) make dev # Run LangGraph server (port 2024)
make gateway # Run Gateway API without reload (port 8001) make gateway # Run Gateway API (port 8001)
make lint # Run linter (ruff) make lint # Run linter (ruff)
make format # Format code (ruff) make format # Format code (ruff)
make detect-blocking-io # Inventory blocking IO that may block the backend event loop
``` ```
### Code Style ### Code Style
@@ -379,18 +382,6 @@ make detect-blocking-io # Inventory blocking IO that may block the backend even
uv run pytest uv run pytest
``` ```
`make detect-blocking-io` statically scans backend business code for blocking
IO that may run on the backend event loop and is not test-coverage-bound. It
prints a concise summary for human review and writes complete JSON findings to
`.deer-flow/blocking-io-findings.json` at the repository root (regardless of
whether the target is invoked from the repo root or from `backend/`). JSON
findings include both broad IO category and review-oriented fields such as
`priority`, `location`, `blocking_call`, `event_loop_exposure`, `reason`, and
`code`. `priority` is a deterministic review ordering from the operation type,
not proof of a bug. Bare-name same-file calls are resolved by function name,
so duplicate helper names in one file can conservatively over-report async
reachability.
--- ---
## Technology Stack ## Technology Stack
+1 -1
View File
@@ -2,7 +2,7 @@
Provides a pluggable channel system that connects external messaging platforms Provides a pluggable channel system that connects external messaging platforms
(Feishu/Lark, Slack, Telegram) to the DeerFlow agent via the ChannelManager, (Feishu/Lark, Slack, Telegram) to the DeerFlow agent via the ChannelManager,
which uses ``langgraph-sdk`` to communicate with Gateway's LangGraph-compatible API. which uses ``langgraph-sdk`` to communicate with the underlying LangGraph Server.
""" """
from app.channels.base import Channel from app.channels.base import Channel
-4
View File
@@ -31,10 +31,6 @@ class Channel(ABC):
def is_running(self) -> bool: def is_running(self) -> bool:
return self._running return self._running
@property
def supports_streaming(self) -> bool:
return False
# -- lifecycle --------------------------------------------------------- # -- lifecycle ---------------------------------------------------------
@abstractmethod @abstractmethod
-740
View File
@@ -1,740 +0,0 @@
"""DingTalk channel implementation."""
from __future__ import annotations
import asyncio
import json
import logging
import re
import threading
import time
from pathlib import Path
from typing import Any
import httpx
from app.channels.base import Channel
from app.channels.commands import KNOWN_CHANNEL_COMMANDS
from app.channels.message_bus import InboundMessage, InboundMessageType, MessageBus, OutboundMessage, ResolvedAttachment
logger = logging.getLogger(__name__)
DINGTALK_API_BASE = "https://api.dingtalk.com"
_TOKEN_REFRESH_MARGIN_SECONDS = 300
_CONVERSATION_TYPE_P2P = "1"
_CONVERSATION_TYPE_GROUP = "2"
_MAX_UPLOAD_SIZE_BYTES = 20 * 1024 * 1024
def _normalize_conversation_type(raw: Any) -> str:
"""Normalize ``conversationType`` to ``"1"`` (P2P) or ``"2"`` (group).
Stream payloads may send int or string values.
"""
if raw is None:
return _CONVERSATION_TYPE_P2P
s = str(raw).strip()
if s == _CONVERSATION_TYPE_GROUP:
return _CONVERSATION_TYPE_GROUP
return _CONVERSATION_TYPE_P2P
def _normalize_allowed_users(allowed_users: Any) -> set[str]:
if allowed_users is None:
return set()
if isinstance(allowed_users, str):
values = [allowed_users]
elif isinstance(allowed_users, (list, tuple, set)):
values = allowed_users
else:
logger.warning(
"DingTalk allowed_users should be a list of user IDs; treating %s as one string value",
type(allowed_users).__name__,
)
values = [allowed_users]
return {str(uid) for uid in values if str(uid)}
def _is_dingtalk_command(text: str) -> bool:
if not text.startswith("/"):
return False
return text.split(maxsplit=1)[0].lower() in KNOWN_CHANNEL_COMMANDS
def _extract_text_from_rich_text(rich_text_list: list) -> str:
parts: list[str] = []
for item in rich_text_list:
if isinstance(item, dict) and "text" in item:
parts.append(item["text"])
return " ".join(parts)
_FENCED_CODE_BLOCK_RE = re.compile(r"```(\w*)\n(.*?)```", re.DOTALL)
_INLINE_CODE_RE = re.compile(r"`([^`\n]+)`")
_HORIZONTAL_RULE_RE = re.compile(r"^-{3,}$", re.MULTILINE)
_TABLE_SEPARATOR_RE = re.compile(r"^\|[-:| ]+\|$", re.MULTILINE)
def _convert_markdown_table(text: str) -> str:
# DingTalk sampleMarkdown does not render pipe-delimited tables.
lines = text.split("\n")
result: list[str] = []
i = 0
while i < len(lines):
line = lines[i]
# Detect table: header row followed by separator row
if i + 1 < len(lines) and line.strip().startswith("|") and _TABLE_SEPARATOR_RE.match(lines[i + 1].strip()):
headers = [h.strip() for h in line.strip().strip("|").split("|")]
i += 2 # skip header + separator
while i < len(lines) and lines[i].strip().startswith("|"):
cells = [c.strip() for c in lines[i].strip().strip("|").split("|")]
for h, c in zip(headers, cells):
result.append(f"> **{h}**: {c}")
result.append("")
i += 1
else:
result.append(line)
i += 1
return "\n".join(result)
def _adapt_markdown_for_dingtalk(text: str) -> str:
"""Adapt markdown for DingTalk's limited sampleMarkdown renderer."""
def _code_block_to_quote(match: re.Match) -> str:
lang = match.group(1)
code = match.group(2).rstrip("\n")
prefix = f"> **{lang}**\n" if lang else ""
quoted_lines = "\n".join(f"> {line}" for line in code.split("\n"))
return f"{prefix}{quoted_lines}\n"
text = _FENCED_CODE_BLOCK_RE.sub(_code_block_to_quote, text)
text = _INLINE_CODE_RE.sub(r"**\1**", text)
text = _convert_markdown_table(text)
text = _HORIZONTAL_RULE_RE.sub("───────────", text)
return text
class DingTalkChannel(Channel):
"""DingTalk IM channel using Stream Push (WebSocket, no public IP needed)."""
def __init__(self, bus: MessageBus, config: dict[str, Any]) -> None:
super().__init__(name="dingtalk", bus=bus, config=config)
self._thread: threading.Thread | None = None
self._main_loop: asyncio.AbstractEventLoop | None = None
self._client_id: str = ""
self._client_secret: str = ""
self._allowed_users: set[str] = _normalize_allowed_users(config.get("allowed_users"))
self._cached_token: str = ""
self._token_expires_at: float = 0.0
self._token_lock = asyncio.Lock()
self._card_template_id: str = config.get("card_template_id", "")
self._card_track_ids: dict[str, str] = {}
self._dingtalk_client: Any = None
self._stream_client: Any = None
self._incoming_messages: dict[str, Any] = {}
self._incoming_messages_lock = threading.Lock()
self._card_repliers: dict[str, Any] = {}
@property
def supports_streaming(self) -> bool:
return bool(self._card_template_id)
async def start(self) -> None:
if self._running:
return
try:
import dingtalk_stream # noqa: F401
except ImportError:
logger.error("dingtalk-stream is not installed. Install it with: uv add dingtalk-stream")
return
client_id = self.config.get("client_id", "")
client_secret = self.config.get("client_secret", "")
if not client_id or not client_secret:
logger.error("DingTalk channel requires client_id and client_secret")
return
self._client_id = client_id
self._client_secret = client_secret
self._main_loop = asyncio.get_running_loop()
if self._card_template_id:
logger.info("[DingTalk] AI Card mode enabled (template=%s)", self._card_template_id)
self._running = True
self.bus.subscribe_outbound(self._on_outbound)
self._thread = threading.Thread(
target=self._run_stream,
args=(client_id, client_secret),
daemon=True,
)
self._thread.start()
logger.info("DingTalk channel started")
async def stop(self) -> None:
self._running = False
self.bus.unsubscribe_outbound(self._on_outbound)
stream_client = self._stream_client
if stream_client is not None:
try:
if hasattr(stream_client, "disconnect"):
stream_client.disconnect()
except Exception:
logger.debug("[DingTalk] error disconnecting stream client", exc_info=True)
self._dingtalk_client = None
self._stream_client = None
with self._incoming_messages_lock:
self._incoming_messages.clear()
self._card_repliers.clear()
self._card_track_ids.clear()
if self._thread:
self._thread.join(timeout=5)
self._thread = None
logger.info("DingTalk channel stopped")
def _resolve_routing(self, msg: OutboundMessage) -> tuple[str, str, str]:
"""Return (conversation_type, sender_staff_id, conversation_id).
Uses msg.chat_id as the primary routing key; metadata as fallback.
"""
conversation_type = _normalize_conversation_type(msg.metadata.get("conversation_type"))
sender_staff_id = msg.metadata.get("sender_staff_id", "")
conversation_id = msg.metadata.get("conversation_id", "")
if conversation_type == _CONVERSATION_TYPE_GROUP:
conversation_id = msg.chat_id or conversation_id
else:
sender_staff_id = msg.chat_id or sender_staff_id
return conversation_type, sender_staff_id, conversation_id
async def send(self, msg: OutboundMessage, *, _max_retries: int = 3) -> None:
conversation_type, sender_staff_id, conversation_id = self._resolve_routing(msg)
robot_code = self._client_id
# Card mode: stream update to existing AI card
source_key = self._make_card_source_key_from_outbound(msg)
out_track_id = self._card_track_ids.get(source_key)
# ``card_template_id`` enables ``runs.stream`` (non-final + final outbounds).
# If card creation failed, skip non-final chunks to avoid duplicate messages.
if self._card_template_id and not out_track_id and not msg.is_final:
return
if out_track_id:
try:
await self._stream_update_card(
out_track_id,
msg.text,
is_finalize=msg.is_final,
)
except Exception:
logger.warning("[DingTalk] card stream failed, falling back to sampleMarkdown")
if msg.is_final:
self._card_track_ids.pop(source_key, None)
self._card_repliers.pop(out_track_id, None)
await self._send_markdown_fallback(robot_code, conversation_type, sender_staff_id, conversation_id, msg.text)
return
if msg.is_final:
self._card_track_ids.pop(source_key, None)
self._card_repliers.pop(out_track_id, None)
return
# Non-card mode: send sampleMarkdown with retry
last_exc: Exception | None = None
for attempt in range(_max_retries):
try:
if conversation_type == _CONVERSATION_TYPE_GROUP:
await self._send_group_message(robot_code, conversation_id, msg.text, at_user_ids=[sender_staff_id] if sender_staff_id else None)
else:
await self._send_p2p_message(robot_code, sender_staff_id, msg.text)
return
except Exception as exc:
last_exc = exc
if attempt < _max_retries - 1:
delay = 2**attempt
logger.warning(
"[DingTalk] send failed (attempt %d/%d), retrying in %ds: %s",
attempt + 1,
_max_retries,
delay,
exc,
)
await asyncio.sleep(delay)
logger.error("[DingTalk] send failed after %d attempts: %s", _max_retries, last_exc)
if last_exc is None:
raise RuntimeError("DingTalk send failed without an exception from any attempt")
raise last_exc
async def _send_markdown_fallback(
self,
robot_code: str,
conversation_type: str,
sender_staff_id: str,
conversation_id: str,
text: str,
) -> None:
try:
if conversation_type == _CONVERSATION_TYPE_GROUP:
await self._send_group_message(robot_code, conversation_id, text)
else:
await self._send_p2p_message(robot_code, sender_staff_id, text)
except Exception:
logger.exception("[DingTalk] markdown fallback also failed")
raise
async def send_file(self, msg: OutboundMessage, attachment: ResolvedAttachment) -> bool:
if attachment.size > _MAX_UPLOAD_SIZE_BYTES:
logger.warning("[DingTalk] file too large (%d bytes), skipping: %s", attachment.size, attachment.filename)
return False
conversation_type, sender_staff_id, conversation_id = self._resolve_routing(msg)
robot_code = self._client_id
try:
media_id = await self._upload_media(attachment.actual_path, "image" if attachment.is_image else "file")
if not media_id:
return False
if attachment.is_image:
msg_key = "sampleImageMsg"
msg_param = json.dumps({"photoURL": media_id})
else:
msg_key = "sampleFile"
msg_param = json.dumps(
{
"fileUrl": media_id,
"fileName": attachment.filename,
"fileSize": str(attachment.size),
}
)
token = await self._get_access_token()
async with httpx.AsyncClient(timeout=httpx.Timeout(30.0)) as client:
if conversation_type == _CONVERSATION_TYPE_GROUP:
response = await client.post(
f"{DINGTALK_API_BASE}/v1.0/robot/groupMessages/send",
headers=self._api_headers(token),
json={
"msgKey": msg_key,
"msgParam": msg_param,
"robotCode": robot_code,
"openConversationId": conversation_id,
},
)
else:
response = await client.post(
f"{DINGTALK_API_BASE}/v1.0/robot/oToMessages/batchSend",
headers=self._api_headers(token),
json={
"msgKey": msg_key,
"msgParam": msg_param,
"robotCode": robot_code,
"userIds": [sender_staff_id],
},
)
response.raise_for_status()
logger.info("[DingTalk] file sent: %s", attachment.filename)
return True
except (httpx.HTTPError, OSError, ValueError, TypeError, AttributeError):
logger.exception("[DingTalk] failed to send file: %s", attachment.filename)
return False
# -- stream client (runs in dedicated thread) --------------------------
def _run_stream(self, client_id: str, client_secret: str) -> None:
try:
import dingtalk_stream
credential = dingtalk_stream.Credential(client_id, client_secret)
client = dingtalk_stream.DingTalkStreamClient(credential)
self._stream_client = client
client.register_callback_handler(
dingtalk_stream.chatbot.ChatbotMessage.TOPIC,
_DingTalkMessageHandler(self),
)
client.start_forever()
except Exception:
if self._running:
logger.exception("DingTalk Stream Push error")
finally:
self._stream_client = None
def _on_chatbot_message(self, message: Any) -> None:
if not self._running:
return
try:
sender_staff_id = message.sender_staff_id or ""
conversation_type = _normalize_conversation_type(message.conversation_type)
conversation_id = message.conversation_id or ""
msg_id = message.message_id or ""
sender_nick = message.sender_nick or ""
if self._allowed_users and sender_staff_id not in self._allowed_users:
logger.debug("[DingTalk] ignoring message from non-allowed user: %s", sender_staff_id)
return
text = self._extract_text(message)
if not text:
logger.info("[DingTalk] empty text, ignoring message")
return
logger.info(
"[DingTalk] parsed message: conv_type=%s, msg_id=%s, sender=%s(%s), text=%r",
conversation_type,
msg_id,
sender_staff_id,
sender_nick,
text[:100],
)
if _is_dingtalk_command(text):
msg_type = InboundMessageType.COMMAND
else:
msg_type = InboundMessageType.CHAT
# P2P: topic_id=None (single thread per user, like Telegram private chat)
# Group: topic_id=msg_id (each new message starts a new topic, like Feishu)
topic_id: str | None = msg_id if conversation_type == _CONVERSATION_TYPE_GROUP else None
# chat_id uses conversation_id for groups, sender_staff_id for P2P
chat_id = conversation_id if conversation_type == _CONVERSATION_TYPE_GROUP else sender_staff_id
inbound = self._make_inbound(
chat_id=chat_id,
user_id=sender_staff_id,
text=text,
msg_type=msg_type,
thread_ts=msg_id,
metadata={
"conversation_type": conversation_type,
"conversation_id": conversation_id,
"sender_staff_id": sender_staff_id,
"sender_nick": sender_nick,
"message_id": msg_id,
},
)
inbound.topic_id = topic_id
if self._card_template_id:
source_key = self._make_card_source_key(inbound)
with self._incoming_messages_lock:
self._incoming_messages[source_key] = message
if self._main_loop and self._main_loop.is_running():
logger.info("[DingTalk] publishing inbound message to bus (type=%s, msg_id=%s)", msg_type.value, msg_id)
fut = asyncio.run_coroutine_threadsafe(
self._prepare_inbound(chat_id, inbound),
self._main_loop,
)
fut.add_done_callback(lambda f, mid=msg_id: self._log_future_error(f, "prepare_inbound", mid))
else:
logger.warning("[DingTalk] main loop not running, cannot publish inbound message")
except Exception:
logger.exception("[DingTalk] error processing chatbot message")
@staticmethod
def _extract_text(message: Any) -> str:
msg_type = message.message_type
if msg_type == "text" and message.text:
return message.text.content.strip()
if msg_type == "richText" and message.rich_text_content:
return _extract_text_from_rich_text(message.rich_text_content.rich_text_list).strip()
return ""
async def _prepare_inbound(self, chat_id: str, inbound: InboundMessage) -> None:
# Running reply must finish before publish_inbound so AI card tracks are
# registered before the manager emits streaming outbounds.
await self._send_running_reply(chat_id, inbound)
await self.bus.publish_inbound(inbound)
async def _send_running_reply(self, chat_id: str, inbound: InboundMessage) -> None:
conversation_type = inbound.metadata.get("conversation_type", _CONVERSATION_TYPE_P2P)
sender_staff_id = inbound.metadata.get("sender_staff_id", "")
conversation_id = inbound.metadata.get("conversation_id", "")
text = "\u23f3 Working on it..."
try:
if self._card_template_id:
source_key = self._make_card_source_key(inbound)
with self._incoming_messages_lock:
chatbot_message = self._incoming_messages.pop(source_key, None)
out_track_id = await self._create_and_deliver_card(
text,
chatbot_message=chatbot_message,
)
if out_track_id:
self._card_track_ids[source_key] = out_track_id
logger.info("[DingTalk] AI card running reply sent for chat=%s", chat_id)
return
robot_code = self._client_id
if conversation_type == _CONVERSATION_TYPE_GROUP:
await self._send_text_message_to_group(robot_code, conversation_id, text)
else:
await self._send_text_message_to_user(robot_code, sender_staff_id, text)
logger.info("[DingTalk] 'Working on it...' reply sent for chat=%s", chat_id)
except Exception:
logger.exception("[DingTalk] failed to send running reply for chat=%s", chat_id)
# -- DingTalk API helpers ----------------------------------------------
async def _get_access_token(self) -> str:
if self._cached_token and time.monotonic() < self._token_expires_at:
return self._cached_token
async with self._token_lock:
if self._cached_token and time.monotonic() < self._token_expires_at:
return self._cached_token
async with httpx.AsyncClient(timeout=httpx.Timeout(10.0)) as client:
response = await client.post(
f"{DINGTALK_API_BASE}/v1.0/oauth2/accessToken",
json={"appKey": self._client_id, "appSecret": self._client_secret}, # DingTalk API field names
)
response.raise_for_status()
data = response.json()
if not isinstance(data, dict):
raise ValueError(f"DingTalk access token response must be a JSON object, got {type(data).__name__}")
access_token = data.get("accessToken")
if not isinstance(access_token, str) or not access_token.strip():
raise ValueError("DingTalk access token response did not contain a usable accessToken")
raw_expires_in = data.get("expireIn", 7200)
try:
expires_in = int(raw_expires_in)
except (TypeError, ValueError):
logger.warning("[DingTalk] invalid expireIn value %r, using default 7200s", raw_expires_in)
expires_in = 7200
self._cached_token = access_token.strip()
self._token_expires_at = time.monotonic() + expires_in - _TOKEN_REFRESH_MARGIN_SECONDS
return self._cached_token
@staticmethod
def _api_headers(token: str) -> dict[str, str]:
return {
"x-acs-dingtalk-access-token": token,
"Content-Type": "application/json",
}
async def _send_text_message_to_user(self, robot_code: str, user_id: str, text: str) -> None:
token = await self._get_access_token()
async with httpx.AsyncClient(timeout=httpx.Timeout(30.0)) as client:
response = await client.post(
f"{DINGTALK_API_BASE}/v1.0/robot/oToMessages/batchSend",
headers=self._api_headers(token),
json={
"msgKey": "sampleText",
"msgParam": json.dumps({"content": text}),
"robotCode": robot_code,
"userIds": [user_id],
},
)
response.raise_for_status()
async def _send_text_message_to_group(self, robot_code: str, conversation_id: str, text: str) -> None:
token = await self._get_access_token()
async with httpx.AsyncClient(timeout=httpx.Timeout(30.0)) as client:
response = await client.post(
f"{DINGTALK_API_BASE}/v1.0/robot/groupMessages/send",
headers=self._api_headers(token),
json={
"msgKey": "sampleText",
"msgParam": json.dumps({"content": text}),
"robotCode": robot_code,
"openConversationId": conversation_id,
},
)
response.raise_for_status()
async def _send_p2p_message(self, robot_code: str, user_id: str, text: str) -> None:
text = _adapt_markdown_for_dingtalk(text)
token = await self._get_access_token()
async with httpx.AsyncClient(timeout=httpx.Timeout(30.0)) as client:
response = await client.post(
f"{DINGTALK_API_BASE}/v1.0/robot/oToMessages/batchSend",
headers=self._api_headers(token),
json={
"msgKey": "sampleMarkdown",
"msgParam": json.dumps({"title": "DeerFlow", "text": text}),
"robotCode": robot_code,
"userIds": [user_id],
},
)
response.raise_for_status()
data = response.json()
if data.get("processQueryKey"):
logger.info("[DingTalk] P2P message sent to user=%s", user_id)
else:
logger.warning("[DingTalk] P2P send response: %s", data)
async def _send_group_message(
self,
robot_code: str,
conversation_id: str,
text: str,
*,
at_user_ids: list[str] | None = None, # noqa: ARG002
) -> None:
# at_user_ids accepted for call-site compatibility but not passed to the API
# (sampleMarkdown does not support @mentions).
text = _adapt_markdown_for_dingtalk(text)
token = await self._get_access_token()
async with httpx.AsyncClient(timeout=httpx.Timeout(30.0)) as client:
response = await client.post(
f"{DINGTALK_API_BASE}/v1.0/robot/groupMessages/send",
headers=self._api_headers(token),
json={
"msgKey": "sampleMarkdown",
"msgParam": json.dumps({"title": "DeerFlow", "text": text}),
"robotCode": robot_code,
"openConversationId": conversation_id,
},
)
response.raise_for_status()
data = response.json()
if data.get("processQueryKey"):
logger.info("[DingTalk] group message sent to conversation=%s", conversation_id)
else:
logger.warning("[DingTalk] group send response: %s", data)
# -- AI Card streaming helpers -------------------------------------------
def _make_card_source_key(self, inbound: InboundMessage) -> str:
m = inbound.metadata
return f"{m.get('conversation_type', '')}:{m.get('sender_staff_id', '')}:{m.get('conversation_id', '')}:{m.get('message_id', '')}"
def _make_card_source_key_from_outbound(self, msg: OutboundMessage) -> str:
m = msg.metadata
correlation_id = m.get("message_id") or msg.thread_ts or ""
return f"{m.get('conversation_type', '')}:{m.get('sender_staff_id', '')}:{m.get('conversation_id', '')}:{correlation_id}"
async def _create_and_deliver_card(
self,
initial_text: str,
*,
chatbot_message: Any = None,
) -> str | None:
if self._dingtalk_client is None or chatbot_message is None:
logger.warning("[DingTalk] SDK client or chatbot_message unavailable, skipping AI card")
return None
try:
from dingtalk_stream.card_replier import AICardReplier
except ImportError:
logger.warning("[DingTalk] dingtalk-stream card_replier not available")
return None
try:
replier = AICardReplier(self._dingtalk_client, chatbot_message)
card_instance_id = await replier.async_create_and_deliver_card(
card_template_id=self._card_template_id,
card_data={"content": initial_text},
)
if not card_instance_id:
return None
self._card_repliers[card_instance_id] = replier
logger.info("[DingTalk] AI card created: outTrackId=%s", card_instance_id)
return card_instance_id
except Exception:
logger.exception("[DingTalk] failed to create AI card")
return None
async def _stream_update_card(
self,
out_track_id: str,
content: str,
*,
is_finalize: bool = False,
is_error: bool = False,
) -> None:
replier = self._card_repliers.get(out_track_id)
if not replier:
raise RuntimeError(f"No AICardReplier found for track ID {out_track_id}")
await replier.async_streaming(
card_instance_id=out_track_id,
content_key="content",
content_value=content,
append=False,
finished=is_finalize,
failed=is_error,
)
# -- media upload --------------------------------------------------------
async def _upload_media(self, file_path: str | Path, media_type: str) -> str | None:
try:
file_bytes = await asyncio.to_thread(Path(file_path).read_bytes)
token = await self._get_access_token()
async with httpx.AsyncClient(timeout=httpx.Timeout(60.0)) as client:
response = await client.post(
f"{DINGTALK_API_BASE}/v1.0/files/upload",
headers={"x-acs-dingtalk-access-token": token},
files={"file": ("upload", file_bytes)},
data={"type": media_type},
)
response.raise_for_status()
try:
payload = response.json()
except json.JSONDecodeError:
logger.exception("[DingTalk] failed to decode upload response JSON: %s", file_path)
return None
if not isinstance(payload, dict):
logger.warning("[DingTalk] unexpected upload response type %s for %s", type(payload).__name__, file_path)
return None
return payload.get("mediaId")
except (httpx.HTTPError, OSError):
logger.exception("[DingTalk] failed to upload media: %s", file_path)
return None
@staticmethod
def _log_future_error(fut: Any, name: str, msg_id: str) -> None:
try:
exc = fut.exception()
if exc:
logger.error("[DingTalk] %s failed for msg_id=%s: %s", name, msg_id, exc)
except (asyncio.CancelledError, asyncio.InvalidStateError):
pass
class _DingTalkMessageHandler:
"""Callback handler registered with dingtalk-stream."""
def __init__(self, channel: DingTalkChannel) -> None:
self._channel = channel
def pre_start(self) -> None:
if hasattr(self, "dingtalk_client") and self.dingtalk_client is not None:
self._channel._dingtalk_client = self.dingtalk_client
async def raw_process(self, callback_message: Any) -> Any:
import dingtalk_stream
from dingtalk_stream.frames import Headers
code, message = await self.process(callback_message)
ack_message = dingtalk_stream.AckMessage()
ack_message.code = code
ack_message.headers.message_id = callback_message.headers.message_id
ack_message.headers.content_type = Headers.CONTENT_TYPE_APPLICATION_JSON
ack_message.data = {"response": message}
return ack_message
async def process(self, callback: Any) -> tuple[int, str]:
import dingtalk_stream
incoming_message = dingtalk_stream.ChatbotMessage.from_dict(callback.data)
self._channel._on_chatbot_message(incoming_message)
return dingtalk_stream.AckMessage.STATUS_OK, "OK"
-553
View File
@@ -1,553 +0,0 @@
"""Discord channel integration using discord.py."""
from __future__ import annotations
import asyncio
import json
import logging
import threading
from pathlib import Path
from typing import Any
from app.channels.base import Channel
from app.channels.message_bus import InboundMessageType, MessageBus, OutboundMessage, ResolvedAttachment
logger = logging.getLogger(__name__)
_DISCORD_MAX_MESSAGE_LEN = 2000
class DiscordChannel(Channel):
"""Discord bot channel.
Configuration keys (in ``config.yaml`` under ``channels.discord``):
- ``bot_token``: Discord Bot token.
- ``allowed_guilds``: (optional) List of allowed Discord guild IDs. Empty = allow all.
- ``mention_only``: (optional) If true, only respond when the bot is mentioned.
- ``allowed_channels``: (optional) List of channel IDs where messages are always accepted
(even when mention_only is true). Use for channels where you want the bot to respond
without mentions. Empty = mention_only applies everywhere.
- ``thread_mode``: (optional) If true, group a channel conversation into a thread.
Default: same as ``mention_only``.
"""
def __init__(self, bus: MessageBus, config: dict[str, Any]) -> None:
super().__init__(name="discord", bus=bus, config=config)
self._bot_token = str(config.get("bot_token", "")).strip()
self._allowed_guilds: set[int] = set()
for guild_id in config.get("allowed_guilds", []):
try:
self._allowed_guilds.add(int(guild_id))
except (TypeError, ValueError):
continue
self._mention_only: bool = bool(config.get("mention_only", False))
self._thread_mode: bool = config.get("thread_mode", self._mention_only)
self._allowed_channels: set[str] = set()
for channel_id in config.get("allowed_channels", []):
self._allowed_channels.add(str(channel_id))
# Session tracking: channel_id -> Discord thread_id (in-memory, persisted to JSON).
# Uses a dedicated JSON file separate from ChannelStore, which maps IM
# conversations to DeerFlow thread IDs — a different concern.
self._active_threads: dict[str, str] = {}
# Reverse-lookup set for O(1) thread ID checks (avoids O(n) scan of _active_threads.values()).
self._active_thread_ids: set[str] = set()
# Lock protecting _active_threads and the JSON file from concurrent access.
# _run_client (Discord loop thread) and the main thread both read/write.
self._thread_store_lock = threading.Lock()
store = config.get("channel_store")
if store is not None:
self._thread_store_path = store._path.parent / "discord_threads.json"
else:
self._thread_store_path = Path.home() / ".deer-flow" / "channels" / "discord_threads.json"
# Typing indicator management
self._typing_tasks: dict[str, asyncio.Task] = {}
self._client = None
self._thread: threading.Thread | None = None
self._discord_loop: asyncio.AbstractEventLoop | None = None
self._main_loop: asyncio.AbstractEventLoop | None = None
self._discord_module = None
async def start(self) -> None:
if self._running:
return
try:
import discord
except ImportError:
logger.error("discord.py is not installed. Install it with: uv add discord.py")
return
if not self._bot_token:
logger.error("Discord channel requires bot_token")
return
intents = discord.Intents.default()
intents.messages = True
intents.guilds = True
intents.message_content = True
client = discord.Client(
intents=intents,
allowed_mentions=discord.AllowedMentions.none(),
)
self._client = client
self._discord_module = discord
self._main_loop = asyncio.get_event_loop()
@client.event
async def on_message(message) -> None:
await self._on_message(message)
self._running = True
self.bus.subscribe_outbound(self._on_outbound)
self._thread = threading.Thread(target=self._run_client, daemon=True)
self._thread.start()
self._load_active_threads()
logger.info("Discord channel started")
def _load_active_threads(self) -> None:
"""Restore Discord thread mappings from the dedicated JSON file on startup."""
with self._thread_store_lock:
try:
if not self._thread_store_path.exists():
logger.debug("[Discord] no thread mappings file at %s", self._thread_store_path)
return
data = json.loads(self._thread_store_path.read_text())
self._active_threads.clear()
self._active_thread_ids.clear()
for channel_id, thread_id in data.items():
self._active_threads[channel_id] = thread_id
self._active_thread_ids.add(thread_id)
if self._active_threads:
logger.info("[Discord] restored %d thread mappings from %s", len(self._active_threads), self._thread_store_path)
except Exception:
logger.exception("[Discord] failed to load thread mappings")
def _save_thread(self, channel_id: str, thread_id: str) -> None:
"""Persist a Discord thread mapping to the dedicated JSON file."""
with self._thread_store_lock:
try:
data: dict[str, str] = {}
if self._thread_store_path.exists():
data = json.loads(self._thread_store_path.read_text())
old_id = data.get(channel_id)
data[channel_id] = thread_id
# Update reverse-lookup set
if old_id:
self._active_thread_ids.discard(old_id)
self._active_thread_ids.add(thread_id)
self._thread_store_path.parent.mkdir(parents=True, exist_ok=True)
self._thread_store_path.write_text(json.dumps(data, indent=2))
except Exception:
logger.exception("[Discord] failed to save thread mapping for channel %s", channel_id)
async def stop(self) -> None:
self._running = False
self.bus.unsubscribe_outbound(self._on_outbound)
# Cancel all active typing indicator tasks
for target_id, task in list(self._typing_tasks.items()):
if not task.done():
task.cancel()
logger.debug("[Discord] cancelled typing task for target %s", target_id)
self._typing_tasks.clear()
if self._client and self._discord_loop and self._discord_loop.is_running():
close_future = asyncio.run_coroutine_threadsafe(self._client.close(), self._discord_loop)
try:
await asyncio.wait_for(asyncio.wrap_future(close_future), timeout=10)
except TimeoutError:
logger.warning("[Discord] client close timed out after 10s")
except Exception:
logger.exception("[Discord] error while closing client")
if self._thread:
self._thread.join(timeout=10)
self._thread = None
self._client = None
self._discord_loop = None
self._discord_module = None
logger.info("Discord channel stopped")
async def send(self, msg: OutboundMessage) -> None:
# Stop typing indicator once we're sending the response
stop_future = asyncio.run_coroutine_threadsafe(self._stop_typing(msg.chat_id, msg.thread_ts), self._discord_loop)
await asyncio.wrap_future(stop_future)
target = await self._resolve_target(msg)
if target is None:
logger.error("[Discord] target not found for chat_id=%s thread_ts=%s", msg.chat_id, msg.thread_ts)
return
text = msg.text or ""
for chunk in self._split_text(text):
send_future = asyncio.run_coroutine_threadsafe(target.send(chunk), self._discord_loop)
await asyncio.wrap_future(send_future)
async def send_file(self, msg: OutboundMessage, attachment: ResolvedAttachment) -> bool:
stop_future = asyncio.run_coroutine_threadsafe(self._stop_typing(msg.chat_id, msg.thread_ts), self._discord_loop)
await asyncio.wrap_future(stop_future)
target = await self._resolve_target(msg)
if target is None:
logger.error("[Discord] target not found for file upload chat_id=%s thread_ts=%s", msg.chat_id, msg.thread_ts)
return False
if self._discord_module is None:
return False
try:
fp = open(str(attachment.actual_path), "rb") # noqa: SIM115
file = self._discord_module.File(fp, filename=attachment.filename)
send_future = asyncio.run_coroutine_threadsafe(target.send(file=file), self._discord_loop)
await asyncio.wrap_future(send_future)
logger.info("[Discord] file uploaded: %s", attachment.filename)
return True
except Exception:
logger.exception("[Discord] failed to upload file: %s", attachment.filename)
return False
async def _start_typing(self, channel, chat_id: str, thread_ts: str | None = None) -> None:
"""Starts a loop to send periodic typing indicators."""
target_id = thread_ts or chat_id
if target_id in self._typing_tasks:
return # Already typing for this target
async def _typing_loop():
try:
while True:
try:
await channel.trigger_typing()
except Exception:
pass
await asyncio.sleep(10)
except asyncio.CancelledError:
pass
task = asyncio.create_task(_typing_loop())
self._typing_tasks[target_id] = task
async def _stop_typing(self, chat_id: str, thread_ts: str | None = None) -> None:
"""Stops the typing loop for a specific target."""
target_id = thread_ts or chat_id
task = self._typing_tasks.pop(target_id, None)
if task and not task.done():
task.cancel()
logger.debug("[Discord] stopped typing indicator for target %s", target_id)
async def _add_reaction(self, message) -> None:
"""Add a checkmark reaction to acknowledge the message was received."""
try:
await message.add_reaction("")
except Exception:
logger.debug("[Discord] failed to add reaction to message %s", message.id, exc_info=True)
async def _on_message(self, message) -> None:
if not self._running or not self._client:
return
if message.author.bot:
return
if self._client.user and message.author.id == self._client.user.id:
return
guild = message.guild
if self._allowed_guilds:
if guild is None or guild.id not in self._allowed_guilds:
return
text = (message.content or "").strip()
if not text:
return
if self._discord_module is None:
return
# Determine whether the bot is mentioned in this message
user = self._client.user if self._client else None
if user:
bot_mention = user.mention # <@ID>
alt_mention = f"<@!{user.id}>" # <@!ID> (ping variant)
standard_mention = f"<@{user.id}>"
else:
bot_mention = None
alt_mention = None
standard_mention = ""
has_mention = (bot_mention and bot_mention in message.content) or (alt_mention and alt_mention in message.content) or (standard_mention and standard_mention in message.content)
# Strip mention from text for processing
if has_mention:
text = text.replace(bot_mention or "", "").replace(alt_mention or "", "").replace(standard_mention or "", "").strip()
# Don't return early if text is empty — still process the mention (e.g., create thread)
# --- Determine thread/channel routing and typing target ---
thread_id = None
chat_id = None
typing_target = None # The Discord object to type into
if isinstance(message.channel, self._discord_module.Thread):
# --- Message already inside a thread ---
thread_obj = message.channel
thread_id = str(thread_obj.id)
chat_id = str(thread_obj.parent_id or thread_obj.id)
typing_target = thread_obj
# If this is a known active thread, process normally
if thread_id in self._active_thread_ids:
msg_type = InboundMessageType.COMMAND if text.startswith("/") else InboundMessageType.CHAT
inbound = self._make_inbound(
chat_id=chat_id,
user_id=str(message.author.id),
text=text,
msg_type=msg_type,
thread_ts=thread_id,
metadata={
"guild_id": str(guild.id) if guild else None,
"channel_id": str(message.channel.id),
"message_id": str(message.id),
},
)
inbound.topic_id = thread_id
self._publish(inbound)
# Start typing indicator in the thread
if typing_target:
asyncio.create_task(self._start_typing(typing_target, chat_id, thread_id))
asyncio.create_task(self._add_reaction(message))
return
# Thread not tracked (orphaned) — create new thread and handle below
logger.debug("[Discord] message in orphaned thread %s, will create new thread", thread_id)
thread_id = None
typing_target = None
# At this point we're guaranteed to be in a channel, not a thread
# (the Thread case is handled above). Apply mention_only for all
# non-thread messages — no special case needed.
channel_id = str(message.channel.id)
# Check if there's an active thread for this channel
if channel_id in self._active_threads:
# respect mention_only: if enabled, only process messages that mention the bot
# (unless the channel is in allowed_channels)
# Messages within a thread are always allowed through (continuation).
# At this code point we know the message is in a channel, not a thread
# (Thread case handled above), so always apply the check.
if self._mention_only and not has_mention and channel_id not in self._allowed_channels:
logger.debug("[Discord] skipping no-@ message in channel %s (not in thread)", channel_id)
return
# mention_only + fresh @ → create new thread instead of routing to existing one
if self._mention_only and has_mention:
thread_obj = await self._create_thread(message)
if thread_obj is not None:
target_thread_id = str(thread_obj.id)
self._active_threads[channel_id] = target_thread_id
self._save_thread(channel_id, target_thread_id)
thread_id = target_thread_id
chat_id = channel_id
typing_target = thread_obj
logger.info("[Discord] created new thread %s in channel %s on mention (replacing existing thread)", target_thread_id, channel_id)
else:
logger.info("[Discord] thread creation failed in channel %s, falling back to channel replies", channel_id)
thread_id = channel_id
chat_id = channel_id
typing_target = message.channel
else:
# Existing session → route to the existing thread
target_thread_id = self._active_threads[channel_id]
logger.debug("[Discord] routing message in channel %s to existing thread %s", channel_id, target_thread_id)
thread_id = target_thread_id
chat_id = channel_id
typing_target = await self._get_channel_or_thread(target_thread_id)
elif self._mention_only and not has_mention and channel_id not in self._allowed_channels:
# Not mentioned and not in an allowed channel → skip
logger.debug("[Discord] skipping message without mention in channel %s", channel_id)
return
elif self._mention_only and has_mention:
# First mention in this channel → create thread
thread_obj = await self._create_thread(message)
if thread_obj is not None:
target_thread_id = str(thread_obj.id)
self._active_threads[channel_id] = target_thread_id
self._save_thread(channel_id, target_thread_id)
thread_id = target_thread_id
chat_id = channel_id
typing_target = thread_obj # Type into the new thread
logger.info("[Discord] created thread %s in channel %s for user %s", target_thread_id, channel_id, message.author.display_name)
else:
# Fallback: thread creation failed (disabled/permissions), reply in channel
logger.info("[Discord] thread creation failed in channel %s, falling back to channel replies", channel_id)
thread_id = channel_id
chat_id = channel_id
typing_target = message.channel # Type into the channel
elif self._thread_mode:
# thread_mode but mention_only is False → create thread anyway for conversation grouping
thread_obj = await self._create_thread(message)
if thread_obj is None:
# Thread creation failed (disabled/permissions), fall back to channel replies
logger.info("[Discord] thread creation failed in channel %s, falling back to channel replies", channel_id)
thread_id = channel_id
chat_id = channel_id
typing_target = message.channel # Type into the channel
else:
target_thread_id = str(thread_obj.id)
self._active_threads[channel_id] = target_thread_id
self._save_thread(channel_id, target_thread_id)
thread_id = target_thread_id
chat_id = channel_id
typing_target = thread_obj # Type into the new thread
else:
# No threading — reply directly in channel
thread_id = channel_id
chat_id = channel_id
typing_target = message.channel # Type into the channel
msg_type = InboundMessageType.COMMAND if text.startswith("/") else InboundMessageType.CHAT
inbound = self._make_inbound(
chat_id=chat_id,
user_id=str(message.author.id),
text=text,
msg_type=msg_type,
thread_ts=thread_id,
metadata={
"guild_id": str(guild.id) if guild else None,
"channel_id": str(message.channel.id),
"message_id": str(message.id),
},
)
inbound.topic_id = thread_id
# Start typing indicator in the correct target (thread or channel)
if typing_target:
asyncio.create_task(self._start_typing(typing_target, chat_id, thread_id))
self._publish(inbound)
asyncio.create_task(self._add_reaction(message))
def _publish(self, inbound) -> None:
"""Publish an inbound message to the main event loop."""
if self._main_loop and self._main_loop.is_running():
future = asyncio.run_coroutine_threadsafe(self.bus.publish_inbound(inbound), self._main_loop)
future.add_done_callback(lambda f: logger.exception("[Discord] publish_inbound failed", exc_info=f.exception()) if f.exception() else None)
def _run_client(self) -> None:
self._discord_loop = asyncio.new_event_loop()
asyncio.set_event_loop(self._discord_loop)
try:
self._discord_loop.run_until_complete(self._client.start(self._bot_token))
except Exception:
if self._running:
logger.exception("Discord client error")
finally:
try:
if self._client and not self._client.is_closed():
self._discord_loop.run_until_complete(self._client.close())
except Exception:
logger.exception("Error during Discord shutdown")
async def _create_thread(self, message):
try:
if self._discord_module is None:
return None
# Only TextChannel (type 0) and NewsChannel (type 10) support threads
channel_type = message.channel.type
if channel_type not in (
self._discord_module.ChannelType.text,
self._discord_module.ChannelType.news,
):
logger.info(
"[Discord] channel type %s (%s) does not support threads",
channel_type.value,
channel_type.name,
)
return None
thread_name = f"deerflow-{message.author.display_name}-{message.id}"[:100]
return await message.create_thread(name=thread_name)
except self._discord_module.errors.HTTPException as exc:
if exc.code == 50024:
logger.info(
"[Discord] cannot create thread in channel %s (error code 50024): %s",
message.channel.id,
channel_type.name if (channel_type := message.channel.type) else "unknown",
)
else:
logger.exception(
"[Discord] failed to create thread for message=%s (HTTPException %s)",
message.id,
exc.code,
)
return None
except Exception:
logger.exception("[Discord] failed to create thread for message=%s (threads may be disabled or missing permissions)", message.id)
return None
async def _resolve_target(self, msg: OutboundMessage):
if not self._client or not self._discord_loop:
return None
target_ids: list[str] = []
if msg.thread_ts:
target_ids.append(msg.thread_ts)
if msg.chat_id and msg.chat_id not in target_ids:
target_ids.append(msg.chat_id)
for raw_id in target_ids:
target = await self._get_channel_or_thread(raw_id)
if target is not None:
return target
return None
async def _get_channel_or_thread(self, raw_id: str):
if not self._client or not self._discord_loop:
return None
try:
target_id = int(raw_id)
except (TypeError, ValueError):
return None
get_future = asyncio.run_coroutine_threadsafe(self._fetch_channel(target_id), self._discord_loop)
try:
return await asyncio.wrap_future(get_future)
except Exception:
logger.exception("[Discord] failed to resolve target id=%s", raw_id)
return None
async def _fetch_channel(self, target_id: int):
if not self._client:
return None
channel = self._client.get_channel(target_id)
if channel is not None:
return channel
try:
return await self._client.fetch_channel(target_id)
except Exception:
return None
@staticmethod
def _split_text(text: str) -> list[str]:
if not text:
return [""]
chunks: list[str] = []
remaining = text
while len(remaining) > _DISCORD_MAX_MESSAGE_LEN:
split_at = remaining.rfind("\n", 0, _DISCORD_MAX_MESSAGE_LEN)
if split_at <= 0:
split_at = _DISCORD_MAX_MESSAGE_LEN
chunks.append(remaining[:split_at])
remaining = remaining[split_at:].lstrip("\n")
if remaining:
chunks.append(remaining)
return chunks
+11 -196
View File
@@ -7,26 +7,15 @@ import json
import logging import logging
import re import re
import threading import threading
import time
from typing import Any, Literal from typing import Any, Literal
from app.channels.base import Channel from app.channels.base import Channel
from app.channels.commands import KNOWN_CHANNEL_COMMANDS from app.channels.commands import KNOWN_CHANNEL_COMMANDS
from app.channels.message_bus import ( from app.channels.message_bus import InboundMessage, InboundMessageType, MessageBus, OutboundMessage, ResolvedAttachment
PENDING_CLARIFICATION_METADATA_KEY,
RESOLVED_FROM_PENDING_CLARIFICATION_METADATA_KEY,
InboundMessage,
InboundMessageType,
MessageBus,
OutboundMessage,
ResolvedAttachment,
)
from deerflow.config.paths import VIRTUAL_PATH_PREFIX, get_paths from deerflow.config.paths import VIRTUAL_PATH_PREFIX, get_paths
from deerflow.runtime.user_context import get_effective_user_id
from deerflow.sandbox.sandbox_provider import get_sandbox_provider from deerflow.sandbox.sandbox_provider import get_sandbox_provider
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
PENDING_CLARIFICATION_TTL_SECONDS = 30 * 60
def _is_feishu_command(text: str) -> bool: def _is_feishu_command(text: str) -> bool:
@@ -66,7 +55,6 @@ class FeishuChannel(Channel):
self._background_tasks: set[asyncio.Task] = set() self._background_tasks: set[asyncio.Task] = set()
self._running_card_ids: dict[str, str] = {} self._running_card_ids: dict[str, str] = {}
self._running_card_tasks: dict[str, asyncio.Task] = {} self._running_card_tasks: dict[str, asyncio.Task] = {}
self._pending_clarifications: dict[tuple[str, str], list[dict[str, Any]]] = {}
self._CreateFileRequest = None self._CreateFileRequest = None
self._CreateFileRequestBody = None self._CreateFileRequestBody = None
self._CreateImageRequest = None self._CreateImageRequest = None
@@ -74,20 +62,6 @@ class FeishuChannel(Channel):
self._GetMessageResourceRequest = None self._GetMessageResourceRequest = None
self._thread_lock = threading.Lock() self._thread_lock = threading.Lock()
@staticmethod
def _non_empty_str(value: Any) -> str | None:
if isinstance(value, str) and value.strip():
return value.strip()
return None
@staticmethod
def _pending_key(chat_id: str, user_id: str) -> tuple[str, str]:
return (chat_id, user_id)
@property
def supports_streaming(self) -> bool:
return True
async def start(self) -> None: async def start(self) -> None:
if self._running: if self._running:
return return
@@ -370,9 +344,8 @@ class FeishuChannel(Channel):
return f"Failed to obtain the [{type}]" return f"Failed to obtain the [{type}]"
paths = get_paths() paths = get_paths()
user_id = get_effective_user_id() paths.ensure_thread_dirs(thread_id)
paths.ensure_thread_dirs(thread_id, user_id=user_id) uploads_dir = paths.sandbox_uploads_dir(thread_id).resolve()
uploads_dir = paths.sandbox_uploads_dir(thread_id, user_id=user_id).resolve()
ext = "png" if type == "image" else "bin" ext = "png" if type == "image" else "bin"
raw_filename = getattr(response, "file_name", "") or f"feishu_{file_key[-12:]}.{ext}" raw_filename = getattr(response, "file_name", "") or f"feishu_{file_key[-12:]}.{ext}"
@@ -552,25 +525,18 @@ class FeishuChannel(Channel):
"[Feishu] failed to patch running card %s, falling back to final reply", "[Feishu] failed to patch running card %s, falling back to final reply",
running_card_id, running_card_id,
) )
fallback_card_id = await self._reply_card(source_message_id, msg.text) await self._reply_card(source_message_id, msg.text)
self._remember_thread_mapping(msg, source_message_id, fallback_card_id)
self._remember_pending_clarification(msg, fallback_card_id)
else: else:
self._remember_thread_mapping(msg, source_message_id, running_card_id)
self._remember_pending_clarification(msg, running_card_id)
logger.info("[Feishu] running card updated: source=%s card=%s", source_message_id, running_card_id) logger.info("[Feishu] running card updated: source=%s card=%s", source_message_id, running_card_id)
elif msg.is_final: elif msg.is_final:
final_card_id = await self._reply_card(source_message_id, msg.text) await self._reply_card(source_message_id, msg.text)
self._remember_thread_mapping(msg, source_message_id, final_card_id)
self._remember_pending_clarification(msg, final_card_id)
elif awaited_running_card_task: elif awaited_running_card_task:
logger.warning( logger.warning(
"[Feishu] running card task finished without message_id for source=%s, skipping duplicate non-final creation", "[Feishu] running card task finished without message_id for source=%s, skipping duplicate non-final creation",
source_message_id, source_message_id,
) )
else: else:
created_card_id = await self._ensure_running_card(source_message_id, msg.text) await self._ensure_running_card(source_message_id, msg.text)
self._remember_thread_mapping(msg, source_message_id, created_card_id)
if msg.is_final: if msg.is_final:
self._running_card_ids.pop(source_message_id, None) self._running_card_ids.pop(source_message_id, None)
@@ -581,129 +547,6 @@ class FeishuChannel(Channel):
# -- internal ---------------------------------------------------------- # -- internal ----------------------------------------------------------
def _remember_thread_mapping(self, msg: OutboundMessage, *topic_ids: str | None) -> None:
store = self.config.get("channel_store")
if store is None or not msg.thread_id:
return
metadata_topic_ids = [
msg.metadata.get("message_id"),
msg.metadata.get("root_id"),
msg.metadata.get("parent_id"),
msg.metadata.get("thread_id"),
msg.metadata.get("topic_id"),
]
user_id = ""
raw_user_id = msg.metadata.get("user_id")
if isinstance(raw_user_id, str):
user_id = raw_user_id
seen: set[str] = set()
for topic_id in [*topic_ids, *metadata_topic_ids]:
topic_id = self._non_empty_str(topic_id)
if not topic_id or topic_id in seen:
continue
seen.add(topic_id)
try:
store.set_thread_id(
self.name,
msg.chat_id,
msg.thread_id,
topic_id=topic_id,
user_id=user_id,
)
except Exception:
logger.exception("[Feishu] failed to remember thread mapping for topic_id=%s", topic_id)
def _remember_pending_clarification(self, msg: OutboundMessage, card_message_id: str | None) -> None:
if not msg.is_final or msg.metadata.get(PENDING_CLARIFICATION_METADATA_KEY) is not True:
return
user_id = self._non_empty_str(msg.metadata.get("user_id"))
topic_id = self._non_empty_str(msg.metadata.get("topic_id"))
source_message_id = self._non_empty_str(msg.thread_ts) or self._non_empty_str(msg.metadata.get("message_id"))
if not (user_id and topic_id and msg.thread_id and source_message_id and card_message_id):
return
key = self._pending_key(msg.chat_id, user_id)
pending = {
"thread_id": msg.thread_id,
"topic_id": topic_id,
"source_message_id": source_message_id,
"card_message_id": card_message_id,
"created_at": time.time(),
}
with self._thread_lock:
# Plain-message clarification continuity is a short-lived in-memory
# hint; explicit Feishu replies are still covered by persisted
# message-id mappings.
self._pending_clarifications.setdefault(key, []).append(pending)
logger.info(
"[Feishu] pending clarification remembered: chat_id=%s user_id=%s topic_id=%s thread_id=%s",
msg.chat_id,
user_id,
topic_id,
msg.thread_id,
)
def _consume_pending_clarification(self, chat_id: str, user_id: str) -> dict[str, Any] | None:
key = self._pending_key(chat_id, user_id)
with self._thread_lock:
pending_items = self._pending_clarifications.get(key)
if not pending_items:
return None
now = time.time()
while pending_items:
pending = pending_items.pop(0)
created_at = pending.get("created_at")
if isinstance(created_at, (int, float)) and now - created_at <= PENDING_CLARIFICATION_TTL_SECONDS:
if pending_items:
self._pending_clarifications[key] = pending_items
else:
self._pending_clarifications.pop(key, None)
return pending
logger.info("[Feishu] pending clarification expired: chat_id=%s user_id=%s", chat_id, user_id)
self._pending_clarifications.pop(key, None)
return None
def _ensure_pending_thread_mapping(self, chat_id: str, user_id: str, pending: dict[str, Any]) -> None:
store = self.config.get("channel_store")
topic_id = self._non_empty_str(pending.get("topic_id"))
thread_id = self._non_empty_str(pending.get("thread_id"))
if store is None or not topic_id or not thread_id:
return
try:
store.set_thread_id(self.name, chat_id, thread_id, topic_id=topic_id, user_id=user_id)
except Exception:
logger.exception("[Feishu] failed to restore pending clarification mapping for topic_id=%s", topic_id)
def _resolve_topic_id(
self,
chat_id: str,
msg_id: str,
*,
root_id: str | None,
parent_id: str | None,
thread_id: str | None,
) -> tuple[str, bool]:
store = self.config.get("channel_store")
candidates = [root_id, parent_id, thread_id]
if store is not None:
for candidate in candidates:
candidate = self._non_empty_str(candidate)
if not candidate:
continue
try:
if store.get_thread_id(self.name, chat_id, topic_id=candidate):
return candidate, True
except Exception:
logger.exception("[Feishu] failed to resolve stored topic mapping for topic_id=%s", candidate)
return root_id or msg_id, False
@staticmethod @staticmethod
def _log_future_error(fut, name: str, msg_id: str) -> None: def _log_future_error(fut, name: str, msg_id: str) -> None:
"""Callback for run_coroutine_threadsafe futures to surface errors.""" """Callback for run_coroutine_threadsafe futures to surface errors."""
@@ -744,9 +587,7 @@ class FeishuChannel(Channel):
# root_id is set when the message is a reply within a Feishu thread. # root_id is set when the message is a reply within a Feishu thread.
# Use it as topic_id so all replies share the same DeerFlow thread. # Use it as topic_id so all replies share the same DeerFlow thread.
root_id = self._non_empty_str(getattr(message, "root_id", None)) root_id = getattr(message, "root_id", None) or None
parent_id = self._non_empty_str(getattr(message, "parent_id", None))
feishu_thread_id = self._non_empty_str(getattr(message, "thread_id", None))
# Parse message content # Parse message content
content = json.loads(message.content) content = json.loads(message.content)
@@ -807,12 +648,10 @@ class FeishuChannel(Channel):
text = text.strip() text = text.strip()
logger.info( logger.info(
"[Feishu] parsed message: chat_id=%s, msg_id=%s, root_id=%s, parent_id=%s, thread_id=%s, sender=%s, text=%r", "[Feishu] parsed message: chat_id=%s, msg_id=%s, root_id=%s, sender=%s, text=%r",
chat_id, chat_id,
msg_id, msg_id,
root_id, root_id,
parent_id,
feishu_thread_id,
sender_id, sender_id,
text[:100] if text else "", text[:100] if text else "",
) )
@@ -828,24 +667,8 @@ class FeishuChannel(Channel):
else: else:
msg_type = InboundMessageType.CHAT msg_type = InboundMessageType.CHAT
# Prefer any platform message id that already maps to a DeerFlow # topic_id: use root_id for replies (same topic), msg_id for new messages (new topic)
# thread. This keeps replies to bot clarification cards in the topic_id = root_id or msg_id
# original conversation even when Feishu reports the card as root.
topic_id, resolved_from_stored_mapping = self._resolve_topic_id(
chat_id,
msg_id,
root_id=root_id,
parent_id=parent_id,
thread_id=feishu_thread_id,
)
resolved_from_pending = False
if msg_type == InboundMessageType.CHAT and not resolved_from_stored_mapping:
pending = self._consume_pending_clarification(chat_id, sender_id)
pending_topic_id = self._non_empty_str(pending.get("topic_id")) if pending else None
if pending_topic_id:
topic_id = pending_topic_id
self._ensure_pending_thread_mapping(chat_id, sender_id, pending)
resolved_from_pending = True
inbound = self._make_inbound( inbound = self._make_inbound(
chat_id=chat_id, chat_id=chat_id,
@@ -854,15 +677,7 @@ class FeishuChannel(Channel):
msg_type=msg_type, msg_type=msg_type,
thread_ts=msg_id, thread_ts=msg_id,
files=files_list, files=files_list,
metadata={ metadata={"message_id": msg_id, "root_id": root_id},
"message_id": msg_id,
"root_id": root_id,
"parent_id": parent_id,
"thread_id": feishu_thread_id,
"topic_id": topic_id,
"user_id": sender_id,
RESOLVED_FROM_PENDING_CLARIFICATION_METADATA_KEY: resolved_from_pending,
},
) )
inbound.topic_id = topic_id inbound.topic_id = topic_id
+22 -169
View File
@@ -1,4 +1,4 @@
"""ChannelManager — consumes inbound messages and dispatches them to the DeerFlow agent via Gateway.""" """ChannelManager — consumes inbound messages and dispatches them to the DeerFlow agent via LangGraph Server."""
from __future__ import annotations from __future__ import annotations
@@ -15,23 +15,12 @@ import httpx
from langgraph_sdk.errors import ConflictError from langgraph_sdk.errors import ConflictError
from app.channels.commands import KNOWN_CHANNEL_COMMANDS from app.channels.commands import KNOWN_CHANNEL_COMMANDS
from app.channels.message_bus import ( from app.channels.message_bus import InboundMessage, InboundMessageType, MessageBus, OutboundMessage, ResolvedAttachment
PENDING_CLARIFICATION_METADATA_KEY,
InboundMessage,
InboundMessageType,
MessageBus,
OutboundMessage,
ResolvedAttachment,
)
from app.channels.store import ChannelStore from app.channels.store import ChannelStore
from app.gateway.csrf_middleware import CSRF_COOKIE_NAME, CSRF_HEADER_NAME, generate_csrf_token
from app.gateway.internal_auth import create_internal_auth_headers
from deerflow.config.paths import make_safe_user_id
from deerflow.runtime.user_context import get_effective_user_id
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
DEFAULT_LANGGRAPH_URL = "http://localhost:8001/api" DEFAULT_LANGGRAPH_URL = "http://localhost:2024"
DEFAULT_GATEWAY_URL = "http://localhost:8001" DEFAULT_GATEWAY_URL = "http://localhost:8001"
DEFAULT_ASSISTANT_ID = "lead_agent" DEFAULT_ASSISTANT_ID = "lead_agent"
CUSTOM_AGENT_NAME_PATTERN = re.compile(r"^[A-Za-z0-9-]+$") CUSTOM_AGENT_NAME_PATTERN = re.compile(r"^[A-Za-z0-9-]+$")
@@ -46,8 +35,6 @@ STREAM_UPDATE_MIN_INTERVAL_SECONDS = 0.35
THREAD_BUSY_MESSAGE = "This conversation is already processing another request. Please wait for it to finish and try again." THREAD_BUSY_MESSAGE = "This conversation is already processing another request. Please wait for it to finish and try again."
CHANNEL_CAPABILITIES = { CHANNEL_CAPABILITIES = {
"dingtalk": {"supports_streaming": False},
"discord": {"supports_streaming": False},
"feishu": {"supports_streaming": True}, "feishu": {"supports_streaming": True},
"slack": {"supports_streaming": False}, "slack": {"supports_streaming": False},
"telegram": {"supports_streaming": False}, "telegram": {"supports_streaming": False},
@@ -57,13 +44,6 @@ CHANNEL_CAPABILITIES = {
InboundFileReader = Callable[[dict[str, Any], httpx.AsyncClient], Awaitable[bytes | None]] InboundFileReader = Callable[[dict[str, Any], httpx.AsyncClient], Awaitable[bytes | None]]
_METADATA_DROP_KEYS = frozenset({"raw_message", "ref_msg"})
def _slim_metadata(meta: dict[str, Any]) -> dict[str, Any]:
"""Return a shallow copy of *meta* with known-large keys removed."""
return {k: v for k, v in meta.items() if k not in _METADATA_DROP_KEYS}
INBOUND_FILE_READERS: dict[str, InboundFileReader] = {} INBOUND_FILE_READERS: dict[str, InboundFileReader] = {}
@@ -163,6 +143,7 @@ def _extract_response_text(result: dict | list) -> str:
Handles special cases: Handles special cases:
- Regular AI text responses - Regular AI text responses
- Clarification interrupts (``ask_clarification`` tool messages) - Clarification interrupts (``ask_clarification`` tool messages)
- AI messages with tool_calls but no text content
""" """
if isinstance(result, list): if isinstance(result, list):
messages = result messages = result
@@ -181,8 +162,6 @@ def _extract_response_text(result: dict | list) -> str:
# Stop at the last human message — anything before it is a previous turn # Stop at the last human message — anything before it is a previous turn
if msg_type == "human": if msg_type == "human":
if _is_hidden_human_control_message(msg):
continue
break break
# Check for tool messages from ask_clarification (interrupt case) # Check for tool messages from ask_clarification (interrupt case)
@@ -210,54 +189,6 @@ def _extract_response_text(result: dict | list) -> str:
return "" return ""
def _messages_from_result(result: dict | list) -> list[Any]:
if isinstance(result, list):
return result
if isinstance(result, dict):
messages = result.get("messages", [])
if isinstance(messages, list):
return messages
return []
def _current_turn_messages(result: dict | list) -> list[dict[str, Any]]:
messages = _messages_from_result(result)
current_turn: list[dict[str, Any]] = []
for msg in reversed(messages):
if not isinstance(msg, dict):
continue
if msg.get("type") == "human":
break
current_turn.append(msg)
current_turn.reverse()
return current_turn
def _has_current_turn_clarification(result: dict | list) -> bool:
"""Return True only when the current turn's final result is clarification."""
for msg in reversed(_current_turn_messages(result)):
msg_type = msg.get("type")
if msg_type == "tool":
return msg.get("name") == "ask_clarification"
if msg_type == "ai":
content = msg.get("content")
if isinstance(content, str):
if content:
return False
elif content:
return False
if msg.get("tool_calls"):
return False
return False
def _response_metadata(base_metadata: dict[str, Any], *, pending_clarification: bool = False) -> dict[str, Any]:
metadata = _slim_metadata(base_metadata)
if pending_clarification:
metadata[PENDING_CLARIFICATION_METADATA_KEY] = True
return metadata
def _extract_text_content(content: Any) -> str: def _extract_text_content(content: Any) -> str:
"""Extract text from a streaming payload content field.""" """Extract text from a streaming payload content field."""
if isinstance(content, str): if isinstance(content, str):
@@ -371,8 +302,6 @@ def _extract_artifacts(result: dict | list) -> list[str]:
continue continue
# Stop at the last human message — anything before it is a previous turn # Stop at the last human message — anything before it is a previous turn
if msg.get("type") == "human": if msg.get("type") == "human":
if _is_hidden_human_control_message(msg):
continue
break break
# Look for AI messages with present_files tool calls # Look for AI messages with present_files tool calls
if msg.get("type") == "ai": if msg.get("type") == "ai":
@@ -385,18 +314,6 @@ def _extract_artifacts(result: dict | list) -> list[str]:
return artifacts return artifacts
def _is_hidden_human_control_message(msg: Mapping[str, Any]) -> bool:
"""Return whether a human message is an internal control message hidden from UI."""
if msg.get("type") != "human":
return False
additional_kwargs = msg.get("additional_kwargs")
if not isinstance(additional_kwargs, Mapping):
return False
return additional_kwargs.get("hide_from_ui") is True
def _format_artifact_text(artifacts: list[str]) -> str: def _format_artifact_text(artifacts: list[str]) -> str:
"""Format artifact paths into a human-readable text block listing filenames.""" """Format artifact paths into a human-readable text block listing filenames."""
import posixpath import posixpath
@@ -424,15 +341,14 @@ def _resolve_attachments(thread_id: str, artifacts: list[str]) -> list[ResolvedA
attachments: list[ResolvedAttachment] = [] attachments: list[ResolvedAttachment] = []
paths = get_paths() paths = get_paths()
user_id = get_effective_user_id() outputs_dir = paths.sandbox_outputs_dir(thread_id).resolve()
outputs_dir = paths.sandbox_outputs_dir(thread_id, user_id=user_id).resolve()
for virtual_path in artifacts: for virtual_path in artifacts:
# Security: only allow files from the agent outputs directory # Security: only allow files from the agent outputs directory
if not virtual_path.startswith(_OUTPUTS_VIRTUAL_PREFIX): if not virtual_path.startswith(_OUTPUTS_VIRTUAL_PREFIX):
logger.warning("[Manager] rejected non-outputs artifact path: %s", virtual_path) logger.warning("[Manager] rejected non-outputs artifact path: %s", virtual_path)
continue continue
try: try:
actual = paths.resolve_virtual_path(thread_id, virtual_path, user_id=user_id) actual = paths.resolve_virtual_path(thread_id, virtual_path)
# Verify the resolved path is actually under the outputs directory # Verify the resolved path is actually under the outputs directory
# (guards against path-traversal even after prefix check) # (guards against path-traversal even after prefix check)
try: try:
@@ -491,13 +407,7 @@ async def _ingest_inbound_files(thread_id: str, msg: InboundMessage) -> list[dic
if not msg.files: if not msg.files:
return [] return []
from deerflow.uploads.manager import ( from deerflow.uploads.manager import claim_unique_filename, ensure_uploads_dir, normalize_filename
UnsafeUploadPathError,
claim_unique_filename,
ensure_uploads_dir,
normalize_filename,
write_upload_file_no_symlink,
)
uploads_dir = ensure_uploads_dir(thread_id) uploads_dir = ensure_uploads_dir(thread_id)
seen_names = {entry.name for entry in uploads_dir.iterdir() if entry.is_file()} seen_names = {entry.name for entry in uploads_dir.iterdir() if entry.is_file()}
@@ -548,10 +458,7 @@ async def _ingest_inbound_files(thread_id: str, msg: InboundMessage) -> list[dic
dest = uploads_dir / safe_name dest = uploads_dir / safe_name
try: try:
dest = write_upload_file_no_symlink(uploads_dir, safe_name, data) dest.write_bytes(data)
except UnsafeUploadPathError:
logger.warning("[Manager] skipping inbound file with unsafe destination: %s", safe_name)
continue
except Exception: except Exception:
logger.exception("[Manager] failed to write inbound file: %s", dest) logger.exception("[Manager] failed to write inbound file: %s", dest)
continue continue
@@ -599,7 +506,7 @@ class ChannelManager:
"""Core dispatcher that bridges IM channels to the DeerFlow agent. """Core dispatcher that bridges IM channels to the DeerFlow agent.
It reads from the MessageBus inbound queue, creates/reuses threads on It reads from the MessageBus inbound queue, creates/reuses threads on
Gateway's LangGraph-compatible API, sends messages via ``runs.wait``, and publishes the LangGraph Server, sends messages via ``runs.wait``, and publishes
outbound responses back through the bus. outbound responses back through the bus.
""" """
@@ -624,20 +531,12 @@ class ChannelManager:
self._default_session = _as_dict(default_session) self._default_session = _as_dict(default_session)
self._channel_sessions = dict(channel_sessions or {}) self._channel_sessions = dict(channel_sessions or {})
self._client = None # lazy init — langgraph_sdk async client self._client = None # lazy init — langgraph_sdk async client
self._csrf_token = generate_csrf_token()
self._semaphore: asyncio.Semaphore | None = None self._semaphore: asyncio.Semaphore | None = None
self._running = False self._running = False
self._task: asyncio.Task | None = None self._task: asyncio.Task | None = None
@staticmethod @staticmethod
def _channel_supports_streaming(channel_name: str) -> bool: def _channel_supports_streaming(channel_name: str) -> bool:
from .service import get_channel_service
service = get_channel_service()
if service:
channel = service.get_channel(channel_name)
if channel is not None:
return channel.supports_streaming
return CHANNEL_CAPABILITIES.get(channel_name, {}).get("supports_streaming", False) return CHANNEL_CAPABILITIES.get(channel_name, {}).get("supports_streaming", False)
def _resolve_session_layer(self, msg: InboundMessage) -> tuple[dict[str, Any], dict[str, Any]]: def _resolve_session_layer(self, msg: InboundMessage) -> tuple[dict[str, Any], dict[str, Any]]:
@@ -660,31 +559,12 @@ class ChannelManager:
user_layer.get("config"), user_layer.get("config"),
) )
configurable = run_config.get("configurable")
if isinstance(configurable, Mapping):
configurable = dict(configurable)
else:
configurable = {}
run_config["configurable"] = configurable
# Pin channel-triggered runs to the root graph namespace so follow-up
# turns continue from the same conversation checkpoint.
configurable["checkpoint_ns"] = ""
configurable["thread_id"] = thread_id
# ``user_id`` drives user-scoped filesystem buckets that only accept
# ``[A-Za-z0-9_-]``, so normalize the channel id and keep the raw value
# under ``channel_user_id`` for platform-facing lookups.
run_context_identity: dict[str, Any] = {"thread_id": thread_id}
if msg.user_id:
run_context_identity["user_id"] = make_safe_user_id(msg.user_id)
run_context_identity["channel_user_id"] = msg.user_id
run_context = _merge_dicts( run_context = _merge_dicts(
DEFAULT_RUN_CONTEXT, DEFAULT_RUN_CONTEXT,
self._default_session.get("context"), self._default_session.get("context"),
channel_layer.get("context"), channel_layer.get("context"),
user_layer.get("context"), user_layer.get("context"),
run_context_identity, {"thread_id": thread_id},
) )
# Custom agents are implemented as lead_agent + agent_name context. # Custom agents are implemented as lead_agent + agent_name context.
@@ -703,14 +583,7 @@ class ChannelManager:
if self._client is None: if self._client is None:
from langgraph_sdk import get_client from langgraph_sdk import get_client
self._client = get_client( self._client = get_client(url=self._langgraph_url)
url=self._langgraph_url,
headers={
**create_internal_auth_headers(),
CSRF_HEADER_NAME: self._csrf_token,
"Cookie": f"{CSRF_COOKIE_NAME}={self._csrf_token}",
},
)
return self._client return self._client
# -- lifecycle --------------------------------------------------------- # -- lifecycle ---------------------------------------------------------
@@ -793,7 +666,7 @@ class ChannelManager:
# -- chat handling ----------------------------------------------------- # -- chat handling -----------------------------------------------------
async def _create_thread(self, client, msg: InboundMessage) -> str: async def _create_thread(self, client, msg: InboundMessage) -> str:
"""Create a new thread through Gateway and store the mapping.""" """Create a new thread on the LangGraph Server and store the mapping."""
thread = await client.threads.create() thread = await client.threads.create()
thread_id = thread["thread_id"] thread_id = thread["thread_id"]
self.store.set_thread_id( self.store.set_thread_id(
@@ -803,7 +676,7 @@ class ChannelManager:
topic_id=msg.topic_id, topic_id=msg.topic_id,
user_id=msg.user_id, user_id=msg.user_id,
) )
logger.info("[Manager] new thread created through Gateway: thread_id=%s for chat_id=%s topic_id=%s", thread_id, msg.chat_id, msg.topic_id) logger.info("[Manager] new thread created on LangGraph Server: thread_id=%s for chat_id=%s topic_id=%s", thread_id, msg.chat_id, msg.topic_id)
return thread_id return thread_id
async def _handle_chat(self, msg: InboundMessage, extra_context: dict[str, Any] | None = None) -> None: async def _handle_chat(self, msg: InboundMessage, extra_context: dict[str, Any] | None = None) -> None:
@@ -852,25 +725,15 @@ class ChannelManager:
return return
logger.info("[Manager] invoking runs.wait(thread_id=%s, text=%r)", thread_id, msg.text[:100]) logger.info("[Manager] invoking runs.wait(thread_id=%s, text=%r)", thread_id, msg.text[:100])
try: result = await client.runs.wait(
result = await client.runs.wait( thread_id,
thread_id, assistant_id,
assistant_id, input={"messages": [{"role": "human", "content": msg.text}]},
input={"messages": [{"role": "human", "content": msg.text}]}, config=run_config,
config=run_config, context=run_context,
context=run_context, )
multitask_strategy="reject",
)
except Exception as exc:
if _is_thread_busy_error(exc):
logger.warning("[Manager] thread busy (concurrent run rejected): thread_id=%s", thread_id)
await self._send_error(msg, THREAD_BUSY_MESSAGE)
return
else:
raise
response_text = _extract_response_text(result) response_text = _extract_response_text(result)
pending_clarification = _has_current_turn_clarification(result)
artifacts = _extract_artifacts(result) artifacts = _extract_artifacts(result)
logger.info( logger.info(
@@ -896,7 +759,6 @@ class ChannelManager:
artifacts=artifacts, artifacts=artifacts,
attachments=attachments, attachments=attachments,
thread_ts=msg.thread_ts, thread_ts=msg.thread_ts,
metadata=_response_metadata(msg.metadata, pending_clarification=pending_clarification),
) )
logger.info("[Manager] publishing outbound message to bus: channel=%s, chat_id=%s", msg.channel_name, msg.chat_id) logger.info("[Manager] publishing outbound message to bus: channel=%s, chat_id=%s", msg.channel_name, msg.chat_id)
await self.bus.publish_outbound(outbound) await self.bus.publish_outbound(outbound)
@@ -958,7 +820,6 @@ class ChannelManager:
text=latest_text, text=latest_text,
is_final=False, is_final=False,
thread_ts=msg.thread_ts, thread_ts=msg.thread_ts,
metadata=_response_metadata(msg.metadata),
) )
) )
last_published_text = latest_text last_published_text = latest_text
@@ -972,7 +833,6 @@ class ChannelManager:
finally: finally:
result = last_values if last_values is not None else {"messages": [{"type": "ai", "content": latest_text}]} result = last_values if last_values is not None else {"messages": [{"type": "ai", "content": latest_text}]}
response_text = _extract_response_text(result) response_text = _extract_response_text(result)
pending_clarification = _has_current_turn_clarification(result)
artifacts = _extract_artifacts(result) artifacts = _extract_artifacts(result)
response_text, attachments = _prepare_artifact_delivery(thread_id, response_text, artifacts) response_text, attachments = _prepare_artifact_delivery(thread_id, response_text, artifacts)
@@ -1004,7 +864,6 @@ class ChannelManager:
attachments=attachments, attachments=attachments,
is_final=True, is_final=True,
thread_ts=msg.thread_ts, thread_ts=msg.thread_ts,
metadata=_response_metadata(msg.metadata, pending_clarification=pending_clarification),
) )
) )
@@ -1024,7 +883,7 @@ class ChannelManager:
return return
if command == "new": if command == "new":
# Create a new thread through Gateway # Create a new thread on the LangGraph Server
client = self._get_client() client = self._get_client()
thread = await client.threads.create() thread = await client.threads.create()
new_thread_id = thread["thread_id"] new_thread_id = thread["thread_id"]
@@ -1063,7 +922,6 @@ class ChannelManager:
thread_id=self.store.get_thread_id(msg.channel_name, msg.chat_id) or "", thread_id=self.store.get_thread_id(msg.channel_name, msg.chat_id) or "",
text=reply, text=reply,
thread_ts=msg.thread_ts, thread_ts=msg.thread_ts,
metadata=_slim_metadata(msg.metadata),
) )
await self.bus.publish_outbound(outbound) await self.bus.publish_outbound(outbound)
@@ -1073,11 +931,7 @@ class ChannelManager:
try: try:
async with httpx.AsyncClient() as http: async with httpx.AsyncClient() as http:
resp = await http.get( resp = await http.get(f"{self._gateway_url}{path}", timeout=10)
f"{self._gateway_url}{path}",
timeout=10,
headers=create_internal_auth_headers(),
)
resp.raise_for_status() resp.raise_for_status()
data = resp.json() data = resp.json()
except Exception: except Exception:
@@ -1101,6 +955,5 @@ class ChannelManager:
thread_id=self.store.get_thread_id(msg.channel_name, msg.chat_id) or "", thread_id=self.store.get_thread_id(msg.channel_name, msg.chat_id) or "",
text=error_text, text=error_text,
thread_ts=msg.thread_ts, thread_ts=msg.thread_ts,
metadata=_slim_metadata(msg.metadata),
) )
await self.bus.publish_outbound(outbound) await self.bus.publish_outbound(outbound)
-3
View File
@@ -13,9 +13,6 @@ from typing import Any
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
PENDING_CLARIFICATION_METADATA_KEY = "pending_clarification"
RESOLVED_FROM_PENDING_CLARIFICATION_METADATA_KEY = "resolved_from_pending_clarification"
# --------------------------------------------------------------------------- # ---------------------------------------------------------------------------
# Message types # Message types
+9 -42
View File
@@ -4,7 +4,7 @@ from __future__ import annotations
import logging import logging
import os import os
from typing import TYPE_CHECKING, Any from typing import Any
from app.channels.base import Channel from app.channels.base import Channel
from app.channels.manager import DEFAULT_GATEWAY_URL, DEFAULT_LANGGRAPH_URL, ChannelManager from app.channels.manager import DEFAULT_GATEWAY_URL, DEFAULT_LANGGRAPH_URL, ChannelManager
@@ -13,13 +13,8 @@ from app.channels.store import ChannelStore
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
if TYPE_CHECKING:
from deerflow.config.app_config import AppConfig
# Channel name → import path for lazy loading # Channel name → import path for lazy loading
_CHANNEL_REGISTRY: dict[str, str] = { _CHANNEL_REGISTRY: dict[str, str] = {
"dingtalk": "app.channels.dingtalk:DingTalkChannel",
"discord": "app.channels.discord:DiscordChannel",
"feishu": "app.channels.feishu:FeishuChannel", "feishu": "app.channels.feishu:FeishuChannel",
"slack": "app.channels.slack:SlackChannel", "slack": "app.channels.slack:SlackChannel",
"telegram": "app.channels.telegram:TelegramChannel", "telegram": "app.channels.telegram:TelegramChannel",
@@ -27,17 +22,6 @@ _CHANNEL_REGISTRY: dict[str, str] = {
"wecom": "app.channels.wecom:WeComChannel", "wecom": "app.channels.wecom:WeComChannel",
} }
# Keys that indicate a user has configured credentials for a channel.
_CHANNEL_CREDENTIAL_KEYS: dict[str, list[str]] = {
"dingtalk": ["client_id", "client_secret"],
"discord": ["bot_token"],
"feishu": ["app_id", "app_secret"],
"slack": ["bot_token", "app_token"],
"telegram": ["bot_token"],
"wecom": ["bot_id", "bot_secret"],
"wechat": ["bot_token"],
}
_CHANNELS_LANGGRAPH_URL_ENV = "DEER_FLOW_CHANNELS_LANGGRAPH_URL" _CHANNELS_LANGGRAPH_URL_ENV = "DEER_FLOW_CHANNELS_LANGGRAPH_URL"
_CHANNELS_GATEWAY_URL_ENV = "DEER_FLOW_CHANNELS_GATEWAY_URL" _CHANNELS_GATEWAY_URL_ENV = "DEER_FLOW_CHANNELS_GATEWAY_URL"
@@ -80,15 +64,14 @@ class ChannelService:
self._running = False self._running = False
@classmethod @classmethod
def from_app_config(cls, app_config: AppConfig | None = None) -> ChannelService: def from_app_config(cls) -> ChannelService:
"""Create a ChannelService from the application config.""" """Create a ChannelService from the application config."""
if app_config is None: from deerflow.config.app_config import get_app_config
from deerflow.config.app_config import get_app_config
app_config = get_app_config() config = get_app_config()
channels_config = {} channels_config = {}
# extra fields are allowed by AppConfig (extra="allow") # extra fields are allowed by AppConfig (extra="allow")
extra = app_config.model_extra or {} extra = config.model_extra or {}
if "channels" in extra: if "channels" in extra:
channels_config = extra["channels"] channels_config = extra["channels"]
return cls(channels_config=channels_config) return cls(channels_config=channels_config)
@@ -104,16 +87,7 @@ class ChannelService:
if not isinstance(channel_config, dict): if not isinstance(channel_config, dict):
continue continue
if not channel_config.get("enabled", False): if not channel_config.get("enabled", False):
cred_keys = _CHANNEL_CREDENTIAL_KEYS.get(name, []) logger.info("Channel %s is disabled, skipping", name)
has_creds = any(not isinstance(channel_config.get(k), bool) and channel_config.get(k) is not None and str(channel_config[k]).strip() for k in cred_keys)
if has_creds:
logger.warning(
"Channel '%s' has credentials configured but is disabled. Set enabled: true under channels.%s in config.yaml to activate it.",
name,
name,
)
else:
logger.info("Channel %s is disabled, skipping", name)
continue continue
await self._start_channel(name, channel_config) await self._start_channel(name, channel_config)
@@ -167,19 +141,12 @@ class ChannelService:
return False return False
try: try:
config = dict(config)
config["channel_store"] = self.store
channel = channel_cls(bus=self.bus, config=config) channel = channel_cls(bus=self.bus, config=config)
self._channels[name] = channel
await channel.start() await channel.start()
if not channel.is_running: self._channels[name] = channel
self._channels.pop(name, None)
logger.error("Channel %s did not enter a running state after start()", name)
return False
logger.info("Channel %s started", name) logger.info("Channel %s started", name)
return True return True
except Exception: except Exception:
self._channels.pop(name, None)
logger.exception("Failed to start channel %s", name) logger.exception("Failed to start channel %s", name)
return False return False
@@ -214,12 +181,12 @@ def get_channel_service() -> ChannelService | None:
return _channel_service return _channel_service
async def start_channel_service(app_config: AppConfig | None = None) -> ChannelService: async def start_channel_service() -> ChannelService:
"""Create and start the global ChannelService from app config.""" """Create and start the global ChannelService from app config."""
global _channel_service global _channel_service
if _channel_service is not None: if _channel_service is not None:
return _channel_service return _channel_service
_channel_service = ChannelService.from_app_config(app_config) _channel_service = ChannelService.from_app_config()
await _channel_service.start() await _channel_service.start()
return _channel_service return _channel_service
+2 -20
View File
@@ -16,31 +16,13 @@ logger = logging.getLogger(__name__)
_slack_md_converter = SlackMarkdownConverter() _slack_md_converter = SlackMarkdownConverter()
def _normalize_allowed_users(allowed_users: Any) -> set[str]:
if allowed_users is None:
return set()
if isinstance(allowed_users, str):
values = [allowed_users]
elif isinstance(allowed_users, list | tuple | set):
values = allowed_users
else:
logger.warning(
"Slack allowed_users should be a list of Slack user IDs or a single Slack user ID string; treating %s as one string value",
type(allowed_users).__name__,
)
values = [allowed_users]
return {str(user_id) for user_id in values if str(user_id)}
class SlackChannel(Channel): class SlackChannel(Channel):
"""Slack IM channel using Socket Mode (WebSocket, no public IP). """Slack IM channel using Socket Mode (WebSocket, no public IP).
Configuration keys (in ``config.yaml`` under ``channels.slack``): Configuration keys (in ``config.yaml`` under ``channels.slack``):
- ``bot_token``: Slack Bot User OAuth Token (xoxb-...). - ``bot_token``: Slack Bot User OAuth Token (xoxb-...).
- ``app_token``: Slack App-Level Token (xapp-...) for Socket Mode. - ``app_token``: Slack App-Level Token (xapp-...) for Socket Mode.
- ``allowed_users``: (optional) List of allowed Slack user IDs, or a - ``allowed_users``: (optional) List of allowed Slack user IDs. Empty = allow all.
single Slack user ID string as shorthand. Empty = allow all. Other
scalar values are treated as a single string with a warning.
""" """
def __init__(self, bus: MessageBus, config: dict[str, Any]) -> None: def __init__(self, bus: MessageBus, config: dict[str, Any]) -> None:
@@ -48,7 +30,7 @@ class SlackChannel(Channel):
self._socket_client = None self._socket_client = None
self._web_client = None self._web_client = None
self._loop: asyncio.AbstractEventLoop | None = None self._loop: asyncio.AbstractEventLoop | None = None
self._allowed_users = _normalize_allowed_users(config.get("allowed_users", [])) self._allowed_users: set[str] = {str(user_id) for user_id in config.get("allowed_users", [])}
async def start(self) -> None: async def start(self) -> None:
if self._running: if self._running:
-4
View File
@@ -29,10 +29,6 @@ class WeComChannel(Channel):
self._ws_stream_ids: dict[str, str] = {} self._ws_stream_ids: dict[str, str] = {}
self._working_message = "Working on it..." self._working_message = "Working on it..."
@property
def supports_streaming(self) -> bool:
return True
def _clear_ws_context(self, thread_ts: str | None) -> None: def _clear_ws_context(self, thread_ts: str | None) -> None:
if not thread_ts: if not thread_ts:
return return
+91 -101
View File
@@ -1,14 +1,15 @@
import asyncio
import logging import logging
import os
from collections.abc import AsyncGenerator from collections.abc import AsyncGenerator
from contextlib import asynccontextmanager from contextlib import asynccontextmanager
from datetime import UTC
from fastapi import FastAPI from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware from fastapi.middleware.cors import CORSMiddleware
from app.gateway.auth_middleware import AuthMiddleware from app.gateway.auth_middleware import AuthMiddleware
from app.gateway.config import get_gateway_config from app.gateway.config import get_gateway_config
from app.gateway.csrf_middleware import CSRFMiddleware, get_configured_cors_origins from app.gateway.csrf_middleware import CSRFMiddleware
from app.gateway.deps import langgraph_runtime from app.gateway.deps import langgraph_runtime
from app.gateway.routers import ( from app.gateway.routers import (
agents, agents,
@@ -27,13 +28,9 @@ from app.gateway.routers import (
threads, threads,
uploads, uploads,
) )
from deerflow.config import app_config as deerflow_app_config from deerflow.config.app_config import get_app_config
from deerflow.config.app_config import apply_logging_level
AppConfig = deerflow_app_config.AppConfig # Configure logging
get_app_config = deerflow_app_config.get_app_config
# Default logging; lifespan overrides from config.yaml log_level.
logging.basicConfig( logging.basicConfig(
level=logging.INFO, level=logging.INFO,
format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
@@ -42,74 +39,79 @@ logging.basicConfig(
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
# Upper bound (seconds) each lifespan shutdown hook is allowed to run.
# Bounds worker exit time so uvicorn's reload supervisor does not keep
# firing signals into a worker that is stuck waiting for shutdown cleanup.
_SHUTDOWN_HOOK_TIMEOUT_SECONDS = 5.0
async def _ensure_admin_user(app: FastAPI) -> None: async def _ensure_admin_user(app: FastAPI) -> None:
"""Startup hook: handle first boot and migrate orphan threads otherwise. """Auto-create the admin user on first boot if no users exist.
After admin creation, migrate orphan threads from the LangGraph After admin creation, migrate orphan threads from the LangGraph
store (metadata.user_id unset) to the admin account. This is the store (metadata.owner_id unset) to the admin account. This is the
"no-auth → with-auth" upgrade path: users who ran DeerFlow without "no-auth → with-auth" upgrade path: users who ran DeerFlow without
authentication have existing LangGraph thread data that needs an authentication have existing LangGraph thread data that needs an
owner assigned. owner assigned.
First boot (no admin exists):
- Does NOT create any user accounts automatically.
- The operator must visit ``/setup`` to create the first admin.
Subsequent boots (admin already exists): No SQL persistence migration is needed: the four owner_id columns
- Runs the one-time "no-auth → with-auth" orphan thread migration for
existing LangGraph thread metadata that has no user_id.
No SQL persistence migration is needed: the four user_id columns
(threads_meta, runs, run_events, feedback) only come into existence (threads_meta, runs, run_events, feedback) only come into existence
alongside the auth module via create_all, so freshly created tables alongside the auth module via create_all, so freshly created tables
never contain NULL-owner rows. 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.
""" """
from sqlalchemy import select import secrets
from app.gateway.auth.credential_file import write_initial_credentials
from app.gateway.deps import get_local_provider from app.gateway.deps import get_local_provider
from deerflow.persistence.engine import get_session_factory
from deerflow.persistence.user.model import UserRow
try: def _announce_credentials(email: str, password: str, *, label: str, headline: str) -> None:
provider = get_local_provider() """Write the password to a 0600 file and log the path (never the secret)."""
except RuntimeError: cred_path = write_initial_credentials(email, password, label=label)
# Auth persistence may not be initialized in some test/boot paths.
# Skip admin migration work rather than failing gateway startup.
logger.warning("Auth persistence not ready; skipping admin bootstrap check")
return
sf = get_session_factory()
if sf is None:
return
admin_count = await provider.count_admin_users()
if admin_count == 0:
logger.info("=" * 60) logger.info("=" * 60)
logger.info(" First boot detected — no admin account exists.") logger.info(" %s", headline)
logger.info(" Visit /setup to complete admin account creation.") logger.info(" Credentials written to: %s (mode 0600)", cred_path)
logger.info(" Change it after login: Settings -> Account")
logger.info("=" * 60) logger.info("=" * 60)
return
# Admin already exists — run orphan thread migration for any provider = get_local_provider()
# LangGraph thread metadata that pre-dates the auth module. user_count = await provider.count_users()
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: admin = None
return # Should not happen (admin_count > 0 above), but be safe.
admin_id = str(row.id) 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
age = time.time() - admin.created_at.replace(tzinfo=UTC).timestamp()
if age >= 30:
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)
_announce_credentials(admin.email, password, label="reset", headline="Admin account setup incomplete — password reset")
if admin is None:
return # Nothing to bind orphans to.
admin_id = str(admin.id)
# LangGraph store orphan migration — non-fatal. # LangGraph store orphan migration — non-fatal.
# This covers the "no-auth → with-auth" upgrade path for users # This covers the "no-auth → with-auth" upgrade path for users
# whose existing LangGraph thread metadata has no user_id set. # whose existing LangGraph thread metadata has no owner_id set.
store = getattr(app.state, "store", None) store = getattr(app.state, "store", None)
if store is not None: if store is not None:
try: try:
@@ -141,7 +143,7 @@ async def _iter_store_items(store, namespace, *, page_size: int = 500):
async def _migrate_orphaned_threads(store, admin_user_id: str) -> int: async def _migrate_orphaned_threads(store, admin_user_id: str) -> int:
"""Migrate LangGraph store threads with no user_id to the given admin. """Migrate LangGraph store threads with no owner_id to the given admin.
Uses cursor pagination so all orphans are migrated regardless of Uses cursor pagination so all orphans are migrated regardless of
count. Returns the number of rows migrated. count. Returns the number of rows migrated.
@@ -149,8 +151,8 @@ async def _migrate_orphaned_threads(store, admin_user_id: str) -> int:
migrated = 0 migrated = 0
async for item in _iter_store_items(store, ("threads",)): async for item in _iter_store_items(store, ("threads",)):
metadata = item.value.get("metadata", {}) metadata = item.value.get("metadata", {})
if not metadata.get("user_id"): if not metadata.get("owner_id"):
metadata["user_id"] = admin_user_id metadata["owner_id"] = admin_user_id
item.value["metadata"] = metadata item.value["metadata"] = metadata
await store.aput(("threads",), item.key, item.value) await store.aput(("threads",), item.key, item.value)
migrated += 1 migrated += 1
@@ -161,16 +163,9 @@ async def _migrate_orphaned_threads(store, admin_user_id: str) -> int:
async def lifespan(app: FastAPI) -> AsyncGenerator[None, None]: async def lifespan(app: FastAPI) -> AsyncGenerator[None, None]:
"""Application lifespan handler.""" """Application lifespan handler."""
# Load config and check necessary environment variables at startup. # Load config and check necessary environment variables at startup
# `startup_config` is a local snapshot used only for one-shot bootstrap
# work (logging level, langgraph_runtime engines, channels). Request-time
# config resolution always routes through `get_app_config()` in
# `app/gateway/deps.py::get_config()` so `config.yaml` edits become
# visible without a process restart. We deliberately do NOT cache this
# snapshot on `app.state` to keep that contract enforceable.
try: try:
startup_config = get_app_config() get_app_config()
apply_logging_level(startup_config.log_level)
logger.info("Configuration loaded successfully") logger.info("Configuration loaded successfully")
except Exception as e: except Exception as e:
error_msg = f"Failed to load configuration during gateway startup: {e}" error_msg = f"Failed to load configuration during gateway startup: {e}"
@@ -180,10 +175,10 @@ async def lifespan(app: FastAPI) -> AsyncGenerator[None, None]:
logger.info(f"Starting API Gateway on {config.host}:{config.port}") logger.info(f"Starting API Gateway on {config.host}:{config.port}")
# Initialize LangGraph runtime components (StreamBridge, RunManager, checkpointer, store) # Initialize LangGraph runtime components (StreamBridge, RunManager, checkpointer, store)
async with langgraph_runtime(app, startup_config): async with langgraph_runtime(app):
logger.info("LangGraph runtime initialised") logger.info("LangGraph runtime initialised")
# Check admin bootstrap state and migrate orphan threads after admin exists. # Ensure admin user exists (auto-create on first boot)
# Must run AFTER langgraph_runtime so app.state.store is available for thread migration # Must run AFTER langgraph_runtime so app.state.store is available for thread migration
await _ensure_admin_user(app) await _ensure_admin_user(app)
@@ -191,26 +186,18 @@ async def lifespan(app: FastAPI) -> AsyncGenerator[None, None]:
try: try:
from app.channels.service import start_channel_service from app.channels.service import start_channel_service
channel_service = await start_channel_service(startup_config) channel_service = await start_channel_service()
logger.info("Channel service started: %s", channel_service.get_status()) logger.info("Channel service started: %s", channel_service.get_status())
except Exception: except Exception:
logger.exception("No IM channels configured or channel service failed to start") logger.exception("No IM channels configured or channel service failed to start")
yield yield
# Stop channel service on shutdown (bounded to prevent worker hang) # Stop channel service on shutdown
try: try:
from app.channels.service import stop_channel_service from app.channels.service import stop_channel_service
await asyncio.wait_for( await stop_channel_service()
stop_channel_service(),
timeout=_SHUTDOWN_HOOK_TIMEOUT_SECONDS,
)
except TimeoutError:
logger.warning(
"Channel service shutdown exceeded %.1fs; proceeding with worker exit.",
_SHUTDOWN_HOOK_TIMEOUT_SECONDS,
)
except Exception: except Exception:
logger.exception("Failed to stop channel service") logger.exception("Failed to stop channel service")
@@ -223,10 +210,6 @@ def create_app() -> FastAPI:
Returns: Returns:
Configured FastAPI application instance. Configured FastAPI application instance.
""" """
config = get_gateway_config()
docs_url = "/docs" if config.enable_docs else None
redoc_url = "/redoc" if config.enable_docs else None
openapi_url = "/openapi.json" if config.enable_docs else None
app = FastAPI( app = FastAPI(
title="DeerFlow API Gateway", title="DeerFlow API Gateway",
@@ -246,14 +229,14 @@ API Gateway for DeerFlow - A LangGraph-based AI agent backend with sandbox execu
### Architecture ### Architecture
LangGraph-compatible requests are routed through nginx to this gateway. LangGraph requests are handled by nginx reverse proxy.
This gateway provides runtime endpoints for agent runs plus custom endpoints for models, MCP configuration, skills, and artifacts. This gateway provides custom endpoints for models, MCP configuration, skills, and artifacts.
""", """,
version="0.1.0", version="0.1.0",
lifespan=lifespan, lifespan=lifespan,
docs_url=docs_url, docs_url="/docs",
redoc_url=redoc_url, redoc_url="/redoc",
openapi_url=openapi_url, openapi_url="/openapi.json",
openapi_tags=[ openapi_tags=[
{ {
"name": "models", "name": "models",
@@ -316,18 +299,25 @@ This gateway provides runtime endpoints for agent runs plus custom endpoints for
# CSRF: Double Submit Cookie pattern for state-changing requests # CSRF: Double Submit Cookie pattern for state-changing requests
app.add_middleware(CSRFMiddleware) app.add_middleware(CSRFMiddleware)
# CORS: the unified nginx endpoint is same-origin by default. Split-origin # CORS: when GATEWAY_CORS_ORIGINS is set (dev without nginx), add CORS middleware.
# browser clients must opt in with this explicit Gateway allowlist so CORS # In production, nginx handles CORS and no middleware is needed.
# and CSRF origin checks share the same source of truth. cors_origins_env = os.environ.get("GATEWAY_CORS_ORIGINS", "")
cors_origins = sorted(get_configured_cors_origins()) if cors_origins_env:
if cors_origins: cors_origins = [o.strip() for o in cors_origins_env.split(",") if o.strip()]
app.add_middleware( # Validate: wildcard origin with credentials is a security misconfiguration
CORSMiddleware, for origin in cors_origins:
allow_origins=cors_origins, if origin == "*":
allow_credentials=True, logger.error("GATEWAY_CORS_ORIGINS contains wildcard '*' with allow_credentials=True. This is a security misconfiguration — browsers will reject the response. Use explicit scheme://host:port origins instead.")
allow_methods=["*"], cors_origins = [o for o in cors_origins if o != "*"]
allow_headers=["*"], break
) if cors_origins:
app.add_middleware(
CORSMiddleware,
allow_origins=cors_origins,
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
# Include routers # Include routers
# Models API is mounted at /api/models # Models API is mounted at /api/models
@@ -376,7 +366,7 @@ This gateway provides runtime endpoints for agent runs plus custom endpoints for
app.include_router(runs.router) app.include_router(runs.router)
@app.get("/health", tags=["health"]) @app.get("/health", tags=["health"])
async def health_check() -> dict[str, str]: async def health_check() -> dict:
"""Health check endpoint. """Health check endpoint.
Returns: Returns:
+6 -34
View File
@@ -4,11 +4,12 @@ import logging
import os import os
import secrets import secrets
from dotenv import load_dotenv
from pydantic import BaseModel, Field from pydantic import BaseModel, Field
logger = logging.getLogger(__name__) load_dotenv()
_SECRET_FILE = ".jwt_secret" logger = logging.getLogger(__name__)
class AuthConfig(BaseModel): class AuthConfig(BaseModel):
@@ -32,46 +33,17 @@ class AuthConfig(BaseModel):
_auth_config: AuthConfig | None = None _auth_config: AuthConfig | None = None
def _load_or_create_secret() -> str:
"""Load persisted JWT secret from ``{base_dir}/.jwt_secret``, or generate and persist a new one."""
from deerflow.config.paths import get_paths
paths = get_paths()
secret_file = paths.base_dir / _SECRET_FILE
try:
if secret_file.exists():
secret = secret_file.read_text(encoding="utf-8").strip()
if secret:
return secret
except OSError as exc:
raise RuntimeError(f"Failed to read JWT secret from {secret_file}. Set AUTH_JWT_SECRET explicitly or fix DEER_FLOW_HOME/base directory permissions so DeerFlow can read its persisted auth secret.") from exc
secret = secrets.token_urlsafe(32)
try:
secret_file.parent.mkdir(parents=True, exist_ok=True)
fd = os.open(secret_file, os.O_WRONLY | os.O_CREAT | os.O_TRUNC, 0o600)
with os.fdopen(fd, "w", encoding="utf-8") as fh:
fh.write(secret)
except OSError as exc:
raise RuntimeError(f"Failed to persist JWT secret to {secret_file}. Set AUTH_JWT_SECRET explicitly or fix DEER_FLOW_HOME/base directory permissions so DeerFlow can store a stable auth secret.") from exc
return secret
def get_auth_config() -> AuthConfig: def get_auth_config() -> AuthConfig:
"""Get the global AuthConfig instance. Parses from env on first call.""" """Get the global AuthConfig instance. Parses from env on first call."""
global _auth_config global _auth_config
if _auth_config is None: if _auth_config is None:
from dotenv import load_dotenv
load_dotenv()
jwt_secret = os.environ.get("AUTH_JWT_SECRET") jwt_secret = os.environ.get("AUTH_JWT_SECRET")
if not jwt_secret: if not jwt_secret:
jwt_secret = _load_or_create_secret() jwt_secret = secrets.token_urlsafe(32)
os.environ["AUTH_JWT_SECRET"] = jwt_secret os.environ["AUTH_JWT_SECRET"] = jwt_secret
logger.warning( logger.warning(
"⚠ AUTH_JWT_SECRET is not set — using an auto-generated secret " "⚠ AUTH_JWT_SECRET is not set — using an auto-generated ephemeral secret. "
"persisted to .jwt_secret. Sessions will survive restarts. " "Sessions will be invalidated on restart. "
"For production, add AUTH_JWT_SECRET to your .env file: " "For production, add AUTH_JWT_SECRET to your .env file: "
'python -c "import secrets; print(secrets.token_urlsafe(32))"' 'python -c "import secrets; print(secrets.token_urlsafe(32))"'
) )
-1
View File
@@ -20,7 +20,6 @@ class AuthErrorCode(StrEnum):
EMAIL_ALREADY_EXISTS = "email_already_exists" EMAIL_ALREADY_EXISTS = "email_already_exists"
PROVIDER_NOT_FOUND = "provider_not_found" PROVIDER_NOT_FOUND = "provider_not_found"
NOT_AUTHENTICATED = "not_authenticated" NOT_AUTHENTICATED = "not_authenticated"
SYSTEM_ALREADY_INITIALIZED = "system_already_initialized"
class TokenError(StrEnum): class TokenError(StrEnum):
+1 -18
View File
@@ -1,14 +1,10 @@
"""Local email/password authentication provider.""" """Local email/password authentication provider."""
import logging
from app.gateway.auth.models import User from app.gateway.auth.models import User
from app.gateway.auth.password import hash_password_async, needs_rehash, verify_password_async from app.gateway.auth.password import hash_password_async, verify_password_async
from app.gateway.auth.providers import AuthProvider from app.gateway.auth.providers import AuthProvider
from app.gateway.auth.repositories.base import UserRepository from app.gateway.auth.repositories.base import UserRepository
logger = logging.getLogger(__name__)
class LocalAuthProvider(AuthProvider): class LocalAuthProvider(AuthProvider):
"""Email/password authentication provider using local database.""" """Email/password authentication provider using local database."""
@@ -47,15 +43,6 @@ class LocalAuthProvider(AuthProvider):
if not await verify_password_async(password, user.password_hash): if not await verify_password_async(password, user.password_hash):
return None return None
if needs_rehash(user.password_hash):
try:
user.password_hash = await hash_password_async(password)
await self._repo.update_user(user)
except Exception:
# Rehash is an opportunistic upgrade; a transient DB error must not
# prevent an otherwise-valid login from succeeding.
logger.warning("Failed to rehash password for user %s; login will still succeed", user.email, exc_info=True)
return user return user
async def get_user(self, user_id: str) -> User | None: async def get_user(self, user_id: str) -> User | None:
@@ -91,10 +78,6 @@ class LocalAuthProvider(AuthProvider):
"""Return total number of registered users.""" """Return total number of registered users."""
return await self._repo.count_users() return await self._repo.count_users()
async def count_admin_users(self) -> int:
"""Return number of admin users."""
return await self._repo.count_admin_users()
async def update_user(self, user: User) -> User: async def update_user(self, user: User) -> User:
"""Update an existing user.""" """Update an existing user."""
return await self._repo.update_user(user) return await self._repo.update_user(user)
+1 -1
View File
@@ -28,7 +28,7 @@ class User(BaseModel):
oauth_id: str | None = Field(None, description="User ID from OAuth provider") oauth_id: str | None = Field(None, description="User ID from OAuth provider")
# Auth lifecycle # Auth lifecycle
needs_setup: bool = Field(default=False, description="True when a reset account must complete setup") needs_setup: bool = Field(default=False, description="True for auto-created admin until setup completes")
token_version: int = Field(default=0, description="Incremented on password change to invalidate old JWTs") token_version: int = Field(default=0, description="Incremented on password change to invalidate old JWTs")
+5 -53
View File
@@ -1,66 +1,18 @@
"""Password hashing utilities with versioned hash format. """Password hashing utilities using bcrypt directly."""
Hash format: ``$dfv<N>$<bcrypt_hash>`` where ``<N>`` is the version.
- **v1** (legacy): ``bcrypt(password)`` plain bcrypt, susceptible to
72-byte silent truncation.
- **v2** (current): ``bcrypt(b64(sha256(password)))`` SHA-256 pre-hash
avoids the 72-byte truncation limit so the full password contributes
to the hash.
Verification auto-detects the version and falls back to v1 for hashes
without a prefix, so existing deployments upgrade transparently on next
login.
"""
import asyncio import asyncio
import base64
import hashlib
import bcrypt import bcrypt
_CURRENT_VERSION = 2
_PREFIX_V2 = "$dfv2$"
_PREFIX_V1 = "$dfv1$"
def _pre_hash_v2(password: str) -> bytes:
"""SHA-256 pre-hash to bypass bcrypt's 72-byte limit."""
return base64.b64encode(hashlib.sha256(password.encode("utf-8")).digest())
def hash_password(password: str) -> str: def hash_password(password: str) -> str:
"""Hash a password (current version: v2 — SHA-256 + bcrypt).""" """Hash a password using bcrypt."""
raw = bcrypt.hashpw(_pre_hash_v2(password), bcrypt.gensalt()).decode("utf-8") return bcrypt.hashpw(password.encode("utf-8"), bcrypt.gensalt()).decode("utf-8")
return f"{_PREFIX_V2}{raw}"
def verify_password(plain_password: str, hashed_password: str) -> bool: def verify_password(plain_password: str, hashed_password: str) -> bool:
"""Verify a password, auto-detecting the hash version. """Verify a password against its hash."""
return bcrypt.checkpw(plain_password.encode("utf-8"), hashed_password.encode("utf-8"))
Accepts v2 (``$dfv2$``), v1 (``$dfv1$``), and bare bcrypt hashes
(treated as v1 for backward compatibility with pre-versioning data).
"""
try:
if hashed_password.startswith(_PREFIX_V2):
bcrypt_hash = hashed_password[len(_PREFIX_V2) :]
return bcrypt.checkpw(_pre_hash_v2(plain_password), bcrypt_hash.encode("utf-8"))
if hashed_password.startswith(_PREFIX_V1):
bcrypt_hash = hashed_password[len(_PREFIX_V1) :]
else:
bcrypt_hash = hashed_password
return bcrypt.checkpw(plain_password.encode("utf-8"), bcrypt_hash.encode("utf-8"))
except ValueError:
# bcrypt raises ValueError for malformed or corrupt hashes (e.g., invalid salt).
# Fail closed rather than crashing the request.
return False
def needs_rehash(hashed_password: str) -> bool:
"""Return True if the hash uses an older version and should be rehashed."""
return not hashed_password.startswith(_PREFIX_V2)
async def hash_password_async(password: str) -> str: async def hash_password_async(password: str) -> str:
+2 -2
View File
@@ -12,12 +12,12 @@ class AuthProvider(ABC):
Returns User if authentication succeeds, None otherwise. Returns User if authentication succeeds, None otherwise.
""" """
raise NotImplementedError ...
@abstractmethod @abstractmethod
async def get_user(self, user_id: str) -> "User | None": async def get_user(self, user_id: str) -> "User | None":
"""Retrieve user by ID.""" """Retrieve user by ID."""
raise NotImplementedError ...
# Import User at runtime to avoid circular imports # Import User at runtime to avoid circular imports
+6 -11
View File
@@ -35,7 +35,7 @@ class UserRepository(ABC):
Raises: Raises:
ValueError: If email already exists ValueError: If email already exists
""" """
raise NotImplementedError ...
@abstractmethod @abstractmethod
async def get_user_by_id(self, user_id: str) -> User | None: async def get_user_by_id(self, user_id: str) -> User | None:
@@ -47,7 +47,7 @@ class UserRepository(ABC):
Returns: Returns:
User if found, None otherwise User if found, None otherwise
""" """
raise NotImplementedError ...
@abstractmethod @abstractmethod
async def get_user_by_email(self, email: str) -> User | None: async def get_user_by_email(self, email: str) -> User | None:
@@ -59,7 +59,7 @@ class UserRepository(ABC):
Returns: Returns:
User if found, None otherwise User if found, None otherwise
""" """
raise NotImplementedError ...
@abstractmethod @abstractmethod
async def update_user(self, user: User) -> User: async def update_user(self, user: User) -> User:
@@ -76,17 +76,12 @@ class UserRepository(ABC):
a hard failure (not a no-op) so callers cannot mistake a a hard failure (not a no-op) so callers cannot mistake a
concurrent-delete race for a successful update. concurrent-delete race for a successful update.
""" """
raise NotImplementedError ...
@abstractmethod @abstractmethod
async def count_users(self) -> int: async def count_users(self) -> int:
"""Return total number of registered users.""" """Return total number of registered users."""
raise NotImplementedError ...
@abstractmethod
async def count_admin_users(self) -> int:
"""Return number of users with system_role == 'admin'."""
raise NotImplementedError
@abstractmethod @abstractmethod
async def get_user_by_oauth(self, provider: str, oauth_id: str) -> User | None: async def get_user_by_oauth(self, provider: str, oauth_id: str) -> User | None:
@@ -99,4 +94,4 @@ class UserRepository(ABC):
Returns: Returns:
User if found, None otherwise User if found, None otherwise
""" """
raise NotImplementedError ...
@@ -114,11 +114,6 @@ class SQLiteUserRepository(UserRepository):
async with self._sf() as session: async with self._sf() as session:
return await session.scalar(stmt) or 0 return await session.scalar(stmt) or 0
async def count_admin_users(self) -> int:
stmt = select(func.count()).select_from(UserRow).where(UserRow.system_role == "admin")
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: async def get_user_by_oauth(self, provider: str, oauth_id: str) -> User | None:
stmt = select(UserRow).where(UserRow.oauth_provider == provider, UserRow.oauth_id == oauth_id) stmt = select(UserRow).where(UserRow.oauth_provider == provider, UserRow.oauth_id == oauth_id)
async with self._sf() as session: async with self._sf() as session:
+5 -14
View File
@@ -18,7 +18,6 @@ from starlette.types import ASGIApp
from app.gateway.auth.errors import AuthErrorCode, AuthErrorResponse from app.gateway.auth.errors import AuthErrorCode, AuthErrorResponse
from app.gateway.authz import _ALL_PERMISSIONS, AuthContext from app.gateway.authz import _ALL_PERMISSIONS, AuthContext
from app.gateway.internal_auth import INTERNAL_AUTH_HEADER_NAME, get_internal_user, is_valid_internal_auth_token
from deerflow.runtime.user_context import reset_current_user, set_current_user from deerflow.runtime.user_context import reset_current_user, set_current_user
# Paths that never require authentication. # Paths that never require authentication.
@@ -37,7 +36,6 @@ _PUBLIC_EXACT_PATHS: frozenset[str] = frozenset(
"/api/v1/auth/register", "/api/v1/auth/register",
"/api/v1/auth/logout", "/api/v1/auth/logout",
"/api/v1/auth/setup-status", "/api/v1/auth/setup-status",
"/api/v1/auth/initialize",
} }
) )
@@ -76,12 +74,8 @@ class AuthMiddleware(BaseHTTPMiddleware):
if _is_public(request.url.path): if _is_public(request.url.path):
return await call_next(request) return await call_next(request)
internal_user = None
if is_valid_internal_auth_token(request.headers.get(INTERNAL_AUTH_HEADER_NAME)):
internal_user = get_internal_user()
# Non-public path: require session cookie # Non-public path: require session cookie
if internal_user is None and not request.cookies.get("access_token"): if not request.cookies.get("access_token"):
return JSONResponse( return JSONResponse(
status_code=401, status_code=401,
content={ content={
@@ -105,13 +99,10 @@ class AuthMiddleware(BaseHTTPMiddleware):
# bubble up, so we catch and render it as JSONResponse here. # bubble up, so we catch and render it as JSONResponse here.
from app.gateway.deps import get_current_user_from_request from app.gateway.deps import get_current_user_from_request
if internal_user is not None: try:
user = internal_user user = await get_current_user_from_request(request)
else: except HTTPException as exc:
try: return JSONResponse(status_code=exc.status_code, content={"detail": exc.detail})
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) # Stamp both request.state.user (for the contextvar pattern)
# and request.state.auth (so @require_permission's "auth is # and request.state.auth (so @require_permission's "auth is
+9 -48
View File
@@ -30,9 +30,7 @@ Inspired by LangGraph Auth system: https://github.com/langchain-ai/langgraph/blo
from __future__ import annotations from __future__ import annotations
import functools import functools
import inspect
from collections.abc import Callable from collections.abc import Callable
from types import SimpleNamespace
from typing import TYPE_CHECKING, Any, ParamSpec, TypeVar from typing import TYPE_CHECKING, Any, ParamSpec, TypeVar
from fastapi import HTTPException, Request from fastapi import HTTPException, Request
@@ -119,15 +117,6 @@ _ALL_PERMISSIONS: list[str] = [
] ]
def _make_test_request_stub() -> Any:
"""Create a minimal request-like object for direct unit calls.
Used when decorated route handlers are invoked without FastAPI's
request injection. Includes fields accessed by auth helpers.
"""
return SimpleNamespace(state=SimpleNamespace(), cookies={}, _deerflow_test_bypass_auth=True)
async def _authenticate(request: Request) -> AuthContext: async def _authenticate(request: Request) -> AuthContext:
"""Authenticate request and return AuthContext. """Authenticate request and return AuthContext.
@@ -145,11 +134,7 @@ async def _authenticate(request: Request) -> AuthContext:
def require_auth[**P, T](func: Callable[P, T]) -> Callable[P, T]: def require_auth[**P, T](func: Callable[P, T]) -> Callable[P, T]:
"""Decorator that authenticates the request and enforces authentication. """Decorator that authenticates the request and sets AuthContext.
Independently raises HTTP 401 for unauthenticated requests, regardless of
whether ``AuthMiddleware`` is present in the ASGI stack. Sets the resolved
``AuthContext`` on ``request.state.auth`` for downstream handlers.
Must be placed ABOVE other decorators (executes after them). Must be placed ABOVE other decorators (executes after them).
@@ -162,33 +147,19 @@ def require_auth[**P, T](func: Callable[P, T]) -> Callable[P, T]:
... ...
Raises: Raises:
HTTPException: 401 if the request is unauthenticated. ValueError: If 'request' parameter is missing
ValueError: If 'request' parameter is missing.
""" """
@functools.wraps(func) @functools.wraps(func)
async def wrapper(*args: Any, **kwargs: Any) -> Any: async def wrapper(*args: Any, **kwargs: Any) -> Any:
request = kwargs.get("request") request = kwargs.get("request")
if request is None: if request is None:
# Unit tests may call decorated handlers directly without a raise ValueError("require_auth decorator requires 'request' parameter")
# FastAPI Request object. Inject a minimal request stub when
# the wrapped function declares `request`.
if "request" in inspect.signature(func).parameters:
kwargs["request"] = _make_test_request_stub()
else:
raise ValueError("require_auth decorator requires 'request' parameter")
request = kwargs["request"]
if getattr(request, "_deerflow_test_bypass_auth", False):
return await func(*args, **kwargs)
# Authenticate and set context # Authenticate and set context
auth_context = await _authenticate(request) auth_context = await _authenticate(request)
request.state.auth = auth_context request.state.auth = auth_context
if not auth_context.is_authenticated:
raise HTTPException(status_code=401, detail="Authentication required")
return await func(*args, **kwargs) return await func(*args, **kwargs)
return wrapper return wrapper
@@ -239,17 +210,7 @@ def require_permission(
async def wrapper(*args: Any, **kwargs: Any) -> Any: async def wrapper(*args: Any, **kwargs: Any) -> Any:
request = kwargs.get("request") request = kwargs.get("request")
if request is None: if request is None:
# Unit tests may call decorated route handlers directly without raise ValueError("require_permission decorator requires 'request' parameter")
# constructing a FastAPI Request object. Inject a minimal stub
# when the wrapped function declares `request`.
if "request" in inspect.signature(func).parameters:
kwargs["request"] = _make_test_request_stub()
else:
return await func(*args, **kwargs)
request = kwargs["request"]
if getattr(request, "_deerflow_test_bypass_auth", False):
return await func(*args, **kwargs)
auth: AuthContext = getattr(request.state, "auth", None) auth: AuthContext = getattr(request.state, "auth", None)
if auth is None: if auth is None:
@@ -272,18 +233,18 @@ def require_permission(
# (``threads_meta`` table). We verify ownership via # (``threads_meta`` table). We verify ownership via
# ``ThreadMetaStore.check_access``: it returns True for # ``ThreadMetaStore.check_access``: it returns True for
# missing rows (untracked legacy thread) and for rows whose # missing rows (untracked legacy thread) and for rows whose
# ``user_id`` is NULL (shared / pre-auth data), so this is # ``owner_id`` is NULL (shared / pre-auth data), so this is
# strict-deny rather than strict-allow — only an *existing* # strict-deny rather than strict-allow — only an *existing*
# row with a *different* user_id triggers 404. # row with a *different* owner_id triggers 404.
if owner_check: if owner_check:
thread_id = kwargs.get("thread_id") thread_id = kwargs.get("thread_id")
if thread_id is None: if thread_id is None:
raise ValueError("require_permission with owner_check=True requires 'thread_id' parameter") raise ValueError("require_permission with owner_check=True requires 'thread_id' parameter")
from app.gateway.deps import get_thread_store from app.gateway.deps import get_thread_meta_repo
thread_store = get_thread_store(request) thread_meta_repo = get_thread_meta_repo(request)
allowed = await thread_store.check_access( allowed = await thread_meta_repo.check_access(
thread_id, thread_id,
str(auth.user.id), str(auth.user.id),
require_existing=require_existing, require_existing=require_existing,
+3 -2
View File
@@ -8,7 +8,7 @@ class GatewayConfig(BaseModel):
host: str = Field(default="0.0.0.0", description="Host to bind the gateway server") host: str = Field(default="0.0.0.0", description="Host to bind the gateway server")
port: int = Field(default=8001, description="Port to bind the gateway server") port: int = Field(default=8001, description="Port to bind the gateway server")
enable_docs: bool = Field(default=True, description="Enable Swagger/ReDoc/OpenAPI endpoints") cors_origins: list[str] = Field(default_factory=lambda: ["http://localhost:3000"], description="Allowed CORS origins")
_gateway_config: GatewayConfig | None = None _gateway_config: GatewayConfig | None = None
@@ -18,9 +18,10 @@ def get_gateway_config() -> GatewayConfig:
"""Get gateway config, loading from environment if available.""" """Get gateway config, loading from environment if available."""
global _gateway_config global _gateway_config
if _gateway_config is None: if _gateway_config is None:
cors_origins_str = os.getenv("CORS_ORIGINS", "http://localhost:3000")
_gateway_config = GatewayConfig( _gateway_config = GatewayConfig(
host=os.getenv("GATEWAY_HOST", "0.0.0.0"), host=os.getenv("GATEWAY_HOST", "0.0.0.0"),
port=int(os.getenv("GATEWAY_PORT", "8001")), port=int(os.getenv("GATEWAY_PORT", "8001")),
enable_docs=os.getenv("GATEWAY_ENABLE_DOCS", "true").lower() == "true", cors_origins=cors_origins_str.split(","),
) )
return _gateway_config return _gateway_config
+3 -120
View File
@@ -4,10 +4,8 @@ Per RFC-001:
State-changing operations require CSRF protection. State-changing operations require CSRF protection.
""" """
import os
import secrets import secrets
from collections.abc import Awaitable, Callable from collections.abc import Callable
from urllib.parse import urlsplit
from fastapi import Request, Response from fastapi import Request, Response
from starlette.middleware.base import BaseHTTPMiddleware from starlette.middleware.base import BaseHTTPMiddleware
@@ -21,7 +19,7 @@ CSRF_TOKEN_LENGTH = 64 # bytes
def is_secure_request(request: Request) -> bool: def is_secure_request(request: Request) -> bool:
"""Detect whether the original client request was made over HTTPS.""" """Detect whether the original client request was made over HTTPS."""
return _request_scheme(request) == "https" return request.headers.get("x-forwarded-proto", request.url.scheme) == "https"
def generate_csrf_token() -> str: def generate_csrf_token() -> str:
@@ -50,7 +48,6 @@ _AUTH_EXEMPT_PATHS: frozenset[str] = frozenset(
"/api/v1/auth/login/local", "/api/v1/auth/login/local",
"/api/v1/auth/logout", "/api/v1/auth/logout",
"/api/v1/auth/register", "/api/v1/auth/register",
"/api/v1/auth/initialize",
} }
) )
@@ -63,129 +60,15 @@ def is_auth_endpoint(request: Request) -> bool:
return request.url.path.rstrip("/") in _AUTH_EXEMPT_PATHS return request.url.path.rstrip("/") in _AUTH_EXEMPT_PATHS
def _host_with_optional_port(hostname: str, port: int | None, scheme: str) -> str:
"""Return normalized host[:port], omitting default ports."""
host = hostname.lower()
if ":" in host and not host.startswith("["):
host = f"[{host}]"
if port is None or (scheme == "http" and port == 80) or (scheme == "https" and port == 443):
return host
return f"{host}:{port}"
def _normalize_origin(origin: str) -> str | None:
"""Return a normalized scheme://host[:port] origin, or None for invalid input."""
try:
parsed = urlsplit(origin.strip())
port = parsed.port
except ValueError:
return None
scheme = parsed.scheme.lower()
if scheme not in {"http", "https"} or not parsed.hostname:
return None
# Browser Origin is only scheme/host/port. Reject URL-shaped or credentialed values.
if parsed.username or parsed.password or parsed.path or parsed.query or parsed.fragment:
return None
return f"{scheme}://{_host_with_optional_port(parsed.hostname, port, scheme)}"
def _configured_cors_origins() -> set[str]:
"""Return explicit configured browser origins that may call auth routes."""
origins = set()
for raw_origin in os.environ.get("GATEWAY_CORS_ORIGINS", "").split(","):
origin = raw_origin.strip()
if not origin or origin == "*":
continue
normalized = _normalize_origin(origin)
if normalized:
origins.add(normalized)
return origins
def get_configured_cors_origins() -> set[str]:
"""Return normalized explicit browser origins from GATEWAY_CORS_ORIGINS."""
return _configured_cors_origins()
def _first_header_value(value: str | None) -> str | None:
"""Return the first value from a comma-separated proxy header."""
if not value:
return None
first = value.split(",", 1)[0].strip()
return first or None
def _forwarded_param(request: Request, name: str) -> str | None:
"""Extract a parameter from the first RFC 7239 Forwarded header entry."""
forwarded = _first_header_value(request.headers.get("forwarded"))
if not forwarded:
return None
for part in forwarded.split(";"):
key, sep, value = part.strip().partition("=")
if sep and key.lower() == name:
return value.strip().strip('"') or None
return None
def _request_scheme(request: Request) -> str:
"""Resolve the original request scheme from trusted proxy headers."""
scheme = _forwarded_param(request, "proto") or _first_header_value(request.headers.get("x-forwarded-proto")) or request.url.scheme
return scheme.lower()
def _request_origin(request: Request) -> str | None:
"""Build the origin for the URL the browser is targeting."""
scheme = _request_scheme(request)
host = _forwarded_param(request, "host") or _first_header_value(request.headers.get("x-forwarded-host")) or request.headers.get("host") or request.url.netloc
forwarded_port = _first_header_value(request.headers.get("x-forwarded-port"))
if forwarded_port and ":" not in host.rsplit("]", 1)[-1]:
host = f"{host}:{forwarded_port}"
return _normalize_origin(f"{scheme}://{host}")
def is_allowed_auth_origin(request: Request) -> bool:
"""Allow auth POSTs only from the same origin or explicit configured origins.
Login/register/initialize are exempt from the double-submit token because
first-time browser clients do not have a CSRF token yet. They still create
a session cookie, so browser requests with a hostile Origin header must be
rejected to prevent login CSRF / session fixation. Requests without Origin
are allowed for non-browser clients such as curl and mobile integrations.
"""
origin = request.headers.get("origin")
if not origin:
return True
normalized_origin = _normalize_origin(origin)
if normalized_origin is None:
return False
request_origin = _request_origin(request)
return normalized_origin in _configured_cors_origins() or (request_origin is not None and normalized_origin == request_origin)
class CSRFMiddleware(BaseHTTPMiddleware): class CSRFMiddleware(BaseHTTPMiddleware):
"""Middleware that implements CSRF protection using Double Submit Cookie pattern.""" """Middleware that implements CSRF protection using Double Submit Cookie pattern."""
def __init__(self, app: ASGIApp) -> None: def __init__(self, app: ASGIApp) -> None:
super().__init__(app) super().__init__(app)
async def dispatch(self, request: Request, call_next: Callable[[Request], Awaitable[Response]]) -> Response: async def dispatch(self, request: Request, call_next: Callable) -> Response:
_is_auth = is_auth_endpoint(request) _is_auth = is_auth_endpoint(request)
if should_check_csrf(request) and _is_auth and not is_allowed_auth_origin(request):
return JSONResponse(
status_code=403,
content={"detail": "Cross-site auth request denied."},
)
if should_check_csrf(request) and not _is_auth: if should_check_csrf(request) and not _is_auth:
cookie_token = request.cookies.get(CSRF_COOKIE_NAME) cookie_token = request.cookies.get(CSRF_COOKIE_NAME)
header_token = request.headers.get(CSRF_HEADER_NAME) header_token = request.headers.get(CSRF_HEADER_NAME)
+37 -200
View File
@@ -1,265 +1,108 @@
"""Centralized accessors for singleton objects stored on ``app.state``. """Centralized accessors for singleton objects stored on ``app.state``.
**Getters** (used by routers): raise 503 when a required dependency is **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``.
``AppConfig`` is intentionally *not* cached on ``app.state``. Routers and the
run path resolve it through :func:`deerflow.config.app_config.get_app_config`,
which performs mtime-based hot reload, so edits to ``config.yaml`` take
effect on the next request without a process restart. The engines created in
:func:`langgraph_runtime` (stream bridge, persistence, checkpointer, store,
run-event store) accept a ``startup_config`` snapshot they are
restart-required by design and stay bound to that snapshot to keep the live
process consistent with itself.
Initialization is handled directly in ``app.py`` via :class:`AsyncExitStack`. Initialization is handled directly in ``app.py`` via :class:`AsyncExitStack`.
""" """
from __future__ import annotations from __future__ import annotations
import asyncio from collections.abc import AsyncGenerator
import logging
from collections.abc import AsyncGenerator, Callable
from contextlib import AsyncExitStack, asynccontextmanager from contextlib import AsyncExitStack, asynccontextmanager
from typing import TYPE_CHECKING, TypeVar, cast from typing import TYPE_CHECKING
from fastapi import FastAPI, HTTPException, Request from fastapi import FastAPI, HTTPException, Request
from langgraph.types import Checkpointer
from deerflow.config.app_config import AppConfig, get_app_config
from deerflow.persistence.feedback import FeedbackRepository
from deerflow.runtime import RunContext, RunManager, StreamBridge
from deerflow.runtime.events.store.base import RunEventStore
from deerflow.runtime.runs.store.base import RunStore
logger = logging.getLogger(__name__)
# Upper bound (seconds) for draining in-flight runs during shutdown, before the
# AsyncExitStack tears down the checkpointer (and its connection pool). Kept
# local to avoid an app -> deps -> app import cycle. This is a *separate* budget
# from ``app.gateway.app._SHUTDOWN_HOOK_TIMEOUT_SECONDS`` (currently also 5.0s,
# which bounds channel-service stop): the two govern independent teardown steps
# and may diverge, but both count toward the lifespan shutdown window — revisit
# them together if their sum must stay within the server's graceful-shutdown
# timeout.
_RUN_DRAIN_TIMEOUT_SECONDS = 5.0
async def _drain_inflight_runs(run_manager: RunManager) -> None:
"""Drain in-flight runs before the checkpointer is torn down (issue #3373).
Shields the (internally-bounded) drain so that even if the lifespan
coroutine is itself cancelled mid-shutdown a second SIGINT or the server's
graceful-shutdown timeout, i.e. the same signal storm behind #3373 — the
checkpointer pool is not closed while run tasks are still writing
checkpoints. On such a cancellation we let the already-running drain finish
(it is bounded by ``RunManager.shutdown``'s own timeout) and then propagate
the cancellation.
"""
drain = asyncio.create_task(run_manager.shutdown(timeout=_RUN_DRAIN_TIMEOUT_SECONDS))
try:
await asyncio.shield(drain)
except asyncio.CancelledError:
# Re-shield so this second wait does not abandon the in-flight drain;
# it is bounded, so this cannot hang. Then re-raise to honour shutdown.
try:
await asyncio.shield(drain)
except Exception:
logger.exception("In-flight run drain failed after shutdown cancellation")
raise
except Exception:
logger.exception("Failed to drain in-flight runs during shutdown")
from deerflow.runtime import RunContext, RunManager
if TYPE_CHECKING: if TYPE_CHECKING:
from app.gateway.auth.local_provider import LocalAuthProvider from app.gateway.auth.local_provider import LocalAuthProvider
from app.gateway.auth.repositories.sqlite import SQLiteUserRepository from app.gateway.auth.repositories.sqlite import SQLiteUserRepository
from deerflow.persistence.thread_meta.base import ThreadMetaStore
from deerflow.runtime import RunRecord
T = TypeVar("T")
async def _mark_latest_recovered_threads_error(
run_manager: RunManager,
thread_store: ThreadMetaStore,
recovered_runs: list[RunRecord],
) -> None:
"""Mark thread status as error only when its newest run was recovered."""
recovered_by_thread: dict[str, set[str]] = {}
for record in recovered_runs:
recovered_by_thread.setdefault(record.thread_id, set()).add(record.run_id)
for thread_id, recovered_run_ids in recovered_by_thread.items():
try:
latest_runs = await run_manager.list_by_thread(thread_id, user_id=None, limit=1)
except Exception:
logger.warning("Failed to find latest run for thread %s during run reconciliation", thread_id, exc_info=True)
continue
if not latest_runs or latest_runs[0].run_id not in recovered_run_ids:
continue
try:
await thread_store.update_status(thread_id, "error", user_id=None)
except Exception:
logger.warning("Failed to mark thread %s as error during run reconciliation", thread_id, exc_info=True)
def get_config() -> AppConfig:
"""Return the freshest ``AppConfig`` for the current request.
Routes through :func:`deerflow.config.app_config.get_app_config`, which
honours runtime ``ContextVar`` overrides and reloads ``config.yaml`` from
disk when its mtime changes. ``AppConfig`` is not cached on ``app.state``
at all the only startup-time snapshot lives as a local
``startup_config`` variable inside ``lifespan()`` and is passed
explicitly into :func:`langgraph_runtime` for the engines that are
restart-required by design. Routing every request through
:func:`get_app_config` closes the bytedance/deer-flow issue #3107 BUG-001
split-brain where the worker / lead-agent thread saw a stale startup
snapshot.
Hot-reload boundary: fields backed by startup-time singletons
(engines, sandbox provider, IM channels, logging handler) require a
process restart to change at runtime. The authoritative list lives in
:mod:`deerflow.config.reload_boundary` and is mirrored by the
standardised ``"startup-only:"`` prefix on the matching
``Field(description=...)`` in :class:`AppConfig` IDE hover on those
fields will surface the boundary inline. See
``backend/CLAUDE.md`` "Config Hot-Reload Boundary" for the operator
summary.
Any failure to materialise the config (missing file, permission denied,
YAML parse error, validation error) is reported as 503 semantically
"the gateway cannot serve requests without a usable configuration" and
logged with the original exception so operators have something to debug.
"""
try:
return get_app_config()
except Exception as exc: # noqa: BLE001 - request boundary: log and degrade gracefully
logger.exception("Failed to load AppConfig at request time")
raise HTTPException(status_code=503, detail="Configuration not available") from exc
@asynccontextmanager @asynccontextmanager
async def langgraph_runtime(app: FastAPI, startup_config: AppConfig) -> AsyncGenerator[None, None]: async def langgraph_runtime(app: FastAPI) -> AsyncGenerator[None, None]:
"""Bootstrap and tear down all LangGraph runtime singletons. """Bootstrap and tear down all LangGraph runtime singletons.
``startup_config`` is the ``AppConfig`` snapshot taken once during
``lifespan()`` for one-shot infrastructure bootstrap. The engines and
stores constructed here (stream bridge, persistence engine, checkpointer,
store, run-event store) are restart-required by design they hold live
connections, file handles, or singleton providers so they bind to this
snapshot and survive across `config.yaml` edits. Request-time consumers
must still go through :func:`get_config` for any field that should be
hot-reloadable. See ``backend/CLAUDE.md`` "Config Hot-Reload Boundary".
The matching ``run_events_config`` is frozen onto ``app.state`` so
:func:`get_run_context` pairs a freshly-loaded ``AppConfig`` with the
*startup-time* run-events configuration the underlying ``event_store``
was built from otherwise the runtime could end up combining a live
new ``run_events_config`` with an event store still bound to the
previous backend.
Usage in ``app.py``:: Usage in ``app.py``::
async with langgraph_runtime(app, startup_config): async with langgraph_runtime(app):
yield 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.persistence.engine import close_engine, get_session_factory, init_engine_from_config
from deerflow.runtime import make_store, make_stream_bridge from deerflow.runtime import make_store, make_stream_bridge
from deerflow.runtime.checkpointer.async_provider import make_checkpointer
from deerflow.runtime.events.store import make_run_event_store from deerflow.runtime.events.store import make_run_event_store
async with AsyncExitStack() as stack: async with AsyncExitStack() as stack:
config = startup_config app.state.stream_bridge = await stack.enter_async_context(make_stream_bridge())
app.state.stream_bridge = await stack.enter_async_context(make_stream_bridge(config))
# Initialize persistence engine BEFORE checkpointer so that # Initialize persistence engine BEFORE checkpointer so that
# auto-create-database logic runs first (postgres backend). # auto-create-database logic runs first (postgres backend).
config = get_app_config()
await init_engine_from_config(config.database) await init_engine_from_config(config.database)
app.state.checkpointer = await stack.enter_async_context(make_checkpointer(config)) app.state.checkpointer = await stack.enter_async_context(make_checkpointer())
app.state.store = await stack.enter_async_context(make_store(config)) app.state.store = await stack.enter_async_context(make_store())
# Initialize repositories — one get_session_factory() call for all. # Initialize repositories — one get_session_factory() call for all.
sf = get_session_factory() sf = get_session_factory()
if sf is not None: if sf is not None:
from deerflow.persistence.feedback import FeedbackRepository from deerflow.persistence.feedback import FeedbackRepository
from deerflow.persistence.run import RunRepository from deerflow.persistence.run import RunRepository
from deerflow.persistence.thread_meta import ThreadMetaRepository
app.state.run_store = RunRepository(sf) app.state.run_store = RunRepository(sf)
app.state.feedback_repo = FeedbackRepository(sf) app.state.feedback_repo = FeedbackRepository(sf)
app.state.thread_meta_repo = ThreadMetaRepository(sf)
else: else:
from deerflow.persistence.thread_meta import MemoryThreadMetaStore
from deerflow.runtime.runs.store.memory import MemoryRunStore from deerflow.runtime.runs.store.memory import MemoryRunStore
app.state.run_store = MemoryRunStore() app.state.run_store = MemoryRunStore()
app.state.feedback_repo = None app.state.feedback_repo = None
app.state.thread_meta_repo = MemoryThreadMetaStore(app.state.store)
from deerflow.persistence.thread_meta import make_thread_store # Run event store (has its own factory with config-driven backend selection)
app.state.thread_store = make_thread_store(sf, app.state.store)
# Run event store. The store and the matching ``run_events_config`` are
# both frozen at startup so ``get_run_context`` does not combine a
# freshly-reloaded ``AppConfig.run_events`` with a store still bound to
# the previous backend.
run_events_config = getattr(config, "run_events", None) run_events_config = getattr(config, "run_events", None)
app.state.run_events_config = run_events_config
app.state.run_event_store = make_run_event_store(run_events_config) app.state.run_event_store = make_run_event_store(run_events_config)
# RunManager with store backing for persistence # RunManager with store backing for persistence
app.state.run_manager = RunManager(store=app.state.run_store) app.state.run_manager = RunManager(store=app.state.run_store)
if getattr(config.database, "backend", None) == "sqlite":
from deerflow.utils.time import now_iso
# Startup-only recovery: clean shutdowns return no active rows and
# the thread-status update below becomes a no-op.
recovered_runs = await app.state.run_manager.reconcile_orphaned_inflight_runs(
error="Gateway restarted before this run reached a durable final state.",
before=now_iso(),
)
await _mark_latest_recovered_threads_error(app.state.run_manager, app.state.thread_store, recovered_runs)
try: try:
yield yield
finally: finally:
# Drain in-flight run tasks BEFORE the AsyncExitStack tears down the
# checkpointer (and its connection pool). A run still mid-graph would
# otherwise leak into asyncio.run() shutdown, where langgraph's
# _checkpointer_put_after_previous aput races the closed pool and
# raises PoolClosed (issue #3373).
run_manager = getattr(app.state, "run_manager", None)
if run_manager is not None:
await _drain_inflight_runs(run_manager)
await close_engine() await close_engine()
# --------------------------------------------------------------------------- # ---------------------------------------------------------------------------
# Getters called by routers per-request # Getters -- called by routers per-request
# --------------------------------------------------------------------------- # ---------------------------------------------------------------------------
def _require(attr: str, label: str) -> Callable[[Request], T]: def _require(attr: str, label: str):
"""Create a FastAPI dependency that returns ``app.state.<attr>`` or 503.""" """Create a FastAPI dependency that returns ``app.state.<attr>`` or 503."""
def dep(request: Request) -> T: def dep(request: Request):
val = getattr(request.app.state, attr, None) val = getattr(request.app.state, attr, None)
if val is None: if val is None:
raise HTTPException(status_code=503, detail=f"{label} not available") raise HTTPException(status_code=503, detail=f"{label} not available")
return cast(T, val) return val
dep.__name__ = dep.__qualname__ = f"get_{attr}" dep.__name__ = dep.__qualname__ = f"get_{attr}"
return dep return dep
get_stream_bridge: Callable[[Request], StreamBridge] = _require("stream_bridge", "Stream bridge") get_stream_bridge = _require("stream_bridge", "Stream bridge")
get_run_manager: Callable[[Request], RunManager] = _require("run_manager", "Run manager") get_run_manager = _require("run_manager", "Run manager")
get_checkpointer: Callable[[Request], Checkpointer] = _require("checkpointer", "Checkpointer") get_checkpointer = _require("checkpointer", "Checkpointer")
get_run_event_store: Callable[[Request], RunEventStore] = _require("run_event_store", "Run event store") get_run_event_store = _require("run_event_store", "Run event store")
get_feedback_repo: Callable[[Request], FeedbackRepository] = _require("feedback_repo", "Feedback") get_feedback_repo = _require("feedback_repo", "Feedback")
get_run_store: Callable[[Request], RunStore] = _require("run_store", "Run store") get_run_store = _require("run_store", "Run store")
def get_store(request: Request): def get_store(request: Request):
@@ -267,31 +110,25 @@ def get_store(request: Request):
return getattr(request.app.state, "store", None) return getattr(request.app.state, "store", None)
def get_thread_store(request: Request) -> ThreadMetaStore: get_thread_meta_repo = _require("thread_meta_repo", "Thread metadata store")
"""Return the thread metadata store (SQL or memory-backed)."""
val = getattr(request.app.state, "thread_store", None)
if val is None:
raise HTTPException(status_code=503, detail="Thread metadata store not available")
return val
def get_run_context(request: Request) -> RunContext: def get_run_context(request: Request) -> RunContext:
"""Build a :class:`RunContext` from ``app.state`` singletons. """Build a :class:`RunContext` from ``app.state`` singletons.
Returns a *base* context with infrastructure dependencies. The Returns a *base* context with infrastructure dependencies. Callers that
``app_config`` field is resolved live so per-run fields (e.g. need per-run fields (e.g. ``follow_up_to_run_id``) should use
``models[*].max_tokens``) follow ``config.yaml`` edits; the ``dataclasses.replace(ctx, follow_up_to_run_id=...)`` before passing it
``event_store`` / ``run_events_config`` pair stays frozen to the snapshot to :func:`run_agent`.
captured in :func:`langgraph_runtime` so callers never see a store bound
to one backend paired with a config pointing at another.
""" """
from deerflow.config import get_app_config
return RunContext( return RunContext(
checkpointer=get_checkpointer(request), checkpointer=get_checkpointer(request),
store=get_store(request), store=get_store(request),
event_store=get_run_event_store(request), event_store=get_run_event_store(request),
run_events_config=getattr(request.app.state, "run_events_config", None), run_events_config=getattr(get_app_config(), "run_events", None),
thread_store=get_thread_store(request), thread_meta_repo=get_thread_meta_repo(request),
app_config=get_config(),
) )
-38
View File
@@ -1,38 +0,0 @@
"""Authentication for trusted Gateway internal callers."""
from __future__ import annotations
import os
import secrets
from types import SimpleNamespace
from deerflow.runtime.user_context import DEFAULT_USER_ID
INTERNAL_AUTH_HEADER_NAME = "X-DeerFlow-Internal-Token"
INTERNAL_AUTH_ENV_VAR = "DEER_FLOW_INTERNAL_AUTH_TOKEN"
INTERNAL_SYSTEM_ROLE = "internal"
def _load_internal_auth_token() -> str:
token = os.environ.get(INTERNAL_AUTH_ENV_VAR)
if token:
return token
return secrets.token_urlsafe(32)
_INTERNAL_AUTH_TOKEN = _load_internal_auth_token()
def create_internal_auth_headers() -> dict[str, str]:
"""Return headers that authenticate trusted Gateway internal calls."""
return {INTERNAL_AUTH_HEADER_NAME: _INTERNAL_AUTH_TOKEN}
def is_valid_internal_auth_token(token: str | None) -> bool:
"""Return True when *token* matches this Gateway worker's internal token."""
return bool(token) and secrets.compare_digest(token, _INTERNAL_AUTH_TOKEN)
def get_internal_user():
"""Return the synthetic user used for trusted internal channel calls."""
return SimpleNamespace(id=DEFAULT_USER_ID, system_role=INTERNAL_SYSTEM_ROLE)
+10 -14
View File
@@ -1,12 +1,8 @@
"""LangGraph compatibility auth handler — shares JWT logic with Gateway. """LangGraph Server auth handler — shares JWT logic with Gateway.
The default DeerFlow runtime is embedded in the FastAPI Gateway; scripts and Loaded by LangGraph Server via langgraph.json ``auth.path``.
Docker deployments do not load this module. It is retained for LangGraph Reuses the same ``decode_token`` / ``get_auth_config`` as Gateway,
tooling, Studio, or direct LangGraph Server compatibility through so both modes validate tokens with the same secret and rules.
``langgraph.json``'s ``auth.path``.
When that compatibility path is used, this module reuses the same JWT and CSRF
rules as Gateway so both modes validate sessions consistently.
Two layers: Two layers:
1. @auth.authenticate validates JWT cookie, extracts user_id, 1. @auth.authenticate validates JWT cookie, extracts user_id,
@@ -77,7 +73,7 @@ async def authenticate(request):
if isinstance(payload, TokenError): if isinstance(payload, TokenError):
raise Auth.exceptions.HTTPException( raise Auth.exceptions.HTTPException(
status_code=401, status_code=401,
detail="Invalid token", detail=f"Token error: {payload.value}",
) )
user = await get_local_provider().get_user(payload.sub) user = await get_local_provider().get_user(payload.sub)
@@ -97,14 +93,14 @@ async def authenticate(request):
@auth.on @auth.on
async def add_owner_filter(ctx: Auth.types.AuthContext, value: dict): 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. 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 = 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 filter dict — LangGraph applies it to search/read/delete
return {"user_id": ctx.user.identity} return {"owner_id": ctx.user.identity}
-15
View File
@@ -1,15 +0,0 @@
"""Shared pagination helpers for gateway routers."""
from __future__ import annotations
def trim_run_message_page(rows: list[dict], *, limit: int, after_seq: int | None) -> tuple[list[dict], bool]:
"""Trim a ``limit + 1`` run-message page while preserving page boundaries."""
has_more = len(rows) > limit
if not has_more:
return rows, False
if after_seq is not None:
return rows[:limit], True
return rows[-limit:], True
+1 -2
View File
@@ -5,7 +5,6 @@ from pathlib import Path
from fastapi import HTTPException from fastapi import HTTPException
from deerflow.config.paths import get_paths from deerflow.config.paths import get_paths
from deerflow.runtime.user_context import get_effective_user_id
def resolve_thread_virtual_path(thread_id: str, virtual_path: str) -> Path: def resolve_thread_virtual_path(thread_id: str, virtual_path: str) -> Path:
@@ -23,7 +22,7 @@ def resolve_thread_virtual_path(thread_id: str, virtual_path: str) -> Path:
HTTPException: If the path is invalid or outside allowed directories. HTTPException: If the path is invalid or outside allowed directories.
""" """
try: try:
return get_paths().resolve_virtual_path(thread_id, virtual_path, user_id=get_effective_user_id()) return get_paths().resolve_virtual_path(thread_id, virtual_path)
except ValueError as e: except ValueError as e:
status = 403 if "traversal" in str(e) else 400 status = 403 if "traversal" in str(e) else 400
raise HTTPException(status_code=status, detail=str(e)) raise HTTPException(status_code=status, detail=str(e))
+22 -85
View File
@@ -8,10 +8,8 @@ import yaml
from fastapi import APIRouter, HTTPException from fastapi import APIRouter, HTTPException
from pydantic import BaseModel, Field from pydantic import BaseModel, Field
from deerflow.config.agents_api_config import get_agents_api_config
from deerflow.config.agents_config import AgentConfig, list_custom_agents, load_agent_config, load_agent_soul from deerflow.config.agents_config import AgentConfig, list_custom_agents, load_agent_config, load_agent_soul
from deerflow.config.paths import get_paths from deerflow.config.paths import get_paths
from deerflow.runtime.user_context import get_effective_user_id
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
router = APIRouter(prefix="/api", tags=["agents"]) router = APIRouter(prefix="/api", tags=["agents"])
@@ -26,7 +24,6 @@ class AgentResponse(BaseModel):
description: str = Field(default="", description="Agent description") description: str = Field(default="", description="Agent description")
model: str | None = Field(default=None, description="Optional model override") model: str | None = Field(default=None, description="Optional model override")
tool_groups: list[str] | None = Field(default=None, description="Optional tool group whitelist") tool_groups: list[str] | None = Field(default=None, description="Optional tool group whitelist")
skills: list[str] | None = Field(default=None, description="Optional skill whitelist (None=all, []=none)")
soul: str | None = Field(default=None, description="SOUL.md content") soul: str | None = Field(default=None, description="SOUL.md content")
@@ -43,7 +40,6 @@ class AgentCreateRequest(BaseModel):
description: str = Field(default="", description="Agent description") description: str = Field(default="", description="Agent description")
model: str | None = Field(default=None, description="Optional model override") model: str | None = Field(default=None, description="Optional model override")
tool_groups: list[str] | None = Field(default=None, description="Optional tool group whitelist") tool_groups: list[str] | None = Field(default=None, description="Optional tool group whitelist")
skills: list[str] | None = Field(default=None, description="Optional skill whitelist (None=all enabled, []=none)")
soul: str = Field(default="", description="SOUL.md content — agent personality and behavioral guardrails") soul: str = Field(default="", description="SOUL.md content — agent personality and behavioral guardrails")
@@ -53,7 +49,6 @@ class AgentUpdateRequest(BaseModel):
description: str | None = Field(default=None, description="Updated description") description: str | None = Field(default=None, description="Updated description")
model: str | None = Field(default=None, description="Updated model override") model: str | None = Field(default=None, description="Updated model override")
tool_groups: list[str] | None = Field(default=None, description="Updated tool group whitelist") tool_groups: list[str] | None = Field(default=None, description="Updated tool group whitelist")
skills: list[str] | None = Field(default=None, description="Updated skill whitelist (None=all, []=none)")
soul: str | None = Field(default=None, description="Updated SOUL.md content") soul: str | None = Field(default=None, description="Updated SOUL.md content")
@@ -78,27 +73,17 @@ def _normalize_agent_name(name: str) -> str:
return name.lower() return name.lower()
def _require_agents_api_enabled() -> None: def _agent_config_to_response(agent_cfg: AgentConfig, include_soul: bool = False) -> AgentResponse:
"""Reject access unless the custom-agent management API is explicitly enabled."""
if not get_agents_api_config().enabled:
raise HTTPException(
status_code=403,
detail=("Custom-agent management API is disabled. Set agents_api.enabled=true to expose agent and user-profile routes over HTTP."),
)
def _agent_config_to_response(agent_cfg: AgentConfig, include_soul: bool = False, *, user_id: str | None = None) -> AgentResponse:
"""Convert AgentConfig to AgentResponse.""" """Convert AgentConfig to AgentResponse."""
soul: str | None = None soul: str | None = None
if include_soul: if include_soul:
soul = load_agent_soul(agent_cfg.name, user_id=user_id) or "" soul = load_agent_soul(agent_cfg.name) or ""
return AgentResponse( return AgentResponse(
name=agent_cfg.name, name=agent_cfg.name,
description=agent_cfg.description, description=agent_cfg.description,
model=agent_cfg.model, model=agent_cfg.model,
tool_groups=agent_cfg.tool_groups, tool_groups=agent_cfg.tool_groups,
skills=agent_cfg.skills,
soul=soul, soul=soul,
) )
@@ -115,12 +100,9 @@ async def list_agents() -> AgentsListResponse:
Returns: Returns:
List of all custom agents with their metadata and soul content. List of all custom agents with their metadata and soul content.
""" """
_require_agents_api_enabled()
user_id = get_effective_user_id()
try: try:
agents = list_custom_agents(user_id=user_id) agents = list_custom_agents()
return AgentsListResponse(agents=[_agent_config_to_response(a, include_soul=True, user_id=user_id) for a in agents]) return AgentsListResponse(agents=[_agent_config_to_response(a, include_soul=True) for a in agents])
except Exception as e: except Exception as e:
logger.error(f"Failed to list agents: {e}", exc_info=True) logger.error(f"Failed to list agents: {e}", exc_info=True)
raise HTTPException(status_code=500, detail=f"Failed to list agents: {str(e)}") raise HTTPException(status_code=500, detail=f"Failed to list agents: {str(e)}")
@@ -143,15 +125,9 @@ async def check_agent_name(name: str) -> dict:
Raises: Raises:
HTTPException: 422 if the name is invalid. HTTPException: 422 if the name is invalid.
""" """
_require_agents_api_enabled()
_validate_agent_name(name) _validate_agent_name(name)
normalized = _normalize_agent_name(name) normalized = _normalize_agent_name(name)
user_id = get_effective_user_id() available = not get_paths().agent_dir(normalized).exists()
paths = get_paths()
# Treat the name as taken if either the per-user path or the legacy shared
# path holds an agent — picking a name that collides with an unmigrated
# legacy agent would shadow the legacy entry once migration runs.
available = not paths.user_agent_dir(user_id, normalized).exists() and not paths.agent_dir(normalized).exists()
return {"available": available, "name": normalized} return {"available": available, "name": normalized}
@@ -173,14 +149,12 @@ async def get_agent(name: str) -> AgentResponse:
Raises: Raises:
HTTPException: 404 if agent not found. HTTPException: 404 if agent not found.
""" """
_require_agents_api_enabled()
_validate_agent_name(name) _validate_agent_name(name)
name = _normalize_agent_name(name) name = _normalize_agent_name(name)
user_id = get_effective_user_id()
try: try:
agent_cfg = load_agent_config(name, user_id=user_id) agent_cfg = load_agent_config(name)
return _agent_config_to_response(agent_cfg, include_soul=True, user_id=user_id) return _agent_config_to_response(agent_cfg, include_soul=True)
except FileNotFoundError: except FileNotFoundError:
raise HTTPException(status_code=404, detail=f"Agent '{name}' not found") raise HTTPException(status_code=404, detail=f"Agent '{name}' not found")
except Exception as e: except Exception as e:
@@ -207,16 +181,12 @@ async def create_agent_endpoint(request: AgentCreateRequest) -> AgentResponse:
Raises: Raises:
HTTPException: 409 if agent already exists, 422 if name is invalid. HTTPException: 409 if agent already exists, 422 if name is invalid.
""" """
_require_agents_api_enabled()
_validate_agent_name(request.name) _validate_agent_name(request.name)
normalized_name = _normalize_agent_name(request.name) normalized_name = _normalize_agent_name(request.name)
user_id = get_effective_user_id()
paths = get_paths()
agent_dir = paths.user_agent_dir(user_id, normalized_name) agent_dir = get_paths().agent_dir(normalized_name)
legacy_dir = paths.agent_dir(normalized_name)
if agent_dir.exists() or legacy_dir.exists(): if agent_dir.exists():
raise HTTPException(status_code=409, detail=f"Agent '{normalized_name}' already exists") raise HTTPException(status_code=409, detail=f"Agent '{normalized_name}' already exists")
try: try:
@@ -230,8 +200,6 @@ async def create_agent_endpoint(request: AgentCreateRequest) -> AgentResponse:
config_data["model"] = request.model config_data["model"] = request.model
if request.tool_groups is not None: if request.tool_groups is not None:
config_data["tool_groups"] = request.tool_groups config_data["tool_groups"] = request.tool_groups
if request.skills is not None:
config_data["skills"] = request.skills
config_file = agent_dir / "config.yaml" config_file = agent_dir / "config.yaml"
with open(config_file, "w", encoding="utf-8") as f: with open(config_file, "w", encoding="utf-8") as f:
@@ -243,8 +211,8 @@ async def create_agent_endpoint(request: AgentCreateRequest) -> AgentResponse:
logger.info(f"Created agent '{normalized_name}' at {agent_dir}") logger.info(f"Created agent '{normalized_name}' at {agent_dir}")
agent_cfg = load_agent_config(normalized_name, user_id=user_id) agent_cfg = load_agent_config(normalized_name)
return _agent_config_to_response(agent_cfg, include_soul=True, user_id=user_id) return _agent_config_to_response(agent_cfg, include_soul=True)
except HTTPException: except HTTPException:
raise raise
@@ -275,52 +243,33 @@ async def update_agent(name: str, request: AgentUpdateRequest) -> AgentResponse:
Raises: Raises:
HTTPException: 404 if agent not found. HTTPException: 404 if agent not found.
""" """
_require_agents_api_enabled()
_validate_agent_name(name) _validate_agent_name(name)
name = _normalize_agent_name(name) name = _normalize_agent_name(name)
user_id = get_effective_user_id()
try: try:
agent_cfg = load_agent_config(name, user_id=user_id) agent_cfg = load_agent_config(name)
except FileNotFoundError: except FileNotFoundError:
raise HTTPException(status_code=404, detail=f"Agent '{name}' not found") raise HTTPException(status_code=404, detail=f"Agent '{name}' not found")
paths = get_paths() agent_dir = get_paths().agent_dir(name)
agent_dir = paths.user_agent_dir(user_id, name)
if not agent_dir.exists() and paths.agent_dir(name).exists():
raise HTTPException(
status_code=409,
detail=(f"Agent '{name}' only exists in the legacy shared layout and is not scoped to a user. Run scripts/migrate_user_isolation.py to move legacy agents into the per-user layout before updating."),
)
try: try:
# Update config if any config fields changed # Update config if any config fields changed
# Use model_fields_set to distinguish "field omitted" from "explicitly set to null". config_changed = any(v is not None for v in [request.description, request.model, request.tool_groups])
# This is critical for skills where None means "inherit all" (not "don't change").
fields_set = request.model_fields_set
config_changed = bool(fields_set & {"description", "model", "tool_groups", "skills"})
if config_changed: if config_changed:
updated: dict = { updated: dict = {
"name": agent_cfg.name, "name": agent_cfg.name,
"description": request.description if "description" in fields_set else agent_cfg.description, "description": request.description if request.description is not None else agent_cfg.description,
} }
new_model = request.model if "model" in fields_set else agent_cfg.model new_model = request.model if request.model is not None else agent_cfg.model
if new_model is not None: if new_model is not None:
updated["model"] = new_model updated["model"] = new_model
new_tool_groups = request.tool_groups if "tool_groups" in fields_set else agent_cfg.tool_groups new_tool_groups = request.tool_groups if request.tool_groups is not None else agent_cfg.tool_groups
if new_tool_groups is not None: if new_tool_groups is not None:
updated["tool_groups"] = new_tool_groups updated["tool_groups"] = new_tool_groups
# skills: None = inherit all, [] = no skills, ["a","b"] = whitelist
if "skills" in fields_set:
new_skills = request.skills
else:
new_skills = agent_cfg.skills
if new_skills is not None:
updated["skills"] = new_skills
config_file = agent_dir / "config.yaml" config_file = agent_dir / "config.yaml"
with open(config_file, "w", encoding="utf-8") as f: with open(config_file, "w", encoding="utf-8") as f:
yaml.dump(updated, f, default_flow_style=False, allow_unicode=True) yaml.dump(updated, f, default_flow_style=False, allow_unicode=True)
@@ -332,8 +281,8 @@ async def update_agent(name: str, request: AgentUpdateRequest) -> AgentResponse:
logger.info(f"Updated agent '{name}'") logger.info(f"Updated agent '{name}'")
refreshed_cfg = load_agent_config(name, user_id=user_id) refreshed_cfg = load_agent_config(name)
return _agent_config_to_response(refreshed_cfg, include_soul=True, user_id=user_id) return _agent_config_to_response(refreshed_cfg, include_soul=True)
except HTTPException: except HTTPException:
raise raise
@@ -366,8 +315,6 @@ async def get_user_profile() -> UserProfileResponse:
Returns: Returns:
UserProfileResponse with content=None if USER.md does not exist yet. UserProfileResponse with content=None if USER.md does not exist yet.
""" """
_require_agents_api_enabled()
try: try:
user_md_path = get_paths().user_md_file user_md_path = get_paths().user_md_file
if not user_md_path.exists(): if not user_md_path.exists():
@@ -394,8 +341,6 @@ async def update_user_profile(request: UserProfileUpdateRequest) -> UserProfileR
Returns: Returns:
UserProfileResponse with the saved content. UserProfileResponse with the saved content.
""" """
_require_agents_api_enabled()
try: try:
paths = get_paths() paths = get_paths()
paths.base_dir.mkdir(parents=True, exist_ok=True) paths.base_dir.mkdir(parents=True, exist_ok=True)
@@ -420,22 +365,14 @@ async def delete_agent(name: str) -> None:
name: The agent name. name: The agent name.
Raises: Raises:
HTTPException: 404 if no per-user copy exists; 409 if only a legacy HTTPException: 404 if agent not found.
shared copy exists (suggesting the migration script).
""" """
_require_agents_api_enabled()
_validate_agent_name(name) _validate_agent_name(name)
name = _normalize_agent_name(name) name = _normalize_agent_name(name)
user_id = get_effective_user_id()
paths = get_paths() agent_dir = get_paths().agent_dir(name)
agent_dir = paths.user_agent_dir(user_id, name)
if not agent_dir.exists(): if not agent_dir.exists():
if paths.agent_dir(name).exists():
raise HTTPException(
status_code=409,
detail=(f"Agent '{name}' only exists in the legacy shared layout and is not scoped to a user. Run scripts/migrate_user_isolation.py to move legacy agents into the per-user layout before deleting."),
)
raise HTTPException(status_code=404, detail=f"Agent '{name}' not found") raise HTTPException(status_code=404, detail=f"Agent '{name}' not found")
try: try:
+5 -24
View File
@@ -20,9 +20,6 @@ ACTIVE_CONTENT_MIME_TYPES = {
"image/svg+xml", "image/svg+xml",
} }
MAX_SKILL_ARCHIVE_MEMBER_BYTES = 16 * 1024 * 1024
_SKILL_ARCHIVE_READ_CHUNK_SIZE = 64 * 1024
def _build_content_disposition(disposition_type: str, filename: str) -> str: def _build_content_disposition(disposition_type: str, filename: str) -> str:
"""Build an RFC 5987 encoded Content-Disposition header value.""" """Build an RFC 5987 encoded Content-Disposition header value."""
@@ -47,22 +44,6 @@ def is_text_file_by_content(path: Path, sample_size: int = 8192) -> bool:
return False return False
def _read_skill_archive_member(zip_ref: zipfile.ZipFile, info: zipfile.ZipInfo) -> bytes:
"""Read a .skill archive member while enforcing an uncompressed size cap."""
if info.file_size > MAX_SKILL_ARCHIVE_MEMBER_BYTES:
raise HTTPException(status_code=413, detail="Skill archive member is too large to preview")
chunks: list[bytes] = []
total_read = 0
with zip_ref.open(info, "r") as src:
while chunk := src.read(_SKILL_ARCHIVE_READ_CHUNK_SIZE):
total_read += len(chunk)
if total_read > MAX_SKILL_ARCHIVE_MEMBER_BYTES:
raise HTTPException(status_code=413, detail="Skill archive member is too large to preview")
chunks.append(chunk)
return b"".join(chunks)
def _extract_file_from_skill_archive(zip_path: Path, internal_path: str) -> bytes | None: def _extract_file_from_skill_archive(zip_path: Path, internal_path: str) -> bytes | None:
"""Extract a file from a .skill ZIP archive. """Extract a file from a .skill ZIP archive.
@@ -79,16 +60,16 @@ def _extract_file_from_skill_archive(zip_path: Path, internal_path: str) -> byte
try: try:
with zipfile.ZipFile(zip_path, "r") as zip_ref: with zipfile.ZipFile(zip_path, "r") as zip_ref:
# List all files in the archive # List all files in the archive
infos_by_name = {info.filename: info for info in zip_ref.infolist()} namelist = zip_ref.namelist()
# Try direct path first # Try direct path first
if internal_path in infos_by_name: if internal_path in namelist:
return _read_skill_archive_member(zip_ref, infos_by_name[internal_path]) return zip_ref.read(internal_path)
# Try with any top-level directory prefix (e.g., "skill-name/SKILL.md") # Try with any top-level directory prefix (e.g., "skill-name/SKILL.md")
for name, info in infos_by_name.items(): for name in namelist:
if name.endswith("/" + internal_path) or name == internal_path: if name.endswith("/" + internal_path) or name == internal_path:
return _read_skill_archive_member(zip_ref, info) return zip_ref.read(name)
# Not found # Not found
return None return None
+6 -115
View File
@@ -1,6 +1,5 @@
"""Authentication endpoints.""" """Authentication endpoints."""
import asyncio
import logging import logging
import os import os
import time import time
@@ -147,13 +146,7 @@ def _set_session_cookie(response: Response, token: str, request: Request) -> Non
# ── Rate Limiting ──────────────────────────────────────────────────────── # ── Rate Limiting ────────────────────────────────────────────────────────
# In-process dict — not shared across workers. # In-process dict — not shared across workers. Sufficient for single-worker deployments.
#
# **Limitation**: with multi-worker deployments (e.g., gunicorn -w N), each
# worker maintains its own lockout table, so an attacker effectively gets
# N × _MAX_LOGIN_ATTEMPTS guesses before being locked out everywhere. For
# production multi-worker setups, replace this with a shared store (Redis,
# database-backed counter) to enforce a true per-IP limit.
_MAX_LOGIN_ATTEMPTS = 5 _MAX_LOGIN_ATTEMPTS = 5
_LOCKOUT_SECONDS = 300 # 5 minutes _LOCKOUT_SECONDS = 300 # 5 minutes
@@ -306,7 +299,7 @@ async def login_local(
async def register(request: Request, response: Response, body: RegisterRequest): async def register(request: Request, response: Response, body: RegisterRequest):
"""Register a new user account (always 'user' role). """Register a new user account (always 'user' role).
The first admin is created explicitly through /initialize. This endpoint creates regular users. Admin is auto-created on first boot. This endpoint creates regular users.
Auto-login by setting the session cookie. Auto-login by setting the session cookie.
""" """
try: try:
@@ -383,113 +376,11 @@ async def get_me(request: Request):
return UserResponse(id=str(user.id), email=user.email, system_role=user.system_role, needs_setup=user.needs_setup) return UserResponse(id=str(user.id), email=user.email, system_role=user.system_role, needs_setup=user.needs_setup)
# Per-IP cache: ip → (timestamp, result_dict).
# Returns the cached result within the TTL instead of 429, because
# the answer (whether an admin exists) rarely changes and returning
# 429 breaks multi-tab / post-restart reconnection storms.
_SETUP_STATUS_CACHE: dict[str, tuple[float, dict]] = {}
_SETUP_STATUS_CACHE_TTL_SECONDS = 60
_MAX_TRACKED_SETUP_STATUS_IPS = 10000
_SETUP_STATUS_INFLIGHT: dict[str, asyncio.Task[dict]] = {}
_SETUP_STATUS_INFLIGHT_GUARD = asyncio.Lock()
@router.get("/setup-status") @router.get("/setup-status")
async def setup_status(request: Request): async def setup_status():
"""Check if an admin account exists. Returns needs_setup=True when no admin exists.""" """Check if admin account exists. Always False after first boot."""
client_ip = _get_client_ip(request) user_count = await get_local_provider().count_users()
now = time.time() return {"needs_setup": user_count == 0}
# Return cached result when within TTL — avoids 429 on multi-tab reconnection.
cached = _SETUP_STATUS_CACHE.get(client_ip)
if cached is not None:
cached_time, cached_result = cached
if now - cached_time < _SETUP_STATUS_CACHE_TTL_SECONDS:
return cached_result
async with _SETUP_STATUS_INFLIGHT_GUARD:
# Recheck cache after waiting for the inflight guard.
now = time.time()
cached = _SETUP_STATUS_CACHE.get(client_ip)
if cached is not None:
cached_time, cached_result = cached
if now - cached_time < _SETUP_STATUS_CACHE_TTL_SECONDS:
return cached_result
task = _SETUP_STATUS_INFLIGHT.get(client_ip)
if task is None:
# Evict stale entries when dict grows too large to bound memory usage.
if len(_SETUP_STATUS_CACHE) >= _MAX_TRACKED_SETUP_STATUS_IPS:
cutoff = now - _SETUP_STATUS_CACHE_TTL_SECONDS
stale = [k for k, (t, _) in _SETUP_STATUS_CACHE.items() if t < cutoff]
for k in stale:
del _SETUP_STATUS_CACHE[k]
if len(_SETUP_STATUS_CACHE) >= _MAX_TRACKED_SETUP_STATUS_IPS:
by_time = sorted(_SETUP_STATUS_CACHE.items(), key=lambda entry: entry[1][0])
for k, _ in by_time[: len(by_time) // 2]:
del _SETUP_STATUS_CACHE[k]
async def _compute_setup_status() -> dict:
admin_count = await get_local_provider().count_admin_users()
return {"needs_setup": admin_count == 0}
task = asyncio.create_task(_compute_setup_status())
_SETUP_STATUS_INFLIGHT[client_ip] = task
try:
result = await task
finally:
async with _SETUP_STATUS_INFLIGHT_GUARD:
if _SETUP_STATUS_INFLIGHT.get(client_ip) is task:
del _SETUP_STATUS_INFLIGHT[client_ip]
# Cache only the stable "initialized" result to avoid stale setup redirects.
if result["needs_setup"] is False:
_SETUP_STATUS_CACHE[client_ip] = (time.time(), result)
else:
_SETUP_STATUS_CACHE.pop(client_ip, None)
return result
class InitializeAdminRequest(BaseModel):
"""Request model for first-boot admin account creation."""
email: EmailStr
password: str = Field(..., min_length=8)
_strong_password = field_validator("password")(classmethod(lambda cls, v: _validate_strong_password(v)))
@router.post("/initialize", response_model=UserResponse, status_code=status.HTTP_201_CREATED)
async def initialize_admin(request: Request, response: Response, body: InitializeAdminRequest):
"""Create the first admin account on initial system setup.
Only callable when no admin exists. Returns 409 Conflict if an admin
already exists.
On success, the admin account is created with ``needs_setup=False`` and
the session cookie is set.
"""
admin_count = await get_local_provider().count_admin_users()
if admin_count > 0:
raise HTTPException(
status_code=status.HTTP_409_CONFLICT,
detail=AuthErrorResponse(code=AuthErrorCode.SYSTEM_ALREADY_INITIALIZED, message="System already initialized").model_dump(),
)
try:
user = await get_local_provider().create_user(email=body.email, password=body.password, system_role="admin", needs_setup=False)
except ValueError:
# DB unique-constraint race: another concurrent request beat us.
raise HTTPException(
status_code=status.HTTP_409_CONFLICT,
detail=AuthErrorResponse(code=AuthErrorCode.SYSTEM_ALREADY_INITIALIZED, message="System already initialized").model_dump(),
)
token = create_access_token(str(user.id), token_version=user.token_version)
_set_session_cookie(response, token, request)
return UserResponse(id=str(user.id), email=user.email, system_role=user.system_role)
# ── OAuth Endpoints (Future/Placeholder) ───────────────────────────────── # ── OAuth Endpoints (Future/Placeholder) ─────────────────────────────────
+2 -58
View File
@@ -30,16 +30,11 @@ class FeedbackCreateRequest(BaseModel):
message_id: str | None = Field(default=None, description="Optional: scope feedback to a specific message") message_id: str | None = Field(default=None, description="Optional: scope feedback to a specific message")
class FeedbackUpsertRequest(BaseModel):
rating: int = Field(..., description="Feedback rating: +1 (positive) or -1 (negative)")
comment: str | None = Field(default=None, description="Optional text feedback")
class FeedbackResponse(BaseModel): class FeedbackResponse(BaseModel):
feedback_id: str feedback_id: str
run_id: str run_id: str
thread_id: str thread_id: str
user_id: str | None = None owner_id: str | None = None
message_id: str | None = None message_id: str | None = None
rating: int rating: int
comment: str | None = None comment: str | None = None
@@ -58,57 +53,6 @@ class FeedbackStatsResponse(BaseModel):
# --------------------------------------------------------------------------- # ---------------------------------------------------------------------------
@router.put("/{thread_id}/runs/{run_id}/feedback", response_model=FeedbackResponse)
@require_permission("threads", "write", owner_check=True, require_existing=True)
async def upsert_feedback(
thread_id: str,
run_id: str,
body: FeedbackUpsertRequest,
request: Request,
) -> dict[str, Any]:
"""Create or update feedback for a run (idempotent)."""
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)
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.upsert(
run_id=run_id,
thread_id=thread_id,
rating=body.rating,
user_id=user_id,
comment=body.comment,
)
@router.delete("/{thread_id}/runs/{run_id}/feedback")
@require_permission("threads", "delete", owner_check=True, require_existing=True)
async def delete_run_feedback(
thread_id: str,
run_id: str,
request: Request,
) -> dict[str, bool]:
"""Delete the current user's feedback for a run."""
user_id = await get_current_user(request)
feedback_repo = get_feedback_repo(request)
deleted = await feedback_repo.delete_by_run(
thread_id=thread_id,
run_id=run_id,
user_id=user_id,
)
if not deleted:
raise HTTPException(status_code=404, detail="No feedback found for this run")
return {"success": True}
@router.post("/{thread_id}/runs/{run_id}/feedback", response_model=FeedbackResponse) @router.post("/{thread_id}/runs/{run_id}/feedback", response_model=FeedbackResponse)
@require_permission("threads", "write", owner_check=True, require_existing=True) @require_permission("threads", "write", owner_check=True, require_existing=True)
async def create_feedback( async def create_feedback(
@@ -136,7 +80,7 @@ async def create_feedback(
run_id=run_id, run_id=run_id,
thread_id=thread_id, thread_id=thread_id,
rating=body.rating, rating=body.rating,
user_id=user_id, owner_id=user_id,
message_id=body.message_id, message_id=body.message_id,
comment=body.comment, comment=body.comment,
) )
+13 -132
View File
@@ -63,99 +63,6 @@ class McpConfigUpdateRequest(BaseModel):
) )
_MASKED_VALUE = "***"
def _mask_server_config(server: McpServerConfigResponse) -> McpServerConfigResponse:
"""Return a copy of server config with sensitive fields masked.
Masks env values, header values, and removes OAuth secrets so they
are not exposed through the GET API endpoint.
"""
masked_env = {k: _MASKED_VALUE for k in server.env}
masked_headers = {k: _MASKED_VALUE for k in server.headers}
masked_oauth = None
if server.oauth is not None:
masked_oauth = server.oauth.model_copy(
update={
"client_secret": None,
"refresh_token": None,
}
)
return server.model_copy(
update={
"env": masked_env,
"headers": masked_headers,
"oauth": masked_oauth,
}
)
def _merge_preserving_secrets(
incoming: McpServerConfigResponse,
existing: McpServerConfigResponse,
) -> McpServerConfigResponse:
"""Merge incoming config with existing, preserving secrets masked by GET.
When the frontend toggles ``enabled`` it round-trips the full config:
GET (masked) modify enabled PUT (masked values sent back).
This function ensures masked values (``***``) are replaced with the
real secrets from the current on-disk config.
``***`` is only accepted for keys that already exist in *existing*.
New keys must provide a real value.
For OAuth secrets, ``None`` means "preserve the existing stored value"
so masked GET responses can be safely round-tripped. To explicitly clear
a stored secret, clients may send an empty string, which is converted
to ``None`` before persisting.
"""
merged_env = {}
for k, v in incoming.env.items():
if v == _MASKED_VALUE:
if k in existing.env:
merged_env[k] = existing.env[k]
else:
raise HTTPException(
status_code=400,
detail=f"Cannot set env key '{k}' to masked value '***'; provide a real value.",
)
else:
merged_env[k] = v
merged_headers = {}
for k, v in incoming.headers.items():
if v == _MASKED_VALUE:
if k in existing.headers:
merged_headers[k] = existing.headers[k]
else:
raise HTTPException(
status_code=400,
detail=f"Cannot set header '{k}' to masked value '***'; provide a real value.",
)
else:
merged_headers[k] = v
merged_oauth = incoming.oauth
if incoming.oauth is not None and existing.oauth is not None:
# None = preserve (masked round-trip), "" = explicitly clear, else = new value
merged_client_secret = existing.oauth.client_secret if incoming.oauth.client_secret is None else (None if incoming.oauth.client_secret == "" else incoming.oauth.client_secret)
merged_refresh_token = existing.oauth.refresh_token if incoming.oauth.refresh_token is None else (None if incoming.oauth.refresh_token == "" else incoming.oauth.refresh_token)
merged_oauth = incoming.oauth.model_copy(
update={
"client_secret": merged_client_secret,
"refresh_token": merged_refresh_token,
}
)
return incoming.model_copy(
update={
"env": merged_env,
"headers": merged_headers,
"oauth": merged_oauth,
}
)
@router.get( @router.get(
"/mcp/config", "/mcp/config",
response_model=McpConfigResponse, response_model=McpConfigResponse,
@@ -176,7 +83,7 @@ async def get_mcp_configuration() -> McpConfigResponse:
"enabled": true, "enabled": true,
"command": "npx", "command": "npx",
"args": ["-y", "@modelcontextprotocol/server-github"], "args": ["-y", "@modelcontextprotocol/server-github"],
"env": {"GITHUB_TOKEN": "***"}, "env": {"GITHUB_TOKEN": "ghp_xxx"},
"description": "GitHub MCP server for repository operations" "description": "GitHub MCP server for repository operations"
} }
} }
@@ -185,8 +92,7 @@ async def get_mcp_configuration() -> McpConfigResponse:
""" """
config = get_extensions_config() config = get_extensions_config()
servers = {name: _mask_server_config(McpServerConfigResponse(**server.model_dump())) for name, server in config.mcp_servers.items()} return McpConfigResponse(mcp_servers={name: McpServerConfigResponse(**server.model_dump()) for name, server in config.mcp_servers.items()})
return McpConfigResponse(mcp_servers=servers)
@router.put( @router.put(
@@ -236,39 +142,14 @@ async def update_mcp_configuration(request: McpConfigUpdateRequest) -> McpConfig
config_path = Path.cwd().parent / "extensions_config.json" config_path = Path.cwd().parent / "extensions_config.json"
logger.info(f"No existing extensions config found. Creating new config at: {config_path}") logger.info(f"No existing extensions config found. Creating new config at: {config_path}")
# Load current config to preserve skills # Load current config to preserve skills configuration
current_config = get_extensions_config() current_config = get_extensions_config()
# Load raw (un-resolved) JSON from disk to use as the merge source. # Convert request to dict format for JSON serialization
# This preserves $VAR placeholders in env values and top-level keys config_data = {
# like mcpInterceptors that would otherwise be lost. "mcpServers": {name: server.model_dump() for name, server in request.mcp_servers.items()},
raw_servers: dict[str, dict] = {} "skills": {name: {"enabled": skill.enabled} for name, skill in current_config.skills.items()},
raw_other_keys: dict = {} }
if config_path is not None and config_path.exists():
with open(config_path, encoding="utf-8") as f:
raw_data = json.load(f)
raw_servers = raw_data.get("mcpServers", {})
# Preserve any top-level keys beyond mcpServers/skills
for key, value in raw_data.items():
if key not in ("mcpServers", "skills"):
raw_other_keys[key] = value
# Merge incoming server configs with raw on-disk secrets
merged_servers: dict[str, McpServerConfigResponse] = {}
for name, incoming in request.mcp_servers.items():
raw_server = raw_servers.get(name)
if raw_server is not None:
merged_servers[name] = _merge_preserving_secrets(
incoming,
McpServerConfigResponse(**raw_server),
)
else:
merged_servers[name] = incoming
# Build config data preserving all top-level keys from the original file
config_data = dict(raw_other_keys)
config_data["mcpServers"] = {name: server.model_dump() for name, server in merged_servers.items()}
config_data["skills"] = {name: {"enabled": skill.enabled} for name, skill in current_config.skills.items()}
# Write the configuration to file # Write the configuration to file
with open(config_path, "w", encoding="utf-8") as f: with open(config_path, "w", encoding="utf-8") as f:
@@ -276,12 +157,12 @@ async def update_mcp_configuration(request: McpConfigUpdateRequest) -> McpConfig
logger.info(f"MCP configuration updated and saved to: {config_path}") logger.info(f"MCP configuration updated and saved to: {config_path}")
# Reload the Gateway configuration and update the global cache. The # NOTE: No need to reload/reset cache here - LangGraph Server (separate process)
# agent runtime lives in Gateway, so this keeps API reads and tool # will detect config file changes via mtime and reinitialize MCP tools automatically
# execution aligned after extensions_config.json changes.
# Reload the configuration and update the global cache
reloaded_config = reload_extensions_config() reloaded_config = reload_extensions_config()
servers = {name: _mask_server_config(McpServerConfigResponse(**server.model_dump())) for name, server in reloaded_config.mcp_servers.items()} return McpConfigResponse(mcp_servers={name: McpServerConfigResponse(**server.model_dump()) for name, server in reloaded_config.mcp_servers.items()})
return McpConfigResponse(mcp_servers=servers)
except Exception as e: except Exception as e:
logger.error(f"Failed to update MCP configuration: {e}", exc_info=True) logger.error(f"Failed to update MCP configuration: {e}", exc_info=True)
+7 -10
View File
@@ -13,7 +13,6 @@ from deerflow.agents.memory.updater import (
update_memory_fact, update_memory_fact,
) )
from deerflow.config.memory_config import get_memory_config from deerflow.config.memory_config import get_memory_config
from deerflow.runtime.user_context import get_effective_user_id
router = APIRouter(prefix="/api", tags=["memory"]) router = APIRouter(prefix="/api", tags=["memory"])
@@ -148,7 +147,7 @@ async def get_memory() -> MemoryResponse:
} }
``` ```
""" """
memory_data = get_memory_data(user_id=get_effective_user_id()) memory_data = get_memory_data()
return MemoryResponse(**memory_data) return MemoryResponse(**memory_data)
@@ -168,7 +167,7 @@ async def reload_memory() -> MemoryResponse:
Returns: Returns:
The reloaded memory data. The reloaded memory data.
""" """
memory_data = reload_memory_data(user_id=get_effective_user_id()) memory_data = reload_memory_data()
return MemoryResponse(**memory_data) return MemoryResponse(**memory_data)
@@ -182,7 +181,7 @@ async def reload_memory() -> MemoryResponse:
async def clear_memory() -> MemoryResponse: async def clear_memory() -> MemoryResponse:
"""Clear all persisted memory data.""" """Clear all persisted memory data."""
try: try:
memory_data = clear_memory_data(user_id=get_effective_user_id()) memory_data = clear_memory_data()
except OSError as exc: except OSError as exc:
raise HTTPException(status_code=500, detail="Failed to clear memory data.") from exc raise HTTPException(status_code=500, detail="Failed to clear memory data.") from exc
@@ -203,7 +202,6 @@ async def create_memory_fact_endpoint(request: FactCreateRequest) -> MemoryRespo
content=request.content, content=request.content,
category=request.category, category=request.category,
confidence=request.confidence, confidence=request.confidence,
user_id=get_effective_user_id(),
) )
except ValueError as exc: except ValueError as exc:
raise _map_memory_fact_value_error(exc) from exc raise _map_memory_fact_value_error(exc) from exc
@@ -223,7 +221,7 @@ async def create_memory_fact_endpoint(request: FactCreateRequest) -> MemoryRespo
async def delete_memory_fact_endpoint(fact_id: str) -> MemoryResponse: async def delete_memory_fact_endpoint(fact_id: str) -> MemoryResponse:
"""Delete a single fact from memory by fact id.""" """Delete a single fact from memory by fact id."""
try: try:
memory_data = delete_memory_fact(fact_id, user_id=get_effective_user_id()) memory_data = delete_memory_fact(fact_id)
except KeyError as exc: except KeyError as exc:
raise HTTPException(status_code=404, detail=f"Memory fact '{fact_id}' not found.") from exc raise HTTPException(status_code=404, detail=f"Memory fact '{fact_id}' not found.") from exc
except OSError as exc: except OSError as exc:
@@ -247,7 +245,6 @@ async def update_memory_fact_endpoint(fact_id: str, request: FactPatchRequest) -
content=request.content, content=request.content,
category=request.category, category=request.category,
confidence=request.confidence, confidence=request.confidence,
user_id=get_effective_user_id(),
) )
except ValueError as exc: except ValueError as exc:
raise _map_memory_fact_value_error(exc) from exc raise _map_memory_fact_value_error(exc) from exc
@@ -268,7 +265,7 @@ async def update_memory_fact_endpoint(fact_id: str, request: FactPatchRequest) -
) )
async def export_memory() -> MemoryResponse: async def export_memory() -> MemoryResponse:
"""Export the current memory data.""" """Export the current memory data."""
memory_data = get_memory_data(user_id=get_effective_user_id()) memory_data = get_memory_data()
return MemoryResponse(**memory_data) return MemoryResponse(**memory_data)
@@ -282,7 +279,7 @@ async def export_memory() -> MemoryResponse:
async def import_memory(request: MemoryResponse) -> MemoryResponse: async def import_memory(request: MemoryResponse) -> MemoryResponse:
"""Import and persist memory data.""" """Import and persist memory data."""
try: try:
memory_data = import_memory_data(request.model_dump(), user_id=get_effective_user_id()) memory_data = import_memory_data(request.model_dump())
except OSError as exc: except OSError as exc:
raise HTTPException(status_code=500, detail="Failed to import memory data.") from exc raise HTTPException(status_code=500, detail="Failed to import memory data.") from exc
@@ -340,7 +337,7 @@ async def get_memory_status() -> MemoryStatusResponse:
Combined memory configuration and current data. Combined memory configuration and current data.
""" """
config = get_memory_config() config = get_memory_config()
memory_data = get_memory_data(user_id=get_effective_user_id()) memory_data = get_memory_data()
return MemoryStatusResponse( return MemoryStatusResponse(
config=MemoryConfigResponse( config=MemoryConfigResponse(
+11 -27
View File
@@ -1,8 +1,7 @@
from fastapi import APIRouter, Depends, HTTPException from fastapi import APIRouter, HTTPException
from pydantic import BaseModel, Field from pydantic import BaseModel, Field
from app.gateway.deps import get_config from deerflow.config import get_app_config
from deerflow.config.app_config import AppConfig
router = APIRouter(prefix="/api", tags=["models"]) router = APIRouter(prefix="/api", tags=["models"])
@@ -18,17 +17,10 @@ class ModelResponse(BaseModel):
supports_reasoning_effort: bool = Field(default=False, description="Whether model supports reasoning effort") supports_reasoning_effort: bool = Field(default=False, description="Whether model supports reasoning effort")
class TokenUsageResponse(BaseModel):
"""Token usage display configuration."""
enabled: bool = Field(default=False, description="Whether token usage display is enabled")
class ModelsListResponse(BaseModel): class ModelsListResponse(BaseModel):
"""Response model for listing all models.""" """Response model for listing all models."""
models: list[ModelResponse] models: list[ModelResponse]
token_usage: TokenUsageResponse
@router.get( @router.get(
@@ -37,14 +29,14 @@ class ModelsListResponse(BaseModel):
summary="List All Models", summary="List All Models",
description="Retrieve a list of all available AI models configured in the system.", description="Retrieve a list of all available AI models configured in the system.",
) )
async def list_models(config: AppConfig = Depends(get_config)) -> ModelsListResponse: async def list_models() -> ModelsListResponse:
"""List all available models from configuration. """List all available models from configuration.
Returns model information suitable for frontend display, Returns model information suitable for frontend display,
excluding sensitive fields like API keys and internal configuration. excluding sensitive fields like API keys and internal configuration.
Returns: Returns:
A list of all configured models with their metadata and token usage display settings. A list of all configured models with their metadata.
Example Response: Example Response:
```json ```json
@@ -52,27 +44,21 @@ async def list_models(config: AppConfig = Depends(get_config)) -> ModelsListResp
"models": [ "models": [
{ {
"name": "gpt-4", "name": "gpt-4",
"model": "gpt-4",
"display_name": "GPT-4", "display_name": "GPT-4",
"description": "OpenAI GPT-4 model", "description": "OpenAI GPT-4 model",
"supports_thinking": false, "supports_thinking": false
"supports_reasoning_effort": false
}, },
{ {
"name": "claude-3-opus", "name": "claude-3-opus",
"model": "claude-3-opus",
"display_name": "Claude 3 Opus", "display_name": "Claude 3 Opus",
"description": "Anthropic Claude 3 Opus model", "description": "Anthropic Claude 3 Opus model",
"supports_thinking": true, "supports_thinking": true
"supports_reasoning_effort": false
} }
], ]
"token_usage": {
"enabled": true
}
} }
``` ```
""" """
config = get_app_config()
models = [ models = [
ModelResponse( ModelResponse(
name=model.name, name=model.name,
@@ -84,10 +70,7 @@ async def list_models(config: AppConfig = Depends(get_config)) -> ModelsListResp
) )
for model in config.models for model in config.models
] ]
return ModelsListResponse( return ModelsListResponse(models=models)
models=models,
token_usage=TokenUsageResponse(enabled=config.token_usage.enabled),
)
@router.get( @router.get(
@@ -96,7 +79,7 @@ async def list_models(config: AppConfig = Depends(get_config)) -> ModelsListResp
summary="Get Model Details", summary="Get Model Details",
description="Retrieve detailed information about a specific AI model by its name.", description="Retrieve detailed information about a specific AI model by its name.",
) )
async def get_model(model_name: str, config: AppConfig = Depends(get_config)) -> ModelResponse: async def get_model(model_name: str) -> ModelResponse:
"""Get a specific model by name. """Get a specific model by name.
Args: Args:
@@ -118,6 +101,7 @@ async def get_model(model_name: str, config: AppConfig = Depends(get_config)) ->
} }
``` ```
""" """
config = get_app_config()
model = config.get_model_config(model_name) model = config.get_model_config(model_name)
if model is None: if model is None:
raise HTTPException(status_code=404, detail=f"Model '{model_name}' not found") raise HTTPException(status_code=404, detail=f"Model '{model_name}' not found")
+18 -74
View File
@@ -7,17 +7,16 @@ is reused so that conversation history is preserved across calls.
from __future__ import annotations from __future__ import annotations
import asyncio
import logging import logging
import uuid import uuid
from fastapi import APIRouter, HTTPException, Query, Request from fastapi import APIRouter, Request
from fastapi.responses import StreamingResponse from fastapi.responses import StreamingResponse
from app.gateway.authz import require_permission from app.gateway.deps import get_checkpointer, get_run_manager, get_stream_bridge
from app.gateway.deps import get_checkpointer, get_feedback_repo, get_run_event_store, get_run_manager, get_run_store, get_stream_bridge
from app.gateway.pagination import trim_run_message_page
from app.gateway.routers.thread_runs import RunCreateRequest from app.gateway.routers.thread_runs import RunCreateRequest
from app.gateway.services import sse_consumer, start_run, wait_for_run_completion from app.gateway.services import sse_consumer, start_run
from deerflow.runtime import serialize_channel_values from deerflow.runtime import serialize_channel_values
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
@@ -66,78 +65,23 @@ async def stateless_wait(body: RunCreateRequest, request: Request) -> dict:
Otherwise a new temporary thread is created. Otherwise a new temporary thread is created.
""" """
thread_id = _resolve_thread_id(body) thread_id = _resolve_thread_id(body)
bridge = get_stream_bridge(request)
run_mgr = get_run_manager(request)
record = await start_run(body, thread_id, request) record = await start_run(body, thread_id, request)
completed = True
if record.task is not None: if record.task is not None:
completed = await wait_for_run_completion(bridge, record, request, run_mgr)
if completed:
checkpointer = get_checkpointer(request)
config = {"configurable": {"thread_id": thread_id}}
try: try:
checkpoint_tuple = await checkpointer.aget_tuple(config) await record.task
if checkpoint_tuple is not None: except asyncio.CancelledError:
checkpoint = getattr(checkpoint_tuple, "checkpoint", {}) or {} pass
channel_values = checkpoint.get("channel_values", {})
return serialize_channel_values(channel_values) checkpointer = get_checkpointer(request)
except Exception: config = {"configurable": {"thread_id": thread_id}}
logger.exception("Failed to fetch final state for run %s", record.run_id) try:
checkpoint_tuple = await checkpointer.aget_tuple(config)
if checkpoint_tuple is not None:
checkpoint = getattr(checkpoint_tuple, "checkpoint", {}) or {}
channel_values = checkpoint.get("channel_values", {})
return serialize_channel_values(channel_values)
except Exception:
logger.exception("Failed to fetch final state for run %s", record.run_id)
return {"status": record.status.value, "error": record.error} return {"status": record.status.value, "error": record.error}
# ---------------------------------------------------------------------------
# Run-scoped read endpoints
# ---------------------------------------------------------------------------
async def _resolve_run(run_id: str, request: Request) -> dict:
"""Fetch run by run_id with user ownership check. Raises 404 if not found."""
run_store = get_run_store(request)
record = await run_store.get(run_id) # user_id=AUTO filters by contextvar
if record is None:
raise HTTPException(status_code=404, detail=f"Run {run_id} not found")
return record
@router.get("/{run_id}/messages")
@require_permission("runs", "read")
async def run_messages(
run_id: str,
request: Request,
limit: int = Query(default=50, le=200, ge=1),
before_seq: int | None = Query(default=None),
after_seq: int | None = Query(default=None),
) -> dict:
"""Return paginated messages for a run (cursor-based).
Pagination:
- after_seq: messages with seq > after_seq (forward)
- before_seq: messages with seq < before_seq (backward)
- neither: latest messages
Response: { data: [...], has_more: bool }
"""
run = await _resolve_run(run_id, request)
event_store = get_run_event_store(request)
rows = await event_store.list_messages_by_run(
run["thread_id"],
run_id,
limit=limit + 1,
before_seq=before_seq,
after_seq=after_seq,
)
data, has_more = trim_run_message_page(rows, limit=limit, after_seq=after_seq)
return {"data": data, "has_more": has_more}
@router.get("/{run_id}/feedback")
@require_permission("runs", "read")
async def run_feedback(run_id: str, request: Request) -> list[dict]:
"""Return all feedback for a run."""
run = await _resolve_run(run_id, request)
feedback_repo = get_feedback_repo(request)
return await feedback_repo.list_by_run(run["thread_id"], run_id)
+65 -61
View File
@@ -1,20 +1,29 @@
import json import json
import logging import logging
import shutil
from pathlib import Path from pathlib import Path
from fastapi import APIRouter, Depends, HTTPException from fastapi import APIRouter, HTTPException
from pydantic import BaseModel, Field from pydantic import BaseModel, Field
from app.gateway.deps import get_config
from app.gateway.path_utils import resolve_thread_virtual_path 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.agents.lead_agent.prompt import refresh_skills_system_prompt_cache_async
from deerflow.config.app_config import AppConfig
from deerflow.config.extensions_config import ExtensionsConfig, SkillStateConfig, get_extensions_config, reload_extensions_config from deerflow.config.extensions_config import ExtensionsConfig, SkillStateConfig, get_extensions_config, reload_extensions_config
from deerflow.skills import Skill from deerflow.skills import Skill, load_skills
from deerflow.skills.installer import SkillAlreadyExistsError 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 from deerflow.skills.security_scanner import scan_skill_content
from deerflow.skills.storage import get_or_new_skill_storage
from deerflow.skills.types import SKILL_MD_FILE, SkillCategory
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
@@ -27,7 +36,7 @@ class SkillResponse(BaseModel):
name: str = Field(..., description="Name of the skill") name: str = Field(..., description="Name of the skill")
description: str = Field(..., description="Description of what the skill does") description: str = Field(..., description="Description of what the skill does")
license: str | None = Field(None, description="License information") license: str | None = Field(None, description="License information")
category: SkillCategory = Field(..., description="Category of the skill (public or custom)") category: str = Field(..., description="Category of the skill (public or custom)")
enabled: bool = Field(default=True, description="Whether this skill is enabled") enabled: bool = Field(default=True, description="Whether this skill is enabled")
@@ -91,9 +100,9 @@ def _skill_to_response(skill: Skill) -> SkillResponse:
summary="List All Skills", summary="List All Skills",
description="Retrieve a list of all available skills from both public and custom directories.", description="Retrieve a list of all available skills from both public and custom directories.",
) )
async def list_skills(config: AppConfig = Depends(get_config)) -> SkillsListResponse: async def list_skills() -> SkillsListResponse:
try: try:
skills = get_or_new_skill_storage(app_config=config).load_skills(enabled_only=False) skills = load_skills(enabled_only=False)
return SkillsListResponse(skills=[_skill_to_response(skill) for skill in skills]) return SkillsListResponse(skills=[_skill_to_response(skill) for skill in skills])
except Exception as e: except Exception as e:
logger.error(f"Failed to load skills: {e}", exc_info=True) logger.error(f"Failed to load skills: {e}", exc_info=True)
@@ -106,10 +115,10 @@ async def list_skills(config: AppConfig = Depends(get_config)) -> SkillsListResp
summary="Install Skill", summary="Install Skill",
description="Install a skill from a .skill file (ZIP archive) located in the thread's user-data directory.", description="Install a skill from a .skill file (ZIP archive) located in the thread's user-data directory.",
) )
async def install_skill(request: SkillInstallRequest, config: AppConfig = Depends(get_config)) -> SkillInstallResponse: async def install_skill(request: SkillInstallRequest) -> SkillInstallResponse:
try: try:
skill_file_path = resolve_thread_virtual_path(request.thread_id, request.path) skill_file_path = resolve_thread_virtual_path(request.thread_id, request.path)
result = await get_or_new_skill_storage(app_config=config).ainstall_skill_from_archive(skill_file_path) result = install_skill_from_archive(skill_file_path)
await refresh_skills_system_prompt_cache_async() await refresh_skills_system_prompt_cache_async()
return SkillInstallResponse(**result) return SkillInstallResponse(**result)
except FileNotFoundError as e: except FileNotFoundError as e:
@@ -126,9 +135,9 @@ async def install_skill(request: SkillInstallRequest, config: AppConfig = Depend
@router.get("/skills/custom", response_model=SkillsListResponse, summary="List Custom Skills") @router.get("/skills/custom", response_model=SkillsListResponse, summary="List Custom Skills")
async def list_custom_skills(config: AppConfig = Depends(get_config)) -> SkillsListResponse: async def list_custom_skills() -> SkillsListResponse:
try: try:
skills = [skill for skill in get_or_new_skill_storage(app_config=config).load_skills(enabled_only=False) if skill.category == SkillCategory.CUSTOM] 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]) return SkillsListResponse(skills=[_skill_to_response(skill) for skill in skills])
except Exception as e: except Exception as e:
logger.error("Failed to list custom skills: %s", e, exc_info=True) logger.error("Failed to list custom skills: %s", e, exc_info=True)
@@ -136,14 +145,13 @@ async def list_custom_skills(config: AppConfig = Depends(get_config)) -> SkillsL
@router.get("/skills/custom/{skill_name}", response_model=CustomSkillContentResponse, summary="Get Custom Skill Content") @router.get("/skills/custom/{skill_name}", response_model=CustomSkillContentResponse, summary="Get Custom Skill Content")
async def get_custom_skill(skill_name: str, config: AppConfig = Depends(get_config)) -> CustomSkillContentResponse: async def get_custom_skill(skill_name: str) -> CustomSkillContentResponse:
try: try:
skill_name = skill_name.replace("\r\n", "").replace("\n", "") skills = load_skills(enabled_only=False)
skills = get_or_new_skill_storage(app_config=config).load_skills(enabled_only=False) skill = next((s for s in skills if s.name == skill_name and s.category == "custom"), None)
skill = next((s for s in skills if s.name == skill_name and s.category == SkillCategory.CUSTOM), None)
if skill is None: if skill is None:
raise HTTPException(status_code=404, detail=f"Custom skill '{skill_name}' not found") raise HTTPException(status_code=404, detail=f"Custom skill '{skill_name}' not found")
return CustomSkillContentResponse(**_skill_to_response(skill).model_dump(), content=get_or_new_skill_storage(app_config=config).read_custom_skill(skill_name)) return CustomSkillContentResponse(**_skill_to_response(skill).model_dump(), content=read_custom_skill_content(skill_name))
except HTTPException: except HTTPException:
raise raise
except Exception as e: except Exception as e:
@@ -152,31 +160,30 @@ async def get_custom_skill(skill_name: str, config: AppConfig = Depends(get_conf
@router.put("/skills/custom/{skill_name}", response_model=CustomSkillContentResponse, summary="Edit Custom Skill") @router.put("/skills/custom/{skill_name}", response_model=CustomSkillContentResponse, summary="Edit Custom Skill")
async def update_custom_skill(skill_name: str, request: CustomSkillUpdateRequest, config: AppConfig = Depends(get_config)) -> CustomSkillContentResponse: async def update_custom_skill(skill_name: str, request: CustomSkillUpdateRequest) -> CustomSkillContentResponse:
try: try:
skill_name = skill_name.replace("\r\n", "").replace("\n", "") ensure_custom_skill_is_editable(skill_name)
storage = get_or_new_skill_storage(app_config=config) validate_skill_markdown_content(skill_name, request.content)
storage.ensure_custom_skill_is_editable(skill_name) scan = await scan_skill_content(request.content, executable=False, location=f"{skill_name}/SKILL.md")
storage.validate_skill_markdown_content(skill_name, request.content)
scan = await scan_skill_content(request.content, executable=False, location=f"{skill_name}/{SKILL_MD_FILE}", app_config=config)
if scan.decision == "block": if scan.decision == "block":
raise HTTPException(status_code=400, detail=f"Security scan blocked the edit: {scan.reason}") raise HTTPException(status_code=400, detail=f"Security scan blocked the edit: {scan.reason}")
prev_content = storage.read_custom_skill(skill_name) skill_file = get_custom_skill_dir(skill_name) / "SKILL.md"
storage.write_custom_skill(skill_name, SKILL_MD_FILE, request.content) prev_content = skill_file.read_text(encoding="utf-8")
storage.append_history( atomic_write(skill_file, request.content)
append_history(
skill_name, skill_name,
{ {
"action": "human_edit", "action": "human_edit",
"author": "human", "author": "human",
"thread_id": None, "thread_id": None,
"file_path": SKILL_MD_FILE, "file_path": "SKILL.md",
"prev_content": prev_content, "prev_content": prev_content,
"new_content": request.content, "new_content": request.content,
"scanner": {"decision": scan.decision, "reason": scan.reason}, "scanner": {"decision": scan.decision, "reason": scan.reason},
}, },
) )
await refresh_skills_system_prompt_cache_async() await refresh_skills_system_prompt_cache_async()
return await get_custom_skill(skill_name, config) return await get_custom_skill(skill_name)
except HTTPException: except HTTPException:
raise raise
except FileNotFoundError as e: except FileNotFoundError as e:
@@ -189,22 +196,24 @@ async def update_custom_skill(skill_name: str, request: CustomSkillUpdateRequest
@router.delete("/skills/custom/{skill_name}", summary="Delete Custom Skill") @router.delete("/skills/custom/{skill_name}", summary="Delete Custom Skill")
async def delete_custom_skill(skill_name: str, config: AppConfig = Depends(get_config)) -> dict[str, bool]: async def delete_custom_skill(skill_name: str) -> dict[str, bool]:
try: try:
skill_name = skill_name.replace("\r\n", "").replace("\n", "") ensure_custom_skill_is_editable(skill_name)
storage = get_or_new_skill_storage(app_config=config) skill_dir = get_custom_skill_dir(skill_name)
storage.delete_custom_skill( prev_content = read_custom_skill_content(skill_name)
append_history(
skill_name, skill_name,
history_meta={ {
"action": "human_delete", "action": "human_delete",
"author": "human", "author": "human",
"thread_id": None, "thread_id": None,
"file_path": SKILL_MD_FILE, "file_path": "SKILL.md",
"prev_content": None, "prev_content": prev_content,
"new_content": None, "new_content": None,
"scanner": {"decision": "allow", "reason": "Deletion requested."}, "scanner": {"decision": "allow", "reason": "Deletion requested."},
}, },
) )
shutil.rmtree(skill_dir)
await refresh_skills_system_prompt_cache_async() await refresh_skills_system_prompt_cache_async()
return {"success": True} return {"success": True}
except FileNotFoundError as e: except FileNotFoundError as e:
@@ -217,13 +226,11 @@ async def delete_custom_skill(skill_name: str, config: AppConfig = Depends(get_c
@router.get("/skills/custom/{skill_name}/history", response_model=CustomSkillHistoryResponse, summary="Get Custom Skill History") @router.get("/skills/custom/{skill_name}/history", response_model=CustomSkillHistoryResponse, summary="Get Custom Skill History")
async def get_custom_skill_history(skill_name: str, config: AppConfig = Depends(get_config)) -> CustomSkillHistoryResponse: async def get_custom_skill_history(skill_name: str) -> CustomSkillHistoryResponse:
try: try:
skill_name = skill_name.replace("\r\n", "").replace("\n", "") if not custom_skill_exists(skill_name) and not get_skill_history_file(skill_name).exists():
storage = get_or_new_skill_storage(app_config=config)
if not storage.custom_skill_exists(skill_name) and not storage.get_skill_history_file(skill_name).exists():
raise HTTPException(status_code=404, detail=f"Custom skill '{skill_name}' not found") raise HTTPException(status_code=404, detail=f"Custom skill '{skill_name}' not found")
return CustomSkillHistoryResponse(history=storage.read_history(skill_name)) return CustomSkillHistoryResponse(history=read_history(skill_name))
except HTTPException: except HTTPException:
raise raise
except Exception as e: except Exception as e:
@@ -232,39 +239,38 @@ async def get_custom_skill_history(skill_name: str, config: AppConfig = Depends(
@router.post("/skills/custom/{skill_name}/rollback", response_model=CustomSkillContentResponse, summary="Rollback Custom Skill") @router.post("/skills/custom/{skill_name}/rollback", response_model=CustomSkillContentResponse, summary="Rollback Custom Skill")
async def rollback_custom_skill(skill_name: str, request: SkillRollbackRequest, config: AppConfig = Depends(get_config)) -> CustomSkillContentResponse: async def rollback_custom_skill(skill_name: str, request: SkillRollbackRequest) -> CustomSkillContentResponse:
try: try:
storage = get_or_new_skill_storage(app_config=config) if not custom_skill_exists(skill_name) and not get_skill_history_file(skill_name).exists():
if not storage.custom_skill_exists(skill_name) and not storage.get_skill_history_file(skill_name).exists():
raise HTTPException(status_code=404, detail=f"Custom skill '{skill_name}' not found") raise HTTPException(status_code=404, detail=f"Custom skill '{skill_name}' not found")
history = storage.read_history(skill_name) history = read_history(skill_name)
if not history: if not history:
raise HTTPException(status_code=400, detail=f"Custom skill '{skill_name}' has no history") raise HTTPException(status_code=400, detail=f"Custom skill '{skill_name}' has no history")
record = history[request.history_index] record = history[request.history_index]
target_content = record.get("prev_content") target_content = record.get("prev_content")
if target_content is None: if target_content is None:
raise HTTPException(status_code=400, detail="Selected history entry has no previous content to roll back to") raise HTTPException(status_code=400, detail="Selected history entry has no previous content to roll back to")
storage.validate_skill_markdown_content(skill_name, target_content) validate_skill_markdown_content(skill_name, target_content)
scan = await scan_skill_content(target_content, executable=False, location=f"{skill_name}/{SKILL_MD_FILE}", app_config=config) scan = await scan_skill_content(target_content, executable=False, location=f"{skill_name}/SKILL.md")
skill_file = storage.get_custom_skill_file(skill_name) skill_file = get_custom_skill_file(skill_name)
current_content = skill_file.read_text(encoding="utf-8") if skill_file.exists() else None current_content = skill_file.read_text(encoding="utf-8") if skill_file.exists() else None
history_entry = { history_entry = {
"action": "rollback", "action": "rollback",
"author": "human", "author": "human",
"thread_id": None, "thread_id": None,
"file_path": SKILL_MD_FILE, "file_path": "SKILL.md",
"prev_content": current_content, "prev_content": current_content,
"new_content": target_content, "new_content": target_content,
"rollback_from_ts": record.get("ts"), "rollback_from_ts": record.get("ts"),
"scanner": {"decision": scan.decision, "reason": scan.reason}, "scanner": {"decision": scan.decision, "reason": scan.reason},
} }
if scan.decision == "block": if scan.decision == "block":
storage.append_history(skill_name, history_entry) append_history(skill_name, history_entry)
raise HTTPException(status_code=400, detail=f"Rollback blocked by security scanner: {scan.reason}") raise HTTPException(status_code=400, detail=f"Rollback blocked by security scanner: {scan.reason}")
storage.write_custom_skill(skill_name, SKILL_MD_FILE, target_content) atomic_write(skill_file, target_content)
storage.append_history(skill_name, history_entry) append_history(skill_name, history_entry)
await refresh_skills_system_prompt_cache_async() await refresh_skills_system_prompt_cache_async()
return await get_custom_skill(skill_name, config) return await get_custom_skill(skill_name)
except HTTPException: except HTTPException:
raise raise
except IndexError: except IndexError:
@@ -284,10 +290,9 @@ async def rollback_custom_skill(skill_name: str, request: SkillRollbackRequest,
summary="Get Skill Details", summary="Get Skill Details",
description="Retrieve detailed information about a specific skill by its name.", description="Retrieve detailed information about a specific skill by its name.",
) )
async def get_skill(skill_name: str, config: AppConfig = Depends(get_config)) -> SkillResponse: async def get_skill(skill_name: str) -> SkillResponse:
try: try:
skill_name = skill_name.replace("\r\n", "").replace("\n", "") skills = load_skills(enabled_only=False)
skills = get_or_new_skill_storage(app_config=config).load_skills(enabled_only=False)
skill = next((s for s in skills if s.name == skill_name), None) skill = next((s for s in skills if s.name == skill_name), None)
if skill is None: if skill is None:
@@ -307,10 +312,9 @@ async def get_skill(skill_name: str, config: AppConfig = Depends(get_config)) ->
summary="Update Skill", summary="Update Skill",
description="Update a skill's enabled status by modifying the extensions_config.json file.", description="Update a skill's enabled status by modifying the extensions_config.json file.",
) )
async def update_skill(skill_name: str, request: SkillUpdateRequest, config: AppConfig = Depends(get_config)) -> SkillResponse: async def update_skill(skill_name: str, request: SkillUpdateRequest) -> SkillResponse:
try: try:
skill_name = skill_name.replace("\r\n", "").replace("\n", "") skills = load_skills(enabled_only=False)
skills = get_or_new_skill_storage(app_config=config).load_skills(enabled_only=False)
skill = next((s for s in skills if s.name == skill_name), None) skill = next((s for s in skills if s.name == skill_name), None)
if skill is None: if skill is None:
@@ -336,7 +340,7 @@ async def update_skill(skill_name: str, request: SkillUpdateRequest, config: App
reload_extensions_config() reload_extensions_config()
await refresh_skills_system_prompt_cache_async() await refresh_skills_system_prompt_cache_async()
skills = get_or_new_skill_storage(app_config=config).load_skills(enabled_only=False) skills = load_skills(enabled_only=False)
updated_skill = next((s for s in skills if s.name == skill_name), None) updated_skill = next((s for s in skills if s.name == skill_name), None)
if updated_skill is None: if updated_skill is None:
+4 -11
View File
@@ -1,13 +1,11 @@
import json import json
import logging import logging
from fastapi import APIRouter, Depends, Request from fastapi import APIRouter, Request
from langchain_core.messages import HumanMessage, SystemMessage from langchain_core.messages import HumanMessage, SystemMessage
from pydantic import BaseModel, Field from pydantic import BaseModel, Field
from app.gateway.authz import require_permission from app.gateway.authz import require_permission
from app.gateway.deps import get_config
from deerflow.config.app_config import AppConfig
from deerflow.models import create_chat_model from deerflow.models import create_chat_model
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
@@ -102,12 +100,7 @@ def _format_conversation(messages: list[SuggestionMessage]) -> str:
description="Generate short follow-up questions a user might ask next, based on recent conversation context.", description="Generate short follow-up questions a user might ask next, based on recent conversation context.",
) )
@require_permission("threads", "read", owner_check=True) @require_permission("threads", "read", owner_check=True)
async def generate_suggestions( async def generate_suggestions(thread_id: str, body: SuggestionsRequest, request: Request) -> SuggestionsResponse:
thread_id: str,
body: SuggestionsRequest,
request: Request,
config: AppConfig = Depends(get_config),
) -> SuggestionsResponse:
if not body.messages: if not body.messages:
return SuggestionsResponse(suggestions=[]) return SuggestionsResponse(suggestions=[])
@@ -129,8 +122,8 @@ async def generate_suggestions(
user_content = f"Conversation Context:\n{conversation}\n\nGenerate {n} follow-up questions" user_content = f"Conversation Context:\n{conversation}\n\nGenerate {n} follow-up questions"
try: try:
model = create_chat_model(name=body.model_name, thinking_enabled=False, app_config=config) model = create_chat_model(name=body.model_name, thinking_enabled=False)
response = await model.ainvoke([SystemMessage(content=system_instruction), HumanMessage(content=user_content)], config={"run_name": "suggest_agent"}) response = await model.ainvoke([SystemMessage(content=system_instruction), HumanMessage(content=user_content)])
raw = _extract_response_text(response.content) raw = _extract_response_text(response.content)
suggestions = _parse_json_string_list(raw) or [] suggestions = _parse_json_string_list(raw) or []
cleaned = [s.replace("\n", " ").strip() for s in suggestions if s.strip()] cleaned = [s.replace("\n", " ").strip() for s in suggestions if s.strip()]
+39 -149
View File
@@ -20,10 +20,9 @@ from fastapi.responses import Response, StreamingResponse
from pydantic import BaseModel, Field from pydantic import BaseModel, Field
from app.gateway.authz import require_permission from app.gateway.authz import require_permission
from app.gateway.deps import get_checkpointer, get_current_user, get_feedback_repo, get_run_event_store, get_run_manager, get_run_store, get_stream_bridge from app.gateway.deps import get_checkpointer, get_run_event_store, get_run_manager, get_run_store, get_stream_bridge
from app.gateway.pagination import trim_run_message_page from app.gateway.services import sse_consumer, start_run
from app.gateway.services import sse_consumer, start_run, wait_for_run_completion from deerflow.runtime import RunRecord, serialize_channel_values
from deerflow.runtime import RunRecord, RunStatus, serialize_channel_values
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
router = APIRouter(prefix="/api/threads", tags=["runs"]) router = APIRouter(prefix="/api/threads", tags=["runs"])
@@ -55,6 +54,7 @@ class RunCreateRequest(BaseModel):
after_seconds: float | None = Field(default=None, description="Delayed execution") after_seconds: float | None = Field(default=None, description="Delayed execution")
if_not_exists: Literal["reject", "create"] = Field(default="create", description="Thread creation policy") 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") 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): class RunResponse(BaseModel):
@@ -67,35 +67,6 @@ class RunResponse(BaseModel):
multitask_strategy: str = "reject" multitask_strategy: str = "reject"
created_at: str = "" created_at: str = ""
updated_at: str = "" updated_at: 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
class ThreadTokenUsageModelBreakdown(BaseModel):
tokens: int = 0
runs: int = 0
class ThreadTokenUsageCallerBreakdown(BaseModel):
lead_agent: int = 0
subagent: int = 0
middleware: int = 0
class ThreadTokenUsageResponse(BaseModel):
thread_id: str
total_tokens: int = 0
total_input_tokens: int = 0
total_output_tokens: int = 0
total_runs: int = 0
by_model: dict[str, ThreadTokenUsageModelBreakdown] = Field(default_factory=dict)
by_caller: ThreadTokenUsageCallerBreakdown = Field(default_factory=ThreadTokenUsageCallerBreakdown)
# --------------------------------------------------------------------------- # ---------------------------------------------------------------------------
@@ -103,12 +74,6 @@ class ThreadTokenUsageResponse(BaseModel):
# --------------------------------------------------------------------------- # ---------------------------------------------------------------------------
def _cancel_conflict_detail(run_id: str, record: RunRecord) -> str:
if record.status in (RunStatus.pending, RunStatus.running):
return f"Run {run_id} is not active on this worker and cannot be cancelled"
return f"Run {run_id} is not cancellable (status: {record.status.value})"
def _record_to_response(record: RunRecord) -> RunResponse: def _record_to_response(record: RunRecord) -> RunResponse:
return RunResponse( return RunResponse(
run_id=record.run_id, run_id=record.run_id,
@@ -120,14 +85,6 @@ def _record_to_response(record: RunRecord) -> RunResponse:
multitask_strategy=record.multitask_strategy, multitask_strategy=record.multitask_strategy,
created_at=record.created_at, created_at=record.created_at,
updated_at=record.updated_at, updated_at=record.updated_at,
total_input_tokens=record.total_input_tokens,
total_output_tokens=record.total_output_tokens,
total_tokens=record.total_tokens,
llm_call_count=record.llm_call_count,
lead_agent_tokens=record.lead_agent_tokens,
subagent_tokens=record.subagent_tokens,
middleware_tokens=record.middleware_tokens,
message_count=record.message_count,
) )
@@ -176,25 +133,24 @@ async def stream_run(thread_id: str, body: RunCreateRequest, request: Request) -
@require_permission("runs", "create", owner_check=True, require_existing=True) @require_permission("runs", "create", owner_check=True, require_existing=True)
async def wait_run(thread_id: str, body: RunCreateRequest, request: Request) -> dict: async def wait_run(thread_id: str, body: RunCreateRequest, request: Request) -> dict:
"""Create a run and block until it completes, returning the final state.""" """Create a run and block until it completes, returning the final state."""
bridge = get_stream_bridge(request)
run_mgr = get_run_manager(request)
record = await start_run(body, thread_id, request) record = await start_run(body, thread_id, request)
completed = True
if record.task is not None: if record.task is not None:
completed = await wait_for_run_completion(bridge, record, request, run_mgr)
if completed:
checkpointer = get_checkpointer(request)
config = {"configurable": {"thread_id": thread_id}}
try: try:
checkpoint_tuple = await checkpointer.aget_tuple(config) await record.task
if checkpoint_tuple is not None: except asyncio.CancelledError:
checkpoint = getattr(checkpoint_tuple, "checkpoint", {}) or {} pass
channel_values = checkpoint.get("channel_values", {})
return serialize_channel_values(channel_values) checkpointer = get_checkpointer(request)
except Exception: config = {"configurable": {"thread_id": thread_id}}
logger.exception("Failed to fetch final state for run %s", record.run_id) try:
checkpoint_tuple = await checkpointer.aget_tuple(config)
if checkpoint_tuple is not None:
checkpoint = getattr(checkpoint_tuple, "checkpoint", {}) or {}
channel_values = checkpoint.get("channel_values", {})
return serialize_channel_values(channel_values)
except Exception:
logger.exception("Failed to fetch final state for run %s", record.run_id)
return {"status": record.status.value, "error": record.error} return {"status": record.status.value, "error": record.error}
@@ -204,8 +160,7 @@ async def wait_run(thread_id: str, body: RunCreateRequest, request: Request) ->
async def list_runs(thread_id: str, request: Request) -> list[RunResponse]: async def list_runs(thread_id: str, request: Request) -> list[RunResponse]:
"""List all runs for a thread.""" """List all runs for a thread."""
run_mgr = get_run_manager(request) run_mgr = get_run_manager(request)
user_id = await get_current_user(request) records = await run_mgr.list_by_thread(thread_id)
records = await run_mgr.list_by_thread(thread_id, user_id=user_id)
return [_record_to_response(r) for r in records] return [_record_to_response(r) for r in records]
@@ -214,8 +169,7 @@ async def list_runs(thread_id: str, request: Request) -> list[RunResponse]:
async def get_run(thread_id: str, run_id: str, request: Request) -> RunResponse: async def get_run(thread_id: str, run_id: str, request: Request) -> RunResponse:
"""Get details of a specific run.""" """Get details of a specific run."""
run_mgr = get_run_manager(request) run_mgr = get_run_manager(request)
user_id = await get_current_user(request) record = run_mgr.get(run_id)
record = await run_mgr.get(run_id, user_id=user_id)
if record is None or record.thread_id != thread_id: if record is None or record.thread_id != thread_id:
raise HTTPException(status_code=404, detail=f"Run {run_id} not found") raise HTTPException(status_code=404, detail=f"Run {run_id} not found")
return _record_to_response(record) return _record_to_response(record)
@@ -238,13 +192,16 @@ async def cancel_run(
- wait=false: Return immediately with 202 - wait=false: Return immediately with 202
""" """
run_mgr = get_run_manager(request) run_mgr = get_run_manager(request)
record = await run_mgr.get(run_id) record = run_mgr.get(run_id)
if record is None or record.thread_id != thread_id: if record is None or record.thread_id != thread_id:
raise HTTPException(status_code=404, detail=f"Run {run_id} not found") raise HTTPException(status_code=404, detail=f"Run {run_id} not found")
cancelled = await run_mgr.cancel(run_id, action=action) cancelled = await run_mgr.cancel(run_id, action=action)
if not cancelled: if not cancelled:
raise HTTPException(status_code=409, detail=_cancel_conflict_detail(run_id, record)) raise HTTPException(
status_code=409,
detail=f"Run {run_id} is not cancellable (status: {record.status.value})",
)
if wait and record.task is not None: if wait and record.task is not None:
try: try:
@@ -260,14 +217,12 @@ async def cancel_run(
@require_permission("runs", "read", owner_check=True) @require_permission("runs", "read", owner_check=True)
async def join_run(thread_id: str, run_id: str, request: Request) -> StreamingResponse: async def join_run(thread_id: str, run_id: str, request: Request) -> StreamingResponse:
"""Join an existing run's SSE stream.""" """Join an existing run's SSE stream."""
bridge = get_stream_bridge(request)
run_mgr = get_run_manager(request) run_mgr = get_run_manager(request)
record = await run_mgr.get(run_id) record = run_mgr.get(run_id)
if record is None or record.thread_id != thread_id: if record is None or record.thread_id != thread_id:
raise HTTPException(status_code=404, detail=f"Run {run_id} not found") raise HTTPException(status_code=404, detail=f"Run {run_id} not found")
if record.store_only:
raise HTTPException(status_code=409, detail=f"Run {run_id} is not active on this worker and cannot be streamed")
bridge = get_stream_bridge(request)
return StreamingResponse( return StreamingResponse(
sse_consumer(bridge, record, request, run_mgr), sse_consumer(bridge, record, request, run_mgr),
media_type="text/event-stream", media_type="text/event-stream",
@@ -279,12 +234,7 @@ async def join_run(thread_id: str, run_id: str, request: Request) -> StreamingRe
) )
# Register GET and POST as separate routes so each method gets a unique OpenAPI @router.api_route("/{thread_id}/runs/{run_id}/stream", methods=["GET", "POST"], response_model=None)
# operationId. ``api_route(methods=["GET", "POST"])`` shares one route registration
# across both methods, which makes FastAPI emit the same ``operationId`` twice and
# warn about a duplicate operation id during OpenAPI generation.
@router.get("/{thread_id}/runs/{run_id}/stream", response_model=None)
@router.post("/{thread_id}/runs/{run_id}/stream", response_model=None)
@require_permission("runs", "read", owner_check=True) @require_permission("runs", "read", owner_check=True)
async def stream_existing_run( async def stream_existing_run(
thread_id: str, thread_id: str,
@@ -301,18 +251,14 @@ async def stream_existing_run(
remaining buffered events so the client observes a clean shutdown. remaining buffered events so the client observes a clean shutdown.
""" """
run_mgr = get_run_manager(request) run_mgr = get_run_manager(request)
record = await run_mgr.get(run_id) record = run_mgr.get(run_id)
if record is None or record.thread_id != thread_id: if record is None or record.thread_id != thread_id:
raise HTTPException(status_code=404, detail=f"Run {run_id} not found") raise HTTPException(status_code=404, detail=f"Run {run_id} not found")
if record.store_only and action is None:
raise HTTPException(status_code=409, detail=f"Run {run_id} is not active on this worker and cannot be streamed")
# Cancel if an action was requested (stop-button / interrupt flow) # Cancel if an action was requested (stop-button / interrupt flow)
if action is not None: if action is not None:
cancelled = await run_mgr.cancel(run_id, action=action) cancelled = await run_mgr.cancel(run_id, action=action)
if not cancelled: if cancelled and wait and record.task is not None:
raise HTTPException(status_code=409, detail=_cancel_conflict_detail(run_id, record))
if wait and record.task is not None:
try: try:
await record.task await record.task
except (asyncio.CancelledError, Exception): except (asyncio.CancelledError, Exception):
@@ -345,66 +291,17 @@ async def list_thread_messages(
before_seq: int | None = Query(default=None), before_seq: int | None = Query(default=None),
after_seq: int | None = Query(default=None), after_seq: int | None = Query(default=None),
) -> list[dict]: ) -> list[dict]:
"""Return displayable messages for a thread (across all runs), with feedback attached.""" """Return displayable messages for a thread (across all runs)."""
event_store = get_run_event_store(request) event_store = get_run_event_store(request)
messages = await event_store.list_messages(thread_id, limit=limit, before_seq=before_seq, after_seq=after_seq) return await event_store.list_messages(thread_id, limit=limit, before_seq=before_seq, after_seq=after_seq)
# Attach feedback to the last AI message of each run
feedback_repo = get_feedback_repo(request)
user_id = await get_current_user(request)
feedback_map = await feedback_repo.list_by_thread_grouped(thread_id, user_id=user_id)
# Find the last ai_message per run_id
last_ai_per_run: dict[str, int] = {} # run_id -> index in messages list
for i, msg in enumerate(messages):
if msg.get("event_type") == "ai_message":
last_ai_per_run[msg["run_id"]] = i
# Attach feedback field
last_ai_indices = set(last_ai_per_run.values())
for i, msg in enumerate(messages):
if i in last_ai_indices:
run_id = msg["run_id"]
fb = feedback_map.get(run_id)
msg["feedback"] = (
{
"feedback_id": fb["feedback_id"],
"rating": fb["rating"],
"comment": fb.get("comment"),
}
if fb
else None
)
else:
msg["feedback"] = None
return messages
@router.get("/{thread_id}/runs/{run_id}/messages") @router.get("/{thread_id}/runs/{run_id}/messages")
@require_permission("runs", "read", owner_check=True) @require_permission("runs", "read", owner_check=True)
async def list_run_messages( async def list_run_messages(thread_id: str, run_id: str, request: Request) -> list[dict]:
thread_id: str, """Return displayable messages for a specific run."""
run_id: str,
request: Request,
limit: int = Query(default=50, le=200, ge=1),
before_seq: int | None = Query(default=None),
after_seq: int | None = Query(default=None),
) -> dict:
"""Return paginated messages for a specific run.
Response: { data: [...], has_more: bool }
"""
event_store = get_run_event_store(request) event_store = get_run_event_store(request)
rows = await event_store.list_messages_by_run( return await event_store.list_messages_by_run(thread_id, run_id)
thread_id,
run_id,
limit=limit + 1,
before_seq=before_seq,
after_seq=after_seq,
)
data, has_more = trim_run_message_page(rows, limit=limit, after_seq=after_seq)
return {"data": data, "has_more": has_more}
@router.get("/{thread_id}/runs/{run_id}/events") @router.get("/{thread_id}/runs/{run_id}/events")
@@ -422,17 +319,10 @@ async def list_run_events(
return await event_store.list_events(thread_id, run_id, event_types=types, limit=limit) return await event_store.list_events(thread_id, run_id, event_types=types, limit=limit)
@router.get("/{thread_id}/token-usage", response_model=ThreadTokenUsageResponse) @router.get("/{thread_id}/token-usage")
@require_permission("threads", "read", owner_check=True) @require_permission("threads", "read", owner_check=True)
async def thread_token_usage( async def thread_token_usage(thread_id: str, request: Request) -> dict:
thread_id: str,
request: Request,
include_active: bool = Query(default=False, description="Include running run progress snapshots"),
) -> ThreadTokenUsageResponse:
"""Thread-level token usage aggregation.""" """Thread-level token usage aggregation."""
run_store = get_run_store(request) run_store = get_run_store(request)
if include_active: agg = await run_store.aggregate_tokens_by_thread(thread_id)
agg = await run_store.aggregate_tokens_by_thread(thread_id, include_active=True) return {"thread_id": thread_id, **agg}
else:
agg = await run_store.aggregate_tokens_by_thread(thread_id)
return ThreadTokenUsageResponse(thread_id=thread_id, **agg)
+53 -85
View File
@@ -13,11 +13,11 @@ matching the LangGraph Platform wire format expected by the
from __future__ import annotations from __future__ import annotations
import logging import logging
import time
import uuid import uuid
from typing import Any from typing import Any
from fastapi import APIRouter, HTTPException, Request from fastapi import APIRouter, HTTPException, Request
from langgraph.checkpoint.base import empty_checkpoint
from pydantic import BaseModel, Field, field_validator from pydantic import BaseModel, Field, field_validator
from app.gateway.authz import require_permission from app.gateway.authz import require_permission
@@ -25,8 +25,6 @@ from app.gateway.deps import get_checkpointer
from app.gateway.utils import sanitize_log_param from app.gateway.utils import sanitize_log_param
from deerflow.config.paths import Paths, get_paths from deerflow.config.paths import Paths, get_paths
from deerflow.runtime import serialize_channel_values from deerflow.runtime import serialize_channel_values
from deerflow.runtime.user_context import get_effective_user_id
from deerflow.utils.time import coerce_iso, now_iso
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
router = APIRouter(prefix="/api/threads", tags=["threads"]) router = APIRouter(prefix="/api/threads", tags=["threads"])
@@ -36,7 +34,7 @@ router = APIRouter(prefix="/api/threads", tags=["threads"])
# them. Pydantic ``@field_validator("metadata")`` strips them on every # them. Pydantic ``@field_validator("metadata")`` strips them on every
# inbound model below so a malicious client cannot reflect a forged # inbound model below so a malicious client cannot reflect a forged
# owner identity through the API surface. Defense-in-depth — the # owner identity through the API surface. Defense-in-depth — the
# row-level invariant is still ``threads_meta.user_id`` populated from # row-level invariant is still ``threads_meta.owner_id`` populated from
# the auth contextvar; this list closes the metadata-blob echo gap. # the auth contextvar; this list closes the metadata-blob echo gap.
_SERVER_RESERVED_METADATA_KEYS: frozenset[str] = frozenset({"owner_id", "user_id"}) _SERVER_RESERVED_METADATA_KEYS: frozenset[str] = frozenset({"owner_id", "user_id"})
@@ -90,28 +88,6 @@ class ThreadSearchRequest(BaseModel):
offset: int = Field(default=0, ge=0, description="Pagination offset") offset: int = Field(default=0, ge=0, description="Pagination offset")
status: str | None = Field(default=None, description="Filter by thread status") status: str | None = Field(default=None, description="Filter by thread status")
@field_validator("metadata")
@classmethod
def _validate_metadata_filters(cls, v: dict[str, Any]) -> dict[str, Any]:
"""Reject filter entries the SQL backend cannot compile.
Enforces consistent behaviour across SQL and memory backends.
See ``deerflow.persistence.json_compat`` for the shared validators.
"""
if not v:
return v
from deerflow.persistence.json_compat import validate_metadata_filter_key, validate_metadata_filter_value
bad_entries: list[str] = []
for key, value in v.items():
if not validate_metadata_filter_key(key):
bad_entries.append(f"{key!r} (unsafe key)")
elif not validate_metadata_filter_value(value):
bad_entries.append(f"{key!r} (unsupported value type {type(value).__name__})")
if bad_entries:
raise ValueError(f"Invalid metadata filter entries: {', '.join(bad_entries)}")
return v
class ThreadStateResponse(BaseModel): class ThreadStateResponse(BaseModel):
"""Response model for thread state.""" """Response model for thread state."""
@@ -166,11 +142,11 @@ class ThreadHistoryRequest(BaseModel):
# --------------------------------------------------------------------------- # ---------------------------------------------------------------------------
def _delete_thread_data(thread_id: str, paths: Paths | None = None, *, user_id: str | None = None) -> ThreadDeleteResponse: def _delete_thread_data(thread_id: str, paths: Paths | None = None) -> ThreadDeleteResponse:
"""Delete local persisted filesystem data for a thread.""" """Delete local persisted filesystem data for a thread."""
path_manager = paths or get_paths() path_manager = paths or get_paths()
try: try:
path_manager.delete_thread_dir(thread_id, user_id=user_id) path_manager.delete_thread_dir(thread_id)
except ValueError as exc: except ValueError as exc:
raise HTTPException(status_code=422, detail=str(exc)) from exc raise HTTPException(status_code=422, detail=str(exc)) from exc
except FileNotFoundError: except FileNotFoundError:
@@ -218,10 +194,10 @@ async def delete_thread_data(thread_id: str, request: Request) -> ThreadDeleteRe
and removes the thread_meta row from the configured ThreadMetaStore and removes the thread_meta row from the configured ThreadMetaStore
(sqlite or memory). (sqlite or memory).
""" """
from app.gateway.deps import get_thread_store from app.gateway.deps import get_thread_meta_repo
# Clean local filesystem # Clean local filesystem
response = _delete_thread_data(thread_id, user_id=get_effective_user_id()) response = _delete_thread_data(thread_id)
# Remove checkpoints (best-effort) # Remove checkpoints (best-effort)
checkpointer = getattr(request.app.state, "checkpointer", None) checkpointer = getattr(request.app.state, "checkpointer", None)
@@ -235,8 +211,8 @@ async def delete_thread_data(thread_id: str, request: Request) -> ThreadDeleteRe
# Remove thread_meta row (best-effort) — required for sqlite backend # Remove thread_meta row (best-effort) — required for sqlite backend
# so the deleted thread no longer appears in /threads/search. # so the deleted thread no longer appears in /threads/search.
try: try:
thread_store = get_thread_store(request) thread_meta_repo = get_thread_meta_repo(request)
await thread_store.delete(thread_id) await thread_meta_repo.delete(thread_id)
except Exception: except Exception:
logger.debug("Could not delete thread_meta for %s (not critical)", sanitize_log_param(thread_id)) logger.debug("Could not delete thread_meta for %s (not critical)", sanitize_log_param(thread_id))
@@ -251,29 +227,29 @@ async def create_thread(body: ThreadCreateRequest, request: Request) -> ThreadRe
and an empty checkpoint (so state endpoints work immediately). and an empty checkpoint (so state endpoints work immediately).
Idempotent: returns the existing record when ``thread_id`` already exists. Idempotent: returns the existing record when ``thread_id`` already exists.
""" """
from app.gateway.deps import get_thread_store from app.gateway.deps import get_thread_meta_repo
checkpointer = get_checkpointer(request) checkpointer = get_checkpointer(request)
thread_store = get_thread_store(request) thread_meta_repo = get_thread_meta_repo(request)
thread_id = body.thread_id or str(uuid.uuid4()) thread_id = body.thread_id or str(uuid.uuid4())
now = now_iso() now = time.time()
# ``body.metadata`` is already stripped of server-reserved keys by # ``body.metadata`` is already stripped of server-reserved keys by
# ``ThreadCreateRequest._strip_reserved`` — see the model definition. # ``ThreadCreateRequest._strip_reserved`` — see the model definition.
# Idempotency: return existing record when already present # Idempotency: return existing record when already present
existing_record = await thread_store.get(thread_id) existing_record = await thread_meta_repo.get(thread_id)
if existing_record is not None: if existing_record is not None:
return ThreadResponse( return ThreadResponse(
thread_id=thread_id, thread_id=thread_id,
status=existing_record.get("status", "idle"), status=existing_record.get("status", "idle"),
created_at=coerce_iso(existing_record.get("created_at", "")), created_at=str(existing_record.get("created_at", "")),
updated_at=coerce_iso(existing_record.get("updated_at", "")), updated_at=str(existing_record.get("updated_at", "")),
metadata=existing_record.get("metadata", {}), metadata=existing_record.get("metadata", {}),
) )
# Write thread_meta so the thread appears in /threads/search immediately # Write thread_meta so the thread appears in /threads/search immediately
try: try:
await thread_store.create( await thread_meta_repo.create(
thread_id, thread_id,
assistant_id=getattr(body, "assistant_id", None), assistant_id=getattr(body, "assistant_id", None),
metadata=body.metadata, metadata=body.metadata,
@@ -285,6 +261,8 @@ async def create_thread(body: ThreadCreateRequest, request: Request) -> ThreadRe
# Write an empty checkpoint so state endpoints work immediately # Write an empty checkpoint so state endpoints work immediately
config = {"configurable": {"thread_id": thread_id, "checkpoint_ns": ""}} config = {"configurable": {"thread_id": thread_id, "checkpoint_ns": ""}}
try: try:
from langgraph.checkpoint.base import empty_checkpoint
ckpt_metadata = { ckpt_metadata = {
"step": -1, "step": -1,
"source": "input", "source": "input",
@@ -302,8 +280,8 @@ async def create_thread(body: ThreadCreateRequest, request: Request) -> ThreadRe
return ThreadResponse( return ThreadResponse(
thread_id=thread_id, thread_id=thread_id,
status="idle", status="idle",
created_at=now, created_at=str(now),
updated_at=now, updated_at=str(now),
metadata=body.metadata, metadata=body.metadata,
) )
@@ -315,28 +293,21 @@ async def search_threads(body: ThreadSearchRequest, request: Request) -> list[Th
Delegates to the configured ThreadMetaStore implementation Delegates to the configured ThreadMetaStore implementation
(SQL-backed for sqlite/postgres, Store-backed for memory mode). (SQL-backed for sqlite/postgres, Store-backed for memory mode).
""" """
from app.gateway.deps import get_thread_store from app.gateway.deps import get_thread_meta_repo
from deerflow.persistence.thread_meta import InvalidMetadataFilterError
repo = get_thread_store(request) repo = get_thread_meta_repo(request)
try: rows = await repo.search(
rows = await repo.search( metadata=body.metadata or None,
metadata=body.metadata or None, status=body.status,
status=body.status, limit=body.limit,
limit=body.limit, offset=body.offset,
offset=body.offset, )
)
except InvalidMetadataFilterError as exc:
raise HTTPException(status_code=400, detail=str(exc)) from exc
return [ return [
ThreadResponse( ThreadResponse(
thread_id=r["thread_id"], thread_id=r["thread_id"],
status=r.get("status", "idle"), status=r.get("status", "idle"),
# ``coerce_iso`` heals legacy unix-second values that created_at=r.get("created_at", ""),
# ``MemoryThreadMetaStore`` historically wrote with ``time.time()``; updated_at=r.get("updated_at", ""),
# SQL-backed rows already arrive as ISO strings and pass through.
created_at=coerce_iso(r.get("created_at", "")),
updated_at=coerce_iso(r.get("updated_at", "")),
metadata=r.get("metadata", {}), metadata=r.get("metadata", {}),
values={"title": r["display_name"]} if r.get("display_name") else {}, values={"title": r["display_name"]} if r.get("display_name") else {},
interrupts={}, interrupts={},
@@ -349,27 +320,27 @@ async def search_threads(body: ThreadSearchRequest, request: Request) -> list[Th
@require_permission("threads", "write", owner_check=True, require_existing=True) @require_permission("threads", "write", owner_check=True, require_existing=True)
async def patch_thread(thread_id: str, body: ThreadPatchRequest, request: Request) -> ThreadResponse: async def patch_thread(thread_id: str, body: ThreadPatchRequest, request: Request) -> ThreadResponse:
"""Merge metadata into a thread record.""" """Merge metadata into a thread record."""
from app.gateway.deps import get_thread_store from app.gateway.deps import get_thread_meta_repo
thread_store = get_thread_store(request) thread_meta_repo = get_thread_meta_repo(request)
record = await thread_store.get(thread_id) record = await thread_meta_repo.get(thread_id)
if record is None: if record is None:
raise HTTPException(status_code=404, detail=f"Thread {thread_id} not found") raise HTTPException(status_code=404, detail=f"Thread {thread_id} not found")
# ``body.metadata`` already stripped by ``ThreadPatchRequest._strip_reserved``. # ``body.metadata`` already stripped by ``ThreadPatchRequest._strip_reserved``.
try: try:
await thread_store.update_metadata(thread_id, body.metadata) await thread_meta_repo.update_metadata(thread_id, body.metadata)
except Exception: except Exception:
logger.exception("Failed to patch thread %s", sanitize_log_param(thread_id)) logger.exception("Failed to patch thread %s", sanitize_log_param(thread_id))
raise HTTPException(status_code=500, detail="Failed to update thread") raise HTTPException(status_code=500, detail="Failed to update thread")
# Re-read to get the merged metadata + refreshed updated_at # Re-read to get the merged metadata + refreshed updated_at
record = await thread_store.get(thread_id) or record record = await thread_meta_repo.get(thread_id) or record
return ThreadResponse( return ThreadResponse(
thread_id=thread_id, thread_id=thread_id,
status=record.get("status", "idle"), status=record.get("status", "idle"),
created_at=coerce_iso(record.get("created_at", "")), created_at=str(record.get("created_at", "")),
updated_at=coerce_iso(record.get("updated_at", "")), updated_at=str(record.get("updated_at", "")),
metadata=record.get("metadata", {}), metadata=record.get("metadata", {}),
) )
@@ -383,12 +354,12 @@ async def get_thread(thread_id: str, request: Request) -> ThreadResponse:
execution status from the checkpointer. Falls back to the checkpointer execution status from the checkpointer. Falls back to the checkpointer
alone for threads that pre-date ThreadMetaStore adoption (backward compat). alone for threads that pre-date ThreadMetaStore adoption (backward compat).
""" """
from app.gateway.deps import get_thread_store from app.gateway.deps import get_thread_meta_repo
thread_store = get_thread_store(request) thread_meta_repo = get_thread_meta_repo(request)
checkpointer = get_checkpointer(request) checkpointer = get_checkpointer(request)
record: dict | None = await thread_store.get(thread_id) record: dict | None = await thread_meta_repo.get(thread_id)
# Derive accurate status from the checkpointer # Derive accurate status from the checkpointer
config = {"configurable": {"thread_id": thread_id, "checkpoint_ns": ""}} config = {"configurable": {"thread_id": thread_id, "checkpoint_ns": ""}}
@@ -409,8 +380,8 @@ async def get_thread(thread_id: str, request: Request) -> ThreadResponse:
record = { record = {
"thread_id": thread_id, "thread_id": thread_id,
"status": "idle", "status": "idle",
"created_at": coerce_iso(ckpt_meta.get("created_at", "")), "created_at": ckpt_meta.get("created_at", ""),
"updated_at": coerce_iso(ckpt_meta.get("updated_at", ckpt_meta.get("created_at", ""))), "updated_at": ckpt_meta.get("updated_at", ckpt_meta.get("created_at", "")),
"metadata": {k: v for k, v in ckpt_meta.items() if k not in ("created_at", "updated_at", "step", "source", "writes", "parents")}, "metadata": {k: v for k, v in ckpt_meta.items() if k not in ("created_at", "updated_at", "step", "source", "writes", "parents")},
} }
@@ -424,14 +395,13 @@ async def get_thread(thread_id: str, request: Request) -> ThreadResponse:
return ThreadResponse( return ThreadResponse(
thread_id=thread_id, thread_id=thread_id,
status=status, status=status,
created_at=coerce_iso(record.get("created_at", "")), created_at=str(record.get("created_at", "")),
updated_at=coerce_iso(record.get("updated_at", "")), updated_at=str(record.get("updated_at", "")),
metadata=record.get("metadata", {}), metadata=record.get("metadata", {}),
values=serialize_channel_values(channel_values), values=serialize_channel_values(channel_values),
) )
# ---------------------------------------------------------------------------
@router.get("/{thread_id}/state", response_model=ThreadStateResponse) @router.get("/{thread_id}/state", response_model=ThreadStateResponse)
@require_permission("threads", "read", owner_check=True) @require_permission("threads", "read", owner_check=True)
async def get_thread_state(thread_id: str, request: Request) -> ThreadStateResponse: async def get_thread_state(thread_id: str, request: Request) -> ThreadStateResponse:
@@ -470,16 +440,14 @@ async def get_thread_state(thread_id: str, request: Request) -> ThreadStateRespo
next_tasks = [t.name for t in tasks_raw if hasattr(t, "name")] next_tasks = [t.name for t in tasks_raw if hasattr(t, "name")]
tasks = [{"id": getattr(t, "id", ""), "name": getattr(t, "name", "")} for t in tasks_raw] tasks = [{"id": getattr(t, "id", ""), "name": getattr(t, "name", "")} for t in tasks_raw]
values = serialize_channel_values(channel_values)
return ThreadStateResponse( return ThreadStateResponse(
values=values, values=serialize_channel_values(channel_values),
next=next_tasks, next=next_tasks,
metadata=metadata, metadata=metadata,
checkpoint={"id": checkpoint_id, "ts": coerce_iso(metadata.get("created_at", ""))}, checkpoint={"id": checkpoint_id, "ts": str(metadata.get("created_at", ""))},
checkpoint_id=checkpoint_id, checkpoint_id=checkpoint_id,
parent_checkpoint_id=parent_checkpoint_id, parent_checkpoint_id=parent_checkpoint_id,
created_at=coerce_iso(metadata.get("created_at", "")), created_at=str(metadata.get("created_at", "")),
tasks=tasks, tasks=tasks,
) )
@@ -494,10 +462,10 @@ async def update_thread_state(thread_id: str, body: ThreadStateUpdateRequest, re
ThreadMetaStore abstraction so that ``/threads/search`` reflects the ThreadMetaStore abstraction so that ``/threads/search`` reflects the
change immediately in both sqlite and memory backends. change immediately in both sqlite and memory backends.
""" """
from app.gateway.deps import get_thread_store from app.gateway.deps import get_thread_meta_repo
checkpointer = get_checkpointer(request) checkpointer = get_checkpointer(request)
thread_store = get_thread_store(request) thread_meta_repo = get_thread_meta_repo(request)
# checkpoint_ns must be present in the config for aput — default to "" # checkpoint_ns must be present in the config for aput — default to ""
# (the root graph namespace). checkpoint_id is optional; omitting it # (the root graph namespace). checkpoint_id is optional; omitting it
@@ -529,7 +497,7 @@ async def update_thread_state(thread_id: str, body: ThreadStateUpdateRequest, re
channel_values.update(body.values) channel_values.update(body.values)
checkpoint["channel_values"] = channel_values checkpoint["channel_values"] = channel_values
metadata["updated_at"] = now_iso() metadata["updated_at"] = time.time()
if body.as_node: if body.as_node:
metadata["source"] = "update" metadata["source"] = "update"
@@ -561,7 +529,7 @@ async def update_thread_state(thread_id: str, body: ThreadStateUpdateRequest, re
new_title = body.values["title"] new_title = body.values["title"]
if new_title: # Skip empty strings and None if new_title: # Skip empty strings and None
try: try:
await thread_store.update_display_name(thread_id, new_title) await thread_meta_repo.update_display_name(thread_id, new_title)
except Exception: except Exception:
logger.debug("Failed to sync title to thread_meta for %s (non-fatal)", sanitize_log_param(thread_id)) logger.debug("Failed to sync title to thread_meta for %s (non-fatal)", sanitize_log_param(thread_id))
@@ -570,7 +538,7 @@ async def update_thread_state(thread_id: str, body: ThreadStateUpdateRequest, re
next=[], next=[],
metadata=metadata, metadata=metadata,
checkpoint_id=new_checkpoint_id, checkpoint_id=new_checkpoint_id,
created_at=coerce_iso(metadata.get("created_at", "")), created_at=str(metadata.get("created_at", "")),
) )
@@ -614,7 +582,7 @@ async def get_thread_history(thread_id: str, body: ThreadHistoryRequest, request
if thread_data := channel_values.get("thread_data"): if thread_data := channel_values.get("thread_data"):
values["thread_data"] = thread_data values["thread_data"] = thread_data
# Attach messages only to the latest checkpoint entry. # Attach messages from checkpointer only for the latest checkpoint
if is_latest_checkpoint: if is_latest_checkpoint:
messages = channel_values.get("messages") messages = channel_values.get("messages")
if messages: if messages:
@@ -637,7 +605,7 @@ async def get_thread_history(thread_id: str, body: ThreadHistoryRequest, request
parent_checkpoint_id=parent_id, parent_checkpoint_id=parent_id,
metadata=user_meta, metadata=user_meta,
values=values, values=values,
created_at=coerce_iso(metadata.get("created_at", "")), created_at=str(metadata.get("created_at", "")),
next=next_tasks, next=next_tasks,
) )
) )
+28 -250
View File
@@ -4,26 +4,20 @@ import logging
import os import os
import stat import stat
from fastapi import APIRouter, Depends, File, HTTPException, Request, UploadFile from fastapi import APIRouter, File, HTTPException, Request, UploadFile
from pydantic import BaseModel, Field from pydantic import BaseModel
from app.gateway.authz import require_permission from app.gateway.authz import require_permission
from app.gateway.deps import get_config
from deerflow.config.app_config import AppConfig
from deerflow.config.paths import get_paths from deerflow.config.paths import get_paths
from deerflow.runtime.user_context import get_effective_user_id from deerflow.sandbox.sandbox_provider import get_sandbox_provider
from deerflow.sandbox.sandbox_provider import SandboxProvider, get_sandbox_provider
from deerflow.uploads.manager import ( from deerflow.uploads.manager import (
PathTraversalError, PathTraversalError,
UnsafeUploadPathError,
claim_unique_filename,
delete_file_safe, delete_file_safe,
enrich_file_listing, enrich_file_listing,
ensure_uploads_dir, ensure_uploads_dir,
get_uploads_dir, get_uploads_dir,
list_files_in_dir, list_files_in_dir,
normalize_filename, normalize_filename,
open_upload_file_no_symlink,
upload_artifact_url, upload_artifact_url,
upload_virtual_path, upload_virtual_path,
) )
@@ -33,51 +27,13 @@ logger = logging.getLogger(__name__)
router = APIRouter(prefix="/api/threads/{thread_id}/uploads", tags=["uploads"]) router = APIRouter(prefix="/api/threads/{thread_id}/uploads", tags=["uploads"])
UPLOAD_CHUNK_SIZE = 8192
DEFAULT_MAX_FILES = 10
DEFAULT_MAX_FILE_SIZE = 50 * 1024 * 1024
DEFAULT_MAX_TOTAL_SIZE = 100 * 1024 * 1024
class UploadedFileInfo(BaseModel):
"""Uploaded file metadata exposed by upload and list APIs."""
filename: str
size: int
path: str
virtual_path: str
artifact_url: str
extension: str | None = None
modified: float | None = None
original_filename: str | None = None
markdown_file: str | None = None
markdown_path: str | None = None
markdown_virtual_path: str | None = None
markdown_artifact_url: str | None = None
class UploadResponse(BaseModel): class UploadResponse(BaseModel):
"""Response model for file upload.""" """Response model for file upload."""
success: bool success: bool
files: list[UploadedFileInfo] files: list[dict[str, str]]
message: str message: str
skipped_files: list[str] = Field(default_factory=list)
class UploadListResponse(BaseModel):
"""Response model for uploaded file listing."""
files: list[UploadedFileInfo]
count: int
class UploadLimits(BaseModel):
"""Application-level upload limits exposed to clients."""
max_files: int
max_file_size: int
max_total_size: int
def _make_file_sandbox_writable(file_path: os.PathLike[str] | str) -> None: def _make_file_sandbox_writable(file_path: os.PathLike[str] | str) -> None:
@@ -93,212 +49,73 @@ def _make_file_sandbox_writable(file_path: os.PathLike[str] | str) -> None:
logger.warning("Skipping sandbox chmod for symlinked upload path: %s", file_path) logger.warning("Skipping sandbox chmod for symlinked upload path: %s", file_path)
return return
writable_mode = stat.S_IMODE(file_stat.st_mode) | stat.S_IWUSR | stat.S_IWGRP | stat.S_IWOTH | stat.S_IRGRP | stat.S_IROTH writable_mode = stat.S_IMODE(file_stat.st_mode) | stat.S_IWUSR | stat.S_IWGRP | stat.S_IWOTH
chmod_kwargs = {"follow_symlinks": False} if os.chmod in os.supports_follow_symlinks else {} chmod_kwargs = {"follow_symlinks": False} if os.chmod in os.supports_follow_symlinks else {}
os.chmod(file_path, writable_mode, **chmod_kwargs) os.chmod(file_path, writable_mode, **chmod_kwargs)
def _make_file_sandbox_readable(file_path: os.PathLike[str] | str) -> None:
"""Ensure uploaded files are readable by the sandbox process.
For Docker sandboxes (AIO), the gateway writes files as root with 0o600
permissions, then bind-mounts the host directory into the container. The
sandbox process inside the container runs as a non-root user and cannot
read those files without group/other read bits. This function adds
``S_IRGRP | S_IROTH`` so the sandbox can read the uploaded content.
"""
file_stat = os.lstat(file_path)
if stat.S_ISLNK(file_stat.st_mode):
logger.warning("Skipping sandbox chmod for symlinked upload path: %s", file_path)
return
readable_mode = stat.S_IMODE(file_stat.st_mode) | stat.S_IRGRP | stat.S_IROTH
chmod_kwargs = {"follow_symlinks": False} if os.chmod in os.supports_follow_symlinks else {}
os.chmod(file_path, readable_mode, **chmod_kwargs)
def _uses_thread_data_mounts(sandbox_provider: SandboxProvider) -> bool:
return bool(getattr(sandbox_provider, "uses_thread_data_mounts", False))
def _get_uploads_config_value(app_config: AppConfig, key: str, default: object) -> object:
"""Read a value from the uploads config, supporting dict and attribute access."""
uploads_cfg = getattr(app_config, "uploads", None)
if isinstance(uploads_cfg, dict):
return uploads_cfg.get(key, default)
return getattr(uploads_cfg, key, default)
def _get_upload_limit(app_config: AppConfig, key: str, default: int, *, legacy_key: str | None = None) -> int:
try:
value = _get_uploads_config_value(app_config, key, None)
if value is None and legacy_key is not None:
value = _get_uploads_config_value(app_config, legacy_key, None)
if value is None:
value = default
limit = int(value)
if limit <= 0:
raise ValueError
return limit
except Exception:
logger.warning("Invalid uploads.%s value; falling back to %d", key, default)
return default
def _get_upload_limits(app_config: AppConfig) -> UploadLimits:
return UploadLimits(
max_files=_get_upload_limit(app_config, "max_files", DEFAULT_MAX_FILES, legacy_key="max_file_count"),
max_file_size=_get_upload_limit(app_config, "max_file_size", DEFAULT_MAX_FILE_SIZE, legacy_key="max_single_file_size"),
max_total_size=_get_upload_limit(app_config, "max_total_size", DEFAULT_MAX_TOTAL_SIZE),
)
def _cleanup_uploaded_paths(paths: list[os.PathLike[str] | str]) -> None:
for path in reversed(paths):
try:
os.unlink(path)
except FileNotFoundError:
pass
except Exception:
logger.warning("Failed to clean up upload path after rejected request: %s", path, exc_info=True)
async def _write_upload_file_with_limits(
file: UploadFile,
*,
uploads_dir: os.PathLike[str] | str,
display_filename: str,
max_single_file_size: int,
max_total_size: int,
total_size: int,
) -> tuple[os.PathLike[str] | str, int, int]:
file_size = 0
file_path, fh = open_upload_file_no_symlink(uploads_dir, display_filename)
try:
while chunk := await file.read(UPLOAD_CHUNK_SIZE):
file_size += len(chunk)
total_size += len(chunk)
if file_size > max_single_file_size:
raise HTTPException(status_code=413, detail=f"File too large: {display_filename}")
if total_size > max_total_size:
raise HTTPException(status_code=413, detail="Total upload size too large")
fh.write(chunk)
except Exception:
fh.close()
try:
os.unlink(file_path)
except FileNotFoundError:
pass
raise
else:
fh.close()
return file_path, file_size, total_size
def _auto_convert_documents_enabled(app_config: AppConfig) -> bool:
"""Return whether automatic host-side document conversion is enabled.
The secure default is disabled unless an operator explicitly opts in via
uploads.auto_convert_documents in config.yaml.
"""
try:
raw = _get_uploads_config_value(app_config, "auto_convert_documents", False)
if isinstance(raw, str):
return raw.strip().lower() in {"1", "true", "yes", "on"}
return bool(raw)
except Exception:
return False
@router.post("", response_model=UploadResponse) @router.post("", response_model=UploadResponse)
@require_permission("threads", "write", owner_check=True, require_existing=False) @require_permission("threads", "write", owner_check=True, require_existing=True)
async def upload_files( async def upload_files(
thread_id: str, thread_id: str,
request: Request, request: Request,
files: list[UploadFile] = File(...), files: list[UploadFile] = File(...),
config: AppConfig = Depends(get_config),
) -> UploadResponse: ) -> UploadResponse:
"""Upload multiple files to a thread's uploads directory.""" """Upload multiple files to a thread's uploads directory."""
if not files: if not files:
raise HTTPException(status_code=400, detail="No files provided") raise HTTPException(status_code=400, detail="No files provided")
limits = _get_upload_limits(config)
if len(files) > limits.max_files:
raise HTTPException(status_code=413, detail=f"Too many files: maximum is {limits.max_files}")
try: try:
uploads_dir = ensure_uploads_dir(thread_id) uploads_dir = ensure_uploads_dir(thread_id)
except ValueError as e: except ValueError as e:
raise HTTPException(status_code=400, detail=str(e)) raise HTTPException(status_code=400, detail=str(e))
sandbox_uploads = get_paths().sandbox_uploads_dir(thread_id, user_id=get_effective_user_id()) sandbox_uploads = get_paths().sandbox_uploads_dir(thread_id)
uploaded_files = [] uploaded_files = []
written_paths = []
sandbox_sync_targets = []
skipped_files = []
total_size = 0
# Track filenames within this request so duplicate form parts do not
# silently truncate each other. Existing uploads keep the historical
# overwrite behavior for a single replacement upload.
seen_filenames: set[str] = set()
sandbox_provider = get_sandbox_provider() sandbox_provider = get_sandbox_provider()
sync_to_sandbox = not _uses_thread_data_mounts(sandbox_provider) sandbox_id = sandbox_provider.acquire(thread_id)
sandbox = None sandbox = sandbox_provider.get(sandbox_id)
if sync_to_sandbox:
sandbox_id = sandbox_provider.acquire(thread_id)
sandbox = sandbox_provider.get(sandbox_id)
if sandbox is None:
raise HTTPException(status_code=500, detail="Failed to acquire sandbox")
auto_convert_documents = _auto_convert_documents_enabled(config)
for file in files: for file in files:
if not file.filename: if not file.filename:
continue continue
try: try:
original_filename = normalize_filename(file.filename) safe_filename = normalize_filename(file.filename)
safe_filename = claim_unique_filename(original_filename, seen_filenames)
except ValueError: except ValueError:
logger.warning(f"Skipping file with unsafe filename: {file.filename!r}") logger.warning(f"Skipping file with unsafe filename: {file.filename!r}")
continue continue
try: try:
file_path, file_size, total_size = await _write_upload_file_with_limits( content = await file.read()
file, file_path = uploads_dir / safe_filename
uploads_dir=uploads_dir, file_path.write_bytes(content)
display_filename=safe_filename,
max_single_file_size=limits.max_file_size,
max_total_size=limits.max_total_size,
total_size=total_size,
)
written_paths.append(file_path)
virtual_path = upload_virtual_path(safe_filename) virtual_path = upload_virtual_path(safe_filename)
if sync_to_sandbox: if sandbox_id != "local":
sandbox_sync_targets.append((file_path, virtual_path)) _make_file_sandbox_writable(file_path)
sandbox.update_file(virtual_path, content)
file_info = { file_info = {
"filename": safe_filename, "filename": safe_filename,
"size": file_size, "size": str(len(content)),
"path": str(sandbox_uploads / safe_filename), "path": str(sandbox_uploads / safe_filename),
"virtual_path": virtual_path, "virtual_path": virtual_path,
"artifact_url": upload_artifact_url(thread_id, safe_filename), "artifact_url": upload_artifact_url(thread_id, safe_filename),
} }
if safe_filename != original_filename:
file_info["original_filename"] = original_filename
logger.info(f"Saved file: {safe_filename} ({file_size} bytes) to {file_info['path']}") logger.info(f"Saved file: {safe_filename} ({len(content)} bytes) to {file_info['path']}")
file_ext = file_path.suffix.lower() file_ext = file_path.suffix.lower()
if auto_convert_documents and file_ext in CONVERTIBLE_EXTENSIONS: if file_ext in CONVERTIBLE_EXTENSIONS:
md_path = await convert_file_to_markdown(file_path) md_path = await convert_file_to_markdown(file_path)
if md_path: if md_path:
written_paths.append(md_path)
md_virtual_path = upload_virtual_path(md_path.name) md_virtual_path = upload_virtual_path(md_path.name)
if sync_to_sandbox: if sandbox_id != "local":
sandbox_sync_targets.append((md_path, md_virtual_path)) _make_file_sandbox_writable(md_path)
sandbox.update_file(md_virtual_path, md_path.read_bytes())
file_info["markdown_file"] = md_path.name file_info["markdown_file"] = md_path.name
file_info["markdown_path"] = str(sandbox_uploads / md_path.name) file_info["markdown_path"] = str(sandbox_uploads / md_path.name)
@@ -307,59 +124,20 @@ async def upload_files(
uploaded_files.append(file_info) uploaded_files.append(file_info)
except HTTPException as e:
_cleanup_uploaded_paths(written_paths)
raise e
except UnsafeUploadPathError as e:
logger.warning("Skipping upload with unsafe destination %s: %s", file.filename, e)
skipped_files.append(safe_filename)
continue
except Exception as e: except Exception as e:
logger.error(f"Failed to upload {file.filename}: {e}") logger.error(f"Failed to upload {file.filename}: {e}")
_cleanup_uploaded_paths(written_paths)
raise HTTPException(status_code=500, detail=f"Failed to upload {file.filename}: {str(e)}") raise HTTPException(status_code=500, detail=f"Failed to upload {file.filename}: {str(e)}")
# Uploaded files are created with 0o600 permissions (owner read/write only).
# In Docker sandbox deployments the gateway writes as root but the sandbox
# process runs as a non-root user (typically UID 1000). Without group/other
# read bits the sandbox cannot access the files — whether the uploads
# directory is bind-mounted into the container or synced via
# sandbox.update_file. Always add group/other read bits so every sandbox
# configuration can read the uploaded content.
for file_path in written_paths:
_make_file_sandbox_readable(file_path)
if sync_to_sandbox:
for file_path, virtual_path in sandbox_sync_targets:
_make_file_sandbox_writable(file_path)
sandbox.update_file(virtual_path, file_path.read_bytes())
message = f"Successfully uploaded {len(uploaded_files)} file(s)"
if skipped_files:
message += f"; skipped {len(skipped_files)} unsafe file(s)"
return UploadResponse( return UploadResponse(
success=not skipped_files, success=True,
files=uploaded_files, files=uploaded_files,
message=message, message=f"Successfully uploaded {len(uploaded_files)} file(s)",
skipped_files=skipped_files,
) )
@router.get("/limits", response_model=UploadLimits) @router.get("/list", response_model=dict)
@require_permission("threads", "read", owner_check=True) @require_permission("threads", "read", owner_check=True)
async def get_upload_limits( async def list_uploaded_files(thread_id: str, request: Request) -> dict:
thread_id: str,
request: Request,
config: AppConfig = Depends(get_config),
) -> UploadLimits:
"""Return upload limits used by the gateway for this thread."""
return _get_upload_limits(config)
@router.get("/list", response_model=UploadListResponse)
@require_permission("threads", "read", owner_check=True)
async def list_uploaded_files(thread_id: str, request: Request) -> UploadListResponse:
"""List all files in a thread's uploads directory.""" """List all files in a thread's uploads directory."""
try: try:
uploads_dir = get_uploads_dir(thread_id) uploads_dir = get_uploads_dir(thread_id)
@@ -369,11 +147,11 @@ async def list_uploaded_files(thread_id: str, request: Request) -> UploadListRes
enrich_file_listing(result, thread_id) enrich_file_listing(result, thread_id)
# Gateway additionally includes the sandbox-relative path. # Gateway additionally includes the sandbox-relative path.
sandbox_uploads = get_paths().sandbox_uploads_dir(thread_id, user_id=get_effective_user_id()) sandbox_uploads = get_paths().sandbox_uploads_dir(thread_id)
for f in result["files"]: for f in result["files"]:
f["path"] = str(sandbox_uploads / f["filename"]) f["path"] = str(sandbox_uploads / f["filename"])
return UploadListResponse(**result) return result
@router.delete("/{filename}") @router.delete("/{filename}")
+63 -203
View File
@@ -8,20 +8,17 @@ frames, and consuming stream bridge events. Router modules
from __future__ import annotations from __future__ import annotations
import asyncio import asyncio
import dataclasses
import json import json
import logging import logging
import re import re
from collections.abc import Mapping
from typing import Any from typing import Any
from fastapi import HTTPException, Request from fastapi import HTTPException, Request
from langchain_core.messages import BaseMessage from langchain_core.messages import HumanMessage
from langchain_core.messages.utils import convert_to_messages
from app.gateway.deps import get_run_context, get_run_manager, get_stream_bridge from app.gateway.deps import get_run_context, get_run_manager, get_run_store, get_stream_bridge
from app.gateway.internal_auth import INTERNAL_SYSTEM_ROLE
from app.gateway.utils import sanitize_log_param from app.gateway.utils import sanitize_log_param
from deerflow.config.app_config import get_app_config
from deerflow.runtime import ( from deerflow.runtime import (
END_SENTINEL, END_SENTINEL,
HEARTBEAT_SENTINEL, HEARTBEAT_SENTINEL,
@@ -34,7 +31,6 @@ from deerflow.runtime import (
UnsupportedStrategyError, UnsupportedStrategyError,
run_agent, run_agent,
) )
from deerflow.runtime.runs.naming import resolve_root_run_name
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
@@ -78,35 +74,21 @@ def normalize_stream_modes(raw: list[str] | str | None) -> list[str]:
def normalize_input(raw_input: dict[str, Any] | None) -> dict[str, Any]: def normalize_input(raw_input: dict[str, Any] | None) -> dict[str, Any]:
"""Convert LangGraph Platform input format to LangChain state dict. """Convert LangGraph Platform input format to LangChain state dict."""
Delegates dictmessage coercion to ``langchain_core.messages.utils.convert_to_messages``
so that ``additional_kwargs`` (e.g. uploaded-file metadata gh #3132), ``id``,
``name``, and non-human roles (ai/system/tool) survive unchanged. An earlier
hand-rolled version only forwarded ``content`` and collapsed every role to
``HumanMessage``, which silently stripped frontend-supplied attachments.
Malformed message dicts (missing ``role``/``type``/``content``, unsupported
role, etc.) raise ``HTTPException(400)`` with the offending index, instead
of bubbling up as a 500. The gateway is a system boundary, so per-entry
validation errors are the right shape for clients to retry against.
"""
if raw_input is None: if raw_input is None:
return {} return {}
messages = raw_input.get("messages") messages = raw_input.get("messages")
if messages and isinstance(messages, list): if messages and isinstance(messages, list):
converted: list[Any] = [] converted = []
for index, msg in enumerate(messages): for msg in messages:
if isinstance(msg, BaseMessage): if isinstance(msg, dict):
converted.append(msg) role = msg.get("role", msg.get("type", "user"))
elif isinstance(msg, dict): content = msg.get("content", "")
try: if role in ("user", "human"):
converted.extend(convert_to_messages([msg])) converted.append(HumanMessage(content=content))
except (ValueError, TypeError, NotImplementedError) as exc: else:
raise HTTPException( # TODO: handle other message types (system, ai, tool)
status_code=400, converted.append(HumanMessage(content=content))
detail=f"Invalid message at input.messages[{index}]: {exc}",
) from exc
else: else:
converted.append(msg) converted.append(msg)
return {**raw_input, "messages": converted} return {**raw_input, "messages": converted}
@@ -116,82 +98,13 @@ def normalize_input(raw_input: dict[str, Any] | None) -> dict[str, Any]:
_DEFAULT_ASSISTANT_ID = "lead_agent" _DEFAULT_ASSISTANT_ID = "lead_agent"
# Whitelist of run-context keys that the langgraph-compat layer forwards from
# ``body.context`` into the run config. ``config["context"]`` exists in
# LangGraph >=0.6, but these values must be written to both ``configurable``
# (for legacy ``_get_runtime_config`` consumers) and ``context`` because
# LangGraph >=1.1.9 no longer makes ``ToolRuntime.context`` fall back to
# ``configurable`` for consumers like ``setup_agent``.
_CONTEXT_CONFIGURABLE_KEYS: frozenset[str] = frozenset(
{
"model_name",
"mode",
"thinking_enabled",
"reasoning_effort",
"is_plan_mode",
"subagent_enabled",
"max_concurrent_subagents",
"agent_name",
"is_bootstrap",
}
)
def merge_run_context_overrides(config: dict[str, Any], context: Mapping[str, Any] | None) -> None:
"""Merge whitelisted keys from ``body.context`` into both ``config['configurable']``
and ``config['context']`` so they are visible to legacy configurable readers and
to LangGraph ``ToolRuntime.context`` consumers (e.g. the ``setup_agent`` tool
see issue #2677).
``user_id`` is intentionally propagated into ``config['context']`` in addition to
the whitelisted keys, so non-web callers (e.g. IM channels) that supply identity in
``body.context`` keep it on ``ToolRuntime.context``. It is merged with
``setdefault`` so a server-authenticated id stamped by
:func:`inject_authenticated_user_context` always wins over the client-supplied one.
"""
if not context:
return
configurable = config.setdefault("configurable", {})
runtime_context = config.setdefault("context", {})
for key in _CONTEXT_CONFIGURABLE_KEYS:
if key in context:
if isinstance(configurable, dict):
configurable.setdefault(key, context[key])
if isinstance(runtime_context, dict):
runtime_context.setdefault(key, context[key])
if "user_id" in context and isinstance(runtime_context, dict):
runtime_context.setdefault("user_id", context["user_id"])
def inject_authenticated_user_context(config: dict[str, Any], request: Request) -> None:
"""Stamp the authenticated user into the run context for background tools.
Tool execution may happen after the request handler has returned, so tools
that persist user-scoped files should not rely only on ambient ContextVars.
The value comes from server-side auth state, never from client context.
"""
user = getattr(request.state, "user", None)
user_id = getattr(user, "id", None)
if user_id is None:
return
if getattr(user, "system_role", None) == INTERNAL_SYSTEM_ROLE:
return
runtime_context = config.setdefault("context", {})
if isinstance(runtime_context, dict):
runtime_context["user_id"] = str(user_id)
def resolve_agent_factory(assistant_id: str | None): def resolve_agent_factory(assistant_id: str | None):
"""Resolve the agent factory callable from config. """Resolve the agent factory callable from config.
Custom agents are implemented as ``lead_agent`` + an ``agent_name`` Custom agents are implemented as ``lead_agent`` + an ``agent_name``
injected into ``configurable`` or ``context`` see injected into ``configurable`` see :func:`build_run_config`. All
:func:`build_run_config`. All ``assistant_id`` values therefore map to the ``assistant_id`` values therefore map to the same factory; the routing
same factory; the routing happens inside ``make_lead_agent`` when it reads happens inside ``make_lead_agent`` when it reads ``cfg["agent_name"]``.
``cfg["agent_name"]``.
""" """
from deerflow.agents.lead_agent.agent import make_lead_agent from deerflow.agents.lead_agent.agent import make_lead_agent
@@ -208,12 +121,10 @@ def build_run_config(
"""Build a RunnableConfig dict for the agent. """Build a RunnableConfig dict for the agent.
When *assistant_id* refers to a custom agent (anything other than When *assistant_id* refers to a custom agent (anything other than
``"lead_agent"`` / ``None``), the name is forwarded as ``agent_name`` in ``"lead_agent"`` / ``None``), the name is forwarded as
whichever runtime options container is active: ``context`` for ``configurable["agent_name"]``. ``make_lead_agent`` reads this key to
LangGraph >= 0.6.0 requests, otherwise ``configurable``. load the matching ``agents/<name>/SOUL.md`` and per-agent config
``make_lead_agent`` reads this key to load the matching without it the agent silently runs as the default lead agent.
``agents/<name>/SOUL.md`` and per-agent config without it the agent
silently runs as the default lead agent.
This mirrors the channel manager's ``_resolve_run_params`` logic so that This mirrors the channel manager's ``_resolve_run_params`` logic so that
the LangGraph Platform-compatible HTTP API and the IM channel path behave the LangGraph Platform-compatible HTTP API and the IM channel path behave
@@ -232,14 +143,7 @@ def build_run_config(
thread_id, thread_id,
list(request_config.get("configurable", {}).keys()), list(request_config.get("configurable", {}).keys()),
) )
context_value = request_config["context"] config["context"] = request_config["context"]
if context_value is None:
context = {}
elif isinstance(context_value, Mapping):
context = dict(context_value)
else:
raise ValueError("request config 'context' must be a mapping or null.")
config["context"] = context
else: else:
configurable = {"thread_id": thread_id} configurable = {"thread_id": thread_id}
configurable.update(request_config.get("configurable", {})) configurable.update(request_config.get("configurable", {}))
@@ -251,20 +155,13 @@ def build_run_config(
config["configurable"] = {"thread_id": thread_id} config["configurable"] = {"thread_id": thread_id}
# Inject custom agent name when the caller specified a non-default assistant. # Inject custom agent name when the caller specified a non-default assistant.
# Honour an explicit agent_name in the active runtime options container. # Honour an explicit configurable["agent_name"] in the request if already set.
if assistant_id and assistant_id != _DEFAULT_ASSISTANT_ID: if assistant_id and assistant_id != _DEFAULT_ASSISTANT_ID and "configurable" in config:
normalized = assistant_id.strip().lower().replace("_", "-") if "agent_name" not in config["configurable"]:
if not normalized or not re.fullmatch(r"[a-z0-9-]+", normalized): normalized = assistant_id.strip().lower().replace("_", "-")
raise ValueError(f"Invalid assistant_id {assistant_id!r}: must contain only letters, digits, and hyphens after normalization.") if not normalized or not re.fullmatch(r"[a-z0-9-]+", normalized):
if "configurable" in config: raise ValueError(f"Invalid assistant_id {assistant_id!r}: must contain only letters, digits, and hyphens after normalization.")
target = config["configurable"] config["configurable"]["agent_name"] = normalized
elif "context" in config:
target = config["context"]
else:
target = config.setdefault("configurable", {})
if target is not None and "agent_name" not in target:
target["agent_name"] = normalized
config.setdefault("run_name", resolve_root_run_name(config, normalized))
if metadata: if metadata:
config.setdefault("metadata", {}).update(metadata) config.setdefault("metadata", {}).update(metadata)
return config return config
@@ -298,22 +195,20 @@ async def start_run(
disconnect = DisconnectMode.cancel if body.on_disconnect == "cancel" else DisconnectMode.continue_ disconnect = DisconnectMode.cancel if body.on_disconnect == "cancel" else DisconnectMode.continue_
body_context = getattr(body, "context", None) or {} # Resolve follow_up_to_run_id: explicit from request, or auto-detect from latest successful run
model_name = body_context.get("model_name") 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
# Coerce non-string model_name values to str before truncation. # Enrich base context with per-run field
if model_name is not None and not isinstance(model_name, str): if follow_up_to_run_id:
model_name = str(model_name) run_ctx = dataclasses.replace(run_ctx, follow_up_to_run_id=follow_up_to_run_id)
# Validate model against the allowlist when a model_name is provided.
if model_name:
app_config = get_app_config()
resolved = app_config.get_model_config(model_name)
if resolved is None:
raise HTTPException(
status_code=400,
detail=f"Model {model_name!r} is not in the configured model allowlist",
)
try: try:
record = await run_mgr.create_or_reject( record = await run_mgr.create_or_reject(
@@ -323,7 +218,7 @@ async def start_run(
metadata=body.metadata or {}, metadata=body.metadata or {},
kwargs={"input": body.input, "config": body.config}, kwargs={"input": body.input, "config": body.config},
multitask_strategy=body.multitask_strategy, multitask_strategy=body.multitask_strategy,
model_name=model_name, follow_up_to_run_id=follow_up_to_run_id,
) )
except ConflictError as exc: except ConflictError as exc:
raise HTTPException(status_code=409, detail=str(exc)) from exc raise HTTPException(status_code=409, detail=str(exc)) from exc
@@ -334,15 +229,15 @@ async def start_run(
# even for threads that were never explicitly created via POST /threads # even for threads that were never explicitly created via POST /threads
# (e.g. stateless runs). # (e.g. stateless runs).
try: try:
existing = await run_ctx.thread_store.get(thread_id) existing = await run_ctx.thread_meta_repo.get(thread_id)
if existing is None: if existing is None:
await run_ctx.thread_store.create( await run_ctx.thread_meta_repo.create(
thread_id, thread_id,
assistant_id=body.assistant_id, assistant_id=body.assistant_id,
metadata=body.metadata, metadata=body.metadata,
) )
else: else:
await run_ctx.thread_store.update_status(thread_id, "running") await run_ctx.thread_meta_repo.update_status(thread_id, "running")
except Exception: except Exception:
logger.warning("Failed to upsert thread_meta for %s (non-fatal)", sanitize_log_param(thread_id)) logger.warning("Failed to upsert thread_meta for %s (non-fatal)", sanitize_log_param(thread_id))
@@ -350,12 +245,25 @@ async def start_run(
graph_input = normalize_input(body.input) graph_input = normalize_input(body.input)
config = build_run_config(thread_id, body.config, body.metadata, assistant_id=body.assistant_id) config = build_run_config(thread_id, body.config, body.metadata, assistant_id=body.assistant_id)
# Merge DeerFlow-specific context overrides into both ``configurable`` and ``context``. # Merge DeerFlow-specific context overrides into configurable.
# The ``context`` field is a custom extension for the langgraph-compat layer # The ``context`` field is a custom extension for the langgraph-compat layer
# that carries agent configuration (model_name, thinking_enabled, etc.). # that carries agent configuration (model_name, thinking_enabled, etc.).
# Only agent-relevant keys are forwarded; unknown keys (e.g. thread_id) are ignored. # Only agent-relevant keys are forwarded; unknown keys (e.g. thread_id) are ignored.
merge_run_context_overrides(config, getattr(body, "context", None)) context = getattr(body, "context", None)
inject_authenticated_user_context(config, request) if context:
_CONTEXT_CONFIGURABLE_KEYS = {
"model_name",
"mode",
"thinking_enabled",
"reasoning_effort",
"is_plan_mode",
"subagent_enabled",
"max_concurrent_subagents",
}
configurable = config.setdefault("configurable", {})
for key in _CONTEXT_CONFIGURABLE_KEYS:
if key in context:
configurable.setdefault(key, context[key])
stream_modes = normalize_stream_modes(body.stream_mode) stream_modes = normalize_stream_modes(body.stream_mode)
@@ -377,7 +285,7 @@ async def start_run(
record.task = task record.task = task
# Title sync is handled by worker.py's finally block which reads the # Title sync is handled by worker.py's finally block which reads the
# title from the checkpoint and calls thread_store.update_display_name # title from the checkpoint and calls thread_meta_repo.update_display_name
# after the run completes. # after the run completes.
return record return record
@@ -415,51 +323,3 @@ async def sse_consumer(
if record.status in (RunStatus.pending, RunStatus.running): if record.status in (RunStatus.pending, RunStatus.running):
if record.on_disconnect == DisconnectMode.cancel: if record.on_disconnect == DisconnectMode.cancel:
await run_mgr.cancel(record.run_id) await run_mgr.cancel(record.run_id)
async def wait_for_run_completion(
bridge: StreamBridge,
record: RunRecord,
request: Request,
run_mgr: RunManager,
) -> bool:
"""Block until the run publishes ``END_SENTINEL``, honouring on_disconnect.
The non-streaming ``/wait`` endpoints used to ``await record.task``
directly with no disconnect handling. When the client (or an
intermediate HTTP proxy) timed out during a long tool call such as
``pip install``, the handler would swallow ``CancelledError`` and
serialize whatever checkpoint happened to exist masking a half-finished
run as a normal completion (issue #3265).
This helper consumes the same bridge that ``sse_consumer`` does so the
wait path shares its disconnect semantics: each wake-up polls
``request.is_disconnected()``; on a real disconnect it cancels the
background run when ``record.on_disconnect`` is ``cancel``. The bridge's
heartbeat sentinels guarantee at least one wake-up per
``heartbeat_interval`` even when the agent emits no events for a while.
Returns:
``True`` when ``END_SENTINEL`` was observed (run reached a terminal
state), ``False`` when the loop exited because the client
disconnected. Callers must skip checkpoint serialization on
``False`` so a partial checkpoint is not returned as a normal
response.
"""
completed = False
try:
async for entry in bridge.subscribe(record.run_id):
# END_SENTINEL means the run reached a terminal state; honour it
# even if the client just disconnected so the caller still serializes
# the real final checkpoint.
if entry is END_SENTINEL:
completed = True
return True
if await request.is_disconnected():
break
# Heartbeats and regular events: keep waiting for END_SENTINEL.
return completed
finally:
if not completed and record.status in (RunStatus.pending, RunStatus.running):
if record.on_disconnect == DisconnectMode.cancel:
await run_mgr.cancel(record.run_id)
+13 -90
View File
@@ -19,72 +19,24 @@ import asyncio
import logging import logging
from dotenv import load_dotenv from dotenv import load_dotenv
from langchain_core.messages import HumanMessage
try: from deerflow.agents import make_lead_agent
from prompt_toolkit import PromptSession
from prompt_toolkit.history import InMemoryHistory
_HAS_PROMPT_TOOLKIT = True
except ImportError:
_HAS_PROMPT_TOOLKIT = False
load_dotenv() load_dotenv()
_LOG_FMT = "%(asctime)s - %(name)s - %(levelname)s - %(message)s" logging.basicConfig(
_LOG_DATEFMT = "%Y-%m-%d %H:%M:%S" level=logging.INFO,
format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
datefmt="%Y-%m-%d %H:%M:%S",
def _setup_logging(log_level: int = logging.INFO) -> None: )
"""Route logs to ``debug.log`` using *log_level* for the initial root/file setup.
This configures the root logger and the ``debug.log`` file handler so logs do
not print on the interactive console. It is idempotent: any pre-existing
handlers on the root logger (e.g. installed by ``logging.basicConfig`` in
transitively imported modules) are removed so the debug session output only
lands in ``debug.log``.
Note: later config-driven logging adjustments may change named logger
verbosity without raising the root logger or file-handler thresholds set
here, so the eventual contents of ``debug.log`` may not be filtered solely by
this function's ``log_level`` argument.
"""
root = logging.root
for h in list(root.handlers):
root.removeHandler(h)
h.close()
root.setLevel(log_level)
file_handler = logging.FileHandler("debug.log", mode="a", encoding="utf-8")
file_handler.setLevel(log_level)
file_handler.setFormatter(logging.Formatter(_LOG_FMT, datefmt=_LOG_DATEFMT))
root.addHandler(file_handler)
async def main(): async def main():
# Install file logging first so warnings emitted while loading config do not
# leak onto the interactive terminal via Python's lastResort handler.
_setup_logging()
from deerflow.config import get_app_config
from deerflow.config.app_config import apply_logging_level
app_config = get_app_config()
apply_logging_level(app_config.log_level)
# Delay the rest of the deerflow imports until *after* logging is installed
# so that any import-time side effects (e.g. deerflow.agents starts a
# background skill-loader thread on import) emit logs to debug.log instead
# of leaking onto the interactive terminal via Python's lastResort handler.
from langchain_core.messages import HumanMessage
from langgraph.runtime import Runtime
from deerflow.agents import make_lead_agent
from deerflow.config.paths import get_paths
from deerflow.mcp import initialize_mcp_tools
from deerflow.runtime.user_context import get_effective_user_id
# Initialize MCP tools at startup # Initialize MCP tools at startup
try: try:
from deerflow.mcp import initialize_mcp_tools
await initialize_mcp_tools() await initialize_mcp_tools()
except Exception as e: except Exception as e:
print(f"Warning: Failed to initialize MCP tools: {e}") print(f"Warning: Failed to initialize MCP tools: {e}")
@@ -100,29 +52,16 @@ async def main():
} }
} }
runtime = Runtime(context={"thread_id": config["configurable"]["thread_id"]})
config["configurable"]["__pregel_runtime"] = runtime
agent = make_lead_agent(config) agent = make_lead_agent(config)
session = PromptSession(history=InMemoryHistory()) if _HAS_PROMPT_TOOLKIT else None
print("=" * 50) print("=" * 50)
print("Lead Agent Debug Mode") print("Lead Agent Debug Mode")
print("Type 'quit' or 'exit' to stop") print("Type 'quit' or 'exit' to stop")
print(f"Logs: debug.log (log_level={app_config.log_level})")
if not _HAS_PROMPT_TOOLKIT:
print("Tip: `uv sync --group dev` to enable arrow-key & history support")
print("=" * 50) print("=" * 50)
seen_artifacts: set[str] = set()
while True: while True:
try: try:
if session: user_input = input("\nYou: ").strip()
user_input = (await session.prompt_async("\nYou: ")).strip()
else:
user_input = input("\nYou: ").strip()
if not user_input: if not user_input:
continue continue
if user_input.lower() in ("quit", "exit"): if user_input.lower() in ("quit", "exit"):
@@ -131,31 +70,15 @@ async def main():
# Invoke the agent # Invoke the agent
state = {"messages": [HumanMessage(content=user_input)]} state = {"messages": [HumanMessage(content=user_input)]}
result = await agent.ainvoke(state, config=config) result = await agent.ainvoke(state, config=config, context={"thread_id": "debug-thread-001"})
# Print the response # Print the response
if result.get("messages"): if result.get("messages"):
last_message = result["messages"][-1] last_message = result["messages"][-1]
print(f"\nAgent: {last_message.content}") print(f"\nAgent: {last_message.content}")
# Show files presented to the user this turn (new artifacts only) except KeyboardInterrupt:
artifacts = result.get("artifacts") or [] print("\nInterrupted. Goodbye!")
new_artifacts = [p for p in artifacts if p not in seen_artifacts]
if new_artifacts:
thread_id = config["configurable"]["thread_id"]
user_id = get_effective_user_id()
paths = get_paths()
print("\n[Presented files]")
for virtual in new_artifacts:
try:
physical = paths.resolve_virtual_path(thread_id, virtual, user_id=user_id)
print(f" - {virtual}\n{physical}")
except ValueError as exc:
print(f" - {virtual} (failed to resolve physical path: {exc})")
seen_artifacts.update(new_artifacts)
except (KeyboardInterrupt, EOFError):
print("\nGoodbye!")
break break
except Exception as e: except Exception as e:
print(f"\nError: {e}") print(f"\nError: {e}")
+42 -52
View File
@@ -6,16 +6,16 @@ This document provides a complete reference for the DeerFlow backend APIs.
DeerFlow backend exposes two sets of APIs: DeerFlow backend exposes two sets of APIs:
1. **LangGraph-compatible API** - Agent interactions, threads, and streaming (`/api/langgraph/*`) 1. **LangGraph API** - Agent interactions, threads, and streaming (`/api/langgraph/*`)
2. **Gateway API** - Models, MCP, skills, uploads, and artifacts (`/api/*`) 2. **Gateway API** - Models, MCP, skills, uploads, and artifacts (`/api/*`)
All APIs are accessed through the Nginx reverse proxy at port 2026. All APIs are accessed through the Nginx reverse proxy at port 2026.
## LangGraph-compatible API ## LangGraph API
Base URL: `/api/langgraph` Base URL: `/api/langgraph`
The public LangGraph-compatible API follows LangGraph SDK conventions. In the unified nginx deployment, Gateway owns `/api/langgraph/*` and translates those paths to its native `/api/*` run, thread, and streaming routers. The LangGraph API is provided by the LangGraph server and follows the LangGraph SDK conventions.
### Threads ### Threads
@@ -104,11 +104,17 @@ Content-Type: application/json
**Recursion Limit:** **Recursion Limit:**
`config.recursion_limit` caps the number of graph steps LangGraph will execute `config.recursion_limit` caps the number of graph steps LangGraph will execute
in a single run. The unified Gateway path defaults to `100` in in a single run. The `/api/langgraph/*` endpoints go straight to the LangGraph
`build_run_config` (see `backend/app/gateway/services.py`), which is a safer server and therefore inherit LangGraph's native default of **25**, which is
starting point for plan-mode or subagent-heavy runs. Clients can still set too low for plan-mode or subagent-heavy runs — the agent typically errors out
`recursion_limit` explicitly in the request body; increase it if you run deeply with `GraphRecursionError` after the first round of subagent results comes
nested subagent graphs. 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:** **Configurable Options:**
- `model_name` (string): Override the default model - `model_name` (string): Override the default model
@@ -241,6 +247,13 @@ GET /api/mcp/config
"GITHUB_TOKEN": "***" "GITHUB_TOKEN": "***"
}, },
"description": "GitHub operations" "description": "GitHub operations"
},
"filesystem": {
"enabled": false,
"type": "stdio",
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-filesystem"],
"description": "File system access"
} }
} }
} }
@@ -528,28 +541,14 @@ All APIs return errors in a consistent format:
## Authentication ## Authentication
DeerFlow enforces authentication for all non-public HTTP routes. Public routes are limited to health/docs metadata and these public auth endpoints: Currently, DeerFlow does not implement authentication. All APIs are accessible without credentials.
- `POST /api/v1/auth/initialize` creates the first admin account when no admin exists. Note: This is about DeerFlow API authentication. MCP outbound connections can still use OAuth for configured HTTP/SSE MCP servers.
- `POST /api/v1/auth/login/local` logs in with email/password and sets an HttpOnly `access_token` cookie.
- `POST /api/v1/auth/register` creates a regular `user` account and sets the session cookie.
- `POST /api/v1/auth/logout` clears the session cookie.
- `GET /api/v1/auth/setup-status` reports whether the first admin still needs to be created.
The authenticated auth endpoints are: For production deployments, it is recommended to:
1. Use Nginx for basic auth or OAuth integration
- `GET /api/v1/auth/me` returns the current user. 2. Deploy behind a VPN or private network
- `POST /api/v1/auth/change-password` changes password, optionally changes email during setup, increments `token_version`, and reissues the cookie. 3. Implement custom authentication middleware
Protected state-changing requests also require the CSRF double-submit token: send the `csrf_token` cookie value as the `X-CSRF-Token` header. Login/register/initialize/logout are bootstrap auth endpoints: they are exempt from the double-submit token but still reject hostile browser `Origin` headers.
User isolation is enforced from the authenticated user context:
- Thread metadata is scoped by `threads_meta.user_id`; search/read/write/delete APIs only expose the current user's threads.
- Thread files live under `{base_dir}/users/{user_id}/threads/{thread_id}/user-data/` and are exposed inside the sandbox as `/mnt/user-data/`.
- Memory and custom agents are stored under `{base_dir}/users/{user_id}/...`.
Note: MCP outbound connections can still use OAuth for configured HTTP/SSE MCP servers; that is separate from DeerFlow API authentication.
--- ---
@@ -568,13 +567,12 @@ location /api/ {
--- ---
## Streaming Support ## WebSocket Support
Gateway's LangGraph-compatible API streams run events with Server-Sent Events (SSE): The LangGraph server supports WebSocket connections for real-time streaming. Connect to:
```http ```
POST /api/langgraph/threads/{thread_id}/runs/stream ws://localhost:2026/api/langgraph/threads/{thread_id}/runs/stream
Accept: text/event-stream
``` ```
--- ---
@@ -610,21 +608,13 @@ const response = await fetch('/api/models');
const data = await response.json(); const data = await response.json();
console.log(data.models); console.log(data.models);
// Create a run and stream SSE events // Using EventSource for streaming
const streamResponse = await fetch(`/api/langgraph/threads/${threadId}/runs/stream`, { const eventSource = new EventSource(
method: "POST", `/api/langgraph/threads/${threadId}/runs/stream`
headers: { );
"Content-Type": "application/json", eventSource.onmessage = (event) => {
Accept: "text/event-stream", console.log(JSON.parse(event.data));
}, };
body: JSON.stringify({
input: { messages: [{ role: "user", content: "Hello" }] },
stream_mode: ["values", "messages-tuple", "custom"],
}),
});
const reader = streamResponse.body?.getReader();
// Decode and parse SSE frames from reader in your client code.
``` ```
### cURL Examples ### cURL Examples
@@ -659,7 +649,7 @@ curl -X POST http://localhost:2026/api/langgraph/threads/abc123/runs \
}' }'
``` ```
> The unified Gateway path defaults `config.recursion_limit` to 100 for > The `/api/langgraph/*` endpoints bypass DeerFlow's Gateway and inherit
> plan-mode and subagent-heavy runs. Clients may still set > LangGraph's native `recursion_limit` default of 25, which is too low for
> `config.recursion_limit` explicitly — see the [Create Run](#create-run) > plan-mode or subagent runs. Set `config.recursion_limit` explicitly — see
> section for details. > the [Create Run](#create-run) section for details.
+30 -30
View File
@@ -14,28 +14,30 @@ This document provides a comprehensive overview of the DeerFlow backend architec
│ Nginx (Port 2026) │ │ Nginx (Port 2026) │
│ Unified Reverse Proxy Entry Point │ │ Unified Reverse Proxy Entry Point │
│ ┌────────────────────────────────────────────────────────────────────┐ │ │ ┌────────────────────────────────────────────────────────────────────┐ │
│ │ /api/langgraph/* → Gateway LangGraph-compatible runtime (8001) │ │ │ │ /api/langgraph/* → LangGraph Server (2024) │ │
│ │ /api/* → Gateway REST APIs (8001) │ │ │ │ /api/* → Gateway API (8001) │ │
│ │ /* → Frontend (3000) │ │ │ │ /* → Frontend (3000) │ │
│ └────────────────────────────────────────────────────────────────────┘ │ │ └────────────────────────────────────────────────────────────────────┘ │
└─────────────────────────────────┬────────────────────────────────────────┘ └─────────────────────────────────┬────────────────────────────────────────┘
┌──────────────────────────────────────────────┐ ┌──────────────────────────────────────────────┐
┌─────────────────────────────────────────────┐ ┌─────────────────────┐ ┌─────────────────────┐ ┌─────────────────────┐ ┌─────────────────────┐
Gateway API │ │ Frontend │ LangGraph Server │ │ Gateway API │ │ Frontend │
│ (Port 8001) │ │ (Port 3000) │ (Port 2024) │ │ (Port 8001) │ │ (Port 3000) │
│ │ │ │ │ │ │ │
│ - LangGraph-compatible runs/threads API │ │ - Next.js App │ │ - Agent Runtime │ │ - Models API │ │ - Next.js App │
│ - Embedded Agent Runtime │ │ - React UI │ │ - Thread Mgmt │ │ - MCP Config │ │ - React UI │
│ - SSE Streaming │ │ - Chat Interface │ │ - SSE Streaming │ │ - Skills Mgmt │ │ - Chat Interface │
│ - Checkpointing │ │ │ │ - Checkpointing │ │ - File Uploads │ │ │
- Models, MCP, Skills, Uploads, Artifacts │ │ │ │ │ - Thread Cleanup │ │ │
- Thread Cleanup │ │ │ │ │ - Artifacts │ │ │
└─────────────────────────────────────────────┘ └─────────────────────┘ └─────────────────────┘ └─────────────────────┘ └─────────────────────┘
│ ┌─────────────────┘
│ │
▼ ▼
┌──────────────────────────────────────────────────────────────────────────┐ ┌──────────────────────────────────────────────────────────────────────────┐
│ Shared Configuration │ │ Shared Configuration │
│ ┌─────────────────────────┐ ┌────────────────────────────────────────┐ │ │ ┌─────────────────────────┐ ┌────────────────────────────────────────┐ │
@@ -50,9 +52,9 @@ This document provides a comprehensive overview of the DeerFlow backend architec
## Component Details ## Component Details
### Gateway Embedded Agent Runtime ### LangGraph Server
The agent runtime is embedded in the FastAPI Gateway and built on LangGraph for robust multi-agent workflow orchestration. Nginx rewrites `/api/langgraph/*` to Gateway's native `/api/*` routes, so the public API remains compatible with LangGraph SDK clients without running a separate LangGraph server. The LangGraph server is the core agent runtime, built on LangGraph for robust multi-agent workflow orchestration.
**Entry Point**: `packages/harness/deerflow/agents/lead_agent/agent.py:make_lead_agent` **Entry Point**: `packages/harness/deerflow/agents/lead_agent/agent.py:make_lead_agent`
@@ -63,8 +65,7 @@ The agent runtime is embedded in the FastAPI Gateway and built on LangGraph for
- Tool execution orchestration - Tool execution orchestration
- SSE streaming for real-time responses - SSE streaming for real-time responses
**Graph registry**: `langgraph.json` remains available for tooling, Studio, or direct LangGraph Server compatibility. **Configuration**: `langgraph.json`
It is not the default service entrypoint; scripts and Docker deployments run the Gateway embedded runtime.
```json ```json
{ {
@@ -77,13 +78,12 @@ It is not the default service entrypoint; scripts and Docker deployments run the
### Gateway API ### Gateway API
FastAPI application providing REST endpoints plus the public LangGraph-compatible `/api/langgraph/*` runtime routes. FastAPI application providing REST endpoints for non-agent operations.
**Entry Point**: `app/gateway/app.py` **Entry Point**: `app/gateway/app.py`
**Routers**: **Routers**:
- `models.py` - `/api/models` - Model listing and details - `models.py` - `/api/models` - Model listing and details
- `thread_runs.py` / `runs.py` - `/api/threads/{id}/runs`, `/api/runs/*` - LangGraph-compatible runs and streaming
- `mcp.py` - `/api/mcp` - MCP server configuration - `mcp.py` - `/api/mcp` - MCP server configuration
- `skills.py` - `/api/skills` - Skills management - `skills.py` - `/api/skills` - Skills management
- `uploads.py` - `/api/threads/{id}/uploads` - File upload - `uploads.py` - `/api/threads/{id}/uploads` - File upload
@@ -91,7 +91,7 @@ FastAPI application providing REST endpoints plus the public LangGraph-compatibl
- `artifacts.py` - `/api/threads/{id}/artifacts` - Artifact serving - `artifacts.py` - `/api/threads/{id}/artifacts` - Artifact serving
- `suggestions.py` - `/api/threads/{id}/suggestions` - Follow-up suggestion generation - `suggestions.py` - `/api/threads/{id}/suggestions` - Follow-up suggestion generation
The web conversation delete flow first deletes Gateway-managed thread state through the LangGraph-compatible route, then the Gateway `threads.py` router removes DeerFlow-managed filesystem data via `Paths.delete_thread_dir()`. The web conversation delete flow is now split across both backend surfaces: LangGraph handles `DELETE /api/langgraph/threads/{thread_id}` for thread state, then the Gateway `threads.py` router removes DeerFlow-managed filesystem data via `Paths.delete_thread_dir()`.
### Agent Architecture ### Agent Architecture
@@ -199,7 +199,7 @@ class ThreadState(AgentState):
│ Built-in Tools │ │ Configured Tools │ │ MCP Tools │ │ Built-in Tools │ │ Configured Tools │ │ MCP Tools │
│ (packages/harness/deerflow/tools/) │ │ (config.yaml) │ │ (extensions.json) │ │ (packages/harness/deerflow/tools/) │ │ (config.yaml) │ │ (extensions.json) │
├─────────────────────┤ ├─────────────────────┤ ├─────────────────────┤ ├─────────────────────┤ ├─────────────────────┤ ├─────────────────────┤
│ - present_files │ │ - web_search │ │ - github │ │ - present_file │ │ - web_search │ │ - github │
│ - ask_clarification │ │ - web_fetch │ │ - filesystem │ │ - ask_clarification │ │ - web_fetch │ │ - filesystem │
│ - view_image │ │ - bash │ │ - postgres │ │ - view_image │ │ - bash │ │ - postgres │
│ │ │ - read_file │ │ - brave-search │ │ │ │ - read_file │ │ - brave-search │
@@ -353,10 +353,10 @@ SKILL.md Format:
POST /api/langgraph/threads/{thread_id}/runs POST /api/langgraph/threads/{thread_id}/runs
{"input": {"messages": [{"role": "user", "content": "Hello"}]}} {"input": {"messages": [{"role": "user", "content": "Hello"}]}}
2. Nginx → Gateway API (8001) 2. Nginx → LangGraph Server (2024)
`/api/langgraph/*` is rewritten to Gateway's LangGraph-compatible `/api/*` routes Proxied to LangGraph server
3. Gateway embedded runtime 3. LangGraph Server
a. Load/create thread state a. Load/create thread state
b. Execute middleware chain: b. Execute middleware chain:
- ThreadDataMiddleware: Set up paths - ThreadDataMiddleware: Set up paths
@@ -412,7 +412,7 @@ SKILL.md Format:
### Thread Cleanup Flow ### Thread Cleanup Flow
``` ```
1. Client deletes conversation via the LangGraph-compatible Gateway route 1. Client deletes conversation via LangGraph
DELETE /api/langgraph/threads/{thread_id} DELETE /api/langgraph/threads/{thread_id}
2. Web UI follows up with Gateway cleanup 2. Web UI follows up with Gateway cleanup
-331
View File
@@ -1,331 +0,0 @@
# 用户认证与隔离设计
本文档描述 DeerFlow 当前内置认证模块的设计,而不是历史 RFC。它覆盖浏览器登录、API 认证、CSRF、用户隔离、首次初始化、密码重置、内部调用和升级迁移。
## 设计目标
认证模块的核心目标是把 DeerFlow 从“本地单用户工具”提升为“可多用户部署的 agent runtime”,并让用户身份贯穿 HTTP API、LangGraph-compatible runtime、文件系统、memory、自定义 agent 和反馈数据。
设计约束:
- 默认强制认证:除健康检查、文档和 auth bootstrap 端点外,HTTP 路由都必须有有效 session。
- 服务端持有所有权:客户端 metadata 不能声明 `user_id``owner_id`
- 隔离默认开启:repository(仓储)、文件路径、memory、agent 配置默认按当前用户解析。
- 旧数据可升级:无认证版本留下的 thread 可以在 admin 存在后迁移到 admin。
- 密码不进日志:首次初始化由操作者设置密码;`reset_admin` 只写 0600 凭据文件。
非目标:
- 当前 OAuth 端点只是占位,尚未实现第三方登录。
- 当前用户角色只有 `admin``user`,尚未实现细粒度 RBAC。
- 当前登录限速是进程内字典,多 worker 下不是全局精确限速。
## 核心模型
```mermaid
graph TB
classDef actor fill:#D8CFC4,stroke:#6E6259,color:#2F2A26;
classDef api fill:#C9D7D2,stroke:#5D706A,color:#21302C;
classDef state fill:#D7D3E8,stroke:#6B6680,color:#29263A;
classDef data fill:#E5D2C4,stroke:#806A5B,color:#30251E;
Browser["Browser — access_token cookie and csrf_token cookie"]:::actor
AuthMiddleware["AuthMiddleware — strict session gate"]:::api
CSRFMiddleware["CSRFMiddleware — double-submit token and Origin check"]:::api
AuthRoutes["Auth routes — initialize login register logout me change-password"]:::api
UserContext["Current user ContextVar — request-scoped identity"]:::state
Repositories["Repositories — AUTO resolves user_id from context"]:::state
Files["Filesystem — users/{user_id}/threads/{thread_id}/user-data"]:::data
Memory["Memory and agents — users/{user_id}/memory.json and agents"]:::data
Browser --> AuthMiddleware
Browser --> CSRFMiddleware
AuthMiddleware --> AuthRoutes
AuthMiddleware --> UserContext
UserContext --> Repositories
UserContext --> Files
UserContext --> Memory
```
### 用户表
用户记录定义在 `app.gateway.auth.models.User`,持久化到 `users` 表。关键字段:
| 字段 | 语义 |
|---|---|
| `id` | 用户主键,JWT `sub` 使用该值 |
| `email` | 唯一登录名 |
| `password_hash` | bcrypt hashOAuth 用户可为空 |
| `system_role` | `admin``user` |
| `needs_setup` | reset 后要求用户完成邮箱 / 密码设置 |
| `token_version` | 改密码或 reset 时递增,用于废弃旧 JWT |
### 运行时身份
认证成功后,`AuthMiddleware` 把用户同时写入:
- `request.state.user`
- `request.state.auth`
- `deerflow.runtime.user_context``ContextVar`
`ContextVar` 是这里的核心边界。上层 Gateway 负责写入身份,下层 persistence / file path 只读取结构化的当前用户,不反向依赖 `app.gateway.auth` 具体类型。
可以把 repository 调用的用户参数理解成一个三态 ADT:
```scala
enum UserScope:
case AutoFromContext
case Explicit(userId: String)
case BypassForMigration
```
对应 Python 实现是 `AUTO | str | None`
- `AUTO`:从 `ContextVar` 解析当前用户;没有上下文则抛错。
- `str`:显式指定用户,主要用于测试或管理脚本。
- `None`:跳过用户过滤,只允许迁移脚本或 admin CLI 使用。
## 登录与初始化流程
### 首次初始化
首次启动时,如果没有 admin,服务不会自动创建账号,只记录日志提示访问 `/setup`
流程:
1. 用户访问 `/setup`
2. 前端调用 `GET /api/v1/auth/setup-status`
3. 如果返回 `{"needs_setup": true}`,前端展示创建 admin 表单。
4. 表单提交 `POST /api/v1/auth/initialize`
5. 服务端确认当前没有 admin,创建 `system_role="admin"``needs_setup=false` 的用户。
6. 服务端设置 `access_token` HttpOnly cookie,用户进入 workspace。
`/api/v1/auth/initialize` 只在没有 admin 时可用。并发初始化由数据库唯一约束兜底,失败方返回 409。
### 普通登录
`POST /api/v1/auth/login/local` 使用 `OAuth2PasswordRequestForm`
- `username` 是邮箱。
- `password` 是密码。
- 成功后签发 JWT,放入 `access_token` HttpOnly cookie。
- 响应体只返回 `expires_in``needs_setup`,不返回 token。
登录失败会按客户端 IP 计数。IP 解析只在 TCP peer 属于 `AUTH_TRUSTED_PROXIES` 时信任 `X-Real-IP`,不使用 `X-Forwarded-For`
### 注册
`POST /api/v1/auth/register` 创建普通 `user`,并自动登录。
当前实现允许在没有 admin 时注册普通用户,但 `setup-status` 仍会返回 `needs_setup=true`,因为 admin 仍不存在。这是当前产品策略边界:如果后续要求“必须先初始化 admin 才能注册普通用户”,需要在 `/register` 增加 admin-exists gate。
### 改密码与 reset setup
`POST /api/v1/auth/change-password` 需要当前密码和新密码:
- 校验当前密码。
- 更新 bcrypt hash。
- `token_version += 1`,使旧 JWT 立即失效。
- 重新签发 cookie。
- 如果 `needs_setup=true` 且传了 `new_email`,则更新邮箱并清除 `needs_setup`
`python -m app.gateway.auth.reset_admin` 会:
- 找到 admin 或指定邮箱用户。
- 生成随机密码。
- 更新密码 hash。
- `token_version += 1`
- 设置 `needs_setup=true`
- 写入 `.deer-flow/admin_initial_credentials.txt`,权限 `0600`
命令行只输出凭据文件路径,不输出明文密码。
## HTTP 认证边界
`AuthMiddleware` 是 fail-closed(默认拒绝)的全局认证门。
公开路径:
- `/health`
- `/docs`
- `/redoc`
- `/openapi.json`
- `/api/v1/auth/login/local`
- `/api/v1/auth/register`
- `/api/v1/auth/logout`
- `/api/v1/auth/setup-status`
- `/api/v1/auth/initialize`
其余路径都要求有效 `access_token` cookie。存在 cookie 但 JWT 无效、过期、用户不存在或 `token_version` 不匹配时,直接返回 401,而不是让请求穿透到业务路由。
路由级别的 owner check 由 `require_permission(..., owner_check=True)` 完成:
- 读类请求允许旧的未追踪 legacy thread 兼容读取。
- 写 / 删除类请求使用 `require_existing=True`,要求 thread row 存在且属于当前用户,避免删除后缺 row 导致其他用户误通过。
## CSRF 设计
DeerFlow 使用 Double Submit Cookie
- 服务端设置 `csrf_token` cookie。
- 前端 state-changing 请求发送同值 `X-CSRF-Token` header。
- 服务端用 `secrets.compare_digest` 比较 cookie/header。
需要 CSRF 的方法:
- `POST`
- `PUT`
- `DELETE`
- `PATCH`
auth bootstrap 端点(login/register/initialize/logout)不要求 double-submit token,因为首次调用时浏览器还没有 token;但这些端点会校验 browser `Origin`,拒绝 hostile Origin,避免 login CSRF / session fixation。
## 用户隔离
### Thread metadata
Thread metadata 存在 `threads_meta`,关键隔离字段是 `user_id`
创建 thread 时:
- 客户端传入的 `metadata.user_id``metadata.owner_id` 会被剥离。
- `ThreadMetaRepository.create(..., user_id=AUTO)``ContextVar` 解析真实用户。
- `/api/threads/search` 默认只返回当前用户的 thread。
读取 / 修改 / 删除时:
- `get()` 默认按当前用户过滤。
- `check_access()` 用于路由 owner check。
- 对其他用户的 thread 返回 404,避免泄露资源存在性。
### 文件系统
当前线程文件布局:
```text
{base_dir}/users/{user_id}/threads/{thread_id}/user-data/
├── workspace/
├── uploads/
└── outputs/
```
agent 在 sandbox 内看到统一虚拟路径:
```text
/mnt/user-data/workspace
/mnt/user-data/uploads
/mnt/user-data/outputs
```
`ThreadDataMiddleware` 使用 `get_effective_user_id()` 解析当前用户并生成线程路径。没有认证上下文时会落到 `default` 用户桶,主要用于内部调用、嵌入式 client 或无 HTTP 的本地执行路径。
### Memory
默认 memory 存储:
```text
{base_dir}/users/{user_id}/memory.json
{base_dir}/users/{user_id}/agents/{agent_name}/memory.json
```
有用户上下文时,空或相对 `memory.storage_path` 都使用上述 per-user 默认路径;只有绝对 `memory.storage_path` 会视为显式 opt-out(退出) per-user isolation,所有用户共享该路径。无用户上下文的 legacy 路径仍会把相对 `storage_path` 解析到 `Paths.base_dir` 下。
### 自定义 agent
用户自定义 agent 写入:
```text
{base_dir}/users/{user_id}/agents/{agent_name}/
├── config.yaml
├── SOUL.md
└── memory.json
```
旧布局 `{base_dir}/agents/{agent_name}/` 只作为只读兼容回退。更新或删除旧共享 agent 会要求先运行迁移脚本。
## 内部调用与 IM 渠道
IM channel worker 不是浏览器用户,不持有浏览器 cookie。它们通过 Gateway 内部认证:
- 请求带 `X-DeerFlow-Internal-Token`
- 同时带匹配的 CSRF cookie/header。
- 服务端识别为内部用户,`id="default"``system_role="internal"`
这意味着 channel 产生的数据默认进入 `default` 用户桶。这个选择适合“平台级 bot 身份”,但不是“每个 IM 用户单独隔离”。如果后续要做到外部 IM 用户隔离,需要把外部 platform user 映射到 DeerFlow user,并让 channel manager 设置对应的 scoped identity。
## LangGraph-compatible 认证
Gateway 内嵌 runtime 路径由 `AuthMiddleware``CSRFMiddleware` 保护。
仓库仍保留 `app.gateway.langgraph_auth`,用于 LangGraph Server 直连模式:
- `@auth.authenticate` 校验 JWT cookie、CSRF、用户存在性和 `token_version`
- `@auth.on` 在写入 metadata 时注入 `user_id`,并在读路径返回 `{"user_id": current_user}` 过滤条件。
这保证 Gateway 路由和 LangGraph-compatible 直连模式使用同一 JWT 语义。
## 升级与迁移
从无认证版本升级时,可能存在没有 `user_id` 的历史 thread。
当前策略:
1. 首次启动如果没有 admin,只提示访问 `/setup`,不迁移。
2. 操作者创建 admin。
3. 后续启动时,`_ensure_admin_user()` 找到 admin,并把 LangGraph store 中缺少 `metadata.user_id` 的 thread 迁移到 admin。
文件系统旧布局迁移由脚本处理:
```bash
cd backend
PYTHONPATH=. python scripts/migrate_user_isolation.py --dry-run
PYTHONPATH=. python scripts/migrate_user_isolation.py --user-id <target-user-id>
```
迁移脚本覆盖 legacy `memory.json``threads/``agents/` 到 per-user layout。
## 安全不变量
必须长期保持的不变量:
- JWT 只在 HttpOnly cookie 中传输,不出现在响应 JSON。
- 任何非 public HTTP 路由都不能只靠“cookie 存在”放行,必须严格验证 JWT。
- `token_version` 不匹配必须拒绝,保证改密码 / reset 后旧 session 失效。
- 客户端 metadata 中的 `user_id` / `owner_id` 必须剥离。
- repository 默认 `AUTO` 必须从当前用户上下文解析,不能静默退化成全局查询。
- 只有迁移脚本和 admin CLI 可以显式传 `user_id=None` 绕过隔离。
- 本地文件路径必须通过 `Paths` 和 sandbox path validation 解析,不能拼接未校验的用户输入。
- 捕获认证、迁移、后台任务异常必须记录日志;不能空 catch。
## 已知边界
| 边界 | 当前行为 | 后续方向 |
|---|---|---|
| 无 admin 时注册普通用户 | 允许注册普通 `user` | 如产品要求先初始化 admin,给 `/register` 加 gate |
| 登录限速 | 进程内 dict,单 worker 精确,多 worker 近似 | Redis / DB-backed rate limiter |
| OAuth | 端点占位,未实现 | 接入 provider 并统一 `token_version` / role 语义 |
| IM 用户隔离 | channel 使用 `default` 内部用户 | 建立外部用户到 DeerFlow user 的映射 |
| 绝对 memory path | 显式共享 memory | UI / docs 明确提示 opt-out 风险 |
## 相关文件
| 文件 | 职责 |
|---|---|
| `app/gateway/auth_middleware.py` | 全局认证门、JWT 严格验证、写入 user context |
| `app/gateway/csrf_middleware.py` | CSRF double-submit 和 auth Origin 校验 |
| `app/gateway/routers/auth.py` | initialize/login/register/logout/me/change-password |
| `app/gateway/auth/jwt.py` | JWT 创建与解析 |
| `app/gateway/auth/reset_admin.py` | 密码 reset CLI |
| `app/gateway/auth/credential_file.py` | 0600 凭据文件写入 |
| `app/gateway/authz.py` | 路由权限与 owner check |
| `deerflow/runtime/user_context.py` | 当前用户 ContextVar 与 `AUTO` sentinel |
| `deerflow/persistence/thread_meta/` | thread metadata owner filter |
| `deerflow/config/paths.py` | per-user filesystem layout |
| `deerflow/agents/middlewares/thread_data_middleware.py` | run 时解析用户线程目录 |
| `deerflow/agents/memory/storage.py` | per-user memory storage |
| `deerflow/config/agents_config.py` | per-user custom agents |
| `app/channels/manager.py` | IM channel 内部认证调用 |
| `scripts/migrate_user_isolation.py` | legacy 数据迁移到 per-user layout |
| `.deer-flow/data/deerflow.db` | 统一 SQLite 数据库,包含 users / threads_meta / runs / feedback 等表 |
| `.deer-flow/users/{user_id}/agents/{agent_name}/` | 用户自定义 agent 配置、SOUL 和 agent memory |
| `.deer-flow/admin_initial_credentials.txt` | `reset_admin` 生成的新凭据文件(0600,读完应删除) |
+8 -8
View File
@@ -24,12 +24,12 @@ All other test plan sections were executed against either:
| Case | Title | What it covers | Why not run | | Case | Title | What it covers | Why not run |
|---|---|---|---| |---|---|---|---|
| TC-DOCKER-01 | `deerflow.db` volume persistence | Verify the `DEER_FLOW_HOME` bind mount survives container restart | needs `docker compose up` | | 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-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-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 use internal Gateway auth | Verify Feishu/Slack/Telegram dispatchers attach the process-local internal auth header plus CSRF cookie/header when calling Gateway-compatible LangGraph APIs | needs `docker logs` | | 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 | Reset credentials surfacing | `reset_admin` writes a 0600 credential file in `DEER_FLOW_HOME` instead of logging plaintext. The file-based behavior is validated by non-Docker reset tests, so the only Docker-specific gap is verifying the volume mount carries the file out to the host | needs container + host volume | | 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 | Docker deploy uses Gateway embedded runtime | `./scripts/deploy.sh` produces a Gateway + frontend + nginx topology (no `langgraph` container); same auth flow as local `make dev` | needs `docker compose up` | | 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 ## Coverage already provided by non-Docker tests
@@ -41,9 +41,9 @@ the test cases that ran on sg_dev or local:
| 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-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-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-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 use internal auth) | Code-level: `app/channels/manager.py` creates the `langgraph_sdk` client with `create_internal_auth_headers()` plus CSRF cookie/header, so channel workers do not rely on browser cookies | | 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) | `reset_admin` writes `.deer-flow/admin_initial_credentials.txt` with mode 0600 and logs only the path — 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-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 embedded runtime container) | Section 七 7.2 covered by TC-GW-01..05 + Section 二 (Gateway auth flow on sg_dev) — same Gateway code, container is just a packaging 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 ## Reproduction steps when Docker becomes available
@@ -72,6 +72,6 @@ Then run TC-DOCKER-01..06 from the test plan as written.
about *container packaging* details (bind mounts, multi-worker, log about *container packaging* details (bind mounts, multi-worker, log
collection), not about whether the auth code paths work. collection), not about whether the auth code paths work.
- **TC-DOCKER-05 was updated in place** in `AUTH_TEST_PLAN.md` to reflect - **TC-DOCKER-05 was updated in place** in `AUTH_TEST_PLAN.md` to reflect
the current reset flow (`reset_admin` → 0600 credentials file, no log leak). the post-simplify reality (credentials file → 0600 file, no log leak).
The old "grep 'Password:' in docker logs" expectation would have failed The old "grep 'Password:' in docker logs" expectation would have failed
silently and given a false sense of coverage. silently and given a false sense of coverage.
+156 -179
View File
@@ -4,12 +4,10 @@
| 模式 | 启动命令 | Auth 层 | 端口 | | 模式 | 启动命令 | Auth 层 | 端口 |
|------|---------|---------|------| |------|---------|---------|------|
| 标准模式 | `make dev` | Gateway AuthMiddleware(全量) | 2026 (nginx) | | 标准模式 | `make dev` | Gateway AuthMiddleware + LangGraph auth | 2026 (nginx) |
| Gateway 模式 | `make dev-pro` | Gateway AuthMiddleware(全量) | 2026 (nginx) |
| 直连 Gateway | `cd backend && make gateway` | Gateway AuthMiddleware | 8001 | | 直连 Gateway | `cd backend && make gateway` | Gateway AuthMiddleware | 8001 |
| 直连 LangGraph 兼容性 | 手动运行 LangGraph 工具链时使用 | LangGraph auth | 2024 | | 直连 LangGraph | `cd backend && make dev` | LangGraph auth | 2024 |
`make dev`、Docker dev 和生产部署默认都运行 Gateway embedded runtime。
`app.gateway.langgraph_auth` 仅用于保留的直连 LangGraph 工具链 / Studio 兼容性测试,不是标准服务启动路径。
每种模式下都需执行以下测试。 每种模式下都需执行以下测试。
@@ -21,18 +19,19 @@
```bash ```bash
# 清除已有数据 # 清除已有数据
rm -f backend/.deer-flow/data/deerflow.db rm -f backend/.deer-flow/users.db
# 启动标准模式(Gateway embedded runtime # 选择模式启动
make dev make dev # 标准模式
# 或
make dev-pro # Gateway 模式
``` ```
**验证点:** **验证点:**
- [ ] 控制台输出 admin 邮箱或明文密码 - [ ] 控制台输出 admin 邮箱和随机密码
- [ ] 控制台提示 `First boot detected — no admin account exists.` - [ ] 密码格式为 `secrets.token_urlsafe(16)` 的 22 字符字符串
- [ ] 控制台提示访问 `/setup` 完成 admin 创建 - [ ] 邮箱为 `admin@deerflow.dev`
- [ ] `GET /api/v1/auth/setup-status` 返回 `{"needs_setup": true}` - [ ] 提示 `Change it after login: Settings -> Account`
- [ ] 前端访问 `/login` 会跳转 `/setup`
### 1.2 非首次启动 ### 1.2 非首次启动
@@ -43,8 +42,7 @@ make dev
**验证点:** **验证点:**
- [ ] 控制台不输出密码 - [ ] 控制台不输出密码
- [ ] `GET /api/v1/auth/setup-status` 返回 `{"needs_setup": false}` - [ ] 如果 admin 仍 `needs_setup=True`,控制台有 warning 提示
- [ ] 已登录用户如果 `needs_setup=True`,访问 workspace 会被引导到 `/setup` 完成改邮箱 / 改密码流程
### 1.3 环境变量配置 ### 1.3 环境变量配置
@@ -57,7 +55,7 @@ make dev
## 二、接口流程测试 ## 二、接口流程测试
> 以下用 `BASE=http://localhost:2026` 为例。标准模式经 nginx 暴露此地址。 > 以下用 `BASE=http://localhost:2026` 为例。标准模式和 Gateway 模式都用此地址。
> 直连测试替换为对应端口。 > 直连测试替换为对应端口。
> >
> **CSRF token 提取**:多处用到从 cookie jar 提取 CSRF token,统一使用: > **CSRF token 提取**:多处用到从 cookie jar 提取 CSRF token,统一使用:
@@ -78,22 +76,19 @@ make dev
curl -s $BASE/api/v1/auth/setup-status | jq . curl -s $BASE/api/v1/auth/setup-status | jq .
``` ```
**预期:** **预期:** 返回 `{"needs_setup": false}`admin 在启动时已自动创建,`count_users() > 0`)。仅在启动完成前的极短窗口内可能返回 `true`
- 干净数据库且尚未初始化 admin:返回 `{"needs_setup": true}`
- 已存在 admin:返回 `{"needs_setup": false}`
#### TC-API-02: 首次初始化 Admin #### TC-API-02: Admin 首次登录
```bash ```bash
curl -s -X POST $BASE/api/v1/auth/initialize \ curl -s -X POST $BASE/api/v1/auth/login/local \
-H "Content-Type: application/json" \ -d "username=admin@deerflow.dev&password=<控制台密码>" \
-d '{"email":"admin@example.com","password":"AdminPass1!"}' \
-c cookies.txt | jq . -c cookies.txt | jq .
``` ```
**预期:** **预期:**
- 状态码 201 - 状态码 200
- Body: `{"id": "...", "email": "admin@example.com", "system_role": "admin", "needs_setup": false}` - Body: `{"expires_in": 604800, "needs_setup": true}`
- `cookies.txt` 包含 `access_token`HttpOnly)和 `csrf_token`(非 HttpOnly - `cookies.txt` 包含 `access_token`HttpOnly)和 `csrf_token`(非 HttpOnly
#### TC-API-03: 获取当前用户 #### TC-API-03: 获取当前用户
@@ -102,9 +97,9 @@ curl -s -X POST $BASE/api/v1/auth/initialize \
curl -s $BASE/api/v1/auth/me -b cookies.txt | jq . curl -s $BASE/api/v1/auth/me -b cookies.txt | jq .
``` ```
**预期:** `{"id": "...", "email": "admin@example.com", "system_role": "admin", "needs_setup": false}` **预期:** `{"id": "...", "email": "admin@deerflow.dev", "system_role": "admin", "needs_setup": true}`
#### TC-API-04: 改密码流程 #### TC-API-04: Setup 流程(改邮箱 + 改密码
```bash ```bash
CSRF=$(grep csrf_token cookies.txt | awk '{print $NF}') CSRF=$(grep csrf_token cookies.txt | awk '{print $NF}')
@@ -112,36 +107,13 @@ curl -s -X POST $BASE/api/v1/auth/change-password \
-b cookies.txt \ -b cookies.txt \
-H "Content-Type: application/json" \ -H "Content-Type: application/json" \
-H "X-CSRF-Token: $CSRF" \ -H "X-CSRF-Token: $CSRF" \
-d '{"current_password":"AdminPass1!","new_password":"NewPass123!"}' | jq . -d '{"current_password":"<控制台密码>","new_password":"NewPass123!","new_email":"admin@example.com"}' | jq .
``` ```
**预期:** **预期:**
- 状态码 200 - 状态码 200
- `{"message": "Password changed successfully"}` - `{"message": "Password changed successfully"}`
- 再调 `/auth/me` `admin@example.com``needs_setup` `false` - 再调 `/auth/me` 邮箱变`admin@example.com``needs_setup` `false`
#### TC-API-04a: reset_admin 后的 Setup 流程(改邮箱 + 改密码)
```bash
cd backend
python -m app.gateway.auth.reset_admin --email admin@example.com
# 从 .deer-flow/admin_initial_credentials.txt 读取 reset 后密码
curl -s -X POST $BASE/api/v1/auth/login/local \
-d "username=admin@example.com&password=<凭据文件密码>" \
-c cookies.txt | jq .
CSRF=$(grep csrf_token cookies.txt | awk '{print $NF}')
curl -s -X POST $BASE/api/v1/auth/change-password \
-b cookies.txt \
-H "Content-Type: application/json" \
-H "X-CSRF-Token: $CSRF" \
-d '{"current_password":"<凭据文件密码>","new_password":"AdminPass2!","new_email":"admin2@example.com"}' | jq .
```
**预期:**
- 登录返回 `{"expires_in": 604800, "needs_setup": true}`
- `change-password``/auth/me` 邮箱变为 `admin2@example.com``needs_setup` 变为 `false`
#### TC-API-05: 普通用户注册 #### TC-API-05: 普通用户注册
@@ -211,18 +183,20 @@ curl -s -X POST $BASE/api/threads/search \
**预期:** 返回 0 或仅包含 user2 自己的 thread **预期:** 返回 0 或仅包含 user2 自己的 thread
### 2.3 LangGraph-compatible Gateway 路由隔离 ### 2.3 标准模式 LangGraph Server 隔离
#### TC-API-10: LangGraph-compatible 端点需要 cookie > 仅在标准模式下测试。Gateway 模式不跑 LangGraph Server。
#### TC-API-10: LangGraph 端点需要 cookie
```bash ```bash
# 不带 cookie 访问 LangGraph-compatible 接口 # 不带 cookie 访问 LangGraph 接口
curl -s -w "%{http_code}" $BASE/api/langgraph/threads curl -s -w "%{http_code}" $BASE/api/langgraph/threads
``` ```
**预期:** 401 **预期:** 401
#### TC-API-11: LangGraph-compatible 路由带 cookie 可访问 #### TC-API-11: LangGraph 带 cookie 可访问
```bash ```bash
curl -s $BASE/api/langgraph/threads -b user1.txt | jq length curl -s $BASE/api/langgraph/threads -b user1.txt | jq length
@@ -230,10 +204,10 @@ curl -s $BASE/api/langgraph/threads -b user1.txt | jq length
**预期:** 200,返回 user1 的 thread 列表 **预期:** 200,返回 user1 的 thread 列表
#### TC-API-12: LangGraph-compatible 路由隔离 — 用户只看到自己的 #### TC-API-12: LangGraph 隔离 — 用户只看到自己的
```bash ```bash
# user2 查 threads # user2 查 LangGraph threads
curl -s $BASE/api/langgraph/threads -b user2.txt | jq length curl -s $BASE/api/langgraph/threads -b user2.txt | jq length
``` ```
@@ -519,7 +493,7 @@ curl -s -X POST $BASE/api/v1/auth/register \
```bash ```bash
# 检查数据库 # 检查数据库
sqlite3 backend/.deer-flow/data/deerflow.db "SELECT email, password_hash FROM users LIMIT 3;" sqlite3 backend/.deer-flow/users.db "SELECT email, password_hash FROM users LIMIT 3;"
``` ```
**预期:** `password_hash``$2b$` 开头(bcrypt 格式) **预期:** `password_hash``$2b$` 开头(bcrypt 格式)
@@ -532,25 +506,24 @@ sqlite3 backend/.deer-flow/data/deerflow.db "SELECT email, password_hash FROM us
### 4.1 首次登录流程 ### 4.1 首次登录流程
#### TC-UI-01: 无 admin 时访问 workspace 跳转 setup #### TC-UI-01: 访问首页跳转登录
1. 打开 `http://localhost:2026/workspace` 1. 打开 `http://localhost:2026/workspace`
2. **预期:** 自动跳转到 `/setup` 2. **预期:** 自动跳转到 `/login`
#### TC-UI-02: Setup 页面创建 admin #### TC-UI-02: Login 页面
1. 输入 admin 邮箱、密码、确认密码 1. 输入 admin 邮箱和控制台密码
2. 点击 Create Admin Account 2. 点击 Login
3. **预期:** 跳转到 `/setup`(因为 `needs_setup=true`
#### TC-UI-03: Setup 页面
1. 输入新邮箱、控制台密码(current)、新密码、确认密码
2. 点击 Complete Setup
3. **预期:** 跳转到 `/workspace` 3. **预期:** 跳转到 `/workspace`
4. 刷新页面不跳回 `/setup` 4. 刷新页面不跳回 `/setup`
#### TC-UI-03: 已初始化后 Login 页面
1. 退出登录后访问 `/login`
2. 输入 admin 邮箱和密码
3. 点击 Login
4. **预期:** 跳转到 `/workspace`
#### TC-UI-04: Setup 密码不匹配 #### TC-UI-04: Setup 密码不匹配
1. 新密码和确认密码不一致 1. 新密码和确认密码不一致
@@ -629,7 +602,7 @@ sqlite3 backend/.deer-flow/data/deerflow.db "SELECT email, password_hash FROM us
#### TC-UI-15: reset_admin 后重新登录 #### TC-UI-15: reset_admin 后重新登录
1. 执行 `cd backend && python -m app.gateway.auth.reset_admin` 1. 执行 `cd backend && python -m app.gateway.auth.reset_admin`
2. `.deer-flow/admin_initial_credentials.txt` 读取新密码登录 2. 使用新密码登录
3. **预期:** 跳转到 `/setup` 页面(`needs_setup` 被重置为 true 3. **预期:** 跳转到 `/setup` 页面(`needs_setup` 被重置为 true
4. 旧 session 已失效 4. 旧 session 已失效
@@ -672,28 +645,18 @@ make install
make dev make dev
``` ```
#### TC-UPG-01: 首次启动等待 admin 初始化 #### TC-UPG-01: 首次启动创建 admin
**预期:** **预期:**
- [ ] 控制台输出 admin 邮箱随机密码 - [ ] 控制台输出 admin 邮箱`admin@deerflow.dev`)和随机密码
- [ ] 访问 `/setup` 可创建第一个 admin
- [ ] 无报错,正常启动 - [ ] 无报错,正常启动
#### TC-UPG-02: 旧 Thread 迁移到 admin #### TC-UPG-02: 旧 Thread 迁移到 admin
```bash ```bash
# 创建第一个 admin
curl -s -X POST http://localhost:2026/api/v1/auth/initialize \
-H "Content-Type: application/json" \
-d '{"email":"admin@example.com","password":"AdminPass1!"}' \
-c cookies.txt
# 重启一次:启动迁移只在已有 admin 的启动路径执行
make stop && make dev
# 登录 admin # 登录 admin
curl -s -X POST http://localhost:2026/api/v1/auth/login/local \ curl -s -X POST http://localhost:2026/api/v1/auth/login/local \
-d "username=admin@example.com&password=AdminPass1!" \ -d "username=admin@deerflow.dev&password=<控制台密码>" \
-c cookies.txt -c cookies.txt
# 查看 thread 列表 # 查看 thread 列表
@@ -707,8 +670,8 @@ curl -s -X POST http://localhost:2026/api/threads/search \
**预期:** **预期:**
- [ ] 返回的 thread 数量 ≥ 旧版创建的数量 - [ ] 返回的 thread 数量 ≥ 旧版创建的数量
- [ ] 控制台日志有 `Migrated N orphan LangGraph thread(s) to admin` - [ ] 控制台日志有 `Migrated N orphaned thread(s) to admin`
- [ ] thread 只对 admin 可见 - [ ] 每个 thread `metadata.owner_id` 都已被设为 admin 的 ID
#### TC-UPG-03: 旧 Thread 内容完整 #### TC-UPG-03: 旧 Thread 内容完整
@@ -720,7 +683,7 @@ curl -s http://localhost:2026/api/threads/<old-thread-id> \
**预期:** **预期:**
- [ ] `metadata.title` 保留原值(如 `old-thread-1` - [ ] `metadata.title` 保留原值(如 `old-thread-1`
- [ ] 响应不回显服务端保留的 `user_id` / `owner_id` - [ ] `metadata.owner_id` 已填充
#### TC-UPG-04: 新用户看不到旧 Thread #### TC-UPG-04: 新用户看不到旧 Thread
@@ -743,19 +706,18 @@ curl -s -X POST http://localhost:2026/api/threads/search \
### 5.3 数据库 Schema 兼容 ### 5.3 数据库 Schema 兼容
#### TC-UPG-05: 无 deerflow.db 时创建 schema 但不创建默认用户 #### TC-UPG-05: 无 users.db 时自动创建
```bash ```bash
ls -la backend/.deer-flow/data/deerflow.db ls -la backend/.deer-flow/users.db
sqlite3 backend/.deer-flow/data/deerflow.db "SELECT COUNT(*) FROM users;"
``` ```
**预期:** 文件存在,`sqlite3` 可查到 `users` 表含 `needs_setup``token_version`;未调用 `/initialize` 前用户数为 0 **预期:** 文件存在,`sqlite3` 可查到 `users` 表含 `needs_setup``token_version`
#### TC-UPG-06: deerflow.db WAL 模式 #### TC-UPG-06: users.db WAL 模式
```bash ```bash
sqlite3 backend/.deer-flow/data/deerflow.db "PRAGMA journal_mode;" sqlite3 backend/.deer-flow/users.db "PRAGMA journal_mode;"
``` ```
**预期:** 返回 `wal` **预期:** 返回 `wal`
@@ -806,9 +768,9 @@ make dev
``` ```
**预期:** **预期:**
- [ ] 服务正常启动(忽略 `deerflow.db`,无 auth 相关代码不报错) - [ ] 服务正常启动(忽略 `users.db`,无 auth 相关代码不报错)
- [ ] 旧对话数据仍然可访问 - [ ] 旧对话数据仍然可访问
- [ ] `deerflow.db` 文件残留但不影响运行 - [ ] `users.db` 文件残留但不影响运行
#### TC-UPG-12: 再次升级到 auth 分支 #### TC-UPG-12: 再次升级到 auth 分支
@@ -819,47 +781,51 @@ make dev
``` ```
**预期:** **预期:**
- [ ] 识别已有 `deerflow.db`,不重新创建 admin - [ ] 识别已有 `users.db`,不重新创建 admin
- [ ] 旧的 admin 账号仍可登录(如果回退期间未删 `deerflow.db` - [ ] 旧的 admin 账号仍可登录(如果回退期间未删 `users.db`
### 5.7 Admin 初始化与 reset_admin ### 5.7 休眠 Admin初始密码未使用/未更改)
> 首次启动生成默认 admin,也不在日志输出密码。忘记密码时走 `reset_admin`,新密码写入 0600 凭据文件 > 首次启动生成 admin + 随机密码,但运维未登录、未改密码
> 密码只在首次启动的控制台闪过一次,后续启动不再显示。
#### TC-UPG-13: 未初始化 admin 时重启不创建默认账号 #### TC-UPG-13: 重启后自动重置密码并打印
```bash ```bash
rm -f backend/.deer-flow/data/deerflow.db # 首次启动,记录密码
rm -f backend/.deer-flow/users.db
make dev make dev
# 控制台输出密码 P0,不登录
make stop make stop
# 隔了几天,再次启动
make dev make dev
curl -s $BASE/api/v1/auth/setup-status | jq . # 控制台输出新密码 P1
``` ```
**预期:** **预期:**
- [ ] 控制台输出密码 - [ ] 控制台输出 `Admin account setup incomplete — password reset`
- [ ] `setup-status` 仍为 `{"needs_setup": true}` - [ ] 输出新密码 P1P0 已失效)
- [ ] 访问 `/setup` 仍可创建第一个 admin - [ ] 用 P1 可以登录,P0 不可以
- [ ] 登录后 `needs_setup=true`,跳转 `/setup`
- [ ] `token_version` 递增(旧 session 如有也失效)
#### TC-UPG-14: 密码丢失 — reset_admin 写入凭据文件 #### TC-UPG-14: 密码丢失 — 无需 CLI,重启即可
```bash ```bash
python -m app.gateway.auth.reset_admin --email admin@example.com # 忘记了控制台密码 → 直接重启服务
ls -la backend/.deer-flow/admin_initial_credentials.txt make stop && make dev
cat backend/.deer-flow/admin_initial_credentials.txt # 控制台自动输出新密码
``` ```
**预期:** **预期:**
- [ ] 命令行只输出凭据文件路径,不输出明文密码 - [ ] 无需 `reset_admin`,重启服务即可拿到新密码
- [ ] 凭据文件权限为 `0600` - [ ] `reset_admin` CLI 仍然可用作手动备选方案
- [ ] 凭据文件包含 email + password 行
- [ ] 该用户下次登录返回 `needs_setup=true`
#### TC-UPG-15: 未初始化 admin 期间普通用户注册策略边界 #### TC-UPG-15: 休眠 admin 期间普通用户注册
```bash ```bash
# admin 尚不存在,普通用户尝试注册 # admin 存在但从未登录,普通用户注册
curl -s -X POST $BASE/api/v1/auth/register \ curl -s -X POST $BASE/api/v1/auth/register \
-H "Content-Type: application/json" \ -H "Content-Type: application/json" \
-d '{"email":"earlybird@example.com","password":"EarlyPass1!"}' \ -d '{"email":"earlybird@example.com","password":"EarlyPass1!"}' \
@@ -867,11 +833,11 @@ curl -s -X POST $BASE/api/v1/auth/register \
``` ```
**预期:** **预期:**
- [ ] 当前代码允许注册普通用户并自动登录201,角色为 `user` - [ ] 注册成功201,角色为 `user`
- [ ] `setup-status` 仍为 `{"needs_setup": true}`,因为 admin 仍不存在 - [ ] 无法提权为 admin
- [ ] 这是一个产品策略边界:若要求“必须先有 admin”,需要在 `/register` 增加 admin-exists gate - [ ] 普通用户的数据与 admin 隔离
#### TC-UPG-16: 普通用户数据与后续 admin 隔离 #### TC-UPG-16: 休眠 admin 不影响后续操作
```bash ```bash
# 普通用户正常创建 thread、发消息 # 普通用户正常创建 thread、发消息
@@ -883,13 +849,14 @@ curl -s -X POST $BASE/api/threads \
-d '{"metadata":{}}' | jq .thread_id -d '{"metadata":{}}' | jq .thread_id
``` ```
**预期:** 普通用户正常创建 thread;后续 admin 创建后,搜索不到该普通用户 thread **预期:** 正常创建,不受休眠 admin 影响
#### TC-UPG-17: reset_admin 完成 Setup #### TC-UPG-17: 休眠 admin 最终完成 Setup
```bash ```bash
# 运维终于登录
curl -s -X POST $BASE/api/v1/auth/login/local \ curl -s -X POST $BASE/api/v1/auth/login/local \
-d "username=admin@example.com&password=<凭据文件密码>" \ -d "username=admin@deerflow.dev&password=<P0或P1>" \
-c admin.txt | jq .needs_setup -c admin.txt | jq .needs_setup
# 预期: true # 预期: true
@@ -899,7 +866,7 @@ curl -s -X POST $BASE/api/v1/auth/change-password \
-b admin.txt \ -b admin.txt \
-H "Content-Type: application/json" \ -H "Content-Type: application/json" \
-H "X-CSRF-Token: $CSRF" \ -H "X-CSRF-Token: $CSRF" \
-d '{"current_password":"<凭据文件密码>","new_password":"AdminFinal1!","new_email":"admin@real.com"}' \ -d '{"current_password":"<密码>","new_password":"AdminFinal1!","new_email":"admin@real.com"}' \
-c admin.txt -c admin.txt
# 验证 # 验证
@@ -909,7 +876,7 @@ curl -s $BASE/api/v1/auth/me -b admin.txt | jq '{email, needs_setup}'
**预期:** **预期:**
- [ ] `email` 变为 `admin@real.com` - [ ] `email` 变为 `admin@real.com`
- [ ] `needs_setup` 变为 `false` - [ ] `needs_setup` 变为 `false`
- [ ] 后续登录使用新密码 - [ ] 后续重启控制台不再有 warning
#### TC-UPG-18: 长期未用后 JWT 密钥轮换 #### TC-UPG-18: 长期未用后 JWT 密钥轮换
@@ -923,8 +890,8 @@ make stop && make dev
**预期:** **预期:**
- [ ] 服务正常启动 - [ ] 服务正常启动
- [ ] 账号密码仍可登录(密码存在 DB,与 JWT 密钥无关) - [ ] 密码仍可登录(密码存在 DB,与 JWT 密钥无关)
- [ ] 旧的 JWT token 失效(密钥变了签名不匹配) - [ ] 旧的 JWT token 失效(密钥变了签名不匹配)— 但因为从未登录过也没有旧 token
--- ---
@@ -943,7 +910,7 @@ for i in 1 2 3; do
done done
# 检查 admin 数量 # 检查 admin 数量
sqlite3 backend/.deer-flow/data/deerflow.db \ sqlite3 backend/.deer-flow/users.db \
"SELECT COUNT(*) FROM users WHERE system_role='admin';" "SELECT COUNT(*) FROM users WHERE system_role='admin';"
``` ```
@@ -1088,7 +1055,7 @@ curl -s -X POST $BASE/api/v1/auth/register \
wait wait
# 检查用户数 # 检查用户数
sqlite3 backend/.deer-flow/data/deerflow.db \ sqlite3 backend/.deer-flow/users.db \
"SELECT COUNT(*) FROM users WHERE email='race@example.com';" "SELECT COUNT(*) FROM users WHERE email='race@example.com';"
``` ```
@@ -1198,16 +1165,13 @@ curl -s -w "%{http_code}" -X DELETE "$BASE/api/threads/$TID" \
```bash ```bash
cd backend cd backend
python -m app.gateway.auth.reset_admin python -m app.gateway.auth.reset_admin
cp .deer-flow/admin_initial_credentials.txt /tmp/deerflow-reset-p1.txt # 记录密码 P1
P1=$(awk -F': ' '/^password:/ {print $2}' /tmp/deerflow-reset-p1.txt)
python -m app.gateway.auth.reset_admin python -m app.gateway.auth.reset_admin
cp .deer-flow/admin_initial_credentials.txt /tmp/deerflow-reset-p2.txt # 记录密码 P2
P2=$(awk -F': ' '/^password:/ {print $2}' /tmp/deerflow-reset-p2.txt)
``` ```
**预期:** **预期:**
- [ ] `.deer-flow/admin_initial_credentials.txt` 每次都会被重写,文件权限为 `0600`
- [ ] P1 ≠ P2(每次生成新随机密码) - [ ] P1 ≠ P2(每次生成新随机密码)
- [ ] P1 不可用,只有 P2 有效 - [ ] P1 不可用,只有 P2 有效
- [ ] `token_version` 递增了 2 - [ ] `token_version` 递增了 2
@@ -1232,11 +1196,21 @@ P2=$(awk -F': ' '/^password:/ {print $2}' /tmp/deerflow-reset-p2.txt)
## 七、模式差异测试 ## 七、模式差异测试
> 以下用 `GW=http://localhost:8001` 表示直连 Gateway`BASE=http://localhost:2026` 表示经 nginx。 > 以下用 `GW=http://localhost:8001` 表示直连 Gateway`BASE=http://localhost:2026` 表示经 nginx。
> 标准启动命令:`make dev`(或 `./scripts/serve.sh --dev`)。 > Gateway 模式启动命令:`make dev-pro`(或 `./scripts/serve.sh --dev --gateway`)。
### 7.1 标准启动模式 ### 7.1 标准模式独有
#### TC-MODE-01: Gateway AuthMiddleware 的 token_version 检查 > 启动命令:`make dev`(或 `./scripts/serve.sh --dev`
#### TC-MODE-01: LangGraph Server 独立运行,需 cookie
```bash
# 无 cookie 访问 LangGraph
curl -s -w "%{http_code}" -o /dev/null $BASE/api/langgraph/threads/search
# 预期: 403LangGraph auth handler 拒绝)
```
#### TC-MODE-02: LangGraph auth 的 token_version 检查
```bash ```bash
# 登录拿 cookie # 登录拿 cookie
@@ -1249,9 +1223,9 @@ curl -s -X POST $BASE/api/v1/auth/change-password \
-b cookies.txt -H "Content-Type: application/json" -H "X-CSRF-Token: $CSRF" \ -b cookies.txt -H "Content-Type: application/json" -H "X-CSRF-Token: $CSRF" \
-d '{"current_password":"正确密码","new_password":"NewPass1!"}' -c new_cookies.txt -d '{"current_password":"正确密码","new_password":"NewPass1!"}' -c new_cookies.txt
# 用旧 cookie 访问 LangGraph-compatible 路由 # 用旧 cookie 访问 LangGraph
curl -s -w "%{http_code}" $BASE/api/langgraph/threads/search -b cookies.txt curl -s -w "%{http_code}" $BASE/api/langgraph/threads/search -b cookies.txt
# 预期: 401token_version 不匹配) # 预期: 403token_version 不匹配)
# 用新 cookie 访问 # 用新 cookie 访问
CSRF2=$(grep csrf_token new_cookies.txt | awk '{print $NF}') CSRF2=$(grep csrf_token new_cookies.txt | awk '{print $NF}')
@@ -1260,7 +1234,7 @@ curl -s -w "%{http_code}" -X POST $BASE/api/langgraph/threads/search \
# 预期: 200 # 预期: 200
``` ```
#### TC-MODE-02: Gateway owner filter 隔离 #### TC-MODE-03: LangGraph auth 的 owner filter 隔离
```bash ```bash
# user1 创建 thread # user1 创建 thread
@@ -1285,9 +1259,18 @@ print('OK: user2 sees', len(threads), 'threads, none belong to user1')
" "
``` ```
#### TC-MODE-03: 所有请求经 AuthMiddleware ### 7.2 Gateway 模式独有
> 启动命令:`make dev-pro`(或 `./scripts/serve.sh --dev --gateway`
> 无 LangGraph Server 进程,agent runtime 嵌入 Gateway。
#### TC-MODE-04: 所有请求经 AuthMiddleware
```bash ```bash
# 确认 LangGraph Server 未运行
curl -s -w "%{http_code}" -o /dev/null http://localhost:2024/ok
# 预期: 000(连接被拒)
# Gateway API 受保护 # Gateway API 受保护
curl -s -w "%{http_code}" -o /dev/null $BASE/api/models curl -s -w "%{http_code}" -o /dev/null $BASE/api/models
# 预期: 401 # 预期: 401
@@ -1298,7 +1281,7 @@ curl -s -w "%{http_code}" -o /dev/null -X POST $BASE/api/langgraph/threads/searc
# 预期: 401 # 预期: 401
``` ```
#### TC-MODE-04: 标准模式下完整 auth 流程 #### TC-MODE-05: Gateway 模式下完整 auth 流程
```bash ```bash
# 登录 # 登录
@@ -1313,7 +1296,7 @@ curl -s -X POST $BASE/api/langgraph/threads \
-d '{"metadata":{}}' | python3 -c "import sys,json; print(json.load(sys.stdin)['thread_id'])" -d '{"metadata":{}}' | python3 -c "import sys,json; print(json.load(sys.stdin)['thread_id'])"
# 预期: 返回 thread_id # 预期: 返回 thread_id
# CSRF 保护(CSRFMiddleware 覆盖所有 Gateway 路由) # CSRF 保护(Gateway 模式下 CSRFMiddleware 直接覆盖所有路由)
curl -s -w "%{http_code}" -o /dev/null -X POST $BASE/api/langgraph/threads \ curl -s -w "%{http_code}" -o /dev/null -X POST $BASE/api/langgraph/threads \
-b cookies.txt -H "Content-Type: application/json" -d '{"metadata":{}}' -b cookies.txt -H "Content-Type: application/json" -d '{"metadata":{}}'
# 预期: 403CSRF token missing # 预期: 403CSRF token missing
@@ -1341,8 +1324,7 @@ done
```bash ```bash
GW=http://localhost:8001 GW=http://localhost:8001
for path in /health /api/v1/auth/setup-status /api/v1/auth/login/local \ for path in /health /api/v1/auth/setup-status /api/v1/auth/login/local /api/v1/auth/register; do
/api/v1/auth/register /api/v1/auth/initialize /api/v1/auth/logout; do
echo "$path: $(curl -s -w '%{http_code}' -o /dev/null $GW$path)" echo "$path: $(curl -s -w '%{http_code}' -o /dev/null $GW$path)"
done done
# 预期: 200 或 405/422(方法不对但不是 401 # 预期: 200 或 405/422(方法不对但不是 401
@@ -1412,14 +1394,14 @@ done
### 7.4 Docker 部署 ### 7.4 Docker 部署
> 启动命令:`./scripts/deploy.sh` > 启动命令:`./scripts/deploy.sh`(标准)或 `./scripts/deploy.sh --gateway`Gateway 模式)
> Docker Compose 文件:`docker/docker-compose.yaml` > Docker Compose 文件:`docker/docker-compose.yaml`
> >
> 前置条件: > 前置条件:
> - `.env` 中设置 `AUTH_JWT_SECRET`(否则每次容器重启 session 全部失效) > - `.env` 中设置 `AUTH_JWT_SECRET`(否则每次容器重启 session 全部失效)
> - `DEER_FLOW_HOME` 挂载到宿主机目录(持久化 `deerflow.db` > - `DEER_FLOW_HOME` 挂载到宿主机目录(持久化 `users.db`
#### TC-DOCKER-01: deerflow.db 通过 volume 持久化 #### TC-DOCKER-01: users.db 通过 volume 持久化
```bash ```bash
# 启动容器 # 启动容器
@@ -1434,13 +1416,13 @@ curl -s -X POST $BASE/api/v1/auth/register \
-H "Content-Type: application/json" \ -H "Content-Type: application/json" \
-d '{"email":"docker-test@example.com","password":"DockerTest1!"}' -w "\nHTTP %{http_code}" -d '{"email":"docker-test@example.com","password":"DockerTest1!"}' -w "\nHTTP %{http_code}"
# 检查宿主机上的 deerflow.db # 检查宿主机上的 users.db
ls -la ${DEER_FLOW_HOME:-backend/.deer-flow}/data/deerflow.db ls -la ${DEER_FLOW_HOME:-backend/.deer-flow}/users.db
sqlite3 ${DEER_FLOW_HOME:-backend/.deer-flow}/data/deerflow.db \ sqlite3 ${DEER_FLOW_HOME:-backend/.deer-flow}/users.db \
"SELECT email FROM users WHERE email='docker-test@example.com';" "SELECT email FROM users WHERE email='docker-test@example.com';"
``` ```
**预期:** deerflow.db 在宿主机 `DEER_FLOW_HOME` 目录中,查询可见刚注册的用户。 **预期:** users.db 在宿主机 `DEER_FLOW_HOME` 目录中,查询可见刚注册的用户。
#### TC-DOCKER-02: 重启容器后 session 保持 #### TC-DOCKER-02: 重启容器后 session 保持
@@ -1484,24 +1466,22 @@ done
**已知限制:** In-process rate limiter 不跨 worker 共享。生产环境如需精确限速,需要 Redis 等外部存储。 **已知限制:** In-process rate limiter 不跨 worker 共享。生产环境如需精确限速,需要 Redis 等外部存储。
#### TC-DOCKER-04: IM 渠道使用内部认证 #### TC-DOCKER-04: IM 渠道不经过 auth
```bash ```bash
# IM 渠道(Feishu/Slack/Telegram)在 gateway 容器内部通过 LangGraph SDK 调 Gateway # IM 渠道(Feishu/Slack/Telegram)在 gateway 容器内部通过 LangGraph SDK 通信
# 请求携带 process-local internal auth header,并带匹配的 CSRF cookie/header # 不走 nginx,不经过 AuthMiddleware
# 验证方式:检查 gateway 日志中 channel manager 的请求不包含 auth 错误 # 验证方式:检查 gateway 日志中 channel manager 的请求不包含 auth 错误
docker logs deer-flow-gateway 2>&1 | grep -E "ChannelManager|channel" | head -10 docker logs deer-flow-gateway 2>&1 | grep -E "ChannelManager|channel" | head -10
``` ```
**预期:** 无 auth 相关错误。渠道不依赖浏览器 cookie;服务端通过内部认证头把请求归入 `default` 用户桶 **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: reset_admin 密码写入 0600 凭证文件(不再走日志) #### TC-DOCKER-05: admin 密码写入 0600 凭证文件(不再走日志)
```bash ```bash
# 首次启动不会自动生成 admin 密码。先重置已有 admin,凭据文件写在挂载到宿主机的 DEER_FLOW_HOME 下 # 凭证文件写在挂载到宿主机的 DEER_FLOW_HOME 下
docker exec deer-flow-gateway python -m app.gateway.auth.reset_admin --email docker-test@example.com
ls -la ${DEER_FLOW_HOME:-backend/.deer-flow}/admin_initial_credentials.txt ls -la ${DEER_FLOW_HOME:-backend/.deer-flow}/admin_initial_credentials.txt
# 预期文件权限: -rw------- (0600) # 预期文件权限: -rw------- (0600)
@@ -1521,26 +1501,25 @@ docker logs deer-flow-gateway 2>&1 | grep -iE "Password: .{15,}" && echo "FAIL:
- 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 - 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) - `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: Docker 部署 #### TC-DOCKER-06: Gateway 模式 Docker 部署
```bash ```bash
# 标准 Docker 模式:runtime 嵌入 gateway 容器 # Gateway 模式:无 langgraph 容器
./scripts/deploy.sh ./scripts/deploy.sh --gateway
sleep 15 sleep 15
# 确认 gateway 容器存在 # 确认 langgraph 容器存在
docker ps --filter name=deer-flow-gateway --format '{{.Names}}' docker ps --filter name=deer-flow-langgraph --format '{{.Names}}' | wc -l
# 预期: deer-flow-gateway # 预期: 0
# auth 流程正常:未登录受保护接口返回 401 # auth 流程正常
curl -s -w "%{http_code}" -o /dev/null $BASE/api/models curl -s -w "%{http_code}" -o /dev/null $BASE/api/models
# 预期: 401 # 预期: 401
curl -s -X POST $BASE/api/v1/auth/initialize \ curl -s -X POST $BASE/api/v1/auth/login/local \
-H "Content-Type: application/json" \ -d "username=admin@deerflow.dev&password=<日志密码>" \
-d '{"email":"admin@example.com","password":"AdminPass1!"}' \
-c cookies.txt -w "\nHTTP %{http_code}" -c cookies.txt -w "\nHTTP %{http_code}"
# 预期: 201 # 预期: 200
``` ```
### 7.4 补充边界用例 ### 7.4 补充边界用例
@@ -1608,15 +1587,13 @@ curl -s -D - -X POST $BASE/api/v1/auth/login/local \
#### TC-EDGE-05: HTTP 无 max_age / HTTPS 有 max_age #### TC-EDGE-05: HTTP 无 max_age / HTTPS 有 max_age
```bash ```bash
GW=http://localhost:8001
# HTTP # HTTP
curl -s -D - -X POST $GW/api/v1/auth/login/local \ curl -s -D - -X POST $BASE/api/v1/auth/login/local \
-d "username=admin@example.com&password=正确密码" 2>/dev/null \ -d "username=admin@example.com&password=正确密码" 2>/dev/null \
| grep "access_token=" | grep -oi "max-age=[0-9]*" || echo "NO max-age (HTTP session cookie)" | grep "access_token=" | grep -oi "max-age=[0-9]*" || echo "NO max-age (HTTP session cookie)"
# HTTPS:直连 Gateway 才能用 X-Forwarded-Proto 模拟 HTTPSnginx 会覆盖该 header # HTTPS
curl -s -D - -X POST $GW/api/v1/auth/login/local \ curl -s -D - -X POST $BASE/api/v1/auth/login/local \
-H "X-Forwarded-Proto: https" \ -H "X-Forwarded-Proto: https" \
-d "username=admin@example.com&password=正确密码" 2>/dev/null \ -d "username=admin@example.com&password=正确密码" 2>/dev/null \
| grep "access_token=" | grep -oi "max-age=[0-9]*" | grep "access_token=" | grep -oi "max-age=[0-9]*"
@@ -1735,10 +1712,10 @@ curl -s -X POST $BASE/api/threads \
-b cookies.txt \ -b cookies.txt \
-H "Content-Type: application/json" \ -H "Content-Type: application/json" \
-H "X-CSRF-Token: $CSRF" \ -H "X-CSRF-Token: $CSRF" \
-d '{"metadata":{"owner_id":"victim-user-id","user_id":"victim-user-id"}}' | jq .metadata -d '{"metadata":{"owner_id":"victim-user-id"}}' | jq .metadata.owner_id
``` ```
**预期:** 返回的 `metadata` 不包含 `owner_id` `user_id`真实所有权写入 `threads_meta.user_id`,不从客户端 metadata 接收,也不通过 metadata 回显 **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 #### 7.5.6 HTTP Method 探测
@@ -1819,6 +1796,6 @@ cd backend && PYTHONPATH=. uv run pytest \
# 核心接口冒烟 # 核心接口冒烟
curl -s $BASE/health # 200 curl -s $BASE/health # 200
curl -s $BASE/api/models # 401 (无 cookie) curl -s $BASE/api/models # 401 (无 cookie)
curl -s $BASE/api/v1/auth/setup-status # 200 curl -s -X POST $BASE/api/v1/auth/setup-status # 200
curl -s $BASE/api/v1/auth/me -b cookies.txt # 200 (有 cookie) curl -s $BASE/api/v1/auth/me -b cookies.txt # 200 (有 cookie)
``` ```
+27 -38
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@@ -2,16 +2,13 @@
DeerFlow 内置了认证模块。本文档面向从无认证版本升级的用户。 DeerFlow 内置了认证模块。本文档面向从无认证版本升级的用户。
完整设计见 [AUTH_DESIGN.md](AUTH_DESIGN.md)。
## 核心概念 ## 核心概念
认证模块采用**始终强制**策略: 认证模块采用**始终强制**策略:
- 首次启动时不会自动创建账号;首次访问 `/setup` 时由操作者创建第一个 admin 账号 - 首次启动时自动创建 admin 账号,随机密码打印到控制台日志
- 认证从一开始就是强制的,无竞争窗口 - 认证从一开始就是强制的,无竞争窗口
- 已有 admin 后,服务启动时会把历史对话(升级前创建且缺少 `user_id` 的 thread)迁移到 admin 名下 - 历史对话(升级前创建的 thread自动迁移到 admin 名下
- 新数据按用户隔离:thread、workspace/uploads/outputs、memory、自定义 agent 都归属当前用户
## 升级步骤 ## 升级步骤
@@ -28,41 +25,39 @@ cd backend && make install
make dev make dev
``` ```
如果没有 admin 账号,控制台只会提示 控制台会输出
``` ```
============================================================ ============================================================
First boot detected — no admin account exists. Admin account created on first boot
Visit /setup to complete admin account creation. Email: admin@deerflow.dev
Password: aB3xK9mN_pQ7rT2w
Change it after login: Settings → Account
============================================================ ============================================================
``` ```
首次启动不会在日志里打印随机密码,也不会写入默认 admin。这样避免启动日志泄露凭据,也避免在操作者创建账号前出现可被猜测的默认身份 如果未登录就重启了服务,不用担心——只要 setup 未完成,每次启动都会重置密码并重新打印到控制台
### 3. 创建 admin ### 3. 登录
访问 `http://localhost:2026/setup`,填写邮箱和密码创建第一个 admin 账号。创建成功后会自动登录并进入 workspace 访问 `http://localhost:2026/login`,使用控制台输出的邮箱和密码登录
如果这是从无认证版本升级,创建 admin 后重启一次服务,让启动迁移把缺少 `user_id` 的历史 thread 归属到 admin。 ### 4. 修改密码
### 4. 登录 登录后进入 Settings → Account → Change Password。
后续访问 `http://localhost:2026/login`,使用已创建的邮箱和密码登录。
### 5. 添加用户(可选) ### 5. 添加用户(可选)
其他用户通过 `/login` 页面注册,自动获得 **user** 角色。每个用户只能看到自己的对话、上传文件、输出文件、memory 和自定义 agent 其他用户通过 `/login` 页面注册,自动获得 **user** 角色。每个用户只能看到自己的对话。
## 安全机制 ## 安全机制
| 机制 | 说明 | | 机制 | 说明 |
|------|------| |------|------|
| JWT HttpOnly Cookie | Token 不暴露给 JavaScript,防止 XSS 窃取 | | JWT HttpOnly Cookie | Token 不暴露给 JavaScript,防止 XSS 窃取 |
| CSRF Double Submit Cookie | 受保护的 POST/PUT/PATCH/DELETE 请求需携带 `X-CSRF-Token`;登录/注册/初始化/登出走 auth 端点 Origin 校验 | | CSRF Double Submit Cookie | 所有 POST/PUT/DELETE 请求需携带 `X-CSRF-Token` |
| bcrypt 密码哈希 | 密码不以明文存储 | | bcrypt 密码哈希 | 密码不以明文存储 |
| Thread owner filter | `threads_meta.user_id` 由服务端认证上下文写入,搜索、读取、更新、删除默认按当前用户过滤 | | 多租户隔离 | 用户只能访问自己的 thread |
| 文件系统隔离 | 线程数据写入 `{base_dir}/users/{user_id}/threads/{thread_id}/user-data/`sandbox 内统一映射为 `/mnt/user-data/` |
| Memory / agent 隔离 | 用户 memory 和自定义 agent 写入 `{base_dir}/users/{user_id}/...`;旧共享 agent 只作为只读兼容回退 |
| HTTPS 自适应 | 检测 `x-forwarded-proto`,自动设置 `Secure` cookie 标志 | | HTTPS 自适应 | 检测 `x-forwarded-proto`,自动设置 `Secure` cookie 标志 |
## 常见操作 ## 常见操作
@@ -79,27 +74,23 @@ python -m app.gateway.auth.reset_admin
python -m app.gateway.auth.reset_admin --email user@example.com python -m app.gateway.auth.reset_admin --email user@example.com
``` ```
新的随机密码写入 `.deer-flow/admin_initial_credentials.txt`,文件权限为 `0600`。命令行只输出文件路径,不输出明文密码 输出新的随机密码。
### 完全重置 ### 完全重置
删除统一 SQLite 数据库,重启后重新访问 `/setup` 创建新 admin 删除用户数据库,重启后自动创建新 admin
```bash ```bash
rm -f backend/.deer-flow/data/deerflow.db rm -f backend/.deer-flow/users.db
# 重启服务后访问 http://localhost:2026/setup # 重启服务,控制台输出新密码
``` ```
## 数据存储 ## 数据存储
| 文件 | 内容 | | 文件 | 内容 |
|------|------| |------|------|
| `.deer-flow/data/deerflow.db` | 统一 SQLite 数据库(users、threads_meta、runs、feedback 等应用数据 | | `.deer-flow/users.db` | SQLite 用户数据库(密码哈希、角色 |
| `.deer-flow/users/{user_id}/threads/{thread_id}/user-data/` | 用户线程的 workspace、uploads、outputs | | `.env` 中的 `AUTH_JWT_SECRET` | JWT 签名密钥(未设置时自动生成临时密钥,重启后 session 失效) |
| `.deer-flow/users/{user_id}/memory.json` | 用户级 memory |
| `.deer-flow/users/{user_id}/agents/{agent_name}/` | 用户自定义 agent 配置、SOUL 和 agent memory |
| `.deer-flow/admin_initial_credentials.txt` | `reset_admin` 生成的新凭据文件(0600,读完应删除) |
| `.env` 中的 `AUTH_JWT_SECRET` | JWT 签名密钥(未设置时自动生成并持久化到 `.deer-flow/.jwt_secret`,重启后 session 保持) |
### 生产环境建议 ### 生产环境建议
@@ -120,21 +111,19 @@ python -c "import secrets; print(secrets.token_urlsafe(32))"
| `/api/v1/auth/me` | GET | 获取当前用户信息 | | `/api/v1/auth/me` | GET | 获取当前用户信息 |
| `/api/v1/auth/change-password` | POST | 修改密码 | | `/api/v1/auth/change-password` | POST | 修改密码 |
| `/api/v1/auth/setup-status` | GET | 检查 admin 是否存在 | | `/api/v1/auth/setup-status` | GET | 检查 admin 是否存在 |
| `/api/v1/auth/initialize` | POST | 首次初始化第一个 admin(仅无 admin 时可调用) |
## 兼容性 ## 兼容性
- **本地开发**`make dev`):Gateway embedded runtime 完全兼容;无 admin 时访问 `/setup` 初始化 - **标准模式**`make dev`):完全兼容admin 自动创建
- **Gateway embedded runtime**:标准脚本、Docker dev 和生产部署均通过 Gateway 提供认证与 LangGraph-compatible API - **Gateway 模式**`make dev-pro`):完全兼容
- **Docker 部署**:完全兼容,`.deer-flow/data/deerflow.db` 需持久化卷挂载 - **Docker 部署**:完全兼容,`.deer-flow/users.db` 需持久化卷挂载
- **IM 渠道**Feishu/Slack/Telegram):通过 Gateway 内部认证通信,使用 `default` 用户桶 - **IM 渠道**Feishu/Slack/Telegram):通过 LangGraph SDK 通信,不经过认证层
- **DeerFlowClient**(嵌入式):不经过 HTTP,不受认证影响 - **DeerFlowClient**(嵌入式):不经过 HTTP,不受认证影响
## 故障排查 ## 故障排查
| 症状 | 原因 | 解决 | | 症状 | 原因 | 解决 |
|------|------|------| |------|------|------|
| 启动后没看到密码 | 当前实现不在启动日志输出密码 | 首次安装访问 `/setup`;忘记密码用 `reset_admin` | | 启动后没看到密码 | admin 已存在(非首次启动) | 用 `reset_admin` 重置,或删 `users.db` |
| `/login` 自动跳到 `/setup` | 系统还没有 admin | 在 `/setup` 创建第一个 admin |
| 登录后 POST 返回 403 | CSRF token 缺失 | 确认前端已更新 | | 登录后 POST 返回 403 | CSRF token 缺失 | 确认前端已更新 |
| 重启后需要重新登录 | `.jwt_secret` 文件被删除且 `.env` 未设置 `AUTH_JWT_SECRET` | 在 `.env` 中设置固定密钥 | | 重启后需要重新登录 | `AUTH_JWT_SECRET` 未持久化 | 在 `.env` 中设置固定密钥 |
-154
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@@ -1,154 +0,0 @@
# Blocking IO detection usage and maintenance
This document describes how to use and maintain DeerFlow backend blocking-IO
detection for async event-loop safety.
The goal is narrow: find and prevent synchronous IO from blocking backend
async event-loop paths. Static and runtime detection are complementary, but
they have different jobs.
## Static detector
The static detector is the discovery tool. It scans backend source code and
reports candidate blocking-IO call sites that may need human review.
Run it from the repository root:
```bash
make detect-blocking-io
```
Or from `backend/`:
```bash
make detect-blocking-io
```
The report is written to:
```text
.deer-flow/blocking-io-findings.json
```
Use this output for review and triage. A static finding is a candidate, not
proof that production blocks the event loop at runtime. The current static
rules are intentionally broad; prefer triaging existing output before adding
new static rules.
Add a static rule only when review finds a recurring high-risk blocking
pattern that is invisible to the current detector.
## Runtime detector
The runtime detector is the CI regression guard. It uses Blockbuster to fail a
focused test when code under `app.*` or `deerflow.*` performs blocking IO on
the asyncio event-loop thread.
Run it from `backend/`:
```bash
make test-blocking-io
```
The runtime gate starts from confirmed production bugs and protects those
paths from regressing. It does not prove that the entire backend is free of
blocking IO; it only covers the production paths exercised by
`backend/tests/blocking_io/`.
## Maintenance workflow
Use the static detector to find candidates, then use review to decide which
async production paths are worth protecting in CI.
The normal workflow is:
1. Run the static detector to find backend blocking-IO candidates.
2. Use human review to pick high-risk production async paths.
3. Add or update a focused runtime anchor in `backend/tests/blocking_io/`.
4. Let CI prevent that path from regressing.
Runtime detection has two maintenance paths.
### Add a runtime rule
Add a runtime rule when Blockbuster's default rules do not cover a generic
blocking primitive used by production code.
Rules belong in:
```text
backend/tests/support/detectors/blocking_io_runtime.py
```
Add them to `_PROJECT_BLOCKING_RULES`, not directly inside individual tests.
Keeping rules centralized makes it clear which extra primitives DeerFlow
expects Blockbuster to catch.
Example shape:
```python
import subprocess
from blockbuster import BlockBusterFunction
_PROJECT_BLOCKING_RULES = (
(
"subprocess.Popen.__init__",
BlockBusterFunction(
subprocess.Popen,
"__init__",
scanned_modules=["app", "deerflow"],
),
),
)
```
Do not add a runtime rule just because a business path is not tested. A rule
only expands what Blockbuster can intercept after code runs.
### Add a runtime anchor
Add a runtime anchor when a high-risk async production path should be protected
by CI but no existing `backend/tests/blocking_io/` test executes it.
Anchors belong in:
```text
backend/tests/blocking_io/
```
A good anchor should:
- Call the real production async entry point.
- Avoid bypassing the blocking surface with test-only `asyncio.to_thread`
wrappers.
- Use real local filesystem inputs when the bug shape is filesystem IO.
- Mock only the external dependency boundary, such as a network service or
third-party saver class.
- Fail if a future change moves the blocking operation back onto the event
loop.
Avoid testing only the low-level helper unless that helper is the production
async entry point. The runtime gate is most useful when it protects the caller
that production actually executes.
## Current runtime coverage
The runtime anchors protect confirmed blocking-IO bug shapes:
- SQLite checkpointer setup, including path resolution and parent-directory
creation.
- Subagent skill metadata loading through `SubagentExecutor._load_skills()`.
- `JsonlRunEventStore` async API (`put` / `list_*` / `delete_*`): the JSONL
run-event backend offloads its synchronous file IO via `asyncio.to_thread`
(fix #3084); this anchor drives the real async API under the gate so any
blocking IO reintroduced on the loop fails, not only removal of one
`to_thread` call.
- `UploadsMiddleware.before_agent` uploads-directory scan: a sync-only middleware
hook runs on the event loop under async graph execution, so the scan is
offloaded via `abefore_agent` + `run_in_executor`.
- Gate health checks: Blockbuster catches unoffloaded calls, opt-out works, and
patches are restored after exceptions.
As static detection and review identify more high-risk async paths, add new
runtime anchors incrementally.
+12 -62
View File
@@ -36,7 +36,6 @@ models:
- OpenAI (`langchain_openai:ChatOpenAI`) - OpenAI (`langchain_openai:ChatOpenAI`)
- Anthropic (`langchain_anthropic:ChatAnthropic`) - Anthropic (`langchain_anthropic:ChatAnthropic`)
- DeepSeek (`langchain_deepseek:ChatDeepSeek`) - DeepSeek (`langchain_deepseek:ChatDeepSeek`)
- Xiaomi MiMo (`deerflow.models.patched_mimo:PatchedChatMiMo`)
- Claude Code OAuth (`deerflow.models.claude_provider:ClaudeChatModel`) - Claude Code OAuth (`deerflow.models.claude_provider:ClaudeChatModel`)
- Codex CLI (`deerflow.models.openai_codex_provider:CodexChatModel`) - Codex CLI (`deerflow.models.openai_codex_provider:CodexChatModel`)
- Any LangChain-compatible provider - Any LangChain-compatible provider
@@ -95,30 +94,20 @@ models:
thinking: thinking:
type: enabled type: enabled
- name: minimax-m3 - name: minimax-m2.5
display_name: MiniMax M3 display_name: MiniMax M2.5
use: langchain_openai:ChatOpenAI use: langchain_openai:ChatOpenAI
model: MiniMax-M3 model: MiniMax-M2.5
api_key: $MINIMAX_API_KEY api_key: $MINIMAX_API_KEY
base_url: https://api.minimax.io/v1 base_url: https://api.minimax.io/v1
max_tokens: 4096 max_tokens: 4096
temperature: 1.0 # MiniMax requires temperature in (0.0, 1.0] temperature: 1.0 # MiniMax requires temperature in (0.0, 1.0]
supports_vision: true supports_vision: true
- name: minimax-m2.7 - name: minimax-m2.5-highspeed
display_name: MiniMax M2.7 display_name: MiniMax M2.5 Highspeed
use: langchain_openai:ChatOpenAI use: langchain_openai:ChatOpenAI
model: MiniMax-M2.7 model: MiniMax-M2.5-highspeed
api_key: $MINIMAX_API_KEY
base_url: https://api.minimax.io/v1
max_tokens: 4096
temperature: 1.0 # MiniMax requires temperature in (0.0, 1.0]
supports_vision: true
- name: minimax-m2.7-highspeed
display_name: MiniMax M2.7 Highspeed
use: langchain_openai:ChatOpenAI
model: MiniMax-M2.7-highspeed
api_key: $MINIMAX_API_KEY api_key: $MINIMAX_API_KEY
base_url: https://api.minimax.io/v1 base_url: https://api.minimax.io/v1
max_tokens: 4096 max_tokens: 4096
@@ -177,37 +166,6 @@ models:
For Gemini accessed **without** thinking (e.g. via OpenRouter where thinking is not activated), the plain `langchain_openai:ChatOpenAI` with `supports_thinking: false` is sufficient and no patch is needed. For Gemini accessed **without** thinking (e.g. via OpenRouter where thinking is not activated), the plain `langchain_openai:ChatOpenAI` with `supports_thinking: false` is sufficient and no patch is needed.
**MiMo with thinking via OpenAI-compatible API**:
MiMo returns `reasoning_content` on assistant messages in thinking mode. In multi-turn agent conversations with tool calls, subsequent requests must preserve that historical `reasoning_content` on assistant messages or the MiMo API can return HTTP 400. Standard `langchain_openai:ChatOpenAI` drops this provider-specific field, so use `deerflow.models.patched_mimo:PatchedChatMiMo`:
For pay-as-you-go API keys (`sk-...`), use `https://api.xiaomimimo.com/v1`. For Token Plan keys (`tp-...`), use the regional Token Plan Base URL shown in the MiMo console, such as `https://token-plan-cn.xiaomimimo.com/v1`. MiMo documents these key types as separate and non-interchangeable.
`PatchedChatMiMo` is model-id agnostic. Use it for every MiMo thinking model entry you configure, including model entries referenced by `subagents.*.model` overrides (for example `mimo-v2.5-pro`, `mimo-v2.5`, `mimo-v2-pro`, `mimo-v2-omni`, or `mimo-v2-flash`).
```yaml
models:
- name: mimo-v2.5-pro
display_name: MiMo V2.5 Pro
use: deerflow.models.patched_mimo:PatchedChatMiMo
model: mimo-v2.5-pro
api_key: $MIMO_API_KEY
base_url: https://api.xiaomimimo.com/v1
max_tokens: 8192
supports_thinking: true
supports_vision: false
when_thinking_enabled:
extra_body:
thinking:
type: enabled
when_thinking_disabled:
extra_body:
thinking:
type: disabled
```
`PatchedChatMiMo` preserves MiMo's `choices[].message.reasoning_content`, streaming `delta.reasoning_content`, and request-history assistant `reasoning_content` fields. It does not reuse the DeepSeek provider.
### Tool Groups ### Tool Groups
Organize tools into logical groups: Organize tools into logical groups:
@@ -301,8 +259,6 @@ sandbox:
When you configure `sandbox.mounts`, DeerFlow exposes those `container_path` values in the agent prompt so the agent can discover and operate on mounted directories directly instead of assuming everything must live under `/mnt/user-data`. When you configure `sandbox.mounts`, DeerFlow exposes those `container_path` values in the agent prompt so the agent can discover and operate on mounted directories directly instead of assuming everything must live under `/mnt/user-data`.
For bare-metal Docker sandbox runs that use localhost, DeerFlow binds the sandbox HTTP port to `127.0.0.1` by default so it is not exposed on every host interface. Docker-outside-of-Docker deployments that connect through `host.docker.internal` keep the broad legacy bind for compatibility. Set `DEER_FLOW_SANDBOX_BIND_HOST` explicitly if your deployment needs a different bind address.
### Skills ### Skills
Configure the skills directory for specialized workflows: Configure the skills directory for specialized workflows:
@@ -361,19 +317,13 @@ models:
- `OPENAI_API_KEY` - OpenAI API key - `OPENAI_API_KEY` - OpenAI API key
- `ANTHROPIC_API_KEY` - Anthropic API key - `ANTHROPIC_API_KEY` - Anthropic API key
- `DEEPSEEK_API_KEY` - DeepSeek API key - `DEEPSEEK_API_KEY` - DeepSeek API key
- `MIMO_API_KEY` - Xiaomi MiMo API key
- `NOVITA_API_KEY` - Novita API key (OpenAI-compatible endpoint) - `NOVITA_API_KEY` - Novita API key (OpenAI-compatible endpoint)
- `TAVILY_API_KEY` - Tavily search API key - `TAVILY_API_KEY` - Tavily search API key
- `DEER_FLOW_PROJECT_ROOT` - Project root for relative runtime paths
- `DEER_FLOW_CONFIG_PATH` - Custom config file path - `DEER_FLOW_CONFIG_PATH` - Custom config file path
- `DEER_FLOW_EXTENSIONS_CONFIG_PATH` - Custom extensions config file path
- `DEER_FLOW_HOME` - Runtime state directory (defaults to `.deer-flow` under the project root)
- `DEER_FLOW_SKILLS_PATH` - Skills directory when `skills.path` is omitted
- `GATEWAY_ENABLE_DOCS` - Set to `false` to disable Swagger UI (`/docs`), ReDoc (`/redoc`), and OpenAPI schema (`/openapi.json`) endpoints (default: `true`)
## Configuration Location ## Configuration Location
The configuration file should be placed in the **project root directory** (`deer-flow/config.yaml`). Set `DEER_FLOW_PROJECT_ROOT` when the process may start from another working directory, or set `DEER_FLOW_CONFIG_PATH` to point at a specific file. The configuration file should be placed in the **project root directory** (`deer-flow/config.yaml`), not in the backend directory.
## Configuration Priority ## Configuration Priority
@@ -381,12 +331,12 @@ DeerFlow searches for configuration in this order:
1. Path specified in code via `config_path` argument 1. Path specified in code via `config_path` argument
2. Path from `DEER_FLOW_CONFIG_PATH` environment variable 2. Path from `DEER_FLOW_CONFIG_PATH` environment variable
3. `config.yaml` under `DEER_FLOW_PROJECT_ROOT`, or under the current working directory when `DEER_FLOW_PROJECT_ROOT` is unset 3. `config.yaml` in current working directory (typically `backend/` when running)
4. Legacy backend/repository-root locations for monorepo compatibility 4. `config.yaml` in parent directory (project root: `deer-flow/`)
## Best Practices ## Best Practices
1. **Place `config.yaml` in project root** - Set `DEER_FLOW_PROJECT_ROOT` if the runtime starts elsewhere 1. **Place `config.yaml` in project root** - Not in `backend/` directory
2. **Never commit `config.yaml`** - It's already in `.gitignore` 2. **Never commit `config.yaml`** - It's already in `.gitignore`
3. **Use environment variables for secrets** - Don't hardcode API keys 3. **Use environment variables for secrets** - Don't hardcode API keys
4. **Keep `config.example.yaml` updated** - Document all new options 4. **Keep `config.example.yaml` updated** - Document all new options
@@ -397,7 +347,7 @@ DeerFlow searches for configuration in this order:
### "Config file not found" ### "Config file not found"
- Ensure `config.yaml` exists in the **project root** directory (`deer-flow/config.yaml`) - Ensure `config.yaml` exists in the **project root** directory (`deer-flow/config.yaml`)
- If the runtime starts outside the project root, set `DEER_FLOW_PROJECT_ROOT` - The backend searches parent directory by default, so root location is preferred
- Alternatively, set `DEER_FLOW_CONFIG_PATH` environment variable to custom location - Alternatively, set `DEER_FLOW_CONFIG_PATH` environment variable to custom location
### "Invalid API key" ### "Invalid API key"
@@ -407,7 +357,7 @@ DeerFlow searches for configuration in this order:
### "Skills not loading" ### "Skills not loading"
- Check that `deer-flow/skills/` directory exists - Check that `deer-flow/skills/` directory exists
- Verify skills have valid `SKILL.md` files - Verify skills have valid `SKILL.md` files
- Check `skills.path` or `DEER_FLOW_SKILLS_PATH` if using a custom path - Check `skills.path` configuration if using custom path
### "Docker sandbox fails to start" ### "Docker sandbox fails to start"
- Ensure Docker is running - Ensure Docker is running
+5 -26
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@@ -2,12 +2,12 @@
## 概述 ## 概述
DeerFlow 后端提供了完整的文件上传功能,支持多文件上传,并可选地将 Office 文档和 PDF 转换为 Markdown 格式。 DeerFlow 后端提供了完整的文件上传功能,支持多文件上传,并自动将 Office 文档和 PDF 转换为 Markdown 格式。
## 功能特性 ## 功能特性
- ✅ 支持多文件同时上传 - ✅ 支持多文件同时上传
- ✅ 可选地转换文档为 MarkdownPDF、PPT、Excel、Word - ✅ 自动转换文档为 MarkdownPDF、PPT、Excel、Word
- ✅ 文件存储在线程隔离的目录中 - ✅ 文件存储在线程隔离的目录中
- ✅ Agent 自动感知已上传的文件 - ✅ Agent 自动感知已上传的文件
- ✅ 支持文件列表查询和删除 - ✅ 支持文件列表查询和删除
@@ -22,8 +22,6 @@ POST /api/threads/{thread_id}/uploads
**请求体:** `multipart/form-data` **请求体:** `multipart/form-data`
- `files`: 一个或多个文件 - `files`: 一个或多个文件
网关会在应用层限制上传规模,默认最多 10 个文件、单文件 50 MiB、单次请求总计 100 MiB。可通过 `config.yaml``uploads.max_files``uploads.max_file_size``uploads.max_total_size` 调整;前端会读取同一组限制并在选择文件时提示,超过限制时后端返回 `413 Payload Too Large`
**响应:** **响应:**
```json ```json
{ {
@@ -50,23 +48,7 @@ POST /api/threads/{thread_id}/uploads
- `virtual_path`: Agent 在沙箱中使用的虚拟路径 - `virtual_path`: Agent 在沙箱中使用的虚拟路径
- `artifact_url`: 前端通过 HTTP 访问文件的 URL - `artifact_url`: 前端通过 HTTP 访问文件的 URL
### 2. 查询上传限制 ### 2. 列出已上传文件
```
GET /api/threads/{thread_id}/uploads/limits
```
返回网关当前生效的上传限制,供前端在用户选择文件前提示和拦截。
**响应:**
```json
{
"max_files": 10,
"max_file_size": 52428800,
"max_total_size": 104857600
}
```
### 3. 列出已上传文件
``` ```
GET /api/threads/{thread_id}/uploads/list GET /api/threads/{thread_id}/uploads/list
``` ```
@@ -89,7 +71,7 @@ GET /api/threads/{thread_id}/uploads/list
} }
``` ```
### 4. 删除文件 ### 3. 删除文件
``` ```
DELETE /api/threads/{thread_id}/uploads/{filename} DELETE /api/threads/{thread_id}/uploads/{filename}
``` ```
@@ -104,7 +86,7 @@ DELETE /api/threads/{thread_id}/uploads/{filename}
## 支持的文档格式 ## 支持的文档格式
以下格式在显式启用 `uploads.auto_convert_documents: true`会自动转换为 Markdown 以下格式会自动转换为 Markdown:
- PDF (`.pdf`) - PDF (`.pdf`)
- PowerPoint (`.ppt`, `.pptx`) - PowerPoint (`.ppt`, `.pptx`)
- Excel (`.xls`, `.xlsx`) - Excel (`.xls`, `.xlsx`)
@@ -112,8 +94,6 @@ DELETE /api/threads/{thread_id}/uploads/{filename}
转换后的 Markdown 文件会保存在同一目录下,文件名为原文件名 + `.md` 扩展名。 转换后的 Markdown 文件会保存在同一目录下,文件名为原文件名 + `.md` 扩展名。
默认情况下,自动转换是关闭的,以避免在网关主机上对不受信任的 Office/PDF 上传执行解析。只有在受信任部署中明确接受此风险时,才应将 `uploads.auto_convert_documents` 设置为 `true`
## Agent 集成 ## Agent 集成
### 自动文件列举 ### 自动文件列举
@@ -227,7 +207,6 @@ backend/.deer-flow/threads/
- 最大文件大小:100MB(可在 nginx.conf 中配置 `client_max_body_size` - 最大文件大小:100MB(可在 nginx.conf 中配置 `client_max_body_size`
- 文件名安全性:系统会自动验证文件路径,防止目录遍历攻击 - 文件名安全性:系统会自动验证文件路径,防止目录遍历攻击
- 线程隔离:每个线程的上传文件相互隔离,无法跨线程访问 - 线程隔离:每个线程的上传文件相互隔离,无法跨线程访问
- 自动文档转换默认关闭;如需启用,需在 `config.yaml` 中显式设置 `uploads.auto_convert_documents: true`
## 技术实现 ## 技术实现
+1 -1
View File
@@ -296,7 +296,7 @@ These are the tool names your provider will see in `request.tool_name`:
| `web_search` | Web search query | | `web_search` | Web search query |
| `web_fetch` | Fetch URL content | | `web_fetch` | Fetch URL content |
| `image_search` | Image search | | `image_search` | Image search |
| `present_files` | Present file to user | | `present_file` | Present file to user |
| `view_image` | Display image | | `view_image` | Display image |
| `ask_clarification` | Ask user a question | | `ask_clarification` | Ask user a question |
| `task` | Delegate to subagent | | `task` | Delegate to subagent |
+343
View File
@@ -0,0 +1,343 @@
# DeerFlow 后端拆分设计文档:Harness + App
> 状态:Draft
> 作者:DeerFlow Team
> 日期:2026-03-13
## 1. 背景与动机
DeerFlow 后端当前是一个单一 Python 包(`src.*`),包含了从底层 agent 编排到上层用户产品的所有代码。随着项目发展,这种结构带来了几个问题:
- **复用困难**:其他产品(CLI 工具、Slack bot、第三方集成)想用 agent 能力,必须依赖整个后端,包括 FastAPI、IM SDK 等不需要的依赖
- **职责模糊**:agent 编排逻辑和用户产品逻辑混在同一个 `src/` 下,边界不清晰
- **依赖膨胀**LangGraph Server 运行时不需要 FastAPI/uvicorn/Slack SDK,但当前必须安装全部依赖
本文档提出将后端拆分为两部分:**deerflow-harness**(可发布的 agent 框架包)和 **app**(不打包的用户产品代码)。
## 2. 核心概念
### 2.1 Harness(线束/框架层)
Harness 是 agent 的构建与编排框架,回答 **"如何构建和运行 agent"** 的问题:
- Agent 工厂与生命周期管理
- Middleware pipeline
- 工具系统(内置工具 + MCP + 社区工具)
- 沙箱执行环境
- 子 agent 委派
- 记忆系统
- 技能加载与注入
- 模型工厂
- 配置系统
**Harness 是一个可发布的 Python 包**(`deerflow-harness`),可以独立安装和使用。
**Harness 的设计原则**:对上层应用完全无感知。它不知道也不关心谁在调用它——可以是 Web App、CLI、Slack Bot、或者一个单元测试。
### 2.2 App(应用层)
App 是面向用户的产品代码,回答 **"如何将 agent 呈现给用户"** 的问题:
- Gateway APIFastAPI REST 接口)
- IM Channels(飞书、Slack、Telegram 集成)
- Custom Agent 的 CRUD 管理
- 文件上传/下载的 HTTP 接口
**App 不打包、不发布**,它是 DeerFlow 项目内部的应用代码,直接运行。
**App 依赖 Harness,但 Harness 不依赖 App。**
### 2.3 边界划分
| 模块 | 归属 | 说明 |
|------|------|------|
| `config/` | Harness | 配置系统是基础设施 |
| `reflection/` | Harness | 动态模块加载工具 |
| `utils/` | Harness | 通用工具函数 |
| `agents/` | Harness | Agent 工厂、middleware、state、memory |
| `subagents/` | Harness | 子 agent 委派系统 |
| `sandbox/` | Harness | 沙箱执行环境 |
| `tools/` | Harness | 工具注册与发现 |
| `mcp/` | Harness | MCP 协议集成 |
| `skills/` | Harness | 技能加载、解析、定义 schema |
| `models/` | Harness | LLM 模型工厂 |
| `community/` | Harness | 社区工具(tavily、jina 等) |
| `client.py` | Harness | 嵌入式 Python 客户端 |
| `gateway/` | App | FastAPI REST API |
| `channels/` | App | IM 平台集成 |
**关于 Custom Agents**agent 定义格式(`config.yaml` + `SOUL.md` schema)由 Harness 层的 `config/agents_config.py` 定义,但文件的存储、CRUD、发现机制由 App 层的 `gateway/routers/agents.py` 负责。
## 3. 目标架构
### 3.1 目录结构
```
backend/
├── packages/
│ └── harness/
│ ├── pyproject.toml # deerflow-harness 包定义
│ └── deerflow/ # Python 包根(import 前缀: deerflow.*
│ ├── __init__.py
│ ├── config/
│ ├── reflection/
│ ├── utils/
│ ├── agents/
│ │ ├── lead_agent/
│ │ ├── middlewares/
│ │ ├── memory/
│ │ ├── checkpointer/
│ │ └── thread_state.py
│ ├── subagents/
│ ├── sandbox/
│ ├── tools/
│ ├── mcp/
│ ├── skills/
│ ├── models/
│ ├── community/
│ └── client.py
├── app/ # 不打包(import 前缀: app.*
│ ├── __init__.py
│ ├── gateway/
│ │ ├── __init__.py
│ │ ├── app.py
│ │ ├── config.py
│ │ ├── path_utils.py
│ │ └── routers/
│ └── channels/
│ ├── __init__.py
│ ├── base.py
│ ├── manager.py
│ ├── service.py
│ ├── store.py
│ ├── message_bus.py
│ ├── feishu.py
│ ├── slack.py
│ └── telegram.py
├── pyproject.toml # uv workspace root
├── langgraph.json
├── tests/
├── docs/
└── Makefile
```
### 3.2 Import 规则
两个层使用不同的 import 前缀,职责边界一目了然:
```python
# ---------------------------------------------------------------
# Harness 内部互相引用(deerflow.* 前缀)
# ---------------------------------------------------------------
from deerflow.agents import make_lead_agent
from deerflow.models import create_chat_model
from deerflow.config import get_app_config
from deerflow.tools import get_available_tools
# ---------------------------------------------------------------
# App 内部互相引用(app.* 前缀)
# ---------------------------------------------------------------
from app.gateway.app import app
from app.gateway.routers.uploads import upload_files
from app.channels.service import start_channel_service
# ---------------------------------------------------------------
# App 调用 Harness(单向依赖,Harness 永远不 import app
# ---------------------------------------------------------------
from deerflow.agents import make_lead_agent
from deerflow.models import create_chat_model
from deerflow.skills import load_skills
from deerflow.config.extensions_config import get_extensions_config
```
**App 调用 Harness 示例 — Gateway 中启动 agent**
```python
# app/gateway/routers/chat.py
from deerflow.agents.lead_agent.agent import make_lead_agent
from deerflow.models import create_chat_model
from deerflow.config import get_app_config
async def create_chat_session(thread_id: str, model_name: str):
config = get_app_config()
model = create_chat_model(name=model_name)
agent = make_lead_agent(config=...)
# ... 使用 agent 处理用户消息
```
**App 调用 Harness 示例 — Channel 中查询 skills**
```python
# app/channels/manager.py
from deerflow.skills import load_skills
from deerflow.agents.memory.updater import get_memory_data
def handle_status_command():
skills = load_skills(enabled_only=True)
memory = get_memory_data()
return f"Skills: {len(skills)}, Memory facts: {len(memory.get('facts', []))}"
```
**禁止方向**:Harness 代码中绝不能出现 `from app.``import app.`
### 3.3 为什么 App 不打包
| 方面 | 打包(放 packages/ 下) | 不打包(放 backend/app/ |
|------|------------------------|--------------------------|
| 命名空间 | 需要 pkgutil `extend_path` 合并,或独立前缀 | 天然独立,`app.*` vs `deerflow.*` |
| 发布需求 | 没有——App 是项目内部代码 | 不需要 pyproject.toml |
| 复杂度 | 需要管理两个包的构建、版本、依赖声明 | 直接运行,零额外配置 |
| 运行方式 | `pip install deerflow-app` | `PYTHONPATH=. uvicorn app.gateway.app:app` |
App 的唯一消费者是 DeerFlow 项目自身,没有独立发布的需求。放在 `backend/app/` 下作为普通 Python 包,通过 `PYTHONPATH` 或 editable install 让 Python 找到即可。
### 3.4 依赖关系
```
┌─────────────────────────────────────┐
│ app/ (不打包,直接运行) │
│ ├── fastapi, uvicorn │
│ ├── slack-sdk, lark-oapi, ... │
│ └── import deerflow.* │
└──────────────┬──────────────────────┘
┌─────────────────────────────────────┐
│ deerflow-harness (可发布的包) │
│ ├── langgraph, langchain │
│ ├── markitdown, pydantic, ... │
│ └── 零 app 依赖 │
└─────────────────────────────────────┘
```
**依赖分类**
| 分类 | 依赖包 |
|------|--------|
| Harness only | agent-sandbox, langchain*, langgraph*, markdownify, markitdown, pydantic, pyyaml, readabilipy, tavily-python, firecrawl-py, tiktoken, ddgs, duckdb, httpx, kubernetes, dotenv |
| App only | fastapi, uvicorn, sse-starlette, python-multipart, lark-oapi, slack-sdk, python-telegram-bot, markdown-to-mrkdwn |
| Shared | langgraph-sdkchannels 用 HTTP client, pydantic, httpx |
### 3.5 Workspace 配置
`backend/pyproject.toml`workspace root):
```toml
[project]
name = "deer-flow"
version = "0.1.0"
requires-python = ">=3.12"
dependencies = ["deerflow-harness"]
[dependency-groups]
dev = ["pytest>=8.0.0", "ruff>=0.14.11"]
# App 的额外依赖(fastapi 等)也声明在 workspace root,因为 app 不打包
app = ["fastapi", "uvicorn", "sse-starlette", "python-multipart"]
channels = ["lark-oapi", "slack-sdk", "python-telegram-bot"]
[tool.uv.workspace]
members = ["packages/harness"]
[tool.uv.sources]
deerflow-harness = { workspace = true }
```
## 4. 当前的跨层依赖问题
在拆分之前,需要先解决 `client.py` 中两处从 harness 到 app 的反向依赖:
### 4.1 `_validate_skill_frontmatter`
```python
# client.py — harness 导入了 app 层代码
from src.gateway.routers.skills import _validate_skill_frontmatter
```
**解决方案**:将该函数提取到 `deerflow/skills/validation.py`。这是一个纯逻辑函数(解析 YAML frontmatter、校验字段),与 FastAPI 无关。
### 4.2 `CONVERTIBLE_EXTENSIONS` + `convert_file_to_markdown`
```python
# client.py — harness 导入了 app 层代码
from src.gateway.routers.uploads import CONVERTIBLE_EXTENSIONS, convert_file_to_markdown
```
**解决方案**:将它们提取到 `deerflow/utils/file_conversion.py`。仅依赖 `markitdown` + `pathlib`,是通用工具函数。
## 5. 基础设施变更
### 5.1 LangGraph Server
LangGraph Server 只需要 harness 包。`langgraph.json` 更新:
```json
{
"dependencies": ["./packages/harness"],
"graphs": {
"lead_agent": "deerflow.agents:make_lead_agent"
},
"checkpointer": {
"path": "./packages/harness/deerflow/agents/checkpointer/async_provider.py:make_checkpointer"
}
}
```
### 5.2 Gateway API
```bash
# serve.sh / Makefile
# PYTHONPATH 包含 backend/ 根目录,使 app.* 和 deerflow.* 都能被找到
PYTHONPATH=. uvicorn app.gateway.app:app --host 0.0.0.0 --port 8001
```
### 5.3 Nginx
无需变更(只做 URL 路由,不涉及 Python 模块路径)。
### 5.4 Docker
Dockerfile 中的 module 引用从 `src.` 改为 `deerflow.` / `app.``COPY` 命令需覆盖 `packages/``app/` 目录。
## 6. 实施计划
分 3 个 PR 递进执行:
### PR 1:提取共享工具函数(Low Risk)
1. 创建 `src/skills/validation.py`,从 `gateway/routers/skills.py` 提取 `_validate_skill_frontmatter`
2. 创建 `src/utils/file_conversion.py`,从 `gateway/routers/uploads.py` 提取文件转换逻辑
3. 更新 `client.py``gateway/routers/skills.py``gateway/routers/uploads.py` 的 import
4. 运行全部测试确认无回归
### PR 2Rename + 物理拆分(High Risk,原子操作)
1. 创建 `packages/harness/` 目录,创建 `pyproject.toml`
2. `git mv` 将 harness 相关模块从 `src/` 移入 `packages/harness/deerflow/`
3. `git mv` 将 app 相关模块从 `src/` 移入 `app/`
4. 全局替换 import
- harness 模块:`src.*``deerflow.*`(所有 `.py` 文件、`langgraph.json`、测试、文档)
- app 模块:`src.gateway.*``app.gateway.*``src.channels.*``app.channels.*`
5. 更新 workspace root `pyproject.toml`
6. 更新 `langgraph.json``Makefile``Dockerfile`
7. `uv sync` + 全部测试 + 手动验证服务启动
### PR 3:边界检查 + 文档(Low Risk)
1. 添加 lint 规则:检查 harness 不 import app 模块
2. 更新 `CLAUDE.md``README.md`
## 7. 风险与缓解
| 风险 | 影响 | 缓解措施 |
|------|------|----------|
| 全局 rename 误伤 | 字符串中的 `src` 被错误替换 | 正则精确匹配 `\bsrc\.`review diff |
| LangGraph Server 找不到模块 | 服务启动失败 | `langgraph.json``dependencies` 指向正确的 harness 包路径 |
| App 的 `PYTHONPATH` 缺失 | Gateway/Channel 启动 import 报错 | Makefile/Docker 统一设置 `PYTHONPATH=.` |
| `config.yaml` 中的 `use` 字段引用旧路径 | 运行时模块解析失败 | `config.yaml` 中的 `use` 字段同步更新为 `deerflow.*` |
| 测试中 `sys.path` 混乱 | 测试失败 | 用 editable install`uv sync`)确保 deerflow 可导入,`conftest.py` 中添加 `app/``sys.path` |
## 8. 未来演进
- **独立发布**harness 可以发布到内部 PyPI,让其他项目直接 `pip install deerflow-harness`
- **插件化 App**:不同的 app(web、CLI、bot)可以各自独立,都依赖同一个 harness
- **更细粒度拆分**:如果 harness 内部模块继续增长,可以进一步拆分(如 `deerflow-sandbox``deerflow-mcp`
+2 -49
View File
@@ -14,19 +14,6 @@ DeerFlow supports configurable MCP servers and skills to extend its capabilities
3. Configure each servers command, arguments, and environment variables as needed. 3. Configure each servers command, arguments, and environment variables as needed.
4. Restart the application to load and register MCP tools. 4. Restart the application to load and register MCP tools.
## Filesystem MCP Servers
DeerFlow already provides built-in file tools for thread-scoped workspace access.
Do not add an MCP filesystem server for the same DeerFlow workspace. The
overlapping file tools use different path semantics, which can make LLM tool
selection and file access behavior unstable.
DeerFlow does not currently adapt the MCP Roots mode for filesystem servers. In
particular, it does not publish per-thread MCP roots or map DeerFlow sandbox
paths such as `/mnt/user-data/...` to paths accepted by
`@modelcontextprotocol/server-filesystem`. Use DeerFlow's built-in file tools
for DeerFlow workspace files.
## OAuth Support (HTTP/SSE MCP Servers) ## OAuth Support (HTTP/SSE MCP Servers)
For `http` and `sse` MCP servers, DeerFlow supports OAuth token acquisition and automatic token refresh. For `http` and `sse` MCP servers, DeerFlow supports OAuth token acquisition and automatic token refresh.
@@ -58,41 +45,6 @@ Example:
} }
``` ```
## Custom Tool Interceptors
You can register custom interceptors that run before every MCP tool call. This is useful for injecting per-request headers (e.g., user auth tokens from the LangGraph execution context), logging, or metrics.
Declare interceptors in `extensions_config.json` using the `mcpInterceptors` field:
```json
{
"mcpInterceptors": [
"my_package.mcp.auth:build_auth_interceptor"
],
"mcpServers": { ... }
}
```
Each entry is a Python import path in `module:variable` format (resolved via `resolve_variable`). The variable must be a **no-arg builder function** that returns an async interceptor compatible with `MultiServerMCPClient`s `tool_interceptors` interface, or `None` to skip.
Example interceptor that injects auth headers from LangGraph metadata:
```python
def build_auth_interceptor():
async def interceptor(request, handler):
from langgraph.config import get_config
metadata = get_config().get("metadata", {})
headers = dict(request.headers or {})
if token := metadata.get("auth_token"):
headers["X-Auth-Token"] = token
return await handler(request.override(headers=headers))
return interceptor
```
- A single string value is accepted and normalized to a one-element list.
- Invalid paths or builder failures are logged as warnings without blocking other interceptors.
- The builder return value must be `callable`; non-callable values are skipped with a warning.
## How It Works ## How It Works
MCP servers expose tools that are automatically discovered and integrated into DeerFlows agent system at runtime. Once enabled, these tools become available to agents without additional code changes. MCP servers expose tools that are automatically discovered and integrated into DeerFlows agent system at runtime. Once enabled, these tools become available to agents without additional code changes.
@@ -101,6 +53,7 @@ MCP servers expose tools that are automatically discovered and integrated into D
MCP servers can provide access to: MCP servers can provide access to:
- **File systems**
- **Databases** (e.g., PostgreSQL) - **Databases** (e.g., PostgreSQL)
- **External APIs** (e.g., GitHub, Brave Search) - **External APIs** (e.g., GitHub, Brave Search)
- **Browser automation** (e.g., Puppeteer) - **Browser automation** (e.g., Puppeteer)
@@ -109,4 +62,4 @@ MCP servers can provide access to:
## Learn More ## Learn More
For detailed documentation about the Model Context Protocol, visit: For detailed documentation about the Model Context Protocol, visit:
https://modelcontextprotocol.io https://modelcontextprotocol.io
-3
View File
@@ -8,7 +8,6 @@ This directory contains detailed documentation for the DeerFlow backend.
|----------|-------------| |----------|-------------|
| [ARCHITECTURE.md](ARCHITECTURE.md) | System architecture overview | | [ARCHITECTURE.md](ARCHITECTURE.md) | System architecture overview |
| [API.md](API.md) | Complete API reference | | [API.md](API.md) | Complete API reference |
| [AUTH_DESIGN.md](AUTH_DESIGN.md) | User authentication, CSRF, and per-user isolation design |
| [CONFIGURATION.md](CONFIGURATION.md) | Configuration options | | [CONFIGURATION.md](CONFIGURATION.md) | Configuration options |
| [SETUP.md](SETUP.md) | Quick setup guide | | [SETUP.md](SETUP.md) | Quick setup guide |
@@ -19,7 +18,6 @@ This directory contains detailed documentation for the DeerFlow backend.
| [STREAMING.md](STREAMING.md) | Token-level streaming design: Gateway vs DeerFlowClient paths, `stream_mode` semantics, per-id dedup | | [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 | | [FILE_UPLOAD.md](FILE_UPLOAD.md) | File upload functionality |
| [PATH_EXAMPLES.md](PATH_EXAMPLES.md) | Path types and usage examples | | [PATH_EXAMPLES.md](PATH_EXAMPLES.md) | Path types and usage examples |
| [SANDBOX_MEMORY_PROFILING.md](SANDBOX_MEMORY_PROFILING.md) | Sandbox memory baseline and runtime comparison guide |
| [summarization.md](summarization.md) | Context summarization feature | | [summarization.md](summarization.md) | Context summarization feature |
| [plan_mode_usage.md](plan_mode_usage.md) | Plan mode with TodoList | | [plan_mode_usage.md](plan_mode_usage.md) | Plan mode with TodoList |
| [AUTO_TITLE_GENERATION.md](AUTO_TITLE_GENERATION.md) | Automatic title generation | | [AUTO_TITLE_GENERATION.md](AUTO_TITLE_GENERATION.md) | Automatic title generation |
@@ -44,7 +42,6 @@ docs/
├── README.md # This file ├── README.md # This file
├── ARCHITECTURE.md # System architecture ├── ARCHITECTURE.md # System architecture
├── API.md # API reference ├── API.md # API reference
├── AUTH_DESIGN.md # User authentication and isolation design
├── CONFIGURATION.md # Configuration guide ├── CONFIGURATION.md # Configuration guide
├── SETUP.md # Setup instructions ├── SETUP.md # Setup instructions
├── FILE_UPLOAD.md # File upload feature ├── FILE_UPLOAD.md # File upload feature
-81
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@@ -1,81 +0,0 @@
# Sandbox Memory Profiling
This guide records a repeatable baseline before changing the sandbox runtime.
Issue #3213 reports per-sandbox memory near 1 GiB in Kubernetes. Before adding
or recommending a new provider, capture the current AIO sandbox baseline and
compare candidates with the same DeerFlow workload.
## What to Measure
Measure at least these samples:
1. Empty sandbox after it becomes ready.
2. After a simple bash command.
3. After a Python task that imports common packages.
4. After a Node task when Node-based workloads are expected.
5. After generating files under `/mnt/user-data/outputs`.
6. After release and warm reuse.
7. At the target concurrency level, for example 10, 50, or 100 sandboxes.
`kubectl top` reports Kubernetes/container working set memory. Treat it as a
capacity signal, not exclusive RSS/PSS. Pod-level memory includes every
container in the Pod and may include cache charged to the cgroup. If a result
looks surprising, inspect the sandbox processes and cgroup metrics on the node
before drawing conclusions.
## Capture a Snapshot
Run this from the repository root:
```bash
python scripts/sandbox_memory_profile.py \
--namespace deer-flow \
--selector app=deer-flow-sandbox \
--sample empty \
--include-processes \
--format markdown
```
Use a descriptive `--sample` value for each phase:
```bash
python scripts/sandbox_memory_profile.py --sample after-bash --format json
python scripts/sandbox_memory_profile.py --sample after-python --format json
python scripts/sandbox_memory_profile.py --sample after-artifact --format json
```
`--include-processes` runs `kubectl exec ... ps` in each sandbox Pod and adds
the highest-RSS processes to the report. This helps distinguish Pod-level cgroup
memory from process RSS. The two numbers will not match exactly because cgroup
memory can include cache and other kernel-accounted memory.
Save the raw JSON when comparing backends so totals, pod names, images,
requests, limits, and timestamps can be audited later.
## Candidate Runtime Matrix
For AIO, CubeSandbox, OpenSandbox, gVisor, Kata, or another candidate, compare
the same workload and record:
| Area | Required Evidence |
| --- | --- |
| Capacity | Pod or instance count, total memory, average memory, max memory |
| Startup | Ready latency at 1, 10, 50, and 100 concurrent sandboxes |
| Commands | Bash output, timeout behavior, failure shape |
| Files | `read_file`, `write_file`, binary `update_file`, `list_dir`, `glob`, `grep` |
| Uploads | Files uploaded by the gateway are visible inside the sandbox |
| Artifacts | Files written to `/mnt/user-data/outputs` are readable by the backend artifact API |
| Paths | `/mnt/user-data/workspace`, `/mnt/user-data/uploads`, `/mnt/user-data/outputs`, `/mnt/acp-workspace`, and skills paths keep their expected semantics |
| Isolation | Different users and threads cannot read each other's data |
| Cleanup | Release, idle timeout, process restart, and orphan cleanup free resources |
| Operations | Deployment prerequisites, privileged components, networking, storage, and upgrade path |
## PR Guidance
Do not claim that a new provider fixes high-concurrency memory usage until the
same DeerFlow workload has been measured on both the current AIO sandbox and the
candidate backend.
For an experimental provider PR, prefer `Related to #3213` unless the PR also
includes reproducible DeerFlow workload data that demonstrates the target memory
reduction and preserves uploads, outputs, artifacts, and isolation behavior.
+8 -14
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@@ -23,9 +23,6 @@ DeerFlow uses a YAML configuration file that should be placed in the **project r
# Option A: Set environment variables (recommended) # Option A: Set environment variables (recommended)
export OPENAI_API_KEY="your-key-here" export OPENAI_API_KEY="your-key-here"
# Optional: pin the project root when running from another directory
export DEER_FLOW_PROJECT_ROOT="/path/to/deer-flow"
# Option B: Edit config.yaml directly # Option B: Edit config.yaml directly
vim config.yaml # or your preferred editor vim config.yaml # or your preferred editor
``` ```
@@ -38,20 +35,17 @@ DeerFlow uses a YAML configuration file that should be placed in the **project r
## Important Notes ## Important Notes
- **Location**: `config.yaml` should be in `deer-flow/` (project root) - **Location**: `config.yaml` should be in `deer-flow/` (project root), not `deer-flow/backend/`
- **Git**: `config.yaml` is automatically ignored by git (contains secrets) - **Git**: `config.yaml` is automatically ignored by git (contains secrets)
- **Runtime root**: Set `DEER_FLOW_PROJECT_ROOT` if DeerFlow may start from outside the project root - **Priority**: If both `backend/config.yaml` and `../config.yaml` exist, backend version takes precedence
- **Runtime data**: State defaults to `.deer-flow` under the project root; set `DEER_FLOW_HOME` to move it
- **Skills**: Skills default to `skills/` under the project root; set `DEER_FLOW_SKILLS_PATH` or `skills.path` to move them
## Configuration File Locations ## Configuration File Locations
The backend searches for `config.yaml` in this order: The backend searches for `config.yaml` in this order:
1. Explicit `config_path` argument from code 1. `DEER_FLOW_CONFIG_PATH` environment variable (if set)
2. `DEER_FLOW_CONFIG_PATH` environment variable (if set) 2. `backend/config.yaml` (current directory when running from backend/)
3. `config.yaml` under `DEER_FLOW_PROJECT_ROOT`, or the current working directory when `DEER_FLOW_PROJECT_ROOT` is unset 3. `deer-flow/config.yaml` (parent directory - **recommended location**)
4. Legacy backend/repository-root locations for monorepo compatibility
**Recommended**: Place `config.yaml` in project root (`deer-flow/config.yaml`). **Recommended**: Place `config.yaml` in project root (`deer-flow/config.yaml`).
@@ -83,8 +77,8 @@ python -c "from deerflow.config.app_config import AppConfig; print(AppConfig.res
If it can't find the config: If it can't find the config:
1. Ensure you've copied `config.example.yaml` to `config.yaml` 1. Ensure you've copied `config.example.yaml` to `config.yaml`
2. Verify you're in the project root, or set `DEER_FLOW_PROJECT_ROOT` 2. Verify you're in the correct directory
3. Check the file exists: `ls -la config.yaml` 3. Check the file exists: `ls -la ../config.yaml`
### Permission denied ### Permission denied
@@ -95,4 +89,4 @@ chmod 600 ../config.yaml # Protect sensitive configuration
## See Also ## See Also
- [Configuration Guide](CONFIGURATION.md) - Detailed configuration options - [Configuration Guide](CONFIGURATION.md) - Detailed configuration options
- [Architecture Overview](../CLAUDE.md) - System architecture - [Architecture Overview](../CLAUDE.md) - System architecture
@@ -124,7 +124,7 @@ title:
# checkpointer.py # checkpointer.py
from langgraph.checkpoint.sqlite import SqliteSaver from langgraph.checkpoint.sqlite import SqliteSaver
checkpointer = SqliteSaver.from_conn_string("deerflow.db") checkpointer = SqliteSaver.from_conn_string("checkpoints.db")
``` ```
```json ```json
+4 -4
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@@ -11,7 +11,6 @@
- [x] Add Plan Mode with TodoList middleware - [x] Add Plan Mode with TodoList middleware
- [x] Add vision model support with ViewImageMiddleware - [x] Add vision model support with ViewImageMiddleware
- [x] Skills system with SKILL.md format - [x] Skills system with SKILL.md format
- [x] Replace `time.sleep(5)` with `asyncio.sleep()` in `packages/harness/deerflow/tools/builtins/task_tool.py` (subagent polling)
## Planned Features ## Planned Features
@@ -22,11 +21,12 @@
- [ ] Support for more document formats in upload - [ ] Support for more document formats in upload
- [ ] Skill marketplace / remote skill installation - [ ] Skill marketplace / remote skill installation
- [ ] Optimize async concurrency in agent hot path (IM channels multi-task scenario) - [ ] Optimize async concurrency in agent hot path (IM channels multi-task scenario)
- [ ] Replace `subprocess.run()` with `asyncio.create_subprocess_shell()` in `packages/harness/deerflow/sandbox/local/local_sandbox.py` - Replace `time.sleep(5)` with `asyncio.sleep()` in `packages/harness/deerflow/tools/builtins/task_tool.py` (subagent polling)
- Replace `subprocess.run()` with `asyncio.create_subprocess_shell()` in `packages/harness/deerflow/sandbox/local/local_sandbox.py`
- Replace sync `requests` with `httpx.AsyncClient` in community tools (tavily, jina_ai, firecrawl, infoquest, image_search) - Replace sync `requests` with `httpx.AsyncClient` in community tools (tavily, jina_ai, firecrawl, infoquest, image_search)
- [x] Replace sync `model.invoke()` with async `model.ainvoke()` in title_middleware and memory updater - Replace sync `model.invoke()` with async `model.ainvoke()` in title_middleware and memory updater
- Consider `asyncio.to_thread()` wrapper for remaining blocking file I/O - Consider `asyncio.to_thread()` wrapper for remaining blocking file I/O
- For production: tune Gateway worker/runtime settings for long-running agent workloads - For production: use `langgraph up` (multi-worker) instead of `langgraph dev` (single-worker)
## Resolved Issues ## Resolved Issues
+65 -79
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@@ -4,22 +4,22 @@
`create_deerflow_agent` 通过 `RuntimeFeatures` 组装的完整 middleware 链(默认全开时): `create_deerflow_agent` 通过 `RuntimeFeatures` 组装的完整 middleware 链(默认全开时):
| # | Middleware | `before_agent` | `before_model` | `after_model` | `after_agent` | `wrap_model_call` | `wrap_tool_call` | 主 Agent | Subagent | 来源 | | # | Middleware | `before_agent` | `before_model` | `after_model` | `after_agent` | `wrap_tool_call` | 主 Agent | Subagent | 来源 |
|---|-----------|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|------| |---|-----------|:-:|:-:|:-:|:-:|:-:|:-:|:-:|------|
| 0 | ThreadDataMiddleware | ✓ | | | | | | ✓ | ✓ | `sandbox` | | 0 | ThreadDataMiddleware | ✓ | | | | | ✓ | ✓ | `sandbox` |
| 1 | UploadsMiddleware | ✓ | | | | | | ✓ | ✗ | `sandbox` | | 1 | UploadsMiddleware | ✓ | | | | | ✓ | ✗ | `sandbox` |
| 2 | SandboxMiddleware | ✓ | | | ✓ | | | ✓ | ✓ | `sandbox` | | 2 | SandboxMiddleware | ✓ | | | ✓ | | ✓ | ✓ | `sandbox` |
| 3 | DanglingToolCallMiddleware | | | | | | | ✓ | ✗ | 始终开启 | | 3 | DanglingToolCallMiddleware | | | | | | ✓ | ✗ | 始终开启 |
| 4 | GuardrailMiddleware | | | | | | ✓ | ✓ | ✓ | *Phase 2 纳入* | | 4 | GuardrailMiddleware | | | | | ✓ | ✓ | ✓ | *Phase 2 纳入* |
| 5 | ToolErrorHandlingMiddleware | | | | | | ✓ | ✓ | ✓ | 始终开启 | | 5 | ToolErrorHandlingMiddleware | | | | | ✓ | ✓ | ✓ | 始终开启 |
| 6 | SummarizationMiddleware | | | | | | | ✓ | ✗ | `summarization` | | 6 | SummarizationMiddleware | | | | | | ✓ | ✗ | `summarization` |
| 7 | TodoMiddleware | | | ✓ | | ✓ | | ✓ | ✗ | `plan_mode` 参数 | | 7 | TodoMiddleware | | | ✓ | | | ✓ | ✗ | `plan_mode` 参数 |
| 8 | TitleMiddleware | | | ✓ | | | | ✓ | ✗ | `auto_title` | | 8 | TitleMiddleware | | | ✓ | | | ✓ | ✗ | `auto_title` |
| 9 | MemoryMiddleware | | | | ✓ | | | ✓ | ✗ | `memory` | | 9 | MemoryMiddleware | | | | ✓ | | ✓ | ✗ | `memory` |
| 10 | ViewImageMiddleware | | ✓ | | | | | ✓ | ✗ | `vision` | | 10 | ViewImageMiddleware | | ✓ | | | | ✓ | ✗ | `vision` |
| 11 | SubagentLimitMiddleware | | | ✓ | | | | ✓ | ✗ | `subagent` | | 11 | SubagentLimitMiddleware | | | ✓ | | | ✓ | ✗ | `subagent` |
| 12 | LoopDetectionMiddleware | | | ✓ | ✓ | ✓ | | ✓ | ✗ | 始终开启 | | 12 | LoopDetectionMiddleware | | | ✓ | | | ✓ | ✗ | 始终开启 |
| 13 | ClarificationMiddleware | | | | | | | ✓ | ✗ | 始终最后 | | 13 | ClarificationMiddleware | | | | | | ✓ | ✗ | 始终最后 |
主 agent **14 个** middleware`make_lead_agent`),subagent **4 个**ThreadData、Sandbox、Guardrail、ToolErrorHandling)。`create_deerflow_agent` Phase 1 实现 **13 个**(Guardrail 仅支持自定义实例,无内置默认)。 主 agent **14 个** middleware`make_lead_agent`),subagent **4 个**ThreadData、Sandbox、Guardrail、ToolErrorHandling)。`create_deerflow_agent` Phase 1 实现 **13 个**(Guardrail 仅支持自定义实例,无内置默认)。
@@ -35,7 +35,7 @@ graph TB
subgraph BA ["<b>before_agent</b> 正序 0→N"] subgraph BA ["<b>before_agent</b> 正序 0→N"]
direction TB direction TB
TD["[0] ThreadData<br/>创建线程目录"] --> UL["[1] Uploads<br/>扫描上传文件"] --> SB["[2] Sandbox<br/>获取沙箱"] --> LD_BA["[12] LoopDetection<br/>清理 stale warning"] TD["[0] ThreadData<br/>创建线程目录"] --> UL["[1] Uploads<br/>扫描上传文件"] --> SB["[2] Sandbox<br/>获取沙箱"]
end end
subgraph BM ["<b>before_model</b> 正序 0→N"] subgraph BM ["<b>before_model</b> 正序 0→N"]
@@ -43,42 +43,34 @@ graph TB
VI["[10] ViewImage<br/>注入图片 base64"] VI["[10] ViewImage<br/>注入图片 base64"]
end end
subgraph WM ["<b>wrap_model_call</b>"] SB --> VI
direction TB VI --> M["<b>MODEL</b>"]
DTC_WM["[3] DanglingToolCall<br/>补悬空 ToolMessage"] --> LD_WM["[12] LoopDetection<br/>注入当前 run warning"]
end
LD_BA --> VI
VI --> DTC_WM
LD_WM --> M["<b>MODEL</b>"]
subgraph AM ["<b>after_model</b> 反序 N→0"] subgraph AM ["<b>after_model</b> 反序 N→0"]
direction TB direction TB
LD["[12] LoopDetection<br/>检测循环/排队 warning"] --> SL["[11] SubagentLimit<br/>截断多余 task"] --> TI["[8] Title<br/>生成标题"] CL["[13] Clarification<br/>拦截 ask_clarification"] --> LD["[12] LoopDetection<br/>检测循环"] --> SL["[11] SubagentLimit<br/>截断多余 task"] --> TI["[8] Title<br/>生成标题"] --> SM["[6] Summarization<br/>上下文压缩"] --> DTC["[3] DanglingToolCall<br/>补缺失 ToolMessage"]
end end
M --> LD M --> CL
subgraph AA ["<b>after_agent</b> 反序 N→0"] subgraph AA ["<b>after_agent</b> 反序 N→0"]
direction TB direction TB
LD_CLEAN["[12] LoopDetection<br/>清理 pending warning"] --> MEM["[9] Memory<br/>入队记忆"] --> SBR["[2] Sandbox<br/>释放沙箱"] SBR["[2] Sandbox<br/>释放沙箱"] --> MEM["[9] Memory<br/>入队记忆"]
end end
TI --> LD_CLEAN DTC --> SBR
SBR --> END(["response"]) MEM --> END(["response"])
classDef beforeNode fill:#a0a8b5,stroke:#636b7a,color:#2d3239 classDef beforeNode fill:#a0a8b5,stroke:#636b7a,color:#2d3239
classDef modelNode fill:#b5a8a0,stroke:#7a6b63,color:#2d3239 classDef modelNode fill:#b5a8a0,stroke:#7a6b63,color:#2d3239
classDef wrapModelNode fill:#a8a0b5,stroke:#6b637a,color:#2d3239
classDef afterModelNode fill:#b5a0a8,stroke:#7a636b,color:#2d3239 classDef afterModelNode fill:#b5a0a8,stroke:#7a636b,color:#2d3239
classDef afterAgentNode fill:#a0b5a8,stroke:#637a6b,color:#2d3239 classDef afterAgentNode fill:#a0b5a8,stroke:#637a6b,color:#2d3239
classDef terminalNode fill:#a8b5a0,stroke:#6b7a63,color:#2d3239 classDef terminalNode fill:#a8b5a0,stroke:#6b7a63,color:#2d3239
class TD,UL,SB,LD_BA,VI beforeNode class TD,UL,SB,VI beforeNode
class DTC_WM,LD_WM wrapModelNode
class M modelNode class M modelNode
class LD,SL,TI afterModelNode class CL,LD,SL,TI,SM,DTC afterModelNode
class LD_CLEAN,SBR,MEM afterAgentNode class SBR,MEM afterAgentNode
class START,END terminalNode class START,END terminalNode
``` ```
@@ -90,12 +82,13 @@ sequenceDiagram
participant TD as ThreadDataMiddleware participant TD as ThreadDataMiddleware
participant UL as UploadsMiddleware participant UL as UploadsMiddleware
participant SB as SandboxMiddleware participant SB as SandboxMiddleware
participant LD as LoopDetectionMiddleware
participant VI as ViewImageMiddleware participant VI as ViewImageMiddleware
participant DTC as DanglingToolCallMiddleware
participant M as MODEL participant M as MODEL
participant CL as ClarificationMiddleware
participant SL as SubagentLimitMiddleware participant SL as SubagentLimitMiddleware
participant TI as TitleMiddleware participant TI as TitleMiddleware
participant SM as SummarizationMiddleware
participant DTC as DanglingToolCallMiddleware
participant MEM as MemoryMiddleware participant MEM as MemoryMiddleware
U ->> TD: invoke U ->> TD: invoke
@@ -110,26 +103,19 @@ sequenceDiagram
activate SB activate SB
Note right of SB: before_agent 获取沙箱 Note right of SB: before_agent 获取沙箱
SB ->> LD: before_agent SB ->> VI: before_model
activate LD
Note right of LD: before_agent 清理同 thread 旧 run 的 pending warning
LD ->> VI: before_model
activate VI activate VI
Note right of VI: before_model 注入图片 base64 Note right of VI: before_model 注入图片 base64
VI ->> DTC: wrap_model_call VI ->> M: messages + tools
activate DTC
Note right of DTC: wrap_model_call 补悬空 ToolMessage
DTC ->> LD: wrap_model_call
Note right of LD: wrap_model_call drain 当前 run warning 并追加到末尾
LD ->> M: messages + tools
activate M activate M
M -->> LD: AI response M -->> CL: AI response
deactivate M deactivate M
Note right of LD: after_model 检测循环;warning 入队,hard-stop 清 tool_calls activate CL
LD -->> SL: after_model Note right of CL: after_model 拦截 ask_clarification
deactivate LD CL -->> SL: after_model
deactivate CL
activate SL activate SL
Note right of SL: after_model 截断多余 task Note right of SL: after_model 截断多余 task
@@ -138,18 +124,22 @@ sequenceDiagram
activate TI activate TI
Note right of TI: after_model 生成标题 Note right of TI: after_model 生成标题
TI -->> DTC: done TI -->> SM: after_model
deactivate TI deactivate TI
activate SM
Note right of SM: after_model 上下文压缩
SM -->> DTC: after_model
deactivate SM
activate DTC
Note right of DTC: after_model 补缺失 ToolMessage
DTC -->> VI: done
deactivate DTC deactivate DTC
VI -->> SB: done VI -->> SB: done
deactivate VI deactivate VI
Note right of LD: after_agent 清理当前 run 未消费 warning
Note right of MEM: after_agent 入队记忆
Note right of SB: after_agent 释放沙箱 Note right of SB: after_agent 释放沙箱
SB -->> UL: done SB -->> UL: done
deactivate SB deactivate SB
@@ -157,6 +147,8 @@ sequenceDiagram
UL -->> TD: done UL -->> TD: done
deactivate UL deactivate UL
Note right of MEM: after_agent 入队记忆
TD -->> U: response TD -->> U: response
deactivate TD deactivate TD
``` ```
@@ -232,12 +224,12 @@ sequenceDiagram
participant TD as ThreadData participant TD as ThreadData
participant UL as Uploads participant UL as Uploads
participant SB as Sandbox participant SB as Sandbox
participant LD as LoopDetection
participant VI as ViewImage participant VI as ViewImage
participant DTC as DanglingToolCall
participant M as MODEL participant M as MODEL
participant CL as Clarification
participant SL as SubagentLimit participant SL as SubagentLimit
participant TI as Title participant TI as Title
participant SM as Summarization
participant MEM as Memory participant MEM as Memory
U ->> TD: invoke U ->> TD: invoke
@@ -246,40 +238,34 @@ sequenceDiagram
Note right of UL: before_agent 扫描文件 Note right of UL: before_agent 扫描文件
UL ->> SB: . UL ->> SB: .
Note right of SB: before_agent 获取沙箱 Note right of SB: before_agent 获取沙箱
SB ->> LD: .
Note right of LD: before_agent 清理 stale pending warning
loop 每轮对话(tool call 循环) loop 每轮对话(tool call 循环)
SB ->> VI: . SB ->> VI: .
Note right of VI: before_model 注入图片 Note right of VI: before_model 注入图片
VI ->> DTC: . VI ->> M: messages + tools
Note right of DTC: wrap_model_call 补悬空工具结果 M -->> CL: AI response
DTC ->> LD: . Note right of CL: after_model 拦截 ask_clarification
Note right of LD: wrap_model_call 注入当前 run warning CL -->> SL: .
LD ->> M: messages + tools
M -->> LD: AI response
Note right of LD: after_model 检测循环/排队 warning
LD -->> SL: .
Note right of SL: after_model 截断多余 task Note right of SL: after_model 截断多余 task
SL -->> TI: . SL -->> TI: .
Note right of TI: after_model 生成标题 Note right of TI: after_model 生成标题
TI -->> SM: .
Note right of SM: after_model 上下文压缩
end end
Note right of LD: after_agent 清理当前 run pending warning
LD -->> MEM: .
Note right of MEM: after_agent 入队记忆
MEM -->> SB: .
Note right of SB: after_agent 释放沙箱 Note right of SB: after_agent 释放沙箱
SB -->> U: response SB -->> MEM: .
Note right of MEM: after_agent 入队记忆
MEM -->> U: response
``` ```
> [!warning] 不是洋葱 > [!warning] 不是洋葱
> 大部分 middleware 只用一个阶段。SandboxMiddleware 使用 `before_agent`/`after_agent` 做资源获取/释放;LoopDetectionMiddleware 也使用这两个钩子,但用途是清理 run-scoped pending warnings,不是资源生命周期对称`before_agent` / `after_agent` 只跑一次,`before_model` / `after_model` / `wrap_model_call` 每轮循环都跑。 > 14 个 middleware 中只有 SandboxMiddleware before/after 对称(获取/释放)。其余都是单向的:要么只在 `before_*` 做事,要么只在 `after_*` 做事`before_agent` / `after_agent` 只跑一次,`before_model` / `after_model` 每轮循环都跑。
硬依赖只有 2 处: 硬依赖只有 2 处:
1. **ThreadData 在 Sandbox 之前** — sandbox 需要线程目录 1. **ThreadData 在 Sandbox 之前** — sandbox 需要线程目录
2. **Clarification 在列表最后**`wrap_tool_call` 处理 `ask_clarification` 时优先拦截,并通过 `Command(goto=END)` 中断执行 2. **Clarification 在列表最后**`after_model` 反序时最先执行,第一个拦截 `ask_clarification`
### 结论 ### 结论
@@ -287,19 +273,19 @@ sequenceDiagram
|---|---|---| |---|---|---|
| 每个 middleware | before + after 对称 | 大多只用一个钩子 | | 每个 middleware | before + after 对称 | 大多只用一个钩子 |
| 激活条 | 嵌套(外长内短) | 不嵌套(串行) | | 激活条 | 嵌套(外长内短) | 不嵌套(串行) |
| 反序的意义 | 清理与初始化配对 | 影响 `after_model` / `after_agent` 的执行优先级 | | 反序的意义 | 清理与初始化配对 | 影响 after_model 的执行优先级 |
| 典型例子 | Auth: 校验 token / 清理上下文 | ThreadData: 只创建目录,没有清理 | | 典型例子 | Auth: 校验 token / 清理上下文 | ThreadData: 只创建目录,没有清理 |
## 关键设计点 ## 关键设计点
### ClarificationMiddleware 为什么在列表最后? ### ClarificationMiddleware 为什么在列表最后?
位置最后使它在工具调用包装链中优先拦截 `ask_clarification`。如果命中,它返回 `Command(goto=END)`,把格式化后的澄清问题写成 `ToolMessage` 并中断执行。 位置最后 = `after_model` 最先执行。它需要**第一个**看到 model 输出,检查是否有 `ask_clarification` tool call。如果有,立即中断(`Command(goto=END)`),后续 middleware 的 `after_model` 不再执行。
### SandboxMiddleware 的对称性 ### SandboxMiddleware 的对称性
`before_agent`(正序第 3 个)获取沙箱,`after_agent`(反序第 1 个)释放沙箱。外层进入 → 外层退出,天然的洋葱对称。 `before_agent`(正序第 3 个)获取沙箱,`after_agent`(反序第 1 个)释放沙箱。外层进入 → 外层退出,天然的洋葱对称。
### LoopDetectionMiddleware 为什么同时用多个钩子 ### 大部分 middleware 只用一个钩子
`after_model` 只做检测:重复工具调用达到 warning 阈值时,把 warning 放入 `(thread_id, run_id)` 作用域的 pending 队列。真正注入发生在下一次 `wrap_model_call`:此时上一轮 `AIMessage(tool_calls)` 对应的 `ToolMessage` 已经在请求里,warning 追加在末尾,不会破坏 OpenAI/Moonshot 的 tool-call pairing。`before_agent` 清理同一 thread 下旧 run 的残留 warning`after_agent` 清理当前 run 没被消费的 warning 14 个 middleware 中,只有 SandboxMiddleware 同时用了 `before_agent` + `after_agent`(获取/释放)。其余都只在一个阶段执行。洋葱模型的反序特性主要影响 `after_model` 阶段的执行顺序
-28
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@@ -41,13 +41,6 @@ summarization:
# Custom summary prompt (optional) # Custom summary prompt (optional)
summary_prompt: null summary_prompt: null
# Tool names treated as skill file reads for skill rescue
skill_file_read_tool_names:
- read_file
- read
- view
- cat
``` ```
### Configuration Options ### Configuration Options
@@ -132,26 +125,6 @@ keep:
- **Default**: `null` (uses LangChain's default prompt) - **Default**: `null` (uses LangChain's default prompt)
- **Description**: Custom prompt template for generating summaries. The prompt should guide the model to extract the most important context. - **Description**: Custom prompt template for generating summaries. The prompt should guide the model to extract the most important context.
#### `preserve_recent_skill_count`
- **Type**: Integer (≥ 0)
- **Default**: `5`
- **Description**: Number of most-recently-loaded skill files (tool results whose tool name is in `skill_file_read_tool_names` and whose target path is under `skills.container_path`, e.g. `/mnt/skills/...`) that are rescued from summarization. Prevents the agent from losing skill instructions after compression. Set to `0` to disable skill rescue entirely.
#### `preserve_recent_skill_tokens`
- **Type**: Integer (≥ 0)
- **Default**: `25000`
- **Description**: Total token budget reserved for rescued skill reads. Once this budget is exhausted, older skill bundles are allowed to be summarized.
#### `preserve_recent_skill_tokens_per_skill`
- **Type**: Integer (≥ 0)
- **Default**: `5000`
- **Description**: Per-skill token cap. Any individual skill read whose tool result exceeds this size is not rescued (it falls through to the summarizer like ordinary content).
#### `skill_file_read_tool_names`
- **Type**: List of strings
- **Default**: `["read_file", "read", "view", "cat"]`
- **Description**: Tool names treated as skill file reads during summarization rescue. A tool call is only eligible for skill rescue when its name appears in this list and its target path is under `skills.container_path`.
**Default Prompt Behavior:** **Default Prompt Behavior:**
The default LangChain prompt instructs the model to: The default LangChain prompt instructs the model to:
- Extract highest quality/most relevant context - Extract highest quality/most relevant context
@@ -174,7 +147,6 @@ The default LangChain prompt instructs the model to:
- A single summary message is added - A single summary message is added
- Recent messages are preserved - Recent messages are preserved
6. **AI/Tool Pair Protection**: The system ensures AI messages and their corresponding tool messages stay together 6. **AI/Tool Pair Protection**: The system ensures AI messages and their corresponding tool messages stay together
7. **Skill Rescue**: Before the summary is generated, the most recently loaded skill files (tool results whose tool name is in `skill_file_read_tool_names` and whose target path is under `skills.container_path`) are lifted out of the summarization set and prepended to the preserved tail. Selection walks newest-first under three budgets: `preserve_recent_skill_count`, `preserve_recent_skill_tokens`, and `preserve_recent_skill_tokens_per_skill`. The triggering AIMessage and all of its paired ToolMessages move together so tool_call ↔ tool_result pairing stays intact.
### Token Counting ### Token Counting

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