f0b065bef62756dcbebf22adf73aa65cc5607fbc
150 Commits
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f0b065bef6 |
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
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4b139fb689 |
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
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f942e4e597 |
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. |
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03c3b18565 |
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. |
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00e0e9a49a |
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 |
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055e4df049 |
fix(sandbox): add input sanitisation guard to SandboxAuditMiddleware (#1872)
* fix(sandbox): add L2 input sanitisation to SandboxAuditMiddleware Add _validate_input() to reject malformed bash commands before regex classification: empty commands, oversized commands (>10 000 chars), and null bytes that could cause detection/execution layer inconsistency. * fix(sandbox): address Copilot review — type guard, log truncation, reject reason - Coerce None/non-string command to str before validation - Truncate oversized commands in audit logs to prevent log amplification - Propagate reject_reason through _pre_process() to block message - Remove L2 label from comments and test class names * fix(sandbox): isinstance type guard + async input sanitisation tests Address review comments: - Replace str() coercion with isinstance(raw_command, str) guard so non-string truthy values (0, [], False) fall back to empty string instead of passing validation as "0"/"[]"/"False". - Add TestInputSanitisationBlocksInAwrapToolCall with 4 async tests covering empty, null-byte, oversized, and None command via awrap_tool_call path. |
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1ced6e977c |
fix(backend): preserve viewed image reducer metadata (#1900)
Fix concurrent viewed_images state updates for multi-image input by preserving the reducer metadata in the vision middleware state schema. |
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dd30e609f7 |
feat(models): add vLLM provider support (#1860)
support for vLLM 0.19.0 OpenAI-compatible chat endpoints and fixes the Qwen reasoning toggle so flash mode can actually disable thinking. Co-authored-by: NmanQAQ <normangyao@qq.com> Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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5fd2c581f6 |
fix: add output truncation to ls_tool to prevent context window overflow (#1896)
ls_tool was the only sandbox tool without output size limits, allowing multi-MB results from large directories to blow up the model context window. Add head-truncation (configurable via ls_output_max_chars, default 20000) consistent with existing bash and read_file truncation. Closes #1887 Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> |
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7c68dd4ad4 |
Fix(#1702): stream resume run (#1858)
* fix: repair stream resume run metadata # Conflicts: # backend/packages/harness/deerflow/runtime/stream_bridge/memory.py # frontend/src/core/threads/hooks.ts * fix(stream): repair resumable replay validation --------- Co-authored-by: luoxiao6645 <luoxiao6645@gmail.com> Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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29575c32f9 |
fix: expose custom events from DeerFlowClient.stream() (#1827)
* fix: expose custom client stream events Signed-off-by: suyua9 <1521777066@qq.com> * fix(client): normalize streamed custom mode values * test(client): satisfy backend ruff import ordering --------- Signed-off-by: suyua9 <1521777066@qq.com> Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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117fa9b05d |
fix(channels): normalize slack allowed user ids (#1802)
* fix(channels): normalize slack allowed user ids * style(channels): apply backend formatter --------- Co-authored-by: haimingZZ <15558128926@qq.com> Co-authored-by: suyua9 <1521777066@qq.com> |
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8049785de6 |
fix(memory): case-insensitive fact deduplication and positive reinforcement detection (#1804)
* fix(memory): case-insensitive fact deduplication and positive reinforcement detection Two fixes to the memory system: 1. _fact_content_key() now lowercases content before comparison, preventing semantically duplicate facts like "User prefers Python" and "user prefers python" from being stored separately. 2. Adds detect_reinforcement() to MemoryMiddleware (closes #1719), mirroring detect_correction(). When users signal approval ("yes exactly", "perfect", "完全正确", etc.), the memory updater now receives reinforcement_detected=True and injects a hint prompting the LLM to record confirmed preferences and behaviors with high confidence. Changes across the full signal path: - memory_middleware.py: _REINFORCEMENT_PATTERNS + detect_reinforcement() - queue.py: reinforcement_detected field in ConversationContext and add() - updater.py: reinforcement_detected param in update_memory() and update_memory_from_conversation(); builds reinforcement_hint alongside the existing correction_hint Tests: 11 new tests covering deduplication, hint injection, and signal detection (Chinese + English patterns, window boundary, conflict with correction). Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(memory): address Copilot review comments on reinforcement detection - Tighten _REINFORCEMENT_PATTERNS: remove 很好, require punctuation/end-of-string boundaries on remaining patterns, split this-is-good into stricter variants - Suppress reinforcement_detected when correction_detected is true to avoid mixed-signal noise - Use casefold() instead of lower() for Unicode-aware fact deduplication - Add missing test coverage for reinforcement_detected OR merge and forwarding in queue --------- Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> |
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9ca68ffaaa |
fix: preserve virtual path separator style (#1828)
* fix: preserve virtual path separator style * Apply suggestions from code review Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> |
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0ffe5a73c1 | chroe(config):Increase subagent max-turn limits (#1852) | ||
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a283d4a02d |
fix: include soul field in GET /api/agents list response (fixes #1819) (#1863)
Previously, the list endpoint always returned soul=null because
_agent_config_to_response() was called without include_soul=True.
This caused confusion since PUT /api/agents/{name} and GET /api/agents/{name}
both returned the soul content, but the list endpoint silently omitted it.
Co-authored-by: octo-patch <octo-patch@users.noreply.github.com>
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2a150f5d4a |
fix: unblock concurrent threads and workspace hydration (#1839)
* fix: unblock concurrent threads and workspace hydration * fix: restore async title generation * fix: address PR review feedback * style: format lead agent prompt |
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163121d327 |
fix(uploads): handle split-bold headings and ** ** artefacts in extract_outline (#1838)
* feat(uploads): guide agent to use grep/glob/read_file for uploaded documents Add workflow guidance to the <uploaded_files> context block so the agent knows to use grep and glob (added in #1784) alongside read_file when working with uploaded documents, rather than falling back to web search. This is the final piece of the three-PR PDF agentic search pipeline: - PR1 (#1727): pymupdf4llm converter produces structured Markdown with headings - PR2 (#1738): document outline injected into agent context with line numbers - PR3 (this): agent guided to use outline + grep + read_file workflow * feat(uploads): add file-first priority and fallback guidance to uploaded_files context * fix(uploads): handle split-bold headings and ** ** artefacts in extract_outline - Add _clean_bold_title() to merge adjacent bold spans (** **) produced by pymupdf4llm when bold text crosses span boundaries - Add _SPLIT_BOLD_HEADING_RE (Style 3) to recognise **<num>** **<title>** headings common in academic papers; excludes pure-number table headers and rows with more than 4 bold blocks - When outline is empty, read first 5 non-empty lines of the .md as a content preview and surface a grep hint in the agent context - Update _format_file_entry to render the preview + grep hint instead of silently omitting the outline section - Add 3 new extract_outline tests and 2 new middleware tests (65 total) * fix(uploads): address Copilot review comments on extract_outline regex - Replace ASCII [A-Za-z] guard with negative lookahead to support non-ASCII titles (e.g. **1** **概述**); pure-numeric/punctuation blocks still excluded - Replace .+ with [^*]+ and cap repetition at {0,2} (four blocks total) to keep _SPLIT_BOLD_HEADING_RE linear and avoid ReDoS on malformed input - Remove now-redundant len(blocks) <= 4 code-level check (enforced by regex) - Log debug message with exc_info when preview extraction fails |
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19809800f1 |
feat: support wecom channel (#1390)
* feat: support wecom channel * fix: sending file to client Signed-off-by: fengxusong <7008971+fengxsong@users.noreply.github.com> * test: add unit tests for wecom channel Signed-off-by: fengxusong <7008971+fengxsong@users.noreply.github.com> * docs: add example configs and setup docs Signed-off-by: fengxusong <7008971+fengxsong@users.noreply.github.com> * revert pypi default index setting Signed-off-by: fengxusong <7008971+fengxsong@users.noreply.github.com> * revert: keeping codes in harness untouched Signed-off-by: fengxusong <7008971+fengxsong@users.noreply.github.com> * fix: format issue Signed-off-by: fengxusong <7008971+fengxsong@users.noreply.github.com> * fix: resolve Copilot comments Signed-off-by: fengxusong <7008971+fengxsong@users.noreply.github.com> --------- Signed-off-by: fengxusong <7008971+fengxsong@users.noreply.github.com> Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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db82b59254 |
fix(middleware): handle list-type AIMessage.content in LoopDetectionMiddleware (#1823)
* fix: inject longTermBackground into memory prompt
The format_memory_for_injection function only processed recentMonths and
earlierContext from the history section, silently dropping longTermBackground.
The LLM writes longTermBackground correctly and it persists to memory.json,
but it was never injected into the system prompt — making the user's
long-term background invisible to the AI.
Add the missing field handling and a regression test.
* fix(middleware): handle list-type AIMessage.content in LoopDetectionMiddleware
LangChain AIMessage.content can be str | list. When using providers that
return structured content blocks (e.g. Anthropic thinking mode, certain
OpenAI-compatible gateways), content is a list of dicts like
[{"type": "text", "text": "..."}].
The hard_limit branch in _apply() concatenated content with a string via
(last_msg.content or "") + f"\n\n{_HARD_STOP_MSG}", which raises
TypeError when content is a non-empty list (list + str is invalid).
Add _append_text() static method that:
- Returns the text directly when content is None
- Appends a {"type": "text"} block when content is a list
- Falls back to string concatenation when content is a str
This is consistent with how other modules in the project already handle
list content (client.py._extract_text, memory_middleware, executor.py).
* test(middleware): add unit tests for _append_text and list content hard stop
Add regression tests to verify LoopDetectionMiddleware handles list-type
AIMessage.content correctly during hard stop:
- TestAppendText: unit tests for the new _append_text() static method
covering None, str, list (including empty list) content types
- TestHardStopWithListContent: integration tests verifying hard stop
works correctly with list content (Anthropic thinking mode), None
content, and str content
Requested by reviewer in PR #1823.
* fix(middleware): improve _append_text robustness and test isolation
- Add explicit isinstance(content, str) check with fallback for
unexpected types (coerce to str) to prevent TypeError on edge cases
- Deep-copy list content in _make_state() test helper to prevent
shared mutable references across test iterations
- Add test_unexpected_type_coerced_to_str: verify fallback for
non-str/list/None content types
- Add test_list_content_not_mutated_in_place: verify _append_text
does not modify the original list
* style: fix ruff format whitespace in test file
---------
Co-authored-by: ppyt <14163465+ppyt@users.noreply.github.com>
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ddfc988bef |
feat(uploads): add pymupdf4llm PDF converter with auto-fallback and async offload (#1727)
* feat(uploads): add pymupdf4llm PDF converter with auto-fallback and async offload - Introduce pymupdf4llm as an optional PDF converter with better heading detection and table preservation than MarkItDown - Auto mode: prefer pymupdf4llm when installed; fall back to MarkItDown when output is suspiciously sparse (image-based / scanned PDFs) - Sparsity check uses chars-per-page (< 50 chars/page) rather than an absolute threshold, correctly handling both short and long documents - Large files (> 1 MB) are offloaded to asyncio.to_thread() to avoid blocking the event loop (related: #1569) - Add UploadsConfig with pdf_converter field (auto/pymupdf4llm/markitdown) - Add pymupdf4llm as optional dependency: pip install deerflow-harness[pymupdf] - Add 14 unit tests covering sparsity heuristic, routing logic, and async path * fix(uploads): address Copilot review comments on PDF converter - Fix docstring: MIN_CHARS_PYMUPDF -> _MIN_CHARS_PER_PAGE (typo) - Fix file handle leak: wrap pymupdf.open in try/finally to ensure doc.close() - Fix silent fallback gap: _convert_pdf_with_pymupdf4llm now catches all conversion exceptions (not just ImportError), so encrypted/corrupt PDFs fall back to MarkItDown instead of propagating - Tighten type: pdf_converter field changed from str to Literal[auto|pymupdf4llm|markitdown] - Normalize config value: _get_pdf_converter() strips and lowercases the raw config string, warns and falls back to 'auto' on unknown values |
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5ff230eafd |
feat(uploads): inject document outline into agent context for converted files (#1738)
* feat(uploads): inject document outline into agent context for converted files
Extract headings from converted .md files and inject them into the
<uploaded_files> context block so the agent can navigate large documents
by line number before reading.
- Add `extract_outline()` to `file_conversion.py`: recognises standard
Markdown headings (#/##/###) and SEC-style bold structural headings
(**ITEM N. BUSINESS**, **PART II**); caps at 50 entries; excludes
cover-page boilerplate (WASHINGTON DC, CURRENT REPORT, SIGNATURES)
- Add `_extract_outline_for_file()` helper in `uploads_middleware.py`:
looks for a sibling `.md` file produced by the conversion pipeline
- Update `UploadsMiddleware._create_files_message()` to render the outline
under each file entry with `L{line}: {title}` format and a `read_file`
prompt for range-based reading
- Tests: 10 new tests for `extract_outline()`, 4 new tests for outline
injection in `UploadsMiddleware`; existing test updated for new `outline`
field in `uploaded_files` state
Partially addresses #1647 (agent ignores uploaded files).
* fix(uploads): stream outline file reads and strip inline bold from heading titles
- Switch extract_outline() from read_text().splitlines() to open()+line iteration
so large converted documents are not loaded into memory on every agent turn;
exits as soon as MAX_OUTLINE_ENTRIES is reached (Copilot suggestion)
- Strip **...** wrapper from standard Markdown heading titles before appending
to outline so agent context stays clean (e.g. "## **Overview**" → "Overview")
(Copilot suggestion)
- Remove unused pathlib.Path import and fix import sort order in test_file_conversion.py
to satisfy ruff CI lint
* fix(uploads): show truncation hint when outline exceeds MAX_OUTLINE_ENTRIES
When extract_outline() hits the cap it now appends a sentinel entry
{"truncated": True} instead of silently dropping the rest of the headings.
UploadsMiddleware reads the sentinel and renders a hint line:
... (showing first 50 headings; use `read_file` to explore further)
Without this the agent had no way to know the outline was incomplete and
would treat the first 50 headings as the full document structure.
* fix(uploads): fall back to configurable.thread_id when runtime.context lacks thread_id
runtime.context does not always carry thread_id (depends on LangGraph
invocation path). ThreadDataMiddleware already falls back to
get_config().configurable.thread_id — apply the same pattern so
UploadsMiddleware can resolve the uploads directory and attach outlines
in all invocation paths.
* style: apply ruff format
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
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6dbdd4674f |
fix: guarantee END sentinel delivery when stream bridge queue is full (#1695)
When MemoryStreamBridge queue reaches capacity, publish_end() previously used the same 30s timeout + drop strategy as regular events. If the END sentinel was dropped, subscribe() would loop forever waiting for it, causing the SSE connection to hang indefinitely and leaking _queues and _counters resources for that run_id. Changes: - publish_end() now evicts oldest regular events when queue is full to guarantee END sentinel delivery — the sentinel is the only signal that allows subscribers to terminate - Added per-run drop counters (_dropped_counts) with dropped_count() and dropped_total properties for observability - cleanup() and close() now clear drop counters - publish() logs total dropped count per run for easier debugging Tests: - test_end_sentinel_delivered_when_queue_full: verifies END arrives even with a completely full queue - test_end_sentinel_evicts_oldest_events: verifies eviction behavior - test_end_sentinel_no_eviction_when_space_available: no side effects when queue has room - test_concurrent_tasks_end_sentinel: 4 concurrent producer/consumer pairs all terminate properly - test_dropped_count_tracking, test_dropped_total, test_cleanup_clears_dropped_counts, test_close_clears_dropped_counts: drop counter coverage Closes #1689 Co-authored-by: voidborne-d <voidborne-d@users.noreply.github.com> |
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83039fa22c |
fix: use SystemMessage+HumanMessage for follow-up question generation (#1751)
* fix: use SystemMessage+HumanMessage for follow-up question generation (fixes #1697) Some models (e.g. MiniMax-M2.7) require the system prompt and user content to be passed as separate message objects rather than a single combined string. Invoking with a plain string sends everything as a HumanMessage, which causes these models to ignore the generation instructions and fail to produce valid follow-up questions. * test: verify model is invoked with SystemMessage and HumanMessage |
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1694c616ef | feat(sandbox): add read-only support for local sandbox path mappings (#1808) | ||
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c6cdf200ce |
feat(sandbox): add built-in grep and glob tools (#1784)
* feat(sandbox): add grep and glob tools * refactor(aio-sandbox): use native file search APIs * fix(sandbox): address review issues in grep/glob tools - aio_sandbox: use should_ignore_path() instead of should_ignore_name() for include_dirs=True branch to filter nested ignored paths correctly - aio_sandbox: add early exit when max_results reached in glob loop - aio_sandbox: guard entry.path.startswith(path) before stripping prefix - aio_sandbox: validate regex locally before sending to remote API - search: skip lines exceeding max_line_chars to prevent ReDoS - search: remove resolve() syscall in os.walk loop - tools: avoid double get_thread_data() call in glob_tool/grep_tool - tests: add 6 new cases covering the above code paths - tests: patch get_app_config in truncation test to isolate config * Fix sandbox grep/glob review feedback * Remove unrelated Langfuse RFC from PR |
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48565664e0 |
fix ACP mcpServers payload (#1735)
* fix ACP mcpServers payload * Handle invalid ACP MCP config |
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76fad8b08d |
feat(client): add available_skills parameter to DeerFlowClient (#1779)
* feat(client): add `available_skills` parameter to DeerFlowClient for dynamic runtime skill filtering * Update backend/packages/harness/deerflow/client.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * fix(client): include `agent_name` and `available_skills` in agent config cache key --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> |
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5664b9d413 |
fix: inject longTermBackground into memory prompt (#1734)
The format_memory_for_injection function only processed recentMonths and earlierContext from the history section, silently dropping longTermBackground. The LLM writes longTermBackground correctly and it persists to memory.json, but it was never injected into the system prompt — making the user's long-term background invisible to the AI. Add the missing field handling and a regression test. Co-authored-by: ppyt <14163465+ppyt@users.noreply.github.com> |
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6de9c7b43f |
Improve Python reliability in channel retries and thread typing (#1776)
Agent-Logs-Url: https://github.com/0xxy0/deer-flow/sessions/95336da6-e16d-43b4-834a-e5534c9396c5 Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com> |
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f56d0b4869 |
fix(sandbox): exclude URL paths from absolute path validation (#1385) (#1419)
* fix(sandbox): URL路径被误判为不安全绝对路径 (#1385) 在本地沙箱模式下,bash工具对命令做绝对路径安全校验时,会把curl命令中的 HTTPS URL(如 https://example.com/api/v1/check)误识别为本地绝对路径并拦截。 根因:_ABSOLUTE_PATH_PATTERN 正则的负向后行断言 (?<![:\w]) 只排除了冒号和 单词字符,但 :// 中第二个斜杠前面是第一个斜杠(/),不在排除列表中,导致 //example.com/api/... 被匹配为绝对路径 /example.com/api/...。 修复:在负向后行断言中增加斜杠字符,改为 (?<![:\w/]),使得 :// 中的连续 斜杠不会触发绝对路径匹配。同时补充了URL相关的单元测试用例。 Signed-off-by: moose-lab <moose-lab@users.noreply.github.com> * fix(sandbox): refine absolute path regex to preserve file:// defense-in-depth Change lookbehind from (?<![:\w/]) to (?<![:\w])(?<!:/) so only the second slash in :// sequences is excluded. This keeps URL paths from false-positiving while still letting the regex detect /etc/passwd in file:///etc/passwd. Also add explicit file:// URL blocking and tests. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Signed-off-by: moose-lab <moose-lab@users.noreply.github.com> Co-authored-by: moose-lab <moose-lab@users.noreply.github.com> Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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a2cb38f62b |
fix: prevent concurrent subagent file write conflicts in sandbox tools (#1714)
* fix: prevent concurrent subagent file write conflicts Serialize same-path str_replace operations in sandbox tools Guard AioSandbox write_file/update_file with the existing sandbox lock Add regression tests for concurrent str_replace and append races Verify with backend full tests and ruff lint checks * fix(sandbox): Fix the concurrency issue of file operations on the same path in isolated sandboxes. Ensure that different sandbox instances use independent locks for file operations on the same virtual path to avoid concurrency conflicts. Change the lock key from a single path to a composite key of (sandbox.id, path), and add tests to verify the concurrent safety of isolated sandboxes. * feat(sandbox): Extract file operation lock logic to standalone module and fix concurrency issues Extract file operation lock related logic from tools.py into a separate file_operation_lock.py module. Fix data race issues during concurrent str_replace and write_file operations. |
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f8fb8d6fb1 |
feat/per agent skill filter (#1650)
* feat(agent): 为AgentConfig添加skills字段并更新lead_agent系统提示 在AgentConfig中添加skills字段以支持配置agent可用技能 更新lead_agent的系统提示模板以包含可用技能信息 * fix: resolve agent skill configuration edge cases and add tests * Update backend/packages/harness/deerflow/agents/lead_agent/prompt.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * refactor(agent): address PR review comments for skills configuration - Add detailed docstring to `skills` field in `AgentConfig` to clarify the semantics of `None` vs `[]`. - Add unit tests in `test_custom_agent.py` to verify `load_agent_config()` correctly parses omitted skills and explicit empty lists. - Fix `test_make_lead_agent_empty_skills_passed_correctly` to include `agent_name` in the runtime config, ensuring it exercises the real code path. * docs: 添加关于按代理过滤技能的配置说明 在配置示例文件和文档中添加说明,解释如何通过代理的config.yaml文件限制加载的技能 --------- Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> |
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2d1f90d5dc |
feat(tracing): add optional Langfuse support (#1717)
* feat(tracing): add optional Langfuse support * Fix tracing fail-fast behavior for explicitly enabled providers * fix(lint) |
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3a672b39c7 |
Fix/1681 llm call retry handling (#1683)
* fix(runtime): handle llm call errors gracefully * fix(runtime): preserve graph control flow in llm retry middleware --------- Co-authored-by: luoxiao6645 <luoxiao6645@gmail.com> |
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df5339b5d0 |
feat(sandbox): truncate oversized bash and read_file tool outputs (#1677)
* feat(sandbox): truncate oversized bash and read_file tool outputs Long tool outputs (large directory listings, multi-MB source files) can overflow the model's context window. Two new configurable limits: - bash_output_max_chars (default 20000): middle-truncates bash output, preserving both head and tail so stderr at the end is not lost - read_file_output_max_chars (default 50000): head-truncates file output with a hint to use start_line/end_line for targeted reads Both limits are enforced at the tool layer (sandbox/tools.py) rather than middleware, so truncation is guaranteed regardless of call path. Setting either limit to 0 disables truncation entirely. Measured: read_file on a 250KB source file drops from 63,698 tokens to 19,927 tokens (69% reduction) with the default limit. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(tests): remove unused pytest import and fix import sort order * style: apply ruff format to sandbox/tools.py * refactor(sandbox): address Copilot review feedback on truncation feature - strict hard cap: while-loop ensures result (including marker) ≤ max_chars - max_chars=0 now returns "" instead of original output - get_app_config() wrapped in try/except with fallback to defaults - sandbox_config.py: add ge=0 validation on truncation limit fields - config.example.yaml: bump config_version 4→5 - tests: add len(result) <= max_chars assertions, edge-case (max=0, small max, various sizes) tests; fix skipped-count test for strict hard cap * refactor(sandbox): replace while-loop truncation with fixed marker budget Use a pre-allocated constant (_MARKER_MAX_LEN) instead of a convergence loop to ensure result <= max_chars. Simpler, safer, and skipped-char count in the marker is now an exact predictable value. * refactor(sandbox): compute marker budget dynamically instead of hardcoding * fix(sandbox): make max_chars=0 disable truncation instead of returning empty string --------- Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> Co-authored-by: JeffJiang <for-eleven@hotmail.com> |
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0a379602b8 |
fix: avoid treating Feishu file paths as commands (#1654)
Feishu channel classified any slash-prefixed text (including absolute paths such as /mnt/user-data/...) as a COMMAND, causing them to be misrouted through the command pipeline instead of the chat pipeline. Fix by introducing a shared KNOWN_CHANNEL_COMMANDS frozenset in app/channels/commands.py — the single authoritative source for the set of supported slash commands. Both the Feishu inbound parser and the ChannelManager's unknown-command reply now derive from it, so adding or removing a command requires only one edit. Changes: - app/channels/commands.py (new): defines KNOWN_CHANNEL_COMMANDS - app/channels/feishu.py: replace local KNOWN_FEISHU_COMMANDS with the shared constant; _is_feishu_command() now gates on it - app/channels/manager.py: import KNOWN_CHANNEL_COMMANDS and use it in the unknown-command fallback reply so the displayed list stays in sync - tests/test_feishu_parser.py: parametrize over every entry in KNOWN_CHANNEL_COMMANDS (each must yield msg_type=command) and add parametrized chat cases for /unknown, absolute paths, etc. Made with Cursor Made-with: Cursor Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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1fb5acee39 |
fix(gateway): prevent 400 error when client sends context with configurable (#1660)
* fix(gateway): prevent 400 error when client sends context with configurable Fixes #1290 LangGraph >= 0.6.0 rejects requests that include both 'configurable' and 'context' in the run config. If the client (e.g. useStream hook) sends a 'context' key, we now honour it and skip creating our own 'configurable' dict to avoid the conflict. When no 'context' is provided, we fall back to the existing 'configurable' behaviour with thread_id. * fix(gateway): address review feedback — warn on dual keys, fix runtime injection, add tests - Log a warning when client sends both 'context' and 'configurable' so it's no longer silently dropped (reviewer feedback) - Ensure thread_id is available in config['context'] when present so middlewares can find it there too - Add test coverage for the context path, the both-keys-present case, passthrough of other keys, and the no-config fallback * style: ruff format services.py --------- Co-authored-by: JasonOA888 <JasonOA888@users.noreply.github.com> Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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e97c8c9943 |
fix(skills): support parsing multiline YAML strings in SKILL.md frontmatter (#1703)
* fix(skills): support parsing multiline YAML strings in SKILL.md frontmatter * test(skills): add tests for multiline YAML descriptions |
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c2ff59a5b1 |
fix(gateway): merge context field into configurable for langgraph-compat runs (#1699) (#1707)
The langgraph-compat layer dropped the DeerFlow-specific `context` field from run requests, causing agent config (subagent_enabled, is_plan_mode, thinking_enabled, etc.) to fall back to defaults. Add `context` to RunCreateRequest and merge allowlisted keys into config.configurable in start_run, with existing configurable values taking precedence. Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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2f3744f807 |
refactor: replace sync requests with async httpx in Jina AI client (#1603)
* refactor: replace sync requests with async httpx in Jina AI client Replace synchronous `requests.post()` with `httpx.AsyncClient` in JinaClient.crawl() and make web_fetch_tool async. This is part of the planned async concurrency optimization for the agent hot path (see docs/TODO.md). * fix: address Copilot review feedback on async Jina client - Short-circuit error strings in web_fetch_tool before passing to ReadabilityExtractor, preventing misleading extraction results - Log missing JINA_API_KEY warning only once per process to reduce noise under concurrent async fetching - Use logger.exception instead of logger.error in crawl exception handler to preserve stack traces for debugging - Add async web_fetch_tool tests and warn-once coverage * fix: mock get_app_config in web_fetch_tool tests for CI The web_fetch_tool tests failed in CI because get_app_config requires a config.yaml file that isn't present in the test environment. Mock the config loader to remove the filesystem dependency. --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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0cdecf7b30 |
feat(memory): structured reflection + correction detection in MemoryMiddleware (#1620) (#1668)
* feat(memory): add structured reflection and correction detection * fix(memory): align sourceError schema and prompt guidance --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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3e461d9d08 |
fix: use safe docker bind mount syntax for sandbox mounts (#1655)
Docker's -v host:container syntax is ambiguous for Windows drive-letter paths (e.g. D:/...) because ':' is both the drive separator and the volume separator, causing mount failures on Windows hosts. Introduce _format_container_mount() which uses '--mount type=bind,...' for Docker (unambiguous on all platforms) and keeps '-v' for Apple Container runtime which does not support the --mount flag yet. Adds unit tests covering Windows paths, read-only mounts, and Apple Container pass-through. Made-with: Cursor |
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6ff60f2af1 |
fix(gateway): forward assistant_id as agent_name in build_run_config (#1667)
* fix(gateway): forward assistant_id as agent_name in build_run_config Fixes #1644 When the LangGraph Platform-compatible /runs endpoint receives a custom assistant_id (e.g. 'finalis'), the Gateway's build_run_config() silently ignored it — configurable['agent_name'] was never set, so make_lead_agent fell through to the default lead agent and SOUL.md was never loaded. Root cause (introduced in #1403): resolve_agent_factory() correctly falls back to make_lead_agent for all assistant_id values, but build_run_config() had no assistant_id parameter and never injected configurable['agent_name']. The full call chain: POST /runs (assistant_id='finalis') → resolve_agent_factory('finalis') # returns make_lead_agent ✓ → build_run_config(thread_id, ...) # no agent_name injected ✗ → make_lead_agent(config) → cfg.get('agent_name') → None → load_agent_soul(None) → base SOUL.md (doesn't exist) → None Fix: - Add keyword-only parameter to build_run_config(). - When assistant_id is set and differs from 'lead_agent', inject it as configurable['agent_name'] (matching the channel manager's existing _resolve_run_params() logic for IM channels). - Honour an explicit configurable['agent_name'] in the request body; assistant_id mapping only fills the gap when it is absent. - Remove stale log-only branch from resolve_agent_factory(); update docstring to explain the factory/configurable split. Tests added (test_gateway_services.py): - Custom assistant_id injects configurable['agent_name'] - 'lead_agent' assistant_id does NOT inject agent_name - None assistant_id does NOT inject agent_name - Explicit configurable['agent_name'] in request is not overwritten - resolve_agent_factory returns make_lead_agent for all inputs * style: format with ruff * fix: validate and normalize assistant_id to prevent path traversal Addresses Copilot review: strip/lowercase/replace underscores and reject names that don't match [a-z0-9-]+, consistent with ChannelManager._normalize_custom_agent_name(). --------- Co-authored-by: voidborne-d <voidborne-d@users.noreply.github.com> |
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a3bfea631c |
fix(sandbox): serialize concurrent exec_command calls in AioSandbox (#1435)
* fix(sandbox): serialize concurrent exec_command calls in AioSandbox The AIO sandbox container maintains a single persistent shell session that corrupts when multiple exec_command requests arrive concurrently (e.g. when ToolNode issues parallel tool_calls). The corrupted session returns 'ErrorObservation' strings as output, cascading into subsequent commands. Add a threading.Lock to AioSandbox to serialize shell commands. As a secondary defense, detect ErrorObservation in output and retry with a fresh session ID. Fixes #1433 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix(sandbox): address Copilot review findings - Fix shell injection in list_dir: use shlex.quote(path) to escape user-provided paths in the find command - Narrow ErrorObservation retry condition from broad substring match to the specific corruption signature to prevent false retries - Improve test_lock_prevents_concurrent_execution: use threading.Barrier to ensure all workers contend for the lock simultaneously - Improve test_list_dir_uses_lock: assert lock.locked() is True during exec_command to verify lock acquisition * style: auto-format with ruff --------- Co-authored-by: Matt Van Horn <455140+mvanhorn@users.noreply.github.com> Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> |
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aae59a8ba8 |
fix: surface configured sandbox mounts to agents (#1638)
* fix: surface configured sandbox mounts to agents * fix: address PR review feedback --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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3ff15423d6 |
fix Windows Docker sandbox path mounting (#1634)
* fix windows docker sandbox paths * fix windows sandbox mount validation * fix backend checks for windows sandbox path PR |
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9a557751d6 |
feat: support memory import and export (#1521)
* feat: support memory import and export * fix(memory): address review feedback * style: format memory settings page --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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34e835bc33 |
feat(gateway): implement LangGraph Platform API in Gateway, replace langgraph-cli (#1403)
* feat(gateway): implement LangGraph Platform API in Gateway, replace langgraph-cli Implement all core LangGraph Platform API endpoints in the Gateway, allowing it to fully replace the langgraph-cli dev server for local development. This eliminates a heavyweight dependency and simplifies the development stack. Changes: - Add runs lifecycle endpoints (create, stream, wait, cancel, join) - Add threads CRUD and search endpoints - Add assistants compatibility endpoints (search, get, graph, schemas) - Add StreamBridge (in-memory pub/sub for SSE) and async provider - Add RunManager with atomic create_or_reject (eliminates TOCTOU race) - Add worker with interrupt/rollback cancel actions and runtime context injection - Route /api/langgraph/* to Gateway in nginx config - Skip langgraph-cli startup by default (SKIP_LANGGRAPH_SERVER=0 to restore) - Add unit tests for RunManager, SSE format, and StreamBridge * fix: drain bridge queue on client disconnect to prevent backpressure When on_disconnect=continue, keep consuming events from the bridge without yielding, so the worker is not blocked by a full queue. Only on_disconnect=cancel breaks out immediately. Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * fix: remove pytest import Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * fix: Fix default stream_mode to ["values", "messages-tuple"] Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * fix: Remove unused if_exists field from ThreadCreateRequest Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * fix: address review comments on gateway LangGraph API - Mount runs.py router in app.py (missing include_router) - Normalize interrupt_before/after "*" to node list before run_agent() - Use entry.id for SSE event ID instead of counter - Drain bridge queue on disconnect when on_disconnect=continue - Reuse serialization helper in wait_run() for consistent wire format - Reject unsupported multitask_strategy with 400 - Remove SKIP_LANGGRAPH_SERVER fallback, always use Gateway * feat: extract app.state access into deps.py Encapsulate read/write operations for singleton objects (RunManager, StreamBridge, checkpointer) held in app.state into a shared utility, reducing repeated access patterns across router modules. * feat: extract deerflow.runtime.serialization module with tests Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * refactor: replace duplicated serialization with deerflow.runtime.serialization Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: extract app/gateway/services.py with run lifecycle logic Create a service layer that centralizes SSE formatting, input/config normalization, and run lifecycle management. Router modules will delegate to these functions instead of using private cross-imported helpers. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * refactor: wire routers to use services layer, remove cross-module private imports Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * style: apply ruff formatting to refactored files Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(runtime): support LangGraph dev server and add compat route - Enable official LangGraph dev server for local development workflow - Decouple runtime components from agents package for better separation - Provide gateway-backed fallback route when dev server is skipped - Simplify lifecycle management using context manager in gateway * feat(runtime): add Store providers with auto-backend selection - Add async_provider.py and provider.py under deerflow/runtime/store/ - Support memory, sqlite, postgres backends matching checkpointer config - Integrate into FastAPI lifespan via AsyncExitStack in deps.py - Replace hardcoded InMemoryStore with config-driven factory * refactor(gateway): migrate thread management from checkpointer to Store and resolve multiple endpoint failures - Add Store-backed CRUD helpers (_store_get, _store_put, _store_upsert) - Replace checkpoint-scanning search with two-phase strategy: phase 1 reads Store (O(threads)), phase 2 backfills from checkpointer for legacy/LangGraph Server threads with lazy migration - Extend Store record schema with values field for title persistence - Sync thread title from checkpoint to Store after run completion - Fix /threads/{id}/runs/{run_id}/stream 405 by accepting both GET and POST methods; POST handles interrupt/rollback actions - Fix /threads/{id}/state 500 by separating read_config and write_config, adding checkpoint_ns to configurable, and shallow-copying checkpoint/metadata before mutation - Sync title to Store on state update for immediate search reflection - Move _upsert_thread_in_store into services.py, remove duplicate logic - Add _sync_thread_title_after_run: await run task, read final checkpoint title, write back to Store record - Spawn title sync as background task from start_run when Store exists * refactor(runtime): deduplicate store and checkpointer provider logic Extract _ensure_sqlite_parent_dir() helper into checkpointer/provider.py and use it in all three places that previously inlined the same mkdir logic. Consolidate duplicate error constants in store/async_provider.py by importing from store/provider.py instead of redefining them. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * refactor(runtime): move SQLite helpers to runtime/store, checkpointer imports from store _resolve_sqlite_conn_str and _ensure_sqlite_parent_dir now live in runtime/store/provider.py. agents/checkpointer/provider and agents/checkpointer/async_provider import from there, reversing the previous dependency direction (store → checkpointer becomes checkpointer → store). Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * refactor(runtime): extract SQLite helpers into runtime/store/_sqlite_utils.py Move resolve_sqlite_conn_str and ensure_sqlite_parent_dir out of checkpointer/provider.py into a dedicated _sqlite_utils module. Functions are now public (no underscore prefix), making cross-module imports semantically correct. All four provider files import from the single shared location. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(gateway): use adelete_thread to fully remove thread checkpoints on delete AsyncSqliteSaver has no adelete method — the previous hasattr check always evaluated to False, silently leaving all checkpoint rows in the database. Switch to adelete_thread(thread_id) which deletes every checkpoint and pending-write row for the thread across all namespaces (including sub-graph checkpoints). Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(gateway): remove dead bridge_cm/ckpt_cm code and fix StrEnum lint app.py had unreachable code after the async-with lifespan refactor: bridge_cm and ckpt_cm were referenced but never defined (F821), and the channel service startup/shutdown was outside the langgraph_runtime block so it never ran. Move channel service lifecycle inside the async-with block where it belongs. Replace str+Enum inheritance in RunStatus and DisconnectMode with StrEnum as suggested by UP042. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * style: format with ruff --------- Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> Co-authored-by: JeffJiang <for-eleven@hotmail.com> Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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9bcdba6038 |
fix: promote deferred tools after tool_search returns schema (#1570)
* fix: promote matched tools from deferred registry after tool_search returns schema After tool_search returns a tool's full schema, the tool is promoted (removed from the deferred registry) so DeferredToolFilterMiddleware stops filtering it from bind_tools on subsequent LLM calls. Without this, deferred tools are permanently filtered — the LLM gets the schema from tool_search but can never invoke the tool because the middleware keeps stripping it. Fixes #1554 * test: add promote() and tool_search promotion tests Tests cover: - promote removes tools from registry - promote nonexistent/empty is no-op - search returns nothing after promote - middleware passes promoted tools through - tool_search auto-promotes matched tools (select + keyword) * fix: address review — lint blank line + empty registry guard - Add missing blank line between FakeRequest methods (E301) - Use 'if not registry' to handle empty registries consistently --------- Co-authored-by: d 🔹 <258577966+voidborne-d@users.noreply.github.com> Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |