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27 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
 Xinmin Zeng
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268fdd6968 |
fix(gateway): drain in-flight runs before closing checkpointer on shutdown (#3381)
* fix(gateway): drain in-flight runs before closing checkpointer on shutdown Chat runs execute in fire-and-forget background asyncio tasks that write checkpoints through a shared checkpointer. On shutdown, langgraph_runtime's AsyncExitStack tore down the checkpointer's postgres connection pool while those run tasks were still mid-graph. langgraph's AsyncPregelLoop._checkpointer_put_after_previous then ran its `finally: await checkpointer.aput(...)` against the closed pool, raising psycopg_pool.PoolClosed. Because that put runs in a langgraph-internal task (not on run_agent's call stack), run_agent's try/except cannot catch it and it surfaces as "unhandled exception during asyncio.run() shutdown". Add RunManager.shutdown() to cancel and bounded-await all in-flight runs, and call it from langgraph_runtime BEFORE the AsyncExitStack closes the checkpointer, so the final checkpoint write lands while the pool is still open. The drain is bounded by a timeout so a stuck run cannot hang worker shutdown, and is shielded so a second shutdown signal cannot abandon it mid-drain and reopen the race. Closes #3373 * fix(gateway): address review — preserve completed-run status, bound drain persistence Addresses Copilot review on #3381: - RunManager.shutdown(): decide run status AFTER the drain. Under the lock it now only requests cancellation; after asyncio.wait it marks/persists `interrupted` only for runs still pending or ended cancelled. A run that completes (e.g. `success`) during the drain window keeps its real terminal status instead of being unconditionally overwritten. - Bound the trailing status persistence within the timeout budget (deadline = loop.time()+timeout; gather wrapped in asyncio.wait_for) so a slow store backing off under DB pressure cannot push shutdown past the deadline. - deps: use asyncio.create_task instead of asyncio.ensure_future. - tests: wait deterministically for the run to be in-flight (poll the first checkpoint) instead of a fixed sleep; init shutdown_calls explicitly in the recovery test double; add regression test asserting a run completing during the drain keeps its status (in memory and in the store). * fix(gateway): address maintainer review — surface failed drain persists, clarify timeout constant Addresses @WillemJiang review on #3381: - shutdown(): inspect the gather result of the trailing interrupted-status persistence. _persist_status is best-effort (it catches + logs its own failure with exc_info and returns False, so it never raises out of the gather), but the aggregate result was never checked — a partial failure had no shutdown-level visibility. Now any escaped Exception is logged, and any False (a persist that did not confirm) is logged with the run_id. Added regression test test_shutdown_surfaces_failed_interrupted_persist. - deps: clarify the _RUN_DRAIN_TIMEOUT_SECONDS comment — state the actual value of _SHUTDOWN_HOOK_TIMEOUT_SECONDS (5.0s) and that both count toward the lifespan shutdown window. Kept as two separate constants (independent teardown steps that may diverge) rather than one shared "must match" value. - Verified no other test fake needs the shutdown stub: _FakeRunManager in test_worker_langfuse_metadata.py is a run_agent() argument (worker path), never injected into langgraph_runtime, so it never receives shutdown(). |
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Nan Gao
|
79cc227917 |
fix(middleware): fix LLM fallback run status (#3321)
* Fix LLM fallback run status * optimize LLM fallback maker extraction in streaming path |
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rayhpeng
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0fb05825a2 |
fix(runtime): make run creation persistence atomic (#3152)
* fix runtime run creation persistence atomicity * fix run creation cancellation rollback * fix run manager test cleanup await * clarify run creation rollback on cancellation * document new run persistence rollback boundary --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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AochenShen99
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66d6a6a4e8 |
fix: harden run finalization persistence (#3155)
* fix: harden run finalization persistence * style: format gateway recovery test * fix: align run repository return types * fix: harden completion recovery follow-up |
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Lawrance_YXLiao
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2eeb597985 |
fix(runs): expose active progress counters (#3148)
* fix(runs): expose active progress counters * fix(runs): avoid delayed progress flush on completion * fix(runs): tighten progress snapshot semantics * fix(runs): preserve omitted progress fields * chore(runs): remove duplicate journal initialization |
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Xinmin Zeng
|
be0eae9825 |
fix(runtime): suppress tool execution when provider safety-terminates with tool_calls (#3035)
* fix(runtime): suppress tool execution when provider safety-terminates with tool_calls When a provider stops generation for safety reasons (OpenAI/Moonshot finish_reason=content_filter, Anthropic stop_reason=refusal, Gemini finish_reason=SAFETY/BLOCKLIST/PROHIBITED_CONTENT/SPII/RECITATION/ IMAGE_SAFETY/...), the response may still carry truncated tool_calls. LangChain's tool router treats any non-empty tool_calls as executable, so partial arguments (e.g. write_file with a half-finished markdown) get dispatched and the agent loops on retry. Add SafetyFinishReasonMiddleware at after_model: detect safety termination via a pluggable detector registry, clear both structured tool_calls and raw additional_kwargs.tool_calls / function_call, preserve response_metadata.finish_reason for downstream observers, stamp additional_kwargs.safety_termination for traces, append a user-facing explanation to message content (list-aware for thinking blocks), and emit a safety_termination custom stream event so SSE consumers can reconcile any "tool starting..." UI. Default detectors cover OpenAI-compatible content_filter, Anthropic refusal, and Gemini safety enums (text + image). Custom providers are added via reflection (same pattern as guardrails). Wired into both lead-agent and subagent runtimes. Closes #3028 * fix(runtime): persist safety_termination as a middleware audit event Address review on #3035: the SSE custom event is great for live consumers but invisible to post-run audit. RunEventStore should carry its own row so operators can answer "which runs were safety-suppressed today?" from a single SQL query without joining the message body. Worker now exposes the run-scoped RunJournal via runtime.context["__run_journal"] (sentinel key, internal channel). SafetyFinishReasonMiddleware calls the previously-unused RunJournal.record_middleware, which emits event_type = "middleware:safety_termination" category = "middleware" content = {name, hook, action, changes={ detector, reason_field, reason_value, suppressed_tool_call_count, suppressed_tool_call_names, suppressed_tool_call_ids, message_id, extras}} Tool *arguments* are deliberately excluded — those are the very content the provider filtered and persisting them would defeat the purpose of the safety filter (per review note in #3035). Graceful skips when journal is absent (subagent runtime, unit tests, no-event-store local dev). Journal exceptions never propagate into the agent loop. Refs #3028 * fix(runtime): satisfy ruff format + address Copilot review - ruff format on safety_finish_reason_config.py and e2e demo (CI lint failed on ruff format --check; backend Makefile lint target runs ruff check AND ruff format --check). - Docstring on SafetyFinishReasonConfig now says resolve_variable to match the actual loader used in from_config (the wording was resolve_class previously; behavior is unchanged — resolve_variable mirrors how guardrails.provider is loaded). - Switch the AIMessage type check in SafetyFinishReasonMiddleware._apply from getattr(last, "type") == "ai" to isinstance(last, AIMessage), matching TokenUsageMiddleware / TodoMiddleware / ViewImageMiddleware / SummarizationMiddleware which are the dominant pattern. Refs #3028 |
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Xinmin Zeng
|
df95154282 |
fix(tracing): propagate session_id and user_id into Langfuse traces (#2944)
* fix(tracing): propagate session_id and user_id into Langfuse traces
Adds Langfuse v4 reserved trace attributes (langfuse_session_id,
langfuse_user_id, langfuse_trace_name, langfuse_tags) to
RunnableConfig.metadata inside the run worker, so the langchain
CallbackHandler can lift them onto the root trace.
- New deerflow.tracing.metadata.build_langfuse_trace_metadata() returns
the reserved keys when Langfuse is in the enabled providers, else {}.
- worker.run_agent merges them with setdefault so caller-supplied keys
win, allowing per-request overrides from upstream metadata.
- session_id mirrors the LangGraph thread_id; user_id reads
get_effective_user_id() (falls back to "default" in no-auth mode).
- trace_name defaults to "lead-agent"; tags carry env and model name
when DEER_FLOW_ENV (or ENVIRONMENT) and a model name are present.
Closes #2930
* fix(tracing): attach Langfuse callback at graph root so metadata propagates
The first commit injected ``langfuse_session_id`` / ``langfuse_user_id`` /
``langfuse_trace_name`` / ``langfuse_tags`` into ``RunnableConfig.metadata``,
but on ``main`` the Langfuse callback is attached at *model* level
(``models/factory.py``). LangChain still threads ``parent_run_id`` through
the contextvar, so the handler sees the model as a nested observation and
``__on_llm_action`` strips the ``langfuse_*`` keys
(``keep_langfuse_trace_attributes=False``). The trace's top-level
``sessionId`` / ``userId`` therefore stayed empty in deer-flow's LangGraph
runtime — confirmed live against a real Langfuse instance.
This commit moves the callback to the **graph invocation root** so the
handler fires ``on_chain_start(parent_run_id=None)`` and runs the
``propagate_attributes`` path that actually lifts ``session_id`` /
``user_id`` onto the trace:
- ``models/factory.py``: add ``attach_tracing`` keyword (default ``True``)
so standalone callers (``MemoryUpdater``, etc.) keep their direct
model-level tracing.
- ``agents/lead_agent/agent.py``: call ``build_tracing_callbacks()`` once
inside ``_make_lead_agent`` and append the result to
``config["callbacks"]``; the four in-graph ``create_chat_model`` sites
(bootstrap, default agent, sync + async summarization) pass
``attach_tracing=False`` to avoid duplicate spans.
- ``agents/middlewares/title_middleware.py``: same ``attach_tracing=False``
for the title-generation model, since it inherits the graph's
RunnableConfig via ``_get_runnable_config``.
Test updates:
- ``tests/test_lead_agent_model_resolution.py`` and
``tests/test_title_middleware_core_logic.py``: extend the fake
``create_chat_model`` signatures / mock assertions to accept the new
``attach_tracing`` kwarg.
- ``tests/test_worker_langfuse_metadata.py``: switch the no-user fallback
test from direct ContextVar mutation to ``monkeypatch.setattr`` on
``get_effective_user_id`` to avoid pollution across the langfuse OTel
global tracer provider.
- ``tests/conftest.py``: add an autouse fixture that resets
``deerflow.config.title_config._title_config`` to its pristine default
after every test. Any test that loads the real ``config.yaml`` (via
``get_app_config()``) calls ``load_title_config_from_dict`` and mutates
the module-level singleton, which previously poisoned the
title-middleware suite when run after, e.g., the new
``test_worker_langfuse_metadata.py`` cases. The fixture is independent
of this PR's main change but unblocks the cross-file test run.
Live verification (same Langfuse instance as before):
- Drove ``worker.run_agent`` against the real ``make_lead_agent`` +
``gpt-4o-mini`` for three distinct ``user_context`` identities
(``fancy-engineer``, ``alice-pm``, ``bob-designer``).
- Each run produced one ``lead-agent`` trace whose top-level
``sessionId`` / ``userId`` / ``tags`` carry the expected values, e.g.
``session=e2e-2930-8f347c-alice-pm user=alice-pm name='lead-agent'
tags=['model:gpt-4o-mini']``.
Refs #2930.
* fix(tracing): extend root-callback + metadata injection to the embedded client
Addresses Copilot review on PR #2944.
Commit 2 disabled model-level tracing for ``TitleMiddleware`` and
``_create_summarization_middleware`` because ``_make_lead_agent`` now
attaches the tracing callbacks at the graph invocation root. But the
embedded ``DeerFlowClient`` does not call ``_make_lead_agent`` — it
calls ``_build_middlewares`` directly and never appends the tracing
handlers to its ``RunnableConfig``. So under the embedded path,
title-generation and summarization LLM calls were left untraced —
a regression introduced by this PR.
This commit mirrors the gateway worker's injection in
``DeerFlowClient.stream``:
- Append ``build_tracing_callbacks()`` to ``config["callbacks"]`` so
the Langfuse handler sees ``on_chain_start(parent_run_id=None)`` at
the graph root and runs the ``propagate_attributes`` path.
- Merge ``build_langfuse_trace_metadata(...)`` into
``config["metadata"]`` with ``setdefault`` so caller-supplied keys
still win.
- ``_ensure_agent`` now creates its main model with
``attach_tracing=False`` to avoid duplicate spans now that the
callback lives at the graph root.
Docs:
- ``backend/CLAUDE.md`` Tracing section rewritten to describe the
graph-root attachment model (replacing the inaccurate
"at model-creation time" wording).
- ``README.md`` Langfuse section now lists both injection points
(worker + client) instead of only the worker path.
Tests:
- ``tests/test_client_langfuse_metadata.py`` (new, 3 cases):
callbacks + metadata are injected when Langfuse is enabled,
caller-supplied metadata overrides win via ``setdefault``, and the
injection is inert when Langfuse is disabled.
Live verification on the real Langfuse instance:
=== user=fancy-client ===
id=cbd22847.. session=client-2930-6b9491-fancy-client user=fancy-client name='lead-agent'
=== user=alice-client ===
id=b4f6f576.. session=client-2930-6b9491-alice-client user=alice-client name='lead-agent'
Refs #2930.
* refactor(tracing): address maintainer review on PR #2944
Addresses @WillemJiang's 5 comments.
1. Duplicated metadata-injection code between worker.py and client.py
New ``deerflow.tracing.inject_langfuse_metadata(config, ...)`` helper
takes the 10-line build + merge + setdefault logic that was duplicated
in ``runtime/runs/worker.py`` and ``client.py``. Both callers now share
a single source of truth, so the two paths cannot drift.
2. Direct private-attribute mutation in conftest.py and tests
Added public ``reset_tracing_config()`` / ``reset_title_config()``
functions. ``tests/conftest.py`` and every test that previously did
``tracing_module._tracing_config = None`` or
``title_module._title_config = TitleConfig()`` now goes through the
public API. A future internal rename will surface as an ImportError
instead of a silent no-op.
3. client.py reading os.environ directly
``DeerFlowClient.__init__`` grows an optional ``environment`` parameter
so programmatic callers can pass the deployment label explicitly.
``stream()`` consults ``self._environment`` first and only falls back
to ``DEER_FLOW_ENV`` / ``ENVIRONMENT`` env vars when nothing was
passed in. Backwards compatible — env-var behaviour preserved for
callers that opt to keep using it.
4. build_tracing_callbacks() cached on hot path
Not implemented. Inspected the langfuse v4 ``langchain.CallbackHandler``
constructor: it only resolves the module-level singleton client via
``get_client()`` and initialises a few dicts (no I/O, no env parsing
at construction time). The build is essentially free. Caching would
trade a non-measurable speedup for two real risks: handler instances
carry per-run state internally (``_run_states``, ``_root_run_states``,
``last_trace_id``), and tracing config can be reloaded by env-var
changes between runs. Will revisit if profiling ever shows it as
a hot spot.
5. attach_tracing=False easy to forget at new in-graph call sites
- Module docstring at the top of ``lead_agent/agent.py`` documents
the invariant ("every in-graph ``create_chat_model`` MUST pass
``attach_tracing=False``") and enumerates the current sites.
- New regression test
``test_make_lead_agent_attaches_tracing_callbacks_at_graph_root`` in
``tests/test_lead_agent_model_resolution.py`` locks both halves of
the invariant: ``config["callbacks"]`` carries the tracing handler
after ``_make_lead_agent``, AND every ``create_chat_model`` call
captured by the test passes ``attach_tracing=False``. A future
in-graph site that forgets the flag will fail this test.
Lint clean. Full touched-suite bundle: 246 passed.
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
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Airene Fang
|
923f516deb |
feat(trace):LangGraph -> lead_agent and set custom agent_name to run_name (#3101)
* feat(trace):LangGraph -> lead_agent and set user custom agent name to run_name * feat(trace):follow github copilot suggest * feat(trace):Refactor run_name resolution and improve test coverage |
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john lee
|
9b19cca91c |
fix(runtime): make RunManager.cancel() idempotent for already-interrupted runs (#3055) (#3058)
A second cancel() call on an interrupted run returned False, causing the cancel and stream_existing_run router endpoints to raise 409 on double-stop. Fix: return True inside the lock when record.status == RunStatus.interrupted. This covers both the POST /cancel and POST /join endpoints without any re-fetch or extra get() call — the idempotency lives at the source. Also fixes stream_existing_run (the LangGraph SDK stop-button path), which had the identical cancel() → 409 pattern and was not covered by the original PR. Both endpoints share the fix automatically. Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> |
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He Wang
|
c810e9f809 |
fix(harness)!: hydrate runs from RunStore and persist interrupted status (#2932)
* fix(harness): hydrate run history from RunStore and persist cancellation status fix: - Make RunManager.get() async and hydrate from RunStore when in-memory record is missing - Merge store rows into list_by_thread() with in-memory precedence for active runs - Persist interrupted status to RunStore in cancel() and create_or_reject(interrupt|rollback) - Extract _persist_status() to reuse the best-effort store update pattern - Await run_mgr.get() in all gateway endpoints - Return 409 with distinct message for store-only runs not active on current worker Closes #2812, Closes #2813 Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * fix(harness): consistent sort and guarded hydration in RunManager fix: - list_by_thread() now sorts by created_at desc (newest first) even when no RunStore is configured, matching the store-backed code path - guard _record_from_store() call sites in get() and list_by_thread() with best-effort error handling so a single malformed store row cannot turn read paths into 500s test: - update test_list_by_thread assertion to expect newest-first order - seed MemoryRunStore via public put() API instead of writing to _runs * fix(harness): guard store-only runs from streaming and fix get() TOCTOU Add RunRecord.store_only flag set by _record_from_store so callers can distinguish hydrated history from live in-memory runs. join_run and stream_existing_run (action=None) now return 409 instead of hanging forever on an empty MemoryStreamBridge channel. Re-check _runs under lock after the store await in RunManager.get() so a concurrent create() that lands between the two checks returns the authoritative in-memory record rather than a stale store-hydrated copy. Co-Authored-By: Claude Sonnet 4 <noreply@anthropic.com> * fix(harness): reorder bridge fetch in join_run and make list_by_thread limit explicit Move get_stream_bridge() after the store_only guard in join_run so a missing bridge cannot produce 503 for historical runs before the 409 guard fires. Add limit parameter to RunManager.list_by_thread (default 100, matching the store's page size) and pass it explicitly to the store call. Update docstring to document the limit instead of claiming all runs are returned. Co-Authored-By: Claude Sonnet 4 <noreply@anthropic.com> * fix(harness): cap list_by_thread result to limit after merge Apply [:limit] to all return paths in list_by_thread so the method consistently returns at most limit records regardless of how many in-memory runs exist, making the limit parameter a true upper bound on the response size rather than just a store-query hint. Co-Authored-By: Claude Sonnet 4 <noreply@anthropic.com> * fix `list_by_thread` docstring Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> * fix(runtime): add update_model_name to RunStore to prevent SQL integrity errors RunManager.update_model_name() was calling _persist_to_store() which uses RunStore.put(), but RunRepository.put() is insert-only. This caused integrity errors when updating model_name for existing runs in SQL-backed stores. fix: - Add abstract update_model_name method to RunStore base class - Implement update_model_name in MemoryRunStore - Implement update_model_name in RunRepository with proper normalization - Add _persist_model_name helper in RunManager - Update RunManager.update_model_name to use the new method test: - Add tests for update_model_name functionality - Add integration tests for RunManager with SQL-backed store Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * fix(runtime): handle NULL status/on_disconnect in _record_from_store `dict.get(key, default)` only uses the default when the key is absent, so a SQL row with an explicit NULL status would pass `None` to `RunStatus(None)` and raise, breaking hydration for otherwise valid rows. Switch to `row.get(...) or fallback` so both missing and NULL values get a safe default. Add tests for get() and list_by_thread() with a NULL status row to prevent regression. Co-Authored-By: Claude Sonnet 4 <noreply@anthropic.com> * fix(runs): address PR review feedback on store consistency changes - Fix list_by_thread limit semantics: pass store_limit = max(0, limit - len(memory_records)) to store so newer store records are not crowded out by in-memory records - Remove dead code: cancelled guard after raise is always True, simplify to if wait and record.task - Document _record_from_store NULL fallback policy (status→pending, on_disconnect→cancel) in docstring Co-Authored-By: Claude Sonnet 4 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com> Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> |
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Willem Jiang
|
39f901d3a5 |
fix(runs): restore historical runs from persistent store after gateway restart (#2989)
* fix(runs): restore historical runs from persistent store after gateway restart
RunManager.list_by_thread() and get() only queried the in-memory _runs
dict, returning empty results after a restart even when PostgreSQL had
the records. Add store fallback to both read paths and a new async
aget() for the API endpoint, keeping sync get() for internal callers
that need live task/abort_event state.
Fixes #2984
* Apply suggestions from code review
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
* fix(runs): scope run store fallback reads by user id
Agent-Logs-Url: https://github.com/bytedance/deer-flow/sessions/e73daada-1215-4bc1-ab7d-7117826c5013
Co-authored-by: WillemJiang <219644+WillemJiang@users.noreply.github.com>
* test(runs): clarify ordering expectation and mock store filters
Agent-Logs-Url: https://github.com/bytedance/deer-flow/sessions/e73daada-1215-4bc1-ab7d-7117826c5013
Co-authored-by: WillemJiang <219644+WillemJiang@users.noreply.github.com>
* test(runs): make user filter fallback assertions explicit
Agent-Logs-Url: https://github.com/bytedance/deer-flow/sessions/e73daada-1215-4bc1-ab7d-7117826c5013
Co-authored-by: WillemJiang <219644+WillemJiang@users.noreply.github.com>
* test(runs): verify user-isolated fallback behavior with memory store
Agent-Logs-Url: https://github.com/bytedance/deer-flow/sessions/e73daada-1215-4bc1-ab7d-7117826c5013
Co-authored-by: WillemJiang <219644+WillemJiang@users.noreply.github.com>
* update the code with feedback from issue-2984
---------
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
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Yi Tang
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de253e4a0a |
feat(run): Propagates model_name from the gateway request through the runtime and persistence stack to the SQLite database. (#2775)
* feat(run): propagate model_name from gateway request context to persistence layer Pass model_name through the full run creation pipeline — from RunCreateRequest.context in the gateway, through RunManager, to the RunStore interface and SQL persistence. This enables client-specified model selection to be recorded per-run in the database. * feat(run): add model allowlist validation and effective model name capture - Validate model_name against allowlist in gateway services.py using get_app_config().get_model_config() - Truncate model_name to 128 chars to match DB column constraint - In worker.py, capture effective model name from agent.metadata after agent creation and persist if resolved differently than requested * feat(run): add defense-in-depth model_name normalization and round-trip persistence tests - Add _normalize_model_name() to RunRepository for whitespace stripping and 128-char truncation before DB writes. - Add round-trip unit tests for model_name creation and default None in test_run_manager.py. * fix(run): coerce non-string model_name values before strip/truncate in _normalize_model_name * fix(gateway): add runtime type guard for model_name coercion in gateway services Add isinstance check and str() coercion before calling .strip() to prevent AttributeError when non-string types (int, None, etc.) flow through the gateway. Paired with SQL integration test for end-to-end model_name persistence across gateway → langgraph → persistence layer. * fix(run): drop Alembic migration for model_name (no-op) and expose public update method on RunManager - Drop a1b2c3d4e5f6 migration: model_name already exists in RunRow schema and is auto-created via Base.metadata.create_all() at startup - Add update_model_name() public method to RunManager to replace the private _persist_to_store call in worker.py, preserving internal locking/persistence |
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Xinmin Zeng
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ca3332f8bf |
fix(gateway): return ISO 8601 timestamps from threads endpoints (#2599)
* fix(gateway): return ISO 8601 timestamps from threads endpoints (#2594) ThreadResponse documents created_at / updated_at as ISO timestamps, matching the LangGraph Platform schema (langgraph_sdk.schema.Thread exposes them as datetime, JSON-encoded as ISO 8601). The gateway threads router was instead emitting str(time.time()) — unix-second floats — breaking frontend new Date() parsing and producing a mixed ISO/unix wire format that also corrupted the search sort order. Centralize timestamp generation in deerflow.utils.time: - now_iso() — datetime.now(UTC).isoformat() - coerce_iso(x) — heals legacy unix-timestamp strings on read so the store converges to ISO without a one-shot migration threads.py: replace 6 time.time() call sites with now_iso(); wrap all read paths and Phase-2 checkpoint metadata with coerce_iso(); _store_upsert opportunistically heals legacy created_at on update; drop unused time import. thread_runs.py: reuse now_iso() instead of a private duplicate _now_iso(), preventing future drift between the two timestamp call sites. Tests: 9 unit tests for the helper; 5 integration tests pinning the ISO contract for create/get/patch/search and the legacy-healing path on the internal store upsert. Full suite: 2144 passed, 15 skipped, 0 failed. Closes #2594 * fix(gateway): coerce checkpoint metadata timestamps to ISO on read After the merge with main, three additional read paths in ``threads.py`` were still emitting raw ``str(metadata.get("created_at", ""))`` — ``get_thread_state``, ``update_thread_state``, and ``get_thread_history``. Same root cause as #2594: when the checkpoint metadata's ``created_at`` is a unix-second float (legacy data, or a checkpoint written by an older Gateway version), ``str(float)`` produces ``"1777252410.411327"`` and the frontend's ``new Date(...)`` returns ``Invalid Date``. The fix on the ``/threads/{id}`` GET path was already in place; these three sibling endpoints needed the same treatment. All four call sites now flow through ``coerce_iso``, so: - legacy float metadata heals to ISO on the way out, - ISO metadata passes through unchanged, - ``datetime`` instances (which the new ``coerce_iso`` branch handles explicitly) emit with the ``T`` separator instead of falling through to the space-separated ``str(datetime)`` form. Coverage added for the two endpoints not already pinned by the merge: - ``test_get_thread_state_returns_iso_for_legacy_checkpoint_metadata`` - ``test_get_thread_history_returns_iso_for_legacy_checkpoint_metadata`` Both pre-seed a checkpoint whose metadata carries the literal float from the issue body and assert the wire format is ISO. |
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KiteEater
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17447fccbe |
fix(runtime): make rollback restore checkpoint supersede newer checkpoints (#2582)
* Restore rollback checkpoints with fresh ids * Tighten rollback checkpoint tests and imports * Update test_run_worker_rollback.py --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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greatmengqi
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8ba01dfd83 |
refactor: thread app_config through lead and subagent task path (#2666)
* refactor: thread app config through lead prompt * fix: honor explicit app config across runtime paths * style: format subagent executor tests * fix: thread resolved app config and guard subagents-only fallback Address two PR review findings: 1. _create_summarization_middleware passed the original (possibly None) app_config into create_chat_model, forcing the model factory back to ambient get_app_config() and risking config drift between the middleware's resolved view and the model's view. Pass the resolved AppConfig instance through end-to-end. 2. get_available_subagent_names accepted Any-typed config and forwarded it to is_host_bash_allowed, which reads ``.sandbox``. A SubagentsAppConfig (also accepted upstream as a sum-type input) has no ``.sandbox`` attribute and would be silently treated as "no sandbox configured", incorrectly disabling the bash subagent. Guard on hasattr and fall back to ambient lookup otherwise. Adds regression tests for both paths. * chore: simplify hasattr guard and tighten regression tests - Collapse if/else into ternary in get_available_subagent_names; hasattr(None, ...) is False so the explicit None check was redundant. - Drop comments that narrate the change rather than explain non-obvious WHY (test names already convey intent). - Replace stringly-typed sentinel "no-arg" in regression test with direct args tuple comparison. --------- Co-authored-by: greatmengqi <chenmengqi.0376@bytedance.com> |
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yangzheli
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78633c69ac |
fix(agents): propagate agent_name into ToolRuntime.context for setup_agent (#2679)
* fix(agents): propagate agent_name into ToolRuntime.context for setup_agent (#2677) When creating a custom agent via the web UI, SOUL.md was always written to the global base_dir/SOUL.md instead of agents/<name>/SOUL.md. Root cause: the bootstrap flow sends agent_name via body.context, but two layers were broken: 1. services.py only forwarded body.context keys into config["configurable"]; config["context"] was never populated. 2. worker.py constructed the parent Runtime with a hard-coded {thread_id, run_id} context, ignoring config["context"] entirely. After the langgraph >= 1.1.9 bump (#98a5b34f), ToolRuntime.context no longer falls back to configurable, so setup_agent's runtime.context.get("agent_name") returned None and the tool's silent agent_name=None -> base_dir fallback kicked in, overwriting the global SOUL.md. Fix: - services.py: extract merge_run_context_overrides() and write the whitelisted context keys into both configurable (legacy readers) and context (langgraph 1.1+ ToolRuntime consumers). - worker.py: extract _build_runtime_context() and merge config["context"] into the Runtime's context (without letting callers override thread_id/run_id). The base_dir fallback in setup_agent_tool.py is left in place because the IM /bootstrap channel command depends on it. That code path can be tightened in a follow-up. Adds regression tests covering both helpers. * 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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greatmengqi
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e82940c03d |
refactor: thread release config through lead path (#2612)
Co-authored-by: greatmengqi <chenmengqi.0376@bytedance.com> |
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JeffJiang
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db5ad86381 |
feat: enhance chat history loading with new hooks and UI components (#2338)
* Refactor API fetch calls to use a unified fetch function; enhance chat history loading with new hooks and UI components - Replaced `fetchWithAuth` with a generic `fetch` function across various API modules for consistency. - Updated `useThreadStream` and `useThreadHistory` hooks to manage chat history loading, including loading states and pagination. - Introduced `LoadMoreHistoryIndicator` component for better user experience when loading more chat history. - Enhanced message handling in `MessageList` to accommodate new loading states and history management. - Added support for run messages in the thread context, improving the overall message handling logic. - Updated translations for loading indicators in English and Chinese. * Fix test assertions for run ordering in RunManager tests - Updated assertions in `test_list_by_thread` to reflect correct ordering of runs. - Modified `test_list_by_thread_is_stable_when_timestamps_tie` to ensure stable ordering when timestamps are tied. |
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rayhpeng
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2e05f380c4 |
feat(persistence): per-user filesystem isolation, run-scoped APIs, and state/history simplification (#2153)
* 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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rayhpeng
|
56d5fa3337 |
feat(persistence):Unified persistence layer with event store, feedback, and rebase cleanup (#2134)
* 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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feat: replace auto-admin creation with secure interactive first-boot setup (#2063)
* 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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rayhpeng
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d8ecaf46c9 |
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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|
luo jiyin
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35f141fc48 |
feat: implement full checkpoint rollback on user cancellation (#1867)
* feat: implement full checkpoint rollback on user cancellation - Capture pre-run checkpoint snapshot including checkpoint state, metadata, and pending_writes - Add _rollback_to_pre_run_checkpoint() function to restore thread state - Implement _call_checkpointer_method() helper to support both async and sync checkpointer methods - Rollback now properly restores checkpoint, metadata, channel_versions, and pending_writes - Remove obsolete TODO comment (Phase 2) as rollback is now complete This resolves the TODO(Phase 2) comment and enables full thread state restoration when a run is cancelled by the user. * fix: address rollback review feedback * fix: strengthen checkpoint rollback validation and error handling - Validate restored_config structure and checkpoint_id before use - Raise RuntimeError on malformed pending_writes instead of silent skip - Normalize None checkpoint_ns to empty string instead of "None" - Move delete_thread to only execute when pre_run_snapshot is None - Add docstring noting non-atomic rollback as known limitation This addresses review feedback on PR #1867 regarding data integrity in the checkpoint rollback implementation. * test: add comprehensive coverage for checkpoint rollback edge cases - test_rollback_restores_snapshot_without_deleting_thread - test_rollback_deletes_thread_when_no_snapshot_exists - test_rollback_raises_when_restore_config_has_no_checkpoint_id - test_rollback_normalizes_none_checkpoint_ns_to_root_namespace - test_rollback_raises_on_malformed_pending_write_not_a_tuple - test_rollback_raises_on_malformed_pending_write_non_string_channel - test_rollback_propagates_aput_writes_failure Covers all scenarios from PR #1867 review feedback. * test: format rollback worker tests |
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Jason
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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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Admire
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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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Admire
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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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rayhpeng
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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> |