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33 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
Zhengcy05
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2f60bee388
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fix: surface length-capped model responses (#4309)
* fix: surface length-capped model responses * fix: avoid the influence of the mid-turn * fix: correcting semantic annotations * fix: add ModelLengthTerminationDetector to compatible providers * fix:delete redundancy code * fix:supplementing log information improves observability * fix: align the document and complete the assertions. * fix: unit test * fix: revert AGENTS.md * fix: unit test * fix: add annotation and skip AIMessage has empty content |
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Aari
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37c343fe30
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fix(summarization): summarize with the run model, fall back on summary-provider failure (#4361)
* fix(summarization): own the run model for compaction; bound failure With summarization.model_name: null the summary model resolved to config.models[0] while the executing model is selected per run; when they differ and models[0]'s provider is broken (expired key, quota, outage) compaction silently failed every triggered turn and context grew unbounded until the main provider 400s the run (#3103's shape), even though the run's own model was healthy. Model ownership is now sourced from the builders, not re-derived at runtime: - The lead, subagent, and manual /compact builders each pass the resolved run model into create_summarization_middleware(run_model_name=...). The middleware no longer reads runtime.context / get_config(), which do not carry a custom agent's or a subagent's resolved model, so a custom-agent lead run and a distinct-model subagent now summarize with their own model, not models[0] / the parent's. Runtime re-resolution and the per-name model cache are removed. - model_name: null summarizes with the run's own model; an explicitly configured summary model generates and falls back to the run model on failure. The fallback is built lazily after the primary fails and its construction is guarded, so a broken fallback cannot skip a healthy primary or escape the automatic failure boundary. Failure is bounded and side-effect-safe: - An empty or whitespace-only response is treated as a generation failure, not a valid summary, so compaction never removes all history for an empty replacement. - compact_state/acompact_state take raise_on_failure independent of force: the manual /compact path always surfaces a generation failure (even force=false) and routes it to the existing ContextCompactionFailed path (HTTP 500 -> frontend error toast) instead of an unconsumed response reason. The automatic path leaves compaction state unchanged. - before_summarization hooks fire only after a replacement summary exists. SummarizationConfig.model_name, config.example.yaml, and docs/summarization.md document the final lead/subagent/manual ownership rules. Part of RFC #4346 (section A). Evaluating fraction/triggers against the run model's profile (profile ownership) is a separate follow-up. * fix(summarization): manual /compact model ownership + fail-open construct/parse Manual /compact carried only agent_name, so it derived the run model from the custom-agent model or config.models[0] and missed the request-selected model the run path uses (request -> custom-agent -> default). Carry model_name through ThreadCompactRequest and the frontend compact call, resolve with the same precedence, and move the custom-agent config read off the event loop (asyncio .to_thread) with user_id so the strict blocking-IO gate is not bypassed by the broad except. Make one summary attempt own its full lifecycle so the fail-open boundary covers construction and response parsing, not just invocation: build each candidate model lazily and guarded (a raising constructor falls through to the healthy run model instead of breaking agent construction), build the model_name:null primary from the run model rather than config.models[0], and run response text extraction inside the invocation try so a failing .text accessor falls back instead of escaping compaction. Adds factory-level constructor-failure, response-extraction-failure (sync/async), and route-path model-ownership tests. |
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hataa
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7857fa0cce
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feat(authz): enforce tool authorization at assembly and runtime (#4370)
* feat(authz): enforce tool authorization at assembly and runtime * fix(middleware): guard deferred tool setup lookup (#4370) --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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Ryker_Feng
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20debf9cc7
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feat(agents): per-agent model and generation settings (#4347)
* feat(agents): per-agent model and generation settings Let each custom agent choose its own model and sampling settings (temperature, max_tokens) plus thinking / reasoning_effort defaults, so agents sharing a model profile are no longer stuck with one shared temperature and output length (#4336). AgentConfig gains optional model_settings / thinking_enabled / reasoning_effort (None = inherit). create_chat_model applies per-caller model_overrides on top of the profile before the thinking/Codex transforms; the lead agent resolves each knob with precedence request > agent config > profile/default. The /api/agents create/update routes persist the fields and reject an unknown model. The default lead agent path is unchanged (no agent config -> overrides None). The agent chat composer also stops force-overriding an agent's configured default model with models[0]. * fix(agents): tri-state thinking control and default-model capability gating The model-settings dialog seeded the thinking switch to false, so opening it to tweak temperature and saving silently disabled thinking (the runtime default is on) with no way back to inherit. It also hid the thinking / reasoning controls whenever the agent inherited the global default model, since `__default__` never resolved through `models.find`. Give thinking an explicit Inherit / On / Off tri-state so an untouched save is a no-op, and resolve `__default__` to the effective default (models[0]) for the capability check. Logic lives in the tested helpers module. |
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Vanzeren
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42baed8c8c
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feat(checkpoint): dual-mode checkpoint storage with LangGraph DeltaChannel (#4292)
* feat(checkpoint): dual-mode checkpoint storage with LangGraph DeltaChannel
Add a restart-required database.checkpoint_channel_mode ("full" default,
"delta") that stores the messages channel via LangGraph 1.2 DeltaChannel,
cutting checkpoint storage from O(n^2) to O(n) for append-only history.
Existing full checkpoints seed delta state transparently; no data migration.
- config: mode schema + freeze-on-first-use with
CheckpointModeReconfigurationError; mode marker persisted in checkpoint
metadata; unsafe delta->full downgrade rejected fail-closed with
CheckpointModeMismatchError (run-level error, failed state read)
- state: delta message state schema; CheckpointStateAccessor centralizes
materialized reads for all consumers (threads API, branches,
regeneration, compaction, state updates, memory, goal workers)
- runtime: raw writers (run durations, interrupted title, thread goal)
parent their checkpoints to the checkpoint they derive from, preserving
delta ancestry; rollback forks the pre-run lineage through a state
mutation graph with Overwrite restores; InMemorySaver delta-history
override delegates to the base walk (fixes dropped first write after
migration, also present upstream)
- tests: conformance suite over {memory, sqlite, postgres} covering
migration replay, stable message IDs, storage shape and writer
preservation; conftest fixture isolates the frozen mode between tests;
stale config fakes refreshed
- ci: backend unit tests gain a postgres service
* fix(checkpoint): close materialization gaps in goal flow, guard public factory
- Route goal-continuation message reads through CheckpointStateAccessor:
raw channel_values reads see the delta sentinel in delta mode, which
disabled goal continuation (stand_down=no_durable_end_of_turn) after
durable assistant turns. Raw tuples remain for tuple-only metadata
(checkpoint id, pending_writes).
- Reject checkpoint_channel_mode='delta' + checkpointer in
create_deerflow_agent at construction: factory-built persisted graphs
bypass mode-marker injection and the fail-closed gate, reproducing
silent mixed-mode state loss. Delta without persistence stays allowed.
- Import the postgres saver lazily (pytest.importorskip in the fixture)
so the documented default install collects the suite; add a CI job
running pytest --collect-only on uv sync --group dev without extras.
- Fix test_checkpointer fallback test to patch get_app_config at its
use site (provider module), making it deterministic when a local
config.yaml selects a persistent backend.
* fix(gateway): preserve extension-owned channels in state mutations, bump config version
- build_state_mutation_graph / build_checkpoint_state_mutation_accessor
accept an explicit state_schema; branch and POST /state now compile the
mutation graph from the thread's effective schema
(graph_state_schema on the assistant graph). The base-ThreadState
fallback silently discarded channels contributed by custom
AgentMiddleware.state_schema on branch (data loss) and returned a
false-success 200 on POST /state.
- POST /state validates values keys against the mutation graph's
channels and rejects unknown fields with 422 instead of ignoring
them; reducer detection covers extension channels
(BinaryOperatorAggregate or DeltaChannel) so Overwrite replace
semantics work for middleware reducers in both modes.
- Endpoint regression: custom AgentMiddleware.state_schema value
survives branch, updates through POST /state, and an unknown field
receives 422.
- config_version 26 -> 27 for the new database.checkpoint_channel_mode
(example, Helm chart values + README, support-bundle fixture), so
existing installs get the outdated-config warning and
make config-upgrade merges the field; covered by a test driving the
real example file and the real config-upgrade script.
* fix(gateway): resolve assistant schema via one boundary, copy branch reducer values with Overwrite
GET /threads/{id}/state now resolves the thread's assistant_id through a
single reusable boundary (thread metadata -> assistant_id -> effective
graph), so channels contributed by a custom AgentMiddleware.state_schema
are materialized instead of dropped by the default lead schema. POST
/state uses the same boundary instead of resolving the schema ad hoc.
Branch writes wrap every copied reducer channel in Overwrite (derived
from the effective mutation graph: BinaryOperatorAggregate + DeltaChannel),
not just messages, so already-aggregated values are never re-merged.
Regression tests use a real AgentMiddleware.state_schema with a
non-identity reducer in both full and delta modes: GET /state returns the
extension value, POST /state replaces it, branch preserves it
byte-for-byte; the unknown-field 422 is a separate assertion.
* refactor(checkpoint): collapse read-path round-trips and ship dual-mode parity tests
Address review round 4 on PR #4292:
- Push ahistory/history limit through Pregel into checkpointer.alist
(SQL LIMIT) instead of materializing all rows and breaking in Python
- Fold the read-side mode-compat gate onto the returned snapshot's
metadata; only writes keep the pre-write tuple fetch (fail-closed)
- Cache factory-built accessor graphs per (assistant_id, mode) with
factory-identity revalidation; state reads no longer build a lead
agent per request
- get_thread: one snapshot fetch + one raw pending_writes fetch on the
resolved checkpoint (post-checkpoint __error__ writes never surface
in snapshot.tasks; verified empirically)
- DeerFlowClient.get_thread: single checkpointer.list walk collects
pending_writes per checkpoint instead of N get_tuple calls
- InMemorySaver delta-history patch: stand-down when the upstream
override disappears, try/except guard, validated-version warning,
guard tests
- make_lead_agent mode precedence: first freeze is owned by app_config
(client-supplied configurable key ignored); once frozen, injected
key/app_config must match or fail closed
- Rollback: lock in non-message channel restoration via fork
inheritance with a dedicated reducer-channel test
- Add tests/test_threads_checkpoint_mode.py and
tests/test_gateway_checkpoint_mode.py referenced by AGENTS.md and
the PR validation section: lifecycle parity (memory + sqlite),
per-step blob-count storage guard, gateway endpoint parity
Counted-saver tests pin checkpoint round-trips for aget/ahistory so
these regressions cannot silently return.
* fix(checkpoint): precise mode-mismatch HTTP mapping, gate E2E, and accessor resilience
- threads router: map CheckpointModeMismatchError to 409 (with cause and
thread id) and CheckpointModeReconfigurationError to 503 across all state
endpoints instead of swallowing both into a generic 500
- gate coverage: seed a real delta checkpoint into AsyncSqliteSaver and
assert aget/aupdate/ahistory fail closed; assert 409 at the HTTP boundary
through the real route stack
- rollback: compile the restore mutation graph with the thread's effective
state schema per the build_state_mutation_graph contract
- inheritance contract locks: rollback and manual compaction preserve
middleware-contributed channels via checkpoint fork cloning
- services: revalidate the accessor-graph cache against app_config identity
so config.yaml hot-reloads never serve a stale compiled graph
- services: degrade full-mode state reads to raw checkpointer reads when the
agent factory is unavailable (delta gate still applies; delta mode has no
fallback)
- deps: override websockets==16.0 (langgraph-sdk 0.4.2's <16 pin silently
downgraded 16.0 -> 15.0.1; pin is not grounded in any API incompatibility)
and bump the langchain lower bound to what the lockfile actually resolves
* fix(checkpoint): include anchor checkpoint in degraded history walk + cover get_thread
- _RawCheckpointReadAccessor.ahistory: alist(before=...) is exclusive while
pregel's get_state_history treats config.checkpoint_id as the inclusive
start; fetch the anchor explicitly so both read paths paginate identically
- extend the degraded-path gateway test: GET /thread returns raw values, and
POST /history with before starts at the anchor checkpoint
* fix(gateway): preserve degraded checkpoint timestamps
* fix(gateway): harden degraded checkpoint access
* fix(gateway): resolve assistants for checkpoint reads
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
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ChenglongZ
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ca16b64b26
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feat(agent): support config-declared lead middlewares (#3964)
* feat(agent): support config-declared lead middlewares * fix(agent): preserve configured extension middlewares * fix(agent): address middleware extension review * fix(agent): tighten middleware extension docs and tests |
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Huixin615
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65afc9b1d2
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fix(skills): apply allowed-tools only to active skills (#4098)
* fix(skills): scope allowed-tools to active skills * fix(skills): tolerate stale active skill paths * chore: retrigger CI * fix(skills): document policy activation limits * perf(skills): reuse per-step tool policy decisions * fix(skills): harden runtime tool policy contracts * fix(skills): redact cached policy decisions * fix(skills): make slash tool policy authoritative * fix(skills): preserve policy-safe discovery tools * test(skills): cover explicit task delegation policy |
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DanielWalnut
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4e209827f3
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feat(agent): Add subagent total delegation cap (#4115)
* fix subagent total delegation cap * fix embedded subagent run cap context * fix subagent cap config consistency * fix resumed subagent run cap boundary * fix legacy resume subagent boundary * address subagent cap review feedback --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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Huixin615
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6389fc03fd
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fix: ensure visible response after tool runs (#4033)
* fix: ensure visible response after tool runs * fix: clean up terminal response recovery state * fix: bound terminal recovery state |
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Ryker_Feng
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ebc09ce130
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feat(mcp): auto-promote deferred MCP tools from routing hints (#4019)
* feat(mcp): auto-promote deferred MCP tools from routing hints
When tool_search.enabled=true defers MCP tool schemas, PR1 routing hints
still require the model to spend a tool_search discovery round trip before
it can call the tool the routing metadata already points at. This adds a
McpRoutingMiddleware that matches the latest user message against PR1
routing keywords and promotes the matching deferred schemas before the
model call, removing that round trip.
Design (soft routing, opt-in, additive):
- Matches only the latest real HumanMessage (shared is_real_user_message
helper, reused by SkillActivationMiddleware so the two cannot drift);
case-insensitive substring match, no tokenizer dependency.
- Ordering: priority desc, then tool name asc; capped by the new global
tool_search.auto_promote_top_k (default 3, clamped 1..5). Does not add or
consume a per-tool auto_promote_top_k (PR1 schema unchanged); a per-tool
value is ignored with a DEBUG note.
- Returns a plain {"promoted": ...} state update (not a Command) and relies
on ThreadState.merge_promoted for union/dedupe, so auto-promote and a
model-triggered tool_search converge on the same catalog hash.
- Installed before DeferredToolFilterMiddleware on every deferred-tool path
(lead agent, subagent, embedded client, webhook via shared builders);
a construction-time assert rejects the reversed order. catalog_hash is
None / no routing index is a complete no-op, so bootstrap and ACP skip it.
- Privacy: never executes tools, never promotes policy-filtered tools, adds
no routing keywords or matched tool names to trace metadata or INFO/WARN
logs.
No behavior change when tool_search.enabled=false.
Tests: index construction, matching semantics, middleware state updates,
same-cycle deferred-filter interaction, lead/subagent/embedded-client
builder wiring + order invariant, config clamping, config.example.yaml
parseability, and privacy assertions.
* refactor(mcp): address auto-promote review nits
- executor: access app_config.tool_search.auto_promote_top_k directly to match
the lead-agent and embedded-client paths (drop the over-defensive getattr that
masked missing config); update the subagent test mock to carry tool_search.
- tool_search / mcp_routing_middleware: cross-reference the duplicated routing
priority/keyword normalization between the builder and the middleware's
defensive _normalize_index so they cannot silently drift.
- MCP_SERVER.md: document that auto-promote keyword matching is a case-insensitive
substring test (not word-boundary), advising distinctive keywords.
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Ryker_Feng
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26d7a5970d
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feat: add manual context compaction (#3969)
* feat: add manual context compaction * fix: harden manual context compaction |
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Xinmin Zeng
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4fc08b4f15
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feat: add scheduled tasks MVP (#3898)
* feat: add scheduled tasks MVP
* fix: harden scheduled task execution semantics
* feat(scheduled-tasks): preset-driven schedule form with timezone and live preview
Replace the raw cron input with a preset Select (hourly/daily/weekly/monthly/custom)
plus structured inputs (time picker, weekday toggles, day-of-month), datetime-local
for one-time tasks, a timezone selector defaulting to the browser timezone, and a
live human-readable preview. Reuses one ScheduledTaskScheduleInput for create and
edit; backend contract unchanged; zero new deps (pure Intl + DST-safe offset helpers).
* feat(scheduled-tasks): full-page i18n + recipe templates + E2E locale pin
Localize the rest of the scheduled-tasks page (filters, detail pane, actions,
edit form, run list, enum values) via t.scheduledTasks.* in en/zh. Add four
built-in recipe templates (GitHub Trending, news digest, issue triage, weekly
report) exposed as a chip row that pre-fills title + prompt + schedule. Pin
Playwright locale to en-US so E2E selectors stay stable against i18n. No backend
change, no new deps.
* fix(scheduled-tasks): idempotent 0003 migration, update head constants, future-date once test
Merge with main surfaced three CI failures:
- 0003_scheduled_tasks create_table collided with legacy test seeds that
build from full metadata; guard with inspector.has_table so the revision
no-ops when the table already exists (0004/0005 are already idempotent via
_helpers.py).
- persistence bootstrap concurrency/regression tests pinned HEAD to main's
0002_runs_token_usage; bump to the new head 0005_scheduled_task_thread_nullable.
- once-task router test used a fixed past run_at and tripped the
must-be-in-the-future validation; use a future date.
* address review: ok-check, 502 for trigger failure, mock fields, migration filename, doc fences
- fetchThreadScheduledTasks now checks response.ok like the other fetchers.
- trigger endpoint returns 502 (not 409) when dispatch fails outright, so
clients can distinguish a real conflict from a server-side failure.
- E2E mock normalizes scheduled-task objects with context_mode/last_thread_id
and nullable thread_id, matching the backend contract the UI renders against.
- Rename 0002_scheduled_tasks.py -> 0003_scheduled_tasks.py to match its
revision id (file was renamed in spirit already; filename now follows).
- CONFIGURATION.md: close the Tool Groups yaml fence and drop the stray fence
after the Scheduler notes so the sections render correctly.
* fix(scheduled-tasks): harden lease, poller, config, and frontend UX after review
* fix(scheduled-tasks): harden run lifecycle, overlap skip, non_interactive gating, and DST conversion after review
- defer a once task's terminal status to the run-completion hook; the task
stays running until the real outcome, and a startup sweep cancels once
tasks orphaned by a crash (launch-time 'completed' could stick forever)
- record interrupted runs as a distinct 'interrupted' run status with a
readable message; an interrupted once task ends 'cancelled', not 'failed'
- enforce overlap_policy=skip for fresh_thread_per_run via an active-run
pre-check (same-thread ConflictError can never fire across fresh threads)
- protect terminal run statuses from the late launch-path 'running' write
- honor context.non_interactive only for internally-authenticated callers;
arbitrary clients can no longer strip ask_clarification
- fix DST-stale timezone offset in zonedLocalToUtcIso by re-deriving the
offset at the resolved instant (once tasks fired an hour late around
spring-forward and the create->edit round-trip diverged)
- drop dead ScheduledTaskRunRepository.update_by_run_id; share one Gateway
API error helper between channels and scheduled-tasks frontends
* fix(scheduled-tasks): close review round-3 gaps in guards, concurrency, and API ergonomics
- scrub internal-only context keys (non_interactive) from the assembled run
config for non-internal callers: gating body.context alone left the same
key smuggle-able through the free-form body.config copied verbatim by
build_run_config
- guard update_after_launch with protect_terminal so the launch bookkeeping
write cannot clobber a once task already finalized by a fast-failing run's
completion hook (parent-row sibling of the run-row guard)
- reject a manual trigger while the task has an active run (409) instead of
launching a duplicate concurrent run on fresh_thread_per_run
- re-arm a terminal once task to enabled when PATCH pushes run_at into the
future; previously the endpoint returned 200 with a next_run_at that could
never be claimed
- make max_concurrent_runs a real global cap: each poll claims only into the
remaining budget of active (queued/running) scheduled runs
- paginate GET /scheduled-tasks/{id}/runs (limit<=200, offset) and push the
thread filter of /threads/{id}/scheduled-tasks into SQL
- stamp context.user_id on scheduler-launched runs, matching IM channels, so
user-scoped guardrail providers see the owning user
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
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AochenShen99
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0fb18e368c
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refactor(lead-agent): make build_middlewares public to drop the last cross-module private import (#3458)
`client.py` imported the private `_build_middlewares` from `agent.py` across a module boundary and called it as public API. Because the `_` name signals "module-private, no external callers", any future rename or signature change silently breaks the embedded `DeerFlowClient` path — and the test suite even monkeypatched `deerflow.client._build_middlewares`, baking the leak in. `DeerFlowClient` is a lead-agent variant that genuinely needs the lead agent's full middleware composition, so make the dependency honest: promote the helper to a documented public entry point `build_middlewares` and update every in-repo caller. Found during #3341 review; #3341 already removed one such leak (`_assemble_deferred` -> public `assemble_deferred_tools`) and left this one out of scope on purpose. - agent.py: rename def + both internal call sites; expand the docstring into a public-entry-point contract and document the previously-undocumented model_name / app_config / deferred_setup params - client.py: import + call site now use the public name (removes the last cross-module private import) - scripts/tool-error-degradation-detection.sh: update its import + call site - tests (5 files): update monkeypatch/patch targets and direct calls - docs (backend/CLAUDE.md, plan_mode_usage.md, middlewares.mdx): sync the live references that describe the symbol as current API Pure mechanical rename, no behavior change. Historical design docs (rfc, superpowers spec) intentionally keep the old name as point-in-time records. Closes #3431 |
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Nan Gao
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d46a5779bc
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fix(chat): preserve messages after summarization (#3280)
* fix(chat): preserve messages after summarization * make format * fix(chat): address summarization review comments |
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Xinmin Zeng
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be0eae9825
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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
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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>
|
||
|
Tao Liu
|
daa3ffc29b
|
feat(loop-detection): make loop detection configurable with per-tool frequency overrides (#2711)
* Make loop detection configurable Expose LoopDetectionMiddleware thresholds through config.yaml while preserving existing defaults and allowing the middleware to be disabled. Refs bytedance/deer-flow#2517 * feat(loop-detection): add per-tool tool_freq_overrides to Phase 1 Adds ToolFreqOverride model and tool_freq_overrides field to LoopDetectionConfig, wires it through LoopDetectionMiddleware, and documents the option in config.example.yaml. Resolves the gap flagged in the #2586 review: without per-tool overrides, users hit by #2510/#2511 (RNA-seq workflows exceeding the bash hard limit) had no way to raise thresholds for one tool without loosening the global limit for every tool. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * Potential fix for pull request finding Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> * docs(loop-detection): document tool_freq_overrides in LoopDetectionMiddleware docstring Add the missing Args entry for tool_freq_overrides, explaining the (warn, hard_limit) tuple structure and how per-tool thresholds supersede the global tool_freq_warn / tool_freq_hard_limit for named tools. Also run ruff format on the three files flagged by the lint check. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(loop-detection): validate LoopDetectionMiddleware __init__ params eagerly Raise clear ValueError at construction time instead of crashing at unpack-time inside _track_and_check when bad values are passed: - tool_freq_overrides: must be 2-tuples of positive ints with hard_limit >= warn - scalar thresholds: warn_threshold, hard_limit, tool_freq_warn, tool_freq_hard_limit must be >= 1 and hard limits must >= their warn pairs - window_size, max_tracked_threads must be >= 1 Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(test): isolate credential loader directory-path test from real ~/.claude The test didn't monkeypatch HOME, so on any machine with real Claude Code credentials at ~/.claude/.credentials.json the function fell through to those credentials and the assertion failed. Adding HOME redirect ensures the default credential path doesn't exist during the test. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * style(test): add blank lines after import pytest in TestInitValidation Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * refactor(loop-detection): collapse dual validation to LoopDetectionConfig Modifications - LoopDetectionMiddleware.__init__: stripped of all ValueError raises; becomes a plain field-assignment constructor. - LoopDetectionMiddleware.from_config: classmethod that builds the middleware from a Pydantic-validated LoopDetectionConfig and handles the ToolFreqOverride -> tuple[int, int] conversion. - agents/factory.py: SDK construction routed through LoopDetectionMiddleware.from_config(LoopDetectionConfig()) so the defaults path is Pydantic-validated too. - agents/lead_agent/agent.py: uses from_config instead of unpacking config fields by hand. - tests/test_loop_detection_middleware.py: deleted TestInitValidation (16 methods exercising the removed __init__ checks); added TestFromConfig (4 tests: scalar field mapping, override tuple conversion, empty overrides, behavioral smoke test). Result: one validation layer (Pydantic), zero duplication, no __new__ hacks. Both production construction sites flow through LoopDetectionConfig. Test results make test -> 2977 passed, 18 skipped, 0 failed (137s) make format -> All checks passed; 411 files left unchanged * feat(agents): make loop_detection configurable in create_deerflow_agent Adds a `loop_detection: bool | AgentMiddleware = True` field to RuntimeFeatures, mirroring the existing pattern used by `sandbox`, `memory`, and `vision`. SDK users can now disable LoopDetectionMiddleware or replace it with a custom instance built from their own LoopDetectionConfig — e.g. `LoopDetectionMiddleware.from_config(my_cfg)` — instead of being stuck with the hardcoded defaults previously installed by the SDK factory. The lead-agent path (which already reads AppConfig.loop_detection) is unchanged, and the default `True` preserves prior always-on behavior for all existing callers. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> --------- Co-authored-by: knight0940 <631532668@qq.com> Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com> Co-authored-by: Amorend <142649913+knight0940@users.noreply.github.com> Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
||
|
greatmengqi
|
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> |
||
|
greatmengqi
|
8b61c94e1d
|
fix: keep lead agent graph factory signature compatible (#2678)
Co-authored-by: greatmengqi <chenmengqi.0376@bytedance.com> |
||
|
greatmengqi
|
38714b6ceb
|
refactor: thread app_config through middleware factories (#2652)
* refactor: thread app_config through middleware factories Continues the incremental config-refactor sequence (#2611 root, #2612 lead path) one layer deeper into the middleware factories. Two ambient lookups inside _build_runtime_middlewares are eliminated and the LLMErrorHandling band-aid removed: - _build_runtime_middlewares / build_lead_runtime_middlewares / build_subagent_runtime_middlewares now require app_config: AppConfig. - get_guardrails_config() inside the factory is replaced with app_config.guardrails (semantically identical — same default-factory GuardrailsConfig — verified by direct equality check). - LLMErrorHandlingMiddleware.__init__ now requires app_config and reads circuit_breaker fields directly. The class-level circuit_failure_threshold / circuit_recovery_timeout_sec defaults are removed along with the try/except (FileNotFoundError, RuntimeError): pass band-aid — the let-it-crash invariant the rest of the refactor enforces. Caller chain (already-resolved app_config sources): - _build_middlewares in lead_agent/agent.py: reorder so resolved_app_config = app_config or get_app_config() is computed BEFORE build_lead_runtime_middlewares is called, then passed as kwarg. - SubagentExecutor: optional app_config parameter (mirrors the lead-agent pattern); _create_agent does the same `or get_app_config()` fallback at agent-build time, so task_tool callers don't need to plumb app_config through yet (typed-context plumbing for tool runtimes is a separate refactor). Tests: - test_llm_error_handling_middleware: _make_app_config helper using AppConfig(sandbox=SandboxConfig(use="test")) — same minimal-config pattern conftest already uses. Three direct LLMErrorHandlingMiddleware() calls each followed by post-construction circuit_breaker mutation fold cleanly into _build_middleware(circuit_failure_threshold=..., circuit_recovery_timeout_sec=...). Verification: - tests/test_llm_error_handling_middleware.py — 14 passed - tests/test_subagent_executor.py — 28 passed - tests/test_tool_error_handling_middleware.py — 6 passed - tests/test_task_tool_core_logic.py — 18 passed (verifies task_tool unchanged behavior) - Full suite: 2697 passed, 3 skipped. The single intermittent failure in tests/test_client_e2e.py::test_tool_call_produces_events is pre-existing LLM flakiness (the test asserts the model decided to call a tool; reproduces 1/3 on unchanged main as well). * fix: address middleware app config review comments * fix: satisfy app config annotation lint * test: cover explicit app config middleware wiring --------- Co-authored-by: greatmengqi <chenmengqi.0376@bytedance.com> |
||
|
greatmengqi
|
e82940c03d
|
refactor: thread release config through lead path (#2612)
Co-authored-by: greatmengqi <chenmengqi.0376@bytedance.com> |
||
|
rayhpeng
|
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 fb2d99f (#1836) but accidentally reverted
by ca2fb95 (#1847). Without them, gateway reads host paths from .env via
env_file, causing FileNotFoundError inside the container.
2. Langgraph command fails when LANGGRAPH_ALLOW_BLOCKING is unset (default).
Empty $${allow_blocking} inserts a bare space between flags, causing
' --no-reload' to be parsed as unexpected extra argument. Fix by building
args string first and conditionally appending --allow-blocking.
Co-authored-by: cooper <cooperfu@tencent.com>
* fix(frontend): resolve invalid HTML nesting and tabnabbing vulnerabilities (#1904)
* fix(frontend): resolve invalid HTML nesting and tabnabbing vulnerabilities
Fix `<button>` inside `<a>` invalid HTML in artifact components and add
missing `noopener,noreferrer` to `window.open` calls to prevent reverse
tabnabbing.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix(frontend): address Copilot review on tabnabbing and double-tab-open
Remove redundant parent onClick on web_fetch ChainOfThoughtStep to
prevent opening two tabs on link click, and explicitly null out
window.opener after window.open() for defensive tabnabbing hardening.
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* refactor(persistence): organize entities into per-entity directories
Restructure the persistence layer from horizontal "models/ + repositories/"
split into vertical entity-aligned directories. Each entity (thread_meta,
run, feedback) now owns its ORM model, abstract interface (where applicable),
and concrete implementations under a single directory with an aggregating
__init__.py for one-line imports.
Layout:
persistence/thread_meta/{base,model,sql,memory}.py
persistence/run/{model,sql}.py
persistence/feedback/{model,sql}.py
models/__init__.py is kept as a facade so Alembic autogenerate continues to
discover all ORM tables via Base.metadata. RunEventRow remains under
models/run_event.py because its storage implementation lives in
runtime/events/store/db.py and has no matching repository directory.
The repositories/ directory is removed entirely. All call sites in
gateway/deps.py and tests are updated to import from the new entity
packages, e.g.:
from deerflow.persistence.thread_meta import ThreadMetaRepository
from deerflow.persistence.run import RunRepository
from deerflow.persistence.feedback import FeedbackRepository
Full test suite passes (1690 passed, 14 skipped).
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix(gateway): sync thread rename and delete through ThreadMetaStore
The POST /threads/{id}/state endpoint previously synced title changes
only to the LangGraph Store via _store_upsert. In sqlite mode the search
endpoint reads from the ThreadMetaRepository SQL table, so renames never
appeared in /threads/search until the next agent run completed (worker.py
syncs title from checkpoint to thread_meta in its finally block).
Likewise the DELETE /threads/{id} endpoint cleaned up the filesystem,
Store, and checkpointer but left the threads_meta row orphaned in sqlite,
so deleted threads kept appearing in /threads/search.
Fix both endpoints by routing through the ThreadMetaStore abstraction
which already has the correct sqlite/memory implementations wired up by
deps.py. The rename path now calls update_display_name() and the delete
path calls delete() — both work uniformly across backends.
Verified end-to-end with curl in gateway mode against sqlite backend.
Existing test suite (1690 passed) and focused router/repo tests pass.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* refactor(gateway): route all thread metadata access through ThreadMetaStore
Following the rename/delete bug fix in PR1, migrate the remaining direct
LangGraph Store reads/writes in the threads router and services to the
ThreadMetaStore abstraction so that the sqlite and memory backends behave
identically and the legacy dual-write paths can be removed.
Migrated endpoints (threads.py):
- create_thread: idempotency check + write now use thread_meta_repo.get/create
instead of dual-writing the LangGraph Store and the SQL row.
- get_thread: reads from thread_meta_repo.get; the checkpoint-only fallback
for legacy threads is preserved.
- patch_thread: replaced _store_get/_store_put with thread_meta_repo.update_metadata.
- delete_thread_data: dropped the legacy store.adelete; thread_meta_repo.delete
already covers it.
Removed dead code (services.py):
- _upsert_thread_in_store — redundant with the immediately following
thread_meta_repo.create() call.
- _sync_thread_title_after_run — worker.py's finally block already syncs
the title via thread_meta_repo.update_display_name() after each run.
Removed dead code (threads.py):
- _store_get / _store_put / _store_upsert helpers (no remaining callers).
- THREADS_NS constant.
- get_store import (router no longer touches the LangGraph Store directly).
New abstract method:
- ThreadMetaStore.update_metadata(thread_id, metadata) merges metadata into
the thread's metadata field. Implemented in both ThreadMetaRepository (SQL,
read-modify-write inside one session) and MemoryThreadMetaStore. Three new
unit tests cover merge / empty / nonexistent behaviour.
Net change: -134 lines. Full test suite: 1693 passed, 14 skipped.
Verified end-to-end with curl in gateway mode against sqlite backend
(create / patch / get / rename / search / delete).
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: Copilot Autofix powered by AI <223894421+github-code-quality[bot]@users.noreply.github.com>
Co-authored-by: DanielWalnut <45447813+hetaoBackend@users.noreply.github.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
Co-authored-by: JilongSun <965640067@qq.com>
Co-authored-by: jie <49781832+stan-fu@users.noreply.github.com>
Co-authored-by: cooper <cooperfu@tencent.com>
Co-authored-by: yangzheli <43645580+yangzheli@users.noreply.github.com>
|
||
|
DanielWalnut
|
b970993425
|
fix: read lead agent options from context (#2515)
* fix: read lead agent options from context * fix: validate runtime context config |
||
|
Nan Gao
|
f9ff3a698d
|
fix(middleware): avoid rescuing non-skill tool outputs during summarization (#2458)
* fix(middelware): narrow skill rescue to skill-related tool outputs * fix(summarization): address skill rescue review feedback * fix: wire summarization skill rescue config * fix: remove dead skill tool helper * fix(lint): fix format --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
||
|
Hinotobi
|
2176b2bbfc
|
fix: validate bootstrap agent names before filesystem writes (#2274)
* fix: validate bootstrap agent names before filesystem writes * fix: tighten bootstrap agent-name validation |
||
|
DanielWalnut
|
4ba3167f48
|
feat: flush memory before summarization (#2176)
* feat: flush memory before summarization * fix: keep agent-scoped memory on summarization flush * fix: harden summarization hook plumbing * fix: address summarization review feedback * style: format memory middleware |
||
|
greatmengqi
|
084dc7e748
|
ci: enforce code formatting checks for backend and frontend (#1536) | ||
|
knukn
|
481494b9c0
|
feat(client): support custom middleware injection (#1520)
* feat(client): support custom middleware injection Add support for custom middleware, allowing custom middleware list to be passed when initializing DeerFlowClient. These middleware will be injected after the default middleware when creating the agent, extending the agent's functionality. * feat: inject custom middlewares before ClarificationMiddleware to preserve ordering - Add `custom_middlewares` param to `_build_middlewares` - Inject custom middlewares right before `ClarificationMiddleware` to keep it as the last in the chain - Remove unsafe `.extend()` in `client.py` - Update tests in `test_client.py` and `test_lead_agent_model_resolution.py` to assert correct injection ordering |
||
|
Admire
|
080a03f3bc
|
fix(config): fix summarization model alias resolution (#1378)
Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
||
|
DanielWalnut
|
76803b826f
|
refactor: split backend into harness (deerflow.*) and app (app.*) (#1131)
* refactor: extract shared utils to break harness→app cross-layer imports Move _validate_skill_frontmatter to src/skills/validation.py and CONVERTIBLE_EXTENSIONS + convert_file_to_markdown to src/utils/file_conversion.py. This eliminates the two reverse dependencies from client.py (harness layer) into gateway/routers/ (app layer), preparing for the harness/app package split. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * refactor: split backend/src into harness (deerflow.*) and app (app.*) Physically split the monolithic backend/src/ package into two layers: - **Harness** (`packages/harness/deerflow/`): publishable agent framework package with import prefix `deerflow.*`. Contains agents, sandbox, tools, models, MCP, skills, config, and all core infrastructure. - **App** (`app/`): unpublished application code with import prefix `app.*`. Contains gateway (FastAPI REST API) and channels (IM integrations). Key changes: - Move 13 harness modules to packages/harness/deerflow/ via git mv - Move gateway + channels to app/ via git mv - Rename all imports: src.* → deerflow.* (harness) / app.* (app layer) - Set up uv workspace with deerflow-harness as workspace member - Update langgraph.json, config.example.yaml, all scripts, Docker files - Add build-system (hatchling) to harness pyproject.toml - Add PYTHONPATH=. to gateway startup commands for app.* resolution - Update ruff.toml with known-first-party for import sorting - Update all documentation to reflect new directory structure Boundary rule enforced: harness code never imports from app. All 429 tests pass. Lint clean. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * chore: add harness→app boundary check test and update docs Add test_harness_boundary.py that scans all Python files in packages/harness/deerflow/ and fails if any `from app.*` or `import app.*` statement is found. This enforces the architectural rule that the harness layer never depends on the app layer. Update CLAUDE.md to document the harness/app split architecture, import conventions, and the boundary enforcement test. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat: add config versioning with auto-upgrade on startup When config.example.yaml schema changes, developers' local config.yaml files can silently become outdated. This adds a config_version field and auto-upgrade mechanism so breaking changes (like src.* → deerflow.* renames) are applied automatically before services start. - Add config_version: 1 to config.example.yaml - Add startup version check warning in AppConfig.from_file() - Add scripts/config-upgrade.sh with migration registry for value replacements - Add `make config-upgrade` target - Auto-run config-upgrade in serve.sh and start-daemon.sh before starting services - Add config error hints in service failure messages Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix comments * fix: update src.* import in test_sandbox_tools_security to deerflow.* Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: handle empty config and search parent dirs for config.example.yaml Address Copilot review comments on PR #1131: - Guard against yaml.safe_load() returning None for empty config files - Search parent directories for config.example.yaml instead of only looking next to config.yaml, fixing detection in common setups Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: correct skills root path depth and config_version type coercion - loader.py: fix get_skills_root_path() to use 5 parent levels (was 3) after harness split, file lives at packages/harness/deerflow/skills/ so parent×3 resolved to backend/packages/harness/ instead of backend/ - app_config.py: coerce config_version to int() before comparison in _check_config_version() to prevent TypeError when YAML stores value as string (e.g. config_version: "1") - tests: add regression tests for both fixes Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix: update test imports from src.* to deerflow.*/app.* after harness refactor Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> |
||
|
JeffJiang
|
7de94394d4
|
feat(agent):Supports custom agent and chat experience with refactoring (#957)
* feat: add agent management functionality with creation, editing, and deletion * feat: enhance agent creation and chat experience - Added AgentWelcome component to display agent description on new thread creation. - Improved agent name validation with availability check during agent creation. - Updated NewAgentPage to handle agent creation flow more effectively, including enhanced error handling and user feedback. - Refactored chat components to streamline message handling and improve user experience. - Introduced new bootstrap skill for personalized onboarding conversations, including detailed conversation phases and a structured SOUL.md template. - Updated localization files to reflect new features and error messages. - General code cleanup and optimizations across various components and hooks. * Refactor workspace layout and agent management components - Updated WorkspaceLayout to use useLayoutEffect for sidebar state initialization. - Removed unused AgentFormDialog and related edit functionality from AgentCard. - Introduced ArtifactTrigger component to manage artifact visibility. - Enhanced ChatBox to handle artifact selection and display. - Improved message list rendering logic to avoid loading states. - Updated localization files to remove deprecated keys and add new translations. - Refined hooks for local settings and thread management to improve performance and clarity. - Added temporal awareness guidelines to deep research skill documentation. * feat: refactor chat components and introduce thread management hooks * feat: improve artifact file detail preview logic and clean up console logs * feat: refactor lead agent creation logic and improve logging details * feat: validate agent name format and enhance error handling in agent setup * feat: simplify thread search query by removing unnecessary metadata * feat: update query key in useDeleteThread and useRenameThread for consistency * feat: add isMock parameter to thread and artifact handling for improved testing * fix: reorder import of setup_agent for consistency in builtins module * feat: append mock parameter to thread links in CaseStudySection for testing purposes * fix: update load_agent_soul calls to use cfg.name for improved clarity * fix: update date format in apply_prompt_template for consistency * feat: integrate isMock parameter into artifact content loading for enhanced testing * docs: add license section to SKILL.md for clarity and attribution * feat(agent): enhance model resolution and agent configuration handling * chore: remove unused import of _resolve_model_name from agents * feat(agent): remove unused field * fix(agent): set default value for requested_model_name in _resolve_model_name function * feat(agent): update get_available_tools call to handle optional agent_config and improve middleware function signature --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
||
|
Zhiyunyao
|
a138d5388a
|
feat: add reasoning_effort configuration support for Doubao/GPT-5 models (#947)
* feat: Add reasoning effort configuration support * Add `reasoning_effort` parameter to model config and agent initialization * Support reasoning effort levels (minimal/low/medium/high) for Doubao/GPT-5 models * Add UI controls in input box for reasoning effort selection * Update doubao-seed-1.8 example config with reasoning effort support Fixes & Cleanup: * Ensure UTF-8 encoding for file operations * Remove unused imports * fix: set reasoning_effort to None for unsupported models * fix: unit test error * Update frontend/src/components/workspace/input-box.tsx Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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|
Xinmin Zeng
|
6a55860a15
|
fix: recover from stale model context when configured models change (#898)
* fix: recover from stale model context after config model changes * fix: fail fast on missing model config and expand model resolution tests * fix: remove duplicate get_app_config imports * fix: align model resolution tests with runtime imports * Apply suggestions from code review Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * fix: remove duplicate model resolution test case --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> |