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43 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
 YuJitang
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5127f08e1a | enable token usage by default (#2841) | ||
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KiteEater
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7caf03e97c |
fix(packaging): add postgres extra for store/checkpointer supportFix postgres extra install guidance (#2584)
* Fix postgres extra install guidance * Fix postgres install message lint * Format postgres install messages * Fix postgres install guidance and config docs |
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Tao Liu
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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> |
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KiteEater
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4ead2c6b19 |
fix(config): reset config-backed singletons on hot reload (#2588)
* Fix stale config singletons on reload * fix(config): update checkpointer imports after runtime move * Fix config reload singleton mutation on validation failure --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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yangzheli
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59c4a3f0a4 |
feat(agent): add custom-agent self-updates with user isolation (#2713)
* feat(agent): add update_agent tool for in-chat custom-agent self-updates (#2616) Custom agents had no built-in way to persist updates to their own SOUL.md / config.yaml from a normal chat — `setup_agent` was only bound during the bootstrap flow, so when the user asked the agent to refine its description or personality, the agent would shell out via bash/write_file and the edits landed in a temporary sandbox/tool workspace instead of `{base_dir}/agents/{agent_name}/`. Changes: - New `update_agent` builtin tool with partial-update semantics (only the fields you pass are written) and atomic temp-file + os.replace writes so a failed update never corrupts existing SOUL.md / config.yaml. - Lead agent now binds `update_agent` in the non-bootstrap path whenever `agent_name` is set in the runtime context. Default agent (no agent_name) and bootstrap flow are unchanged. - New `<self_update>` system-prompt section is injected for custom agents, instructing them to use `update_agent` — and explicitly NOT bash / write_file — to persist self-updates. - Tests: 11 new cases in `tests/test_update_agent_tool.py` covering validation (missing/invalid agent_name, unknown agent, no fields), partial updates (soul-only, description-only, skills=[] vs omitted), no-op detection, atomic-write safety, and AgentConfig round-tripping; plus 2 new cases in `tests/test_lead_agent_prompt.py` covering the self-update prompt section. - Docs: updated backend/CLAUDE.md builtin tools list and tools.mdx (en/zh) with the new tool description. * feat(agent): isolate custom agents per user Store custom agent definitions under the effective user, keep legacy agents readable until migration, and cover API/tool/migration behavior with tests. Co-authored-by: Cursor <cursoragent@cursor.com> * feat: consistent write/delete targets & add --user-id to migration --------- Co-authored-by: Cursor <cursoragent@cursor.com> |
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Nan Gao
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f80ac961ec |
fix(harness): restore legacy skills path fallback (#2694) (#2696)
* fix(harness): restore legacy skills path fallback (#2694) * fix(format): make format * Potential fix for pull request finding Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.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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Nan Gao
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c09c334544 |
fix(harness): resolve runtime paths from project root (#2642)
* fix(harness): resolve runtime paths from project root * docs(config): update * fix(config): address runtime path review feedback * test(config): fix skills path e2e root * test(config): cover legacy config fallback when project root lacks config files Verifies that when DEER_FLOW_PROJECT_ROOT is unset and cwd has no config.yaml/extensions_config.json, AppConfig and ExtensionsConfig fall back to the legacy backend/repo-root candidates — the backward-compat path requested in PR #2642 review. --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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Xun
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1ad1420e31 | refactor(skills): Unified skill storage capability (#2613) | ||
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He Wang
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eba3b9e18d |
fix(config): unify log_level from config.yaml across Gateway and debug entry points (#2601)
Centralize log level parsing in `logging_level_from_config()` and application in `apply_logging_level()` within `deerflow.config.app_config`. - Gateway lifespan applies configured log level on startup - `debug.py` uses shared helpers instead of local duplicates - `apply_logging_level()` targets only `deerflow`/`app` logger hierarchies so third-party library verbosity is not affected; root handler levels are only lowered (never raised) to allow configured loggers through without suppressing third-party output; root logger level is not modified - Config field description updated to clarify scope - Tests save/restore global logging state to avoid test pollution Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com> |
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greatmengqi
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b8bc4826d8 |
refactor: root release config in gateway runtime (#2611)
Co-authored-by: greatmengqi <chenmengqi.0376@bytedance.com> |
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JeffJiang
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35ef8b7c13 | feat: add default database configuration for AppConfig and update example config | ||
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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
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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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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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Nan Gao
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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> |
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Xinmin Zeng
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30d619de08 |
feat(subagents): support per-subagent skill loading and custom subagent types (#2253)
* feat(subagents): support per-subagent skill loading and custom subagent types (#2230) Add per-subagent skill configuration and custom subagent type registration, aligned with Codex's role-based config layering and per-session skill injection. Backend: - SubagentConfig gains `skills` field (None=all, []=none, list=whitelist) - New CustomSubagentConfig for user-defined subagent types in config.yaml - SubagentsAppConfig gains `custom_agents` section and `get_skills_for()` - Registry resolves custom agents with three-layer config precedence - SubagentExecutor loads skills per-session as conversation items (Codex pattern) - task_tool no longer appends skills to system_prompt - Lead agent system prompt dynamically lists all registered subagent types - setup_agent tool accepts optional skills parameter - Gateway agents API transparently passes skills in CRUD operations Frontend: - Agent/CreateAgentRequest/UpdateAgentRequest types include skills field - Agent card displays skills as badges alongside tool_groups Config: - config.example.yaml documents custom_agents and per-agent skills override Tests: - 40 new tests covering all skill config, custom agents, and registry logic - Existing tests updated for new get_skills_prompt_section signature Closes #2230 * fix: address review feedback on skills PR - Remove stale get_skills_prompt_section monkeypatches from test_task_tool_core_logic.py (task_tool no longer imports this function after skill injection moved to executor) - Add key prefixes (tg:/sk:) to agent-card badges to prevent React key collisions between tool_groups and skills * fix(ci): resolve lint and test failures - Format agent-card.tsx with prettier (lint-frontend) - Remove stale "Skills Appendix" system_prompt assertion — skills are now loaded per-session by SubagentExecutor, not appended to system_prompt * fix(ci): sort imports in test_subagent_skills_config.py (ruff I001) * fix(ci): use nullish coalescing in agent-card badge condition (eslint) * fix: address review feedback on skills PR - Use model_fields_set in AgentUpdateRequest to distinguish "field omitted" from "explicitly set to null" — fixes skills=None ambiguity where None means "inherit all" but was treated as "don't change" - Move lazy import of get_subagent_config outside loop in _build_available_subagents_description to avoid repeated import overhead --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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Hinotobi
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2176b2bbfc |
fix: validate bootstrap agent names before filesystem writes (#2274)
* fix: validate bootstrap agent names before filesystem writes * fix: tighten bootstrap agent-name validation |
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Hinotobi
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a7e7c6d667 |
fix: disable custom-agent management API by default (#2161)
* fix: disable custom-agent management API by default * style: format agents API hardening files * fix: address review feedback for agents API hardening * fix: add missing disabled API coverage |
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Jin
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4d4ddb3d3f | feat(llm): introduce lightweight circuit breaker to prevent rate-limit bans and resource exhaustion (#2095) | ||
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Javen Fang
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ac04f2704f |
feat(subagents): allow model override per subagent in config.yaml (#2064)
* feat(subagents): allow model override per subagent in config.yaml Wire the existing SubagentConfig.model field to config.yaml so users can assign different models to different subagent types. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * test(subagents): cover model override in SubagentsAppConfig + registry Addresses review feedback on #2064: - registry.py: update stale inline comment — the block now applies timeout, max_turns AND model overrides, not just timeout. - test_subagent_timeout_config.py: add coverage for model override resolution across SubagentOverrideConfig, SubagentsAppConfig (get_model_for + load), and registry.get_subagent_config: - per-agent model override is applied to registry-returned config - omitted `model` keeps the builtin value - explicit `model: null` in config.yaml is equivalent to omission - model override on one agent does not affect other agents - model override preserves all other fields (name, description, timeout_seconds, max_turns) - model override does not mutate BUILTIN_SUBAGENTS Copilot's suggestion (3) "setting model to 'inherit' forces inheritance" is skipped intentionally: there is no 'inherit' sentinel in the current implementation — model is `str | None`, and None already means "inherit from parent". Adding a sentinel would be a new feature, not test coverage for this PR. Tests run locally: 51 passed (37 existing + 14 new / expanded). * test(subagents): reject empty-string model at config load time Addresses WillemJiang's review comment on #2064 (empty-string edge case): - subagents_config.py: add `min_length=1` to the `model` field on SubagentOverrideConfig. `model: ""` in config.yaml would otherwise bypass the `is not None` check and reach create_chat_model(name="") as a confusing runtime error. This is symmetric with the existing `ge=1` guards on timeout_seconds / max_turns, so the validation style stays consistent across all three override fields. - test_subagent_timeout_config.py: add test_rejects_empty_model mirroring the existing test_rejects_zero / test_rejects_negative cases; update the docstring on test_model_accepts_any_string (now test_model_accepts_any_non_empty_string) to reflect the new guard. Not addressing the first comment (validating `model` against the `models:` section at load time) in this PR. `SubagentsAppConfig` is scoped to the `subagents:` block and cannot see the sibling `models:` section, so proper cross-section validation needs a second pass or a structural change that is out of scope here — and the current behavior is consistent with how timeout_seconds / max_turns work today. Happy to track this as a follow-up issue covering cross-section validation uniformly for all three fields. Tests run locally: 52 passed in this file; 1847 passed, 18 skipped across the full backend suite. Ruff check + format clean. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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shivam johri
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194bab4691 |
feat(config): add when_thinking_disabled support for model configs (#1970)
* feat(config): add when_thinking_disabled support for model configs Allow users to explicitly configure what parameters are sent to the model when thinking is disabled, via a new `when_thinking_disabled` field in model config. This mirrors the existing `when_thinking_enabled` pattern and takes full precedence over the hardcoded disable behavior when set. Backwards compatible — existing configs work unchanged. Closes #1675 * fix(config): address copilot review — gate when_thinking_disabled independently - Switch truthiness check to `is not None` so empty dict overrides work - Restructure disable path so when_thinking_disabled is gated independently of has_thinking_settings, allowing it to work without when_thinking_enabled - Update test to reflect new behavior |
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DanielWalnut
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888f7bfb9d |
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> |
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yangzheli
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5fd2c581f6 |
fix: add output truncation to ls_tool to prevent context window overflow (#1896)
ls_tool was the only sandbox tool without output size limits, allowing multi-MB results from large directories to blow up the model context window. Add head-truncation (configurable via ls_output_max_chars, default 20000) consistent with existing bash and read_file truncation. Closes #1887 Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> |
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Markus Corazzione
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0ffe5a73c1 | chroe(config):Increase subagent max-turn limits (#1852) | ||
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DanielWalnut
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2a150f5d4a |
fix: unblock concurrent threads and workspace hydration (#1839)
* fix: unblock concurrent threads and workspace hydration * fix: restore async title generation * fix: address PR review feedback * style: format lead agent prompt |
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SHIYAO ZHANG
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ddfc988bef |
feat(uploads): add pymupdf4llm PDF converter with auto-fallback and async offload (#1727)
* feat(uploads): add pymupdf4llm PDF converter with auto-fallback and async offload - Introduce pymupdf4llm as an optional PDF converter with better heading detection and table preservation than MarkItDown - Auto mode: prefer pymupdf4llm when installed; fall back to MarkItDown when output is suspiciously sparse (image-based / scanned PDFs) - Sparsity check uses chars-per-page (< 50 chars/page) rather than an absolute threshold, correctly handling both short and long documents - Large files (> 1 MB) are offloaded to asyncio.to_thread() to avoid blocking the event loop (related: #1569) - Add UploadsConfig with pdf_converter field (auto/pymupdf4llm/markitdown) - Add pymupdf4llm as optional dependency: pip install deerflow-harness[pymupdf] - Add 14 unit tests covering sparsity heuristic, routing logic, and async path * fix(uploads): address Copilot review comments on PDF converter - Fix docstring: MIN_CHARS_PYMUPDF -> _MIN_CHARS_PER_PAGE (typo) - Fix file handle leak: wrap pymupdf.open in try/finally to ensure doc.close() - Fix silent fallback gap: _convert_pdf_with_pymupdf4llm now catches all conversion exceptions (not just ImportError), so encrypted/corrupt PDFs fall back to MarkItDown instead of propagating - Tighten type: pdf_converter field changed from str to Literal[auto|pymupdf4llm|markitdown] - Normalize config value: _get_pdf_converter() strips and lowercases the raw config string, warns and falls back to 'auto' on unknown values |
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knukn
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f8fb8d6fb1 |
feat/per agent skill filter (#1650)
* feat(agent): 为AgentConfig添加skills字段并更新lead_agent系统提示 在AgentConfig中添加skills字段以支持配置agent可用技能 更新lead_agent的系统提示模板以包含可用技能信息 * fix: resolve agent skill configuration edge cases and add tests * Update backend/packages/harness/deerflow/agents/lead_agent/prompt.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * refactor(agent): address PR review comments for skills configuration - Add detailed docstring to `skills` field in `AgentConfig` to clarify the semantics of `None` vs `[]`. - Add unit tests in `test_custom_agent.py` to verify `load_agent_config()` correctly parses omitted skills and explicit empty lists. - Fix `test_make_lead_agent_empty_skills_passed_correctly` to include `agent_name` in the runtime config, ensuring it exercises the real code path. * docs: 添加关于按代理过滤技能的配置说明 在配置示例文件和文档中添加说明，解释如何通过代理的config.yaml文件限制加载的技能 --------- Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> |
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totoyang
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2d1f90d5dc |
feat(tracing): add optional Langfuse support (#1717)
* feat(tracing): add optional Langfuse support * Fix tracing fail-fast behavior for explicitly enabled providers * fix(lint) |
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SHIYAO ZHANG
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df5339b5d0 |
feat(sandbox): truncate oversized bash and read_file tool outputs (#1677)
* feat(sandbox): truncate oversized bash and read_file tool outputs Long tool outputs (large directory listings, multi-MB source files) can overflow the model's context window. Two new configurable limits: - bash_output_max_chars (default 20000): middle-truncates bash output, preserving both head and tail so stderr at the end is not lost - read_file_output_max_chars (default 50000): head-truncates file output with a hint to use start_line/end_line for targeted reads Both limits are enforced at the tool layer (sandbox/tools.py) rather than middleware, so truncation is guaranteed regardless of call path. Setting either limit to 0 disables truncation entirely. Measured: read_file on a 250KB source file drops from 63,698 tokens to 19,927 tokens (69% reduction) with the default limit. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(tests): remove unused pytest import and fix import sort order * style: apply ruff format to sandbox/tools.py * refactor(sandbox): address Copilot review feedback on truncation feature - strict hard cap: while-loop ensures result (including marker) ≤ max_chars - max_chars=0 now returns "" instead of original output - get_app_config() wrapped in try/except with fallback to defaults - sandbox_config.py: add ge=0 validation on truncation limit fields - config.example.yaml: bump config_version 4→5 - tests: add len(result) <= max_chars assertions, edge-case (max=0, small max, various sizes) tests; fix skipped-count test for strict hard cap * refactor(sandbox): replace while-loop truncation with fixed marker budget Use a pre-allocated constant (_MARKER_MAX_LEN) instead of a convergence loop to ensure result <= max_chars. Simpler, safer, and skipped-char count in the marker is now an exact predictable value. * refactor(sandbox): compute marker budget dynamically instead of hardcoding * fix(sandbox): make max_chars=0 disable truncation instead of returning empty string --------- Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> Co-authored-by: JeffJiang <for-eleven@hotmail.com> |
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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> |
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|
13ernkastel
|
92c7a20cb7 |
[Security] Address critical host-shell escape in LocalSandboxProvider (#1547)
* fix(security): disable host bash by default in local sandbox * fix(security): address review feedback for local bash hardening * fix(ci): sort live test imports for lint * style: apply backend formatter --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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|
DanielWalnut
|
8590249db4 |
feat(acp): add env field to ACPAgentConfig for subprocess env injection (#1447)
Allow per-agent environment variables to be declared in config.yaml under acp_agents.<name>.env. Values prefixed with $ are resolved from the host environment at invocation time, consistent with other config fields. Passes None to spawn_agent_process when env is empty so the subprocess inherits the parent environment unchanged. Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> |
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|
knukn
|
1c542ab7f1 |
feat(memory): Introduce configurable memory storage abstraction (#1353)
* feat(内存存储): 添加可配置的内存存储提供者支持 实现内存存储的抽象基类 MemoryStorage 和文件存储实现 FileMemoryStorage 重构内存数据加载和保存逻辑到存储提供者中 添加 storage_class 配置项以支持自定义存储提供者 * refactor(memory): 重构内存存储模块并更新相关测试 将内存存储逻辑从updater模块移动到独立的storage模块 使用存储接口模式替代直接文件操作 更新所有相关测试以使用新的存储接口 * Update backend/packages/harness/deerflow/agents/memory/storage.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Update backend/packages/harness/deerflow/agents/memory/storage.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * fix(内存存储): 添加线程安全锁并增加测试用例 添加线程锁确保内存存储单例初始化的线程安全 增加对无效代理名称的验证测试 补充单例线程安全性和异常处理的测试用例 * Update backend/tests/test_memory_storage.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * fix(agents): 使用统一模式验证代理名称 修改代理名称验证逻辑以使用仓库中定义的AGENT_NAME_PATTERN模式，确保代码库一致性并防止路径遍历等安全问题。同时更新测试用例以覆盖更多无效名称情况。 --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> |
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|
DanielWalnut
|
d119214fee |
feat(harness): integration ACP agent tool (#1344)
* 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> * feat(harness): add tool-first ACP agent invocation (#37) * feat(harness): add tool-first ACP agent invocation * build(harness): make ACP dependency required * fix(harness): address ACP review feedback * feat(harness): decouple ACP agent workspace from thread data ACP agents (codex, claude-code) previously used per-thread workspace directories, causing path resolution complexity and coupling task execution to DeerFlow's internal thread data layout. This change: - Replace _resolve_cwd() with a fixed _get_work_dir() that always uses {base_dir}/acp-workspace/, eliminating virtual path translation and thread_id lookups - Introduce /mnt/acp-workspace virtual path for lead agent read-only access to ACP agent output files (same pattern as /mnt/skills) - Add security guards: read-only validation, path traversal prevention, command path allowlisting, and output masking for acp-workspace - Update system prompt and tool description to guide LLM: send self-contained tasks to ACP agents, copy results via /mnt/acp-workspace - Add 11 new security tests for ACP workspace path handling Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * refactor(prompt): inject ACP section only when ACP agents are configured The ACP agent guidance in the system prompt is now conditionally built by _build_acp_section(), which checks get_acp_agents() and returns an empty string when no ACP agents are configured. This avoids polluting the prompt with irrelevant instructions for users who don't use ACP. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix lint * fix(harness): address Copilot review comments on sandbox path handling and ACP tool - local_sandbox: fix path-segment boundary bug in _resolve_path (== or startswith +"/") and add lookahead in _resolve_paths_in_command regex to prevent /mnt/skills matching inside /mnt/skills-extra - local_sandbox_provider: replace print() with logger.warning(..., exc_info=True) - invoke_acp_agent_tool: guard getattr(option, "optionId") with None default + continue; move full prompt from INFO to DEBUG level (truncated to 200 chars) - sandbox/tools: fix _get_acp_workspace_host_path docstring to match implementation; remove misleading "read-only" language from validate_local_bash_command_paths Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(acp): thread-isolated workspaces, permission guardrail, and ContextVar registry P1.1 – ACP workspace thread isolation - Add `Paths.acp_workspace_dir(thread_id)` for per-thread paths - `_get_work_dir(thread_id)` in invoke_acp_agent_tool now uses `{base_dir}/threads/{thread_id}/acp-workspace/`; falls back to global workspace when thread_id is absent or invalid - `_invoke` extracts thread_id from `RunnableConfig` via `Annotated[RunnableConfig, InjectedToolArg]` - `sandbox/tools.py`: `_get_acp_workspace_host_path(thread_id)`, `_resolve_acp_workspace_path(path, thread_id)`, and all callers (`replace_virtual_paths_in_command`, `mask_local_paths_in_output`, `ls_tool`, `read_file_tool`) now resolve ACP paths per-thread P1.2 – ACP permission guardrail - New `auto_approve_permissions: bool = False` field in `ACPAgentConfig` - `_build_permission_response(options, *, auto_approve: bool)` now defaults to deny; only approves when `auto_approve=True` - Document field in `config.example.yaml` P2 – Deferred tool registry race condition - Replace module-level `_registry` global with `contextvars.ContextVar` - Each asyncio request context gets its own registry; worker threads inherit the context automatically via `loop.run_in_executor` - Expose `get_deferred_registry` / `set_deferred_registry` / `reset_deferred_registry` helpers Tests: 831 pass (57 for affected modules, 3 new tests) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(sandbox): mount /mnt/acp-workspace in docker sandbox container The AioSandboxProvider was not mounting the ACP workspace into the sandbox container, so /mnt/acp-workspace was inaccessible when the lead agent tried to read ACP results in docker mode. Changes: - `ensure_thread_dirs`: also create `acp-workspace/` (chmod 0o777) so the directory exists before the sandbox container starts — required for Docker volume mounts - `_get_thread_mounts`: add read-only `/mnt/acp-workspace` mount using the per-thread host path (`host_paths.acp_workspace_dir(thread_id)`) - Update stale CLAUDE.md description (was "fixed global workspace") Tests: `test_aio_sandbox_provider.py` (4 new tests) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix(lint): remove unused imports in test_aio_sandbox_provider Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix config --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> |
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|
greatmengqi
|
16ed797e0e |
feat: add configurable log level and token usage tracking (#1301)
* feat: add configurable log level and token usage tracking - Add `log_level` config to control deerflow module log level, synced to LangGraph Server via serve.sh `--server-log-level` - Add `token_usage.enabled` config with TokenUsageMiddleware that logs input/output/total tokens per LLM call from usage_metadata - Add .omc/ to .gitignore * fix: use info level for token usage logs since feature has its own toggle * fix: sort imports to pass lint check --------- Co-authored-by: greatmengqi <chenmengqi.0376@bytedance.com> Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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|
amdoi7.
|
8b0f3fe233 |
fix(threads): clean up local thread data after thread deletion (#1262)
* fix(threads): clean up local thread data after thread deletion Delete DeerFlow-managed thread directories after the web UI removes a LangGraph thread. This keeps local thread data in sync with conversation deletion and adds regression coverage for the cleanup flow. * fix(threads): address thread cleanup review feedback Encode thread cleanup URLs in the web client, keep cache updates explicit when no thread search data is cached, and return a generic 500 response from the cleanup endpoint while documenting the sanitized error behavior. --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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|
Uchi Uchibeke
|
a29134d7c9 |
feat(guardrails): add pre-tool-call authorization middleware with pluggable providers (#1240)
Add GuardrailMiddleware that evaluates every tool call before execution. Three provider options: built-in AllowlistProvider (zero deps), OAP passport providers (open standard), or custom providers loaded by class path. - GuardrailProvider protocol with GuardrailRequest/Decision dataclasses - GuardrailMiddleware (AgentMiddleware, position 5 in chain) - AllowlistProvider for simple deny/allow by tool name - GuardrailsConfig (Pydantic singleton, loaded from config.yaml) - 25 tests covering allow/deny, fail-closed/open, async, GraphBubbleUp - Comprehensive docs at backend/docs/GUARDRAILS.md Closes #1213 Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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|
mxyhi
|
e119dc74ae |
feat(codex): support explicit OpenAI Responses API config (#1235)
* feat: support explicit OpenAI Responses API config Co-authored-by: Codex <noreply@openai.com> * Update backend/packages/harness/deerflow/config/model_config.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --------- Co-authored-by: Codex <noreply@openai.com> Co-authored-by: Willem Jiang <willem.jiang@gmail.com> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> |
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|
Gao Mingfei
|
644501ae07 |
fix(config): reload AppConfig when config path or mtime changes (#1239)
* fix(config): reload AppConfig when config path or mtime changes - Track resolved path + mtime; invalidate cache on change - Preserve set_app_config() injection behavior - Add regression tests (test_app_config_reload.py) - Document behavior in README and backend/CLAUDE.md Signed-off-by: Gao Mingfei <g199209@gmail.com> * Apply suggestions from code review Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --------- Signed-off-by: Gao Mingfei <g199209@gmail.com> Co-authored-by: Willem Jiang <willem.jiang@gmail.com> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> |
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|
lhd
|
0091d9f071 |
feat(tools): add tool_search for deferred MCP tool loading (#1176)
* feat(tools): add tool_search for deferred MCP tool loading When multiple MCP servers are enabled, total tool count can exceed 30-50, causing context bloat and degraded tool selection accuracy. This adds a deferred tool loading mechanism controlled by `tool_search.enabled` config. - Add ToolSearchConfig with single `enabled` field - Add DeferredToolRegistry with regex search (select:, +keyword, keyword) - Add tool_search tool returning OpenAI-compatible function JSON - Add DeferredToolFilterMiddleware to hide deferred schemas from bind_tools - Add <available-deferred-tools> section to system prompt - Enable MCP tool_name_prefix to prevent cross-server name collisions - Add 34 unit tests covering registry, tool, prompt, and middleware * fix: reset stale deferred registry and bump config_version - Reset deferred registry upfront in get_available_tools() to prevent stale tool entries when MCP servers are disabled between calls - Bump config_version to 2 for new tool_search config field Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix(tests): mock get_app_config in prompt section tests for CI CI has no config.yaml, causing TestDeferredToolsPromptSection to fail with FileNotFoundError. Add autouse fixture to mock get_app_config. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> |
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|
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> |