d8ecaf46c9
* 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 infb2d99f(#1836) but accidentally reverted byca2fb95(#1847). Without them, gateway reads host paths from .env via env_file, causing FileNotFoundError inside the container. 2. Langgraph command fails when LANGGRAPH_ALLOW_BLOCKING is unset (default). Empty $${allow_blocking} inserts a bare space between flags, causing ' --no-reload' to be parsed as unexpected extra argument. Fix by building args string first and conditionally appending --allow-blocking. Co-authored-by: cooper <cooperfu@tencent.com> * fix(frontend): resolve invalid HTML nesting and tabnabbing vulnerabilities (#1904) * fix(frontend): resolve invalid HTML nesting and tabnabbing vulnerabilities Fix `<button>` inside `<a>` invalid HTML in artifact components and add missing `noopener,noreferrer` to `window.open` calls to prevent reverse tabnabbing. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix(frontend): address Copilot review on tabnabbing and double-tab-open Remove redundant parent onClick on web_fetch ChainOfThoughtStep to prevent opening two tabs on link click, and explicitly null out window.opener after window.open() for defensive tabnabbing hardening. --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> * refactor(persistence): organize entities into per-entity directories Restructure the persistence layer from horizontal "models/ + repositories/" split into vertical entity-aligned directories. Each entity (thread_meta, run, feedback) now owns its ORM model, abstract interface (where applicable), and concrete implementations under a single directory with an aggregating __init__.py for one-line imports. Layout: persistence/thread_meta/{base,model,sql,memory}.py persistence/run/{model,sql}.py persistence/feedback/{model,sql}.py models/__init__.py is kept as a facade so Alembic autogenerate continues to discover all ORM tables via Base.metadata. RunEventRow remains under models/run_event.py because its storage implementation lives in runtime/events/store/db.py and has no matching repository directory. The repositories/ directory is removed entirely. All call sites in gateway/deps.py and tests are updated to import from the new entity packages, e.g.: from deerflow.persistence.thread_meta import ThreadMetaRepository from deerflow.persistence.run import RunRepository from deerflow.persistence.feedback import FeedbackRepository Full test suite passes (1690 passed, 14 skipped). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(gateway): sync thread rename and delete through ThreadMetaStore The POST /threads/{id}/state endpoint previously synced title changes only to the LangGraph Store via _store_upsert. In sqlite mode the search endpoint reads from the ThreadMetaRepository SQL table, so renames never appeared in /threads/search until the next agent run completed (worker.py syncs title from checkpoint to thread_meta in its finally block). Likewise the DELETE /threads/{id} endpoint cleaned up the filesystem, Store, and checkpointer but left the threads_meta row orphaned in sqlite, so deleted threads kept appearing in /threads/search. Fix both endpoints by routing through the ThreadMetaStore abstraction which already has the correct sqlite/memory implementations wired up by deps.py. The rename path now calls update_display_name() and the delete path calls delete() — both work uniformly across backends. Verified end-to-end with curl in gateway mode against sqlite backend. Existing test suite (1690 passed) and focused router/repo tests pass. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * refactor(gateway): route all thread metadata access through ThreadMetaStore Following the rename/delete bug fix in PR1, migrate the remaining direct LangGraph Store reads/writes in the threads router and services to the ThreadMetaStore abstraction so that the sqlite and memory backends behave identically and the legacy dual-write paths can be removed. Migrated endpoints (threads.py): - create_thread: idempotency check + write now use thread_meta_repo.get/create instead of dual-writing the LangGraph Store and the SQL row. - get_thread: reads from thread_meta_repo.get; the checkpoint-only fallback for legacy threads is preserved. - patch_thread: replaced _store_get/_store_put with thread_meta_repo.update_metadata. - delete_thread_data: dropped the legacy store.adelete; thread_meta_repo.delete already covers it. Removed dead code (services.py): - _upsert_thread_in_store — redundant with the immediately following thread_meta_repo.create() call. - _sync_thread_title_after_run — worker.py's finally block already syncs the title via thread_meta_repo.update_display_name() after each run. Removed dead code (threads.py): - _store_get / _store_put / _store_upsert helpers (no remaining callers). - THREADS_NS constant. - get_store import (router no longer touches the LangGraph Store directly). New abstract method: - ThreadMetaStore.update_metadata(thread_id, metadata) merges metadata into the thread's metadata field. Implemented in both ThreadMetaRepository (SQL, read-modify-write inside one session) and MemoryThreadMetaStore. Three new unit tests cover merge / empty / nonexistent behaviour. Net change: -134 lines. Full test suite: 1693 passed, 14 skipped. Verified end-to-end with curl in gateway mode against sqlite backend (create / patch / get / rename / search / delete). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> Co-authored-by: Copilot Autofix powered by AI <223894421+github-code-quality[bot]@users.noreply.github.com> Co-authored-by: DanielWalnut <45447813+hetaoBackend@users.noreply.github.com> Co-authored-by: Willem Jiang <willem.jiang@gmail.com> Co-authored-by: JilongSun <965640067@qq.com> Co-authored-by: jie <49781832+stan-fu@users.noreply.github.com> Co-authored-by: cooper <cooperfu@tencent.com> Co-authored-by: yangzheli <43645580+yangzheli@users.noreply.github.com>
402 lines
17 KiB
Python
402 lines
17 KiB
Python
import logging
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import os
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from contextvars import ContextVar
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from pathlib import Path
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from typing import Any, Self
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import yaml
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from dotenv import load_dotenv
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from pydantic import BaseModel, ConfigDict, Field
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from deerflow.config.acp_config import load_acp_config_from_dict
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from deerflow.config.agents_api_config import AgentsApiConfig, load_agents_api_config_from_dict
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from deerflow.config.checkpointer_config import CheckpointerConfig, load_checkpointer_config_from_dict
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from deerflow.config.database_config import DatabaseConfig
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from deerflow.config.extensions_config import ExtensionsConfig
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from deerflow.config.guardrails_config import GuardrailsConfig, load_guardrails_config_from_dict
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from deerflow.config.memory_config import MemoryConfig, load_memory_config_from_dict
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from deerflow.config.model_config import ModelConfig
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from deerflow.config.run_events_config import RunEventsConfig
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from deerflow.config.sandbox_config import SandboxConfig
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from deerflow.config.skill_evolution_config import SkillEvolutionConfig
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from deerflow.config.skills_config import SkillsConfig
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from deerflow.config.stream_bridge_config import StreamBridgeConfig, load_stream_bridge_config_from_dict
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from deerflow.config.subagents_config import SubagentsAppConfig, load_subagents_config_from_dict
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from deerflow.config.summarization_config import SummarizationConfig, load_summarization_config_from_dict
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from deerflow.config.title_config import TitleConfig, load_title_config_from_dict
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from deerflow.config.token_usage_config import TokenUsageConfig
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from deerflow.config.tool_config import ToolConfig, ToolGroupConfig
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from deerflow.config.tool_search_config import ToolSearchConfig, load_tool_search_config_from_dict
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load_dotenv()
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logger = logging.getLogger(__name__)
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class CircuitBreakerConfig(BaseModel):
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"""Configuration for the LLM Circuit Breaker."""
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failure_threshold: int = Field(default=5, description="Number of consecutive failures before tripping the circuit")
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recovery_timeout_sec: int = Field(default=60, description="Time in seconds before attempting to recover the circuit")
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def _default_config_candidates() -> tuple[Path, ...]:
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"""Return deterministic config.yaml locations without relying on cwd."""
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backend_dir = Path(__file__).resolve().parents[4]
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repo_root = backend_dir.parent
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return (backend_dir / "config.yaml", repo_root / "config.yaml")
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class AppConfig(BaseModel):
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"""Config for the DeerFlow application"""
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log_level: str = Field(default="info", description="Logging level for deerflow modules (debug/info/warning/error)")
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token_usage: TokenUsageConfig = Field(default_factory=TokenUsageConfig, description="Token usage tracking configuration")
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models: list[ModelConfig] = Field(default_factory=list, description="Available models")
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sandbox: SandboxConfig = Field(description="Sandbox configuration")
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tools: list[ToolConfig] = Field(default_factory=list, description="Available tools")
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tool_groups: list[ToolGroupConfig] = Field(default_factory=list, description="Available tool groups")
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skills: SkillsConfig = Field(default_factory=SkillsConfig, description="Skills configuration")
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skill_evolution: SkillEvolutionConfig = Field(default_factory=SkillEvolutionConfig, description="Agent-managed skill evolution configuration")
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extensions: ExtensionsConfig = Field(default_factory=ExtensionsConfig, description="Extensions configuration (MCP servers and skills state)")
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tool_search: ToolSearchConfig = Field(default_factory=ToolSearchConfig, description="Tool search / deferred loading configuration")
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title: TitleConfig = Field(default_factory=TitleConfig, description="Automatic title generation configuration")
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summarization: SummarizationConfig = Field(default_factory=SummarizationConfig, description="Conversation summarization configuration")
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memory: MemoryConfig = Field(default_factory=MemoryConfig, description="Memory subsystem configuration")
|
|
agents_api: AgentsApiConfig = Field(default_factory=AgentsApiConfig, description="Custom-agent management API configuration")
|
|
subagents: SubagentsAppConfig = Field(default_factory=SubagentsAppConfig, description="Subagent runtime configuration")
|
|
guardrails: GuardrailsConfig = Field(default_factory=GuardrailsConfig, description="Guardrail middleware configuration")
|
|
circuit_breaker: CircuitBreakerConfig = Field(default_factory=CircuitBreakerConfig, description="LLM circuit breaker configuration")
|
|
model_config = ConfigDict(extra="allow", frozen=False)
|
|
database: DatabaseConfig = Field(default_factory=DatabaseConfig, description="Unified database backend configuration")
|
|
run_events: RunEventsConfig = Field(default_factory=RunEventsConfig, description="Run event storage configuration")
|
|
checkpointer: CheckpointerConfig | None = Field(default=None, description="Checkpointer configuration")
|
|
stream_bridge: StreamBridgeConfig | None = Field(default=None, description="Stream bridge configuration")
|
|
|
|
@classmethod
|
|
def resolve_config_path(cls, config_path: str | None = None) -> Path:
|
|
"""Resolve the config file path.
|
|
|
|
Priority:
|
|
1. If provided `config_path` argument, use it.
|
|
2. If provided `DEER_FLOW_CONFIG_PATH` environment variable, use it.
|
|
3. Otherwise, search deterministic backend/repository-root defaults from `_default_config_candidates()`.
|
|
"""
|
|
if config_path:
|
|
path = Path(config_path)
|
|
if not Path.exists(path):
|
|
raise FileNotFoundError(f"Config file specified by param `config_path` not found at {path}")
|
|
return path
|
|
elif os.getenv("DEER_FLOW_CONFIG_PATH"):
|
|
path = Path(os.getenv("DEER_FLOW_CONFIG_PATH"))
|
|
if not Path.exists(path):
|
|
raise FileNotFoundError(f"Config file specified by environment variable `DEER_FLOW_CONFIG_PATH` not found at {path}")
|
|
return path
|
|
else:
|
|
for path in _default_config_candidates():
|
|
if path.exists():
|
|
return path
|
|
raise FileNotFoundError("`config.yaml` file not found at the default backend or repository root locations")
|
|
|
|
@classmethod
|
|
def from_file(cls, config_path: str | None = None) -> Self:
|
|
"""Load config from YAML file.
|
|
|
|
See `resolve_config_path` for more details.
|
|
|
|
Args:
|
|
config_path: Path to the config file.
|
|
|
|
Returns:
|
|
AppConfig: The loaded config.
|
|
"""
|
|
resolved_path = cls.resolve_config_path(config_path)
|
|
with open(resolved_path, encoding="utf-8") as f:
|
|
config_data = yaml.safe_load(f) or {}
|
|
|
|
# Check config version before processing
|
|
cls._check_config_version(config_data, resolved_path)
|
|
|
|
config_data = cls.resolve_env_variables(config_data)
|
|
|
|
# Load title config if present
|
|
if "title" in config_data:
|
|
load_title_config_from_dict(config_data["title"])
|
|
|
|
# Load summarization config if present
|
|
if "summarization" in config_data:
|
|
load_summarization_config_from_dict(config_data["summarization"])
|
|
|
|
# Load memory config if present
|
|
if "memory" in config_data:
|
|
load_memory_config_from_dict(config_data["memory"])
|
|
|
|
# Always refresh agents API config so removed config sections reset
|
|
# singleton-backed state to its default/disabled values on reload.
|
|
load_agents_api_config_from_dict(config_data.get("agents_api") or {})
|
|
|
|
# Load subagents config if present
|
|
if "subagents" in config_data:
|
|
load_subagents_config_from_dict(config_data["subagents"])
|
|
|
|
# Load tool_search config if present
|
|
if "tool_search" in config_data:
|
|
load_tool_search_config_from_dict(config_data["tool_search"])
|
|
|
|
# Load guardrails config if present
|
|
if "guardrails" in config_data:
|
|
load_guardrails_config_from_dict(config_data["guardrails"])
|
|
|
|
# Load circuit_breaker config if present
|
|
if "circuit_breaker" in config_data:
|
|
config_data["circuit_breaker"] = config_data["circuit_breaker"]
|
|
|
|
# Load checkpointer config if present
|
|
if "checkpointer" in config_data:
|
|
load_checkpointer_config_from_dict(config_data["checkpointer"])
|
|
|
|
# Load stream bridge config if present
|
|
if "stream_bridge" in config_data:
|
|
load_stream_bridge_config_from_dict(config_data["stream_bridge"])
|
|
|
|
# Always refresh ACP agent config so removed entries do not linger across reloads.
|
|
load_acp_config_from_dict(config_data.get("acp_agents", {}))
|
|
|
|
# Load extensions config separately (it's in a different file)
|
|
extensions_config = ExtensionsConfig.from_file()
|
|
config_data["extensions"] = extensions_config.model_dump()
|
|
|
|
result = cls.model_validate(config_data)
|
|
return result
|
|
|
|
@classmethod
|
|
def _check_config_version(cls, config_data: dict, config_path: Path) -> None:
|
|
"""Check if the user's config.yaml is outdated compared to config.example.yaml.
|
|
|
|
Emits a warning if the user's config_version is lower than the example's.
|
|
Missing config_version is treated as version 0 (pre-versioning).
|
|
"""
|
|
try:
|
|
user_version = int(config_data.get("config_version", 0))
|
|
except (TypeError, ValueError):
|
|
user_version = 0
|
|
|
|
# Find config.example.yaml by searching config.yaml's directory and its parents
|
|
example_path = None
|
|
search_dir = config_path.parent
|
|
for _ in range(5): # search up to 5 levels
|
|
candidate = search_dir / "config.example.yaml"
|
|
if candidate.exists():
|
|
example_path = candidate
|
|
break
|
|
parent = search_dir.parent
|
|
if parent == search_dir:
|
|
break
|
|
search_dir = parent
|
|
if example_path is None:
|
|
return
|
|
|
|
try:
|
|
with open(example_path, encoding="utf-8") as f:
|
|
example_data = yaml.safe_load(f)
|
|
raw = example_data.get("config_version", 0) if example_data else 0
|
|
try:
|
|
example_version = int(raw)
|
|
except (TypeError, ValueError):
|
|
example_version = 0
|
|
except Exception:
|
|
return
|
|
|
|
if user_version < example_version:
|
|
logger.warning(
|
|
"Your config.yaml (version %d) is outdated — the latest version is %d. Run `make config-upgrade` to merge new fields into your config.",
|
|
user_version,
|
|
example_version,
|
|
)
|
|
|
|
@classmethod
|
|
def resolve_env_variables(cls, config: Any) -> Any:
|
|
"""Recursively resolve environment variables in the config.
|
|
|
|
Environment variables are resolved using the `os.getenv` function. Example: $OPENAI_API_KEY
|
|
|
|
Args:
|
|
config: The config to resolve environment variables in.
|
|
|
|
Returns:
|
|
The config with environment variables resolved.
|
|
"""
|
|
if isinstance(config, str):
|
|
if config.startswith("$"):
|
|
env_value = os.getenv(config[1:])
|
|
if env_value is None:
|
|
raise ValueError(f"Environment variable {config[1:]} not found for config value {config}")
|
|
return env_value
|
|
return config
|
|
elif isinstance(config, dict):
|
|
return {k: cls.resolve_env_variables(v) for k, v in config.items()}
|
|
elif isinstance(config, list):
|
|
return [cls.resolve_env_variables(item) for item in config]
|
|
return config
|
|
|
|
def get_model_config(self, name: str) -> ModelConfig | None:
|
|
"""Get the model config by name.
|
|
|
|
Args:
|
|
name: The name of the model to get the config for.
|
|
|
|
Returns:
|
|
The model config if found, otherwise None.
|
|
"""
|
|
return next((model for model in self.models if model.name == name), None)
|
|
|
|
def get_tool_config(self, name: str) -> ToolConfig | None:
|
|
"""Get the tool config by name.
|
|
|
|
Args:
|
|
name: The name of the tool to get the config for.
|
|
|
|
Returns:
|
|
The tool config if found, otherwise None.
|
|
"""
|
|
return next((tool for tool in self.tools if tool.name == name), None)
|
|
|
|
def get_tool_group_config(self, name: str) -> ToolGroupConfig | None:
|
|
"""Get the tool group config by name.
|
|
|
|
Args:
|
|
name: The name of the tool group to get the config for.
|
|
|
|
Returns:
|
|
The tool group config if found, otherwise None.
|
|
"""
|
|
return next((group for group in self.tool_groups if group.name == name), None)
|
|
|
|
|
|
_app_config: AppConfig | None = None
|
|
_app_config_path: Path | None = None
|
|
_app_config_mtime: float | None = None
|
|
_app_config_is_custom = False
|
|
_current_app_config: ContextVar[AppConfig | None] = ContextVar("deerflow_current_app_config", default=None)
|
|
_current_app_config_stack: ContextVar[tuple[AppConfig | None, ...]] = ContextVar("deerflow_current_app_config_stack", default=())
|
|
|
|
|
|
def _get_config_mtime(config_path: Path) -> float | None:
|
|
"""Get the modification time of a config file if it exists."""
|
|
try:
|
|
return config_path.stat().st_mtime
|
|
except OSError:
|
|
return None
|
|
|
|
|
|
def _load_and_cache_app_config(config_path: str | None = None) -> AppConfig:
|
|
"""Load config from disk and refresh cache metadata."""
|
|
global _app_config, _app_config_path, _app_config_mtime, _app_config_is_custom
|
|
|
|
resolved_path = AppConfig.resolve_config_path(config_path)
|
|
_app_config = AppConfig.from_file(str(resolved_path))
|
|
_app_config_path = resolved_path
|
|
_app_config_mtime = _get_config_mtime(resolved_path)
|
|
_app_config_is_custom = False
|
|
return _app_config
|
|
|
|
|
|
def get_app_config() -> AppConfig:
|
|
"""Get the DeerFlow config instance.
|
|
|
|
Returns a cached singleton instance and automatically reloads it when the
|
|
underlying config file path or modification time changes. Use
|
|
`reload_app_config()` to force a reload, or `reset_app_config()` to clear
|
|
the cache.
|
|
"""
|
|
global _app_config, _app_config_path, _app_config_mtime
|
|
|
|
runtime_override = _current_app_config.get()
|
|
if runtime_override is not None:
|
|
return runtime_override
|
|
|
|
if _app_config is not None and _app_config_is_custom:
|
|
return _app_config
|
|
|
|
resolved_path = AppConfig.resolve_config_path()
|
|
current_mtime = _get_config_mtime(resolved_path)
|
|
|
|
should_reload = _app_config is None or _app_config_path != resolved_path or _app_config_mtime != current_mtime
|
|
if should_reload:
|
|
if _app_config_path == resolved_path and _app_config_mtime is not None and current_mtime is not None and _app_config_mtime != current_mtime:
|
|
logger.info(
|
|
"Config file has been modified (mtime: %s -> %s), reloading AppConfig",
|
|
_app_config_mtime,
|
|
current_mtime,
|
|
)
|
|
_load_and_cache_app_config(str(resolved_path))
|
|
return _app_config
|
|
|
|
|
|
def reload_app_config(config_path: str | None = None) -> AppConfig:
|
|
"""Reload the config from file and update the cached instance.
|
|
|
|
This is useful when the config file has been modified and you want
|
|
to pick up the changes without restarting the application.
|
|
|
|
Args:
|
|
config_path: Optional path to config file. If not provided,
|
|
uses the default resolution strategy.
|
|
|
|
Returns:
|
|
The newly loaded AppConfig instance.
|
|
"""
|
|
return _load_and_cache_app_config(config_path)
|
|
|
|
|
|
def reset_app_config() -> None:
|
|
"""Reset the cached config instance.
|
|
|
|
This clears the singleton cache, causing the next call to
|
|
`get_app_config()` to reload from file. Useful for testing
|
|
or when switching between different configurations.
|
|
"""
|
|
global _app_config, _app_config_path, _app_config_mtime, _app_config_is_custom
|
|
_app_config = None
|
|
_app_config_path = None
|
|
_app_config_mtime = None
|
|
_app_config_is_custom = False
|
|
|
|
|
|
def set_app_config(config: AppConfig) -> None:
|
|
"""Set a custom config instance.
|
|
|
|
This allows injecting a custom or mock config for testing purposes.
|
|
|
|
Args:
|
|
config: The AppConfig instance to use.
|
|
"""
|
|
global _app_config, _app_config_path, _app_config_mtime, _app_config_is_custom
|
|
_app_config = config
|
|
_app_config_path = None
|
|
_app_config_mtime = None
|
|
_app_config_is_custom = True
|
|
|
|
|
|
def peek_current_app_config() -> AppConfig | None:
|
|
"""Return the runtime-scoped AppConfig override, if one is active."""
|
|
return _current_app_config.get()
|
|
|
|
|
|
def push_current_app_config(config: AppConfig) -> None:
|
|
"""Push a runtime-scoped AppConfig override for the current execution context."""
|
|
stack = _current_app_config_stack.get()
|
|
_current_app_config_stack.set(stack + (_current_app_config.get(),))
|
|
_current_app_config.set(config)
|
|
|
|
|
|
def pop_current_app_config() -> None:
|
|
"""Pop the latest runtime-scoped AppConfig override for the current execution context."""
|
|
stack = _current_app_config_stack.get()
|
|
if not stack:
|
|
_current_app_config.set(None)
|
|
return
|
|
previous = stack[-1]
|
|
_current_app_config_stack.set(stack[:-1])
|
|
_current_app_config.set(previous)
|