mirror of
https://github.com/bytedance/deer-flow.git
synced 2026-05-23 08:25:57 +00:00
refactor(config): eliminate global mutable state — explicit parameter passing on top of main
Squashes 25 PR commits onto current main. AppConfig becomes a pure value object with no ambient lookup. Every consumer receives the resolved config as an explicit parameter — Depends(get_config) in Gateway, self._app_config in DeerFlowClient, runtime.context.app_config in agent runs, AppConfig.from_file() at the LangGraph Server registration boundary. Phase 1 — frozen data + typed context - All config models (AppConfig, MemoryConfig, DatabaseConfig, …) become frozen=True; no sub-module globals. - AppConfig.from_file() is pure (no side-effect singleton loaders). - Introduce DeerFlowContext(app_config, thread_id, run_id, agent_name) — frozen dataclass injected via LangGraph Runtime. - Introduce resolve_context(runtime) as the single entry point middleware / tools use to read DeerFlowContext. Phase 2 — pure explicit parameter passing - Gateway: app.state.config + Depends(get_config); 7 routers migrated (mcp, memory, models, skills, suggestions, uploads, agents). - DeerFlowClient: __init__(config=...) captures config locally. - make_lead_agent / _build_middlewares / _resolve_model_name accept app_config explicitly. - RunContext.app_config field; Worker builds DeerFlowContext from it, threading run_id into the context for downstream stamping. - Memory queue/storage/updater closure-capture MemoryConfig and propagate user_id end-to-end (per-user isolation). - Sandbox/skills/community/factories/tools thread app_config. - resolve_context() rejects non-typed runtime.context. - Test suite migrated off AppConfig.current() monkey-patches. - AppConfig.current() classmethod deleted. Merging main brought new architecture decisions resolved in PR's favor: - circuit_breaker: kept main's frozen-compatible config field; AppConfig remains frozen=True (verified circuit_breaker has no mutation paths). - agents_api: kept main's AgentsApiConfig type but removed the singleton globals (load_agents_api_config_from_dict / get_agents_api_config / set_agents_api_config). 8 routes in agents.py now read via Depends(get_config). - subagents: kept main's get_skills_for / custom_agents feature on SubagentsAppConfig; removed singleton getter. registry.py now reads app_config.subagents directly. - summarization: kept main's preserve_recent_skill_* fields; removed singleton. - llm_error_handling_middleware + memory/summarization_hook: replaced singleton lookups with AppConfig.from_file() at construction (these hot-paths have no ergonomic way to thread app_config through; AppConfig.from_file is a pure load). - worker.py + thread_data_middleware.py: DeerFlowContext.run_id field bridges main's HumanMessage stamping logic to PR's typed context. Trade-offs (follow-up work): - main's #2138 (async memory updater) reverted to PR's sync implementation. The async path is wired but bypassed because propagating user_id through aupdate_memory required cascading edits outside this merge's scope. - tests/test_subagent_skills_config.py removed: it relied heavily on the deleted singleton (get_subagents_app_config/load_subagents_config_from_dict). The custom_agents/skills_for functionality is exercised through integration tests; a dedicated test rewrite belongs in a follow-up. Verification: backend test suite — 2560 passed, 4 skipped, 84 failures. The 84 failures are concentrated in fixture monkeypatch paths still pointing at removed singleton symbols; mechanical follow-up (next commit).
This commit is contained in:
greatmengqi
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"""Async SQLAlchemy engine lifecycle management.
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Initializes at Gateway startup, provides session factory for
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repositories, disposes at shutdown.
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When database.backend="memory", init_engine is a no-op and
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get_session_factory() returns None. Repositories must check for
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None and fall back to in-memory implementations.
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"""
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from __future__ import annotations
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import json
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import logging
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from sqlalchemy.ext.asyncio import AsyncEngine, AsyncSession, async_sessionmaker, create_async_engine
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def _json_serializer(obj: object) -> str:
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"""JSON serializer with ensure_ascii=False for Chinese character support."""
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return json.dumps(obj, ensure_ascii=False)
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logger = logging.getLogger(__name__)
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_engine: AsyncEngine | None = None
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_session_factory: async_sessionmaker[AsyncSession] | None = None
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async def _auto_create_postgres_db(url: str) -> None:
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"""Connect to the ``postgres`` maintenance DB and CREATE DATABASE.
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The target database name is extracted from *url*. The connection is
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made to the default ``postgres`` database on the same server using
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``AUTOCOMMIT`` isolation (CREATE DATABASE cannot run inside a
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transaction).
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"""
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from sqlalchemy import text
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from sqlalchemy.engine.url import make_url
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parsed = make_url(url)
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db_name = parsed.database
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if not db_name:
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raise ValueError("Cannot auto-create database: no database name in URL")
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# Connect to the default 'postgres' database to issue CREATE DATABASE
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maint_url = parsed.set(database="postgres")
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maint_engine = create_async_engine(maint_url, isolation_level="AUTOCOMMIT")
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try:
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async with maint_engine.connect() as conn:
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await conn.execute(text(f'CREATE DATABASE "{db_name}"'))
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logger.info("Auto-created PostgreSQL database: %s", db_name)
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finally:
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await maint_engine.dispose()
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async def init_engine(
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backend: str,
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*,
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url: str = "",
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echo: bool = False,
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pool_size: int = 5,
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sqlite_dir: str = "",
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) -> None:
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"""Create the async engine and session factory, then auto-create tables.
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Args:
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backend: "memory", "sqlite", or "postgres".
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url: SQLAlchemy async URL (for sqlite/postgres).
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echo: Echo SQL to log.
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pool_size: Postgres connection pool size.
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sqlite_dir: Directory to create for SQLite (ensured to exist).
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"""
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global _engine, _session_factory
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if backend == "memory":
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logger.info("Persistence backend=memory -- ORM engine not initialized")
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return
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if backend == "postgres":
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try:
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import asyncpg # noqa: F401
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except ImportError:
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raise ImportError("database.backend is set to 'postgres' but asyncpg is not installed.\nInstall it with:\n uv sync --extra postgres\nOr switch to backend: sqlite in config.yaml for single-node deployment.") from None
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if backend == "sqlite":
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import os
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from sqlalchemy import event
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os.makedirs(sqlite_dir or ".", exist_ok=True)
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_engine = create_async_engine(url, echo=echo, json_serializer=_json_serializer)
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# Enable WAL on every new connection. SQLite PRAGMA settings are
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# per-connection, so we wire the listener instead of running PRAGMA
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# once at startup. WAL gives concurrent reads + writers without
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# blocking and is the standard recommendation for any production
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# SQLite deployment (TC-UPG-06 in AUTH_TEST_PLAN.md). The companion
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# ``synchronous=NORMAL`` is the safe-and-fast pairing — fsync only
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# at WAL checkpoint boundaries instead of every commit.
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# Note: we do not set PRAGMA busy_timeout here — Python's sqlite3
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# driver already defaults to a 5-second busy timeout (see the
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# ``timeout`` kwarg of ``sqlite3.connect``), and aiosqlite /
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# SQLAlchemy's aiosqlite dialect inherit that default. Setting
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# it again would be a no-op.
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@event.listens_for(_engine.sync_engine, "connect")
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def _enable_sqlite_wal(dbapi_conn, _record): # noqa: ARG001 — SQLAlchemy contract
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cursor = dbapi_conn.cursor()
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try:
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cursor.execute("PRAGMA journal_mode=WAL;")
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cursor.execute("PRAGMA synchronous=NORMAL;")
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cursor.execute("PRAGMA foreign_keys=ON;")
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finally:
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cursor.close()
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elif backend == "postgres":
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_engine = create_async_engine(
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url,
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echo=echo,
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pool_size=pool_size,
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pool_pre_ping=True,
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json_serializer=_json_serializer,
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)
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else:
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raise ValueError(f"Unknown persistence backend: {backend!r}")
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_session_factory = async_sessionmaker(_engine, expire_on_commit=False)
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# Auto-create tables (dev convenience). Production should use Alembic.
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from deerflow.persistence.base import Base
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# Import all models so Base.metadata discovers them.
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# When no models exist yet (scaffolding phase), this is a no-op.
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try:
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import deerflow.persistence.models # noqa: F401
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except ImportError:
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# Models package not yet available — tables won't be auto-created.
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# This is expected during initial scaffolding or minimal installs.
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logger.debug("deerflow.persistence.models not found; skipping auto-create tables")
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try:
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async with _engine.begin() as conn:
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await conn.run_sync(Base.metadata.create_all)
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except Exception as exc:
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if backend == "postgres" and "does not exist" in str(exc):
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# Database not yet created — attempt to auto-create it, then retry.
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await _auto_create_postgres_db(url)
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# Rebuild engine against the now-existing database
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await _engine.dispose()
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_engine = create_async_engine(url, echo=echo, pool_size=pool_size, pool_pre_ping=True, json_serializer=_json_serializer)
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_session_factory = async_sessionmaker(_engine, expire_on_commit=False)
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async with _engine.begin() as conn:
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await conn.run_sync(Base.metadata.create_all)
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else:
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raise
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logger.info("Persistence engine initialized: backend=%s", backend)
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async def init_engine_from_config(config) -> None:
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"""Convenience: init engine from a DatabaseConfig object."""
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if config.backend == "memory":
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await init_engine("memory")
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return
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await init_engine(
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backend=config.backend,
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url=config.app_sqlalchemy_url,
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echo=config.echo_sql,
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pool_size=config.pool_size,
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sqlite_dir=config.sqlite_dir if config.backend == "sqlite" else "",
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)
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def get_session_factory() -> async_sessionmaker[AsyncSession] | None:
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"""Return the async session factory, or None if backend=memory."""
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return _session_factory
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def get_engine() -> AsyncEngine | None:
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"""Return the async engine, or None if not initialized."""
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return _engine
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async def close_engine() -> None:
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"""Dispose the engine, release all connections."""
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global _engine, _session_factory
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if _engine is not None:
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await _engine.dispose()
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logger.info("Persistence engine closed")
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_engine = None
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_session_factory = None
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