Files
deer-flow/backend/packages/harness/deerflow/runtime/checkpointer/async_provider.py
T
greatmengqi 3e6a34297d 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).
2026-04-26 21:45:02 +08:00

158 lines
5.2 KiB
Python

"""Async checkpointer factory.
Provides an **async context manager** for long-running async servers that need
proper resource cleanup.
Supported backends: memory, sqlite, postgres.
Usage (e.g. FastAPI lifespan)::
from deerflow.runtime.checkpointer.async_provider import make_checkpointer
async with make_checkpointer() as checkpointer:
app.state.checkpointer = checkpointer # InMemorySaver if not configured
For sync usage see :mod:`deerflow.runtime.checkpointer.provider`.
"""
from __future__ import annotations
import asyncio
import contextlib
import logging
from collections.abc import AsyncIterator
from langgraph.types import Checkpointer
from deerflow.config.app_config import AppConfig
from deerflow.runtime.checkpointer.provider import (
POSTGRES_CONN_REQUIRED,
POSTGRES_INSTALL,
SQLITE_INSTALL,
)
from deerflow.runtime.store._sqlite_utils import ensure_sqlite_parent_dir, resolve_sqlite_conn_str
logger = logging.getLogger(__name__)
# ---------------------------------------------------------------------------
# Async factory
# ---------------------------------------------------------------------------
@contextlib.asynccontextmanager
async def _async_checkpointer(config) -> AsyncIterator[Checkpointer]:
"""Async context manager that constructs and tears down a checkpointer."""
if config.type == "memory":
from langgraph.checkpoint.memory import InMemorySaver
yield InMemorySaver()
return
if config.type == "sqlite":
try:
from langgraph.checkpoint.sqlite.aio import AsyncSqliteSaver
except ImportError as exc:
raise ImportError(SQLITE_INSTALL) from exc
conn_str = resolve_sqlite_conn_str(config.connection_string or "store.db")
await asyncio.to_thread(ensure_sqlite_parent_dir, conn_str)
async with AsyncSqliteSaver.from_conn_string(conn_str) as saver:
await saver.setup()
yield saver
return
if config.type == "postgres":
try:
from langgraph.checkpoint.postgres.aio import AsyncPostgresSaver
except ImportError as exc:
raise ImportError(POSTGRES_INSTALL) from exc
if not config.connection_string:
raise ValueError(POSTGRES_CONN_REQUIRED)
async with AsyncPostgresSaver.from_conn_string(config.connection_string) as saver:
await saver.setup()
yield saver
return
raise ValueError(f"Unknown checkpointer type: {config.type!r}")
# ---------------------------------------------------------------------------
# Public async context manager
# ---------------------------------------------------------------------------
@contextlib.asynccontextmanager
async def _async_checkpointer_from_database(db_config) -> AsyncIterator[Checkpointer]:
"""Async context manager that constructs a checkpointer from unified DatabaseConfig."""
if db_config.backend == "memory":
from langgraph.checkpoint.memory import InMemorySaver
yield InMemorySaver()
return
if db_config.backend == "sqlite":
try:
from langgraph.checkpoint.sqlite.aio import AsyncSqliteSaver
except ImportError as exc:
raise ImportError(SQLITE_INSTALL) from exc
conn_str = db_config.checkpointer_sqlite_path
ensure_sqlite_parent_dir(conn_str)
async with AsyncSqliteSaver.from_conn_string(conn_str) as saver:
await saver.setup()
yield saver
return
if db_config.backend == "postgres":
try:
from langgraph.checkpoint.postgres.aio import AsyncPostgresSaver
except ImportError as exc:
raise ImportError(POSTGRES_INSTALL) from exc
if not db_config.postgres_url:
raise ValueError("database.postgres_url is required for the postgres backend")
async with AsyncPostgresSaver.from_conn_string(db_config.postgres_url) as saver:
await saver.setup()
yield saver
return
raise ValueError(f"Unknown database backend: {db_config.backend!r}")
@contextlib.asynccontextmanager
async def make_checkpointer(app_config: AppConfig) -> AsyncIterator[Checkpointer]:
"""Async context manager that yields a checkpointer for the caller's lifetime.
Resources are opened on enter and closed on exit -- no global state::
async with make_checkpointer(app_config) as checkpointer:
app.state.checkpointer = checkpointer
Yields an ``InMemorySaver`` when no checkpointer is configured in *config.yaml*.
Priority:
1. Legacy ``checkpointer:`` config section (backward compatible)
2. Unified ``database:`` config section
3. Default InMemorySaver
"""
# Legacy: standalone checkpointer config takes precedence
if app_config.checkpointer is not None:
async with _async_checkpointer(app_config.checkpointer) as saver:
yield saver
return
# Unified database config
db_config = getattr(app_config, "database", None)
if db_config is not None and db_config.backend != "memory":
async with _async_checkpointer_from_database(db_config) as saver:
yield saver
return
# Default: in-memory
from langgraph.checkpoint.memory import InMemorySaver
yield InMemorySaver()