greatmengqi
3e6a34297d
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).
56 lines
1.9 KiB
Python
56 lines
1.9 KiB
Python
"""Per-invocation context for DeerFlow agent execution.
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Injected via LangGraph Runtime. Middleware and tools access this
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via Runtime[DeerFlowContext] parameters, through resolve_context().
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"""
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from __future__ import annotations
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import logging
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from dataclasses import dataclass
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from typing import TYPE_CHECKING, Any
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if TYPE_CHECKING:
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from deerflow.config.app_config import AppConfig
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logger = logging.getLogger(__name__)
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@dataclass(frozen=True)
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class DeerFlowContext:
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"""Typed, immutable, per-invocation context injected via LangGraph Runtime.
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Fields are all known at run start and never change during execution.
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Mutable runtime state (e.g. sandbox_id) flows through ThreadState, not here.
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"""
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app_config: AppConfig
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thread_id: str
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agent_name: str | None = None
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def resolve_context(runtime: Any) -> DeerFlowContext:
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"""Return the typed DeerFlowContext that the runtime carries.
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Gateway mode (``DeerFlowClient``, ``run_agent``) always attaches a typed
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``DeerFlowContext`` via ``agent.astream(context=...)``; the LangGraph
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Server path uses ``langgraph.json`` registration where the top-level
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``make_lead_agent`` loads ``AppConfig`` from disk itself, so we still
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arrive here with a typed context.
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Only the dict/None shapes that legacy tests used to exercise would fall
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through this function; we now reject them loudly instead of papering
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over the missing context with an ambient ``AppConfig`` lookup.
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"""
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ctx = getattr(runtime, "context", None)
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if isinstance(ctx, DeerFlowContext):
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return ctx
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raise RuntimeError(
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"resolve_context: runtime.context is not a DeerFlowContext "
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"(got type %s). Every entry point must attach one at invoke time — "
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"Gateway/Client via agent.astream(context=DeerFlowContext(...)), "
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"LangGraph Server via the make_lead_agent boundary that loads "
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"AppConfig.from_file()." % type(ctx).__name__
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)
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