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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).
41 lines
1.3 KiB
Python
41 lines
1.3 KiB
Python
"""SQLAlchemy declarative base with automatic to_dict support.
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All DeerFlow ORM models inherit from this Base. It provides a generic
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to_dict() method via SQLAlchemy's inspect() so individual models don't
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need to write their own serialization logic.
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LangGraph's checkpointer tables are NOT managed by this Base.
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"""
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from __future__ import annotations
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from sqlalchemy import inspect as sa_inspect
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from sqlalchemy.orm import DeclarativeBase
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class Base(DeclarativeBase):
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"""Base class for all DeerFlow ORM models.
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Provides:
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- Automatic to_dict() via SQLAlchemy column inspection.
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- Standard __repr__() showing all column values.
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"""
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def to_dict(self, *, exclude: set[str] | None = None) -> dict:
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"""Convert ORM instance to plain dict.
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Uses SQLAlchemy's inspect() to iterate mapped column attributes.
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Args:
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exclude: Optional set of column keys to omit.
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Returns:
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Dict of {column_key: value} for all mapped columns.
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"""
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exclude = exclude or set()
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return {c.key: getattr(self, c.key) for c in sa_inspect(type(self)).mapper.column_attrs if c.key not in exclude}
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def __repr__(self) -> str:
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cols = ", ".join(f"{c.key}={getattr(self, c.key)!r}" for c in sa_inspect(type(self)).mapper.column_attrs)
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return f"{type(self).__name__}({cols})"
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