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https://github.com/bytedance/deer-flow.git
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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).
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@@ -11,10 +11,11 @@ import asyncio
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import logging
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import uuid
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from fastapi import APIRouter, Request
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from fastapi import APIRouter, HTTPException, Query, Request
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from fastapi.responses import StreamingResponse
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from app.gateway.deps import get_checkpointer, get_run_manager, get_stream_bridge
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from app.gateway.authz import require_permission
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from app.gateway.deps import get_checkpointer, get_feedback_repo, get_run_event_store, get_run_manager, get_run_store, get_stream_bridge
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from app.gateway.routers.thread_runs import RunCreateRequest
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from app.gateway.services import sse_consumer, start_run
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from deerflow.runtime import serialize_channel_values
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@@ -85,3 +86,57 @@ async def stateless_wait(body: RunCreateRequest, request: Request) -> dict:
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logger.exception("Failed to fetch final state for run %s", record.run_id)
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return {"status": record.status.value, "error": record.error}
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# ---------------------------------------------------------------------------
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# Run-scoped read endpoints
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# ---------------------------------------------------------------------------
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async def _resolve_run(run_id: str, request: Request) -> dict:
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"""Fetch run by run_id with user ownership check. Raises 404 if not found."""
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run_store = get_run_store(request)
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record = await run_store.get(run_id) # user_id=AUTO filters by contextvar
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if record is None:
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raise HTTPException(status_code=404, detail=f"Run {run_id} not found")
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return record
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@router.get("/{run_id}/messages")
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@require_permission("runs", "read")
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async def run_messages(
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run_id: str,
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request: Request,
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limit: int = Query(default=50, le=200, ge=1),
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before_seq: int | None = Query(default=None),
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after_seq: int | None = Query(default=None),
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) -> dict:
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"""Return paginated messages for a run (cursor-based).
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Pagination:
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- after_seq: messages with seq > after_seq (forward)
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- before_seq: messages with seq < before_seq (backward)
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- neither: latest messages
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Response: { data: [...], has_more: bool }
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"""
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run = await _resolve_run(run_id, request)
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event_store = get_run_event_store(request)
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rows = await event_store.list_messages_by_run(
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run["thread_id"], run_id,
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limit=limit + 1,
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before_seq=before_seq,
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after_seq=after_seq,
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)
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has_more = len(rows) > limit
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data = rows[:limit] if has_more else rows
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return {"data": data, "has_more": has_more}
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@router.get("/{run_id}/feedback")
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@require_permission("runs", "read")
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async def run_feedback(run_id: str, request: Request) -> list[dict]:
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"""Return all feedback for a run."""
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run = await _resolve_run(run_id, request)
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feedback_repo = get_feedback_repo(request)
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return await feedback_repo.list_by_run(run["thread_id"], run_id)
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