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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).
62 lines
2.2 KiB
Python
62 lines
2.2 KiB
Python
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# --- Phase 2 config-refactor test helper ---
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# Memory APIs now take MemoryConfig / AppConfig explicitly. Tests construct a
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# minimal config once and reuse it across call sites.
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from deerflow.config.app_config import AppConfig as _TestAppConfig
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from deerflow.config.memory_config import MemoryConfig as _TestMemoryConfig
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from deerflow.config.sandbox_config import SandboxConfig as _TestSandboxConfig
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_TEST_MEMORY_CONFIG = _TestMemoryConfig(enabled=True)
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_TEST_APP_CONFIG = _TestAppConfig(sandbox=_TestSandboxConfig(use="test"), memory=_TEST_MEMORY_CONFIG)
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# -------------------------------------------
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"""Tests for user_id propagation through memory queue."""
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from unittest.mock import MagicMock, patch
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import pytest
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from deerflow.agents.memory.queue import ConversationContext, MemoryUpdateQueue
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from deerflow.config.app_config import AppConfig
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from deerflow.config.memory_config import MemoryConfig
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@pytest.fixture(autouse=True)
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def _enable_memory(monkeypatch):
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"""Ensure MemoryUpdateQueue.add() doesn't early-return on disabled memory."""
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config = MagicMock(spec=AppConfig)
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config.memory = MemoryConfig(enabled=True)
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def test_conversation_context_has_user_id():
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ctx = ConversationContext(thread_id="t1", messages=[], user_id="alice")
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assert ctx.user_id == "alice"
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def test_conversation_context_user_id_default_none():
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ctx = ConversationContext(thread_id="t1", messages=[])
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assert ctx.user_id is None
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def test_queue_add_stores_user_id():
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q = MemoryUpdateQueue(_TEST_APP_CONFIG)
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with patch.object(q, "_reset_timer"):
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q.add(thread_id="t1", messages=["msg"], user_id="alice")
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assert len(q._queue) == 1
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assert q._queue[0].user_id == "alice"
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q.clear()
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def test_queue_process_passes_user_id_to_updater():
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q = MemoryUpdateQueue(_TEST_APP_CONFIG)
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with patch.object(q, "_reset_timer"):
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q.add(thread_id="t1", messages=["msg"], user_id="alice")
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mock_updater = MagicMock()
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mock_updater.update_memory.return_value = True
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with patch("deerflow.agents.memory.updater.MemoryUpdater", return_value=mock_updater):
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q._process_queue()
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mock_updater.update_memory.assert_called_once()
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call_kwargs = mock_updater.update_memory.call_args.kwargs
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assert call_kwargs["user_id"] == "alice"
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