mirror of
https://github.com/bytedance/deer-flow.git
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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).
117 lines
4.6 KiB
Python
117 lines
4.6 KiB
Python
import asyncio
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from unittest.mock import AsyncMock, MagicMock
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from app.gateway.routers import suggestions
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def test_strip_markdown_code_fence_removes_wrapping():
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text = '```json\n["a"]\n```'
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assert suggestions._strip_markdown_code_fence(text) == '["a"]'
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def test_strip_markdown_code_fence_no_fence_keeps_content():
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text = ' ["a"] '
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assert suggestions._strip_markdown_code_fence(text) == '["a"]'
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def test_parse_json_string_list_filters_invalid_items():
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text = '```json\n["a", " ", 1, "b"]\n```'
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assert suggestions._parse_json_string_list(text) == ["a", "b"]
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def test_parse_json_string_list_rejects_non_list():
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text = '{"a": 1}'
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assert suggestions._parse_json_string_list(text) is None
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def test_format_conversation_formats_roles():
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messages = [
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suggestions.SuggestionMessage(role="User", content="Hi"),
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suggestions.SuggestionMessage(role="assistant", content="Hello"),
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suggestions.SuggestionMessage(role="system", content="note"),
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]
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assert suggestions._format_conversation(messages) == "User: Hi\nAssistant: Hello\nsystem: note"
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def test_generate_suggestions_parses_and_limits(monkeypatch):
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req = suggestions.SuggestionsRequest(
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messages=[
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suggestions.SuggestionMessage(role="user", content="Hi"),
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suggestions.SuggestionMessage(role="assistant", content="Hello"),
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],
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n=3,
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model_name=None,
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)
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fake_model = MagicMock()
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fake_model.ainvoke = AsyncMock(return_value=MagicMock(content='```json\n["Q1", "Q2", "Q3", "Q4"]\n```'))
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monkeypatch.setattr(suggestions, "create_chat_model", lambda **kwargs: fake_model)
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# Bypass the require_permission decorator (which needs request +
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# thread_store) — these tests cover the parsing logic.
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result = asyncio.run(suggestions.generate_suggestions.__wrapped__("t1", req, request=None))
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assert result.suggestions == ["Q1", "Q2", "Q3"]
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fake_model.ainvoke.assert_awaited_once()
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assert fake_model.ainvoke.await_args.kwargs["config"] == {"run_name": "suggest_agent"}
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def test_generate_suggestions_parses_list_block_content(monkeypatch):
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req = suggestions.SuggestionsRequest(
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messages=[
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suggestions.SuggestionMessage(role="user", content="Hi"),
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suggestions.SuggestionMessage(role="assistant", content="Hello"),
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],
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n=2,
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model_name=None,
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)
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fake_model = MagicMock()
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fake_model.ainvoke = AsyncMock(return_value=MagicMock(content=[{"type": "text", "text": '```json\n["Q1", "Q2"]\n```'}]))
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monkeypatch.setattr(suggestions, "create_chat_model", lambda **kwargs: fake_model)
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# Bypass the require_permission decorator (which needs request +
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# thread_store) — these tests cover the parsing logic.
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result = asyncio.run(suggestions.generate_suggestions.__wrapped__("t1", req, request=None))
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assert result.suggestions == ["Q1", "Q2"]
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fake_model.ainvoke.assert_awaited_once()
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assert fake_model.ainvoke.await_args.kwargs["config"] == {"run_name": "suggest_agent"}
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def test_generate_suggestions_parses_output_text_block_content(monkeypatch):
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req = suggestions.SuggestionsRequest(
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messages=[
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suggestions.SuggestionMessage(role="user", content="Hi"),
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suggestions.SuggestionMessage(role="assistant", content="Hello"),
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],
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n=2,
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model_name=None,
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)
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fake_model = MagicMock()
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fake_model.ainvoke = AsyncMock(return_value=MagicMock(content=[{"type": "output_text", "text": '```json\n["Q1", "Q2"]\n```'}]))
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monkeypatch.setattr(suggestions, "create_chat_model", lambda **kwargs: fake_model)
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# Bypass the require_permission decorator (which needs request +
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# thread_store) — these tests cover the parsing logic.
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result = asyncio.run(suggestions.generate_suggestions.__wrapped__("t1", req, request=None))
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assert result.suggestions == ["Q1", "Q2"]
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fake_model.ainvoke.assert_awaited_once()
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assert fake_model.ainvoke.await_args.kwargs["config"] == {"run_name": "suggest_agent"}
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def test_generate_suggestions_returns_empty_on_model_error(monkeypatch):
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req = suggestions.SuggestionsRequest(
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messages=[suggestions.SuggestionMessage(role="user", content="Hi")],
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n=2,
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model_name=None,
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)
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fake_model = MagicMock()
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fake_model.ainvoke = AsyncMock(side_effect=RuntimeError("boom"))
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monkeypatch.setattr(suggestions, "create_chat_model", lambda **kwargs: fake_model)
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# Bypass the require_permission decorator (which needs request +
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# thread_store) — these tests cover the parsing logic.
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result = asyncio.run(suggestions.generate_suggestions.__wrapped__("t1", req, request=None))
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assert result.suggestions == []
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