mirror of
https://github.com/jxxghp/MoviePilot.git
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547 lines
18 KiB
Python
547 lines
18 KiB
Python
"""Agent 图缓存行为测试。"""
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from contextlib import ExitStack
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from datetime import datetime, timedelta
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from types import SimpleNamespace
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from unittest.mock import AsyncMock, patch
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import pytest
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from langchain_core.messages import AIMessage, HumanMessage
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from app.agent import MoviePilotAgent, ReplyMode, _CompiledAgentBundle
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from app.agent.mcp import AgentMcpToolSpec
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from app.agent.middleware.policy import AgentPolicyMiddleware
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from app.agent.tools.catalog import (
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ToolCatalogSnapshot,
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ToolIdentityAmbiguousError,
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)
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from app.agent.tools.impl.mcp import create_external_mcp_tools
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from app.core.config import settings
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from app.schemas.agent import AgentMcpServerConfig
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@pytest.fixture
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def anyio_backend():
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"""使用 asyncio 后端运行 anyio 异步测试。"""
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return "asyncio"
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class _FakeGraphState:
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"""提供 LangGraph get_state 测试替身。"""
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def __init__(self, messages):
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"""保存测试消息状态。"""
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self.values = {"messages": messages}
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class _CapturingAgent:
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"""捕获传入消息的非流式 Agent 测试替身。"""
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def __init__(self):
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"""初始化捕获容器。"""
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self.payload = None
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async def ainvoke(self, payload, config=None):
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"""记录 Agent 调用输入。"""
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self.payload = payload
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def get_state(self, _config):
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"""返回包含最终 AI 回复的图状态。"""
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return _FakeGraphState([AIMessage(content="ok")])
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@pytest.mark.anyio
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async def test_create_agent_reuses_cached_graph_when_signature_matches():
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"""构造签名一致时应直接复用已编译 Agent 图。"""
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cached_graph = object()
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catalog = ToolCatalogSnapshot.from_tools(
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[], plugin_revision=0, factory_revision="factory-v1"
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)
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agent = MoviePilotAgent(session_id="cache-hit", user_id="user-1")
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agent._compiled_agent_bundle = _CompiledAgentBundle(
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signature=("sig",),
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agent=cached_graph,
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streaming=False,
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created_at=datetime.now(),
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tool_catalog=catalog,
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subagent_catalog=catalog,
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plugin_revision=0,
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mcp_config_signature="mcp-config",
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catalog_checked_at=datetime.now(),
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)
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with patch.object(
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agent,
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"_agent_bundle_signature",
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new=AsyncMock(return_value=("sig",)),
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), patch(
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"app.agent.PluginManager.get_plugin_agent_tools_revision",
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return_value=0,
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), patch(
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"app.agent.agent_mcp_manager.config_signature",
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return_value="mcp-config",
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), patch("app.agent.create_agent") as create_agent:
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graph = await agent._create_agent(streaming=False)
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assert graph is cached_graph
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assert agent._last_agent_cache_hit is True
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create_agent.assert_not_called()
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@pytest.mark.anyio
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async def test_fresh_catalog_cache_hit_skips_tool_and_mcp_discovery() -> None:
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"""目录仍在 freshness 窗口内时，缓存命中不得重建工具或访问 MCP。"""
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cached_graph = object()
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catalog = ToolCatalogSnapshot.from_tools(
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[], plugin_revision=0, factory_revision="factory-v1"
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)
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agent = MoviePilotAgent(session_id="catalog-cache-hit", user_id="user-1")
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agent._compiled_agent_bundle = _CompiledAgentBundle(
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signature=("sig",),
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agent=cached_graph,
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streaming=False,
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created_at=datetime.now(),
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tool_catalog=catalog,
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subagent_catalog=catalog,
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plugin_revision=0,
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mcp_config_signature="mcp-config",
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catalog_checked_at=datetime.now(),
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)
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with patch.object(
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agent,
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"_agent_bundle_signature",
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new=AsyncMock(return_value=("sig",)),
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), patch.object(
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agent,
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"_initialize_local_tool_catalogs",
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side_effect=AssertionError("tool catalog rebuilt"),
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), patch(
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"app.agent.PluginManager.get_plugin_agent_tools_revision",
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return_value=0,
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), patch(
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"app.agent.agent_mcp_manager.config_signature",
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return_value="mcp-config",
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), patch(
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"app.agent.agent_mcp_manager.list_enabled_tool_specs",
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new=AsyncMock(side_effect=AssertionError("MCP discovery called")),
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):
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graph = await agent._create_agent(streaming=False)
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assert graph is cached_graph
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assert agent._last_agent_cache_hit is True
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@pytest.mark.anyio
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async def test_expired_unchanged_catalog_renews_freshness() -> None:
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"""过期目录复核后若签名未变，应续期缓存而不是每轮重复 discovery。"""
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cached_graph = object()
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catalog = ToolCatalogSnapshot.from_tools(
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[], plugin_revision=0, factory_revision="factory-v1"
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)
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expired_at = datetime.now() - timedelta(minutes=5)
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agent = MoviePilotAgent(session_id="catalog-refresh", user_id="user-1")
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agent._compiled_agent_bundle = _CompiledAgentBundle(
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signature=("sig",),
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agent=cached_graph,
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streaming=False,
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created_at=datetime.now(),
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tool_catalog=catalog,
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subagent_catalog=catalog,
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plugin_revision=0,
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mcp_config_signature="mcp-config",
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catalog_checked_at=expired_at,
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)
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fake_llm = SimpleNamespace(
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_llm_type="openai-chat",
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model="fake",
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profile={"max_input_tokens": 64000},
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)
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with patch.object(
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agent,
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"_agent_bundle_signature",
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new=AsyncMock(return_value=("sig",)),
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), patch.object(
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agent,
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"_initialize_local_tool_catalogs",
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return_value=(catalog, catalog),
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), patch.object(
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agent,
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"_initialize_mcp_tools",
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new=AsyncMock(return_value=[]),
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), patch.object(
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agent,
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"_initialize_subagent_mcp_tools",
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new=AsyncMock(return_value=[]),
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), patch.object(
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agent,
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"_initialize_llm",
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new=AsyncMock(return_value=fake_llm),
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), patch.object(
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agent,
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"_sync_model_profile",
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), patch(
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"app.agent.ServerToolRegistry.resolve_web_search",
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return_value=SimpleNamespace(use_local_web_search=True),
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), patch(
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"app.agent.LLMHelper.get_server_tools",
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return_value=[],
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), patch(
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"app.agent.prompt_manager.get_agent_prompt",
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return_value="prompt",
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), patch(
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"app.agent.SkillsMiddleware",
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return_value=SimpleNamespace(name="skills", tools=[]),
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), patch(
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"app.agent.create_subagent_middlewares",
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return_value=([], []),
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), patch(
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"app.agent.PluginManager.get_plugin_agent_tools_revision",
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return_value=0,
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), patch(
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"app.agent.agent_mcp_manager.config_signature",
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return_value="mcp-config",
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), patch(
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"app.agent.agent_mcp_manager.list_enabled_tool_specs",
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new=AsyncMock(return_value=[]),
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):
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graph = await agent._create_agent(streaming=False)
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assert graph is cached_graph
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assert agent._compiled_agent_bundle.catalog_checked_at > expired_at
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@pytest.mark.anyio
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async def test_agent_bundle_signature_changes_with_temperature(monkeypatch) -> None:
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"""温度配置变化时应使会话内 Agent 图缓存失效。"""
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agent = MoviePilotAgent(session_id="temperature-change", user_id="user-1")
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runtime_config = {
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"provider": "openai",
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"model": "gpt-test",
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"api_key": "test-key",
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"base_url": "https://llm.example.com/v1",
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"base_url_preset": None,
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"user_agent": None,
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"use_proxy": False,
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"thinking_level": "off",
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"api_protocol": "auto",
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}
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with patch.object(
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agent,
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"_resolve_llm_runtime_config",
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new=AsyncMock(return_value=runtime_config),
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):
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monkeypatch.setattr(settings, "LLM_TEMPERATURE", 0.3)
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initial_signature = await agent._agent_bundle_signature(streaming=False)
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monkeypatch.setattr(settings, "LLM_TEMPERATURE", 1.0)
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updated_signature = await agent._agent_bundle_signature(streaming=False)
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assert updated_signature != initial_signature
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@pytest.mark.anyio
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async def test_agent_bundle_signature_changes_with_context_cap(monkeypatch) -> None:
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"""有效窗口配置变化时应使会话内 Agent 图缓存失效。"""
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agent = MoviePilotAgent(session_id="context-cap-change", user_id="user-1")
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runtime_config = {
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"provider": "openai",
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"model": "gpt-test",
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"api_key": "test-key",
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"base_url": "https://llm.example.com/v1",
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}
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with patch.object(
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agent,
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"_resolve_llm_runtime_config",
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new=AsyncMock(return_value=runtime_config),
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):
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monkeypatch.setattr(settings, "LLM_MAX_CONTEXT_TOKENS", 32)
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initial_signature = await agent._agent_bundle_signature(streaming=False)
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monkeypatch.setattr(settings, "LLM_MAX_CONTEXT_TOKENS", 64)
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updated_signature = await agent._agent_bundle_signature(streaming=False)
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assert updated_signature != initial_signature
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@pytest.mark.anyio
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async def test_agent_bundle_signature_changes_with_tool_catalog() -> None:
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"""工具目录 revision 必须参与会话内 Agent 图缓存签名。"""
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agent = MoviePilotAgent(session_id="tool-revision", user_id="user-1")
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runtime_config = {"provider": "openai", "model": "gpt-test"}
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first_catalog = ToolCatalogSnapshot.from_tools(
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[], plugin_revision=1, factory_revision="factory-v1"
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)
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second_catalog = ToolCatalogSnapshot.from_tools(
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[], plugin_revision=2, factory_revision="factory-v1"
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)
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with patch.object(
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agent,
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"_resolve_llm_runtime_config",
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new=AsyncMock(return_value=runtime_config),
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):
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first_signature = await agent._agent_bundle_signature(
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streaming=False,
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tool_catalog=first_catalog,
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subagent_catalog=first_catalog,
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)
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second_signature = await agent._agent_bundle_signature(
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streaming=False,
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tool_catalog=second_catalog,
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subagent_catalog=second_catalog,
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)
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assert second_signature != first_signature
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@pytest.mark.anyio
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@pytest.mark.parametrize("max_tools", [0, 5])
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async def test_graph_keeps_mcp_first_winner_and_catalogs_all_collisions(
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max_tools: int,
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) -> None:
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"""主图与子图保持 MCP first-wins，严格目录覆盖全部客户端工具。"""
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servers = [
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AgentMcpServerConfig(
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id=server_id,
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name="Shared Name",
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transport="stdio",
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command=server_id,
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)
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for server_id in ("one", "two")
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]
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specs = [
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AgentMcpToolSpec(
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server=server,
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name="echo",
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agent_tool_name="shared_echo",
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description="echo",
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input_schema={"type": "object", "properties": {}},
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)
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for server in servers
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]
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main_tools = await create_external_mcp_tools(
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session_id="session",
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user_id="user",
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specs=specs,
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)
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subagent_tools = await create_external_mcp_tools(
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session_id="session",
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user_id="user",
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specs=specs,
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)
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empty_catalog = ToolCatalogSnapshot.from_tools(
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[], plugin_revision=0, factory_revision="factory-v1"
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)
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fake_llm = SimpleNamespace(
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_llm_type="openai-chat",
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model="fake",
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profile={"max_input_tokens": 64000},
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)
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skill_tool = SimpleNamespace(
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name="shared_echo",
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description="skill collision",
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args_schema={"type": "object", "properties": {}},
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_agent_tool_source="middleware:skills",
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)
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activity_tool = SimpleNamespace(
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name="query_activity_log",
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description="activity log",
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args_schema={"type": "object", "properties": {}},
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_agent_tool_source="middleware:activity_log",
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)
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subagent_task_tool = SimpleNamespace(
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name="task",
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description="subagent task",
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args_schema={"type": "object", "properties": {}},
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_agent_tool_source="middleware:subagents",
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)
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captured = {}
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agent = MoviePilotAgent(
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session_id="mcp-collision",
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user_id="user",
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channel="web",
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source="test",
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)
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def _capture_subagents(**kwargs):
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captured["subagent_tools"] = kwargs["tools"]
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captured["subagent_catalog"] = kwargs["catalog"]
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return [], [subagent_task_tool]
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def _capture_selector(**kwargs):
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captured["selection_tools"] = kwargs["selection_tools"]
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return SimpleNamespace(name="selector")
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def _capture_agent(**kwargs):
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captured["agent_tools"] = kwargs["tools"]
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captured["middlewares"] = kwargs["middleware"]
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return object()
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patchers = [
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patch.object(
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agent,
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"_resolve_llm_runtime_config",
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new=AsyncMock(return_value={"provider": "openai", "model": "fake"}),
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),
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patch.object(
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agent,
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"_initialize_local_tool_catalogs",
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return_value=(empty_catalog, empty_catalog),
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),
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patch.object(
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agent,
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"_initialize_mcp_tools",
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new=AsyncMock(return_value=main_tools),
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),
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patch.object(
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agent,
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"_initialize_subagent_mcp_tools",
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new=AsyncMock(return_value=subagent_tools),
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),
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patch.object(
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agent,
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"_agent_bundle_signature",
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new=AsyncMock(return_value=("mcp-collision", max_tools)),
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),
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patch.object(
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agent,
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"_initialize_llm",
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new=AsyncMock(return_value=fake_llm),
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),
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patch.object(agent, "_sync_model_profile"),
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patch(
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"app.agent.PluginManager.get_plugin_agent_tools_revision",
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return_value=0,
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),
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patch(
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"app.agent.agent_mcp_manager.config_signature",
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return_value="mcp-config",
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),
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patch(
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"app.agent.agent_mcp_manager.list_enabled_tool_specs",
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new=AsyncMock(return_value=specs),
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),
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patch(
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"app.agent.ServerToolRegistry.resolve_web_search",
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return_value=SimpleNamespace(use_local_web_search=True),
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),
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patch("app.agent.LLMHelper.get_server_tools", return_value=[]),
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patch("app.agent.prompt_manager.get_agent_prompt", return_value="prompt"),
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patch(
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"app.agent.create_subagent_middlewares",
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side_effect=_capture_subagents,
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),
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patch(
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"app.agent.MoviePilotToolFactory.get_tool_selector_always_include_names",
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return_value=[],
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),
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patch(
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"app.agent.SkillsMiddleware",
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return_value=SimpleNamespace(name="skills", tools=[skill_tool]),
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),
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patch(
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"app.agent.ActivityLogMiddleware",
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return_value=SimpleNamespace(name="activity", tools=[activity_tool]),
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),
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patch(
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"app.agent.JobsMiddleware",
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return_value=SimpleNamespace(name="jobs"),
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),
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||
patch(
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"app.agent.RuntimeConfigMiddleware",
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return_value=SimpleNamespace(name="runtime"),
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),
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patch(
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"app.agent.MemoryMiddleware",
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return_value=SimpleNamespace(name="memory"),
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),
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patch(
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"app.agent.SummarizationMiddleware",
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||
return_value=SimpleNamespace(name="summary"),
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||
),
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patch(
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"app.agent.PatchToolCallsMiddleware",
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||
return_value=SimpleNamespace(name="patch"),
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),
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patch(
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"app.agent.UsageMiddleware",
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return_value=SimpleNamespace(name="usage"),
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),
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patch(
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"app.agent.ToolSelectorMiddleware",
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side_effect=_capture_selector,
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),
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patch("app.agent.InMemorySaver", return_value=object()),
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patch("app.agent.create_agent", side_effect=_capture_agent),
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patch.object(settings, "LLM_MAX_TOOLS", max_tools),
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]
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with ExitStack() as stack:
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for patcher in patchers:
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stack.enter_context(patcher)
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await agent._create_agent(streaming=False)
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assert captured["agent_tools"] == [main_tools[0], skill_tool, activity_tool]
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assert captured["subagent_tools"] == [subagent_tools[0]]
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if max_tools:
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assert captured["selection_tools"] == [
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main_tools[0],
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skill_tool,
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activity_tool,
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subagent_task_tool,
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]
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assert captured["middlewares"][-3].name == "selector"
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else:
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assert "selection_tools" not in captured
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assert captured["middlewares"][-2].name == "FinalRequestCompactionMiddleware"
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assert captured["middlewares"][-1].name == "usage"
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policy_middleware = next(
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middleware
|
||
for middleware in captured["middlewares"]
|
||
if isinstance(middleware, AgentPolicyMiddleware)
|
||
)
|
||
assert [
|
||
entry.source
|
||
for entry in policy_middleware.catalog.collisions["shared_echo"]
|
||
] == ["mcp:one", "mcp:two", "middleware:skills"]
|
||
assert (
|
||
policy_middleware.catalog.resolve_unique("query_activity_log").tool
|
||
is activity_tool
|
||
)
|
||
assert policy_middleware.catalog.resolve_unique("task").tool is subagent_task_tool
|
||
with pytest.raises(ToolIdentityAmbiguousError, match="TOOL_IDENTITY_AMBIGUOUS"):
|
||
policy_middleware.catalog.resolve_unique("shared_echo")
|
||
assert [
|
||
entry.source
|
||
for entry in captured["subagent_catalog"].collisions["shared_echo"]
|
||
] == ["mcp:one", "mcp:two"]
|
||
|
||
|
||
@pytest.mark.anyio
|
||
async def test_execute_agent_sends_only_latest_message_on_cache_hit():
|
||
"""缓存命中时只把本轮新消息交给 LangGraph，避免重复提交历史。"""
|
||
fake_graph = _CapturingAgent()
|
||
agent = MoviePilotAgent(session_id="cache-hit", user_id="user-1")
|
||
agent.reply_mode = ReplyMode.CAPTURE_ONLY
|
||
agent._tool_context = {"user_reply_sent": False}
|
||
agent._streamed_output = ""
|
||
agent._should_stream = lambda: False
|
||
agent.stream_handler = SimpleNamespace(
|
||
stop_streaming=AsyncMock(return_value=(False, ""))
|
||
)
|
||
|
||
async def _create_agent(streaming=False):
|
||
"""模拟缓存命中后的 Agent 创建结果。"""
|
||
agent._last_agent_cache_hit = True
|
||
return fake_graph
|
||
|
||
agent._create_agent = _create_agent
|
||
messages = [HumanMessage(content="上一轮"), HumanMessage(content="本轮")]
|
||
|
||
with patch("app.agent.eventmanager.send_event"):
|
||
await agent._execute_agent(messages)
|
||
|
||
assert agent._streamed_output == "ok"
|
||
assert fake_graph.payload["messages"] == [messages[-1]]
|