Files
MoviePilot/tests/test_agent_graph_cache.py
T

632 lines
22 KiB
Python

"""Agent 图缓存行为测试。"""
from contextlib import ExitStack
from datetime import datetime, timedelta
from types import SimpleNamespace
from unittest.mock import AsyncMock, patch
import pytest
from langchain_core.messages import AIMessage, HumanMessage
from app.agent.contracts import ReplyMode
from app.agent.mcp import AgentMcpToolSpec
from app.agent.middleware.policy import AgentPolicyMiddleware
from app.agent.orchestrator import MoviePilotAgent, _CompiledAgentBundle
from app.agent.tools.catalog import (
ToolCatalogSnapshot,
ToolIdentityAmbiguousError,
)
from app.agent.tools.impl.mcp import create_external_mcp_tools
from app.runtime.config import settings
from app.schemas.agent import AgentMcpServerConfig
@pytest.fixture
def anyio_backend():
"""使用 asyncio 后端运行 anyio 异步测试。"""
return "asyncio"
class _FakeGraphState:
"""提供 LangGraph get_state 测试替身。"""
def __init__(self, messages):
"""保存测试消息状态。"""
self.values = {"messages": messages}
class _CapturingAgent:
"""捕获传入消息的非流式 Agent 测试替身。"""
def __init__(self):
"""初始化捕获容器。"""
self.payload = None
async def ainvoke(self, payload, config=None):
"""记录 Agent 调用输入。"""
self.payload = payload
def get_state(self, _config):
"""返回包含最终 AI 回复的图状态。"""
return _FakeGraphState([AIMessage(content="ok")])
@pytest.mark.anyio
async def test_create_agent_reuses_cached_graph_when_signature_matches():
"""构造签名一致时应直接复用已编译 Agent 图。"""
cached_graph = object()
catalog = ToolCatalogSnapshot.from_tools(
[], plugin_revision=0, factory_revision="factory-v1"
)
agent = MoviePilotAgent(session_id="cache-hit", user_id="user-1")
agent._compiled_agent_bundle = _CompiledAgentBundle(
signature=("sig",),
agent=cached_graph,
streaming=False,
created_at=datetime.now(),
tool_catalog=catalog,
subagent_catalog=catalog,
plugin_revision=0,
mcp_config_signature="mcp-config",
catalog_checked_at=datetime.now(),
)
with patch.object(
agent,
"_agent_bundle_signature",
new=AsyncMock(return_value=("sig",)),
), patch(
"app.agent.orchestrator._get_plugin_tools_revision",
return_value=0,
), patch(
"app.agent.orchestrator.agent_mcp_manager.config_signature",
return_value="mcp-config",
), patch("app.agent.orchestrator.create_agent") as create_agent:
graph = await agent._create_agent(streaming=False)
assert graph is cached_graph
assert agent._last_agent_cache_hit is True
create_agent.assert_not_called()
@pytest.mark.anyio
async def test_fresh_catalog_cache_hit_skips_tool_and_mcp_discovery() -> None:
"""目录仍在 freshness 窗口内时,缓存命中不得重建工具或访问 MCP。"""
cached_graph = object()
catalog = ToolCatalogSnapshot.from_tools(
[], plugin_revision=0, factory_revision="factory-v1"
)
agent = MoviePilotAgent(session_id="catalog-cache-hit", user_id="user-1")
agent._compiled_agent_bundle = _CompiledAgentBundle(
signature=("sig",),
agent=cached_graph,
streaming=False,
created_at=datetime.now(),
tool_catalog=catalog,
subagent_catalog=catalog,
plugin_revision=0,
mcp_config_signature="mcp-config",
catalog_checked_at=datetime.now(),
)
with patch.object(
agent,
"_agent_bundle_signature",
new=AsyncMock(return_value=("sig",)),
), patch.object(
agent,
"_initialize_local_tool_catalogs",
side_effect=AssertionError("tool catalog rebuilt"),
), patch(
"app.agent.orchestrator._get_plugin_tools_revision",
return_value=0,
), patch(
"app.agent.orchestrator.agent_mcp_manager.config_signature",
return_value="mcp-config",
), patch(
"app.agent.orchestrator.agent_mcp_manager.list_enabled_tool_specs",
new=AsyncMock(side_effect=AssertionError("MCP discovery called")),
):
graph = await agent._create_agent(streaming=False)
assert graph is cached_graph
assert agent._last_agent_cache_hit is True
@pytest.mark.anyio
async def test_expired_unchanged_catalog_renews_freshness() -> None:
"""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。"""
cached_graph = object()
catalog = ToolCatalogSnapshot.from_tools(
[], plugin_revision=0, factory_revision="factory-v1"
)
expired_at = datetime.now() - timedelta(minutes=5)
agent = MoviePilotAgent(session_id="catalog-refresh", user_id="user-1")
agent._compiled_agent_bundle = _CompiledAgentBundle(
signature=("sig",),
agent=cached_graph,
streaming=False,
created_at=datetime.now(),
tool_catalog=catalog,
subagent_catalog=catalog,
plugin_revision=0,
mcp_config_signature="mcp-config",
catalog_checked_at=expired_at,
)
fake_llm = SimpleNamespace(
_llm_type="openai-chat",
model="fake",
profile={"max_input_tokens": 64000},
)
temporary_middleware = SimpleNamespace(close=AsyncMock())
with patch.object(
agent,
"_agent_bundle_signature",
new=AsyncMock(return_value=("sig",)),
), patch.object(
agent,
"_initialize_local_tool_catalogs",
return_value=(catalog, catalog),
), patch.object(
agent,
"_initialize_mcp_tools",
new=AsyncMock(return_value=[]),
), patch.object(
agent,
"_initialize_subagent_mcp_tools",
new=AsyncMock(return_value=[]),
), patch.object(
agent,
"_initialize_llm",
new=AsyncMock(return_value=fake_llm),
), patch.object(
agent,
"_sync_model_profile",
), patch(
"app.agent.orchestrator.ServerToolRegistry.resolve_web_search",
return_value=SimpleNamespace(use_local_web_search=True),
), patch(
"app.agent.orchestrator.LLMHelper.get_server_tools",
return_value=[],
), patch(
"app.agent.orchestrator.prompt_manager.get_agent_prompt",
return_value="prompt",
), patch(
"app.agent.orchestrator.SkillsMiddleware",
return_value=SimpleNamespace(name="skills", tools=[]),
), patch(
"app.agent.orchestrator.create_subagent_middlewares",
return_value=([temporary_middleware], []),
), patch(
"app.agent.orchestrator._get_plugin_tools_revision",
return_value=0,
), patch(
"app.agent.orchestrator.agent_mcp_manager.config_signature",
return_value="mcp-config",
), patch(
"app.agent.orchestrator.agent_mcp_manager.list_enabled_tool_specs",
new=AsyncMock(return_value=[]),
):
graph = await agent._create_agent(streaming=False)
assert graph is cached_graph
assert agent._compiled_agent_bundle.catalog_checked_at > expired_at
temporary_middleware.close.assert_awaited_once()
@pytest.mark.anyio
async def test_create_agent_cancellation_closes_temporary_subagent_middleware() -> None:
"""构图取消时必须释放尚未被缓存接管的子代理控制器。"""
catalog = ToolCatalogSnapshot.from_tools(
[], plugin_revision=0, factory_revision="factory-v1"
)
fake_llm = SimpleNamespace(
_llm_type="openai-chat",
model="fake",
profile={"max_input_tokens": 64000},
)
temporary_middleware = SimpleNamespace(close=AsyncMock())
signature_started = __import__("asyncio").Event()
agent = MoviePilotAgent(session_id="cancel-create", user_id="user-1")
async def _wait_for_signature(*_args, **_kwargs):
signature_started.set()
await __import__("asyncio").Future()
with patch.object(
agent,
"_resolve_llm_runtime_config",
new=AsyncMock(return_value={"provider": "openai", "model": "fake"}),
), patch.object(
agent,
"_initialize_local_tool_catalogs",
return_value=(catalog, catalog),
), patch.object(
agent,
"_initialize_mcp_tools",
new=AsyncMock(return_value=[]),
), patch.object(
agent,
"_initialize_subagent_mcp_tools",
new=AsyncMock(return_value=[]),
), patch.object(
agent,
"_initialize_llm",
new=AsyncMock(return_value=fake_llm),
), patch.object(
agent,
"_sync_model_profile",
), patch.object(
agent,
"_agent_bundle_signature",
new=_wait_for_signature,
), patch(
"app.agent.orchestrator._get_plugin_tools_revision",
return_value=0,
), patch(
"app.agent.orchestrator.agent_mcp_manager.config_signature",
return_value="mcp-config",
), patch(
"app.agent.orchestrator.agent_mcp_manager.list_enabled_tool_specs",
new=AsyncMock(return_value=[]),
), patch(
"app.agent.orchestrator.ServerToolRegistry.resolve_web_search",
return_value=SimpleNamespace(use_local_web_search=True),
), patch(
"app.agent.orchestrator.LLMHelper.get_server_tools",
return_value=[],
), patch(
"app.agent.orchestrator.prompt_manager.get_agent_prompt",
return_value="prompt",
), patch(
"app.agent.orchestrator.SkillsMiddleware",
return_value=SimpleNamespace(name="skills", tools=[]),
), patch(
"app.agent.orchestrator.create_subagent_middlewares",
return_value=([temporary_middleware], []),
):
create_task = __import__("asyncio").create_task(
agent._create_agent(streaming=False)
)
await signature_started.wait()
create_task.cancel()
with pytest.raises(__import__("asyncio").CancelledError):
await create_task
temporary_middleware.close.assert_awaited_once()
@pytest.mark.anyio
async def test_agent_bundle_signature_changes_with_temperature(monkeypatch) -> None:
"""温度配置变化时应使会话内 Agent 图缓存失效。"""
agent = MoviePilotAgent(session_id="temperature-change", user_id="user-1")
runtime_config = {
"provider": "openai",
"model": "gpt-test",
"api_key": "test-key",
"base_url": "https://llm.example.com/v1",
"base_url_preset": None,
"user_agent": None,
"use_proxy": False,
"thinking_level": "off",
"api_protocol": "auto",
}
with patch.object(
agent,
"_resolve_llm_runtime_config",
new=AsyncMock(return_value=runtime_config),
):
monkeypatch.setattr(settings, "LLM_TEMPERATURE", 0.3)
initial_signature = await agent._agent_bundle_signature(streaming=False)
monkeypatch.setattr(settings, "LLM_TEMPERATURE", 1.0)
updated_signature = await agent._agent_bundle_signature(streaming=False)
assert updated_signature != initial_signature
@pytest.mark.anyio
async def test_agent_bundle_signature_changes_with_context_cap(monkeypatch) -> None:
"""有效窗口配置变化时应使会话内 Agent 图缓存失效。"""
agent = MoviePilotAgent(session_id="context-cap-change", user_id="user-1")
runtime_config = {
"provider": "openai",
"model": "gpt-test",
"api_key": "test-key",
"base_url": "https://llm.example.com/v1",
}
with patch.object(
agent,
"_resolve_llm_runtime_config",
new=AsyncMock(return_value=runtime_config),
):
monkeypatch.setattr(settings, "LLM_MAX_CONTEXT_TOKENS", 32)
initial_signature = await agent._agent_bundle_signature(streaming=False)
monkeypatch.setattr(settings, "LLM_MAX_CONTEXT_TOKENS", 64)
updated_signature = await agent._agent_bundle_signature(streaming=False)
assert updated_signature != initial_signature
@pytest.mark.anyio
async def test_agent_bundle_signature_changes_with_tool_catalog() -> None:
"""工具目录 revision 必须参与会话内 Agent 图缓存签名。"""
agent = MoviePilotAgent(session_id="tool-revision", user_id="user-1")
runtime_config = {"provider": "openai", "model": "gpt-test"}
first_catalog = ToolCatalogSnapshot.from_tools(
[], plugin_revision=1, factory_revision="factory-v1"
)
second_catalog = ToolCatalogSnapshot.from_tools(
[], plugin_revision=2, factory_revision="factory-v1"
)
with patch.object(
agent,
"_resolve_llm_runtime_config",
new=AsyncMock(return_value=runtime_config),
):
first_signature = await agent._agent_bundle_signature(
streaming=False,
tool_catalog=first_catalog,
subagent_catalog=first_catalog,
)
second_signature = await agent._agent_bundle_signature(
streaming=False,
tool_catalog=second_catalog,
subagent_catalog=second_catalog,
)
assert second_signature != first_signature
@pytest.mark.anyio
@pytest.mark.parametrize("max_tools", [0, 5])
async def test_graph_keeps_mcp_first_winner_and_catalogs_all_collisions(
max_tools: int,
) -> None:
"""主图与子图保持 MCP first-wins,严格目录覆盖全部客户端工具。"""
servers = [
AgentMcpServerConfig(
id=server_id,
name="Shared Name",
transport="stdio",
command=server_id,
)
for server_id in ("one", "two")
]
specs = [
AgentMcpToolSpec(
server=server,
name="echo",
agent_tool_name="shared_echo",
description="echo",
input_schema={"type": "object", "properties": {}},
)
for server in servers
]
main_tools = await create_external_mcp_tools(
session_id="session",
user_id="user",
specs=specs,
)
subagent_tools = await create_external_mcp_tools(
session_id="session",
user_id="user",
specs=specs,
)
empty_catalog = ToolCatalogSnapshot.from_tools(
[], plugin_revision=0, factory_revision="factory-v1"
)
fake_llm = SimpleNamespace(
_llm_type="openai-chat",
model="fake",
profile={"max_input_tokens": 64000},
)
skill_tool = SimpleNamespace(
name="shared_echo",
description="skill collision",
args_schema={"type": "object", "properties": {}},
_agent_tool_source="middleware:skills",
)
activity_tool = SimpleNamespace(
name="query_activity_log",
description="activity log",
args_schema={"type": "object", "properties": {}},
_agent_tool_source="middleware:activity_log",
)
subagent_task_tool = SimpleNamespace(
name="task",
description="subagent task",
args_schema={"type": "object", "properties": {}},
_agent_tool_source="middleware:subagents",
)
captured = {}
agent = MoviePilotAgent(
session_id="mcp-collision",
user_id="user",
channel="web",
source="test",
)
def _capture_subagents(**kwargs):
captured["subagent_tools"] = kwargs["tools"]
captured["subagent_catalog"] = kwargs["catalog"]
return [], [subagent_task_tool]
def _capture_selector(**kwargs):
captured["selection_tools"] = kwargs["selection_tools"]
return SimpleNamespace(name="selector")
def _capture_agent(**kwargs):
captured["agent_tools"] = kwargs["tools"]
captured["middlewares"] = kwargs["middleware"]
return object()
patchers = [
patch.object(
agent,
"_resolve_llm_runtime_config",
new=AsyncMock(return_value={"provider": "openai", "model": "fake"}),
),
patch.object(
agent,
"_initialize_local_tool_catalogs",
return_value=(empty_catalog, empty_catalog),
),
patch.object(
agent,
"_initialize_mcp_tools",
new=AsyncMock(return_value=main_tools),
),
patch.object(
agent,
"_initialize_subagent_mcp_tools",
new=AsyncMock(return_value=subagent_tools),
),
patch.object(
agent,
"_agent_bundle_signature",
new=AsyncMock(return_value=("mcp-collision", max_tools)),
),
patch.object(
agent,
"_initialize_llm",
new=AsyncMock(return_value=fake_llm),
),
patch.object(agent, "_sync_model_profile"),
patch(
"app.agent.orchestrator._get_plugin_tools_revision",
return_value=0,
),
patch(
"app.agent.orchestrator.agent_mcp_manager.config_signature",
return_value="mcp-config",
),
patch(
"app.agent.orchestrator.agent_mcp_manager.list_enabled_tool_specs",
new=AsyncMock(return_value=specs),
),
patch(
"app.agent.orchestrator.ServerToolRegistry.resolve_web_search",
return_value=SimpleNamespace(use_local_web_search=True),
),
patch("app.agent.orchestrator.LLMHelper.get_server_tools", return_value=[]),
patch("app.agent.orchestrator.prompt_manager.get_agent_prompt", return_value="prompt"),
patch(
"app.agent.orchestrator.create_subagent_middlewares",
side_effect=_capture_subagents,
),
patch(
"app.agent.tools.factory.MoviePilotToolFactory.get_tool_selector_always_include_names",
return_value=[],
),
patch(
"app.agent.orchestrator.SkillsMiddleware",
return_value=SimpleNamespace(name="skills", tools=[skill_tool]),
),
patch(
"app.agent.orchestrator.ActivityLogMiddleware",
return_value=SimpleNamespace(name="activity", tools=[activity_tool]),
),
patch(
"app.agent.orchestrator.JobsMiddleware",
return_value=SimpleNamespace(name="jobs"),
),
patch(
"app.agent.orchestrator.RuntimeConfigMiddleware",
return_value=SimpleNamespace(name="runtime"),
),
patch(
"app.agent.orchestrator.MemoryMiddleware",
return_value=SimpleNamespace(name="memory"),
),
patch(
"app.agent.orchestrator.SummarizationMiddleware",
return_value=SimpleNamespace(name="summary"),
),
patch(
"app.agent.orchestrator.PatchToolCallsMiddleware",
return_value=SimpleNamespace(name="patch"),
),
patch(
"app.agent.orchestrator.UsageMiddleware",
return_value=SimpleNamespace(name="usage"),
),
patch(
"app.agent.orchestrator.ToolSelectorMiddleware",
side_effect=_capture_selector,
),
patch("app.agent.orchestrator.InMemorySaver", return_value=object()),
patch("app.agent.orchestrator.create_agent", side_effect=_capture_agent),
patch.object(settings, "LLM_MAX_TOOLS", max_tools),
]
with ExitStack() as stack:
for patcher in patchers:
stack.enter_context(patcher)
await agent._create_agent(streaming=False)
assert captured["agent_tools"] == [main_tools[0], skill_tool, activity_tool]
assert captured["subagent_tools"] == [subagent_tools[0]]
if max_tools:
assert captured["selection_tools"] == [
main_tools[0],
skill_tool,
activity_tool,
subagent_task_tool,
]
assert captured["middlewares"][-3].name == "selector"
else:
assert "selection_tools" not in captured
assert captured["middlewares"][-2].name == "FinalRequestCompactionMiddleware"
assert captured["middlewares"][-1].name == "usage"
policy_middleware = next(
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.orchestrator.eventmanager.send_event"):
await agent._execute_agent(messages)
assert agent._streamed_output == "ok"
assert fake_graph.payload["messages"] == [messages[-1]]