chore: 清理废弃的生成文件和重命名文件
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qzl
@@ -1,201 +0,0 @@
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from __future__ import annotations
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import pytest
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from ag_ui.core import RunAgentInput
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from agentscope.message import Msg
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from core.agentscope.runtime.react_runner import (
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AgentScopeReActRunner,
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StageExecutionResult,
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SystemAgentRuntimeConfig,
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)
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from schemas.agent.runtime_models import (
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RouterAgentOutput,
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UiMode,
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WorkerAgentOutputRich,
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)
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from schemas.agent.system_agent import AgentType, SystemAgentLLMConfig
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from schemas.user.context import UserContext, parse_profile_settings
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class _FakePipeline:
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def __init__(self) -> None:
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self.events: list[dict[str, object]] = []
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async def emit(self, *, session_id: str, event: dict[str, object]) -> str:
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self.events.append({"session_id": session_id, "event": event})
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return "1-0"
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class _FakeSessionCtx:
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def __init__(self, session: object) -> None:
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self._session = session
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async def __aenter__(self) -> object:
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return self._session
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async def __aexit__(self, exc_type, exc, tb) -> None:
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del exc_type, exc, tb
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def _user_context() -> UserContext:
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return UserContext(
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id="00000000-0000-0000-0000-000000000001",
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username="alice",
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email="alice@example.com",
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settings=parse_profile_settings(None),
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)
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def _run_input() -> RunAgentInput:
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return RunAgentInput.model_validate(
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{
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"threadId": "00000000-0000-0000-0000-000000000010",
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"runId": "run-1",
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"state": {},
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"messages": [{"id": "u1", "role": "user", "content": "hello"}],
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"tools": [
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{
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"name": "calendar.read",
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"description": "read",
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"parameters": {"type": "object"},
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},
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{
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"name": "calendar-write",
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"description": "write",
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"parameters": {"type": "object"},
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},
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],
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"context": [],
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"forwardedProps": {},
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}
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)
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def _router_output(*, ui_mode: UiMode) -> RouterAgentOutput:
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return RouterAgentOutput.model_validate(
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{
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"normalized_task_input": {
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"user_text": "hello",
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"multimodal_summary": [],
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},
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"key_entities": [],
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"constraints": [],
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"task_typing": {"primary": "knowledge", "secondary": []},
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"execution_mode": "onestep",
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"result_typing": {"primary": "direct_answer", "secondary": []},
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"ui": {
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"ui_mode": ui_mode.value,
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"ui_decision_reason": "need structure"
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if ui_mode == UiMode.RICH
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else "plain text",
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},
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}
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)
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@pytest.mark.asyncio
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async def test_execute_uses_router_ui_mode_to_select_worker_output_model(
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monkeypatch: pytest.MonkeyPatch,
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) -> None:
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runner = AgentScopeReActRunner()
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pipeline = _FakePipeline()
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worker_model_holder: dict[str, type[object]] = {}
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class _CommitSession:
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async def commit(self) -> None:
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return None
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monkeypatch.setattr(
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"core.agentscope.runtime.react_runner.AsyncSessionLocal",
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lambda: _FakeSessionCtx(_CommitSession()),
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)
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monkeypatch.setattr(
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runner,
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"_build_toolkits",
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lambda **kwargs: ("router-toolkit", "worker-toolkit"),
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)
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async def _load_system_agent_config(**kwargs):
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return SystemAgentRuntimeConfig(
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agent_type=kwargs["agent_type"],
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model_code="qwen3.5-flash"
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if kwargs["agent_type"] == AgentType.ROUTER
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else "deepseek-chat",
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llm_config=SystemAgentLLMConfig(
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temperature=0.1, max_tokens=256, timeout_seconds=30
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),
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)
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monkeypatch.setattr(runner, "_load_system_agent_config", _load_system_agent_config)
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async def _run_router_stage(**kwargs):
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return StageExecutionResult(
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message=Msg(name="router", content="", role="assistant"),
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payload=_router_output(ui_mode=UiMode.RICH).model_dump(mode="json"),
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response_metadata={
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"model": "qwen3.5-flash",
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"inputTokens": 12,
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"outputTokens": 6,
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"cost": 0.001,
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"latencyMs": 50,
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},
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)
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monkeypatch.setattr(runner, "_run_router_stage", _run_router_stage)
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async def _persist_router_message(**kwargs) -> None:
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assert kwargs["model_code"] == "qwen3.5-flash"
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monkeypatch.setattr(runner, "_persist_router_message", _persist_router_message)
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async def _run_worker_stage(**kwargs):
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worker_model_holder["model"] = kwargs["worker_output_model"]
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return StageExecutionResult(
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message=Msg(name="worker", content="done", role="assistant"),
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payload=WorkerAgentOutputRich.model_validate(
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{
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"status": "success",
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"answer": "done",
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"key_points": [],
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"result_type": "direct_answer",
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"suggested_actions": [],
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"error": None,
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"ui_hints": None,
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}
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).model_dump(mode="json", exclude_none=True),
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response_metadata={
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"model": "deepseek-chat",
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"inputTokens": 8,
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"outputTokens": 4,
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"cost": 0.002,
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"latencyMs": 40,
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},
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)
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monkeypatch.setattr(runner, "_run_worker_stage", _run_worker_stage)
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result = await runner.execute(
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user_context=_user_context(),
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context_messages=[],
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pipeline=pipeline,
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run_input=_run_input(),
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)
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assert worker_model_holder["model"].__name__ == "WorkerAgentOutputRich"
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event_types = []
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for item in pipeline.events:
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event = item.get("event")
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if isinstance(event, dict):
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event_types.append(event.get("type"))
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assert event_types == ["step.start", "step.finish", "step.start", "step.finish"]
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assert result["router"]["ui"]["ui_mode"] == "rich"
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assert result["worker"]["answer"] == "done"
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def test_extract_tool_names_normalizes_client_tool_names() -> None:
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runner = AgentScopeReActRunner()
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names = runner._extract_tool_names(_run_input())
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assert names == {"calendar_read", "calendar_write"}
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