M4b：ai_provider 删除手术①-⑥——神识全面接管模型出口
- ① 后端删除 app/ai_provider/（38 文件，含 anthropic/openai 格式、billing、audio、embedding）、services/ai_provider_admin.py、core/config/model_config.py、tests/ai_provider/（21 文件） - ② 连带退役 application/agent/（旧 Agent 循环/steer/follow-up/确认注册表）、application/skill_executor.py、app/skills/（python skills 孤儿）、endpoints/audio.py、application/imports.py（ProviderManager 消费方）；settings 端点收敛为生成偏好 - ③ runs.py 修剪：AgentRunRegistry/steer/follow-up/confirmations 端点退役，保留 list/get/events/cancel/stream；safety 确认改为直接落库裁决（pending→approved/denied） - ④ 前端删除：models 页、ModelGatewayView、gateway.ts、GatewayPanel（玄关）、ModelGatewayPanel/ModelStrategyForm、audio.ts/useVoiceInput、网关类型与 mock；设置页收敛为外观/语言/通知 - ⑤ 配置收敛：config/models|providers|pricing.example.yaml 归档 shenshi/config/；.env.example 删 provider keys/MODEL_ENDPOINT_POOL/MODEL_CONFIG_PATH，收敛 SHENSHI_* - ⑥ 验收：rg 审计灵台 Provider SDK import 与 ai_provider 引用归零；后端 528 passed（2 个预存失败经 HEAD 复跑验证与本手术无关）、前端 type-check+201 passed、神识 go vet+test、BFF 4 passed
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@@ -1,203 +0,0 @@
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from types import SimpleNamespace
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import pytest
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from app.application.agent import (
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compose_system_messages,
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next_step_for_tool,
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step_event_payload,
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task_from_deliberative_plan,
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task_plan_payload,
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)
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from app.application.agent.skill_loader import load_skill_manifests
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from app.modules.agent import (
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AgentDefinition,
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AgentTask,
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ExecutionPolicy,
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Plan,
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PlanStep,
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ToolPolicy,
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)
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from app.modules.planner import DeliberativePlan
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from app.modules.planner import PlanStep as DeliberativePlanStep
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from app.modules.skills import parse_skill_manifest
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def test_agent_definition_keeps_minimal_execution_and_tool_policy() -> None:
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agent = AgentDefinition(
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name="工师",
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system_prompt="完成已授权的工程任务。",
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skill_refs=("代码审查",),
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tool_policy=ToolPolicy(("read_file", "shell")),
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execution_policy=ExecutionPolicy(max_iterations=3),
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)
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assert agent.skill_refs == ("代码审查",)
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assert agent.tool_policy.allowed_tools == ("read_file", "shell")
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assert agent.execution_policy.max_iterations == 3
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def test_agent_task_keeps_plan_as_runtime_only_contract() -> None:
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task = AgentTask(
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id="task_1",
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objective="审查当前变更",
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agent_name="工师",
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plan=Plan(
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steps=(PlanStep(id="step_1", title="读取变更", tool="read_file"),),
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status="approved",
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),
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)
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assert task.status == "queued"
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assert task.plan is not None
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assert task.plan.steps[0].status == "pending"
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def test_deliberative_plan_becomes_traceable_agent_task() -> None:
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task = task_from_deliberative_plan(
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DeliberativePlan(
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title="调研计划",
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steps=[
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DeliberativePlanStep(
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id=1,
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title="检索资料",
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description="读取相关资料",
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tool="fetch_url",
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risk_level="L2",
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)
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],
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assumptions=["资料可访问"],
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risks=["来源不完整"],
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),
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run_id="run_1",
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agent_name="学士",
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objective="调研主题",
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)
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assert task.status == "running"
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assert task.plan is not None
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assert task.plan.steps[0].id == "1"
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assert task_plan_payload(task)["steps"] == [
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{
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"id": "1",
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"title": "检索资料",
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"description": "读取相关资料",
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"tool": "fetch_url",
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"risk_level": "L2",
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"status": "pending",
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}
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]
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def test_tool_maps_only_to_its_next_uncompleted_plan_step() -> None:
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task = AgentTask(
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id="task_1",
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objective="执行计划",
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agent_name="工师",
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plan=Plan(
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steps=(
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PlanStep(id="1", title="读取", tool="read_file"),
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PlanStep(id="2", title="再次读取", tool="read_file"),
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)
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),
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)
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first = next_step_for_tool(task, "read_file", set())
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second = next_step_for_tool(task, "read_file", {"1"})
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assert first is not None and first.id == "1"
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assert second is not None and second.id == "2"
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assert next_step_for_tool(task, "shell", set()) is None
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assert step_event_payload(task, first, status="completed", result_summary="读取成功") == {
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"task_id": "task_1",
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"step_id": "1",
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"title": "读取",
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"tool": "read_file",
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"risk_level": "L2",
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"status": "completed",
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"result_summary": "读取成功",
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}
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def test_execution_policy_rejects_invalid_iteration_limit() -> None:
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with pytest.raises(ValueError, match="max_iterations"):
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ExecutionPolicy(max_iterations=0)
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def test_manifest_and_prompt_composer_keep_stable_order() -> None:
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skill = SimpleNamespace(
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name="代码审查",
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description="审查变更",
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trigger="审查, review",
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prompt_fragment="先理解调用路径，再报告问题。",
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risk_level="L1",
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status="enabled",
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tool_bindings_json='["read_file"]',
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)
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manifest = parse_skill_manifest(skill, ["read_file"])
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messages = compose_system_messages(
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["全局约束"],
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AgentDefinition(name="工师", system_prompt="只执行已授权任务。"),
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[manifest],
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)
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assert manifest.triggers == ("审查", "review")
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assert messages == [
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"全局约束",
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"【Agent：工师】\n只执行已授权任务。",
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"【代码审查·能力注入】\n先理解调用路径，再报告问题。",
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]
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def test_default_tools_filters_explicit_allowlist() -> None:
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from app.application.agent.tools import default_tools
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tools = default_tools(allowed_tools=("read_file",))
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assert [tool["function"]["name"] for tool in tools] == ["read_file"]
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async def test_skill_loader_unions_matches_with_explicit_references(
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monkeypatch: pytest.MonkeyPatch,
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) -> None:
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skills = [
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SimpleNamespace(
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name="代码审查",
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description="审查",
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trigger="审查",
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prompt_fragment="审查流程",
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risk_level="L1",
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status="enabled",
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tool_bindings_json='["read_file"]',
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),
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SimpleNamespace(
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name="网页研究",
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description="研究",
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trigger="研究",
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prompt_fragment="研究流程",
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risk_level="L2",
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status="enabled",
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tool_bindings_json='["web_search"]',
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),
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]
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async def fake_match_active_skills(_context: str):
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return [skills[0]]
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async def fake_get_enabled_skills_by_names(names: tuple[str, ...]):
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return [skill for skill in skills if skill.name in names]
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monkeypatch.setattr(
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"app.application.agent.skill_loader.match_active_skills",
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fake_match_active_skills,
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)
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monkeypatch.setattr(
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"app.application.agent.skill_loader.get_enabled_skills_by_names",
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fake_get_enabled_skills_by_names,
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)
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manifests = await load_skill_manifests("请审查", skill_refs=("网页研究",))
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assert [manifest.name for manifest in manifests] == ["代码审查", "网页研究"]
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assert manifests[0].allowed_tools == ("read_file",)
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@@ -1,235 +0,0 @@
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from pathlib import Path
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import pytest
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from app.ai_provider.types.messages import HumanMessage
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from app.application.agent import AgentContext, AgentRunContext, ExtensionRegistry
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from app.application.agent.python_skills import (
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PythonSkillCatalog,
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PythonSkillDefinition,
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activate_python_skills,
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discover_python_skills,
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)
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def _write_skill(package: Path, module: str, *, name: str, trigger: str) -> None:
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(package / f"{module}.py").write_text(
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f"""
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from app.application.agent.python_skills import PythonSkillDefinition
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from app.ai_provider.types.messages import HumanMessage
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async def transform(context, run):
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return type(context)(
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messages=(*context.messages, HumanMessage(content={name!r})),
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tools=context.tools,
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model_hint=context.model_hint,
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)
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def setup(registry):
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registry.add_context_transformer(transform)
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SKILL = PythonSkillDefinition(
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name={name!r},
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description={name!r},
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triggers=({trigger!r},),
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instructions={name!r},
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setup=setup,
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)
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""",
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encoding="utf-8",
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)
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async def test_catalog_discovers_without_activating_and_matches_per_run(
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tmp_path: Path,
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monkeypatch: pytest.MonkeyPatch,
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) -> None:
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package = tmp_path / "example_skills"
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package.mkdir()
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(package / "__init__.py").write_text("", encoding="utf-8")
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_write_skill(package, "b_skill", name="乙", trigger="研究")
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_write_skill(package, "a_skill", name="甲", trigger="审查")
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(package / "_ignored.py").write_text(
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"raise AssertionError('私有模块不应装载')",
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encoding="utf-8",
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)
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monkeypatch.syspath_prepend(str(tmp_path))
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catalog = discover_python_skills(("example_skills", "example_skills"))
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registry = ExtensionRegistry()
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unchanged = await registry.transform_context(
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AgentContext(messages=(HumanMessage(content="开始"),), tools=()),
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AgentRunContext(),
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)
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matched = catalog.match("请做研究", skill_refs=("甲",))
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activation = await activate_python_skills(registry, matched)
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transformed = await registry.transform_context(
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AgentContext(messages=(HumanMessage(content="开始"),), tools=()),
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AgentRunContext(),
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)
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await activation.close()
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assert [skill.name for skill in catalog.skills] == ["甲", "乙"]
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assert [message.content for message in unchanged.messages] == ["开始"]
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assert [skill.name for skill in matched] == ["甲", "乙"]
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assert [message.content for message in transformed.messages] == ["开始", "甲", "乙"]
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async def test_activation_cleanup_is_run_scoped() -> None:
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cleaned: list[str] = []
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def setup(registry: ExtensionRegistry):
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async def transform(context: AgentContext, _run: AgentRunContext) -> AgentContext:
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return AgentContext(
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(*context.messages, HumanMessage(content="active")),
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context.tools,
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context.model_hint,
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)
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registry.add_context_transformer(transform)
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return lambda: cleaned.append("closed")
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skill = PythonSkillDefinition("guard", "", ("guard",), "", setup)
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catalog = PythonSkillCatalog((skill,))
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first_registry = ExtensionRegistry()
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second_registry = ExtensionRegistry()
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activation = await activate_python_skills(first_registry, catalog.match("guard"))
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first = await first_registry.transform_context(AgentContext((), ()), AgentRunContext())
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second = await second_registry.transform_context(AgentContext((), ()), AgentRunContext())
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await activation.close()
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assert [message.content for message in first.messages] == ["active"]
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assert second.messages == ()
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assert cleaned == ["closed"]
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def test_catalog_supports_custom_matcher_with_run_metadata() -> None:
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skill = PythonSkillDefinition(
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"metadata_skill",
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"",
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(),
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"",
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lambda _registry: None,
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match=lambda text, metadata: text == "执行" and metadata.get("channel") == "voice",
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)
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catalog = PythonSkillCatalog((skill,))
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assert catalog.match("执行", metadata={"channel": "text"}) == ()
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assert catalog.match("执行", metadata={"channel": "voice"}) == (skill,)
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def test_catalog_rejects_duplicate_names() -> None:
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skill = PythonSkillDefinition("same", "", (), "", lambda _registry: None)
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with pytest.raises(ValueError, match="名称重复"):
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PythonSkillCatalog((skill, skill))
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def test_discovery_rejects_module_without_definition(
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tmp_path: Path,
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monkeypatch: pytest.MonkeyPatch,
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) -> None:
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package = tmp_path / "invalid_skills"
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package.mkdir()
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(package / "__init__.py").write_text("", encoding="utf-8")
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(package / "broken.py").write_text("SKILL_NAME = '坏技能'", encoding="utf-8")
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monkeypatch.syspath_prepend(str(tmp_path))
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with pytest.raises(TypeError, match="缺少 SKILL 定义"):
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discover_python_skills(("invalid_skills",))
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async def test_budget_guard_skill_stops_when_usage_exceeds_threshold() -> None:
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from app.ai_provider.types.chat import TokenUsage
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from app.application.agent.extensions import TurnSnapshot
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from app.skills.budget_guard import _BUDGET_TOTAL_TOKENS, SKILL
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registry = ExtensionRegistry()
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activation = await activate_python_skills(registry, (SKILL,))
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over_budget = TurnSnapshot(
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iteration=4,
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content="",
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reasoning="",
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tool_calls=(),
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tool_results=(),
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usage=TokenUsage(total_tokens=_BUDGET_TOTAL_TOKENS + 1),
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)
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within_budget = TurnSnapshot(
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iteration=1,
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content="",
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reasoning="",
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tool_calls=(),
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tool_results=(),
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usage=TokenUsage(total_tokens=max(_BUDGET_TOTAL_TOKENS - 1, 0)),
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)
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assert await registry.should_stop(over_budget, AgentRunContext()) is True
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assert await registry.should_stop(within_budget, AgentRunContext()) is False
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await activation.close()
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async def test_context_budget_folds_long_history() -> None:
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from app.ai_provider.types.messages import HumanMessage
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from app.application.agent.extensions import AgentContext
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from app.skills.context_budget import SKILL
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registry = ExtensionRegistry()
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activation = await activate_python_skills(registry, (SKILL,))
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messages = tuple(HumanMessage(content="x" * 1000) for _ in range(20))
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ctx = AgentContext(messages=messages, tools=())
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trimmed = await registry.transform_context(ctx, AgentRunContext())
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assert len(trimmed.messages) < len(messages)
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assert "已省略" in trimmed.messages[0].content
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await activation.close()
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async def test_arg_guard_rejects_oversized_input() -> None:
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from app.application.agent.extensions import ToolCallContext
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from app.skills.arg_guard import _MAX_ARG_CHARS, SKILL
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registry = ExtensionRegistry()
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activation = await activate_python_skills(registry, (SKILL,))
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oversized = ToolCallContext(
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"call_1", "write_file", {"content": "x" * (_MAX_ARG_CHARS + 10)}, ()
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)
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normal = ToolCallContext("call_2", "read_file", {"path": "/a"}, ())
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big = await registry.before_tool_call(oversized, AgentRunContext())
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small = await registry.before_tool_call(normal, AgentRunContext())
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assert big.allowed is False
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assert big.reason is not None
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assert small.allowed is True
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await activation.close()
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|
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async def test_run_metrics_listens_through_settled() -> None:
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from app.application.agent.extensions import AgentEvent
|
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from app.skills.run_metrics import SKILL
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|
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registry = ExtensionRegistry()
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activation = await activate_python_skills(registry, (SKILL,))
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run = AgentRunContext(run_id="run_metrics_test")
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await registry.publish(AgentEvent("agent.started"), run)
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await registry.publish(AgentEvent("agent.turn.started", {"iteration": 1}), run)
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await registry.publish(
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AgentEvent("tool.started", {"tool_call_id": "c1", "tool_name": "search"}),
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run,
|
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)
|
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await registry.publish(
|
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AgentEvent("tool.completed", {"tool_call_id": "c1", "status": "success"}),
|
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run,
|
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)
|
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await registry.publish(
|
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AgentEvent("tool.completed", {"tool_call_id": "c2", "status": "denied"}),
|
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run,
|
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)
|
||||
await registry.publish(AgentEvent("agent.turn.started", {"iteration": 2}), run)
|
||||
await registry.publish(AgentEvent("agent.settled", {"status": "completed"}), run)
|
||||
await activation.close()
|
||||
# 指标经 loguru 输出；此处验证含工具级事件的事件链被完整消费且 settled 不抛错。
|
||||
@@ -1,405 +0,0 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
from typing import Any
|
||||
from unittest.mock import MagicMock
|
||||
|
||||
import pytest
|
||||
|
||||
from app.ai_provider.types.chat import TokenUsage
|
||||
from app.ai_provider.types.messages import HumanMessage
|
||||
from app.application.agent import (
|
||||
AfterToolCallDecision,
|
||||
Agent,
|
||||
AgentConfig,
|
||||
AgentContext,
|
||||
AgentEvent,
|
||||
AgentRunContext,
|
||||
AgentTurnResult,
|
||||
BeforeToolCallDecision,
|
||||
ExtensionRegistry,
|
||||
PendingMessageQueue,
|
||||
QueueMode,
|
||||
ToolCallContext,
|
||||
TurnSnapshot,
|
||||
)
|
||||
from app.modules.tool_runtime.definition import ToolResult
|
||||
|
||||
|
||||
def test_pending_message_queue_supports_both_modes() -> None:
|
||||
queue = PendingMessageQueue(QueueMode.one_at_a_time)
|
||||
queue.put(HumanMessage(content="一"))
|
||||
queue.put(HumanMessage(content="二"))
|
||||
|
||||
assert [message.content for message in queue.drain()] == ["一"]
|
||||
assert [message.content for message in queue.drain()] == ["二"]
|
||||
|
||||
queue.mode = QueueMode.all
|
||||
queue.put(HumanMessage(content="三"))
|
||||
queue.put(HumanMessage(content="四"))
|
||||
assert [message.content for message in queue.drain()] == ["三", "四"]
|
||||
|
||||
|
||||
async def test_extension_registry_orders_context_and_tool_hooks() -> None:
|
||||
registry = ExtensionRegistry()
|
||||
run = AgentRunContext(run_id="run_1")
|
||||
|
||||
async def first(context: AgentContext, _run: AgentRunContext) -> AgentContext:
|
||||
return AgentContext(
|
||||
messages=(*context.messages, HumanMessage(content="first")),
|
||||
tools=context.tools,
|
||||
model_hint=context.model_hint,
|
||||
)
|
||||
|
||||
async def second(context: AgentContext, _run: AgentRunContext) -> AgentContext:
|
||||
return AgentContext(
|
||||
messages=(*context.messages, HumanMessage(content="second")),
|
||||
tools=context.tools,
|
||||
model_hint=context.model_hint,
|
||||
)
|
||||
|
||||
async def rewrite(
|
||||
_call: ToolCallContext, _run: AgentRunContext
|
||||
) -> BeforeToolCallDecision:
|
||||
return BeforeToolCallDecision(input={"value": 2})
|
||||
|
||||
async def terminate(
|
||||
_call: ToolCallContext,
|
||||
result: ToolResult,
|
||||
_run: AgentRunContext,
|
||||
) -> AfterToolCallDecision:
|
||||
return AfterToolCallDecision(result=result, terminate=True)
|
||||
|
||||
registry.add_context_transformer(first)
|
||||
registry.add_context_transformer(second)
|
||||
registry.add_before_tool_hook(rewrite)
|
||||
registry.add_after_tool_hook(terminate)
|
||||
|
||||
transformed = await registry.transform_context(AgentContext((), ()), run)
|
||||
assert [message.content for message in transformed.messages] == ["first", "second"]
|
||||
|
||||
call = ToolCallContext("call_1", "tool", {"value": 1}, ())
|
||||
before = await registry.before_tool_call(call, run)
|
||||
assert before.input == {"value": 2}
|
||||
|
||||
result = ToolResult(True, 0, "ok", "", 1, False, False, "trace_1")
|
||||
after = await registry.after_tool_call(call, result, run)
|
||||
assert after.result is result
|
||||
assert after.terminate is True
|
||||
|
||||
|
||||
async def test_extension_registry_extend_preserves_registration_order() -> None:
|
||||
registry = ExtensionRegistry()
|
||||
skill_registry = ExtensionRegistry()
|
||||
|
||||
async def base(context: AgentContext, _run: AgentRunContext) -> AgentContext:
|
||||
return AgentContext((*context.messages, HumanMessage(content="base")), context.tools)
|
||||
|
||||
async def skill(context: AgentContext, _run: AgentRunContext) -> AgentContext:
|
||||
return AgentContext((*context.messages, HumanMessage(content="skill")), context.tools)
|
||||
|
||||
registry.add_context_transformer(base)
|
||||
skill_registry.add_context_transformer(skill)
|
||||
registry.extend(skill_registry)
|
||||
|
||||
transformed = await registry.transform_context(AgentContext((), ()), AgentRunContext())
|
||||
|
||||
assert [message.content for message in transformed.messages] == ["base", "skill"]
|
||||
|
||||
|
||||
async def test_stateful_agent_consumes_follow_up_and_publishes_events() -> None:
|
||||
calls: list[list[str]] = []
|
||||
events: list[str] = []
|
||||
|
||||
async def runner(*, messages: list[Any], **_kwargs: object) -> AgentTurnResult:
|
||||
calls.append([message.content for message in messages])
|
||||
messages.append(HumanMessage(content=f"assistant-{len(calls)}"))
|
||||
return AgentTurnResult(
|
||||
content=f"done-{len(calls)}",
|
||||
reasoning="",
|
||||
iterations=1,
|
||||
tool_history=[{"name": f"tool-{len(calls)}"}],
|
||||
usage=TokenUsage(total_tokens=10),
|
||||
)
|
||||
|
||||
extensions = ExtensionRegistry()
|
||||
|
||||
async def listen(event: AgentEvent, _run: AgentRunContext) -> None:
|
||||
events.append(event.type)
|
||||
|
||||
extensions.add_event_listener(listen)
|
||||
agent = Agent(
|
||||
AgentConfig(tools=(), tool_runtime=MagicMock(), max_iterations=2),
|
||||
extensions=extensions,
|
||||
runner=runner,
|
||||
)
|
||||
|
||||
async def enqueue_follow_up(event: AgentEvent, _run: AgentRunContext) -> None:
|
||||
if event.type == "agent.started":
|
||||
assert agent.follow_up("再做一步") is True
|
||||
|
||||
extensions.add_event_listener(enqueue_follow_up)
|
||||
result = await agent.prompt("开始")
|
||||
|
||||
assert result.content == "done-2"
|
||||
assert calls == [["开始"], ["开始", "assistant-1", "再做一步"]]
|
||||
assert result.iterations == 2
|
||||
assert result.usage.total_tokens == 20
|
||||
assert [item["name"] for item in result.tool_history] == ["tool-1", "tool-2"]
|
||||
assert events == ["agent.started", "agent.ended", "agent.settled"]
|
||||
assert agent.state.status == "completed"
|
||||
assert agent.state.streaming_message == "done-2"
|
||||
|
||||
|
||||
async def test_stateful_agent_does_not_continue_after_runner_truncates() -> None:
|
||||
calls = 0
|
||||
|
||||
async def runner(*, messages: list[Any], **_kwargs: object) -> AgentTurnResult:
|
||||
nonlocal calls
|
||||
calls += 1
|
||||
messages.append(HumanMessage(content="assistant"))
|
||||
return AgentTurnResult(content="partial", reasoning="", iterations=1, truncated=True)
|
||||
|
||||
extensions = ExtensionRegistry()
|
||||
agent = Agent(
|
||||
AgentConfig(tools=(), tool_runtime=None, max_iterations=3),
|
||||
extensions=extensions,
|
||||
runner=runner,
|
||||
)
|
||||
|
||||
async def enqueue(event: AgentEvent, _run: AgentRunContext) -> None:
|
||||
if event.type == "agent.started":
|
||||
assert agent.follow_up("稍后处理") is True
|
||||
|
||||
extensions.add_event_listener(enqueue)
|
||||
result = await agent.prompt("开始")
|
||||
|
||||
assert calls == 1
|
||||
assert result.truncated is True
|
||||
assert [message.content for message in agent.follow_ups.drain()] == ["稍后处理"]
|
||||
|
||||
|
||||
async def test_follow_up_is_preserved_when_iteration_budget_is_exhausted() -> None:
|
||||
async def runner(*, messages: list[Any], **_kwargs: object) -> AgentTurnResult:
|
||||
messages.append(HumanMessage(content="assistant"))
|
||||
return AgentTurnResult(content="done", reasoning="", iterations=1)
|
||||
|
||||
extensions = ExtensionRegistry()
|
||||
agent = Agent(
|
||||
AgentConfig(tools=(), tool_runtime=None, max_iterations=1),
|
||||
extensions=extensions,
|
||||
runner=runner,
|
||||
)
|
||||
|
||||
async def enqueue(event: AgentEvent, _run: AgentRunContext) -> None:
|
||||
if event.type == "agent.started":
|
||||
assert agent.follow_up("稍后处理") is True
|
||||
|
||||
extensions.add_event_listener(enqueue)
|
||||
result = await agent.prompt("开始")
|
||||
|
||||
assert result.truncated is True
|
||||
assert bool(agent.follow_ups) is True
|
||||
assert [message.content for message in agent.follow_ups.drain()] == ["稍后处理"]
|
||||
|
||||
|
||||
async def test_started_listener_failure_restores_idle_state() -> None:
|
||||
extensions = ExtensionRegistry()
|
||||
|
||||
async def fail(_event: AgentEvent, _run: AgentRunContext) -> None:
|
||||
raise RuntimeError("event store unavailable")
|
||||
|
||||
extensions.add_event_listener(fail)
|
||||
agent = Agent(
|
||||
AgentConfig(tools=(), tool_runtime=MagicMock()),
|
||||
extensions=extensions,
|
||||
)
|
||||
|
||||
with pytest.raises(RuntimeError, match="event store unavailable"):
|
||||
await agent.prompt("开始")
|
||||
await agent.wait_for_idle()
|
||||
assert agent.state.status == "failed"
|
||||
|
||||
|
||||
async def test_stateful_agent_abort_cancels_active_run() -> None:
|
||||
started = asyncio.Event()
|
||||
events: list[str] = []
|
||||
|
||||
async def runner(**_kwargs: object) -> AgentTurnResult:
|
||||
started.set()
|
||||
await asyncio.Event().wait()
|
||||
raise AssertionError("unreachable")
|
||||
|
||||
extensions = ExtensionRegistry()
|
||||
|
||||
async def listen(event: AgentEvent, _run: AgentRunContext) -> None:
|
||||
events.append(event.type)
|
||||
|
||||
extensions.add_event_listener(listen)
|
||||
agent = Agent(
|
||||
AgentConfig(tools=(), tool_runtime=MagicMock()),
|
||||
extensions=extensions,
|
||||
runner=runner,
|
||||
)
|
||||
task = asyncio.create_task(agent.prompt("开始"))
|
||||
await started.wait()
|
||||
|
||||
assert await agent.abort() is True
|
||||
assert agent.run_context.cancellation.cancelled is True
|
||||
with pytest.raises(asyncio.CancelledError):
|
||||
await task
|
||||
await agent.wait_for_idle()
|
||||
assert agent.state.status == "cancelled"
|
||||
assert events == ["agent.started", "agent.cancelled", "agent.settled"]
|
||||
|
||||
|
||||
async def test_agent_replaces_cancelled_token_on_next_run() -> None:
|
||||
async def runner(**_kwargs: object) -> AgentTurnResult:
|
||||
return AgentTurnResult(content="done", reasoning="", iterations=1)
|
||||
|
||||
agent = Agent(AgentConfig(tools=(), tool_runtime=None), runner=runner)
|
||||
agent.run_context.cancellation.cancel()
|
||||
|
||||
await agent.prompt("重新开始")
|
||||
|
||||
assert agent.run_context.cancellation.cancelled is False
|
||||
|
||||
|
||||
async def test_extension_registry_should_stop_short_circuits_on_first_policy() -> None:
|
||||
registry = ExtensionRegistry()
|
||||
run = AgentRunContext(run_id="run_1")
|
||||
turn = TurnSnapshot(
|
||||
iteration=1,
|
||||
content="done",
|
||||
reasoning="",
|
||||
tool_calls=(),
|
||||
tool_results=(),
|
||||
)
|
||||
calls: list[str] = []
|
||||
|
||||
async def keep_going(snapshot: TurnSnapshot, _run: AgentRunContext) -> bool:
|
||||
calls.append("keep_going")
|
||||
assert snapshot is turn
|
||||
return False
|
||||
|
||||
async def stop_now(_snapshot: TurnSnapshot, _run: AgentRunContext) -> bool:
|
||||
calls.append("stop_now")
|
||||
return True
|
||||
|
||||
async def never_called(_snapshot: TurnSnapshot, _run: AgentRunContext) -> bool:
|
||||
calls.append("never_called")
|
||||
return False
|
||||
|
||||
registry.add_turn_policy(keep_going)
|
||||
registry.add_turn_policy(stop_now)
|
||||
registry.add_turn_policy(never_called)
|
||||
|
||||
assert await registry.should_stop(turn, run) is True
|
||||
assert calls == ["keep_going", "stop_now"]
|
||||
|
||||
|
||||
async def test_extension_registry_should_stop_false_when_all_policies_decline() -> None:
|
||||
registry = ExtensionRegistry()
|
||||
turn = TurnSnapshot(
|
||||
iteration=2,
|
||||
content="",
|
||||
reasoning="",
|
||||
tool_calls=({"name": "tool", "args": "{}"},),
|
||||
tool_results=(),
|
||||
)
|
||||
|
||||
async def decline(_snapshot: TurnSnapshot, _run: AgentRunContext) -> bool:
|
||||
return False
|
||||
|
||||
registry.add_turn_policy(decline)
|
||||
registry.add_turn_policy(decline)
|
||||
|
||||
assert await registry.should_stop(turn, AgentRunContext()) is False
|
||||
|
||||
|
||||
async def test_extension_registry_should_stop_respects_cancellation() -> None:
|
||||
registry = ExtensionRegistry()
|
||||
run = AgentRunContext()
|
||||
run.cancellation.cancel()
|
||||
turn = TurnSnapshot(
|
||||
iteration=1,
|
||||
content="",
|
||||
reasoning="",
|
||||
tool_calls=(),
|
||||
tool_results=(),
|
||||
)
|
||||
|
||||
async def policy(_snapshot: TurnSnapshot, _run: AgentRunContext) -> bool:
|
||||
return False
|
||||
|
||||
# raise_if_cancelled 在 policy 遍历循环内，故至少注册一个 policy 才会触发；
|
||||
# 这与 transform_context / before_tool_call / after_tool_call 一致：空注册时
|
||||
# 方法无 await 点，不额外检查取消信号。
|
||||
registry.add_turn_policy(policy)
|
||||
with pytest.raises(asyncio.CancelledError):
|
||||
await registry.should_stop(turn, run)
|
||||
|
||||
|
||||
async def test_on_tool_event_publishes_tool_lifecycle_to_extensions() -> None:
|
||||
"""_on_tool_event 既转发 SSE，又把同一事件发布进扩展事件流。"""
|
||||
events: list[tuple[str, dict[str, Any]]] = []
|
||||
sse_events: list[tuple[str, dict[str, Any]]] = []
|
||||
|
||||
async def on_tool_event(event_type: str, payload: dict[str, Any]) -> None:
|
||||
sse_events.append((event_type, payload))
|
||||
|
||||
async def listen(event: AgentEvent, _run: AgentRunContext) -> None:
|
||||
events.append((event.type, dict(event.payload)))
|
||||
|
||||
extensions = ExtensionRegistry()
|
||||
extensions.add_event_listener(listen)
|
||||
agent = Agent(
|
||||
AgentConfig(tools=(), tool_runtime=None, on_tool_event=on_tool_event),
|
||||
extensions=extensions,
|
||||
)
|
||||
|
||||
await agent._on_tool_event(
|
||||
"tool.started", {"tool_call_id": "c1", "tool_name": "search"}
|
||||
)
|
||||
await agent._on_tool_event(
|
||||
"tool.completed", {"tool_call_id": "c1", "status": "success"}
|
||||
)
|
||||
await agent._on_tool_event(
|
||||
"tool.completed", {"tool_call_id": "c2", "status": "denied"}
|
||||
)
|
||||
|
||||
assert [item[0] for item in sse_events] == [
|
||||
"tool.started",
|
||||
"tool.completed",
|
||||
"tool.completed",
|
||||
]
|
||||
assert [item[0] for item in events] == [
|
||||
"tool.started",
|
||||
"tool.completed",
|
||||
"tool.completed",
|
||||
]
|
||||
assert events[1][1]["status"] == "success"
|
||||
# pending 状态维护未被桥接改动破坏
|
||||
assert "c1" not in agent.state.pending_tool_calls
|
||||
|
||||
|
||||
async def test_on_tool_event_swallows_listener_failure() -> None:
|
||||
"""扩展 listener 抛异常不应阻断 SSE 转发或工具事件主流程。"""
|
||||
sse: list[str] = []
|
||||
|
||||
async def on_tool_event(event_type: str, _payload: dict[str, Any]) -> None:
|
||||
sse.append(event_type)
|
||||
|
||||
async def boom(_event: AgentEvent, _run: AgentRunContext) -> None:
|
||||
raise RuntimeError("listener boom")
|
||||
|
||||
extensions = ExtensionRegistry()
|
||||
extensions.add_event_listener(boom)
|
||||
agent = Agent(
|
||||
AgentConfig(tools=(), tool_runtime=None, on_tool_event=on_tool_event),
|
||||
extensions=extensions,
|
||||
)
|
||||
|
||||
# 不抛：异常被吞，SSE 仍照常转发
|
||||
await agent._on_tool_event("tool.started", {"tool_call_id": "c1"})
|
||||
assert sse == ["tool.started"]
|
||||
@@ -1,101 +0,0 @@
|
||||
from unittest.mock import AsyncMock, MagicMock
|
||||
|
||||
from app.application.agent.tools import to_ai_provider_tools
|
||||
from app.application.skill_executor import SkillExecutor
|
||||
from app.application.tool_runtime.view import RunScopedToolView
|
||||
from app.modules.skills.manifest import SkillManifest
|
||||
from app.modules.tool_runtime.definition import ToolResult, ToolSpec
|
||||
|
||||
|
||||
def _spec(name: str) -> ToolSpec:
|
||||
return ToolSpec(
|
||||
name=name,
|
||||
description=f"{name} description",
|
||||
risk_level="L1",
|
||||
permission_policy=MagicMock(),
|
||||
input_schema={
|
||||
"type": "object",
|
||||
"properties": {"value": {"type": "string"}},
|
||||
"required": ["value"],
|
||||
},
|
||||
)
|
||||
|
||||
|
||||
async def test_aliases_are_isolated_and_execute_through_base_runtime() -> None:
|
||||
runtime = MagicMock()
|
||||
runtime.list_specs.return_value = [_spec("shared_tool")]
|
||||
runtime.execute = AsyncMock(
|
||||
return_value=ToolResult(True, 0, "ok", "", 1, False, False, "trace_1")
|
||||
)
|
||||
first = RunScopedToolView(runtime)
|
||||
second = RunScopedToolView(runtime)
|
||||
|
||||
assert first.bind_alias("skill:甲/shared_tool", "shared_tool", description_prefix="[甲] ")
|
||||
assert second.bind_alias("skill:乙/shared_tool", "shared_tool", description_prefix="[乙] ")
|
||||
|
||||
first_names = {spec.name for spec in first.list_specs()}
|
||||
second_names = {spec.name for spec in second.list_specs()}
|
||||
result = await first.execute(
|
||||
"skill:甲/shared_tool",
|
||||
{"value": "x"},
|
||||
run_id="run_1",
|
||||
character_id="char_1",
|
||||
)
|
||||
|
||||
assert "skill:甲/shared_tool" in first_names
|
||||
assert "skill:乙/shared_tool" not in first_names
|
||||
assert "skill:乙/shared_tool" in second_names
|
||||
assert "skill:甲/shared_tool" not in second_names
|
||||
assert result.stdout == "ok"
|
||||
runtime.execute.assert_awaited_once_with(
|
||||
"shared_tool",
|
||||
{"value": "x"},
|
||||
run_id="run_1",
|
||||
character_id="char_1",
|
||||
trace_id=None,
|
||||
confirmed=False,
|
||||
context=None,
|
||||
)
|
||||
runtime.register.assert_not_called()
|
||||
runtime.unregister.assert_not_called()
|
||||
|
||||
|
||||
def test_alias_keeps_target_input_schema() -> None:
|
||||
runtime = MagicMock()
|
||||
runtime.list_specs.return_value = [_spec("custom_tool")]
|
||||
view = RunScopedToolView(runtime)
|
||||
view.bind_alias("skill:研究/custom_tool", "custom_tool")
|
||||
|
||||
tools = to_ai_provider_tools(view.list_specs())
|
||||
alias = next(tool for tool in tools if tool["function"]["name"] == "skill:研究/custom_tool")
|
||||
|
||||
assert alias["function"]["parameters"]["required"] == ["value"]
|
||||
|
||||
|
||||
async def test_skill_executor_binds_only_current_run_aliases(
|
||||
monkeypatch,
|
||||
) -> None:
|
||||
manifest = SkillManifest(
|
||||
name="研究",
|
||||
description="",
|
||||
triggers=("研究",),
|
||||
prompt="研究说明",
|
||||
allowed_tools=("shared_tool", "missing"),
|
||||
risk_level="L1",
|
||||
)
|
||||
|
||||
async def load(*_args, **_kwargs):
|
||||
return [manifest]
|
||||
|
||||
monkeypatch.setattr("app.application.skill_executor.load_skill_manifests", load)
|
||||
runtime = MagicMock()
|
||||
runtime.list_specs.return_value = [_spec("shared_tool")]
|
||||
view = RunScopedToolView(runtime)
|
||||
messages: list[str] = []
|
||||
|
||||
await SkillExecutor(view).match_and_activate("请研究", messages, run_id="run_1")
|
||||
|
||||
assert messages == ["【研究·能力注入】\n研究说明"]
|
||||
assert "skill:研究/shared_tool" in view.specs_by_name()
|
||||
assert "skill:研究/missing" not in view.specs_by_name()
|
||||
runtime.register.assert_not_called()
|
||||
Reference in new issue
Block a user