steven_li
30ab74ffb2
- 集成MCP连接管理器，支持MCP服务器连接 - 添加多种内置工具：ClarifyTool、CronTool、DelegateTool、ExecuteCodeTool、 PatchFileTool、ProcessTool、SendMessageTool、SpawnTool、TerminalTool、 TodoTool、WebFetchTool、WebSearchTool、WriteFileTool等 - 实现工具注册和装配功能 - 添加技能选择上下文参数 - 支持思考模式控制参数thinking_enabled feat(coordinator): 重构任务执行计划器参数命名 - 将learning_candidate_enabled重命名为allow_candidate_generation - 更新TeamGraphScheduler中的参数传递 - 修改LocalAgentRunner中的相关参数处理 - 更新README文档中的相应描述 refactor(context): 标准化工具调用参数格式 - 添加_json导入用于参数序列化 - 实现_provider_tool_calls方法标准化OpenAI兼容的工具调用载荷 - 修复工具调用中参数非字符串类型的序列化问题 refactor(session): 优化消息历史记录过滤逻辑 - 修改get_messages_as_conversation为基于运行状态过滤消息 - 排除未完成、失败或错误结束的运行记录 - 改进对话历史的可见性控制机制 fix(store): 修复FTS索引重建逻辑 - 添加异常处理防止FTS索引创建失败 - 实现_rebuild_fts_index方法重新构建全文搜索索引 - 优化索引触发器和表的维护流程
146 lines
4.0 KiB
Python
146 lines
4.0 KiB
Python
from __future__ import annotations
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import asyncio
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import pytest
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from types import SimpleNamespace
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from beaver.engine.providers.litellm import LiteLLMProvider
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def test_qwen_thinking_mode_is_sent_as_chat_template_kwargs(monkeypatch: pytest.MonkeyPatch) -> None:
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captured: dict = {}
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class Message:
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content = "可以"
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reasoning_content = ""
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tool_calls = []
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class Choice:
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message = Message()
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finish_reason = "stop"
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class Response:
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choices = [Choice()]
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usage = None
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async def fake_acompletion(**kwargs):
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captured.update(kwargs)
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return Response()
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monkeypatch.setattr("beaver.engine.providers.litellm.acompletion", fake_acompletion)
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monkeypatch.setattr("beaver.engine.providers.litellm.litellm", SimpleNamespace())
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provider = LiteLLMProvider(
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api_key="sk-test",
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api_base="https://oai.example.com/v1",
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default_model="Qwen3.6-35B",
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provider_name="openai",
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)
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response = asyncio.run(
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provider.chat(
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[{"role": "user", "content": "只回复可以"}],
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model="Qwen3.6-35B",
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thinking_enabled=False,
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)
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)
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assert response.content == "可以"
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assert captured["extra_body"] == {"chat_template_kwargs": {"enable_thinking": False}}
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def test_non_qwen_thinking_mode_is_not_sent(monkeypatch: pytest.MonkeyPatch) -> None:
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captured: dict = {}
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class Message:
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content = "ok"
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reasoning_content = None
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tool_calls = []
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class Choice:
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message = Message()
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finish_reason = "stop"
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class Response:
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choices = [Choice()]
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usage = None
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async def fake_acompletion(**kwargs):
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captured.update(kwargs)
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return Response()
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monkeypatch.setattr("beaver.engine.providers.litellm.acompletion", fake_acompletion)
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monkeypatch.setattr("beaver.engine.providers.litellm.litellm", SimpleNamespace())
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provider = LiteLLMProvider(
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api_key="sk-test",
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api_base="https://oai.example.com/v1",
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default_model="gpt-4.1-mini",
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provider_name="openai",
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)
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asyncio.run(
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provider.chat(
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[{"role": "user", "content": "reply ok"}],
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model="gpt-4.1-mini",
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thinking_enabled=False,
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)
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)
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assert "extra_body" not in captured
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def test_litellm_provider_sanitizes_tool_call_arguments(monkeypatch: pytest.MonkeyPatch) -> None:
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captured: dict = {}
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class Message:
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content = "ok"
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reasoning_content = None
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tool_calls = []
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class Choice:
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message = Message()
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finish_reason = "stop"
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class Response:
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choices = [Choice()]
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usage = None
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async def fake_acompletion(**kwargs):
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captured.update(kwargs)
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return Response()
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monkeypatch.setattr("beaver.engine.providers.litellm.acompletion", fake_acompletion)
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monkeypatch.setattr("beaver.engine.providers.litellm.litellm", SimpleNamespace())
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provider = LiteLLMProvider(
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api_key="sk-test",
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api_base="https://oai.example.com/v1",
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default_model="Qwen3.6-35B",
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provider_name="openai",
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)
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asyncio.run(
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provider.chat(
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[
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{
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"role": "assistant",
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"content": None,
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"tool_calls": [
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{
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"id": "call-1",
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"type": "function",
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"function": {
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"name": "cron",
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"arguments": {"action": "add", "mode": "notification"},
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},
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}
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],
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},
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{"role": "tool", "tool_call_id": "call-1", "name": "cron", "content": "done"},
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],
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model="Qwen3.6-35B",
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thinking_enabled=False,
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)
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)
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tool_call = captured["messages"][0]["tool_calls"][0]
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assert tool_call["function"]["arguments"] == '{"action": "add", "mode": "notification"}'
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