steven_li
520a21a027
添加 DEFAULT_TEAM_NODE_MAX_TOOL_ITERATIONS 配置项以控制团队节点的最大工具迭代次数， 并修改 LocalAgentRunner 中的逻辑来使用此默认值当 envelope 中未指定时。 fix(runtime): 修复团队节点运行成功判断逻辑 更新运行成功判断条件，将 finish_reason 为 "max_tool_iterations_finalized" 的情况 视为运行失败，并添加对原始工具调用输出的检测，避免将其误判为成功完成。 feat(mcp): 添加团队工作流MCP工具类别支持 增加新的本地MCP工具类别 "team_workflow" 及其对应的工具创建功能， 为团队工作流提供本地工具支持。 refactor(engine): 调整AgentLoop最大工具迭代次数设置 将 AgentProfile 中的默认 max_tool_iterations 从 30 增加到 100， 同时移除 TaskExecutionPlanner 构造函数中的重复参数传递。 perf(mcp): 优化MCP连接管理避免重复连接 添加 mcp_connected 标志来跟踪MCP连接状态，确保 connect_all 只执行一次， 提高性能并避免不必要的重复连接。 refactor(skills): 移除技能团队模板相关功能 移除与技能团队模板相关的代码，包括解析、存储和处理逻辑， 简化技能记录结构和加载流程。 feat(process): 增强会话过程投影器功能 添加技能激活快照事件处理，改进团队运行完成消息显示， 并增强技能激活事件的时间戳记录功能。 refactor(tasks): 简化任务尝试编排器团队执行逻辑 移除团队执行相关代码，将所有任务统一按单步执行处理， 简化任务编排器的复杂度并提升执行效率。 fix(evidence): 修复节点证据评估中需求验证逻辑 更新节点证据评估逻辑，跳过自然语言证据需求的确定性验证， 只执行机器可读的需求验证，避免因自然语言需求导致的节点失败。
98 lines
3.2 KiB
Python
98 lines
3.2 KiB
Python
"""MCP tool wrappers for Beaver's tool contract."""
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from __future__ import annotations
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import asyncio
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from dataclasses import dataclass
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import json
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from typing import Any, Awaitable, Callable
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from beaver.tools.base import BaseTool, ToolContext, ToolResult, ToolSpec
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def _tool_schema(tool_def: Any) -> dict[str, Any]:
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schema = getattr(tool_def, "inputSchema", None) or getattr(tool_def, "input_schema", None)
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if isinstance(schema, dict):
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return schema
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return {"type": "object", "properties": {}}
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def _tool_name(tool_def: Any) -> str:
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return str(getattr(tool_def, "name", "") or "")
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def _tool_description(tool_def: Any) -> str:
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return str(getattr(tool_def, "description", "") or _tool_name(tool_def))
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def _mcp_result_to_text(result: Any) -> str:
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parts: list[str] = []
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for block in list(getattr(result, "content", []) or []):
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text = getattr(block, "text", None)
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parts.append(str(text if text is not None else block))
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if not parts and getattr(result, "structuredContent", None) is not None:
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return json.dumps(getattr(result, "structuredContent"), ensure_ascii=False, indent=2)
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return "\n".join(parts) or "(no output)"
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@dataclass(slots=True)
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class MCPToolWrapper(BaseTool):
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server_id: str
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tool_def: Any
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call_tool: Callable[[str, dict[str, Any]], Awaitable[Any]]
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tool_timeout: int = 30
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sensitive: bool = False
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kind: str = "online"
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category: str = "online"
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display_name: str = ""
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@property
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def original_name(self) -> str:
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return _tool_name(self.tool_def)
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@property
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def spec(self) -> ToolSpec:
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return ToolSpec(
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name=f"mcp_{self.server_id}_{self.original_name}",
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description=_tool_description(self.tool_def),
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input_schema=_tool_schema(self.tool_def),
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toolset=f"mcp-{self.server_id}",
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metadata={
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"server_id": self.server_id,
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"original_tool_name": self.original_name,
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"kind": self.kind,
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"category": self.category,
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"display_name": self.display_name or self.server_id,
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"transport": "mcp",
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},
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)
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async def invoke(self, arguments: dict[str, Any], context: ToolContext) -> ToolResult:
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if self.category == "team_workflow":
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from beaver.team_workflows.executor import TeamWorkflowExecutor
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return await TeamWorkflowExecutor().execute(
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self.original_name,
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dict(arguments or {}),
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context,
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tool_name=self.spec.name,
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)
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try:
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result = await asyncio.wait_for(
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self.call_tool(self.original_name, dict(arguments or {})),
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timeout=max(1, int(self.tool_timeout or 30)),
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)
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return ToolResult(
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success=True,
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content=_mcp_result_to_text(result),
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tool_name=self.spec.name,
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raw_output=result,
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)
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except Exception as exc:
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return ToolResult(
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success=False,
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content=f"MCP tool {self.server_id}.{self.original_name} failed: {exc}",
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tool_name=self.spec.name,
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error=str(exc),
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)
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