- 新增 embedding_service(语义检索)、knowledge_service(RAG)、text_chunker、document_parser - 新增 tool_registry(自定义工具注册表)并完善工具市场 API(CRUD + code/http 执行) - 新增 agent_vector_memory / knowledge_base 模型及对应数据库表 - 实现 SSE 流式响应与 Agent 预算控制 - AgentChat.vue 集成 MainLayout 导航布局 - 完善测试体系:7 个新测试文件共 110 个测试覆盖 - 修复 conftest.py SQLite 内存数据库连接隔离问题 Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
77 lines
2.5 KiB
Python
77 lines
2.5 KiB
Python
"""
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Agent 工具管理器:包装已有 ToolRegistry,提供 Agent 需要的工具格式转换和执行。
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"""
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from __future__ import annotations
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import logging
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from typing import Any, Dict, List, Optional
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from app.services.tool_registry import tool_registry
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logger = logging.getLogger(__name__)
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class AgentToolManager:
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"""
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为 Agent Runtime 管理工具:
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- 将 ToolRegistry 的工具 schema 转为 OpenAI Function Calling 格式
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- 按 Agent 配置过滤(白名单/黑名单)
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- 执行工具调用并返回结果字符串
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"""
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def __init__(self, include_tools: Optional[List[str]] = None,
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exclude_tools: Optional[List[str]] = None):
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self._include_tools: set = set(include_tools or [])
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self._exclude_tools: set = set(exclude_tools or [])
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def get_tool_schemas(self) -> List[Dict[str, Any]]:
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"""获取 Agent 可用的工具定义列表(OpenAI Function Calling 格式)。"""
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all_schemas = tool_registry.get_all_tool_schemas()
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if not self._include_tools and not self._exclude_tools:
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return all_schemas
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filtered = []
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for schema in all_schemas:
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name = self._extract_tool_name(schema)
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if not name:
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continue
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if self._include_tools and name not in self._include_tools:
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continue
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if name in self._exclude_tools:
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continue
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filtered.append(schema)
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return filtered
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def has_tools(self) -> bool:
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"""是否有可用工具。"""
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return len(self.get_tool_schemas()) > 0
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def tool_names(self) -> List[str]:
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"""可用工具名称列表。"""
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return [
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self._extract_tool_name(s) or "?"
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for s in self.get_tool_schemas()
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]
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async def execute(self, name: str, args: Dict[str, Any]) -> str:
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"""
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执行工具调用。
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优先查找内置工具,其次查找数据库自定义工具(HTTP / Code)。
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Args:
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name: 工具名称
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args: 工具参数字典
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Returns:
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工具执行结果的字符串表示
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"""
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logger.info("Agent 执行工具: %s", name)
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return await tool_registry.execute_tool(name, args)
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@staticmethod
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def _extract_tool_name(schema: Dict[str, Any]) -> Optional[str]:
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"""从工具 schema 中提取工具名称。"""
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fn = schema.get("function") or schema
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return fn.get("name") if isinstance(fn, dict) else None
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