feat(apikey system): tool system development
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谢俊男
302
api/app/core/tools/base.py
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302
api/app/core/tools/base.py
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"""工具基础接口定义"""
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import time
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from abc import ABC, abstractmethod
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from typing import Any, Dict, List, Optional, Union
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from pydantic import BaseModel, Field
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from enum import Enum
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from app.models.tool_model import ToolType, ToolStatus
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class ParameterType(str, Enum):
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"""参数类型枚举"""
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STRING = "string"
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INTEGER = "integer"
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NUMBER = "number"
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BOOLEAN = "boolean"
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ARRAY = "array"
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OBJECT = "object"
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class ToolParameter(BaseModel):
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"""工具参数定义"""
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name: str = Field(..., description="参数名称")
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type: ParameterType = Field(..., description="参数类型")
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description: str = Field("", description="参数描述")
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required: bool = Field(False, description="是否必需")
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default: Any = Field(None, description="默认值")
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enum: Optional[List[Any]] = Field(None, description="枚举值")
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minimum: Optional[Union[int, float]] = Field(None, description="最小值")
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maximum: Optional[Union[int, float]] = Field(None, description="最大值")
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pattern: Optional[str] = Field(None, description="正则表达式模式")
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class Config:
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use_enum_values = True
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class ToolResult(BaseModel):
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"""工具执行结果"""
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success: bool = Field(..., description="执行是否成功")
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data: Any = Field(None, description="返回数据")
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error: Optional[str] = Field(None, description="错误信息")
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error_code: Optional[str] = Field(None, description="错误代码")
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execution_time: float = Field(..., description="执行时间（秒）")
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token_usage: Optional[Dict[str, int]] = Field(None, description="Token使用情况")
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metadata: Dict[str, Any] = Field(default_factory=dict, description="额外元数据")
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@classmethod
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def success_result(
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cls,
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data: Any,
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execution_time: float,
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token_usage: Optional[Dict[str, int]] = None,
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metadata: Optional[Dict[str, Any]] = None
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) -> "ToolResult":
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"""创建成功结果"""
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return cls(
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success=True,
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data=data,
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execution_time=execution_time,
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token_usage=token_usage,
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metadata=metadata or {}
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)
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@classmethod
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def error_result(
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cls,
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error: str,
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execution_time: float,
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error_code: Optional[str] = None,
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metadata: Optional[Dict[str, Any]] = None
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) -> "ToolResult":
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"""创建错误结果"""
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return cls(
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success=False,
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error=error,
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error_code=error_code,
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execution_time=execution_time,
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metadata=metadata or {}
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)
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class ToolInfo(BaseModel):
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"""工具信息"""
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id: str = Field(..., description="工具ID")
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name: str = Field(..., description="工具名称")
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description: str = Field(..., description="工具描述")
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tool_type: ToolType = Field(..., description="工具类型")
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version: str = Field("1.0.0", description="工具版本")
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parameters: List[ToolParameter] = Field(default_factory=list, description="工具参数")
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status: ToolStatus = Field(ToolStatus.ACTIVE, description="工具状态")
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tags: List[str] = Field(default_factory=list, description="工具标签")
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tenant_id: Optional[str] = Field(None, description="租户ID")
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class Config:
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use_enum_values = True
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class BaseTool(ABC):
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"""所有工具的基础抽象类"""
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def __init__(self, tool_id: str, config: Dict[str, Any]):
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"""初始化工具
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Args:
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tool_id: 工具ID
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config: 工具配置
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"""
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self.tool_id = tool_id
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self.config = config
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self._status = ToolStatus.ACTIVE
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@property
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@abstractmethod
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def name(self) -> str:
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"""工具名称"""
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pass
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@property
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@abstractmethod
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def description(self) -> str:
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"""工具描述"""
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pass
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@property
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@abstractmethod
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def tool_type(self) -> ToolType:
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"""工具类型"""
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pass
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@property
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def version(self) -> str:
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"""工具版本"""
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return self.config.get("version", "1.0.0")
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@property
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def status(self) -> ToolStatus:
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"""工具状态"""
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return self._status
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@status.setter
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def status(self, value: ToolStatus):
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"""设置工具状态"""
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self._status = value
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@property
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@abstractmethod
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def parameters(self) -> List[ToolParameter]:
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"""工具参数定义"""
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pass
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@property
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def tags(self) -> List[str]:
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"""工具标签"""
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return self.config.get("tags", [])
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def get_info(self) -> ToolInfo:
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"""获取工具信息"""
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return ToolInfo(
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id=self.tool_id,
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name=self.name,
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description=self.description,
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tool_type=self.tool_type,
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version=self.version,
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parameters=self.parameters,
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status=self.status,
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tags=self.tags,
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tenant_id=self.config.get("tenant_id")
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)
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def validate_parameters(self, parameters: Dict[str, Any]) -> Dict[str, str]:
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"""验证参数
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Args:
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parameters: 输入参数
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Returns:
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验证错误字典，空字典表示验证通过
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"""
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errors = {}
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param_definitions = {p.name: p for p in self.parameters}
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# 检查必需参数
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for param_def in self.parameters:
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if param_def.required and param_def.name not in parameters:
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errors[param_def.name] = f"Required parameter '{param_def.name}' is missing"
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# 检查参数类型和约束
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for param_name, param_value in parameters.items():
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if param_name not in param_definitions:
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continue
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param_def = param_definitions[param_name]
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# 类型检查
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if not self._validate_parameter_type(param_value, param_def):
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errors[param_name] = f"Parameter '{param_name}' has invalid type, expected {param_def.type}"
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# 约束检查
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constraint_error = self._validate_parameter_constraints(param_value, param_def)
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if constraint_error:
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errors[param_name] = constraint_error
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return errors
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def _validate_parameter_type(self, value: Any, param_def: ToolParameter) -> bool:
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"""验证参数类型"""
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if value is None:
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return not param_def.required
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type_mapping = {
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ParameterType.STRING: str,
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ParameterType.INTEGER: int,
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ParameterType.NUMBER: (int, float),
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ParameterType.BOOLEAN: bool,
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ParameterType.ARRAY: list,
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ParameterType.OBJECT: dict
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}
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expected_type = type_mapping.get(param_def.type)
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if expected_type:
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return isinstance(value, expected_type)
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return True
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def _validate_parameter_constraints(self, value: Any, param_def: ToolParameter) -> Optional[str]:
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"""验证参数约束"""
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if value is None:
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return None
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# 枚举值检查
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if param_def.enum and value not in param_def.enum:
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return f"Value must be one of {param_def.enum}"
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# 数值范围检查
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if param_def.type in [ParameterType.INTEGER, ParameterType.NUMBER]:
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if param_def.minimum is not None and value < param_def.minimum:
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return f"Value must be >= {param_def.minimum}"
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if param_def.maximum is not None and value > param_def.maximum:
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return f"Value must be <= {param_def.maximum}"
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# 字符串模式检查
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if param_def.type == ParameterType.STRING and param_def.pattern:
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import re
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if not re.match(param_def.pattern, str(value)):
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return f"Value must match pattern: {param_def.pattern}"
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return None
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@abstractmethod
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async def execute(self, **kwargs) -> ToolResult:
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"""执行工具
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Args:
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**kwargs: 工具参数
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Returns:
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执行结果
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"""
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pass
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async def safe_execute(self, **kwargs) -> ToolResult:
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"""安全执行工具（包含参数验证和异常处理）
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Args:
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**kwargs: 工具参数
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Returns:
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执行结果
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"""
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start_time = time.time()
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try:
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# 参数验证
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validation_errors = self.validate_parameters(kwargs)
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if validation_errors:
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execution_time = time.time() - start_time
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error_msg = "; ".join([f"{k}: {v}" for k, v in validation_errors.items()])
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return ToolResult.error_result(
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error=f"Parameter validation failed: {error_msg}",
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error_code="VALIDATION_ERROR",
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execution_time=execution_time
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)
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# 执行工具
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result = await self.execute(**kwargs)
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return result
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except Exception as e:
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execution_time = time.time() - start_time
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return ToolResult.error_result(
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error=str(e),
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error_code="EXECUTION_ERROR",
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execution_time=execution_time
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)
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def to_langchain_tool(self):
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"""转换为Langchain工具格式"""
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from .langchain_adapter import LangchainAdapter
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return LangchainAdapter.convert_tool(self)
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def __repr__(self):
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return f"<{self.__class__.__name__}(id={self.tool_id}, name={self.name})>"
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