f7508d915b
主要变更： - 使用原生 Request 对象接收请求数据 - 先记录原始 client_request（完整 JSON）到数据库 - 然后解析为 IncomingRequest 对象进行验证 - 添加请求解析的错误处理 修复问题： - ChatMessage 的 content 改为 Optional[str]，支持空值 - 添加 name 字段支持 function 角色的工具名称 - 添加 tool_calls 字段支持 assistant 消息的工具调用 - 修复 function 类型消息 content 为空时报错的问题 优化改进： - 保留完整的原始客户端请求 - 更好的数据完整性和可追溯性 - 代码清理：移除重复的 import 语句 测试验证： - 多轮工具调用对话正常工作 - function 消息空 content 正常处理 - 所有单元测试通过 (20/20) - 完全兼容 OpenAI API 消息格式 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
50 lines
1.5 KiB
Python
50 lines
1.5 KiB
Python
from pydantic import BaseModel, Field
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from typing import List, Dict, Any, Optional
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# Models for incoming requests
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class ChatMessage(BaseModel):
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"""Represents a single message in the chat history."""
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role: str
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content: Optional[str] = None
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name: Optional[str] = None # For function role messages
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tool_calls: Optional[List[Dict[str, Any]]] = None # For assistant messages with tool calls
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class Function(BaseModel):
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"""Represents the function definition within a tool."""
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name: str
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description: str
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parameters: Dict[str, Any]
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class Tool(BaseModel):
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"""Represents a tool definition provided by the user."""
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type: str
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function: Function
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class IncomingRequest(BaseModel):
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"""Defines the structure of the request from the client."""
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messages: List[ChatMessage]
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tools: Optional[List[Tool]] = None
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stream: Optional[bool] = False
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# Models for outgoing responses
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class ToolCallFunction(BaseModel):
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"""Function call details within a tool call."""
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name: str
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arguments: str # JSON string of arguments
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class ToolCall(BaseModel):
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"""Represents a tool call requested by the LLM."""
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id: str
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type: str = "function"
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function: ToolCallFunction
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class ResponseMessage(BaseModel):
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"""The message part of the response from the proxy."""
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role: str = "assistant"
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content: Optional[str] = None
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tool_calls: Optional[List[ToolCall]] = None
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class ProxyResponse(BaseModel):
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"""Defines the final structured response sent back to the client."""
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message: ResponseMessage
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