94 lines
3.3 KiB
Python
94 lines
3.3 KiB
Python
"""
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Anthropic Claude适配器
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"""
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from typing import Dict, Any
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from ..base_adapter import BaseLLMAdapter
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from ..types import LLMRequest, LLMResponse, LLMUsage, DEFAULT_BASE_URLS, LLMProvider
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class ClaudeAdapter(BaseLLMAdapter):
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"""Claude适配器"""
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@property
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def base_url(self) -> str:
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return self.config.base_url or DEFAULT_BASE_URLS.get(LLMProvider.CLAUDE, "https://api.anthropic.com/v1")
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async def complete(self, request: LLMRequest) -> LLMResponse:
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try:
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await self.validate_config()
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return await self.retry(lambda: self._send_request(request))
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except Exception as error:
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self.handle_error(error, "Claude API调用失败")
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async def _send_request(self, request: LLMRequest) -> LLMResponse:
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# Claude API需要将system消息分离
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system_message = None
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messages = []
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for msg in request.messages:
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if msg.role == "system":
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system_message = msg.content
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else:
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messages.append({
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"role": msg.role,
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"content": msg.content
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})
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request_body: Dict[str, Any] = {
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"model": self.config.model,
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"messages": messages,
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"max_tokens": request.max_tokens if request.max_tokens is not None else self.config.max_tokens or 4096,
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"temperature": request.temperature if request.temperature is not None else self.config.temperature,
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"top_p": request.top_p if request.top_p is not None else self.config.top_p,
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}
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if system_message:
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request_body["system"] = system_message
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# 构建请求头
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headers = {
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"x-api-key": self.config.api_key,
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"anthropic-version": "2023-06-01",
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}
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url = f"{self.base_url.rstrip('/')}/messages"
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response = await self.client.post(
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url,
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headers=self.build_headers(headers),
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json=request_body
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)
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if response.status_code != 200:
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error_data = response.json() if response.text else {}
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error_msg = error_data.get("error", {}).get("message", f"HTTP {response.status_code}")
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raise Exception(f"{error_msg}")
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data = response.json()
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if not data.get("content") or not data["content"][0]:
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raise Exception("API响应格式异常: 缺少content字段")
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usage = None
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if "usage" in data:
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usage = LLMUsage(
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prompt_tokens=data["usage"].get("input_tokens", 0),
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completion_tokens=data["usage"].get("output_tokens", 0),
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total_tokens=data["usage"].get("input_tokens", 0) + data["usage"].get("output_tokens", 0)
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)
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return LLMResponse(
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content=data["content"][0].get("text", ""),
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model=data.get("model"),
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usage=usage,
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finish_reason=data.get("stop_reason")
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)
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async def validate_config(self) -> bool:
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await super().validate_config()
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if not self.config.model.startswith("claude-"):
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raise Exception(f"无效的Claude模型: {self.config.model}")
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return True
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