114 lines
3.6 KiB
Python
114 lines
3.6 KiB
Python
from __future__ import annotations
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import logging
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from typing import Any, Dict, List, Tuple
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import httpx
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from app.exceptions import ProviderAPICallError
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from app.models import (
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LLMChoice,
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LLMMessage,
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LLMProvider,
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LLMRequest,
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LLMResponse,
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LLMRole,
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)
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from app.providers.base import LLMProviderClient
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logger = logging.getLogger(__name__)
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class AnthropicProvider(LLMProviderClient):
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name = LLMProvider.ANTHROPIC.value
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api_key_env = "ANTHROPIC_API_KEY"
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base_url = "https://api.anthropic.com/v1/messages"
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anthropic_version = "2023-06-01"
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async def chat(
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self, request: LLMRequest, client: httpx.AsyncClient
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) -> LLMResponse:
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self.ensure_stream_supported(request.stream)
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system_prompt, chat_messages = self._convert_messages(request.messages)
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payload = self.merge_payload(
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{
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"model": request.model,
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"messages": chat_messages,
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"max_tokens": request.max_tokens or 1024,
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"temperature": request.temperature,
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"top_p": request.top_p,
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},
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request.extra_params,
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)
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if system_prompt:
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payload["system"] = system_prompt
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headers = {
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"x-api-key": self.api_key,
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"anthropic-version": self.anthropic_version,
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"content-type": "application/json",
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}
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try:
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response = await client.post(self.base_url, json=payload, headers=headers)
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response.raise_for_status()
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except httpx.HTTPStatusError as exc:
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status_code = exc.response.status_code
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body = exc.response.text
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logger.error(
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"Anthropic upstream returned %s: %s", status_code, body, exc_info=True
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)
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raise ProviderAPICallError(
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f"Anthropic request failed with status {status_code}",
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status_code=status_code,
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response_text=body,
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) from exc
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except httpx.HTTPError as exc:
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logger.error("Anthropic transport error: %s", exc, exc_info=True)
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raise ProviderAPICallError(f"Anthropic request failed: {exc}") from exc
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data: Dict[str, Any] = response.json()
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message = self._build_message(data)
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return LLMResponse(
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provider=LLMProvider.ANTHROPIC,
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model=data.get("model", request.model),
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choices=[LLMChoice(index=0, message=message)],
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raw=data,
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)
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@staticmethod
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def _convert_messages(
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messages: List[LLMMessage],
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) -> Tuple[str | None, List[dict[str, Any]]]:
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system_parts: List[str] = []
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chat_payload: List[dict[str, Any]] = []
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for msg in messages:
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if msg.role == LLMRole.SYSTEM:
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system_parts.append(msg.content)
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continue
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role = "user" if msg.role == LLMRole.USER else "assistant"
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chat_payload.append(
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{"role": role, "content": [{"type": "text", "text": msg.content}]}
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)
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system_prompt = "\n\n".join(system_parts) if system_parts else None
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return system_prompt, chat_payload
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@staticmethod
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def _build_message(data: Dict[str, Any]) -> LLMMessage:
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role = data.get("role", "assistant")
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content_blocks = data.get("content", [])
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text_parts = [
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block.get("text", "")
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for block in content_blocks
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if isinstance(block, dict) and block.get("type") == "text"
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]
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content = "\n\n".join(part for part in text_parts if part)
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return LLMMessage(role=role, content=content)
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