102 lines
3.2 KiB
Python
102 lines
3.2 KiB
Python
from __future__ import annotations
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import logging
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import os
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from typing import Any, Dict, List
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import httpx
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from app.exceptions import ProviderAPICallError
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from app.models import LLMChoice, LLMMessage, LLMProvider, LLMRequest, LLMResponse
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from app.providers.base import LLMProviderClient
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logger = logging.getLogger(__name__)
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def _resolve_timeout_seconds() -> float:
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raw = os.getenv("DEEPSEEK_TIMEOUT_SECONDS")
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if raw is None:
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return 60.0
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try:
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return float(raw)
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except ValueError:
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logger.warning(
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"Invalid value for DEEPSEEK_TIMEOUT_SECONDS=%r, falling back to 60 seconds",
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raw,
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)
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return 60.0
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DEEPSEEK_TIMEOUT_SECONDS = _resolve_timeout_seconds()
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class DeepSeekProvider(LLMProviderClient):
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name = LLMProvider.DEEPSEEK.value
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api_key_env = "DEEPSEEK_API_KEY"
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supports_stream = True
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base_url = "https://api.deepseek.com/v1/chat/completions"
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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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payload = self.merge_payload(
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{
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"model": request.model,
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"messages": [msg.model_dump() for msg in request.messages],
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"temperature": request.temperature,
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"top_p": request.top_p,
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"max_tokens": request.max_tokens,
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"stream": request.stream,
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},
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request.extra_params,
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)
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headers = {
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"Authorization": f"Bearer {self.api_key}",
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"Content-Type": "application/json",
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}
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timeout = httpx.Timeout(DEEPSEEK_TIMEOUT_SECONDS)
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try:
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response = await client.post(
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self.base_url, json=payload, headers=headers, timeout=timeout
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)
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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("DeepSeek upstream returned %s: %s", status_code, body, exc_info=True)
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raise ProviderAPICallError(
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f"DeepSeek 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("DeepSeek transport error: %s", exc, exc_info=True)
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raise ProviderAPICallError(f"DeepSeek request failed: {exc}") from exc
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data: Dict[str, Any] = response.json()
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choices = self._build_choices(data.get("choices", []))
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return LLMResponse(
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provider=LLMProvider.DEEPSEEK,
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model=data.get("model", request.model),
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choices=choices,
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raw=data,
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)
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@staticmethod
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def _build_choices(choices: List[dict[str, Any]]) -> List[LLMChoice]:
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built: List[LLMChoice] = []
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for choice in choices:
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message_data = choice.get("message") or {}
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message = LLMMessage(
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role=message_data.get("role", "assistant"),
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content=message_data.get("content", ""),
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)
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built.append(LLMChoice(index=choice.get("index", len(built)), message=message))
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return built
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