3de3c8cb36
- matrix-gateway: POST /internal/matrix/presence/online endpoint - usePresenceHeartbeat hook with activity tracking - Auto away after 5 min inactivity - Offline on page close/visibility change - Integrated in MatrixChatRoom component
76 lines
2.3 KiB
Python
76 lines
2.3 KiB
Python
import httpx
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import time
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from models import ChatMessage, LLMResponse, Usage, ProviderConfig
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class DeepSeekProvider:
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"""DeepSeek API provider (OpenAI-compatible)"""
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def __init__(self, config: ProviderConfig):
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self.config = config
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self.client = httpx.AsyncClient(
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base_url=config.base_url,
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timeout=config.timeout,
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headers={
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"Authorization": f"Bearer {config.api_key}",
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"Content-Type": "application/json"
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} if config.api_key else {}
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)
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async def chat(
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self,
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messages: list[ChatMessage],
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model_name: str,
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max_tokens: int | None = None,
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temperature: float = 0.7,
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top_p: float = 1.0,
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**kwargs
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) -> LLMResponse:
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"""Call DeepSeek Chat API (OpenAI-compatible)"""
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start_time = time.time()
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payload = {
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"model": model_name,
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"messages": [{"role": m.role, "content": m.content} for m in messages],
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"temperature": temperature,
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"top_p": top_p
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}
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if max_tokens:
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payload["max_tokens"] = max_tokens
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try:
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response = await self.client.post(
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"/chat/completions",
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json=payload
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)
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response.raise_for_status()
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data = response.json()
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latency_ms = (time.time() - start_time) * 1000
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return LLMResponse(
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content=data["choices"][0]["message"]["content"],
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usage=Usage(
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prompt_tokens=data.get("usage", {}).get("prompt_tokens", 0),
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completion_tokens=data.get("usage", {}).get("completion_tokens", 0),
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total_tokens=data.get("usage", {}).get("total_tokens", 0)
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),
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provider="deepseek",
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model_resolved=model_name,
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latency_ms=latency_ms,
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cached=False
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)
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except httpx.HTTPStatusError as e:
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raise Exception(f"DeepSeek API error: {e.response.status_code} - {e.response.text}")
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except Exception as e:
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raise Exception(f"DeepSeek provider error: {str(e)}")
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async def close(self):
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"""Close HTTP client"""
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await self.client.aclose()
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