# src/services/llm/deepseek_client.py
"""DeepSeek LLM客户端 - OpenAI兼容API"""

import time
from typing import List, Dict, Optional
from loguru import logger
import httpx

from .base_client import BaseLLMClient, LLMResponse, LLMConfig, LLMProvider


class DeepSeekClient(BaseLLMClient):
    """
    DeepSeek API客户端（OpenAI兼容格式）

    支持模型：
    - deepseek-chat
    - deepseek-coder
    - deepseek-reasoner
    - deepseek-v3
    - deepseek-v3.2
    - deepseek-v4-flash
    """

    SUPPORTED_MODELS = [
        "deepseek-chat",
        "deepseek-coder",
        "deepseek-reasoner",
        "deepseek-v3",
        "deepseek-v3.2",
        "deepseek-v4-flash"
    ]

    def __init__(self, config: LLMConfig):
        if config.provider != LLMProvider.DEEPSEEK:
            raise ValueError(f"配置provider应为DEEPSEEK，实际为{config.provider}")
        super().__init__(config)
        self._init_client()

    def _init_client(self):
        """初始化HTTP客户端"""
        self._client = httpx.Client(
            base_url=self.config.base_url,
            headers={
                "Authorization": f"Bearer {self.config.api_key}",
                "Content-Type": "application/json"
            },
            timeout=self.config.timeout
        )
        logger.info(f"DeepSeek客户端初始化完成: {self.config.base_url} - {self.config.model}")

    def chat(
        self,
        messages: List[Dict[str, str]],
        max_tokens: Optional[int] = None,
        temperature: Optional[float] = None,
        **kwargs
    ) -> LLMResponse:
        """对话补全"""
        start_time = time.time()

        try:
            payload = {
                "model": self.config.model,
                "messages": messages,
                "max_tokens": max_tokens or self.config.max_tokens,
                "temperature": temperature or self.config.temperature,
                "top_p": kwargs.get("top_p", self.config.top_p),
                "stream": False
            }

            response = self._client.post("/chat/completions", json=payload)
            response.raise_for_status()

            data = response.json()

            latency_ms = int((time.time() - start_time) * 1000)

            choices = data.get("choices", [{}])
            message = choices[0].get("message", {})

            return LLMResponse(
                content=message.get("content", ""),
                model=data.get("model", self.config.model),
                usage=data.get("usage", {}),
                finish_reason=choices[0].get("finish_reason", "stop"),
                latency_ms=latency_ms
            )

        except httpx.HTTPStatusError as e:
            logger.error(f"DeepSeek API错误: {e.response.status_code} - {e.response.text}")
            return LLMResponse(
                content="",
                model=self.config.model,
                error=f"API错误: {e.response.status_code} - {e.response.text[:200]}"
            )

        except Exception as e:
            logger.error(f"DeepSeek调用失败: {e}")
            return LLMResponse(
                content="",
                model=self.config.model,
                error=str(e)
            )

    def get_available_models(self) -> List[str]:
        """获取可用模型列表"""
        return self.SUPPORTED_MODELS

    def close(self):
        """关闭客户端"""
        if self._client:
            self._client.close()


def create_deepseek_client(
    api_key: str,
    model: str = "deepseek-v4-flash",
    base_url: str = "http://6.86.80.4:30080/v1",
    **kwargs
) -> DeepSeekClient:
    """便捷函数：创建DeepSeek客户端"""
    config = LLMConfig(
        provider=LLMProvider.DEEPSEEK,
        model=model,
        api_key=api_key,
        base_url=base_url,
        **kwargs
    )
    return DeepSeekClient(config)