import json
import httpx


class LLMClient:
    """统一 LLM 接口，支持 OpenAI 兼容接口和 Anthropic 原生接口。"""

    def __init__(self, provider: str, api_key: str, base_url: str, model: str):
        self.provider = provider.lower()
        self.api_key = api_key
        self.base_url = base_url.rstrip("/")
        self.model = model

    async def complete(self, system_prompt: str, user_prompt: str) -> str:
        if self.provider == "anthropic":
            return await self._call_anthropic(system_prompt, user_prompt)
        return await self._call_openai_compat(system_prompt, user_prompt)

    async def _call_openai_compat(self, system_prompt: str, user_prompt: str) -> str:
        """适配 DeepSeek / 通义千问 / OpenAI 等兼容 /v1/chat/completions 的接口。"""
        async with httpx.AsyncClient(timeout=90) as client:
            resp = await client.post(
                f"{self.base_url}/v1/chat/completions",
                headers={"Authorization": f"Bearer {self.api_key}"},
                json={
                    "model": self.model,
                    "temperature": 0.2,
                    "messages": [
                        {"role": "system", "content": system_prompt},
                        {"role": "user", "content": user_prompt},
                    ],
                },
            )
            resp.raise_for_status()
            return resp.json()["choices"][0]["message"]["content"]

    async def _call_anthropic(self, system_prompt: str, user_prompt: str) -> str:
        async with httpx.AsyncClient(timeout=90) as client:
            resp = await client.post(
                f"{self.base_url}/v1/messages",
                headers={
                    "x-api-key": self.api_key,
                    "anthropic-version": "2023-06-01",
                    "content-type": "application/json",
                },
                json={
                    "model": self.model,
                    "max_tokens": 2048,
                    "system": system_prompt,
                    "messages": [{"role": "user", "content": user_prompt}],
                },
            )
            resp.raise_for_status()
            return resp.json()["content"][0]["text"]