"""星火 Spark 翻译(OpenAI 兼容协议)。

- 端点:https://spark-api-open.xf-yun.com/v1/chat/completions
- 模型:lite(也支持 generalv3.5 等,但该项目用 Lite,免费额度)
- 鉴权:Bearer token(APIPassword 直接当 Bearer 用)
- 请求:POST /chat/completions,system prompt 告诉模型做翻译

设计上独立于 LlmClient,专门走 spark_* 配置,避免和 LLM 智能增强共用 client 的节流。
"""
from __future__ import annotations

import asyncio
import logging
import random

import httpx

from app.config import settings
from app.services.translation.base import BaseTranslator, TranslationResult

logger = logging.getLogger("news.translate.spark")


# 经过实测,这套 prompt 在 Spark Lite 上输出稳定(不夹带 reasoning / 注释)。
# Lite 不支持 system 角色(早期 Lite 模型),但 v1 OpenAI 兼容的 Lite 接受 system;
# 保留 system prompt 走 4.0Ultra/Max/Pro 时也通用。
_SYSTEM_PROMPT = """你是一个即时翻译助手。对于用户输入的英文或日文文章,请直接输出对应的简体中文译文。严格遵守:

不要进行任何分步思考、不要输出分析、不要添加注释或说明。

只输出中文译文本身,不包含任何额外文字(如"翻译结果:"、"以下是中文:"等)。

如果输入内容既非英文也非日文,仅回复:"仅支持英文或日文翻译为中文。" """


class SparkTranslator(BaseTranslator):
    """星火 Spark 翻译(OpenAI 兼容协议,模型 lite / generalv3.5 等)。"""

    name = "spark"

    def __init__(self):
        if not settings.spark_api_password:
            raise RuntimeError("Spark APIPassword missing")
        self.api_password = settings.spark_api_password
        self.base_url = settings.spark_base_url.rstrip("/")
        self.model = settings.spark_model
        self.interval_sec = settings.spark_interval_sec

    def is_configured(self) -> bool:
        return bool(self.api_password)

    async def translate(
        self, text: str, source: str = "auto", target: str = "zh"
    ) -> TranslationResult:
        """翻译接口。source/target 当前固定 EN/JA → ZH(由 prompt 控制)。"""
        if not text.strip():
            return TranslationResult(text=text, engine=self.name, chars=0)

        if not self.is_configured():
            raise RuntimeError("Spark APIPassword missing")

        system = _SYSTEM_PROMPT
        user = text

        url = f"{self.base_url}/chat/completions"
        payload = {
            "model": self.model,
            "messages": [
                {"role": "system", "content": system},
                {"role": "user", "content": user},
            ],
            "temperature": 0.0,
            "max_tokens": max(256, len(text) * 3),
        }
        headers = {
            "Authorization": f"Bearer {self.api_password}",
            "Content-Type": "application/json",
        }

        # 简单串行 + 重试 1 次
        last_exc: Exception | None = None
        for attempt in range(2):
            try:
                async with httpx.AsyncClient(timeout=60.0) as client:
                    r = await client.post(url, json=payload, headers=headers)
                if r.status_code >= 500:
                    raise RuntimeError(f"Spark 5xx: {r.status_code} {r.text[:200]}")
                if r.status_code != 200:
                    raise RuntimeError(f"Spark {r.status_code}: {r.text[:300]}")
                data = r.json()
                # 错误响应:{"error": {...}}
                if "error" in data:
                    raise RuntimeError(f"Spark error: {data['error']}")
                content = (
                    data.get("choices", [{}])[0]
                    .get("message", {})
                    .get("content", "")
                    .strip()
                )
                if not content:
                    raise RuntimeError(f"Spark empty content: {r.text[:300]}")
                await asyncio.sleep(self.interval_sec)
                return TranslationResult(
                    text=content, engine=self.name, chars=len(text), cached=False
                )
            except Exception as e:
                last_exc = e
                logger.warning("spark attempt %s failed: %s", attempt, e)
                if attempt == 0:
                    await asyncio.sleep(0.5 + random.random())
                else:
                    raise
        assert last_exc is not None
        raise last_exc