"""
Qwen AI 服务
"""
import httpx
import json
from typing import AsyncGenerator
from utils.config import settings
from utils.logger import logger
from utils.prompt_loader import load_prompt


class QwenService:
    def __init__(self):
        # 确保 API URL 包含完整路径
        base_url = settings.qwen3.api_url.rstrip('/')
        self.api_url = f"{base_url}/v1/chat/completions"
        self.model = settings.qwen3.model
        self.intent_model = settings.qwen3.model  # 意图识别使用相同模型
    
    async def extract_keywords(self, question: str) -> str:
        """从问题中提炼搜索关键词"""
        # 使用prompt加载器加载关键词提取prompt（如果配置了的话）
        # 这里暂时保留原有逻辑，可以后续添加到prompt配置中
        keyword_prompt = """你是一个关键词提取助手。请从用户的问题中提炼出最核心的搜索关键词。
要求：
1. 提取2-5个最关键的词语
2. 去除语气词、助词等无意义词汇
3. 保留专业术语和核心概念
4. 以空格分隔多个关键词

直接返回关键词，不要其他说明。

用户问题："""
        
        messages = [
            {"role": "system", "content": keyword_prompt},
            {"role": "user", "content": question}
        ]
        
        try:
            keywords = await self.chat(messages)
            return keywords.strip()
        except Exception as e:
            logger.error(f"关键词提取失败: {e}")
            # 失败时返回原问题
            return question
    
    async def intent_recognition(self, message: str) -> dict:
        """意图识别"""
        # 使用prompt加载器加载意图识别prompt
        intent_prompt = load_prompt("intent_recognition", userMessage=message)
        
        messages = [
            {"role": "user", "content": intent_prompt}
        ]
        
        try:
            response = await self.chat(messages)
            # 尝试解析JSON
            import re
            json_match = re.search(r'\{[^}]+\}', response)
            if json_match:
                result = json.loads(json_match.group())
                intent_type = result.get("intent_type", "").lower()
                
                # 为 greeting 和 faq 添加预设回复
                if intent_type in ("greeting", "问候"):
                    result["response"] = "您好！我是蜀道集团智能助手，很高兴为您服务。"
                elif intent_type in ("faq", "常见问题"):
                    result["response"] = "我可以帮您解答常见问题，请告诉我您想了解什么。"
                else:
                    result["response"] = ""
                
                return result
            return {"intent_type": "general_chat", "confidence": 0.5, "reason": "无法解析", "response": ""}
        except Exception as e:
            logger.error(f"意图识别失败: {e}")
            return {"intent_type": "general_chat", "confidence": 0.5, "reason": str(e), "response": ""}
    
    async def chat(self, messages: list, model: str = None) -> str:
        """同步聊天"""
        data = {
            "model": model or self.model,
            "messages": messages,
            "stream": False  # 明确指定非流式
        }
        
        try:
            async with httpx.AsyncClient(timeout=60.0) as client:
                response = await client.post(
                    self.api_url,
                    json=data
                )
                
                logger.info(f"Qwen API 响应状态: {response.status_code}")
                
                response.raise_for_status()
                
                # 检查响应是否为空
                if not response.text:
                    logger.error("Qwen API 返回空响应")
                    return ""
                
                # 检查是否是流式响应（以 data: 开头）
                if response.text.startswith("data:"):
                    logger.info("检测到流式响应，解析 SSE 格式")
                    # 解析 SSE 格式
                    content_parts = []
                    for line in response.text.split('\n'):
                        if line.startswith("data:"):
                            data_str = line[5:].strip()
                            if data_str and data_str != "[DONE]":
                                try:
                                    data_json = json.loads(data_str)
                                    delta_content = data_json.get('choices', [{}])[0].get('delta', {}).get('content', '')
                                    if delta_content:
                                        content_parts.append(delta_content)
                                except json.JSONDecodeError:
                                    continue
                    return ''.join(content_parts)
                
                # 普通 JSON 响应
                try:
                    result = response.json()
                    return result.get('response', result.get('choices', [{}])[0].get('message', {}).get('content', ''))
                except json.JSONDecodeError as je:
                    logger.error(f"Qwen API 响应不是有效的 JSON: {response.text[:200]}")
                    raise ValueError(f"无效的 JSON 响应: {str(je)}")
                
        except Exception as e:
            logger.error(f"Qwen API 调用失败: {e}")
            raise
    
    async def stream_chat(self, messages: list) -> AsyncGenerator[str, None]:
        """流式聊天"""
        data = {
            "model": self.model,
            "messages": messages,
            "stream": True
        }
        
        try:
            async with httpx.AsyncClient(timeout=120.0) as client:
                async with client.stream(
                    "POST",
                    self.api_url,
                    json=data
                ) as response:
                    response.raise_for_status()
                    async for line in response.aiter_lines():
                        if line.startswith("data: "):
                            data_str = line[6:]
                            if data_str == "[DONE]":
                                break
                            try:
                                data_json = json.loads(data_str)
                                # 兼容 OpenAI 格式 choices[0].delta.content
                                choices = data_json.get('choices', [])
                                if choices:
                                    content = choices[0].get('delta', {}).get('content', '') or choices[0].get('message', {}).get('content', '')
                                else:
                                    content = data_json.get('content', '')
                                if content:
                                    yield content
                            except json.JSONDecodeError:
                                continue
        except Exception as e:
            logger.error(f"Qwen 流式 API 调用失败: {e}")
            raise


# 全局实例
qwen_service = QwenService()