import logging
from datetime import datetime
from apps.chat.models import ChatHistory
from apps.common.services.ai_service import AIService
import traceback
from django.db.models import Q


logger = logging.getLogger(__name__)

def get_conversation(conversation_id):
    """
    获取给定对话ID的对话内容
    
    参数:
    - conversation_id: 对话ID
    
    返回:
    - 对话数据，包含消息列表，如无法获取则返回None
    """
    try:
        # 获取对话消息
        messages = ChatHistory.objects.filter(
            conversation_id=conversation_id,
            is_deleted=False
        ).order_by('created_at')
        
        if not messages:
            logger.warning(f"对话 {conversation_id} 没有消息记录")
            return None
            
        # 构造消息列表
        message_list = []
        for msg in messages:
            message_list.append({
                'id': str(msg.id),
                'content': msg.content,
                'is_user': msg.role == 'user',
                'timestamp': msg.created_at.isoformat(),
                'metadata': msg.metadata or {}
            })
        
        # 获取对话标题
        title = messages.first().title if messages.exists() else "新对话"
            
        return {
            'id': conversation_id,
            'title': title,
            'messages': message_list
        }
        
    except Exception as e:
        logger.error(f"获取对话时发生错误: {str(e)}")
        logger.error(traceback.format_exc())
        return None

def get_conversation_summary(conversation_id):
    """
    获取对话摘要
    
    Args:
        conversation_id: 对话ID
        
    Returns:
        str: 摘要内容或None
    """
    try:
        # 获取对话消息
        chat_history = ChatHistory.objects.filter(
            conversation_id=conversation_id,
            is_deleted=False
        ).order_by('-created_at')[:5]
        
        if not chat_history:
            return None
            
        # 生成简单摘要（最近几条消息）
        messages = []
        for msg in chat_history:
            if len(messages) < 3:  # 只取最新的3条
                role = "用户" if msg.role == "user" else "助手"
                content = msg.content
                if len(content) > 100:
                    content = content[:100] + "..."
                messages.append(f"{role}: {content}")
                
        if messages:
            return "最近对话: " + " | ".join(reversed(messages))
            
        # 如果简单摘要方式不行，可以通过AI服务生成摘要
        conversation_data = get_conversation(conversation_id)
        if conversation_data and conversation_data.get('messages'):
            # 将消息数据转换为AI服务需要的格式
            conv_messages = []
            for msg in conversation_data['messages']:
                conv_messages.append({
                    'content': msg['content'],
                    'is_from_user': msg['is_user']
                })
                
            # 调用AI服务生成摘要
            summary, error = AIService.generate_conversation_summary(conv_messages)
            if not error and summary:
                return summary
                
        return None
    except Exception as e:
        logger.error(f"获取对话摘要失败: {str(e)}")
        logger.error(traceback.format_exc())
        return None

def get_last_message(conversation_id):
    """
    获取给定对话的最后一条消息
    
    参数:
    - conversation_id: 对话ID
    
    返回:
    - 最后一条消息文本，如果无法获取则返回None
    """
    try:
        # 获取对话消息
        chat_messages = ChatHistory.objects.filter(
            conversation_id=conversation_id,
            is_deleted=False
        ).order_by('created_at')
        
        if not chat_messages:
            logger.warning(f"对话 {conversation_id} 没有消息记录")
            return None
        
        # 过滤出助手发送的消息
        assistant_messages = [msg for msg in chat_messages if msg.role == 'assistant']
        
        if not assistant_messages:
            logger.warning(f"对话 {conversation_id} 中没有助手发送的消息")
            return None
            
        # 返回最后一条助手消息
        last_message = assistant_messages[-1].content
        return last_message
        
    except Exception as e:
        logger.error(f"获取最后一条消息时发生错误: {str(e)}")
        logger.error(traceback.format_exc())
        return None

def generate_recommended_reply(user, goal_description, conversation_summary, last_message):
    """
    根据用户目标、对话摘要和最后一条消息生成推荐话术
    
    Args:
        user: 用户对象
        goal_description: 用户目标描述
        conversation_summary: 对话摘要
        last_message: 助手最后发送的消息内容
        
    Returns:
        tuple: (推荐话术内容, 错误信息)
    """
    # 直接调用AIService生成回复
    return AIService.generate_email_reply(goal_description, conversation_summary, last_message)