102 lines
3.3 KiB
Python
102 lines
3.3 KiB
Python
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import logging
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from django.conf import settings
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from datetime import datetime
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from apps.accounts.models import UserGoal
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from apps.gmail.models import GmailConversation, ConversationSummary
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from apps.chat.models import ChatHistory
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from apps.common.services.ai_service import AIService
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logger = logging.getLogger(__name__)
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def get_active_goal(user):
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"""
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获取用户最新的活跃目标
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Args:
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user: 用户对象
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Returns:
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UserGoal: 用户目标对象或None
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"""
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return UserGoal.objects.filter(user=user, is_active=True).order_by('-updated_at').first()
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def get_conversation_summary(conversation_id):
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"""
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获取对话摘要
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Args:
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conversation_id: 对话ID
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Returns:
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str: 摘要内容或None
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"""
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try:
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# 先检查持久化存储的摘要
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try:
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conversation = GmailConversation.objects.get(conversation_id=conversation_id)
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summary = ConversationSummary.objects.get(conversation=conversation)
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return summary.content
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except (GmailConversation.DoesNotExist, ConversationSummary.DoesNotExist):
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pass
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# 如果没有持久化的摘要，尝试生成简单摘要
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chat_history = ChatHistory.objects.filter(conversation_id=conversation_id).order_by('-created_at')[:5]
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if not chat_history:
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return None
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# 生成简单摘要（最近几条消息）
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messages = []
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for msg in chat_history:
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if len(messages) < 3: # 只取最新的3条
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role = "用户" if msg.role == "user" else "达人"
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content = msg.content
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if len(content) > 100:
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content = content[:100] + "..."
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messages.append(f"{role}: {content}")
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if messages:
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return "最近对话: " + " | ".join(reversed(messages))
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return None
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except Exception as e:
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logger.error(f"获取对话摘要失败: {str(e)}")
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return None
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def get_last_message(conversation_id):
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"""
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获取对话中最后一条对方发送的消息
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Args:
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conversation_id: 对话ID
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Returns:
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str: 最后一条消息内容或None
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"""
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try:
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# 获取对话中最后一条对方（达人）发送的消息
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last_message = ChatHistory.objects.filter(
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conversation_id=conversation_id,
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role='assistant' # 达人的消息
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).order_by('-created_at').first()
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if last_message:
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return last_message.content
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return None
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except Exception as e:
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logger.error(f"获取最后一条消息失败: {str(e)}")
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return None
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def generate_recommended_reply(user, goal_description, conversation_summary, last_message):
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"""
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根据用户目标、对话摘要和最后一条消息生成推荐话术
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Args:
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user: 用户对象
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goal_description: 用户目标描述
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conversation_summary: 对话摘要
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last_message: 达人最后发送的消息内容
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Returns:
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tuple: (推荐话术内容, 错误信息)
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"""
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# 直接调用AIService生成回复
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return AIService.generate_email_reply(goal_description, conversation_summary, last_message)
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