128 lines
5.4 KiB
Python
128 lines
5.4 KiB
Python
import os
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import logging
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import pandas as pd
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from datetime import datetime
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from django.db.models import Q, F
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from django.utils import timezone
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from apps.gmail.models import GmailConversation, GmailAttachment, ConversationSummary
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from apps.chat.models import ChatHistory
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logger = logging.getLogger(__name__)
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class GmailExportService:
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"""
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Gmail导出服务，提供将达人回复导出为Excel的功能
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"""
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@staticmethod
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def export_replied_influencers(user, format='xlsx'):
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"""
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导出已回复的达人Gmail列表
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Args:
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user: 用户对象
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format: 导出格式, 默认为xlsx
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Returns:
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tuple: (文件路径, 错误信息)
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"""
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try:
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# 获取用户所有的Gmail对话
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conversations = GmailConversation.objects.filter(
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user=user,
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is_active=True
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)
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if not conversations.exists():
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return None, "未找到任何Gmail对话"
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# 准备导出数据
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export_data = []
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for conversation in conversations:
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# 查询达人是否有回复
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chat_history = ChatHistory.objects.filter(
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user=user,
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conversation_id=conversation.conversation_id,
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metadata__contains={"from": conversation.influencer_email}
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).order_by('created_at')
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# 如果达人有回复，则添加到导出列表
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if chat_history.exists():
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# 获取第一条回复的时间
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first_reply = chat_history.first()
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first_reply_time = first_reply.created_at.replace(tzinfo=None) if first_reply else None
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# 获取最后一条回复的时间
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last_reply = chat_history.last()
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last_reply_time = last_reply.created_at.replace(tzinfo=None) if last_reply else None
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# 获取回复次数
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reply_count = chat_history.count()
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# 直接从数据库中获取对话摘要，不调用外部API
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summary = ""
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try:
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# 先从ConversationSummary模型中查找
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conversation_summary = ConversationSummary.objects.filter(
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conversation=conversation
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).first()
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if conversation_summary:
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summary = conversation_summary.content
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else:
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# 如果没有摘要，尝试获取最新的几条消息内容
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recent_messages = ChatHistory.objects.filter(
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user=user,
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conversation_id=conversation.conversation_id
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).order_by('-created_at')[:5]
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if recent_messages:
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summary = "最近消息: " + " | ".join([msg.content[:100] + ("..." if len(msg.content) > 100 else "") for msg in recent_messages])
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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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summary = '无法获取摘要'
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# 构建导出记录 - 注意移除时区信息
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export_record = {
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'用户邮箱': conversation.user_email,
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'达人邮箱': conversation.influencer_email,
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'对话标题': conversation.title,
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'对话开始时间': conversation.created_at.replace(tzinfo=None),
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'首次回复时间': first_reply_time,
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'最近回复时间': last_reply_time,
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'回复次数': reply_count,
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'对话摘要': summary,
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'对话ID': conversation.conversation_id
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}
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export_data.append(export_record)
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if not export_data:
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return None, "没有找到已回复的达人"
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# 创建DataFrame
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df = pd.DataFrame(export_data)
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# 生成文件名和路径
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timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
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file_name = f"influencer_replies_{timestamp}.{format}"
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export_dir = os.path.join('media', 'exports')
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os.makedirs(export_dir, exist_ok=True)
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file_path = os.path.join(export_dir, file_name)
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# 根据格式导出
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if format == 'xlsx':
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df.to_excel(file_path, index=False, engine='openpyxl')
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elif format == 'csv':
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df.to_csv(file_path, index=False, encoding='utf-8-sig')
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else:
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return None, f"不支持的导出格式: {format}"
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return file_path, None
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except Exception as e:
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logger.error(f"导出已回复达人失败: {str(e)}")
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import traceback
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logger.error(traceback.format_exc())
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return None, f"导出失败: {str(e)}" |