pmc
bd95ba470c
- Update food, outfits, props, home-decor pages and components - Add permissions page and sidebar updates - Update API client and all API modules (auth, food, dances, etc.) - Add card model migrations for optional fields - Update Django views, serializers, and authentication - Add affinity level migrations and user app updates - Add project documentation Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
430 lines
18 KiB
Python
430 lines
18 KiB
Python
from rest_framework.views import APIView
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from rest_framework.response import Response
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from rest_framework import status, viewsets, permissions
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from django.contrib.auth.models import User
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from .models import ChatMessage, Bot
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from userapp.models import ParadiseUser
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from .serializers import ChatMessageSerializer
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from rest_framework.permissions import IsAuthenticated
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from userapp.authentication import RedisTokenAuthentication
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from rest_framework import serializers
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from common.swagger_utils import swagger_schema
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from drf_yasg import openapi
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from drf_yasg.utils import swagger_auto_schema
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import logging
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import requests
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import re
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logger = logging.getLogger(__name__)
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class BotSerializer(serializers.ModelSerializer):
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class Meta:
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model = Bot
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fields = ['id', 'name', 'description']
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class IsAdminOrReadOnly(permissions.BasePermission):
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def has_permission(self, request, view):
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if request.method in permissions.SAFE_METHODS:
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return request.user and request.user.is_authenticated
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return request.user and request.user.is_staff
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class BotViewSet(viewsets.ModelViewSet):
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"""
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机器人(AI模型)管理接口
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管理员可增删改查，普通用户只读
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"""
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queryset = Bot.objects.all()
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serializer_class = BotSerializer
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permission_classes = [IsAdminOrReadOnly]
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authentication_classes = [RedisTokenAuthentication]
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from .kimi import KIMI
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from .audio.AudioService import get_audio_service
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# Swagger Schema 定义
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class ChatRequestSchema(serializers.Serializer):
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message = serializers.CharField(required=True, help_text="用户发送的文本消息内容")
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class ChatMessageDetailSchema(serializers.Serializer):
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id = serializers.IntegerField(help_text="消息ID")
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user = serializers.IntegerField(help_text="用户ID")
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bot = serializers.IntegerField(help_text="机器人ID")
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message = serializers.CharField(help_text="消息内容")
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sender = serializers.CharField(help_text="发送者，user或bot")
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message_type = serializers.CharField(help_text="消息类型")
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message_audio_url = serializers.URLField(help_text="音频链接", allow_null=True, required=False)
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message_video_url = serializers.URLField(help_text="视频链接", allow_null=True, required=False)
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created_at = serializers.DateTimeField(help_text="创建时间")
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class ChatResponseSchema(serializers.Serializer):
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user_message = ChatMessageDetailSchema(help_text="用户发送的消息详情")
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bot_reply = ChatMessageDetailSchema(help_text="机器人的回复消息详情")
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class MultiChatRequestSchema(serializers.Serializer):
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botId = serializers.IntegerField(required=True, help_text="机器人ID")
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message = serializers.CharField(required=True, help_text="用户发送的消息内容")
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messageType = serializers.ChoiceField(
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choices=[ChatMessage.MESSAGE_TYPE_TEXT, ChatMessage.MESSAGE_TYPE_AUDIO, ChatMessage.MESSAGE_TYPE_VIDEO],
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help_text="消息类型(text, audio, video)"
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)
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messageAudioUrl = serializers.URLField(required=False, help_text="音频消息的URL(当messageType为audio时)")
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messageAudioBase64 = serializers.CharField(required=False, help_text="Base64编码的音频数据(当messageType为audio时)")
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messageVideoUrl = serializers.URLField(required=False, help_text="视频消息的URL(当messageType为video时)")
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messageVideoBase64 = serializers.CharField(required=False, help_text="Base64编码的视频数据(当messageType为video时)")
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returnAudioAsBase64 = serializers.BooleanField(required=False, default=False, help_text="是否返回Base64编码的音频而不是URL")
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class ChatBotAPIView(APIView):
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"""
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AI 聊天机器人接口
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提供与 AI 聊天机器人的单轮对话功能。
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支持发送文本消息并获取 AI 的回复。
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"""
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authentication_classes = [RedisTokenAuthentication] # 使用自定义的认证类
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permission_classes = [IsAuthenticated] # 仅允许已认证用户访问
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tags = ['ai-chat']
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@swagger_schema(
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request_schema=ChatRequestSchema,
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responses={
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201: openapi.Response('对话成功', ChatResponseSchema),
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404: openapi.Response('机器人不存在', openapi.Schema(
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type=openapi.TYPE_OBJECT,
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properties={
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'error': openapi.Schema(type=openapi.TYPE_STRING, description='错误信息')
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}
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))
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},
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operation_description="与AI机器人进行单轮对话，发送文本消息并获取回复",
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tags=['AI聊天'],
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security=[{'Bearer': []}],
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manual_parameters=[
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openapi.Parameter(
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'bot_id',
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openapi.IN_PATH,
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description="AI机器人的唯一标识",
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type=openapi.TYPE_INTEGER,
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required=True
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)
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]
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)
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def post(self, request, bot_id):
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"""
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发送消息给 AI 聊天机器人
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接收用户发送的文本消息，并返回 AI 机器人的回复。
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"""
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self.user = request.user
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try:
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self.bot = Bot.objects.get(id=bot_id)
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except Exception as _:
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return Response(
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{"error": "Bot not found"}, status=status.HTTP_404_NOT_FOUND
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)
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# Check is there a message for the current user and bot,if not, create a initial message
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handle_first_access(self.user, self.bot)
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# create a new message for the current request
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message_type = ChatMessage.MESSAGE_TYPE_TEXT
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user_message = request.data.get("message")
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message_audio_url = ''
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message_video_url = ''
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user_chat_message = create_user_message(self.user, self.bot, message_type, user_message, message_audio_url, message_video_url)
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# prepare the history
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history = list(map(lambda message: {'role':message.sender, 'content':message.message},
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ChatMessage.objects.filter(bot=self.bot,user=self.user).all()))
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bot_chat_message = ask_kimi(self.user, self.bot, history)
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# serialize the messages
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user_message_serializer = ChatMessageSerializer(user_chat_message)
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bot_message_serializer = ChatMessageSerializer(bot_chat_message)
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logger.info(bot_chat_message)
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return Response(
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{
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"user_message": user_message_serializer.data,
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"bot_reply": bot_message_serializer.data,
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},
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status=status.HTTP_201_CREATED,
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)
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class MultiChatAPIView(APIView):
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"""
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AI 多轮对话接口
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提供与 AI 的多轮对话功能。
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支持上下文关联的对话，AI 能够记住对话历史。
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"""
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authentication_classes = [RedisTokenAuthentication] # 使用自定义的认证类
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permission_classes = [IsAuthenticated] # 仅允许已认证用户访问
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tags = ['ai-multichat']
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@swagger_schema(
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request_schema=MultiChatRequestSchema,
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responses={
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201: openapi.Response('对话成功', ChatMessageDetailSchema),
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400: openapi.Response('请求参数错误', openapi.Schema(
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type=openapi.TYPE_OBJECT,
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properties={
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'error': openapi.Schema(type=openapi.TYPE_STRING, description='错误信息')
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}
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)),
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404: openapi.Response('机器人不存在', openapi.Schema(
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type=openapi.TYPE_OBJECT,
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properties={
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'error': openapi.Schema(type=openapi.TYPE_STRING, description='错误信息')
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}
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))
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},
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operation_description="与AI进行多轮对话，支持文本、音频和视频消息，AI能记住对话历史",
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tags=['AI聊天'],
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security=[{'Bearer': []}]
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)
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def post(self, request):
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"""
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发起多轮对话
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支持与 AI 进行多轮对话，AI 会记住对话上下文。
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"""
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self.user = request.user
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bot_id = request.data.get("botId")
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if bot_id is None:
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logger.warning("Bot id is missing in request")
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return Response(
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{"error": "Bot id is required"}
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)
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try:
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self.bot = Bot.objects.get(id=bot_id)
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logger.info(f"Found bot with id {bot_id}")
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except Exception as e:
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logger.error(f"Bot not found: {str(e)}")
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return Response(
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{"error": "Bot not found"}, status=status.HTTP_404_NOT_FOUND
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)
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# Check is there a message for the current user and bot,if not, create a initial message
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handle_first_access(self.user, self.bot)
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# create a new message for the current request
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message_type = request.data.get("messageType")
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user_message = request.data.get("message")
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message_audio_url = request.data.get("messageAudioUrl")
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message_audio_base64 = request.data.get("messageAudioBase64")
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message_video_url = request.data.get("messageVideoUrl")
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message_video_base64 = request.data.get("messageVideoBase64")
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return_audio_as_base64 = request.data.get("returnAudioAsBase64", False)
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logger.info(f"Processing message of type {message_type} from user {self.user.id}")
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user_chat_message = create_user_message(
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self.user,
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self.bot,
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message_type,
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user_message,
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message_audio_url,
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message_video_url,
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message_audio_base64,
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message_video_base64
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)
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# prepare the history
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history = list(map(lambda message: {'role':message.sender, 'content':message.message},
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ChatMessage.objects.filter(bot=self.bot,user=self.user).all()))
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bot_chat_message = ask_kimi(self.user, self.bot, history)
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# 对于语音请求，合成语音返回
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if message_type == ChatMessage.MESSAGE_TYPE_AUDIO:
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audio_ser = get_audio_service()
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logger.info(f"Processing audio message: {bot_chat_message.message}")
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if return_audio_as_base64:
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# 生成音频并返回Base64编码
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audio_data = audio_ser.synthesize_speech_raw(bot_chat_message.message)
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import base64
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response_message_audio_base64 = base64.b64encode(audio_data).decode('utf-8')
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bot_chat_message.message_audio_url = None # 不使用URL
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bot_chat_message.message_type = ChatMessage.MESSAGE_TYPE_AUDIO
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bot_chat_message.save()
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logger.info("Generated audio as Base64 data")
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else:
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# 生成音频URL并返回
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response_message_audio_url = audio_ser.synthesize_speech(bot_chat_message.message)
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logger.info(f"Generated audio URL: {response_message_audio_url}")
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bot_chat_message.message_audio_url = response_message_audio_url
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bot_chat_message.message_type = ChatMessage.MESSAGE_TYPE_AUDIO
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bot_chat_message.save()
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logger.info(f"Bot response: {bot_chat_message.message}")
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# 构建响应数据
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response_data = {
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"text": bot_chat_message.message
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}
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# 添加用户的语音URL和识别的文字（如果是语音消息）
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if message_type == ChatMessage.MESSAGE_TYPE_AUDIO:
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response_data["user_message"] = user_chat_message.message
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if message_audio_url:
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response_data["user_audio_url"] = message_audio_url
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elif message_audio_base64:
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response_data["user_audio_base64"] = message_audio_base64
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# 如果有音频URL，添加到响应中
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if bot_chat_message.message_audio_url:
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response_data["audio_url"] = bot_chat_message.message_audio_url
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# 如果有返回Base64编码的音频数据
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if return_audio_as_base64 and message_type == ChatMessage.MESSAGE_TYPE_AUDIO:
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response_data["audio_base64"] = response_message_audio_base64
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# 如果有视频URL，添加到响应中
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if bot_chat_message.message_video_url:
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response_data["video_url"] = bot_chat_message.message_video_url
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return Response(
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response_data,
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status=status.HTTP_201_CREATED,
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)
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def ask_kimi(user: ParadiseUser, bot: Bot, history: list) -> ChatMessage:
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response = KIMI(history).get_response()
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# 移除开头和结尾的括号内容
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# 移除开头的中英文括号内容
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response = re.sub(r'^[\(（][^)）]*[\)）][\s]*', '', response)
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# 移除结尾的中英文括号内容
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response = re.sub(r'[\s]*[\(（][^)）]*[\)）]$', '', response)
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chat_message = ChatMessage.objects.create(
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user=user,
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bot=bot,
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message=response,
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sender=ChatMessage.SENDER_BOT,
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)
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chat_message.save()
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return chat_message
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def handle_first_access(user: ParadiseUser, bot: Bot):
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if not ChatMessage.objects.filter(user=user, bot=bot).exists():
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ChatMessage.objects.create(
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user=user,
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bot=bot,
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message=bot.description,
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sender=ChatMessage.SENDER_SYSTEM,
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message_type=ChatMessage.MESSAGE_TYPE_TEXT
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).save()
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def create_user_message(user: ParadiseUser, bot: Bot, message_type: str, user_message: str, message_audio_url: str, message_video_url: str, message_audio_base64: str = None, message_video_base64: str = None) -> ChatMessage:
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if message_type == ChatMessage.MESSAGE_TYPE_TEXT:
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user_chat_message = ChatMessage.objects.create(
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user=user,
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bot=bot,
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message=user_message,
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sender=ChatMessage.SENDER_USER,
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message_type=ChatMessage.MESSAGE_TYPE_TEXT
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)
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user_chat_message.save()
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logger.info(f"Created text message for user {user.id} and bot {bot.id}")
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return user_chat_message
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if message_type == ChatMessage.MESSAGE_TYPE_AUDIO:
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# 从 URL 获取音频文件内容或处理 Base64 音频数据
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audio_data = None
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audio_service = get_audio_service()
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# 检查是否提供了音频URL
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if message_audio_url:
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logger.info(f"Processing audio message from URL: {message_audio_url}")
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response = requests.get(message_audio_url)
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if response.status_code != 200:
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logger.error(f"Failed to download audio file: {response.status_code}")
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raise Exception("无法下载音频文件")
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audio_data = response.content
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elif message_audio_base64:
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# 处理Base64编码的音频数据
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logger.info("Processing audio message from Base64 data")
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import base64
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try:
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audio_data = base64.b64decode(message_audio_base64)
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except Exception as e:
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logger.error(f"Failed to decode base64 audio data: {str(e)}")
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raise Exception("无法解码Base64音频数据")
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if not audio_data:
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logger.error("No audio data provided (neither URL nor Base64)")
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raise Exception("未提供音频数据")
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message = audio_service.recognize_speech(audio_data)
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logger.info(f"Recognized speech message: {message}")
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user_chat_message = ChatMessage.objects.create(
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user=user,
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bot=bot,
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message=message,
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sender=ChatMessage.SENDER_USER,
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message_type=ChatMessage.MESSAGE_TYPE_AUDIO
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)
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if message_audio_url:
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user_chat_message.message_audio_url = message_audio_url
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user_chat_message.save()
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logger.info(f"Created audio message for user {user.id} and bot {bot.id}")
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return user_chat_message
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if message_type == ChatMessage.MESSAGE_TYPE_VIDEO:
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# 处理视频消息
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# 目前仅保存视频URL或转换Base64数据为文件URL的逻辑
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video_url = message_video_url
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# 处理Base64视频数据
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if not video_url and message_video_base64:
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logger.info("Processing video message from Base64 data")
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import base64
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try:
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# 这里需要将Base64解码并保存为文件，然后返回URL
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# 以下为示例代码，实际实现需要根据项目需求调整
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import os
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import uuid
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from django.conf import settings
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# 创建保存视频的目录
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video_dir = os.path.join(settings.MEDIA_ROOT, 'video')
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os.makedirs(video_dir, exist_ok=True)
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# 生成唯一文件名
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video_filename = f"{uuid.uuid4()}.mp4"
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video_path = os.path.join(video_dir, video_filename)
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# 解码并保存文件
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video_data = base64.b64decode(message_video_base64)
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with open(video_path, 'wb') as f:
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f.write(video_data)
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# 生成URL
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video_url = f"{settings.MEDIA_URL}video/{video_filename}"
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logger.info(f"Generated video URL from Base64: {video_url}")
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except Exception as e:
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logger.error(f"Failed to process base64 video data: {str(e)}")
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raise Exception("无法处理Base64视频数据")
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if not video_url:
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logger.error("No video URL or data provided")
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raise Exception("未提供视频数据")
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user_chat_message = ChatMessage.objects.create(
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user=user,
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bot=bot,
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message=user_message, # 可能需要从视频中提取文本
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sender=ChatMessage.SENDER_USER,
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message_type=ChatMessage.MESSAGE_TYPE_VIDEO,
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message_video_url=video_url
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)
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user_chat_message.save()
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logger.info(f"Created video message for user {user.id} and bot {bot.id}")
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return user_chat_message
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return None |