refactor: 处理历史会话中图片的问题

apps/application/flow/step_node/document_extract_node/impl/base_document_extract_node.py

@@ -15,7 +15,7 @@ def execute(self, document, **kwargs):
 
         self.context['document_list'] = document
         content = ''
-        spliter = '\n-----------------------------------\n'
+        splitter = '\n-----------------------------------\n'
         if document is None:
             return NodeResult({'content': content}, {})
 
@@ -29,7 +29,7 @@ def execute(self, document, **kwargs):
                     # 回到文件头
                     buffer.seek(0)
                     file_content = split_handle.get_content(buffer)
-                    content += spliter + '## ' + doc['name'] + '\n' + file_content
+                    content += splitter + '## ' + doc['name'] + '\n' + file_content
                     break
 
         return NodeResult({'content': content}, {})

apps/application/flow/step_node/image_understand_step_node/i_image_understand_node.py

@@ -16,6 +16,8 @@ class ImageUnderstandNodeSerializer(serializers.Serializer):
     # 多轮对话数量
     dialogue_number = serializers.IntegerField(required=True, error_messages=ErrMessage.integer("多轮对话数量"))
 
+    dialogue_type = serializers.CharField(required=True, error_messages=ErrMessage.char("对话存储类型"))
+
     is_result = serializers.BooleanField(required=False, error_messages=ErrMessage.boolean('是否返回内容'))
 
     image_list = serializers.ListField(required=False, error_messages=ErrMessage.list("图片"))
@@ -32,7 +34,7 @@ def _run(self):
                                                        self.node_params_serializer.data.get('image_list')[1:])
         return self.execute(image=res, **self.node_params_serializer.data, **self.flow_params_serializer.data)
 
-    def execute(self, model_id, system, prompt, dialogue_number, history_chat_record, stream, chat_id,
+    def execute(self, model_id, system, prompt, dialogue_number, dialogue_type, history_chat_record, stream, chat_id,
                 chat_record_id,
                 image,
                 **kwargs) -> NodeResult:

apps/application/flow/step_node/image_understand_step_node/impl/base_image_understand_node.py

@@ -63,18 +63,18 @@ def save_context(self, details, workflow_manage):
         self.context['question'] = details.get('question')
         self.answer_text = details.get('answer')
 
-    def execute(self, model_id, system, prompt, dialogue_number, history_chat_record, stream, chat_id, chat_record_id,
+    def execute(self, model_id, system, prompt, dialogue_number, dialogue_type, history_chat_record, stream, chat_id, chat_record_id,
                 image,
                 **kwargs) -> NodeResult:
         image_model = get_model_instance_by_model_user_id(model_id, self.flow_params_serializer.data.get('user_id'))
         history_message = self.get_history_message(history_chat_record, dialogue_number)
         self.context['history_message'] = history_message
         question = self.generate_prompt_question(prompt)
         self.context['question'] = question.content
-        # todo 处理上传图片
         message_list = self.generate_message_list(image_model, system, prompt, history_message, image)
         self.context['message_list'] = message_list
         self.context['image_list'] = image
+        self.context['dialogue_type'] = dialogue_type
         if stream:
             r = image_model.stream(message_list)
             return NodeResult({'result': r, 'chat_model': image_model, 'message_list': message_list,
@@ -86,15 +86,31 @@ def execute(self, model_id, system, prompt, dialogue_number, history_chat_record
                                'history_message': history_message, 'question': question.content}, {},
                               _write_context=write_context)
 
-    @staticmethod
-    def get_history_message(history_chat_record, dialogue_number):
+    def get_history_message(self, history_chat_record, dialogue_number):
         start_index = len(history_chat_record) - dialogue_number
         history_message = reduce(lambda x, y: [*x, *y], [
-            [history_chat_record[index].get_human_message(), history_chat_record[index].get_ai_message()]
+            [self.generate_history_human_message(history_chat_record[index]), history_chat_record[index].get_ai_message()]
             for index in
             range(start_index if start_index > 0 else 0, len(history_chat_record))], [])
         return history_message
 
+    def generate_history_human_message(self, chat_record):
+
+        for data in chat_record.details.values():
+            if self.node.id == data['node_id'] and 'image_list' in data:
+                image_list = data['image_list']
+                if len(image_list) == 0 or data['dialogue_type'] == 'WORKFLOW':
+                    return HumanMessage(content=chat_record.problem_text)
+                file_id = image_list[0]['file_id']
+                file = QuerySet(File).filter(id=file_id).first()
+                base64_image = base64.b64encode(file.get_byte()).decode("utf-8")
+                return HumanMessage(
+                    content=[
+                        {'type': 'text', 'text': data['question']},
+                        {'type': 'image_url', 'image_url': {'url': f'data:image/jpeg;base64,{base64_image}'}},
+                    ])
+        return HumanMessage(content=chat_record.problem_text)
+
     def generate_prompt_question(self, prompt):
         return HumanMessage(self.workflow_manage.generate_prompt(prompt))
 
@@ -148,5 +164,6 @@ def get_details(self, index: int, **kwargs):
             'answer_tokens': self.context.get('answer_tokens'),
             'status': self.status,
             'err_message': self.err_message,
-            'image_list': self.context.get('image_list')
+            'image_list': self.context.get('image_list'),
+            'dialogue_type': self.context.get('dialogue_type')
         }

apps/application/views/chat_views.py

@@ -442,7 +442,8 @@ class UploadFile(APIView):
         def post(self, request: Request, application_id: str, chat_id: str):
             files = request.FILES.getlist('file')
             file_ids = []
-            meta = {'application_id': application_id, 'chat_id': chat_id}
+            debug = request.data.get("debug", "false").lower() == "true"
+            meta = {'application_id': application_id, 'chat_id': chat_id, 'debug': debug}
             for file in files:
                 file_url = FileSerializer(data={'file': file, 'meta': meta}).upload()
                 file_ids.append({'name': file.name, 'url': file_url, 'file_id': file_url.split('/')[-1]})

apps/common/job/__init__.py

@@ -8,8 +8,10 @@
 """
 from .client_access_num_job import *
 from .clean_chat_job import *
+from .clean_debug_file_job import *
 
 
 def run():
     client_access_num_job.run()
     clean_chat_job.run()
+    clean_debug_file_job.run()

apps/common/job/clean_debug_file_job.py

@@ -0,0 +1,36 @@
+# coding=utf-8
+
+import logging
+from datetime import timedelta
+
+from apscheduler.schedulers.background import BackgroundScheduler
+from django.db.models import Q
+from django.utils import timezone
+from django_apscheduler.jobstores import DjangoJobStore
+
+from common.lock.impl.file_lock import FileLock
+from dataset.models import File
+
+scheduler = BackgroundScheduler()
+scheduler.add_jobstore(DjangoJobStore(), "default")
+lock = FileLock()
+
+
+def clean_debug_file():
+    logging.getLogger("max_kb").info('开始清理debug文件')
+    two_hours_ago = timezone.now() - timedelta(hours=2)
+    # 删除对应的文件
+    File.objects.filter(Q(create_time__lt=two_hours_ago) & Q(meta__debug=True)).delete()
+    logging.getLogger("max_kb").info('结束清理debug文件')
+
+
+def run():
+    if lock.try_lock('clean_debug_file', 30 * 30):
+        try:
+            scheduler.start()
+            clean_debug_file_job = scheduler.get_job(job_id='clean_debug_file')
+            if clean_debug_file_job is not None:
+                clean_debug_file_job.remove()
+            scheduler.add_job(clean_debug_file, 'cron', hour='2', minute='0', second='0', id='clean_debug_file')
+        finally:
+            lock.un_lock('clean_debug_file')

ui/src/components/ai-chat/component/chat-input-operate/index.vue

@@ -100,6 +100,7 @@ const props = withDefaults(
     appId?: string
     chatId: string
     sendMessage: (question: string, other_params_data?: any, chat?: chatType) => void
+    openChatId: () => Promise<string>
   }>(),
   {
     applicationDetails: () => ({}),
@@ -165,8 +166,14 @@ const uploadFile = async (file: any, fileList: any) => {
   }
 
   if (!chatId_context.value) {
-    const res = await applicationApi.getChatOpen(props.applicationDetails.id as string)
-    chatId_context.value = res.data
+    const res = await props.openChatId()
+    chatId_context.value = res
+  }
+
+  if (props.type === 'debug-ai-chat') {
+    formData.append('debug', 'true')
+  } else {
+    formData.append('debug', 'false')
   }
 
   applicationApi

ui/src/components/ai-chat/index.vue

@@ -38,6 +38,7 @@
       :is-mobile="isMobile"
       :type="type"
       :send-message="sendMessage"
+      :open-chat-id="openChatId"
       v-model:chat-id="chartOpenId"
       v-model:loading="loading"
       v-if="type !== 'log'"

ui/src/workflow/nodes/image-understand/index.vue

@@ -128,7 +128,16 @@
             @submitDialog="submitDialog"
           />
         </el-form-item>
-        <el-form-item label="历史聊天记录">
+        <el-form-item>
+          <template #label>
+            <div class="flex-between">
+              <div>历史聊天记录</div>
+              <el-select v-model="form_data.dialogue_type" class="w-120">
+                <el-option label="节点" value="NODE"/>
+                <el-option label="工作流" value="WORKFLOW"/>
+              </el-select>
+            </div>
+          </template>
           <el-input-number
             v-model="form_data.dialogue_number"
             :min="0"
@@ -213,6 +222,7 @@ const form = {
   system: '',
   prompt: defaultPrompt,
   dialogue_number: 0,
+  dialogue_type: 'NODE',
   is_result: true,
   temperature: null,
   max_tokens: null,