feat: 【Agent】AI conversation nodes support multimodal capabilities

apps/application/flow/step_node/ai_chat_step_node/i_chat_node.py

@@ -49,6 +49,10 @@ class ChatNodeSerializer(serializers.Serializer):
                                            label=_("Skill IDs"), )
     mcp_output_enable = serializers.BooleanField(required=False, default=True, label=_("Whether to enable MCP output"))
 
+    video_list = serializers.ListField(required=False, label=_("video"))
+
+    image_list = serializers.ListField(required=False, label=_("picture"))
+
 
 class IChatNode(INode):
     type = 'ai-chat-node'

apps/application/flow/step_node/ai_chat_step_node/impl/base_chat_node.py

@@ -6,10 +6,12 @@
     @date：2024/6/4 14:30
     @desc:
 """
+import base64
 import json
 import re
 import time
 from functools import reduce
+from imghdr import what
 from typing import List, Dict
 
 from django.db.models import QuerySet
@@ -25,6 +27,7 @@
 from common.utils.rsa_util import rsa_long_decrypt
 from common.utils.shared_resource_auth import filter_authorized_ids
 from common.utils.tool_code import ToolExecutor
+from knowledge.models import File
 from models_provider.models import Model
 from models_provider.tools import get_model_credential, get_model_instance_by_model_workspace_id
 from tools.models import Tool, ToolType
@@ -196,11 +199,11 @@ def execute(self, model_id, system, prompt, dialogue_number, history_chat_record
                                                    self.runtime_node_id)
         self.context['history_message'] = [{'content': message.content, 'role': message.type} for message in
                                            (history_message if history_message is not None else [])]
-        question = self.generate_prompt_question(prompt)
+        question = self.generate_prompt_question(prompt, chat_model)
         self.context['question'] = question.content
         system = self.workflow_manage.generate_prompt(system)
         self.context['system'] = system
-        message_list = self.generate_message_list(prompt, history_message)
+        message_list = self.generate_message_list(question, history_message)
         self.context['message_list'] = message_list
 
         # 过滤tool_id
@@ -386,11 +389,73 @@ def get_history_message(history_chat_record, dialogue_number, dialogue_type, run
                 message.content = re.sub(r'<form_rander>.*?<\/form_rander>', '', message.content, flags=re.DOTALL)
         return history_message
 
-    def generate_prompt_question(self, prompt):
-        return HumanMessage(self.workflow_manage.generate_prompt(prompt))
+    def generate_prompt_question(self, prompt, model):
+        image = self.get_image()
+        video = self.get_video()
+        videos = []
+        images = []
+        if image:
+            images = self._process_images(image)
+        if video:
+            videos = self._process_videos(video, model)
+        return HumanMessage(
+            content=[*videos, *images, {'type': 'text', 'text': self.workflow_manage.generate_prompt(prompt)}])
+
+    def get_image(self):
+        if 'image_list' in self.node_params_serializer.data:
+            image = self.workflow_manage.get_reference_field(self.node_params_serializer.data.get('image_list')[0],
+                                                             self.node_params_serializer.data.get('image_list')[1:])
+            return image
+        return None
+
+    def get_video(self):
+        if 'video_list' in self.node_params_serializer.data:
+            video = self.workflow_manage.get_reference_field(self.node_params_serializer.data.get('video_list')[0],
+                                                             self.node_params_serializer.data.get('video_list')[1:])
+            return video
+        return None
 
-    def generate_message_list(self, prompt: str, history_message):
-        return [*history_message, HumanMessage(self.workflow_manage.generate_prompt(prompt))]
+    def _process_videos(self, image, video_model):
+        videos = []
+        if isinstance(image, str) and image.startswith('http'):
+            videos.append({'type': 'video_url', 'video_url': {'url': image}})
+        elif image is not None and len(image) > 0:
+            for img in image:
+                if 'file_id' in img:
+                    file_id = img['file_id']
+                    file = QuerySet(File).filter(id=file_id).first()
+                    url = video_model.upload_file_and_get_url(file.get_bytes(), file.file_name)
+                    videos.append(
+                        {'type': 'video_url', 'video_url': {'url': url}})
+                elif 'url' in img and img['url'].startswith('http'):
+                    videos.append(
+                        {'type': 'video_url', 'video_url': {'url': img['url']}})
+        return videos
+
+    def _process_images(self, image):
+        """
+        处理图像数据，转换为模型可识别的格式
+        """
+        images = []
+        if isinstance(image, str) and image.startswith('http'):
+            images.append({'type': 'image_url', 'image_url': {'url': image}})
+        elif image is not None and len(image) > 0:
+            for img in image:
+                if 'file_id' in img:
+                    file_id = img['file_id']
+                    file = QuerySet(File).filter(id=file_id).first()
+                    image_bytes = file.get_bytes()
+                    base64_image = base64.b64encode(image_bytes).decode("utf-8")
+                    image_format = what(None, image_bytes)
+                    images.append(
+                        {'type': 'image_url', 'image_url': {'url': f'data:image/{image_format};base64,{base64_image}'}})
+                elif 'url' in img and img['url'].startswith('http'):
+                    images.append(
+                        {'type': 'image_url', 'image_url': {'url': img["url"]}})
+        return images
+
+    def generate_message_list(self, question, history_message):
+        return [*history_message, question]
 
     @staticmethod
     def reset_message_list(message_list: List[BaseMessage], answer_text):

ui/src/workflow/nodes/ai-chat-node/index.vue

@@ -170,7 +170,60 @@
             :step-strictly="true"
           />
         </el-form-item>
-
+        <el-form-item
+          :rules="{
+            type: 'array',
+            required: true,
+            message: $t('workflow.nodes.imageUnderstandNode.image.requiredMessage'),
+            trigger: 'change',
+          }"
+        >
+          <div class="flex align-center">
+            <div>
+              <span>{{ $t('workflow.nodes.imageUnderstandNode.image.label') }} </span>
+            </div>
+            <el-tooltip effect="dark" placement="right">
+              <template #content>
+                <div style="white-space: pre-wrap; font-family: monospace">{{ fileTooltip }}</div>
+              </template>
+              <AppIcon iconName="app-warning" class="app-warning-icon"></AppIcon>
+            </el-tooltip>
+          </div>
+          <NodeCascader
+            ref="nodeCascaderRef"
+            :nodeModel="nodeModel"
+            class="w-full"
+            :placeholder="$t('workflow.nodes.imageUnderstandNode.image.requiredMessage')"
+            v-model="chat_data.image_list"
+          />
+        </el-form-item>
+        <el-form-item
+          :rules="{
+            type: 'array',
+            required: false,
+            message: $t('workflow.nodes.videoUnderstandNode.video.requiredMessage'),
+            trigger: 'change',
+          }"
+        >
+          <div class="flex align-center">
+            <div>
+              <span>{{ $t('workflow.nodes.videoUnderstandNode.video.label') }} </span>
+            </div>
+            <el-tooltip effect="dark" placement="right">
+              <template #content>
+                <div style="white-space: pre-wrap; font-family: monospace">{{ fileTooltip }}</div>
+              </template>
+              <AppIcon iconName="app-warning" class="app-warning-icon"></AppIcon>
+            </el-tooltip>
+          </div>
+          <NodeCascader
+            ref="nodeCascaderRef"
+            :nodeModel="nodeModel"
+            class="w-full"
+            :placeholder="$t('workflow.nodes.videoUnderstandNode.video.requiredMessage')"
+            v-model="chat_data.video_list"
+          />
+        </el-form-item>
         <div class="mb-8 mt-12 flex-between">
           <span class="mr-4 lighter">
             {{ $t('views.tool.skill.title') }}
@@ -555,6 +608,7 @@ import { resetUrl } from '@/utils/common'
 import { relatedObject } from '@/utils/array.ts'
 import { WorkflowMode } from '@/enums/application'
 import ApplicationDialog from '@/views/application/component/ApplicationDialog.vue'
+import { fileTooltip } from '@/workflow/common/data.ts'
 const workflowMode = (inject('workflowMode') as WorkflowMode) || WorkflowMode.Application
 const getResourceDetail = inject('getResourceDetail') as any
 const route = useRoute()
@@ -604,7 +658,6 @@ const defaultPrompt = `${t('workflow.nodes.aiChatNode.defaultPrompt')}：
 ${t('views.problem.title')}：
 {{${t('workflow.nodes.startNode.label')}.question}}`
 
-
 const collapseData = reactive({
   MCP: true,
   tool: true,