Merge branch 'v2' into knowledge_workflow

# Conflicts:
#	apps/application/flow/workflow_manage.py
#	apps/common/utils/tool_code.py
#	ui/src/views/tool/component/ToolListContainer.vue

Author: shaohuzhang1

.github/workflows/build-and-push-vector-model.yml

@@ -5,7 +5,7 @@ on:
     inputs:
       dockerImageTag:
         description: 'Docker Image Tag'
-        default: 'v2.0.2'
+        default: 'v2.0.3'
         required: true
       architecture:
         description: 'Architecture'

.github/workflows/build-and-push.yml

@@ -7,7 +7,7 @@ on:
     inputs:
       dockerImageTag:
         description: 'Image Tag'
-        default: 'v2.3.0-dev'
+        default: 'v2.4.0-dev'
         required: true
       dockerImageTagWithLatest:
         description: '是否发布latest tag（正式发版时选择，测试版本切勿选择）'

.gitignore

@@ -188,4 +188,5 @@ apps/models_provider/impl/*/icon/
 apps/models_provider/impl/tencent_model_provider/credential/stt.py
 apps/models_provider/impl/tencent_model_provider/model/stt.py
 tmp/
-config.yml
+config.yml
+.SANDBOX_BANNED_HOSTS

apps/application/chat_pipeline/step/chat_step/impl/base_chat_step.py

@@ -93,6 +93,7 @@ def event_content(response,
                 reasoning_content_chunk = chunk.additional_kwargs.get('reasoning_content', '')
             else:
                 reasoning_content_chunk = reasoning_chunk.get('reasoning_content')
+            content_chunk = reasoning._normalize_content(content_chunk)
             all_text += content_chunk
             if reasoning_content_chunk is None:
                 reasoning_content_chunk = ''
@@ -191,23 +192,17 @@ def execute(self, message_list: List[BaseMessage],
                                        manage, padding_problem_text, chat_user_id, chat_user_type,
                                        no_references_setting,
                                        model_setting,
-                                       mcp_enable, mcp_tool_ids, mcp_servers, mcp_source, tool_enable, tool_ids, mcp_output_enable)
+                                       mcp_enable, mcp_tool_ids, mcp_servers, mcp_source, tool_enable, tool_ids,
+                                       mcp_output_enable)
         else:
             return self.execute_block(message_list, chat_id, problem_text, post_response_handler, chat_model,
                                       paragraph_list,
                                       manage, padding_problem_text, chat_user_id, chat_user_type, no_references_setting,
                                       model_setting,
-                                      mcp_enable, mcp_tool_ids, mcp_servers, mcp_source, tool_enable, tool_ids, mcp_output_enable)
+                                      mcp_enable, mcp_tool_ids, mcp_servers, mcp_source, tool_enable, tool_ids,
+                                      mcp_output_enable)
 
     def get_details(self, manage, **kwargs):
-        # 删除临时生成的MCP代码文件
-        if self.context.get('execute_ids'):
-            executor = ToolExecutor(CONFIG.get('SANDBOX'))
-            # 清理工具代码文件，延时删除，避免文件被占用
-            for tool_id in self.context.get('execute_ids'):
-                code_path = f'{executor.sandbox_path}/execute/{tool_id}.py'
-                if os.path.exists(code_path):
-                    os.remove(code_path)
         return {
             'step_type': 'chat_step',
             'run_time': self.context['run_time'],
@@ -254,7 +249,6 @@ def _handle_mcp_request(self, mcp_enable, tool_enable, mcp_source, mcp_servers,
         if tool_enable:
             if tool_ids and len(tool_ids) > 0:  # 如果有工具ID，则将其转换为MCP
                 self.context['tool_ids'] = tool_ids
-                self.context['execute_ids'] = []
                 for tool_id in tool_ids:
                     tool = QuerySet(Tool).filter(id=tool_id).first()
                     if tool is None or tool.is_active is False:
@@ -264,17 +258,15 @@ def _handle_mcp_request(self, mcp_enable, tool_enable, mcp_source, mcp_servers,
                         params = json.loads(rsa_long_decrypt(tool.init_params))
                     else:
                         params = {}
-                    _id, tool_config = executor.get_tool_mcp_config(tool.code, params)
+                    tool_config = executor.get_tool_mcp_config(tool.code, params)
 
-                    self.context['execute_ids'].append(_id)
                     mcp_servers_config[str(tool.id)] = tool_config
 
         if len(mcp_servers_config) > 0:
             return mcp_response_generator(chat_model, message_list, json.dumps(mcp_servers_config), mcp_output_enable)
 
         return None
 
-
     def get_stream_result(self, message_list: List[BaseMessage],
                           chat_model: BaseChatModel = None,
                           paragraph_list=None,
@@ -304,7 +296,8 @@ def get_stream_result(self, message_list: List[BaseMessage],
         else:
             # 处理 MCP 请求
             mcp_result = self._handle_mcp_request(
-                mcp_enable, tool_enable, mcp_source, mcp_servers, mcp_tool_ids, tool_ids, mcp_output_enable, chat_model, message_list,
+                mcp_enable, tool_enable, mcp_source, mcp_servers, mcp_tool_ids, tool_ids, mcp_output_enable, chat_model,
+                message_list,
             )
             if mcp_result:
                 return mcp_result, True
@@ -329,7 +322,8 @@ def execute_stream(self, message_list: List[BaseMessage],
                        tool_ids=None,
                        mcp_output_enable=True):
         chat_result, is_ai_chat = self.get_stream_result(message_list, chat_model, paragraph_list,
-                                                         no_references_setting, problem_text, mcp_enable, mcp_tool_ids, mcp_servers, mcp_source, tool_enable, tool_ids,
+                                                         no_references_setting, problem_text, mcp_enable, mcp_tool_ids,
+                                                         mcp_servers, mcp_source, tool_enable, tool_ids,
                                                          mcp_output_enable)
         chat_record_id = uuid.uuid7()
         r = StreamingHttpResponse(
@@ -404,7 +398,9 @@ def execute_block(self, message_list: List[BaseMessage],
         # 调用模型
         try:
             chat_result, is_ai_chat = self.get_block_result(message_list, chat_model, paragraph_list,
-                                                            no_references_setting, problem_text, mcp_enable, mcp_tool_ids, mcp_servers, mcp_source, tool_enable, tool_ids, mcp_output_enable)
+                                                            no_references_setting, problem_text, mcp_enable,
+                                                            mcp_tool_ids, mcp_servers, mcp_source, tool_enable,
+                                                            tool_ids, mcp_output_enable)
             if is_ai_chat:
                 request_token = chat_model.get_num_tokens_from_messages(message_list)
                 response_token = chat_model.get_num_tokens(chat_result.content)
@@ -416,10 +412,10 @@ def execute_block(self, message_list: List[BaseMessage],
             reasoning_result_end = reasoning.get_end_reasoning_content()
             content = reasoning_result.get('content') + reasoning_result_end.get('content')
             if 'reasoning_content' in chat_result.response_metadata:
-                reasoning_content = chat_result.response_metadata.get('reasoning_content', '')
+                reasoning_content = (chat_result.response_metadata.get('reasoning_content', '') or '')
             else:
-                reasoning_content = reasoning_result.get('reasoning_content') + reasoning_result_end.get(
-                    'reasoning_content')
+                reasoning_content = (reasoning_result.get('reasoning_content') or "") + (reasoning_result_end.get(
+                    'reasoning_content') or "")
             post_response_handler.handler(chat_id, chat_record_id, paragraph_list, problem_text,
                                           content, manage, self, padding_problem_text,
                                           reasoning_content=reasoning_content)

apps/application/flow/i_step_node.py

@@ -95,6 +95,7 @@ def handler(self, workflow):
                 application_public_access_client.access_num = application_public_access_client.access_num + 1
                 application_public_access_client.intraday_access_num = application_public_access_client.intraday_access_num + 1
                 application_public_access_client.save()
+        self.chat_info = None
 
 
 class KnowledgeWorkflowPostHandler(WorkFlowPostHandler):

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

@@ -108,9 +108,9 @@ def write_context(node_variable: Dict, workflow_variable: Dict, node: INode, wor
     content = reasoning_result.get('content') + reasoning_result_end.get('content')
     meta = {**response.response_metadata, **response.additional_kwargs}
     if 'reasoning_content' in meta:
-        reasoning_content = meta.get('reasoning_content', '')
+        reasoning_content = (meta.get('reasoning_content', '') or '')
     else:
-        reasoning_content = reasoning_result.get('reasoning_content') + reasoning_result_end.get('reasoning_content')
+        reasoning_content = (reasoning_result.get('reasoning_content') or '') + (reasoning_result_end.get('reasoning_content') or '')
     _write_context(node_variable, workflow_variable, node, workflow, content, reasoning_content)
 
 
@@ -233,7 +233,6 @@ def _handle_mcp_request(self, mcp_enable, tool_enable, mcp_source, mcp_servers,
         if tool_enable:
             if tool_ids and len(tool_ids) > 0:  # 如果有工具ID，则将其转换为MCP
                 self.context['tool_ids'] = tool_ids
-                self.context['execute_ids'] = []
                 for tool_id in tool_ids:
                     tool = QuerySet(Tool).filter(id=tool_id).first()
                     if not tool.is_active:
@@ -243,9 +242,8 @@ def _handle_mcp_request(self, mcp_enable, tool_enable, mcp_source, mcp_servers,
                         params = json.loads(rsa_long_decrypt(tool.init_params))
                     else:
                         params = {}
-                    _id, tool_config = executor.get_tool_mcp_config(tool.code, params)
+                    tool_config = executor.get_tool_mcp_config(tool.code, params)
 
-                    self.context['execute_ids'].append(_id)
                     mcp_servers_config[str(tool.id)] = tool_config
 
         if len(mcp_servers_config) > 0:
@@ -307,14 +305,6 @@ def reset_message_list(message_list: List[BaseMessage], answer_text):
         return result
 
     def get_details(self, index: int, **kwargs):
-        # 删除临时生成的MCP代码文件
-        if self.context.get('execute_ids'):
-            executor = ToolExecutor(CONFIG.get('SANDBOX'))
-            # 清理工具代码文件，延时删除，避免文件被占用
-            for tool_id in self.context.get('execute_ids'):
-                code_path = f'{executor.sandbox_path}/execute/{tool_id}.py'
-                if os.path.exists(code_path):
-                    os.remove(code_path)
         return {
             'name': self.node.properties.get('stepName'),
             "index": index,

apps/application/flow/step_node/image_to_video_step_node/impl/base_image_to_video_node.py

@@ -74,7 +74,7 @@ def execute(self, model_id, prompt, negative_prompt, dialogue_number, dialogue_t
     def get_file_base64(self, image_url):
         try:
             if isinstance(image_url, list):
-                image_url = image_url[0].get('file_id')
+                image_url = image_url[0].get('file_id') if 'file_id' in image_url[0] else image_url[0].get('url')
             if isinstance(image_url, str) and not image_url.startswith('http'):
                 file = QuerySet(File).filter(id=image_url).first()
                 file_bytes = file.get_bytes()

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

@@ -131,11 +131,18 @@ def generate_history_human_message_for_details(self, chat_record):
                 image_list = data['image_list']
                 if len(image_list) == 0 or data['dialogue_type'] == 'WORKFLOW':
                     return HumanMessage(content=chat_record.problem_text)
-                file_id_list = [image.get('file_id') for image in image_list]
+
+                file_id_list = []
+                url_list = []
+                for image in image_list:
+                    if 'file_id' in image:
+                        file_id_list.append(image.get('file_id'))
+                    elif 'url' in image:
+                        url_list.append(image.get('url'))
                 return HumanMessage(content=[
                     {'type': 'text', 'text': data['question']},
-                    *[{'type': 'image_url', 'image_url': {'url': f'./oss/file/{file_id}'}} for file_id in file_id_list]
-
+                    *[{'type': 'image_url', 'image_url': {'url': f'./oss/file/{file_id}'}} for file_id in file_id_list],
+                    *[{'type': 'image_url', 'image_url': {'url': url}} for url in url_list]
                 ])
         return HumanMessage(content=chat_record.problem_text)
 
@@ -155,13 +162,22 @@ def generate_history_human_message(self, chat_record):
                 image_list = data['image_list']
                 if len(image_list) == 0 or data['dialogue_type'] == 'WORKFLOW':
                     return HumanMessage(content=chat_record.problem_text)
-                image_base64_list = [file_id_to_base64(image.get('file_id')) for image in image_list]
+                file_id_list = []
+                url_list = []
+                for image in image_list:
+                    if 'file_id' in image:
+                        file_id_list.append(image.get('file_id'))
+                    elif 'url' in image:
+                        url_list.append(image.get('url'))
+                image_base64_list = [file_id_to_base64(file_id) for file_id in file_id_list]
+
                 return HumanMessage(
                     content=[
                         {'type': 'text', 'text': data['question']},
                         *[{'type': 'image_url',
                            'image_url': {'url': f'data:image/{base64_image[1]};base64,{base64_image[0]}'}} for
-                          base64_image in image_base64_list]
+                          base64_image in image_base64_list],
+                        *[{'type': 'image_url', 'image_url': url} for url in url_list]
                     ])
         return HumanMessage(content=chat_record.problem_text)
 
@@ -177,13 +193,17 @@ def _process_images(self, image):
             images.append({'type': 'image_url', 'image_url': {'url': image}})
         elif image is not None and len(image) > 0:
             for img in image:
-                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}'}})
+                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, image_model, system: str, prompt: str, history_message, image):

apps/application/flow/step_node/loop_node/impl/base_loop_node.py

@@ -226,11 +226,14 @@ class BaseLoopNode(ILoopNode):
     def save_context(self, details, workflow_manage):
         self.context['loop_context_data'] = details.get('loop_context_data')
         self.context['loop_answer_data'] = details.get('loop_answer_data')
+        self.context['loop_node_data'] = details.get('loop_node_data')
         self.context['result'] = details.get('result')
         self.context['params'] = details.get('params')
         self.context['run_time'] = details.get('run_time')
         self.context['index'] = details.get('current_index')
         self.context['item'] = details.get('current_item')
+        for key, value in (details.get('loop_context_data') or {}).items():
+            self.context[key] = value
         self.answer_text = ""
 
     def get_answer_list(self) -> List[Answer] | None:

apps/application/flow/step_node/text_to_video_step_node/impl/base_text_to_video_node.py

@@ -37,7 +37,6 @@ def execute(self, model_id, prompt, negative_prompt, dialogue_number, dialogue_t
         self.context['dialogue_type'] = dialogue_type
         self.context['negative_prompt'] = self.generate_prompt_question(negative_prompt)
         video_urls = ttv_model.generate_video(question, negative_prompt)
-        print('video_urls', video_urls)
         # 保存图片
         if video_urls is None:
             return NodeResult({'answer': gettext('Failed to generate video')}, {})