fix: 修复创建web知识库时,向量模型错误 (#948)

(cherry picked from commit 3edb1f29b1)

apps/application/flow/i_step_node.py

@@ -10,6 +10,7 @@ import time
 from abc import abstractmethod
 from typing import Type, Dict, List
 
+from django.core import cache
 from django.db.models import QuerySet
 from rest_framework import serializers
 
@@ -18,7 +19,6 @@ from application.models.api_key_model import ApplicationPublicAccessClient
 from common.constants.authentication_type import AuthenticationType
 from common.field.common import InstanceField
 from common.util.field_message import ErrMessage
-from django.core import cache
 
 chat_cache = cache.caches['chat_cache']
 
@@ -27,9 +27,14 @@ def write_context(step_variable: Dict, global_variable: Dict, node, workflow):
     if step_variable is not None:
         for key in step_variable:
             node.context[key] = step_variable[key]
+        if workflow.is_result() and 'answer' in step_variable:
+            answer = step_variable['answer'] + '\n'
+            yield answer
+            workflow.answer += answer
     if global_variable is not None:
         for key in global_variable:
             workflow.context[key] = global_variable[key]
+    node.context['run_time'] = time.time() - node.context['start_time']
 
 
 class WorkFlowPostHandler:
@@ -70,18 +75,14 @@ class WorkFlowPostHandler:
 
 
 class NodeResult:
-    def __init__(self, node_variable: Dict, workflow_variable: Dict, _to_response=None, _write_context=write_context):
+    def __init__(self, node_variable: Dict, workflow_variable: Dict,
+                 _write_context=write_context):
         self._write_context = _write_context
         self.node_variable = node_variable
         self.workflow_variable = workflow_variable
-        self._to_response = _to_response
 
     def write_context(self, node, workflow):
-        self._write_context(self.node_variable, self.workflow_variable, node, workflow)
+        return self._write_context(self.node_variable, self.workflow_variable, node, workflow)
-
-    def to_response(self, chat_id, chat_record_id, node, workflow, post_handler: WorkFlowPostHandler):
-        return self._to_response(chat_id, chat_record_id, self.node_variable, self.workflow_variable, node, workflow,
-                                 post_handler)
 
     def is_assertion_result(self):
         return 'branch_id' in self.node_variable

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

@@ -22,6 +22,8 @@ class ChatNodeSerializer(serializers.Serializer):
     # 多轮对话数量
     dialogue_number = serializers.IntegerField(required=True, error_messages=ErrMessage.integer("多轮对话数量"))
 
+    is_result = serializers.BooleanField(required=False, error_messages=ErrMessage.boolean('是否返回内容'))
+
 
 class IChatNode(INode):
     type = 'ai-chat-node'

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

@@ -13,12 +13,25 @@ from typing import List, Dict
 from langchain.schema import HumanMessage, SystemMessage
 from langchain_core.messages import BaseMessage
 
-from application.flow import tools
 from application.flow.i_step_node import NodeResult, INode
 from application.flow.step_node.ai_chat_step_node.i_chat_node import IChatNode
 from setting.models_provider.tools import get_model_instance_by_model_user_id
 
 
+def _write_context(node_variable: Dict, workflow_variable: Dict, node: INode, workflow, answer: str):
+    chat_model = node_variable.get('chat_model')
+    message_tokens = chat_model.get_num_tokens_from_messages(node_variable.get('message_list'))
+    answer_tokens = chat_model.get_num_tokens(answer)
+    node.context['message_tokens'] = message_tokens
+    node.context['answer_tokens'] = answer_tokens
+    node.context['answer'] = answer
+    node.context['history_message'] = node_variable['history_message']
+    node.context['question'] = node_variable['question']
+    node.context['run_time'] = time.time() - node.context['start_time']
+    if workflow.is_result():
+        workflow.answer += answer
+
+
 def write_context_stream(node_variable: Dict, workflow_variable: Dict, node: INode, workflow):
     """
     写入上下文数据 (流式)
@@ -31,15 +44,10 @@ def write_context_stream(node_variable: Dict, workflow_variable: Dict, node: INo
     answer = ''
     for chunk in response:
         answer += chunk.content
-    chat_model = node_variable.get('chat_model')
+        yield chunk.content
-    message_tokens = chat_model.get_num_tokens_from_messages(node_variable.get('message_list'))
+    answer += '\n'
-    answer_tokens = chat_model.get_num_tokens(answer)
+    yield '\n'
-    node.context['message_tokens'] = message_tokens
+    _write_context(node_variable, workflow_variable, node, workflow, answer)
-    node.context['answer_tokens'] = answer_tokens
-    node.context['answer'] = answer
-    node.context['history_message'] = node_variable['history_message']
-    node.context['question'] = node_variable['question']
-    node.context['run_time'] = time.time() - node.context['start_time']
 
 
 def write_context(node_variable: Dict, workflow_variable: Dict, node: INode, workflow):
@@ -51,71 +59,8 @@ def write_context(node_variable: Dict, workflow_variable: Dict, node: INode, wor
     @param workflow:           工作流管理器
     """
     response = node_variable.get('result')
-    chat_model = node_variable.get('chat_model')
     answer = response.content
-    message_tokens = chat_model.get_num_tokens_from_messages(node_variable.get('message_list'))
+    _write_context(node_variable, workflow_variable, node, workflow, answer)
-    answer_tokens = chat_model.get_num_tokens(answer)
-    node.context['message_tokens'] = message_tokens
-    node.context['answer_tokens'] = answer_tokens
-    node.context['answer'] = answer
-    node.context['history_message'] = node_variable['history_message']
-    node.context['question'] = node_variable['question']
-
-
-def get_to_response_write_context(node_variable: Dict, node: INode):
-    def _write_context(answer, status=200):
-        chat_model = node_variable.get('chat_model')
-
-        if status == 200:
-            answer_tokens = chat_model.get_num_tokens(answer)
-            message_tokens = chat_model.get_num_tokens_from_messages(node_variable.get('message_list'))
-        else:
-            answer_tokens = 0
-            message_tokens = 0
-        node.err_message = answer
-        node.status = status
-        node.context['message_tokens'] = message_tokens
-        node.context['answer_tokens'] = answer_tokens
-        node.context['answer'] = answer
-        node.context['run_time'] = time.time() - node.context['start_time']
-
-    return _write_context
-
-
-def to_stream_response(chat_id, chat_record_id, node_variable: Dict, workflow_variable: Dict, node, workflow,
-                       post_handler):
-    """
-    将流式数据 转换为 流式响应
-    @param chat_id:           会话id
-    @param chat_record_id:    对话记录id
-    @param node_variable:     节点数据
-    @param workflow_variable: 工作流数据
-    @param node:              节点
-    @param workflow:          工作流管理器
-    @param post_handler:      后置处理器 输出结果后执行
-    @return: 流式响应
-    """
-    response = node_variable.get('result')
-    _write_context = get_to_response_write_context(node_variable, node)
-    return tools.to_stream_response(chat_id, chat_record_id, response, workflow, _write_context, post_handler)
-
-
-def to_response(chat_id, chat_record_id, node_variable: Dict, workflow_variable: Dict, node, workflow,
-                post_handler):
-    """
-    将结果转换
-    @param chat_id:           会话id
-    @param chat_record_id:    对话记录id
-    @param node_variable:     节点数据
-    @param workflow_variable: 工作流数据
-    @param node:              节点
-    @param workflow:          工作流管理器
-    @param post_handler:      后置处理器
-    @return: 响应
-    """
-    response = node_variable.get('result')
-    _write_context = get_to_response_write_context(node_variable, node)
-    return tools.to_response(chat_id, chat_record_id, response, workflow, _write_context, post_handler)
 
 
 class BaseChatNode(IChatNode):
@@ -132,13 +77,12 @@ class BaseChatNode(IChatNode):
             r = chat_model.stream(message_list)
             return NodeResult({'result': r, 'chat_model': chat_model, 'message_list': message_list,
                                'history_message': history_message, 'question': question.content}, {},
-                              _write_context=write_context_stream,
+                              _write_context=write_context_stream)
-                              _to_response=to_stream_response)
         else:
             r = chat_model.invoke(message_list)
             return NodeResult({'result': r, 'chat_model': chat_model, 'message_list': message_list,
                                'history_message': history_message, 'question': question.content}, {},
-                              _write_context=write_context, _to_response=to_response)
+                              _write_context=write_context)
 
     @staticmethod
     def get_history_message(history_chat_record, dialogue_number):

apps/application/flow/step_node/direct_reply_node/i_reply_node.py

@@ -20,6 +20,7 @@ class ReplyNodeParamsSerializer(serializers.Serializer):
     fields = serializers.ListField(required=False, error_messages=ErrMessage.list("引用字段"))
     content = serializers.CharField(required=False, allow_blank=True, allow_null=True,
                                     error_messages=ErrMessage.char("直接回答内容"))
+    is_result = serializers.BooleanField(required=False, error_messages=ErrMessage.boolean('是否返回内容'))
 
     def is_valid(self, *, raise_exception=False):
         super().is_valid(raise_exception=True)

apps/application/flow/step_node/direct_reply_node/impl/base_reply_node.py

@@ -6,69 +6,19 @@
     @date：2024/6/11 17:25
     @desc:
 """
-from typing import List, Dict
+from typing import List
 
-from langchain_core.messages import AIMessage, AIMessageChunk
+from application.flow.i_step_node import NodeResult
-
-from application.flow import tools
-from application.flow.i_step_node import NodeResult, INode
 from application.flow.step_node.direct_reply_node.i_reply_node import IReplyNode
 
 
-def get_to_response_write_context(node_variable: Dict, node: INode):
-    def _write_context(answer, status=200):
-        node.context['answer'] = answer
-
-    return _write_context
-
-
-def to_stream_response(chat_id, chat_record_id, node_variable: Dict, workflow_variable: Dict, node, workflow,
-                       post_handler):
-    """
-    将流式数据 转换为 流式响应
-    @param chat_id:           会话id
-    @param chat_record_id:    对话记录id
-    @param node_variable:     节点数据
-    @param workflow_variable: 工作流数据
-    @param node:              节点
-    @param workflow:          工作流管理器
-    @param post_handler:      后置处理器 输出结果后执行
-    @return: 流式响应
-    """
-    response = node_variable.get('result')
-    _write_context = get_to_response_write_context(node_variable, node)
-    return tools.to_stream_response(chat_id, chat_record_id, response, workflow, _write_context, post_handler)
-
-
-def to_response(chat_id, chat_record_id, node_variable: Dict, workflow_variable: Dict, node, workflow,
-                post_handler):
-    """
-    将结果转换
-    @param chat_id:           会话id
-    @param chat_record_id:    对话记录id
-    @param node_variable:     节点数据
-    @param workflow_variable: 工作流数据
-    @param node:              节点
-    @param workflow:          工作流管理器
-    @param post_handler:      后置处理器
-    @return: 响应
-    """
-    response = node_variable.get('result')
-    _write_context = get_to_response_write_context(node_variable, node)
-    return tools.to_response(chat_id, chat_record_id, response, workflow, _write_context, post_handler)
-
-
 class BaseReplyNode(IReplyNode):
     def execute(self, reply_type, stream, fields=None, content=None, **kwargs) -> NodeResult:
         if reply_type == 'referencing':
             result = self.get_reference_content(fields)
         else:
             result = self.generate_reply_content(content)
-        if stream:
+        return NodeResult({'answer': result}, {})
-            return NodeResult({'result': iter([AIMessageChunk(content=result)]), 'answer': result}, {},
-                              _to_response=to_stream_response)
-        else:
-            return NodeResult({'result': AIMessage(content=result), 'answer': result}, {}, _to_response=to_response)
 
     def generate_reply_content(self, prompt):
         return self.workflow_manage.generate_prompt(prompt)

apps/application/flow/step_node/question_node/i_question_node.py

@@ -22,6 +22,8 @@ class QuestionNodeSerializer(serializers.Serializer):
     # 多轮对话数量
     dialogue_number = serializers.IntegerField(required=True, error_messages=ErrMessage.integer("多轮对话数量"))
 
+    is_result = serializers.BooleanField(required=False, error_messages=ErrMessage.boolean('是否返回内容'))
+
 
 class IQuestionNode(INode):
     type = 'question-node'

apps/application/flow/step_node/question_node/impl/base_question_node.py

@@ -13,12 +13,25 @@ from typing import List, Dict
 from langchain.schema import HumanMessage, SystemMessage
 from langchain_core.messages import BaseMessage
 
-from application.flow import tools
 from application.flow.i_step_node import NodeResult, INode
 from application.flow.step_node.question_node.i_question_node import IQuestionNode
 from setting.models_provider.tools import get_model_instance_by_model_user_id
 
 
+def _write_context(node_variable: Dict, workflow_variable: Dict, node: INode, workflow, answer: str):
+    chat_model = node_variable.get('chat_model')
+    message_tokens = chat_model.get_num_tokens_from_messages(node_variable.get('message_list'))
+    answer_tokens = chat_model.get_num_tokens(answer)
+    node.context['message_tokens'] = message_tokens
+    node.context['answer_tokens'] = answer_tokens
+    node.context['answer'] = answer
+    node.context['history_message'] = node_variable['history_message']
+    node.context['question'] = node_variable['question']
+    node.context['run_time'] = time.time() - node.context['start_time']
+    if workflow.is_result():
+        workflow.answer += answer
+
+
 def write_context_stream(node_variable: Dict, workflow_variable: Dict, node: INode, workflow):
     """
     写入上下文数据 (流式)
@@ -31,15 +44,10 @@ def write_context_stream(node_variable: Dict, workflow_variable: Dict, node: INo
     answer = ''
     for chunk in response:
         answer += chunk.content
-    chat_model = node_variable.get('chat_model')
+        yield chunk.content
-    message_tokens = chat_model.get_num_tokens_from_messages(node_variable.get('message_list'))
+    answer += '\n'
-    answer_tokens = chat_model.get_num_tokens(answer)
+    yield '\n'
-    node.context['message_tokens'] = message_tokens
+    _write_context(node_variable, workflow_variable, node, workflow, answer)
-    node.context['answer_tokens'] = answer_tokens
-    node.context['answer'] = answer
-    node.context['history_message'] = node_variable['history_message']
-    node.context['question'] = node_variable['question']
-    node.context['run_time'] = time.time() - node.context['start_time']
 
 
 def write_context(node_variable: Dict, workflow_variable: Dict, node: INode, workflow):
@@ -51,71 +59,8 @@ def write_context(node_variable: Dict, workflow_variable: Dict, node: INode, wor
     @param workflow:           工作流管理器
     """
     response = node_variable.get('result')
-    chat_model = node_variable.get('chat_model')
     answer = response.content
-    message_tokens = chat_model.get_num_tokens_from_messages(node_variable.get('message_list'))
+    _write_context(node_variable, workflow_variable, node, workflow, answer)
-    answer_tokens = chat_model.get_num_tokens(answer)
-    node.context['message_tokens'] = message_tokens
-    node.context['answer_tokens'] = answer_tokens
-    node.context['answer'] = answer
-    node.context['history_message'] = node_variable['history_message']
-    node.context['question'] = node_variable['question']
-
-
-def get_to_response_write_context(node_variable: Dict, node: INode):
-    def _write_context(answer, status=200):
-        chat_model = node_variable.get('chat_model')
-
-        if status == 200:
-            answer_tokens = chat_model.get_num_tokens(answer)
-            message_tokens = chat_model.get_num_tokens_from_messages(node_variable.get('message_list'))
-        else:
-            answer_tokens = 0
-            message_tokens = 0
-        node.err_message = answer
-        node.status = status
-        node.context['message_tokens'] = message_tokens
-        node.context['answer_tokens'] = answer_tokens
-        node.context['answer'] = answer
-        node.context['run_time'] = time.time() - node.context['start_time']
-
-    return _write_context
-
-
-def to_stream_response(chat_id, chat_record_id, node_variable: Dict, workflow_variable: Dict, node, workflow,
-                       post_handler):
-    """
-    将流式数据 转换为 流式响应
-    @param chat_id:           会话id
-    @param chat_record_id:    对话记录id
-    @param node_variable:     节点数据
-    @param workflow_variable: 工作流数据
-    @param node:              节点
-    @param workflow:          工作流管理器
-    @param post_handler:      后置处理器 输出结果后执行
-    @return: 流式响应
-    """
-    response = node_variable.get('result')
-    _write_context = get_to_response_write_context(node_variable, node)
-    return tools.to_stream_response(chat_id, chat_record_id, response, workflow, _write_context, post_handler)
-
-
-def to_response(chat_id, chat_record_id, node_variable: Dict, workflow_variable: Dict, node, workflow,
-                post_handler):
-    """
-    将结果转换
-    @param chat_id:           会话id
-    @param chat_record_id:    对话记录id
-    @param node_variable:     节点数据
-    @param workflow_variable: 工作流数据
-    @param node:              节点
-    @param workflow:          工作流管理器
-    @param post_handler:      后置处理器
-    @return: 响应
-    """
-    response = node_variable.get('result')
-    _write_context = get_to_response_write_context(node_variable, node)
-    return tools.to_response(chat_id, chat_record_id, response, workflow, _write_context, post_handler)
 
 
 class BaseQuestionNode(IQuestionNode):
@@ -131,15 +76,13 @@ class BaseQuestionNode(IQuestionNode):
         if stream:
             r = chat_model.stream(message_list)
             return NodeResult({'result': r, 'chat_model': chat_model, 'message_list': message_list,
-                               'get_to_response_write_context': get_to_response_write_context,
                                'history_message': history_message, 'question': question.content}, {},
-                              _write_context=write_context_stream,
+                              _write_context=write_context_stream)
-                              _to_response=to_stream_response)
         else:
             r = chat_model.invoke(message_list)
             return NodeResult({'result': r, 'chat_model': chat_model, 'message_list': message_list,
                                'history_message': history_message, 'question': question.content}, {},
-                              _write_context=write_context, _to_response=to_response)
+                              _write_context=write_context)
 
     @staticmethod
     def get_history_message(history_chat_record, dialogue_number):

apps/application/flow/tools.py

@@ -85,3 +85,21 @@ def to_response(chat_id, chat_record_id, response: BaseMessage, workflow, write_
     post_handler.handler(chat_id, chat_record_id, answer, workflow)
     return result.success({'chat_id': str(chat_id), 'id': str(chat_record_id), 'operate': True,
                            'content': answer, 'is_end': True})
+
+
+def to_response_simple(chat_id, chat_record_id, response: BaseMessage, workflow,
+                       post_handler: WorkFlowPostHandler):
+    answer = response.content
+    post_handler.handler(chat_id, chat_record_id, answer, workflow)
+    return result.success({'chat_id': str(chat_id), 'id': str(chat_record_id), 'operate': True,
+                           'content': answer, 'is_end': True})
+
+
+def to_stream_response_simple(stream_event):
+    r = StreamingHttpResponse(
+        streaming_content=stream_event,
+        content_type='text/event-stream;charset=utf-8',
+        charset='utf-8')
+
+    r['Cache-Control'] = 'no-cache'
+    return r

apps/application/flow/workflow_manage.py

@@ -6,10 +6,11 @@
     @date：2024/1/9 17:40
     @desc:
 """
+import json
 from functools import reduce
 from typing import List, Dict
 
-from langchain_core.messages import AIMessageChunk, AIMessage
+from langchain_core.messages import AIMessage
 from langchain_core.prompts import PromptTemplate
 
 from application.flow import tools
@@ -63,7 +64,6 @@ class Flow:
     def get_search_node(self):
         return [node for node in self.nodes if node.type == 'search-dataset-node']
 
-
     def is_valid(self):
         """
         校验工作流数据
@@ -140,33 +140,71 @@ class WorkflowManage:
         self.work_flow_post_handler = work_flow_post_handler
         self.current_node = None
         self.current_result = None
+        self.answer = ""
 
     def run(self):
-        """
+        if self.params.get('stream'):
-        运行工作流
+            return self.run_stream()
-        """
+        return self.run_block()
+
+    def run_block(self):
         try:
             while self.has_next_node(self.current_result):
                 self.current_node = self.get_next_node()
                 self.node_context.append(self.current_node)
                 self.current_result = self.current_node.run()
-                if self.has_next_node(self.current_result):
+                result = self.current_result.write_context(self.current_node, self)
-                    self.current_result.write_context(self.current_node, self)
+                if result is not None:
-                else:
+                    list(result)
-                    r = self.current_result.to_response(self.params['chat_id'], self.params['chat_record_id'],
+                if not self.has_next_node(self.current_result):
-                                                        self.current_node, self,
+                    return tools.to_response_simple(self.params['chat_id'], self.params['chat_record_id'],
-                                                        self.work_flow_post_handler)
+                                                    AIMessage(self.answer), self,
-                    return r
+                                                    self.work_flow_post_handler)
         except Exception as e:
-            if self.params.get('stream'):
+            return tools.to_response(self.params['chat_id'], self.params['chat_record_id'],
-                return tools.to_stream_response(self.params['chat_id'], self.params['chat_record_id'],
+                                     AIMessage(str(e)), self, self.current_node.get_write_error_context(e),
-                                                iter([AIMessageChunk(str(e))]), self,
+                                     self.work_flow_post_handler)
-                                                self.current_node.get_write_error_context(e),
+
-                                                self.work_flow_post_handler)
+    def run_stream(self):
-            else:
+        return tools.to_stream_response_simple(self.stream_event())
-                return tools.to_response(self.params['chat_id'], self.params['chat_record_id'],
+
-                                         AIMessage(str(e)), self, self.current_node.get_write_error_context(e),
+    def stream_event(self):
-                                         self.work_flow_post_handler)
+        try:
+            while self.has_next_node(self.current_result):
+                self.current_node = self.get_next_node()
+                self.node_context.append(self.current_node)
+                self.current_result = self.current_node.run()
+                result = self.current_result.write_context(self.current_node, self)
+                if result is not None:
+                    for r in result:
+                        if self.is_result():
+                            yield self.get_chunk_content(r)
+                if not self.has_next_node(self.current_result):
+                    yield self.get_chunk_content('', True)
+                    break
+            self.work_flow_post_handler.handler(self.params['chat_id'], self.params['chat_record_id'],
+                                                self.answer,
+                                                self)
+        except Exception as e:
+            self.current_node.get_write_error_context(e)
+            self.answer += str(e)
+            self.work_flow_post_handler.handler(self.params['chat_id'], self.params['chat_record_id'],
+                                                self.answer,
+                                                self)
+            yield self.get_chunk_content(str(e), True)
+
+    def is_result(self):
+        """
+        判断是否是返回节点
+        @return:
+        """
+        return self.current_node.node_params.get('is_result', not self.has_next_node(
+            self.current_result)) if self.current_node.node_params is not None else False
+
+    def get_chunk_content(self, chunk, is_end=False):
+        return 'data: ' + json.dumps(
+            {'chat_id': self.params['chat_id'], 'id': self.params['chat_record_id'], 'operate': True,
+             'content': chunk, 'is_end': is_end}, ensure_ascii=False) + "\n\n"
 
     def has_next_node(self, node_result: NodeResult | None):
         """

apps/application/serializers/chat_serializers.py

@@ -28,7 +28,6 @@ from application.models.api_key_model import ApplicationAccessToken
 from application.serializers.application_serializers import ModelDatasetAssociation, DatasetSettingSerializer, \
     ModelSettingSerializer
 from application.serializers.chat_message_serializers import ChatInfo
-from common.config.embedding_config import ModelManage
 from common.constants.permission_constants import RoleConstants
 from common.db.search import native_search, native_page_search, page_search, get_dynamics_model
 from common.event import ListenerManagement
@@ -40,8 +39,6 @@ from common.util.lock import try_lock, un_lock
 from dataset.models import Document, Problem, Paragraph, ProblemParagraphMapping
 from dataset.serializers.common_serializers import get_embedding_model_by_dataset_id
 from dataset.serializers.paragraph_serializers import ParagraphSerializers
-from setting.models import Model
-from setting.models_provider import get_model
 from smartdoc.conf import PROJECT_DIR
 
 chat_cache = caches['chat_cache']
@@ -312,7 +309,8 @@ class ChatSerializers(serializers.Serializer):
             chat_id = str(uuid.uuid1())
             model_id = self.data.get('model_id')
             dataset_id_list = self.data.get('dataset_id_list')
-            application = Application(id=None, dialogue_number=3, model_id=model_id,
+            dialogue_number = 3 if self.data.get('multiple_rounds_dialogue', False) else 0
+            application = Application(id=None, dialogue_number=dialogue_number, model_id=model_id,
                                       dataset_setting=self.data.get('dataset_setting'),
                                       model_setting=self.data.get('model_setting'),
                                       problem_optimization=self.data.get('problem_optimization'),

apps/common/config/embedding_config.py

@@ -18,7 +18,7 @@ class ModelManage:
     @staticmethod
     def get_model(_id, get_model):
         model_instance = ModelManage.cache.get(_id)
-        if model_instance is None:
+        if model_instance is None or not model_instance.is_cache_model():
             model_instance = get_model(_id)
             ModelManage.cache.set(_id, model_instance, timeout=60 * 30)
             return model_instance

apps/common/event/listener_manage.py

@@ -110,11 +110,16 @@ class ListenerManagement:
     @embedding_poxy
     def embedding_by_paragraph_data_list(data_list, paragraph_id_list, embedding_model: Embeddings):
         max_kb.info(f'开始--->向量化段落:{paragraph_id_list}')
+        status = Status.success
         try:
             # 删除段落
             VectorStore.get_embedding_vector().delete_by_paragraph_ids(paragraph_id_list)
+
+            def is_save_function():
+                return QuerySet(Paragraph).filter(id__in=paragraph_id_list).exists()
+
             # 批量向量化
-            VectorStore.get_embedding_vector().batch_save(data_list, embedding_model)
+            VectorStore.get_embedding_vector().batch_save(data_list, embedding_model, is_save_function)
         except Exception as e:
             max_kb_error.error(f'向量化段落:{paragraph_id_list}出现错误{str(e)}{traceback.format_exc()}')
             status = Status.error
@@ -141,8 +146,12 @@ class ListenerManagement:
                     os.path.join(PROJECT_DIR, "apps", "common", 'sql', 'list_embedding_text.sql')))
             # 删除段落
             VectorStore.get_embedding_vector().delete_by_paragraph_id(paragraph_id)
+
+            def is_save_function():
+                return QuerySet(Paragraph).filter(id=paragraph_id).exists()
+
             # 批量向量化
-            VectorStore.get_embedding_vector().batch_save(data_list, embedding_model)
+            VectorStore.get_embedding_vector().batch_save(data_list, embedding_model, is_save_function)
         except Exception as e:
             max_kb_error.error(f'向量化段落:{paragraph_id}出现错误{str(e)}{traceback.format_exc()}')
             status = Status.error
@@ -175,8 +184,12 @@ class ListenerManagement:
                     os.path.join(PROJECT_DIR, "apps", "common", 'sql', 'list_embedding_text.sql')))
             # 删除文档向量数据
             VectorStore.get_embedding_vector().delete_by_document_id(document_id)
+
+            def is_save_function():
+                return QuerySet(Document).filter(id=document_id).exists()
+
             # 批量向量化
-            VectorStore.get_embedding_vector().batch_save(data_list, embedding_model)
+            VectorStore.get_embedding_vector().batch_save(data_list, embedding_model, is_save_function)
         except Exception as e:
             max_kb_error.error(f'向量化文档:{document_id}出现错误{str(e)}{traceback.format_exc()}')
             status = Status.error
@@ -258,7 +271,7 @@ class ListenerManagement:
     @staticmethod
     def update_problem(args: UpdateProblemArgs):
         problem_paragraph_mapping_list = QuerySet(ProblemParagraphMapping).filter(problem_id=args.problem_id)
-        embed_value = VectorStore.get_embedding_vector().embed_query(args.problem_content)
+        embed_value = args.embedding_model.embed_query(args.problem_content)
         VectorStore.get_embedding_vector().update_by_source_ids([v.id for v in problem_paragraph_mapping_list],
                                                                 {'embedding': embed_value})
 

apps/common/handle/impl/qa/xls_parse_qa_handle.py

@@ -31,6 +31,7 @@ def handle_sheet(file_name, sheet):
         problem_list = [{'content': p[0:255]} for p in problem.split('\n') if len(p.strip()) > 0]
         title = get_row_value(row, title_row_index_dict, 'title')
         title = str(title) if title is not None else ''
+        content = str(content)
         paragraph_list.append({'title': title[0:255],
                                'content': content[0:4096],
                                'problem_list': problem_list})

apps/common/handle/impl/qa/xlsx_parse_qa_handle.py

@@ -33,7 +33,7 @@ def handle_sheet(file_name, sheet):
         problem_list = [{'content': p[0:255]} for p in problem.split('\n') if len(p.strip()) > 0]
         title = get_row_value(row, title_row_index_dict, 'title')
         title = str(title.value) if title is not None and title.value is not None else ''
-        content = content.value
+        content = str(content.value)
         paragraph_list.append({'title': title[0:255],
                                'content': content[0:4096],
                                'problem_list': problem_list})

apps/common/util/split_model.py

@@ -27,7 +27,7 @@ def get_level_block(text, level_content_list, level_content_index, cursor):
         level_content_list) else None
     start_index = text.index(start_content, cursor)
     end_index = text.index(next_content, start_index + 1) if next_content is not None else len(text)
-    return text[start_index+len(start_content):end_index], end_index
+    return text[start_index + len(start_content):end_index], end_index
 
 
 def to_tree_obj(content, state='title'):
@@ -303,17 +303,20 @@ class SplitModel:
             level_content_list.insert(0, to_tree_obj(""))
 
         cursor = 0
-        for i in range(len(level_content_list)):
+        level_title_content_list = [item for item in level_content_list if item.get('state') == 'title']
-            block, cursor = get_level_block(text, level_content_list, i, cursor)
+        for i in range(len(level_title_content_list)):
+            start_content: str = level_title_content_list[i].get('content')
+            if cursor < text.index(start_content, cursor):
+                level_content_list.insert(0, to_tree_obj(text[cursor:   text.index(start_content, cursor)], 'block'))
+            block, cursor = get_level_block(text, level_title_content_list, i, cursor)
             if len(block) == 0:
-                level_content_list[i]['children'] = [to_tree_obj("", "block")]
                 continue
             children = self.parse_to_tree(text=block, index=index + 1)
-            level_content_list[i]['children'] = children
+            level_title_content_list[i]['children'] = children
             first_child_idx_in_block = block.lstrip().index(children[0]["content"].lstrip())
             if first_child_idx_in_block != 0:
                 inner_children = self.parse_to_tree(block[:first_child_idx_in_block], index + 1)
-                level_content_list[i]['children'].extend(inner_children)
+                level_title_content_list[i]['children'].extend(inner_children)
         return level_content_list
 
     def parse(self, text: str):

apps/dataset/serializers/dataset_serializers.py

@@ -463,6 +463,7 @@ class DataSetSerializers(serializers.ModelSerializer):
             dataset = DataSet(
                 **{'id': dataset_id, 'name': instance.get("name"), 'desc': instance.get('desc'), 'user_id': user_id,
                    'type': Type.web,
+                   'embedding_mode_id': instance.get('embedding_mode_id'),
                    'meta': {'source_url': instance.get('source_url'), 'selector': instance.get('selector'),
                             'embedding_mode_id': instance.get('embedding_mode_id')}})
             dataset.save()

apps/dataset/serializers/document_serializers.py

@@ -365,7 +365,7 @@ class DocumentSerializers(ApiMixin, serializers.Serializer):
             if document.type != Type.web:
                 return True
             try:
-                document.status = Status.embedding
+                document.status = Status.queue_up
                 document.save()
                 source_url = document.meta.get('source_url')
                 selector_list = document.meta.get('selector').split(

apps/embedding/vector/base_vector.py

@@ -84,9 +84,9 @@ class BaseVectorStore(ABC):
         chunk_list = chunk_data(data)
         result = sub_array(chunk_list)
         for child_array in result:
-            self._batch_save(child_array, embedding)
+            self._batch_save(child_array, embedding, lambda: True)
 
-    def batch_save(self, data_list: List[Dict], embedding: Embeddings):
+    def batch_save(self, data_list: List[Dict], embedding: Embeddings, is_save_function):
         # 获取锁
         lock.acquire()
         try:
@@ -100,7 +100,10 @@ class BaseVectorStore(ABC):
             chunk_list = chunk_data_list(data_list)
             result = sub_array(chunk_list)
             for child_array in result:
-                self._batch_save(child_array, embedding)
+                if is_save_function():
+                    self._batch_save(child_array, embedding, is_save_function)
+                else:
+                    break
         finally:
             # 释放锁
             lock.release()
@@ -113,7 +116,7 @@ class BaseVectorStore(ABC):
         pass
 
     @abstractmethod
-    def _batch_save(self, text_list: List[Dict], embedding: Embeddings):
+    def _batch_save(self, text_list: List[Dict], embedding: Embeddings, is_save_function):
         pass
 
     def search(self, query_text, dataset_id_list: list[str], exclude_document_id_list: list[str],

apps/embedding/vector/pg_vector.py

@@ -55,7 +55,7 @@ class PGVector(BaseVectorStore):
         embedding.save()
         return True
 
-    def _batch_save(self, text_list: List[Dict], embedding: Embeddings):
+    def _batch_save(self, text_list: List[Dict], embedding: Embeddings, is_save_function):
         texts = [row.get('text') for row in text_list]
         embeddings = embedding.embed_documents(texts)
         embedding_list = [Embedding(id=uuid.uuid1(),
@@ -68,7 +68,8 @@ class PGVector(BaseVectorStore):
                                     embedding=embeddings[index],
                                     search_vector=to_ts_vector(text_list[index]['text'])) for index in
                           range(0, len(text_list))]
-        QuerySet(Embedding).bulk_create(embedding_list) if len(embedding_list) > 0 else None
+        if is_save_function():
+            QuerySet(Embedding).bulk_create(embedding_list) if len(embedding_list) > 0 else None
         return True
 
     def hit_test(self, query_text, dataset_id_list: list[str], exclude_document_id_list: list[str], top_number: int,

apps/setting/models_provider/base_model_provider.py

@@ -89,6 +89,10 @@ class MaxKBBaseModel(ABC):
     def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):
         pass
 
+    @staticmethod
+    def is_cache_model():
+        return True
+
 
 class BaseModelCredential(ABC):
 

apps/setting/models_provider/impl/ollama_model_provider/model/llm.py

@@ -18,9 +18,10 @@ from setting.models_provider.base_model_provider import MaxKBBaseModel
 
 def get_base_url(url: str):
     parse = urlparse(url)
-    return ParseResult(scheme=parse.scheme, netloc=parse.netloc, path='', params='',
+    result_url = ParseResult(scheme=parse.scheme, netloc=parse.netloc, path=parse.path, params='',
-                       query='',
+                             query='',
-                       fragment='').geturl()
+                             fragment='').geturl()
+    return result_url[:-1] if result_url.endswith("/") else result_url
 
 
 class OllamaChatModel(MaxKBBaseModel, ChatOpenAI):
@@ -28,7 +29,8 @@ class OllamaChatModel(MaxKBBaseModel, ChatOpenAI):
     def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):
         api_base = model_credential.get('api_base', '')
         base_url = get_base_url(api_base)
-        return OllamaChatModel(model=model_name, openai_api_base=(base_url + '/v1'),
+        base_url = base_url if base_url.endswith('/v1') else (base_url + '/v1')
+        return OllamaChatModel(model=model_name, openai_api_base=base_url,
                                openai_api_key=model_credential.get('api_key'))
 
     def get_num_tokens_from_messages(self, messages: List[BaseMessage]) -> int:

apps/setting/models_provider/impl/ollama_model_provider/ollama_model_provider.py

@@ -113,9 +113,10 @@ model_info_manage = ModelInfoManage.builder().append_model_info_list(model_info_
 
 def get_base_url(url: str):
     parse = urlparse(url)
-    return ParseResult(scheme=parse.scheme, netloc=parse.netloc, path='', params='',
+    result_url = ParseResult(scheme=parse.scheme, netloc=parse.netloc, path=parse.path, params='',
-                       query='',
+                             query='',
-                       fragment='').geturl()
+                             fragment='').geturl()
+    return result_url[:-1] if result_url.endswith("/") else result_url
 
 
 def convert_to_down_model_chunk(row_str: str, chunk_index: int):

apps/setting/models_provider/impl/xf_model_provider/model/llm.py

@@ -20,6 +20,9 @@ from setting.models_provider.base_model_provider import MaxKBBaseModel
 
 
 class XFChatSparkLLM(MaxKBBaseModel, ChatSparkLLM):
+    @staticmethod
+    def is_cache_model():
+        return False
 
     @staticmethod
     def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):

apps/setting/serializers/provider_serializers.py

@@ -65,7 +65,7 @@ class ModelSerializer(serializers.Serializer):
     class Query(serializers.Serializer):
         user_id = serializers.UUIDField(required=True, error_messages=ErrMessage.uuid("用户id"))
 
-        name = serializers.CharField(required=False, max_length=20,
+        name = serializers.CharField(required=False, max_length=64,
                                      error_messages=ErrMessage.char("模型名称"))
 
         model_type = serializers.CharField(required=False, error_messages=ErrMessage.char("模型类型"))
@@ -99,7 +99,7 @@ class ModelSerializer(serializers.Serializer):
     class Edit(serializers.Serializer):
         user_id = serializers.CharField(required=False, error_messages=ErrMessage.uuid("用户id"))
 
-        name = serializers.CharField(required=False, max_length=20,
+        name = serializers.CharField(required=False, max_length=64,
                                      error_messages=ErrMessage.char("模型名称"))
 
         model_type = serializers.CharField(required=False, error_messages=ErrMessage.char("模型类型"))
@@ -142,7 +142,7 @@ class ModelSerializer(serializers.Serializer):
     class Create(serializers.Serializer):
         user_id = serializers.CharField(required=True, error_messages=ErrMessage.uuid("用户id"))
 
-        name = serializers.CharField(required=True, max_length=20, error_messages=ErrMessage.char("模型名称"))
+        name = serializers.CharField(required=True, max_length=64, error_messages=ErrMessage.char("模型名称"))
 
         provider = serializers.CharField(required=True, error_messages=ErrMessage.char("供应商"))
 

apps/smartdoc/settings/base.py

@@ -3,13 +3,15 @@ import mimetypes
 import os
 from pathlib import Path
 
+from PIL import Image
+
 from ..const import CONFIG, PROJECT_DIR
 
 mimetypes.add_type("text/css", ".css", True)
 mimetypes.add_type("text/javascript", ".js", True)
 # Build paths inside the project like this: BASE_DIR / 'subdir'.
 BASE_DIR = Path(__file__).resolve().parent.parent
-
+Image.MAX_IMAGE_PIXELS = 20000000000
 # Quick-start development settings - unsuitable for production
 # See https://docs.djangoproject.com/en/4.2/howto/deployment/checklist/
 

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

@@ -104,7 +104,7 @@
                     </div>
                     <div class="card-never border-r-4 mt-8">
                       <h5 class="p-8-12">本次对话</h5>
-                      <div class="p-8-12 border-t-dashed lighter pre-line">
+                      <div class="p-8-12 border-t-dashed lighter pre-wrap">
                         {{ item.question || '-' }}
                       </div>
                     </div>

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

@@ -42,7 +42,7 @@
               </AppAvatar>
             </div>
             <div class="content">
-              <div class="text break-all">
+              <div class="text break-all pre-wrap">
                 {{ item.problem_text }}
               </div>
             </div>
@@ -607,7 +607,7 @@ watch(
 
 onMounted(() => {
   setTimeout(() => {
-    if (quickInputRef.value) {
+    if (quickInputRef.value && mode === 'embed') {
       quickInputRef.value.textarea.style.height = '0'
     }
   }, 1800)

ui/src/locales/lang/en_US/views/application-overview.ts

@@ -48,10 +48,10 @@ export default {
       upload: 'Upload',
       default: 'Default Logo',
       custom: 'Custom',
-      sizeTip: 'Suggested size 32*32, supports ico, png, size no more than 200KB',
+      sizeTip: 'Suggested size 32*32, supports jpg, png, gif, size no more than 10 MB',
       cancel: 'Cancel',
       save: 'Save',
-      fileSizeExceeded: 'File size exceeds 200KB',
+      fileSizeExceeded: 'File size exceeds 10 MB',
       setSuccess: 'Setting Successful',
       uploadImagePrompt: 'Please upload an image'
     },

ui/src/locales/lang/zh_CN/views/application-overview.ts

@@ -42,15 +42,15 @@ export default {
       disabledSuccess: '已禁用'
     },
     EditAvatarDialog: {
-      title: '编辑logo',
+      title: '应用头像',
       customizeUpload: '自定义上传',
       upload: '上传',
       default: '默认logo',
       custom: '自定义',
-      sizeTip: '建议尺寸 32*32，支持 ico、png，大小不超过200KB',
+      sizeTip: '建议尺寸 32*32，支持 JPG、PNG, GIF，大小不超过 10 MB',
       cancel: '取消',
       save: '保存',
-      fileSizeExceeded: '文件大小超过 200KB',
+      fileSizeExceeded: '文件大小超过 10 MB',
       setSuccess: '设置成功',
       uploadImagePrompt: '请上传一张图片'
     },

ui/src/styles/app.scss

@@ -341,8 +341,8 @@ h5 {
   word-break: break-all;
 }
 
-.pre-line {
+.pre-wrap {
-  white-space: pre-line;
+  white-space: pre-wrap;
 }
 
 /*

ui/src/views/application-overview/component/DisplaySettingDialog.vue

@@ -47,7 +47,7 @@
             }}</el-button>
             <template #tip>
               <div class="el-upload__tip info" style="margin-top: 0">
-                建议尺寸 32*32，支持 JPG、PNG，大小不超过 200 KB
+                建议尺寸 32*32，支持 JPG、PNG, GIF，大小不超过 10 MB
               </div>
             </template>
           </el-upload>
@@ -84,7 +84,7 @@
             }}</el-button>
             <template #tip>
               <div class="el-upload__tip info" style="margin-top: 0">
-                建议尺寸 32*32，支持 JPG、PNG，大小不超过 200 KB
+                建议尺寸 32*32，支持 JPG、PNG, GIF，大小不超过 10 MB
               </div>
             </template>
           </el-upload>
@@ -178,8 +178,8 @@ function resetForm() {
 }
 
 const onChange = (file: any, fileList: UploadFiles, attr: string) => {
-  //1、判断文件大小是否合法，文件限制不能大于 200KB
+  //1、判断文件大小是否合法，文件限制不能大于 10 MB
-  const isLimit = file?.size / 1024 < 200
+  const isLimit = file?.size / 1024 / 1024 < 10
   if (!isLimit) {
     // @ts-ignore
     MsgError(t('views.applicationOverview.appInfo.EditAvatarDialog.fileSizeExceeded'))

ui/src/views/application-overview/component/EditAvatarDialog.vue

@@ -1,9 +1,12 @@
 <template>
-  <el-dialog :title="$t('views.applicationOverview.appInfo.EditAvatarDialog.title')" v-model="dialogVisible">
+  <el-dialog
+    :title="$t('views.applicationOverview.appInfo.EditAvatarDialog.title')"
+    v-model="dialogVisible"
+  >
     <el-radio-group v-model="radioType" class="radio-block mb-16">
       <div>
         <el-radio value="default">
-          <p>{{$t('views.applicationOverview.appInfo.EditAvatarDialog.default')}}</p>
+          <p>{{ $t('views.applicationOverview.appInfo.EditAvatarDialog.default') }}</p>
           <AppAvatar
             v-if="detail?.name"
             :name="detail?.name"
@@ -16,7 +19,7 @@
       </div>
       <div class="mt-8">
         <el-radio value="custom">
-          <p>{{$t('views.applicationOverview.appInfo.EditAvatarDialog.customizeUpload')}}</p>
+          <p>{{ $t('views.applicationOverview.appInfo.EditAvatarDialog.customizeUpload') }}</p>
           <div class="flex mt-8">
             <AppAvatar
               v-if="fileURL"
@@ -35,19 +38,25 @@
               accept="image/*"
               :on-change="onChange"
             >
-              <el-button icon="Upload" :disabled="radioType !== 'custom'">{{$t('views.applicationOverview.appInfo.EditAvatarDialog.upload')}}</el-button>
+              <el-button icon="Upload" :disabled="radioType !== 'custom'">{{
+                $t('views.applicationOverview.appInfo.EditAvatarDialog.upload')
+              }}</el-button>
             </el-upload>
           </div>
           <div class="el-upload__tip info mt-16">
-            {{$t('views.applicationOverview.appInfo.EditAvatarDialog.sizeTip')}}
+            {{ $t('views.applicationOverview.appInfo.EditAvatarDialog.sizeTip') }}
           </div>
         </el-radio>
       </div>
     </el-radio-group>
     <template #footer>
       <span class="dialog-footer">
-        <el-button @click.prevent="dialogVisible = false"> {{$t('views.applicationOverview.appInfo.EditAvatarDialog.cancel')}}</el-button>
+        <el-button @click.prevent="dialogVisible = false">
-        <el-button type="primary" @click="submit" :loading="loading"> {{$t('views.applicationOverview.appInfo.EditAvatarDialog.save')}}</el-button>
+          {{ $t('views.applicationOverview.appInfo.EditAvatarDialog.cancel') }}</el-button
+        >
+        <el-button type="primary" @click="submit" :loading="loading">
+          {{ $t('views.applicationOverview.appInfo.EditAvatarDialog.save') }}</el-button
+        >
       </span>
     </template>
   </el-dialog>
@@ -94,17 +103,16 @@ const open = (data: any) => {
 }
 
 const onChange = (file: any) => {
-  //1、判断文件大小是否合法，文件限制不能大于 200KB
+  //1、判断文件大小是否合法，文件限制不能大于10MB
-  const isLimit = file?.size / 1024 < 200
+  const isLimit = file?.size / 1024 / 1024 < 10
   if (!isLimit) {
     // @ts-ignore
     MsgError(t('views.applicationOverview.appInfo.EditAvatarDialog.fileSizeExceeded'))
     return false
-  } else { 
+  } else {
     iconFile.value = file
     fileURL.value = URL.createObjectURL(file.raw)
   }
-
 }
 
 function submit() {

ui/src/views/application-overview/component/EmbedDialog.vue

@@ -42,7 +42,7 @@
                 <AppIcon iconName="app-copy"></AppIcon>
               </el-button>
             </div>
-            <div class="mt-8 white-space">
+            <div class="mt-8 pre-wrap">
               {{ source2 }}
             </div>
           </div>
@@ -109,9 +109,6 @@ defineExpose({ open })
     font-size: 13px;
     white-space: pre;
     height: 180px;
-    .white-space {
-      white-space: pre-wrap;
-    }
   }
 }
 </style>

ui/src/views/application-workflow/index.vue

@@ -36,7 +36,7 @@
             @mousedown="onmousedown(item)"
           >
             <component :is="iconComponent(`${item.type}-icon`)" class="mr-8 mt-4" :size="32" />
-            <div class="pre-line">
+            <div class="pre-wrap">
               <div class="lighter">{{ item.label }}</div>
               <el-text type="info" size="small">{{ item.text }}</el-text>
             </div>
@@ -114,6 +114,7 @@ import { MsgSuccess, MsgConfirm, MsgError } from '@/utils/message'
 import { datetimeFormat } from '@/utils/time'
 import useStore from '@/stores'
 import { WorkFlowInstance } from '@/workflow/common/validate'
+import { hasPermission } from '@/utils/permission'
 
 const { user, application } = useStore()
 const router = useRouter()
@@ -250,7 +251,9 @@ const closeInterval = () => {
 onMounted(() => {
   getDetail()
   // 初始化定时任务
-  initInterval()
+  if (hasPermission(`APPLICATION:MANAGE:${id}`, 'AND')) {
+    initInterval()
+  }
 })
 
 onBeforeUnmount(() => {

ui/src/views/log/component/EditMarkDialog.vue

@@ -38,7 +38,7 @@
             </el-input>
           </el-form-item>
         </el-form>
-        <span v-else class="pre-line">{{ form?.content }}</span>
+        <span v-else class="pre-wrap">{{ form?.content }}</span>
       </div>
     </el-scrollbar>
 

ui/src/workflow/common/NodeControl.vue

@@ -20,10 +20,10 @@ const props = defineProps({
 })
 
 function zoomIn() {
-  props.lf?.zoom(true)
+  props.lf?.zoom(true, [0, 0])
 }
 function zoomOut() {
-  props.lf?.zoom(false)
+  props.lf?.zoom(false, [0, 0])
 }
 function fitView() {
   props.lf?.resetZoom()

ui/src/workflow/common/data.ts

@@ -170,3 +170,13 @@ export const nodeDict: any = {
 export function isWorkFlow(type: string | undefined) {
   return type === 'WORK_FLOW'
 }
+
+export function isLastNode(nodeModel: any) {
+  const incoming = nodeModel.graphModel.getNodeIncomingNode(nodeModel.id)
+  const outcomming = nodeModel.graphModel.getNodeOutgoingNode(nodeModel.id)
+  if (incoming.length > 0 && outcomming.length === 0) {
+    return true
+  } else {
+    return false
+  }
+}

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

@@ -115,13 +115,23 @@
               </el-tooltip>
             </div>
           </template>
-          <el-input
+          <MdEditor
+            @wheel="wheel"
+            @keydown="isKeyDown = true"
+            @keyup="isKeyDown = false"
+            class="reply-node-editor"
+            style="height: 150px"
             v-model="chat_data.prompt"
-            :rows="6"
+            :preview="false"
-            type="textarea"
+            :toolbars="[]"
-            maxlength="2048"
+            :footers="footers"
-            :placeholder="defaultPrompt"
+          >
-          />
+            <template #defFooters>
+              <el-button text type="info" @click="openDialog">
+                <AppIcon iconName="app-magnify" style="font-size: 16px"></AppIcon>
+              </el-button>
+            </template>
+          </MdEditor>
         </el-form-item>
         <el-form-item label="历史聊天记录">
           <el-input-number
@@ -132,9 +142,34 @@
             class="w-full"
           />
         </el-form-item>
+        <el-form-item label="返回内容" @click.prevent>
+          <template #label>
+            <div class="flex align-center">
+              <div class="mr-4">
+                <span>返回内容<span class="danger">*</span></span>
+              </div>
+              <el-tooltip effect="dark" placement="right" popper-class="max-w-200">
+                <template #content>
+                  关闭后该节点的内容则不输出给用户。
+                  如果你想让用户看到该节点的输出内容，请打开开关。
+                </template>
+                <AppIcon iconName="app-warning" class="app-warning-icon"></AppIcon>
+              </el-tooltip>
+            </div>
+          </template>
+          <el-switch size="small" v-model="chat_data.is_result" />
+        </el-form-item>
       </el-form>
     </el-card>
-
+    <!-- 回复内容弹出层 -->
+    <el-dialog v-model="dialogVisible" title="提示词" append-to-body>
+      <MdEditor v-model="cloneContent" :preview="false" :toolbars="[]" :footers="[]"> </MdEditor>
+      <template #footer>
+        <div class="dialog-footer mt-24">
+          <el-button type="primary" @click="submitDialog"> 确认 </el-button>
+        </div>
+      </template>
+    </el-dialog>
     <!-- 添加模版 -->
     <CreateModelDialog
       ref="createModelRef"
@@ -156,6 +191,7 @@ import applicationApi from '@/api/application'
 import useStore from '@/stores'
 import { relatedObject } from '@/utils/utils'
 import type { Provider } from '@/api/type/model'
+import { isLastNode } from '@/workflow/common/data'
 
 const { model } = useStore()
 const isKeyDown = ref(false)
@@ -167,6 +203,17 @@ const wheel = (e: any) => {
     return true
   }
 }
+const dialogVisible = ref(false)
+const cloneContent = ref('')
+const footers: any = [null, '=', 0]
+function openDialog() {
+  cloneContent.value = chat_data.value.prompt
+  dialogVisible.value = true
+}
+function submitDialog() {
+  set(props.nodeModel.properties.node_data, 'prompt', cloneContent.value)
+  dialogVisible.value = false
+}
 const {
   params: { id }
 } = app.config.globalProperties.$route as any
@@ -180,7 +227,8 @@ const form = {
   model_id: '',
   system: '',
   prompt: defaultPrompt,
-  dialogue_number: 1
+  dialogue_number: 1,
+  is_result: false
 }
 
 const chat_data = computed({
@@ -240,7 +288,17 @@ const openCreateModel = (provider?: Provider) => {
 onMounted(() => {
   getProvider()
   getModel()
+  if (isLastNode(props.nodeModel)) {
+    set(props.nodeModel.properties.node_data, 'is_result', true)
+  }
+
   set(props.nodeModel, 'validate', validate)
 })
 </script>
-<style lang="scss" scoped></style>
+<style lang="scss" scoped>
+.reply-node-editor {
+  :deep(.md-editor-footer) {
+    border: none !important;
+  }
+}
+</style>

ui/src/workflow/nodes/base-node/index.vue

@@ -40,14 +40,32 @@
       </el-form-item>
       <el-form-item label="开场白">
         <MdEditor
+          @wheel="wheel"
+          @keydown="isKeyDown = true"
+          @keyup="isKeyDown = false"
           style="height: 150px"
           v-model="form_data.prologue"
           :preview="false"
           :toolbars="[]"
-          :footers="[]"
+          class="reply-node-editor"
-        />
+          :footers="footers"
+        >
+          <template #defFooters>
+            <el-button text type="info" @click="openDialog">
+              <AppIcon iconName="app-magnify" style="font-size: 16px"></AppIcon>
+            </el-button> </template
+        ></MdEditor>
       </el-form-item>
     </el-form>
+    <!-- 回复内容弹出层 -->
+    <el-dialog v-model="dialogVisible" title="开场白" append-to-body>
+      <MdEditor v-model="cloneContent" :preview="false" :toolbars="[]" :footers="[]"> </MdEditor>
+      <template #footer>
+        <div class="dialog-footer mt-24">
+          <el-button type="primary" @click="submitDialog"> 确认 </el-button>
+        </div>
+      </template>
+    </el-dialog>
   </NodeContainer>
 </template>
 <script setup lang="ts">
@@ -63,6 +81,26 @@ const form = {
   prologue:
     '您好，我是 MaxKB 小助手，您可以向我提出 MaxKB 使用问题。\n- MaxKB 主要功能有什么？\n- MaxKB 支持哪些大语言模型？\n- MaxKB 支持哪些文档类型？'
 }
+const isKeyDown = ref(false)
+const wheel = (e: any) => {
+  if (isKeyDown.value) {
+    e.preventDefault()
+  } else {
+    e.stopPropagation()
+    return true
+  }
+}
+const dialogVisible = ref(false)
+const cloneContent = ref('')
+const footers: any = [null, '=', 0]
+function openDialog() {
+  cloneContent.value = form_data.value.prologue
+  dialogVisible.value = true
+}
+function submitDialog() {
+  set(props.nodeModel.properties.node_data, 'prologue', cloneContent.value)
+  dialogVisible.value = false
+}
 const form_data = computed({
   get: () => {
     if (props.nodeModel.properties.node_data) {
@@ -89,4 +127,10 @@ onMounted(() => {
   set(props.nodeModel, 'validate', validate)
 })
 </script>
-<style lang="scss" scoped></style>
+<style lang="scss" scoped>
+.reply-node-editor {
+  :deep(.md-editor-footer) {
+    border: none !important;
+  }
+}
+</style>

ui/src/workflow/nodes/question-node/index.vue

@@ -116,13 +116,23 @@
               </el-tooltip>
             </div>
           </template>
-          <el-input
+          <MdEditor
+            @wheel="wheel"
+            @keydown="isKeyDown = true"
+            @keyup="isKeyDown = false"
+            class="reply-node-editor"
+            style="height: 150px"
             v-model="form_data.prompt"
-            :rows="6"
+            :preview="false"
-            type="textarea"
+            :toolbars="[]"
-            maxlength="2048"
+            :footers="footers"
-            :placeholder="defaultPrompt"
+          >
-          />
+            <template #defFooters>
+              <el-button text type="info" @click="openDialog">
+                <AppIcon iconName="app-magnify" style="font-size: 16px"></AppIcon>
+              </el-button>
+            </template>
+          </MdEditor>
         </el-form-item>
         <el-form-item label="历史聊天记录">
           <el-input-number
@@ -133,8 +143,34 @@
             class="w-full"
           />
         </el-form-item>
+        <el-form-item label="返回内容" @click.prevent>
+          <template #label>
+            <div class="flex align-center">
+              <div class="mr-4">
+                <span>返回内容<span class="danger">*</span></span>
+              </div>
+              <el-tooltip effect="dark" placement="right" popper-class="max-w-200">
+                <template #content>
+                  关闭后该节点的内容则不输出给用户。
+                  如果你想让用户看到该节点的输出内容，请打开开关。
+                </template>
+                <AppIcon iconName="app-warning" class="app-warning-icon"></AppIcon>
+              </el-tooltip>
+            </div>
+          </template>
+          <el-switch size="small" v-model="form_data.is_result" />
+        </el-form-item>
       </el-form>
     </el-card>
+    <!-- 回复内容弹出层 -->
+    <el-dialog v-model="dialogVisible" title="提示词" append-to-body>
+      <MdEditor v-model="cloneContent" :preview="false" :toolbars="[]" :footers="[]"> </MdEditor>
+      <template #footer>
+        <div class="dialog-footer mt-24">
+          <el-button type="primary" @click="submitDialog"> 确认 </el-button>
+        </div>
+      </template>
+    </el-dialog>
     <!-- 添加模版 -->
     <CreateModelDialog
       ref="createModelRef"
@@ -156,6 +192,8 @@ import applicationApi from '@/api/application'
 import useStore from '@/stores'
 import { relatedObject } from '@/utils/utils'
 import type { Provider } from '@/api/type/model'
+import { isLastNode } from '@/workflow/common/data'
+
 const { model } = useStore()
 const isKeyDown = ref(false)
 const wheel = (e: any) => {
@@ -166,6 +204,17 @@ const wheel = (e: any) => {
     return true
   }
 }
+const dialogVisible = ref(false)
+const cloneContent = ref('')
+const footers: any = [null, '=', 0]
+function openDialog() {
+  cloneContent.value = form_data.value.prompt
+  dialogVisible.value = true
+}
+function submitDialog() {
+  set(props.nodeModel.properties.node_data, 'prompt', cloneContent.value)
+  dialogVisible.value = false
+}
 const {
   params: { id }
 } = app.config.globalProperties.$route as any
@@ -177,7 +226,8 @@ const form = {
   model_id: '',
   system: '你是一个问题优化大师',
   prompt: defaultPrompt,
-  dialogue_number: 1
+  dialogue_number: 1,
+  is_result: false
 }
 
 const form_data = computed({
@@ -237,7 +287,16 @@ const openCreateModel = (provider?: Provider) => {
 onMounted(() => {
   getProvider()
   getModel()
+  if (isLastNode(props.nodeModel)) {
+    set(props.nodeModel.properties.node_data, 'is_result', true)
+  }
   set(props.nodeModel, 'validate', validate)
 })
 </script>
-<style lang="scss" scoped></style>
+<style lang="scss" scoped>
+.reply-node-editor {
+  :deep(.md-editor-footer) {
+    border: none !important;
+  }
+}
+</style>

ui/src/workflow/nodes/reply-node/index.vue

@@ -16,7 +16,12 @@
           <template #label>
             <div class="flex-between">
               <span>回复内容</span>
-              <el-select v-model="form_data.reply_type" size="small" style="width: 85px">
+              <el-select
+                :teleported="false"
+                v-model="form_data.reply_type"
+                size="small"
+                style="width: 85px"
+              >
                 <el-option label="引用变量" value="referencing" />
                 <el-option label="自定义" value="content" />
               </el-select>
@@ -24,6 +29,9 @@
           </template>
           <MdEditor
             v-if="form_data.reply_type === 'content'"
+            @wheel="wheel"
+            @keydown="isKeyDown = true"
+            @keyup="isKeyDown = false"
             class="reply-node-editor"
             style="height: 150px"
             v-model="form_data.content"
@@ -46,6 +54,23 @@
             v-model="form_data.fields"
           />
         </el-form-item>
+        <el-form-item label="返回内容" @click.prevent>
+          <template #label>
+            <div class="flex align-center">
+              <div class="mr-4">
+                <span>返回内容<span class="danger">*</span></span>
+              </div>
+              <el-tooltip effect="dark" placement="right" popper-class="max-w-200">
+                <template #content>
+                  关闭后该节点的内容则不输出给用户。
+                  如果你想让用户看到该节点的输出内容，请打开开关。
+                </template>
+                <AppIcon iconName="app-warning" class="app-warning-icon"></AppIcon>
+              </el-tooltip>
+            </div>
+          </template>
+          <el-switch size="small" v-model="form_data.is_result" />
+        </el-form-item>
       </el-form>
     </el-card>
     <!-- 回复内容弹出层 -->
@@ -64,12 +89,23 @@ import { set } from 'lodash'
 import NodeContainer from '@/workflow/common/NodeContainer.vue'
 import NodeCascader from '@/workflow/common/NodeCascader.vue'
 import { ref, computed, onMounted } from 'vue'
+import { isLastNode } from '@/workflow/common/data'
 
 const props = defineProps<{ nodeModel: any }>()
+const isKeyDown = ref(false)
+const wheel = (e: any) => {
+  if (isKeyDown.value) {
+    e.preventDefault()
+  } else {
+    e.stopPropagation()
+    return true
+  }
+}
 const form = {
   reply_type: 'content',
   content: '',
-  fields: []
+  fields: [],
+  is_result: false
 }
 const footers: any = [null, '=', 0]
 
@@ -111,6 +147,10 @@ const validate = () => {
 }
 
 onMounted(() => {
+  if (isLastNode(props.nodeModel)) {
+    set(props.nodeModel.properties.node_data, 'is_result', true)
+  }
+
   set(props.nodeModel, 'validate', validate)
 })
 </script>