perf: Optimize code style

Author: wangliang181230

apps/application/flow/step_node/search_knowledge_node/impl/base_search_knowledge_node.py

@@ -27,10 +27,10 @@
 
 def get_embedding_id(dataset_id_list):
     dataset_list = QuerySet(Knowledge).filter(id__in=dataset_id_list)
+    if not dataset_list:
+        raise Exception("知识库设置错误,请重新设置知识库")
     if len(set([dataset.embedding_model_id for dataset in dataset_list])) > 1:
         raise Exception("关联知识库的向量模型不一致，无法召回分段。")
-    if len(dataset_list) == 0:
-        raise Exception("知识库设置错误,请重新设置知识库")
     return dataset_list[0].embedding_model_id
 
 

apps/application/flow/step_node/tool_lib_node/impl/base_tool_lib_node.py

@@ -85,7 +85,7 @@ def valid_reference_value(_type, value, name):
 
 
 def convert_value(name: str, value, _type, is_required, source, node):
-    if not is_required and (value is None or ((isinstance(value, str) or isinstance(value, list)) and len(value) == 0)):
+    if not is_required and (value is None or (isinstance(value, (str, list)) and len(value) == 0)):
         return None
     if source == 'reference':
         value = node.workflow_manage.get_reference_field(

apps/application/flow/step_node/tool_node/impl/base_tool_node.py

@@ -61,7 +61,7 @@ def valid_reference_value(_type, value, name):
 
 
 def convert_value(name: str, value, _type, is_required, source, node):
-    if not is_required and (value is None or ((isinstance(value, str) or isinstance(value, list)) and len(value) == 0)):
+    if not is_required and (value is None or (isinstance(value, (str, list)) and len(value) == 0)):
         return None
     if source == 'reference':
         value = node.workflow_manage.get_reference_field(

apps/application/flow/step_node/video_understand_step_node/impl/base_video_understand_node.py

@@ -211,9 +211,8 @@ def generate_history_ai_message(self, chat_record):
     def generate_history_human_message_for_details(self, chat_record):
         for data in chat_record.details.values():
             if self.node.id == data['node_id'] and 'video_list' in data:
-                video_list = data['video_list'] or  []
-                # 增加对 None 和空列表的检查
-                if not video_list or len(video_list) == 0 or data['dialogue_type'] == 'WORKFLOW':
+                video_list = data['video_list'] or []
+                if not video_list or data['dialogue_type'] == 'WORKFLOW':
                     return HumanMessage(content=chat_record.problem_text)
                 file_id_list = []
                 url_list = []
@@ -242,8 +241,8 @@ def generate_history_human_message(self, chat_record, video_model):
 
         for data in chat_record.details.values():
             if self.node.id == data['node_id'] and 'video_list' in data:
-                video_list = data['video_list'] or  []
-                if video_list is None or len(video_list) == 0 or data['dialogue_type'] == 'WORKFLOW':
+                video_list = data['video_list'] or []
+                if not video_list or data['dialogue_type'] == 'WORKFLOW':
                     return HumanMessage(content=chat_record.problem_text)
                 file_id_list = []
                 url_list = []

apps/application/serializers/application_chat_record.py

@@ -170,7 +170,7 @@ def reset_chat_record(chat_record, show_source, show_exec):
             'padding_problem_text': chat_record.details.get('problem_padding').get(
                 'padding_problem_text') if 'problem_padding' in chat_record.details else None,
             **(show_source_dict if show_source else {}),
-            **(show_exec_dict if show_exec else show_exec_dict)
+            **show_exec_dict
         }
 
     def page(self, current_page: int, page_size: int, with_valid=True, show_source=None, show_exec=None):

apps/chat/mcp/tools.py

@@ -64,9 +64,7 @@ def _get_chat_id(self):
         }).open()
 
     def call_tool(self, params):
-        name = params["name"]
         args = params.get("arguments", {})
-        # print(params)
 
         payload = {
             'message': args.get('message'),

apps/chat/serializers/chat.py

@@ -385,7 +385,6 @@ def get_chat_record(chat_info, chat_record_id):
             chat_record = QuerySet(ChatRecord).filter(id=chat_record_id, chat_id=chat_info.chat_id).first()
             if chat_record is None:
                 raise ChatException(500, _("Conversation record does not exist"))
-            
             return chat_record
         chat_record = QuerySet(ChatRecord).filter(id=chat_record_id).first()
         return chat_record

apps/models_provider/impl/xinference_model_provider/model/reranker.py

@@ -14,6 +14,14 @@
 
 from models_provider.base_model_provider import MaxKBBaseModel
 
+RESTfulClient = None
+try:
+    from xinference.client import RESTfulClient
+except ImportError:
+    try:
+        from xinference_client import RESTfulClient
+    except ImportError as e:
+        pass
 
 class XInferenceReranker(MaxKBBaseModel, BaseDocumentCompressor):
     server_url: Optional[str]
@@ -31,21 +39,14 @@ def new_instance(model_type, model_name, model_credential: Dict[str, object], **
 
     def compress_documents(self, documents: Sequence[Document], query: str, callbacks: Optional[Callbacks] = None) -> \
             Sequence[Document]:
-        if documents is None or len(documents) == 0:
+        if not documents:
             return []
-        client: Any
-        if documents is None or len(documents) == 0:
-            return []
-        try:
-            from xinference.client import RESTfulClient
-        except ImportError:
-            try:
-                from xinference_client import RESTfulClient
-            except ImportError as e:
-                raise ImportError(
-                    "Could not import RESTfulClient from xinference. Please install it"
-                    " with `pip install xinference` or `pip install xinference_client`."
-                ) from e
+
+        if RESTfulClient is None:
+            raise ImportError(
+                "Could not import RESTfulClient from xinference. Please install it"
+                " with `pip install xinference` or `pip install xinference_client`."
+            ) from e
 
         client = RESTfulClient(self.server_url, self.api_key)
         model: RESTfulRerankModelHandle = client.get_model(self.model_uid)

ui/src/locales/lang/en-US/workflow.ts

@@ -215,15 +215,15 @@ export default {
       systemDefault: `#Role
 You are a master of problem optimization, adept at accurately inferring user intentions based on context and optimizing the questions raised by users.
 
-##Skills
-###Skill 1: Optimizing Problems
-2. Receive user input questions.
-3. Carefully analyze the meaning of the problem based on the context.
-4. Output optimized problems.
+## Skills
+### Skill 1: Optimizing Problems
+1. Receive user input questions.
+2. Carefully analyze the meaning of the problem based on the context.
+3. Output optimized problems.
 
-##Limitations:
--Only return the optimized problem without any additional explanation or clarification.
--Ensure that the optimized problem accurately reflects the original problem intent and does not alter the original intention.`,
+## Limitations:
+- Only return the optimized problem without any additional explanation or clarification.
+- Ensure that the optimized problem accurately reflects the original problem intent and does not alter the original intention.`,
     },
     conditionNode: {
       label: 'Conditional Branch',

ui/src/locales/lang/zh-CN/workflow.ts

@@ -217,9 +217,9 @@ export default {
 
 ## 技能
 ### 技能 1: 优化问题
-2. 接收用户输入的问题。
-3. 依据上下文仔细分析问题含义。
-4. 输出优化后的问题。
+1. 接收用户输入的问题。
+2. 依据上下文仔细分析问题含义。
+3. 输出优化后的问题。
 
 ## 限制:
 - 仅返回优化后的问题，不进行额外解释或说明。