fix: Easy application import (#1930)

Author: shaohuzhang1

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

@@ -170,7 +170,7 @@ def get_stream_result(message_list: List[BaseMessage],
             return iter(
                 [AIMessageChunk(content=no_references_setting.get('value').replace('{question}', problem_text))]), False
         if chat_model is None:
-            return iter([AIMessageChunk('抱歉，没有配置 AI 模型，无法优化引用分段，请先去应用中设置 AI 模型。')]), False
+            return iter([AIMessageChunk('抱歉，没有配置 AI 模型，请先去应用中设置 AI 模型。')]), False
         else:
             return chat_model.stream(message_list), True
 
@@ -214,7 +214,7 @@ def get_block_result(message_list: List[BaseMessage],
                 'status') == 'designated_answer':
             return AIMessage(no_references_setting.get('value').replace('{question}', problem_text)), False
         if chat_model is None:
-            return AIMessage('抱歉，没有配置 AI 模型，无法优化引用分段，请先去应用中设置 AI 模型。'), False
+            return AIMessage('抱歉，没有配置 AI 模型，请先去应用中设置 AI 模型。'), False
         else:
             return chat_model.invoke(message_list), True
 

apps/application/chat_pipeline/step/reset_problem_step/i_reset_problem_step.py

@@ -45,8 +45,9 @@ def _run(self, manage: PipelineManage):
         manage.context['problem_text'] = source_problem_text
         manage.context['padding_problem_text'] = padding_problem
         # 累加tokens
-        manage.context['message_tokens'] = manage.context['message_tokens'] + self.context.get('message_tokens')
-        manage.context['answer_tokens'] = manage.context['answer_tokens'] + self.context.get('answer_tokens')
+        manage.context['message_tokens'] = manage.context.get('message_tokens', 0) + self.context.get('message_tokens',
+                                                                                                      0)
+        manage.context['answer_tokens'] = manage.context.get('answer_tokens', 0) + self.context.get('answer_tokens', 0)
 
     @abstractmethod
     def execute(self, problem_text: str, history_chat_record: List[ChatRecord] = None, model_id: str = None,

apps/application/chat_pipeline/step/reset_problem_step/impl/base_reset_problem_step.py

@@ -25,6 +25,8 @@ def execute(self, problem_text: str, history_chat_record: List[ChatRecord] = Non
                 user_id=None,
                 **kwargs) -> str:
         chat_model = get_model_instance_by_model_user_id(model_id, user_id) if model_id is not None else None
+        if chat_model is None:
+            return problem_text
         start_index = len(history_chat_record) - 3
         history_message = [[history_chat_record[index].get_human_message(), history_chat_record[index].get_ai_message()]
                            for index in
@@ -57,8 +59,8 @@ def get_details(self, manage, **kwargs):
             'step_type': 'problem_padding',
             'run_time': self.context['run_time'],
             'model_id': str(manage.context['model_id']) if 'model_id' in manage.context else None,
-            'message_tokens': self.context['message_tokens'],
-            'answer_tokens': self.context['answer_tokens'],
+            'message_tokens': self.context.get('message_tokens', 0),
+            'answer_tokens': self.context.get('answer_tokens', 0),
             'cost': 0,
             'padding_problem_text': self.context.get('padding_problem_text'),
             'problem_text': self.context.get("step_args").get('problem_text'),

apps/application/serializers/application_serializers.py

@@ -716,10 +716,11 @@ def to_application(application, user_id):
                                desc=application.get('desc'),
                                prologue=application.get('prologue'), dialogue_number=application.get('dialogue_number'),
                                dataset_setting=application.get('dataset_setting'),
+                               model_setting=application.get('model_setting'),
                                model_params_setting=application.get('model_params_setting'),
                                tts_model_params_setting=application.get('tts_model_params_setting'),
                                problem_optimization=application.get('problem_optimization'),
-                               icon=application.get('icon'),
+                               icon="/ui/favicon.ico",
                                work_flow=work_flow,
                                type=application.get('type'),
                                problem_optimization_prompt=application.get('problem_optimization_prompt'),