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fix: 修复大模型返回json时，解析出错 #656 #697

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Merged
merged 1 commit into from
Jul 3, 2024
Merged

fix: 修复大模型返回json时，解析出错 #656 #697

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15 changes: 9 additions & 6 deletions apps/application/chat_pipeline/step/chat_step/impl/base_chat_step.py
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Original file line number Diff line number Diff line change
Expand Up @@ -143,7 +143,8 @@ def reset_message_list(message_list: List[BaseMessage], answer_text):
def get_stream_result(message_list: List[BaseMessage],
chat_model: BaseChatModel = None,
paragraph_list=None,
no_references_setting=None):
no_references_setting=None,
problem_text=None):
if paragraph_list is None:
paragraph_list = []
directly_return_chunk_list = [AIMessageChunk(content=paragraph.content)
Expand All @@ -153,7 +154,8 @@ def get_stream_result(message_list: List[BaseMessage],
return iter(directly_return_chunk_list), False
elif len(paragraph_list) == 0 and no_references_setting.get(
'status') == 'designated_answer':
return iter([AIMessageChunk(content=no_references_setting.get('value'))]), False
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
else:
Expand All @@ -170,7 +172,7 @@ def execute_stream(self, message_list: List[BaseMessage],
client_id=None, client_type=None,
no_references_setting=None):
chat_result, is_ai_chat = self.get_stream_result(message_list, chat_model, paragraph_list,
no_references_setting)
no_references_setting, problem_text)
chat_record_id = uuid.uuid1()
r = StreamingHttpResponse(
streaming_content=event_content(chat_result, chat_id, chat_record_id, paragraph_list,
Expand All @@ -185,7 +187,8 @@ def execute_stream(self, message_list: List[BaseMessage],
def get_block_result(message_list: List[BaseMessage],
chat_model: BaseChatModel = None,
paragraph_list=None,
no_references_setting=None):
no_references_setting=None,
problem_text=None):
if paragraph_list is None:
paragraph_list = []

Expand All @@ -196,7 +199,7 @@ def get_block_result(message_list: List[BaseMessage],
return directly_return_chunk_list[0], False
elif len(paragraph_list) == 0 and no_references_setting.get(
'status') == 'designated_answer':
return AIMessage(no_references_setting.get('value')), False
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
else:
Expand All @@ -215,7 +218,7 @@ 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)
no_references_setting, problem_text)
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)
Expand Down
6 changes: 3 additions & 3 deletions ...n/chat_pipeline/step/generate_human_message_step/impl/base_generate_human_message_step.py
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Original file line number Diff line number Diff line change
Expand Up @@ -48,9 +48,9 @@ def to_human_message(prompt: str,
if paragraph_list is None or len(paragraph_list) == 0:
if no_references_setting.get('status') == 'ai_questioning':
return HumanMessage(
content=no_references_setting.get('value').format(**{'question': problem}))
content=no_references_setting.get('value').replace('{question}', problem))
else:
return HumanMessage(content=prompt.format(**{'data': "", 'question': problem}))
return HumanMessage(content=prompt.replace('{data}', "").replace('{question}', problem))
temp_data = ""
data_list = []
for p in paragraph_list:
Expand All @@ -63,4 +63,4 @@ def to_human_message(prompt: str,
else:
data_list.append(f"<data>{content}</data>")
data = "\n".join(data_list)
return HumanMessage(content=prompt.format(**{'data': data, 'question': problem}))
return HumanMessage(content=prompt.replace('{data}', data).replace('{question}', problem))
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