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Qwen3-32B JSON格式化输出不稳定，微调输出格式

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ouyangyouzhang
2025-08-28 09:04:29 +08:00
parent cdaf6870d2
commit 660b5f6561
4 changed files with 110 additions and 55 deletions
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rag2_0/intent_recognition/IntentRecognition.py
+24 -10
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@@ -188,17 +188,19 @@ class AsyncIntentRecognizer:
classification_parser = PydanticOutputParser(pydantic_object=Classification)
formatted_prompt = classification_prompt.format(user_input=query,
classification_info=classification_info,
output_format=classification_parser.get_format_instructions(),
output_format=Classification.get_format_instructions(),
# conversation_context=conversation_context,
chat_history=json.dumps(chat_history, ensure_ascii=False))
# 解析输出
try:
# 异步调用LLM
response = await self._llm.ainvoke(formatted_prompt, extra_body={"enable_thinking": False})
response = await self._llm.ainvoke(formatted_prompt, response_format={"type": "json_object"}, extra_body={"enable_thinking": False})
# response = await self._llm.ainvoke(formatted_prompt, extra_body={"enable_thinking": False})
# 尝试直接解析JSON响应
response.content = response.content.strip()
clean_output = re.sub(r'<think>.*?</think>', '', response.content, flags=re.DOTALL)
clean_output = re.sub(r'\s+', '', clean_output)
parsed_output = classification_parser.parse(clean_output)
# 计算并打印耗时
@@ -262,11 +264,13 @@ class AsyncIntentRecognizer:
formatted_prompt = formatted_prompt.replace("{output_format}", terms_list_parser.get_format_instructions())
# 异步调用LLM
response = await self._llm.ainvoke(formatted_prompt, extra_body={"enable_thinking": False})
response = await self._llm.ainvoke(formatted_prompt, response_format={"type": "json_object"}, extra_body={"enable_thinking": False})
# response = await self._llm.ainvoke(formatted_prompt, extra_body={"enable_thinking": False})
# 尝试使用Pydantic解析器解析TermList
response.content = response.content.strip()
clean_output = re.sub(r'<think>.*?</think>', '', response.content, flags=re.DOTALL)
clean_output = re.sub(r'\s+', '', clean_output)
parsed_output = terms_list_parser.parse(clean_output)
return parsed_output.terms
@@ -335,18 +339,22 @@ class AsyncIntentRecognizer:
</chat_history>
1、请从当前提问内容中提取电力造价行中定额编码、定额名称、清单编码、清单名称
2、请勿随机编造，如果没有提取到，返回空内容
3、返回结果为json格式
2、请勿随机编造，如果没有提取到内容返回空的JSON
3、返回结果为json格式,必须严格以纯JSON格式输出
```json
{{
"dinge_info_list":{{"dinge_code_list":["xxxx","xxxx"], "dinge_name_list":["xxxx","xxxx"]}},
"qingdan_info":{{"qingdan_code_list":["xxxx","xxxx"], "qingdan_name_list":["xxxx","xxxx"]}}
}}
```json
"""
try:
response = await self._llm.ainvoke(prompt, response_format={"type": "json_object"}, extra_body={"enable_thinking": False})
# response = await self._llm.ainvoke(prompt, extra_body={"enable_thinking": False})
response.content = response.content.strip()
clean_output = re.sub(r'<think>.*?</think>', '', response.content, flags=re.DOTALL)
clean_output = re.sub(r'\s+', '', clean_output)
parsed_output = JsonOutputParser().parse(clean_output)
# 计算并打印耗时
@@ -378,16 +386,18 @@ class AsyncIntentRecognizer:
keywords_str = json.dumps(terms_dict, ensure_ascii=False)
query_rewrite_parser = PydanticOutputParser(pydantic_object=QueryRewrite)
formatted_prompt = query_rewrite_prompt_pro.format(query=query,
output_format=query_rewrite_parser.get_format_instructions(),
output_format=QueryRewrite.get_format_instructions(),
keywords=keywords_str,
chat_history=chat_history,
context=context)
# 解析输出
try:
# 异步调用LLM
response = await self._llm.ainvoke(formatted_prompt, extra_body={"enable_thinking": False})
response = await self._llm.ainvoke(formatted_prompt,response_format={"type": "json_object"}, extra_body={"enable_thinking": False})
# response = await self._llm.ainvoke(formatted_prompt, extra_body={"enable_thinking": False})
response.content = response.content.strip()
clean_output = re.sub(r'<think>.*?</think>', '', response.content, flags=re.DOTALL)
clean_output = re.sub(r'\s+', '', clean_output)
parsed_output = query_rewrite_parser.parse(clean_output)
end_time = time.time()
process_time=end_time-start_time
@@ -630,9 +640,11 @@ class AsyncIntentRecognizer:
)
try:
# 异步调用LLM
response = await self._llm.ainvoke(formatted_prompt, extra_body={"enable_thinking": False})
response = await self._llm.ainvoke(formatted_prompt,response_format={"type": "json_object"}, extra_body={"enable_thinking": False})
# response = await self._llm.ainvoke(formatted_prompt, extra_body={"enable_thinking": False})
response.content = response.content.strip()
clean_output = re.sub(r'<think>.*?</think>', '', response.content, flags=re.DOTALL)
clean_output = re.sub(r'\s+', '', clean_output)
# 尝试解析LLM响应
parsed_output = slot_parser.parse(clean_output)
return parsed_output
@@ -660,16 +672,18 @@ class AsyncIntentRecognizer:
query=query,
chat_history=json.dumps(chat_history, ensure_ascii=False) if chat_history else "[]",
# conversation_context=conversation_context,
output_format=step_back_parser.get_format_instructions()
output_format=StepBackPrompt.get_format_instructions()
)
try:
# 异步调用LLM
response = await self._llm.ainvoke(formatted_prompt, extra_body={"enable_thinking": False})
response = await self._llm.ainvoke(formatted_prompt, response_format={"type": "json_object"}, extra_body={"enable_thinking": False})
# response = await self._llm.ainvoke(formatted_prompt, extra_body={"enable_thinking": False})
# 解析输出
response.content = response.content.strip()
clean_output = re.sub(r'<think>.*?</think>', '', response.content, flags=re.DOTALL)
clean_output = re.sub(r'\s+', '', clean_output)
parsed_output = step_back_parser.parse(clean_output)
step_back_end_time = time.time()
step_back_time = step_back_end_time - step_back_start_time