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refactor: 移除llm.invoke中冗余的need_retry参数

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ouyangyouzhang
2025-09-15 16:54:55 +08:00
parent 0f11b0ba5e
commit 0541db1e34
2 changed files with 5 additions and 5 deletions
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rag2_0/demo/dialogue_to_workorder.py
+4 -4
View File
@@ -366,7 +366,7 @@ class DialogueToWorkorder:
output_format = self.user_question_and_solution_parser.get_format_instructions()
llm_prompt = prompt.format(output_format=output_format, dialogue_str=dialogue_str)
response = self.llm.invoke(user_prompt=llm_prompt, need_retry=False)
response = self.llm.invoke(user_prompt=llm_prompt)
clean_output = re.sub(r'<think>.*?</think>', '', response.content, flags=re.DOTALL)
try:
if clean_output.count('user_question') == 1:
@@ -396,7 +396,7 @@ class DialogueToWorkorder:
except Exception as e:
output_format = self.user_question_and_solution_list_parser.get_format_instructions()
llm_prompt = prompt.format(output_format=output_format, dialogue_str=dialogue_str)
response = self.llm.invoke(user_prompt=llm_prompt, need_retry=False)
response = self.llm.invoke(user_prompt=llm_prompt)
clean_output = re.sub(r'<think>.*?</think>', '', response.content, flags=re.DOTALL)
user_question_and_solution_temp = self.user_question_and_solution_list_parser.parse(clean_output)
return user_question_and_solution_temp.user_question_list
@@ -434,7 +434,7 @@ class DialogueToWorkorder:
{dialogue_str}
"""
response = self.llm.invoke(user_prompt=prompt, need_retry=False)
response = self.llm.invoke(user_prompt=prompt)
clean_output = re.sub(r'<think>.*?</think>', '', response.content, flags=re.DOTALL)
question_type = self.question_type_parser.parse(clean_output)
@@ -471,7 +471,7 @@ class DialogueToWorkorder:
"""
response = self.llm.invoke(user_prompt=prompt, need_retry=False)
response = self.llm.invoke(user_prompt=prompt)
clean_output = re.sub(r'<think>.*?</think>', '', response.content, flags=re.DOTALL)
is_complaint = self.is_complaint_parser.parse(clean_output)
rag2_0/dify/DifyCompareTest.py
+1 -1
View File
@@ -73,7 +73,7 @@ class DifyCompareTest:
return "回答基本不相同"
while retry_count < max_retries:
try:
response = self.llm.invoke(user_prompt=user_prompt, need_retry=False, response_format={"type": "json_object"})
response = self.llm.invoke(user_prompt=user_prompt, response_format={"type": "json_object"})
response.content = response.content.strip()
clean_output = re.sub(r'<think>.*?</think>', '', response.content, flags=re.DOTALL)
result = JsonOutputParser().parse(clean_output)