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Migrate to openai 1.0 #2

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7c57022
migrate to openai 1.0
vanhoanglepsa May 21, 2025
a8ea499
Update gpt_query.py
vanhoanglepsa May 21, 2025
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104 changes: 43 additions & 61 deletions benchmark/logparser/LILAC/gpt_query.py
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
import openai
from openai import OpenAI
import os
import re
import time
Expand All @@ -14,71 +14,51 @@ def get_openai_key(file_path):
key_str = file.readline().strip()
return api_base, key_str

openai.api_base, openai.api_key = get_openai_key('../../openai_key.txt')
print(openai.api_base)
print(openai.api_key)

api_base, api_key = get_openai_key('../../openai_key.txt')
print(api_base)
print(api_key)

openai_client = OpenAI(
api_key=api_key
)


def infer_llm(instruction, exemplars, query, log_message, model='gpt-3.5-turbo-0613', temperature=0.0, max_tokens=2048):
if "turbo" in model:
messages = [{"role": "system", "content": "You are an expert of log parsing, and now you will help to do log parsing."},
{"role": "user", "content": instruction},
{"role": "assistant", "content": "Sure, I can help you with log parsing."},
]

# print(exemplars)
if exemplars is not None:
for i, exemplar in enumerate(exemplars):
messages.append({"role": "user", "content": exemplar['query']})
messages.append(
{"role": "assistant", "content": exemplar['answer']})
messages.append({"role": "user", "content": query})
# my_json = json.dumps(messages, ensure_ascii=False, separators=(',', ':'))
# print(my_json)
else:
messages = f"{instruction}\n"
if exemplars is not None:
messages += "Here are some examples:\n"
for i, exemplar in enumerate(exemplars):
messages += f"{exemplar['query']}\n{exemplar['answer']}\n"
messages += f"Please parse the following log message:\n{query}\n"
messages = [{"role": "system", "content": "You are an expert of log parsing, and now you will help to do log parsing."},
{"role": "user", "content": instruction},
{"role": "assistant",
"content": "Sure, I can help you with log parsing."},
]

# print(exemplars)
if exemplars is not None:
for i, exemplar in enumerate(exemplars):
messages.append({"role": "user", "content": exemplar['query']})
messages.append(
{"role": "assistant", "content": exemplar['answer']})
messages.append({"role": "user", "content": query})
# my_json = json.dumps(messages, ensure_ascii=False, separators=(',', ':'))
# print(my_json)
retry_times = 0
print("model: ", model)
if "turbo" in model:
while retry_times < 3:
try:
answers = openai.ChatCompletion.create(
model=model,
messages=messages,
temperature=temperature,
stream=False,
# frequency_penalty=0.0,
# presence_penalty=0.0,
)
return [response["message"]["content"] for response in answers["choices"] if response['finish_reason'] != 'length'][0]
except Exception as e:
print("Exception :", e)
if "list index out of range" in str(e):
break
# print(answers)
retry_times += 1
else:
while retry_times < 3:
try:
response = openai.Completion.create(
model=model,
prompt=messages,
temperature=temperature,
max_tokens=max_tokens,
)
return response['choices'][0]['text'].strip()
except Exception as e:
print("Exception :", e)
retry_times += 1
while retry_times < 3:
try:
response = openai_client.chat.completions.create(
model=model,
messages=messages,
temperature=temperature,
)
return response.choices[0].message.content.strip('\n')
except Exception as e:
print("Exception :", e)
retry_times += 1
print(f"Failed to get response from OpenAI after {retry_times} retries.")
if exemplars is not None and len(exemplars) > 0:
if exemplars[0]['query'] != 'Log message: `try to connected to host: 172.16.254.1, finished.`' \
or exemplars[0]['answer'] != 'Log template: `try to connected to host: {ip_address}, finished.`':
examples = [{'query': 'Log message: `try to connected to host: 172.16.254.1, finished.`', 'answer': 'Log template: `try to connected to host: {ip_address}, finished.`'}]
or exemplars[0]['answer'] != 'Log template: `try to connected to host: {ip_address}, finished.`':
examples = [{'query': 'Log message: `try to connected to host: 172.16.254.1, finished.`',
'answer': 'Log template: `try to connected to host: {ip_address}, finished.`'}]
return infer_llm(instruction, examples, query, log_message, model, temperature, max_tokens)
return 'Log message: `{}`'.format(log_message)

Expand All @@ -88,7 +68,8 @@ def get_response_from_openai_key(query, examples=[], model='gpt-3.5-turbo-0613',
# instruction = "I want you to act like an expert of log parsing. I will give you a log message enclosed in backticks. You must identify and abstract all the dynamic variables in logs with {placeholder} and output a static log template. Print the input log's template enclosed in backticks."
instruction = "I want you to act like an expert of log parsing. I will give you a log message delimited by backticks. You must identify and abstract all the dynamic variables in logs with {placeholder} and output a static log template. Print the input log's template delimited by backticks."
if examples is None or len(examples) == 0:
examples = [{'query': 'Log message: `try to connected to host: 172.16.254.1, finished.`', 'answer': 'Log template: `try to connected to host: {ip_address}, finished.`'}]
examples = [{'query': 'Log message: `try to connected to host: 172.16.254.1, finished.`',
'answer': 'Log template: `try to connected to host: {ip_address}, finished.`'}]
question = 'Log message: `{}`'.format(query)
responses = infer_llm(instruction, examples, question, query,
model, temperature, max_tokens=2048)
Expand Down Expand Up @@ -158,7 +139,8 @@ def query_template_from_gpt_with_check(log_message, regs_common=[], examples=[],
if tree.match_event(log_message)[0] == "NoMatch":
print("==========================================================")
print(log_message)
print("ChatGPT template wrong: cannot match itself! And the wrong template is : ")
print(
"ChatGPT template wrong: cannot match itself! And the wrong template is : ")
print(template)
print("==========================================================")
else:
Expand Down