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# -*- coding: utf-8 -*-
__author__ = "Yash Kumar Lal, Github@ykl7"
import os
import openai
from openai import OpenAI
import anthropic
import time
import random
random.seed(1234)
class LLMReasoner():
def __init__(self, options):
if options["model_family"] == "OpenAI":
self.client = OpenAI(api_key=options["API_KEY"])
elif options["model_family"] == "Anthropic":
os.environ["ANTHROPIC_API_KEY"] = options["API_KEY"]
self.client = anthropic.Anthropic()
self.model_family = options["model_family"]
self.model_name = options["model_name"]
self.max_tokens = options["max_tokens"]
self.temp = 0.0 if "temperature" not in options else options["temperature"]
self.top_p = 1.0 if "top_p" not in options else options["top_p"]
self.frequency_penalty = 0.0 if "frequency_penalty" not in options else options["frequency_penalty"]
self.presence_penalty = 0.0 if "presence_penalty" not in options else options["presence_penalty"]
def make_openai_chat_completions_api_call(self, message):
prompt = [{"role": "user", "content": message}]
try:
if "gpt-4o" in self.model_name:
response = self.client.chat.completions.create(
model=self.model_name,
messages=prompt,
temperature=self.temp,
max_completion_tokens=self.max_tokens,
top_p=self.top_p,
frequency_penalty=self.frequency_penalty,
presence_penalty=self.presence_penalty
)
elif "o3-mini" in self.model_name:
response = self.client.chat.completions.create(
model=self.model_name,
messages=prompt,
reasoning_effort="medium"
)
return self.parse_chat_completions_api_response(response)
except openai.APIConnectionError as e:
print("The server could not be reached")
print(e.__cause__) # an underlying Exception, likely raised within httpx.
time.sleep(60)
return self.make_openai_chat_completions_api_call(prompt)
except openai.RateLimitError as e:
print("Rate limit error hit")
exit()
except openai.NotFoundError as e:
print("Model not found")
exit()
except openai.APIStatusError as e:
print("Another non-200-range status code was received")
print(e.status_code)
print(e)
time.sleep(60)
return self.make_openai_chat_completions_api_call(prompt)
def parse_chat_completions_api_response(self, response):
# print(response.model_dump())
choices = response.choices
main_response = choices[0].message
main_response_message, main_response_role = main_response.content, main_response.role
return main_response_message, response
def call_claude(self, claude_prompt=""):
try:
message = self.client.messages.create(
model=self.model_name,
max_tokens=self.max_tokens,
temperature=self.temp,
system="",
messages=[
{
"role": "user",
"content": [
{
"type": "text",
"text": claude_prompt
}
]
}
]
)
except Exception as e:
breakpoint()
print(e)
time.sleep(30)
call_claude(self, claude_prompt)
if message.content[0].type == "text":
return message.content[0].text, message
else:
return "Error", message
def run_inference(self, prompt=[]):
if self.model_family == "OpenAI":
response_text, response = self.make_openai_chat_completions_api_call(prompt)
elif self.model_family == "Anthropic":
response_text, response = self.call_claude(prompt)
return response_text |