OpenAI Skeleton for Those Looking to Iteratively Employ ChatGPT

GPT_iteration.py

#!/usr/bin/env python3

import json
import openai
import time
import os
import logging
from openai.error import InvalidRequestError, RateLimitError
from concurrent.futures import ThreadPoolExecutor

# Set up logging
logging.basicConfig(filename='placeholder.log', level=logging.DEBUG)

file_path = "~/placeholder.json"
output_path = "placeholder.json"
assert file_path != output_path
model = 'gpt-4-1106-preview'
api_keys = "sk-placeholder"

prompt_template = """
[placeholder]
"""

system_prompt = """
[placeholder]
"""

# Read the JSON file
logging.info('Reading JSON file')
print('Reading JSON file')
with open(file_path, 'r') as f:
    data = json.load(f)

# Open the output file in append mode
logging.info('Opening output file in append mode')
print('Opening output file in append mode')
with open(output_path, 'a') as f:
    # Iterate over the key-value pairs in the JSON data
    logging.info('Iterating over JSON data')
    print('Iterating over JSON data')
    for item in data:

        # Format the prompt
        logging.info('Formatting prompt')
        print('Formatting prompt')
        prompt = prompt_template.format(source_code=item["source_code"])

        # Send the prompt to the OpenAI API
        def send_prompt(api_key):
            logging.info('Sending prompt to OpenAI API')
            print('Sending prompt to OpenAI API')
            openai.api_key = api_key
            try:
                logging.info('Creating chat completion')
                print('Creating chat completion')
                chat_completion = openai.ChatCompletion.create(
                    model=model,
                    messages=[{"role": "system", "content": prompt}]
                )
            except InvalidRequestError as e:
                logging.error(f"InvalidRequestError: {e}")
                print("\nError: ", e)
                print()
                time.sleep(10)
                return
            except RateLimitError as e:
                logging.error(f"RateLimitError: {e}")
                print("\nError: ", e)
                print()
                time.sleep(10)
                return

            # Write the response to the output file
            logging.info('Writing response to output file')
            print('Writing response to output file')
            f.write(json.dumps({"prompt": chat_completion}))
            f.write('\n')  # Write a newline character to separate responses

        # Use ThreadPoolExecutor to send concurrent requests
        logging.info('Sending concurrent requests')
        print('Sending concurrent requests')
        with ThreadPoolExecutor() as executor:
            executor.map(send_prompt, api_keys)

        # Sleep for a while to avoid hitting the rate limit
        logging.info('Sleeping to avoid hitting rate limit')
        print('Sleeping to avoid hitting rate limit')
        time.sleep(10)