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| import openai | |
| from time import time | |
| import os | |
| import logging | |
| import streamlit as st | |
| openai.api_key = st.secrets['openai_API_key'] | |
| def open_file(filepath): | |
| with open(filepath, 'r', encoding='utf-8') as file: | |
| return file.read() | |
| def gpt35_rephrase(fact): | |
| # Dynamically generate the prompt to rephrase the fact as a PubMed query using GPT3.5 | |
| prompt = open_file('prompts/gpt35_rephrase.txt').replace('<<FACT>>', fact) | |
| try: | |
| response = openai.Completion.create( | |
| model='text-davinci-003', | |
| prompt=prompt, | |
| max_tokens=250, | |
| temperature=0 | |
| ) | |
| response = response['choices'][0]['text'].strip() | |
| filename = '%s_gpt3.txt' % time() | |
| # Create the logs folder if it does not exist | |
| if not os.path.exists('gpt3_rephrase_logs'): | |
| os.makedirs('gpt3_rephrase_logs') | |
| # Save the whole prompt and the response so that we can inspect it when necessary | |
| with open('gpt3_rephrase_logs/%s' % filename, 'w', encoding="utf-8") as outfile: | |
| outfile.write('PROMPT:\n\n' + prompt + '\n\n###############\n\nRESPONSE:\n\n' + response) | |
| return response | |
| except Exception as e: | |
| logging.error('Error communicating with OpenAI (rephrase): ', exc_info=e) | |
| def gpt35_check_fact(evidence, fact): | |
| # Dynamically generate the prompt to check the fact against the given PubMed article conclusion/abstract | |
| prompt = open_file('prompts/gpt35_fact_check.txt').replace('<<EVIDENCE>>', evidence).replace('<<HYPOTHESIS>>', fact) | |
| try: | |
| response = openai.Completion.create( | |
| model="text-davinci-003", | |
| prompt=prompt, | |
| max_tokens=3, # Don't need more for Entails/Contradicts/Undetermined | |
| temperature=0 | |
| ) | |
| response = response['choices'][0]['text'].strip() | |
| response = response.replace('.', '') | |
| filename = '%s_gpt3.txt' % time() | |
| if not os.path.exists('gpt3_factchecking_logs'): | |
| os.makedirs('gpt3_factchecking_logs') | |
| with open('gpt3_factchecking_logs/%s' % filename, 'w', encoding='utf-8') as outfile: | |
| outfile.write('PROMPT:\n\n' + prompt + '\n\n###############\n\nRESPONSE:\n\n' + response) | |
| return response | |
| except Exception as e: | |
| logging.error('Error communicating with OpenAI (check_fact): ', exc_info=e) | |
| def gpt35_turbo_rephrase(fact): | |
| # Dynamically generate the prompt to rephrase the fact as a PubMed query using GPT3.5 turbo - lower cost than 3.5 | |
| prompt = open_file('prompts/gpt35_rephrase.txt').replace('<<FACT>>', fact) | |
| try: | |
| response = openai.ChatCompletion.create( | |
| model="gpt-3.5-turbo", | |
| messages=[ | |
| {'role': 'user', | |
| 'content': prompt} | |
| ] | |
| ) | |
| response = response['choices'][0]['message']['content'].strip() | |
| filename = '%s_gpt3.txt' % time() | |
| if not os.path.exists('gpt35_rephrase_logs'): | |
| os.makedirs('gpt35_rephrase_logs') | |
| with open('gpt35_rephrase_logs/%s' % filename, 'w', encoding="utf-8") as outfile: | |
| outfile.write('PROMPT:\n\n' + prompt + '\n\n###############\n\nRESPONSE:\n\n' + response) | |
| return response | |
| except Exception as e: | |
| logging.error('Error communicating with OpenAI (gpt35_rephrase): ', exc_info=e) | |