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| import openai | |
| from time import time | |
| import os | |
| import logging | |
| import streamlit | |
| openai.api_key = st.secrets["openai_api_key"] | |
| def gpt_rephrase(fact): | |
| # Dynamically generate the prompt to rephrase the fact as a PubMed query using GPT3.5 | |
| prompt = f"Rephrase the following fact as a Pubmed search query.\n\ | |
| FACT: {fact}\n\ | |
| PUBMED QUERY:" | |
| try: | |
| response = openai.Completion.create( | |
| model="text-ada-001", | |
| 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 check_fact(evidence, fact): | |
| # Dynamically generate the prompt to check the fact against the given PubMed article conclusion/abstract | |
| prompt = f"Based exclusively on the evidence provided, is the following hypothesis True, False or Undetermined?\n\ | |
| EVIDENCE: {evidence}\n \ | |
| HYPOTHESIS: {fact}\n \ | |
| ANSWER:" | |
| try: | |
| response = openai.Completion.create( | |
| model="text-ada-001", | |
| prompt=prompt, | |
| max_tokens=2, | |
| 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_rephrase(fact): | |
| # Dynamically generate the prompt to rephrase the fact as a PubMed query using GPT3.5 turbo - lower cost than 3.5 | |
| prompt = f"Rephrase the following fact as a Pubmed search query.\n\ | |
| FACT: {fact}\n\ | |
| PUBMED QUERY:" | |
| 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) | |