import openai
from time import time
import os
import logging
import streamlit as st

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)