app.py

import numpy as np
import requests
import streamlit as st
import openai

#def main():
st.title("Scientific Question Generation")

checkpoints = ['dhmeltzer/bart-large_askscience-qg',
          'dhmeltzer/flan-t5-base_askscience-qg',
          'google/flan-t5-xxl']

headers = {"Authorization": f"Bearer {st.secrets['HF_token']}"}
openai.api_key = st.secrets['OpenAI_token']

def query(checkpoint, payload):
    API_URL = f"https://api-inference.huggingface.co/models/{checkpoint}"
    
    response = requests.post(API_URL, 
                                headers=headers, 
                                json=payload)
    
    return response.json()

# User search
user_input = st.text_area("Question Generator", 
                            """Black holes are the most gravitationally dense objects in the universe.""")

# Filters
st.sidebar.markdown("**Filters**")

temperature = st.sidebar.slider("Temperature", 0.0, 1.0, 0.0,.1)

if user_input:
    for checkpoint in checkpoints:
        
        model_name = checkpoint.split('/')[1]

        if 'flan' in model_name.lower():
            
            prompt = 'generate a question: ' + user_input
        
            output = query(checkpoint,{
                "inputs": prompt,
                "temperature":temperature,
                "wait_for_model":True})[0]['generated_text']
        else:

            prompt = user_input
            
            output = query(checkpoint,{
                "inputs": prompt,
                "temperature":temperature,
                "wait_for_model":True})[0]['generated_text']
        
        st.write(f'Model {model_name}: {output}')

    model_engine = "gpt-3.5-turbo"
    max_tokens = 50
    
    prompt = f"generate a question: {user_input}"

    response=openai.ChatCompletion.create(
        model=model_engine,
        messages=[
            {"role": "system", "content": "You are a helpful assistant that generates questions from text."},
            {"role": "user", "content": prompt},
        ])

    output = response['choices'][0]['message']['content']
    
    st.write(f'Model {model_engine}: {output}')

        
#if __name__ == "__main__":
#    main()