Update app.py

app.py

@@ -1,6 +1,7 @@
 import numpy as np
 import requests
 import streamlit as st
+import openai
 
 #def main():
 st.title("Scientific Question Generation")
@@ -10,6 +11,7 @@ checkpoints = ['dhmeltzer/bart-large_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}"
@@ -35,16 +37,40 @@ if user_input:
         model_name = checkpoint.split('/')[1]
 
         if 'flan' in model_name.lower():
-            user_input = 'generate a question: '+user_input
+            
+            prompt = 'generate a question: ' + user_input
         
-        output = query(checkpoint,{
-            "inputs": user_input,
-            "temperature":temperature,
-            "wait_for_model":True})
+            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()