Update app.py

app.py

@@ -1,45 +1,73 @@
 import streamlit as st
+from transformers import pipeline
 import openai
+import requests
+import torch
 
 # Initialize OpenAI API key
 openai.api_key = "sk-...1-AA"  # Replace with your actual OpenAI API key
 
 # Function to get responses from OpenAI
 def get_chat_response(query):
-    try:
-        response = openai.ChatCompletion.create(
-            model="gpt-3.5-turbo",  # Use the desired model from OpenAI
-            messages=[
-                {"role": "user", "content": query}
-            ]
-        )
-        return response.choices[0].message['content']
-    except Exception as e:
-        st.error(f"An error occurred: {e}")
-        return None
+    response = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo",  # Choose the model you want to use
+        messages=[
+            {"role": "user", "content": query}
+        ]
+    )
+    return response.choices[0].message['content']
+
+# Class for the local chatbot using Hugging Face Transformers
+class StudyAssistantChatbot:
+    def __init__(self):
+        # Load local model (ensure PyTorch is installed)
+        try:
+            self.qa_pipeline = pipeline("text-generation", model="distilgpt2")
+        except RuntimeError as e:
+            st.error(f"Error loading the model: {e}")
+            st.error("Please make sure either TensorFlow or PyTorch is installed.")
+            raise
+
+    def generate_study_tips(self, query):
+        # Generate a local response
+        response = self.qa_pipeline(query, max_length=50, num_return_sequences=1)
+        return response[0]['generated_text']
 
 # Initialize Streamlit app
 st.title("Personalized Study Assistant Chatbot")
 
+# Create chatbot instance
+try:
+    chatbot = StudyAssistantChatbot()
+except RuntimeError:
+    st.stop()
+
 # Input for user query
 query = st.text_input("Ask your study-related question:")
 
-# Generate response
 if st.button("Get Tips and Resources"):
     if query:
-        # Get response from OpenAI
+        # Get response from OpenAI API
         response = get_chat_response(query)
         if response:
+            st.subheader("OpenAI GPT Response:")
             st.write(response)
         else:
-            st.write("There was an error generating the response. Please try again.")
+            st.write("Unable to get a response from OpenAI at the moment.")
+        
+        # Get study tips from the local model as well
+        st.subheader("Study Tips from Local Model:")
+        tips_response = chatbot.generate_study_tips(query)
+        if tips_response:
+            st.write(tips_response)
+        else:
+            st.write("Unable to generate study tips at the moment.")
     else:
         st.write("Please enter a question to get started!")
 
 # Add a sidebar for additional information
 st.sidebar.header("About")
-st.sidebar.text("This is a personalized study assistant chatbot."
-
+st.sidebar.text("This is a personalized study assistant chatbot that provides responses from OpenAI GPT and study tips generated locally.")