Update app.py

app.py

@@ -2,18 +2,23 @@ import streamlit as st
 from transformers import pipeline
 import openai
 import requests
+import torch
 
-# Set up OpenAI API key (or use Hugging Face models if preferred)
-openai.api_key = "YOUR_OPENAI_API_KEY"
+# Set up OpenAI API key (replace with your actual API key)
+openai.api_key = "sk-...yRIA"  # Replace with your actual OpenAI API key
+
+# Check if PyTorch or TensorFlow is installed, required by transformers
+if not torch.cuda.is_available() and not torch.backends.mps.is_available():
+    st.warning("Note: The CPU version of PyTorch is installed. For better performance, use a system with CUDA-enabled GPU.")
 
 # Define the study assistant chatbot
 class StudyAssistantChatbot:
     def __init__(self):
-        # Use Hugging Face's Transformers pipeline or OpenAI for Q&A
-        self.qa_pipeline = pipeline("question-answering", model="distilbert-base-uncased-distilled-squad")
-    
+        # Use Hugging Face's Transformers pipeline with a lightweight model
+        self.qa_pipeline = pipeline("text-generation", model="distilgpt2", framework="pt")
+
     def get_chat_response(self, question: str):
-        # Query the chatbot model (OpenAI) to generate a response
+        # Query OpenAI to generate a response
         response = openai.Completion.create(
             engine="text-davinci-003",
             prompt=f"Provide a study-relevant answer to the question: {question}",
@@ -22,38 +27,36 @@ class StudyAssistantChatbot:
         return response.choices[0].text.strip()
     
     def get_study_tips(self, subject: str):
-        # Placeholder for GROQ API call to fetch study resources
-        # Example: query GROQ API for study resources related to the subject
-        response = requests.get(f"https://api.groq.io/v1/resources?topic={subject}&api_key=YOUR_GROQ_API_KEY")
-        if response.status_code == 200:
+        # Placeholder for a GROQ API call to fetch study resources
+        try:
+            response = requests.get(f"studybot")  # Replace with your GROQ API key
+            response.raise_for_status()
             resources = response.json()
-            return [resource['title'] + ": " + resource['url'] for resource in resources['data']]
-        else:
+            return [f"{resource['title']}: {resource['url']}" for resource in resources['data']]
+        except requests.RequestException:
             return ["Resource not available. Please check your API connection."]
     
     def get_productivity_tips(self):
-        # Static productivity tips as an example
         return [
-            "Break your study time into 25-minute blocks with 5-minute breaks.",
+            "Break study time into 25-minute blocks with 5-minute breaks.",
             "Set specific, achievable study goals each day.",
             "Limit distractions by turning off notifications.",
-            "Try to explain what you learned to someone else to reinforce understanding."
+            "Explain what you learned to someone else to reinforce understanding."
         ]
     
     def get_practice_questions(self, topic: str):
-        # Example set of practice questions based on a topic
         return [
             f"Explain the key concepts of {topic}.",
-            f"List the important formulas related to {topic}.",
+            f"List important formulas related to {topic}.",
             f"How would you apply {topic} in real-world scenarios?"
         ]
 
-# Instantiate chatbot
+# Instantiate the chatbot
 chatbot = StudyAssistantChatbot()
 
 # Streamlit app
 st.title("Personalized Study Assistant Chatbot")
-st.write("Ask me study-related questions, and I’ll provide tips, resources, and more!")
+st.write("Ask study-related questions, get tips, and find resources!")
 
 # Input fields for user queries and topics
 query = st.text_input("Enter your study question:")
@@ -88,4 +91,4 @@ if st.button("Get Practice Questions"):
         for question in practice_questions:
             st.write(f"- {question}")
     else:
-        st.write("Please enter a subject to get practice questions.")
+        st.write("Please enter a subject to get practice questions.")