import streamlit as st
from transformers import pipeline
import openai
import requests

# 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):
    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 StudyAssistantChatbot:
    def __init__(self):
        # Check if either TensorFlow or 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

# 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:")

if st.button("Get Tips and Resources"):
    if query:
        # Get response from OpenAI
        response = get_chat_response(query)
        st.write(response)
    else:
        st.write("Please enter a question to get started!")

# Add a sidebar for additional options
st.sidebar.header("About")
st.sidebar.text("This is a personalized study assistant chatbot.")