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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.")
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