import streamlit as st import google.generativeai as palm from gradio_client import Client # Initialize the Gradio client with the API URL client = Client("https://akdeniz27-llama-2-70b-chat-hf-with-easyllm.hf.space/") # Information about obtaining a free API key st.sidebar.info("Get your free palm2 API key at [makersuite.google.com/app/apikey](https://makersuite.google.com/app/apikey)") # Ask the user for palm2 API key api_key_palm2 = st.sidebar.text_input("Enter your palm2 API key for study notes:", type="password") palm.configure(api_key=api_key_palm2) # Styling for the title st.title("Auto Study Notes Generator") st.markdown("---") # Sidebar for settings st.sidebar.title("Settings") # User choice for mode selection selected_mode = st.sidebar.radio("Select Mode:", ['Generate Study Notes (Palm2)', 'Use Llama 70b for Notes']) # Main content area if selected_mode == 'Generate Study Notes (Palm2)': st.header("Study Notes Generation (Palm2)") user_class = st.sidebar.selectbox('Select your class:', ['Class 1', 'Class 2', 'Class 3', 'Class 4', 'Class 5', 'Class 6', 'Class 7', 'Class 8', 'Class 9', 'Class 10', 'Class 11', 'Class 12']) user_input = st.text_input(f'Enter your study topic for {user_class}:') st.markdown("---") if st.button('Generate Study Notes'): if user_input.lower() in ['quit', 'exit', 'bye']: st.success("Goodbye! Have a great day!") else: with st.spinner("Generating study notes. Please wait..."): st.subheader(f"Making notes for you on '{user_input}'") prompt = f"Provide study notes for {user_class} on the topic: {user_input}." response = palm.generate_text(model='models/text-bison-001', prompt=prompt) study_notes = response.result # Display the generated study notes st.subheader(f"Study Notes for {user_class} - {user_input}:") st.write(study_notes) elif selected_mode == 'Use Llama 70b for Notes': st.header("Llama 70b Mode") llama_input = st.text_input('Enter a message for Llama 70b (type "exit" to quit):') st.markdown("---") if st.button('Get Llama 70b Response'): if llama_input.lower() == 'exit': st.success("Exiting Llama 70b mode. Have a great day!") else: with st.spinner("Getting response from Llama 70b. Please wait..."): # Make a prediction using Llama 70b API llama_result = client.predict( llama_input, api_name="/chat" ) # Check if the result is not None if llama_result is not None: # Display the result st.subheader("Llama 70b Response:") st.write(llama_result) else: st.warning("Llama 70b API response was None. Please try again later.") # Add a footer with updated text st.sidebar.markdown("---") st.sidebar.text("© 2023 HelpingAI") # Hide Streamlit menu st.markdown(""" """, unsafe_allow_html=True)