import gradio as gr  # For building the chatbot UI
import random  # For generating random responses

# Chatbot response function
def chatbot_response(user_input, history):
    user_input = user_input.lower()

    # Handle empty input and greet the user
    if user_input.strip() == "":
        return "Welcome! How can I assist you with your studies today?", history

    # Predefined responses based on user input
    if "time management" in user_input:
        return "Time management is key! Try creating a prioritized to-do list and setting specific study blocks.", history

    elif "study tips" in user_input:
        tips = [
            "Take regular breaks while studying to stay focused.",
            "Use active recall and spaced repetition for better retention.",
            "Set a specific goal for each study session."
        ]
        return random.choice(tips), history

    elif "hello" in user_input or "hi" in user_input:
        return "Hello! How can I help you with your studies today?", history

    else:
        return "I'm here to assist with general academic questions. Feel free to ask about study tips, time management, or anything else!", history

# Gradio interface setup
with gr.Blocks() as demo:
    gr.Markdown("# Study Assistance Chatbot")
    gr.Markdown("Welcome! Ask me anything related to your academic studies.")
    
    chatbot = gr.Chatbot()  # Chat history UI
    user_input = gr.Textbox(label="Enter your question here:", placeholder="Type your question...")  # Textbox for user input
    submit_button = gr.Button("Submit")  # Submit button for user input
    
    # Initialize the chat history with a welcome message
    initial_history = [("Chatbot", "Welcome! How can I assist you with your studies today?")]

    # Submit action - to update chat with response and add it to chat history
    submit_button.click(chatbot_response, inputs=[user_input, chatbot], outputs=[user_input, chatbot])

# Launch the Gradio app
demo.launch()