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

# Chatbot response function
def chatbot_response(user_input):
    # Ensure the input is in lowercase and stripped of extra spaces
    user_input = user_input.strip().lower()

    # Define responses for specific queries
    if "hello" in user_input or "hi" in user_input:
        return "Hello! How can I help you with your studies today?"

    # Handle time management query
    elif "time management" in user_input:
        return "Time management is key! Try creating a prioritized to-do list and setting specific study blocks."

    # Handle study tips query
    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)

    # If input doesn't match predefined queries
    else:
        return "I'm here to assist with general academic questions. Feel free to ask about study tips, time management, or anything else!"

# Gradio interface setup
with gr.Blocks() as demo:
    gr.Markdown("# Study Assistance Chatbot")
    gr.Markdown("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
    
    # Submit action - to update chat with response
    submit_button.click(chatbot_response, inputs=user_input, outputs=chatbot)

# Launch the Gradio app
demo.launch()