studychatbot / chatbot_ui.py
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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()