app.py

import gradio as gr
from transformers import pipeline

# Load the pre-trained model (cached for performance)
def load_model():
    return pipeline('sentiment-analysis', model='cardiffnlp/twitter-roberta-base-sentiment')

sentiment_model = load_model()

# Define the function to analyze sentiment
def analyze_sentiment(user_input):
    result = sentiment_model(user_input)[0]
    sentiment = result['label']
    
    if sentiment in ['NEGATIVE', 'NEUTRAL']:
        return "Stay positive! 🌟 You can handle anything that comes your way."
    return "You're on the right track! Keep shining! 🌞"

# Gradio UI
def chatbot_ui():
    # Define the interface
    interface = gr.Interface(
        fn=analyze_sentiment,
        inputs=gr.Textbox(label="Enter your text here:"),
        outputs=gr.Textbox(label="Motivational Message"),
        title="Student Sentiment Analysis Chatbot",
        description="This chatbot detects your mood and provides positive or motivational messages."
    )

    return interface

# Launch the interface
if __name__ == "__main__":
    chatbot_ui().launch()