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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()
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