Create app.py

app.py

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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()
+