Update app.py

app.py

@@ -1,8 +1,7 @@
-import streamlit as st
+import gradio as gr
 from transformers import pipeline
 
 # Load the pre-trained model (cached for performance)
-@st.cache_resource
 def load_model():
     return pipeline('sentiment-analysis', model='cardiffnlp/twitter-roberta-base-sentiment')
 
@@ -17,17 +16,19 @@ def analyze_sentiment(user_input):
         return "Stay positive! 🌟 You can handle anything that comes your way."
     return "You're on the right track! Keep shining! 🌞"
 
-# Streamlit UI
-st.title("Student Sentiment Analysis Chatbot")
-st.write("This chatbot detects your mood and provides positive or motivational messages.")
+# 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."
+    )
 
-# User input section
-user_input = st.text_area("Enter your text here:")
+    return interface
 
-# Button to analyze sentiment
-if st.button("Analyze Sentiment"):
-    if user_input.strip() == "":
-        st.warning("Please enter some text.")
-    else:
-        message = analyze_sentiment(user_input)
-        st.success(message)
+# Launch the interface
+if __name__ == "__main__":
+    chatbot_ui().launch()