Update app.py

app.py

@@ -1,4 +1,4 @@
-import gradio as gr
+import streamlit as st
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 import torch
 
@@ -15,12 +15,13 @@ def predict_emotion(text):
     prediction = torch.argmax(outputs.logits, dim=-1).item()
     return "Positive Emotion" if prediction == 1 else "Negative Emotion"
 
-# Create the Gradio interface
-iface = gr.Interface(fn=predict_emotion, 
-                     inputs="text", 
-                     outputs="text", 
-                     title="ChefBERT Emotion Classifier",
-                     description="Enter a sentence and ChefBERT will predict whether the emotion is positive (1) or negative (0).")
+# Streamlit app layout
+st.title("Emotion Classifier")
+st.write("Enter a sentence and ChefBERT will predict whether the emotion is positive (1) or negative (0).")
 
-# Launch the interface
-iface.launch()
+# Input box
+user_input = st.text_input("Input Sentence", "")
+
+if user_input:
+    result = predict_emotion(user_input)
+    st.write("Prediction: ", result)