Update app.py

app.py

@@ -1,4 +1,36 @@
 import streamlit as st
+from transformers import pipeline
 
-x = st.slider('Select a value')
-st.write(x, 'squared is', x * x)
+# Load classification model from Hugging Face
+model_name = "ale-dp/distilbert-base-uncased-finetuned-emotion"
+text_classifier = pipeline('text-classification', model=model_name)
+
+# Define class labels
+class_labels = ["Sadness", "Joy", "Love", "Anger", "Fear", "Surprise"]
+
+def main():
+    st.title("Ordinal Emotion Classifier")
+    user_input = st.text_area("Enter text:")
+
+    if st.button("Classify"):
+        if user_input:
+            results = classify_text(user_input)
+            display_results(results)
+        else:
+            st.warning("Please enter some text to classify.")
+
+def classify_text(text):
+    results = text_classifier(text)
+    return results
+
+def display_results(results):
+    st.subheader("Prediction:")
+
+    for result in results:
+        label = result['label']
+        score = result['score']
+        score_percent = score * 100
+        st.write(f"{label}: {score_percent:.2f}%")
+
+if __name__ == "__main__":
+    main()