Update app.py

app.py

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+import streamlit as st
+from transformers import pipeline
+
+# Initialize the emotion detection pipeline
+emotion_model = pipeline("text-classification", model="j-hartmann/emotion-english-distilroberta-base")
+
+# Set up the title and description
+st.title("Emotion Detector in Text")
+st.write("Type a text below, and the model will predict the emotion behind it.")
+
+# Input field for text
+user_input = st.text_area("Enter your text here:")
+
+if st.button("Detect Emotion"):
+    if user_input.strip():
+        # Get emotion predictions
+        emotion = emotion_model(user_input)[0]
+        label = emotion['label']
+        score = emotion['score']
+        
+        # Display emotion and confidence score
+        st.write(f"**Detected Emotion:** {label}")
+        st.write(f"**Confidence Score:** {score:.2f}")
+    else:
+        st.error("Please enter some text.")
+
+# Footer
+st.markdown("Developed by [Your Name]. Deployed on Hugging Face Spaces.")