Update app.py

app.py

@@ -1,25 +1,23 @@
 import gradio as gr
 from transformers import pipeline
 
-# Load the pretrained sentiment pipeline
-sentiment_pipeline = pipeline("sentiment-analysis")
+# Load the emotion detection pipeline
+emotion_pipeline = pipeline("text-classification", model="bhadresh-savani/distilbert-base-uncased-emotion")
 
-def predict_sentiment(text):
-    result = sentiment_pipeline(text)[0]
+def predict_emotion(text):
+    result = emotion_pipeline(text)[0]
     label = result["label"]
-    
-    if label == "POSITIVE":
-        return "✅ POSITIVE 😊"
-    else:
-        return "❌ NEGATIVE 😠"
+    score = result["score"]
+
+    return f"🧠 Emotion: {label.upper()} ({score:.2f})"
 
 # Gradio Interface
 demo = gr.Interface(
-    fn=predict_sentiment,
-    inputs=gr.Textbox(lines=3, placeholder="Type your sentence here..."),
+    fn=predict_emotion,
+    inputs=gr.Textbox(lines=3, placeholder="Type something emotional..."),
     outputs="text",
-    title="💬 LM Studios Sentiment Detector",
-    description="Now powered by a Hugging Face transformer model for smarter predictions.",
+    title="🎭 LM Studios Emotion Detector",
+    description="Now with real emotional awareness: detects joy, anger, sadness, fear, love, and surprise.",
     theme="default",
     flagging_mode="never"
 )