Update app.py

app.py

@@ -2,24 +2,43 @@ import gradio as gr
 from transformers import pipeline
 
 # Load the sentiment analysis pipeline
-classifier = pipeline("sentiment-analysis")
+sentiment_pipeline = pipeline("sentiment-analysis")
 
-# Define the prediction function
+# Function to process input text
 def analyze_sentiment(text):
-    result = classifier(text)[0]
-    label = result['label']
-    score = round(result['score'], 3)
-    return f"Sentiment: {label} (Confidence: {score})"
+    if not text.strip():
+        return "⚠️ Please enter some text."
+    result = sentiment_pipeline(text)[0]
+    label_emoji = "😊" if result["label"] == "POSITIVE" else "😞"
+    return f"{label_emoji} **{result['label']}** (confidence: `{round(result['score'], 3)}`)"
 
-# Create the Gradio interface
-interface = gr.Interface(
-    fn=analyze_sentiment,
-    inputs=gr.Textbox(lines=4, placeholder="Enter some text here..."),
-    outputs="text",
-    title="Sentiment Analysis with Hugging Face 🤗",
-    description="Enter text to find out if the sentiment is positive, negative, or neutral."
-)
+# Create a more styled interface using Gradio Blocks
+with gr.Blocks(title="Sentiment Analyzer") as demo:
+    gr.Markdown(
+        """
+        # 🧠 Sentiment Analysis App
+        _Enter a sentence to discover its emotional tone!_  
+        Uses `distilbert-base-uncased-finetuned-sst-2-english` from Hugging Face 🤗
+        ---
+        """
+    )
+    
+    with gr.Row():
+        with gr.Column():
+            input_text = gr.Textbox(
+                placeholder="Type something like 'I love this app!'",
+                label="Your Text",
+                lines=3
+            )
+            submit_btn = gr.Button("🔍 Analyze")
+        with gr.Column():
+            output = gr.Markdown(label="Sentiment Result")
 
-# Run the app
+    submit_btn.click(fn=analyze_sentiment, inputs=input_text, outputs=output)
+
+    gr.Markdown("---")
+    gr.Markdown("Made with ❤️ using [Gradio](https://gradio.app) and [Hugging Face Transformers](https://huggingface.co/transformers/)")
+
+# For local testing; not required for Spaces
 if __name__ == "__main__":
-    interface.launch()
+    demo.launch()