app.py

app.py

@@ -1,21 +1,20 @@
-from transformers import pipeline
 import gradio as gr
+from transformers import pipeline
 
-# Load the sentiment-analysis pipeline
-sentiment_pipeline = pipeline("sentiment-analysis", model="nlptown/bert-base-multilingual-uncased-sentiment")
+# Load multilingual sentiment model
+sentiment_pipeline = pipeline("sentiment-analysis", model="tabularisai/multilingual-sentiment-analysis")
 
 def analyze_sentiment(text):
-    result = sentiment_pipeline(text)
-    return result[0]
+    result = sentiment_pipeline(text)[0]
+    return f"{result['label']} ({round(result['score'], 2)})"
 
-# Create a Gradio interface
 iface = gr.Interface(
-    fn=analyze_sentiment, 
-    inputs="text", 
-    outputs="text", 
-    title="Sentiment Analysis",
-    description="Enter some text to analyze its sentiment."
+    fn=analyze_sentiment,
+    inputs=gr.Textbox(label="Enter Text"),
+    outputs="text",
+    title="Multilingual Sentiment Analysis 🌐",
+    description="Analyze text sentiment in multiple languages using Hugging Face."
 )
 
-# Launch the interface
-iface.launch()
+if __name__ == "__main__":
+    iface.launch()