Update app.py

app.py

@@ -1,11 +1,11 @@
- import gradio as gr
+import gradio as gr
 from transformers import pipeline
 
 # Load the sentiment analysis pipeline
-model_name = "monsifnadir/DarijaBERT-Sentiment"  # Remplacez par le bon modèle si nécessaire
+model_name = "monsifnadir/DarijaBERT-Sentiment"  # Change if necessary
 sentiment_pipeline = pipeline("text-classification", model=model_name)
 
-# Mapping des labels Hugging Face vers des catégories de sentiments compréhensibles
+# Map numerical labels to sentiment categories
 label_map = {
     "LABEL_0": "Negative",
     "LABEL_1": "Neutral",
@@ -13,16 +13,15 @@ label_map = {
 }
 
 def classify_text(text):
-    """Analyse le sentiment du texte."""
     result = sentiment_pipeline(text)
     label = result[0]["label"]
     score = result[0]["score"]
     
-    # Convertir le label en catégorie de sentiment
+    # Map the label to actual sentiment
     sentiment = label_map.get(label, "Unknown")
     return f"Sentiment: {sentiment} (Confidence: {score:.2f})"
 
-# Interface Gradio
+# Create Gradio interface
 iface = gr.Interface(
     fn=classify_text,
     inputs=gr.Textbox(lines=2, placeholder="Enter a Darija sentence..."),
@@ -31,7 +30,8 @@ iface = gr.Interface(
     description="Enter a text in Darija to analyze its sentiment (Positive, Negative, Neutral)."
 )
 
-# Lancer l’application
+# Launch the app
 iface.launch()
 
 
+