Update app.py

app.py

@@ -1,17 +1,26 @@
 import gradio as gr
 from transformers import pipeline
-import torch 
 
 # Load sentiment analysis models
 english_sentiment_model = pipeline("sentiment-analysis", model="nlptown/bert-base-multilingual-uncased-sentiment")
-arabic_sentiment_model = pipeline("text-classification", model="CAMeL-Lab/bert-base-arabic-camelbert-da-sentiment")          
+arabic_sentiment_model = pipeline("text-classification", model="CAMeL-Lab/bert-base-arabic-camelbert-da-sentiment")
+
+# Define label meanings for Arabic sentiment analysis
+arabic_labels = {
+    "positive": "إيجابي",
+    "negative": "سلبي",
+    "neutral": "محايد"  # Add any other labels that your model may use
+}
 
 def analyze_sentiment(text, language):
     if language == "English":
         result = english_sentiment_model(text)
+        return result[0]['label'], result[0]['score']
     else:
         result = arabic_sentiment_model(text)
-    return result[0]['label'], result[0]['score']
+        label = result[0]['label']
+        arabic_label = arabic_labels.get(label, "غير معروف")  # Default to "Unknown" if label not found
+        return arabic_label, result[0]['score']
 
 # Create Gradio interface
 iface = gr.Interface(