Update app.py

app.py

@@ -1,5 +1,22 @@
-# Use a pipeline as a high-level helper
 from transformers import pipeline
+import gradio as gr
 
-pipe = pipeline("text-classification", model="CAMeL-Lab/bert-base-arabic-camelbert-ca-sentiment")
+# Load the text classification pipeline
+pipe = pipeline("text-classification", model="CAMeL-Lab/bert-base-arabic-camelbert-mix-sentiment")
 
+# Define the function to classify text
+def classify_text(text):
+    result = pipe(text)
+    return f"Label: {result[0]['label']}, Score: {result[0]['score']:.2f}"
+
+# Create the Gradio interface
+demo = gr.Interface(
+    fn=classify_text, 
+    inputs="text", 
+    outputs="text", 
+    title="Arabic Text Classification",
+    description="Enter Arabic text to analyze its sentiment using CAMeL-Lab's Arabic BERT model."
+)
+
+# Launch the Gradio app
+demo.launch()