Update app.py

app.py

@@ -1,30 +1,8 @@
-
-import gradio as gr
-from datasets import load_dataset
-
-
-# Load the dataset
-dataset = load_dataset("mohres/The_Arabic_E-Book_Corpus")
-def filter_arabic_novels():
-    # Select only rows containing novel-like words
-    filtered_data = dataset['train'].filter(lambda x: "رواية" in x['text'])
-    return filtered_data
-
-
-# Function to display the first row text
-def get_first_text():
-    try:
-        return dataset['train'][0]['text']
-    except Exception as e:
-        return str(e)
-
-
-# Create a Gradio Interface
-interface = gr.Interface(
-    fn=lambda: filter_arabic_novels()[0]['text'],  # Only show first filtered sample
-    inputs=[],
-    outputs="text",
-)
-
-# Launch the interface
-interface.launch()
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+
+messages = [
+    {"role": "user", "content": "Who are you?"},
+]
+pipe = pipeline("text-generation", model="Ruqiya/Fine-Tuning-Gemma-2b-it-for-Arabic")
+pipe(messages)