| 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() | |