app.py

import gradio as gr
from transformers import pipeline

# Load the multilingual model for text generation
model_name = "google/mt5-small"
text_generator = pipeline("text-generation", model=model_name)

def generate_text(prompt, language):
    # Depending on the language, prepend a language token if needed
    if language == "Arabic":
        prompt = "<ar>" + prompt
    else:  # English
        prompt = "<en>" + prompt
    
    generated_text = text_generator(prompt, max_length=200, num_return_sequences=1)
    return generated_text[0]['generated_text']

# Create the Gradio interface
with gr.Blocks() as demo:
    gr.Markdown("## Bilingual Text Generator")
    with gr.Row():
        language_choice = gr.Radio(choices=["English", "Arabic"], label="Select Language")
        prompt_input = gr.Textbox(label="Enter your prompt", placeholder="Type your prompt here...")
        generate_button = gr.Button("Generate Text")
    
    output_text = gr.Textbox(label="Generated Text", interactive=False)
    
    generate_button.click(generate_text, inputs=[prompt_input, language_choice], outputs=output_text)

# Launch the Gradio app
demo.launch()