app.py

import gradio as gr
from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer

# Load the pre-trained multilingual model for translation (facebook/m2m100_418M)
model_name = "facebook/m2m100_418M"
model = M2M100ForConditionalGeneration.from_pretrained(model_name)
tokenizer = M2M100Tokenizer.from_pretrained(model_name)

def translate_text(text):
    # Tokenize the input text
    inputs = tokenizer(text, return_tensors="pt", padding=True)
    
    # Automatically detect source language and translate it to English
    generated_tokens = model.generate(**inputs)
    
    # Decode the translated tokens into English
    translated_text = tokenizer.decode(generated_tokens[0], skip_special_tokens=True)
    return translated_text

# Create Gradio interface
iface = gr.Interface(
    fn=translate_text, 
    inputs=gr.Textbox(label="Enter Text for Translation"), 
    outputs=gr.Textbox(label="Translated Text"),
    live=True
)

if __name__ == "__main__":
    iface.launch()