app.py

import gradio as gr
from transformers import MarianMTModel, MarianTokenizer

# Define the translator function
def translate_text(text, target_language):
    model_name = {
        "Spanish": "Helsinki-NLP/opus-mt-en-es",
        "French": "Helsinki-NLP/opus-mt-en-fr",
        "Italian": "Helsinki-NLP/opus-mt-en-it",
        "Ukrainian": "Helsinki-NLP/opus-mt-en-uk",
    }

    tokenizer = MarianTokenizer.from_pretrained(model_name[target_language])
    model = MarianMTModel.from_pretrained(model_name[target_language])

    # Tokenize the input text
    input_tokens = tokenizer(text, return_tensors="pt")

    # Generate translated tokens
    translated_tokens = model.generate(**input_tokens)

    # Decode the translated tokens
    translated_text = tokenizer.decode(translated_tokens[0], skip_special_tokens=True)

    return translated_text

# Define the Gradio interface
language_options = ["Spanish", "French", "Italian", "Ukrainian"]
inputs = [
    gr.component.TextInput(lines=5, label="Enter text to translate:"),
    gr.component.Dropdown(choices=language_options, label="Select target language:"),
]
outputs = gr.component.Textbox(label="Translated text:")


iface = gr.Interface(fn=translate_text, inputs=inputs, outputs=outputs, title="Language Translator")

# Launch the Hugging Face Spaces app
iface.launch()