app.py

import gradio as gr
from transformers import MarianMTModel, MarianTokenizer

# Define a function that loads a model and tokenizer based on the chosen language
def load_model(lang_pair):
    if lang_pair == "English to French":
        model_name = 'Helsinki-NLP/opus-mt-en-fr'
    elif lang_pair == "Kinyarwanda to English":
        model_name = 'Helsinki-NLP/opus-mt-rw-en'
    else:
        raise ValueError("Unsupported language pair")
    
    tokenizer = MarianTokenizer.from_pretrained(model_name)
    model = MarianMTModel.from_pretrained(model_name)
    return model, tokenizer

# Function to translate text based on selected language
def translate(lang_pair, text):
    model, tokenizer = load_model(lang_pair)
    
    # Tokenize the text using the __call__ method
    model_inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
    
    # Perform the translation
    gen = model.generate(**model_inputs)
    
    # Decode the generated tokens to string
    translation = tokenizer.batch_decode(gen, skip_special_tokens=True)
    return translation[0]

# Create a Gradio interface with a dropdown menu for language selection
iface = gr.Interface(
    fn=translate,
    inputs=[
        gr.Dropdown(choices=["English to French", "Kinyarwanda to English"], label="Select Language"),
        gr.Textbox(lines=2, placeholder="Enter Message...")
    ],
    outputs=gr.Textbox()
)

# Launch the interface
iface.launch(debug=True,inline=False)