app.py

import gradio as gr
from transformers import pipeline
import torch

# Load the model and tokenizer
model_name = 'bilalfaye/nllb-200-distilled-600M-wo-fr-en'
device = "cuda" if torch.cuda.is_available() else "cpu"

# Define the translation pipeline
translator = pipeline(
    "translation",
    model=model_name,
    device=device
)


# Define the translation function
def translate_chat(message, history, source_language, target_language):
    # Mapping of languages to model codes
    lang_map = {
        "Wolof": "wol_Latn",
        "English": "eng_Latn",
        "French": "fra_Latn"
    }
    
    if source_language not in lang_map or target_language not in lang_map:
        return "Invalid language selection."
    
    src_lang = lang_map[source_language]
    tgt_lang = lang_map[target_language]
    
    if src_lang == tgt_lang:
        return "Source and target languages must be different."
    
    # Perform the translation
    translation = translator(message, src_lang=src_lang, tgt_lang=tgt_lang)
    return translation[0]["translation_text"]

# Gradio chat interface
interface = gr.ChatInterface(
    fn=translate_chat,
    additional_inputs=[
        gr.Dropdown(
            choices=["Wolof", "French", "English"],
            label="Source Language",
            value="Wolof",  # Default value
        ),
        gr.Dropdown(
            choices=["Wolof", "French", "English"],
            label="Target Language",
            value="English",  # Default value
        ),
    ],
    title="Wolof ↔ French ↔ English Translator",
    description="Select the source and target languages (in the bottom) to translate between Wolof, French, and English.",
)

# Launch the app
interface.launch(debug=True, share=True)