app.py

import gradio as gr
from transformers import pipeline
import torch
import logging
import spaces
from typing import Union, List


logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

if torch.cuda.is_available():
    device = "cuda"
    logger.info("Using CUDA for inference.")
elif torch.backends.mps.is_available():
    device = "mps"
    logger.info("Using MPS for inference.")
else:
    device = "cpu"
    logger.info("Using CPU for inference.")

class BambaraTranslator:
    def __init__(self, model_name: str = "sudoping01/nllb-bambara-v2"):
        self.translator = pipeline(
            "translation",
            model=model_name,
            device=device,
            max_length=512,
            truncation=True
        )
        self.flores_codes = {
            "French": "fra_Latn",
            "English": "eng_Latn",
            "Bambara": "bam_Latn"
        }
        logger.info("Translation pipeline initialized successfully.")

    def translate(self, text: Union[str, List[str]], src_lang: str, tgt_lang: str) -> Union[str, List[str]]:
        source_lang = self.flores_codes[src_lang]
        target_lang = self.flores_codes[tgt_lang]
        
        logger.info(f"Translating text from {source_lang} to {target_lang}.")
        
        try:
            if isinstance(text, str):
                translation = self.translator(text, src_lang=source_lang, tgt_lang=target_lang, num_beams=2)
                return str(translation[0]['translation_text'])
            else:
                translations = self.translator(text, src_lang=source_lang, tgt_lang=target_lang, num_beams=2)
                return [str(t['translation_text']) for t in translations]
        except Exception as e:
            logger.error(f"Translation failed: {e}")
            return "An error occurred during translation."


translator = BambaraTranslator()

examples = [
    ["An filɛ ni ye yɔrɔ minna ni an ye an sigi ka a layɛ yala an bɛ ka baara min kɛ ɛsike a kɛlen don ka Ɲɛ wa ? Bɛɛ ka kan ka i jɔyɔrɔ fa walasa an ka se ka taa Ɲɛ", "Bambara", "French"],
    ["Le Mali est un pays riche en culture mais confronté à de nombreux défis.", "French", "Bambara"],
    ["The sun rises every morning to bring light to the world.", "English", "Bambara"],
    ["Good morning", "English", "Bambara"],
]

@spaces.GPU()
def translate_text(text: str, src_lang: str, tgt_lang: str) -> str:
    """
    Translate the input text from the source language to the target language.
    """
    if not text.strip():
        return "Please enter text to translate."
    
    if src_lang == tgt_lang:
        return "Source and target languages must be different."
    
    try:
        result = translator.translate(text, src_lang, tgt_lang)
        logger.info("Translation successful.")
        return result
    except Exception as e:
        logger.error(f"Translation failed: {e}")
        return f"Error: {str(e)}"

def build_interface():
    """
    Builds the Gradio interface for translating text between supported languages.
    """
    with gr.Blocks(title="Bambara Translator") as demo:
        gr.Markdown(
            """
            # 🇲🇱 Bambara Translator
            Translate between Bambara, French, and English instantly using NLLB model.
            
            ## How to Use
            1. Select source and target languages from the dropdowns
            2. Enter your text or choose from examples
            3. Click "Translate" to see the result
            """
        )
        
        with gr.Row():
            with gr.Column():
                text_input = gr.Textbox(
                    lines=5, 
                    label="Text to Translate", 
                    placeholder="Enter text here..."
                )
                
                with gr.Row():
                    src_lang = gr.Dropdown(
                        choices=["Bambara", "French", "English"], 
                        label="Source Language", 
                        value="Bambara"
                    )
                    tgt_lang = gr.Dropdown(
                        choices=["Bambara", "French", "English"], 
                        label="Target Language", 
                        value="French"
                    )
                
                translate_btn = gr.Button("Translate", variant="primary")
            
            with gr.Column():
                output = gr.Textbox(label="Translation", lines=5, interactive=False)
        
        # Examples section
        gr.Examples(
            examples=examples,
            inputs=[text_input, src_lang, tgt_lang],
            outputs=output,
            fn=translate_text,
            cache_examples=False
        )
        
        gr.Markdown(
            """
            **Model:** [sudoping01/nllb-bambara-v2](https://huggingface.co/sudoping01/nllb-bambara-v2)  
            **License:** CC BY-NC 4.0 (Non-commercial use)  
            **Based on:** Meta's NLLB (No Language Left Behind)
            """
        )
        
        translate_btn.click(
            fn=translate_text,
            inputs=[text_input, src_lang, tgt_lang],
            outputs=output
        )
    
    return demo

if __name__ == "__main__":
    logger.info("Starting the Gradio interface for the Bambara translator.")
    interface = build_interface()
    interface.launch()
    logger.info("Gradio interface running.")