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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 = [ | |
["Gafe kalan ka di Saratu ye. Saratu bɛ gafew kalan minnu siginidenw ye wow ye, a bɛ se ka minnu kalan ni a bolonkɔninw ye. O sɛbɛnni cogo in bɛ wele ko barayi. Saratu bɛ se ka gafe kalan i n'a fɔ denmisɛn min bɛ yeli kɛ.", "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"], | |
] | |
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( | |
""" | |
**License:** CC BY-NC 4.0 | |
**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.") |