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Update app.py
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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"],
]
@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(
"""
**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.")