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import torch
import gradio as gr
import json
# Use a pipeline as a high-level helper
from transformers import pipeline
# Initialize the translation pipeline
text_translator = pipeline("translation", model="facebook/nllb-200-distilled-600M", torch_dtype=torch.bfloat16)
# Load the JSON data from the file
with open('language.json', 'r') as file:
language_data = json.load(file)
# Extract language names from the JSON data
language_names = [entry['Language'] for entry in language_data]
def get_FLORES_code_from_language(language):
for entry in language_data:
if entry['Language'].lower() == language.lower():
return entry['FLORES-200 code']
return None
def translate_text(text, destination_language):
dest_code = get_FLORES_code_from_language(destination_language)
if dest_code:
translation = text_translator(text, src_lang="eng_Latn", tgt_lang=dest_code)
return translation[0]["translation_text"]
else:
return "Destination language code not found."
# Create and launch the Gradio interface
gr.close_all()
demo = gr.Interface(
fn=translate_text,
inputs=[
gr.Textbox(label="Input text to translate", lines=6),
gr.Dropdown(language_names, label="Select Destination Language")
],
outputs=[gr.Textbox(label="Translated text", lines=4)],
title="Multi-language Translator",
description="This application translates any English text to multiple languages."
)
demo.launch()
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