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import json
import gradio as gr
import torch
# Use a pipeline as a high-level helper
from transformers import 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)
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):
# text = "Hello Friends, How are you?"
dest_code= get_FLORES_code_from_language(destination_language)
translation = text_translator(text,
src_lang="eng_Latn",
tgt_lang=dest_code)
return translation[0]["translation_text"]
gr.close_all()
# demo = gr.Interface(fn=summary, inputs="text",outputs="text")
demo = gr.Interface(fn=translate_text,
inputs=[gr.Textbox(label="Input text for translation",lines=6), gr.Dropdown(
["Arabic", "Afrikaans", "Bengali", "Greek", "Estonian", "Portuguese", "Spanish"],
label="Select Destination Language")
],
outputs=[gr.Textbox(label="Translated Text",lines=4)],
title="@caesar-2series: Multilingual Language Interpreter",
description="Translations from English into a few foreign languages")
demo.launch() |