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import torch
import gradio as gr
import json
# Use a pipeline as a high-level helper
from transformers import pipeline
model_path= ("../Models/models--facebook--nllb-200-distilled-600M/snapshots"
"/f8d333a098d19b4fd9a8b18f94170487ad3f821d")
text_translator = pipeline("translation", model="facebook/nllb-200-distilled-600M",
torch_dtype=torch.bfloat16)
# text_translator = pipeline("translation", model=model_path,
# 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 to translate",lines=6), gr.Dropdown(["Hindi", "Spanish", "Portuguese", "French", "German", "Italian", "Russian", "Japanese"], label="Select destination language")],
outputs=[gr.Textbox(label="Translated text",lines=6)],
title="Multi Language Translator",
description="Translate any English text to multiple languages.")
demo.launch()
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