app.py

import torch
import gradio as gr
import json

# 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)



with open('Language.json', 'r') as file:
    language_data = json.load(file)
    
def get_languages():
    languages = []
    for item in language_data:
        languages.append(item["Language"])
    return languages
        	

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(get_languages(), label="Select Destination Language")],
                    outputs=[gr.Textbox(label="Translated text",lines=4)],
                    title="@GenAILearniverse Project 4: Multi language translator",
                    description="THIS APPLICATION WILL BE USED TO TRNSLATE ANY ENGLIST TEXT TO MULTIPLE LANGUAGES.")
demo.launch()