app.py

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()