app.py

import torch
import json
import gradio as gr

# 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=model_path, torch_dtype=torch.bfloat16)

text_translator = pipeline("translation", model="facebook/nllb-200-distilled-600M", torch_dtype=torch.bfloat16)

# text = "Hello friends, How are you?"

# translation = text_translator(text, src_lang="eng_Latn", tgt_lang="deu_Latn")

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):
    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()

# print(translate_text(text, "Hindi"))
demo = gr.Interface(fn=translate_text,
                    inputs=[gr.Textbox(label="Input text to translate",lines=6), gr.Dropdown(["German", "French", "Hindi", "Romanian", "Marathi"], 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()