app.py

import json
import torch
import gradio as gr
from transformers import pipeline
from gtts import gTTS
import os

# Load FLORES-200 language codes from lang_code.json
with open("lang_code.json", "r", encoding="utf-8") as f:
    LANG_CODES = json.load(f)

# Translation pipeline
translator = pipeline("translation", model="facebook/nllb-200-distilled-600M")

# Translation + TTS function
def translate_and_speak(text, src_lang, tgt_lang):
    try:
        src_code = LANG_CODES[src_lang]
        tgt_code = LANG_CODES[tgt_lang]

        # Translate
        result = translator(text, src_lang=src_code, tgt_lang=tgt_code)
        translated_text = result[0]['translation_text']

        # Generate speech for translated text
        tts = gTTS(translated_text, lang=tgt_lang.split("_")[0])
        audio_path = "translated_audio.mp3"
        tts.save(audio_path)

        return translated_text, audio_path
    except Exception as e:
        return f"Error: {e}", None

# Gradio UI
with gr.Blocks(theme="soft") as demo:
    gr.HTML("<h1 style='color:black; text-align:center;'>@GenAi MultiLanguage Translator Model</h1>")

    with gr.Row():
        with gr.Column():
            src_text = gr.Textbox(label="Enter Text", placeholder="Type something here...")
            src_lang = gr.Dropdown(choices=list(LANG_CODES.keys()), value="English (Latin script)", label="Source Language")
            tgt_lang = gr.Dropdown(choices=list(LANG_CODES.keys()), value="French", label="Target Language")
            translate_btn = gr.Button("Translate")

        with gr.Column():
            output_text = gr.Textbox(label="Translated Text")
            output_audio = gr.Audio(label="Speech Output", type="filepath")

    translate_btn.click(fn=translate_and_speak,
                        inputs=[src_text, src_lang, tgt_lang],
                        outputs=[output_text, output_audio])

# Run app
demo.launch()