app.py

import gradio as gr
from transformers import MarianMTModel, MarianTokenizer

# Load the model and tokenizer
model_name = 'Helsinki-NLP/opus-mt-en-hi'  # Model for English to Hindi
model = MarianMTModel.from_pretrained(model_name)
tokenizer = MarianTokenizer.from_pretrained(model_name)

# Function to translate English to Hindi
def translate_to_hindi(text):
    # Tokenize input text
    tokens = tokenizer(text, return_tensors="pt", padding=True, truncation=True)
    # Perform translation
    translated_tokens = model.generate(**tokens)
    # Decode the translation
    translated_text = tokenizer.decode(translated_tokens[0], skip_special_tokens=True)
    return translated_text

# Gradio interface
iface = gr.Interface(fn=translate_to_hindi, inputs="text", outputs="text", 
                     title="English to Hindi Translator", 
                     description="Enter English text and get the Hindi translation.")

# Launch the interface
iface.launch()