import gradio as gr
import subprocess
subprocess.run(["pip", "install", "transformers"])
subprocess.run(["pip", "install", "sentencepiece"])
subprocess.run(["pip", "install", "torch"])
from transformers import MarianMTModel, MarianTokenizer

# Load the model and tokenizer
model_name = "Helsinki-NLP/opus-mt-en-hi"
tokenizer = MarianTokenizer.from_pretrained(model_name)
model = MarianMTModel.from_pretrained(model_name)

def translate(text):
    inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True)
    translated = model.generate(**inputs)
    return tokenizer.decode(translated[0], skip_special_tokens=True)

# Gradio interface
iface = gr.Interface(
    fn=translate,
    inputs=gr.Textbox(label="Enter English Text"),
    outputs=gr.Textbox(label="Hindi Translation"),
    title="English to Hindi Translator",
    description="Enter an English sentence, and the model will translate it into Hindi."
)

iface.launch()