app.py

import gradio as gr
from transformers import pipeline

# Load the translation model
translator = pipeline("translation_en_to_hi", model="Helsinki-NLP/opus-mt-en-hi")

# Define the translation function
#def translate_text(text):
    #if not text:
        #return "⚠️ Please provide some input text."
    #result = translator(text)[0]["translation_text"]
    #return result

def translate_text(text):
    if not text:
        return "⚠️ Please provide some input text."
    result = translator(
        text,
        max_length=100,
        clean_up_tokenization_spaces=True
    )[0]["translation_text"]
    return result

# Create the Gradio interface
iface = gr.Interface(
    fn=translate_text,
    inputs=gr.Textbox(label="Enter English Text"),
    outputs=gr.Textbox(label="Hindi Translation"),
    title="English to Hindi Translator",
    description="Enter English text to translate it into Hindi using a HuggingFace transformer model."
)

# 🚀 Launch with API enabled so external clients like Discord can POST data
# Enable queuing
iface.queue()

# Launch the app
iface.launch()