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# app.py
import gradio as gr
from transformers import pipeline
# 1. Load a translation pipeline.
# By default this is English → French; swap model for other language pairs.
translator = pipeline("translation_en_to_fr", model="Helsinki-NLP/opus-mt-en-fr")
def translate(text: str) -> str:
"""
Translate input English text into French.
"""
# The pipeline returns a list of dicts; we grab the 'translation_text'
result = translator(text, max_length=512)
return result[0]["translation_text"]
# 2. Create the Gradio interface.
iface = gr.Interface(
fn=translate,
inputs=gr.Textbox(lines=5, label="Input Text (English)"),
outputs=gr.Textbox(lines=5, label="Translated Text (French)"),
title="HuggingFace Translation Service",
description="Enter English text and get a French translation powered by a Hugging Face model."
)
if __name__ == "__main__":
iface.launch()
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