# Necessary imports
import gradio as gr
from src.app.predict import ZeroShotTextClassification


# Examples to display in the interface
examples = [
    ["I love to play the guitar", "music, artist, food, travel"],
    ["I am a software engineer at Google", "technology, engineering, art, science"],
    ["I am a professional basketball player", "sports, athlete, chef, politics"],
]

# Title and description and article for the interface
title = "Zero Shot Text Classification"
description = "Classify text using zero-shot classification with ModernBERT-large zeroshot model! Provide a text input and a list of candidate labels separated by commas. Read more at the links below."
article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2412.13663' target='_blank'>Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference</a> | <a href='https://huggingface.co/MoritzLaurer/ModernBERT-large-zeroshot-v2.0' target='_blank'>Model Page</a></p>"


# Launch the interface
demo = gr.Interface(
    fn=ZeroShotTextClassification,
    inputs=[gr.Textbox(label="Input"), gr.Textbox(label="Candidate Labels")],
    outputs=gr.Label(label="Classification"),
    title=title,
    description=description,
    article=article,
    examples=examples,
    cache_examples=True,
    cache_mode="lazy",
    theme="Soft",
    flagging_mode="never",
)
demo.launch(debug=False)