import gradio as gr
from transformers import pipeline

# Load pre-trained model for CoLA (linguistic acceptability)
model_name = "sentence-transformers/all-MiniLM-L6-v2"
classifier = pipeline("text-classification", model=model_name)

def classify_sentence(sentence):
    result = classifier(sentence)[0]
    return f"Label: {result['label']} (Confidence: {result['score']:.2f})"

# Create Gradio interface
iface = gr.Interface(
    fn=classify_sentence,
    inputs=gr.Textbox(lines=2, placeholder="Enter a sentence..."),
    outputs="text",
    title="Sentence Acceptability Classifier",
    description="This model classifies whether a sentence is linguistically acceptable (LABEL_1) or not (LABEL_0).",
)

# Launch app
iface.launch()