app.py

import gradio as gr
from sentence_transformers import CrossEncoder

# Load CrossEncoder model
model = CrossEncoder("cross-encoder/nli-deberta-v3-base")

def predict_similarity(sentence1, sentence2):
    score = model.predict([(sentence1, sentence2)])  # returns numpy array
    return float(score.squeeze()[0])  # ✅ safe extraction of single float

demo = gr.Interface(
    fn=predict_similarity,
    inputs=["text", "text"],
    outputs="number",
    title="CrossEncoder (nli-deberta-v3-base)",
    description="Enter two sentences to compute semantic similarity."
)

demo.launch()