app.py

import gradio as gr
from sentence_transformers import SentenceTransformer, util

# Use a more powerful model for paraphrasing and semantic similarity
model = SentenceTransformer("sentence-transformers/all-mpnet-base-v2")

def compare_sentences(sentence_a, sentence_b):
    emb = model.encode([sentence_a, sentence_b], convert_to_tensor=True)
    score = util.pytorch_cos_sim(emb[0], emb[1]).item()
    return f"{score * 100:.2f}%"  # Similarity score as percentage

iface = gr.Interface(
    fn=compare_sentences,
    inputs=["text", "text"],
    outputs="text",
    title="Sentence Similarity Checker (MPNet Model)",
    description="Enter two sentences to compare their meaning using a powerful transformer model. Score is shown as a percent."
)

iface.launch()