app.py

import gradio as gr
from sentence_transformers import SentenceTransformer

# Load the pre-trained paraphrase-mpnet-base-v2 model
model = SentenceTransformer('sentence-transformers/paraphrase-mpnet-base-v2')

def get_embeddings(sentences):
    # Get embeddings for the input sentences
    embeddings = model.encode(sentences, convert_to_tensor=True)
    return embeddings.tolist()

# Define the Gradio interface
interface = gr.Interface(
    fn=get_embeddings,  # Function to call
    inputs=gr.Textbox(lines=2, placeholder="Enter sentences here, one per line"),  # Input component
    outputs=gr.JSON(),  # Output component
    title="Sentence Embeddings with MPNet",  # Interface title
    description="Enter sentences to get their embeddings with paraphrase-mpnet-base-v2."  # Description
)

# Launch the interface
interface.launch()