app.py

from typing import List

import gradio as gr
import spaces
from sentence_transformers import SentenceTransformer

model = SentenceTransformer("nomic-ai/nomic-embed-text-v1", trust_remote_code=True, device='cuda')


@spaces.GPU
def embed(documents: List[str]):
    embeddings = []
    for document in documents:
        embeddings.append(model.encode(document))
    return embeddings


with gr.Blocks() as app:
    # Create an input text box
    text_input = gr.Textbox(label="Enter text to embed")

    # Create an output component to display the embedding
    output = gr.JSON(label="Text Embedding")

    # When the input text is submitted, call the embedding function and display the output
    text_input.submit(embed, inputs=text_input, outputs=output)

if __name__ == '__main__':
    app.queue().launch(server_name="0.0.0.0", show_error=True, server_port=7860)