app.py

from typing import List

import gradio as gr
from sentence_transformers import SentenceTransformer

model = SentenceTransformer("nomic-ai/nomic-embed-text-v1.5", trust_remote_code=True, device='cpu')


def embed(document: str):
    return model.encode(document)


with gr.Blocks(title="Nomic Text Embeddings") as app:
    gr.Markdown("# Nomic Text Embeddings v1.5")
    gr.Markdown("Generate embeddings for your text using the nomic-embed-text-v1.5 model.")
    
    # Create an input text box
    text_input = gr.Textbox(label="Enter text to embed", placeholder="Type or paste your text here...")

    # 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)
    
    # Add API usage guide
    gr.Markdown("## API Usage with cURL")
    gr.Markdown("""
    You can use this API programmatically with cURL. Here's how:
    
    ```bash
    curl -X POST https://ipepe-nomic-embeddings.hf.space/run/predict \
      -H "Content-Type: application/json" \
      -d '{
        "data": ["Your text to embed goes here"]
      }'
    ```
    
    The response will be in JSON format:
    ```json
    {
      "data": [[0.123, -0.456, 0.789, ...]], 
      "duration": 0.123
    }
    ```
    
    Replace `https://ipepe-nomic-embeddings.hf.space` with your actual Space URL.
    """)

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