Ready-to-Use Text Embedding API

This repository contains a simple Flask API for generating text embeddings from the instructor-embedding base model. As of 2023-05-11, this model is 6th on the Massive Text Embedding Benchmark (MTEB) Leaderboard. The application is dockerized and is designed to be deployed using Docker Compose. It features Redis for caching embeddings to improve performance, and uses nginx-proxy for handling incoming requests.

👩🏼‍💻 Developer setup

Linked is our guide for setting up all Vrooli repos. No extra steps are required.

Minimum requirements for Virtual Private Server (VPS)

• Memory: 2GB
• CPUs: 1

Usage

Send a POST request to http://localhost:<PORT_EMBEDDING> if testing locally, or https://<your-domain> if testing on a Virtual Private Server (VPS). The request must contain the following structure:

{
    "key": "<your-api-key>", // Only if API_KEY environment variable is set
    "instruction": "Hello, world!",
    "sentences": ["First text you are creating an embedding for", "Another text that needs embeddings"]
}

As a curl request, it looks like this:

curl -X POST \
     -H "Content-Type: application/json" \
     -H "key: <your_api_key>" \
     -d '{"instruction":"Hello, world!", "sentences": ["First text you are creating an embedding for", "Another text that needs embeddings"]}' \
     http://localhost:3369

If you are authenticated, it will return an object of this shape:

{
    "embeddings": [[0.5000, 0.3456, ..., 0.1234]], // 768-dimensional vector for each sentence
    "model": "instructor-embedding",
}

Feel free to change instruction depending on your specific use case. If you are embedding multiple fields at once, you'll have to convert the fields to a single string. One way to do is is by using yaml:

title: "The title with characters escaped correctly"
description: "the description with characters escaped correctly"

License

This project is licensed under the terms of the GNU General Public License v3.0. You can check out the full license in the LICENSE file.

This project uses the unmodified instructor-embedding base model, which is licensed under Apache License 2.0. The license for this model can be found in the LICENSE.instructor-embedding file.

Contributions

Contributions are always welcome! If you have suggestions for improvements, please create an issue or a pull request💖