embedding_studio

(β˜… 382)

Embedding Studio is a framework which allows you transform your Vector Database into a feature-rich Search Engine.

  • .env
  • .gitignore
  • docker-compose.local.yml
  • docker-compose.yml
  • LICENSE
  • mkdocs.yml
  • pyproject.toml
  • README.md
  • service.Dockerfile
  • setup.py
  • worker.fine_tuning.Dockerfile
  • worker.improvement_worker.Dockerfile
  • worker.inference.Dockerfile
  • worker.upsertion_worker.Dockerfile

# Installation Guide

1. Get the code
git clone https://github.com/EulerSearch/embedding_studio

Downloads the entire project code from GitHub to your computer.

cd embedding_studio

Moves into the project folder you just downloaded.

2. Docker

Easy Recommended
Prerequisites
  • Git Needed to download the project code from GitHub.
  • Docker Desktop Needed to build and run containers. Install it and keep it running in the background.
<a href="#"><img src="https://img.shields.io/badge/docker--compose-2.17.0-blue.svg" alt="Docker Compose Version"></a>

Runs the command against the services defined in the compose file.

βœ… Run docker compose ps to check the containers are Up. If the README mentions a port, open http://localhost:PORT in your browser.

Pulled directly from this repo's README.

3. Python

Easy
Prerequisites
  • Git Needed to download the project code from GitHub.
  • Python 3 On Windows, be sure to check 'Add Python to PATH' during installation.
pip install .

Installs the package published on PyPI directly β€” no need to clone the source.

python <μ‹€ν–‰ν•  파일λͺ…>.py # READMEμ—μ„œ μ •ν™•ν•œ μ‹€ν–‰ 파일λͺ…을 ν™•μΈν•˜μ„Έμš”

Runs the Python script (or module).

βœ… If it runs without errors and prints output in the terminal, it worked.
// repository documentation