/concierge

Repo for Concierge AI dev work

Primary LanguagePythonApache License 2.0Apache-2.0

Data Concierge AI

AI should be simple, safe, and amazing.

TL;DR:

Data Concierge AI (aka Concierge) is an AI system that works ONLY with the data you feed it. Your data, your prompts, everything are local to your instance.

More details

Concierge is a local and modular RAG framework still in alpha.

Built with simplicy and security in mind, it has some features we love -- and hope you do too!

  • The quick install method is so easy. (Note: fast install method is only supported on Linux and Windows. MacOS in development now.)
  • Loading data: Upload PDFs or point to a URL, click the ingest button... and the data is there for your use
  • Tasks: you can change what the AI can do for you via dropdowns

Dependencies

Concierge requires the following to be available:

  1. python (note: for all commands in documentation we will call the executable python. On your system you may need to use python3)
  2. Docker (currently the vector database and natural language response engine are running in docker containers)
  3. Docker compose (while frequently installed with docker, sometimes it's not. Docker compose files are how the docker containers are setup)

Optional:
If you want to use GPU acceleration (Concierge does NOT require this, but it will make responses dramatically faster), you must have the NVIDIA drivers correctly setup and running. Concierge will not install or make any adjustmetns to your driver configuration.

Note: if you want to use GPU acceleration on a Windows host, you must use WSL2.
More details here:
https://docs.docker.com/desktop/gpu/

Refer to the documentation from NVIDIA for information on how to do this for your OS.

Setup: quick install

git clone repo or extract zip.

cd concierge go into the cloned project directory.

python install.py to launch the installer.
Answer the questions and then the installer will ask if you are ready to make changes to the system.
Answer "Y" and let the downloading begin!

Setup: manual

If install.py did not work, follow these steps to setup your system.

python -m venv . create a python virtual environment in the current directory.

Linux: source ./bin/activate / Windows PowerShell: .\Scripts\Activate.ps1 enter into the virtual environment.

pip install -r requirements.txt install all dependencies.

copy .env.example into a file named .env and set the folder on your computer that will contain the concierge data.

docker compose up -d will load the docker dependencies.

docker compose -f docker-compose-gpu.yml up -d will load the docker dependencies and use the GPU.

Usage: launch script

From the cloned project directory simply run launch.py.

If the Docker container dependencies aren't found, you will be given the option to launch with CPU or GPU.

Usage: manual

If launch.py did not work:

If you are not in the python virtual environment, please enter it by the correct method:
Linux: source ./bin/activate
Windows PowerShell: .\Scripts\Activate.ps1

To start the web UI, run the following command:
streamlit run Concierge.py

Want to get involved?

Please read our Code of Conduct then our Contribution Guide.