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Setup

Compressa App is distributed as docker containers which are available at Github package storage and can be deployed in one command.

Requirements​

1. Linux Server with supported Nvidia GPU​

Current release is tested on:

  • Nvidia A100
  • Nvidia V100
  • Nvidia T4
  • Nvidia 4090
  • Nvidia 4080
  • Nvidia 4070 / 4070Ti
  • Nvidia 3080 / 3080Ti
  • Nvidia 3070 / 3070Ti
  • Nvidia 3060 / 3060Ti
  • Nvidia 2080Ti

Server should have at least the same amount of RAM (we recommend 1.2 of GPU's RAM).

2. Cuda Drivers Installed​

The latest compatible drivers should be installed.

примечание

Default version of CUDA driver can be installed via:

sudo apt update
sudo apt install software-properties-common -y
sudo apt install ubuntu-drivers-common -y
sudo ubuntu-drivers autoinstall
sudo apt install nvidia-cuda-toolkit

3. Docker​

Installation instruction for Ubuntu:
https://docs.docker.com/engine/install/ubuntu/

It should be the version which supports Docker Compose V2.

4. Nvidia Container Toolkit​

Linux installation instruction:
https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html

Deployment​

At the first step of integration, Compressa Team provides you with access token.

1. The further process is simple:​

Set environment variable with token:

export COMPRESSA_TOKEN=<TOKEN>

2. Authenticate to docker with your token:​

echo $COMPRESSA_TOKEN | docker login -u compressa --password-stdin

3. Get docker-compose.yaml file:​

wget https://raw.githubusercontent.com/compressa-ai/compressa-deploy/main/docker-compose.yaml

4. Get nginx config:​

wget https://raw.githubusercontent.com/compressa-ai/compressa-deploy/main/nginx.conf

5. Pull the latest Compressa:​

docker compose pull

6. Set environment variable and run service:​

  • DOCKER_GPU_IDS - list of GPU ids which will be visible for Compressa

  • RESOURCES_PATH - path to directory to store models. It can be ./data for example.
    Please set read-write access for this directory using chmod -R 777 ./data

    примечание

    If you're deploying Compressa in private network without internet access, please use the instruction to download resources.

Deploy:

export DOCKER_GPU_IDS=0
export RESOURCES_PATH=./data
docker compose up

That's it! The service is available at the port 8080.