Installation Guide - Kairntech Documentation

Supported Operating Systems

The Kairntech platform has been successfully validated on the following operating systems, for both CPU and GPU deployments:

Ubuntu 20.04.6 LTS (x64), or higher
RHEL / CentOS7 (x64), or higher

Note: When deploying in a CPU-only environment, Docker-based virtualization removes most OS-level constraints. However, for GPU-based deployment, compatibility is restricted due to NVIDIA driver requirements. Only the above-listed OS versions are officially supported for GPU setups.

Installation steps

All listed commands below come from the environment UBUNTU 18.04 LTS x64.

Host configuration prerequisites:

Host configuration prerequisites
User/folders creation
Binaries installation

Kairntech platform Docker volumes prerequisites

Docker volumes to mount

Kairntech platform installation

Kairntech platform installation

Host configuration prerequisites:

ELASTICSEARCH recommendation

You may need to increase the vm.max_map_count kernel parameter to avoid running out of map areas.

In order to avoid such message:

[1]: max virtual memory areas vm.max_map_count [65530] is too low, increase to at least [262144]

It is recommended to edit file /etc/sysctl.conf and insert the following lines:

# ES - at least 262144 for production use
vm.max_map_count=262144

Apply the modification with using the following command

sudo sysctl -p

INOTIFY recommendation

You may need to increase the fs.inotify.max_user_instances parameter to avoid reaching user limits on the number of inotify resources.

In order to avoid such message

[Errno 24] inotify instance limit reached

It is recommended to edit file /etc/sysctl.conf and insert the following lines:

# Prevent [Errno 24] inotify instance limit reached
fs.inotify.max_user_instances = 65530

Apply the modification with using the following command

sudo sysctl -p

HAPROXY recommendation

You may need to set net.ipv4.ip_unprivileged_port_start to let to non root user haproxy the permission to run on priviledged port 443.

In order to avoid such message (in haproxy container console output)

[ALERT]    (1) : Starting frontend http-in-sherpa: cannot bind socket (Permission denied) [0.0.0.0:443]
[ALERT]    (1) : [haproxy.main()] Some protocols failed to start their listeners! Exiting.

It is recommended to edit file /etc/sysctl.conf and insert the following lines:

# Enable haproxy to listen to 443
net.ipv4.ip_unprivileged_port_start=0

Apply the modification with using the following command

sudo sysctl -p

User/Folder creation

USER creation

Is it highly advised to create a specific user, for the deployment of the platform:

# FOR A STANDARD USER
sudo adduser kairntech

# OR FOR A HEADLESS USER
sudo adduser --disabled-password --gecos "" kairntech

FOLDER creation

Is it highly advised to create a specific folder, for the deployment of the platform:

sudo mkdir -p /opt/sherpa
sudo chown -R kairntech. /opt/sherpa

Directory /opt/sherpa/ will store all files and folders relative to the platform (delivered by Kairntech)

File docker-compose.yml will be used to deploy/pull Docker images of the platform

Folder init will be used to deploy prerequisites docker volumes content

Binaries installation

Docker / Docker Compose installation

The platform being based on a Docker-type solution, please install docker and docker compose plugin.
The official page indicating the installation commands is located here.

sudo apt-get update
sudo apt-get install ca-certificates curl gnupg

sudo install -m 0755 -d /etc/apt/keyrings
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /etc/apt/keyrings/docker.gpg
sudo chmod a+r /etc/apt/keyrings/docker.gpg

echo "deb [arch="$(dpkg --print-architecture)" signed-by=/etc/apt/keyrings/docker.gpg] https://download.docker.com/linux/ubuntu "$(. /etc/os-release && echo "$VERSION_CODENAME")" stable" | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null

sudo apt-get install docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin

Then you will have to add the kairntech user to the docker group

sudo usermod -aG docker kairntech

As mentionned in the installation guide, log out and log back in so that your group membership is re-evaluated.

If you want to test, open a new session terminal and run

sudo su - kairntech

docker run hello-world

After installing the compose plugin, you can test via:

sudo su - kairntech

docker compose version

Docker volumes to mount

The binary docker will be used to feed docker volumes with embeddings files; to select specific languages, or all languages, an .env file is used for indicating the choice.

FLAIR embeddings

The engine Flair require some « embeddings » files: these static files are stored as Docker volumes. In order to get these files, please run:

sudo su - kairntech

cd /opt/sherpa/init/flair-init-job

# INSTALL AR, DE, EN AND FR
cat flair.env 
FLAIR_LANGUAGES=ar,de,en,fr
FLAIR_RESOURCES_VERSION=default
docker compose -f docker-compose.yml up

# OR INSTALL ALL LANGUAGES
cat flair.env 
FLAIR_LANGUAGES=all
FLAIR_RESOURCES_VERSION=default
docker compose -f docker-compose.yml up

The variable FLAIR_LANGUAGES can be modified to indicate the language selection.

The Docker container can be removed, once Flair embeddings are deployed, via:

docker rm flair-resources-init-job

The table below gives disk usage corresponding to available languages:

Language	Size
Arabic (AR)	2.9G
German (DE)	4.3G
English (EN)	3.8G
Spanish (ES)	4.2G
Farsi (FA)	768M
French (FR)	4.2G
Hindi (HI)	1.0G
Italian (IT)	3.9G
Dutch (NL)	3.9G
Portuguese (PT)	2.7G
Russian (RU)	4.1G
Chinese (ZH)	1.6G
All	35G

FASTTEXT embeddings

The engine fastText require some « embeddings » files: these static files are stored as Docker volumes. In order to get these files, please run:

sudo su - kairntech

cd /opt/sherpa/init/fasttext-init-job

# INSTALL AR, DE, EN AND FR
cat fasttext.env 
FASTTEXT_LANGUAGES=ar,de,en,fr
FASTTEXT_RESOURCES_VERSION=default
docker compose -f docker-compose.yml up

# OR INSTALL ALL LANGUAGES
cat fasttext.env 
FASTTEXT_LANGUAGES=all
FASTTEXT_RESOURCES_VERSION=default
docker compose -f docker-compose.yml up

The variable FASTTEXT_LANGUAGES can be modified to indicate the language selection.

The Docker container can be removed, once fastText embeddings are deployed, via:

docker rm flair-resources-init-job

The table below gives disk usage corresponding to available languages:

Language	Size
Arabic (AR)	1.5G
German (DE)	5.6G
English (EN)	6.2G
Spanish (ES)	2.5G
French (FR)	2.9G
Italian (IT)	2.2G
Japanese (JA)	1.3G
Portuguese (PT)	1.5G
Russian (RU)	4.7G
Chinese (ZH)	822M
All	29G

ENTITY-FISHING knowledge

The component entity-fishing require some « knowledge » files: these static files are generated every month, and stored as Docker volumes. In order to get these files, please run:

sudo su - kairntech

cd /opt/sherpa/init/entity-fishing-init-job

# INSTALL AR, DE, EN AND FR
cat entity-fishing.env 
ENTITY_FISHING_LANGUAGES=ar,de,en,fr
ENTITY_FISHING_RESOURCES_VERSION=2025-07-10
docker compose -f docker-compose.yml up

# OR INSTALL ALL LANGUAGES
cat entity-fishing.env 
ENTITY_FISHING_LANGUAGES=all
ENTITY_FISHING_RESOURCES_VERSION=2025-07-10
docker compose -f docker-compose.yml up

The variable ENTITY_FISHING_RESOURCES_VERSION can be modified to match the most recent knwoledge.

The Docker container can be removed, once entity-fishing knowledge is deployed, via:

docker rm entity-fishing-init-job

The table below gives disk usage corresponding to available languages:

Language	Size
Arabic (AR)	36.7G (3.7G + 33G)
German (DE)	40.0G (6.0G + 33G)
English (EN)	49G (16G + 33G)
Spanish (ES)	37.4G (4.4G + 33G)
Farsi (FA)	36.5G (3.5G + 33G)
French (FR)	38.6G (5.6G + 33G)
Italian (IT)	36.9G (3.9G + 33G)
Japanese (JA)	36.6G (3.6G + 33G)
Portuguese (PT)	35.8G (2.8G + 33G)
Russian (RU)	39.4G (6.4G + 33G)
Chinese (ZH)	36.1G (3.1G + 33G)
Ukrainian (UA)	36.6G (3.6G + 33G)
Indian (HI)	33.5G (455M + 33G)
Swedish (SE)	37.2G (4.2G + 33G)
Bengali (BD)	33.7G (700M + 33G)
All	100G (67G + 33G)

In these metrics, the common knowledge takes 33G of disk usage, and is mandatory.

VECTORIZERS

In order to fully utilize the vectorizers, language models files must be downloaded: these static files are stored as Docker volumes. In order to get these files, please run:

sudo su - kairntech

cd /opt/sherpa/init/vectorizers-init-job/

# INSTALL allMiniLML6V2
cat vectorizer.env
VECTORIZER_RESOURCES_VERSION=sentence-transformers/all-MiniLM-L6-v2
docker compose -f docker-compose.allminilml6v2.yml up
docker rm vectorizer-resources-init-job

# INSTALL multiMiniLML12V2
cat vectorizer.env
VECTORIZER_RESOURCES_VERSION=sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2
docker compose -f docker-compose.multiminilml12v2.yml up
docker rm vectorizer-resources-init-job

# INSTALL spDilaCamembert
cat vectorizer.env
VECTORIZER_RESOURCES_VERSION=oterrier/sp-dila-camembert-base-gpl
docker compose -f docker-compose.spdilacamembertgpl.yml up
docker rm vectorizer-resources-init-job

# INSTALL sentenceCamembertBase
cat vectorizer.env
VECTORIZER_RESOURCES_VERSION=dangvantuan/sentence-camembert-base
docker compose -f docker-compose.sentencecamembertbase.yml up
docker rm vectorizer-resources-init-job

# INSTALL bge-m3 (GPU only)
cat vectorizer.env
VECTORIZER_RESOURCES_VERSION=BAAI/bge-m3
docker compose -f docker-compose.bge-m3.yml up
docker rm vectorizer-resources-init-job

The variable VECTORIZER_RESOURCES_VERSION can be modified to indicate the model selection.

Kairntech platform installation

In order to download the different images needed to install the platform, you must first connect to dockerhub.
(The password to be used will be delivered by Kairntech ).

sudo su - kairntech

cd /opt/sherpa

docker login

username: ktguestkt

password:

Once logged in, you can start downloading the images:

docker compose -f docker-compose.yml pull

If you have deployed with authentication (MongoDB or ElasticSearch), for compatibility purpose, you’ll need to symlink .env file:
sudo su - kairntech

cd /opt/sherpa

ln -s mongodb-credentials.env .env

cat elasticsearch-credentials.env >> .env

Finally, to start the platform, run:

docker compose -f docker-compose.yml up -d

Once the platform is started, you can check the status of the containers; the following console output is given as an example. Some containers may not be present, depending on the kind of deployment you processed.

docker ps -a --format "{{.ID}}\t\t{{.Names}}\t\t{{.Status}}"

79e235f82787        sherpa-core                           Up 20 sec

e69f95855809        sherpa-crfsuite-suggester             Up 20 sec
c9d95639c808        sherpa-entityfishing-suggester        Up 20 sec
94e4574b95de        sherpa-fasttext-suggester             Up 20 sec

8f13e72aeb0d        sherpa-phrasematcher-test-suggester   Up 20 sec
0f49dec91340        sherpa-phrasematcher-train-suggester  Up 20 sec
aa08f1008770        sherpa-sklearn-test-suggester         Up 20 sec
988976ef327d        sherpa-sklearn-train-suggester        Up 20 sec
bed6169d9185        sherpa-spacy-test-suggester           Up 20 sec
302bd98a44ab        sherpa-spacy-train-suggester          Up 20 sec
7754162ae44c        sherpa-flair-test-suggester           Up 20 sec
08d1ad415adb        sherpa-flair-train-suggester          Up 20 sec
4835129a77c9        sherpa-bertopic-test-suggester        Up 20 sec
b999a848044c        sherpa-bertopic-train-suggester       Up 20 sec

0826e0dd9c85        sherpa-elasticsearch                  Up 20 sec
7f781bf11ddf        sherpa-mongodb                        Up 20 sec

d3b0e0557309        sherpa-builtins-importer              Up 20 sec

cf075d3b06f4        sherpa-multirole                      Up 20 sec
ae1b24e0ccdb        sherpa-pymultirole                    Up 20 sec
2a737b399388        sherpa-pymultirole-trf                Up 20 sec
f43121e96544        sherpa-pymultirole-ner                Up 20 sec