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CLI Reference

Updated 2025.08.26

This document provides a reference for the ALO-LLM command-line interface (CLI).

Service API List Inquiry at the register / deploy / activate stages​

Check Registered Service API List (alm register --list)​

  • After registering a service, you can check the list of services registered in the AI Conductor's workspace with the alm register command. Running this command will list all services registered so far:
alm register --list
alm register -l

The list of service names is displayed as the execution result. You can also check the newly registered service in this list. This allows you to verify that the service you just registered has been properly registered. The service APIs shown as the execution result are the list registered in the workspace set when you logged in. To change the workspace, you must perform the login procedure again.

If executed successfully, the entire list of Service APIs registered in a specific AI Conductor workspace is displayed as follows.

API Names
survey-genius-cloud-service
aipack
ALO-chatbot

Check Deployed Service API List (alm deploy --list)​

  • This command is for checking the service API deployed in the service operation environment.
alm deploy --list
alm deploy -l
  • It shows the entire list of deployed service APIs among those registered in the AI Conductor Workspace set at login.
Deployed API Names
survey-genius-cloud-service
alochat-0710
ald-ym-alochat-3

Check Activated Service API List (alm activate --list)​

  • This command is for checking the service API activated in the service operation environment.
alm activate --list
alm activate -l
  • It shows the entire list of activated service APIs among those registered in the AI Conductor Workspace set at login.
Activate API Names
chatbot-rag (vl)

Deleting Service APIs at the register / deploy / activate stages​

Services or deployment instances that are no longer needed can be deleted through the CLI. There are three delete commands, and they should be used according to the purpose: To delete a registered Service API, you must delete it in the order of Activate -> Deploy -> Register.

Delete Registered Service API (alm register --delete)​

This command deletes the registered service itself from the registry. This is the action of deleting the metadata (name, description, etc.) for the service from the platform and is used when completely removing the service.

To delete a registered service, the following command is required.

alm register --delete (Service API Name)
alm register -d (Service API Name)
  • The name of the deleted service is displayed as the execution result.
Registration Deleted!
Name: survey-genius-cloud-service
Versions: N/A

Delete Deployed Service API (alm deploy --delete)​

To delete a deployed service, the following command is required.

alm deploy --delete (Service API Name)
alm deploy -d (Service API Name)
  • The name of the deleted service is displayed as the execution result.
Deploy Delete Success:
name: survey-genius-cloud-service

Deactivate Activated Service API (alm deactivate)​

Running this command will stop and remove the cloud instance of that service. After deletion, you will no longer be able to access the service at that URL. (Deployment resources are released, so billing and resource occupation are also stopped)

You can delete services or deployment instances that are no longer needed through the CLI command.

alm deactivate --name (Service API Name)
alm deactivate -n (Service API Name)

Other CLI Commands​

Check current workspace information (alm get --workspace_info)​

  • After alm login, you can find out the information of the workspace currently set as default.
alm get --workspace_info
alm get -w
  • Detailed information is displayed as follows.
Workspace info: {'name': 'test-ws', 'display_name': 'test', 'mode': 'LLM', 'cloud': 'AWS', 's3_bucket_name':
's3-an2-llmops-dev-aia', 'ecr_base_path': '339713051385.dkr.ecr.ap-northeast-2.amazonaws.com/ecr-an2-llmops-
dev/test/ai-solutions/', 'edge_conductor_url': 'https://edge@lge.com', 'specs': [{'name': 'standard',
'display_name': 'STANDARD#2vCPU:8GB', 'label': 'test-ws-standard', 'instance': 'm5.large', 'instance_type':
'CPU', 'vcpu': 2, 'ram_gb': 8, 'gpu': 0, 'gpu_ram_gb': 0}]}

Check available base image list (alm get --image_info)​

  • You can check the list of base images available for Service API deployment.
alm get --image_info
alm get -i
  • The list of available base images is displayed as follows.
Base image list
python-3.13
python-3.12-slim
python-3.13-bullseye
python-3.11
python-3.12-bullseye
python-3.12
erp-mcp
python-3.11-bullseye
python-3.13-slim
nginxdemos-hello
python-3.11-slim
python-3.12-slim-bullseye
python-3.11-slim-bullseye
python-3.13-slim-bullseye
echo-server

Check current AI Logic Deployer version (alm get --version)​

  • You can check the versions of the AI Logic Deployer and AI Conductor you are currently using.
alm get --version
alm get -v
  • The version of the AI Logic Deployer you are currently using is displayed as follows.

0.10.1

How to change workspace

  • Changing the workspace is done by logging in again.
alm login
Please enter your AI Conductor ID: gildong.hong
Please enter your AI Conductor password: **********
  • If there are multiple workspaces accessible after logging in, the user can enter the desired workspace to use.
File /home/gildong.hong/.token/key.json has been removed for initialization.
access_token has been updated in /home/gildong.hong/.token/key.json
Login success
test2-ws has been updated in /home/gildong.hong/.token/key.json
test-ws has been updated in /home/gildong.hong/.token/key.json
test1-ws has been updated in /home/gildong.hong/.token/key.json
You can access these workspaces: ['test2-ws', 'test-ws', 'test1-ws']
Please input default workspace: test1-ws
default_ws has been updated in /home/gong.hong/.token/key.json
Default workspace: test1-ws

The example above shows a situation where test1-ws was selected.