liquidai-cli 0.0.1b0

CLI tool for Liquid Labs on-prem stack

Liquid Labs CLI

Command line interface for managing Liquid Labs on-prem stack.

Installation

pip install liquidai-cli

A docker-compose.yaml file is also shipped together with the package. Any changes to this file may cause some unexpected behaviors.

Run with uv

uv allows to run this tool without installing the package into the system.

uv run --directory [PATH_TO_THIS_DIRECTORY] liquidai [command] [args]

Configuration

The CLI uses a YAML configuration file (liquid.yaml) in your working directory. A default configuration will be created on first use, but you can customize it:

stack:
  version: "c3d7dbacd1"
  model_image: "liquidai/lfm-7b-e:0.0.1"
  api_secret: "local_api_token"
  # Other values will be auto-generated
database:
  name: "liquid_labs"
  user: "local_user"
  password: "local_password"
  port: 5432
  schema: "labs"

Usage

Stack Management

# Launch stack
liquidai stack launch

# Launch with upgrades
liquidai stack launch --upgrade-stack --upgrade-model

# Shutdown stack
liquidai stack shutdown

# Test API endpoints
liquidai stack test

# Purge stack (removes all components)
liquidai stack purge

# Purge without confirmation
liquidai stack purge --force

Model Operations

# Run a model in docker container
liquidai model run-model-image \
  --name lfm-3b-e \
  --image "liquidai/lfm-3b-e:0.0.6"

# Run a HuggingFace model and expose on port 9000
liquidai model run-hf \
  --name llama-7b \
  --path meta-llama/Llama-2-7b-chat-hf \
  --port 9000 \
  --gpu-memory-utilization 0.6 \
  --max-num-seqs 600 \
  --max-model-len 32768

# Run a local checkpoint and expose on port 9001 to avoid conflicts
liquidai model run-checkpoint \
  --path /path/to/checkpoint \
  --port 9001 \
  --gpu-memory-utilization 0.6 \
  --max-num-seqs 600

# List running models
liquidai model list

# Stop a specific model
liquidai model stop llama-7b

# Stop a model interactively
liquidai model stop

Database Operations

# Connect to database using pgcli
liquidai db connect

Infrastructure

# Create Cloudflare tunnel with token
liquidai tunnel create --token YOUR_TOKEN

# Create tunnel interactively
liquidai tunnel create

Configuration Management

# Import configuration from .env file
liquidai config import

# Import from specific .env file
liquidai config import --env-file /path/to/.env

# Import to specific config file
liquidai config import --config-file /path/to/liquid.yaml

# Force overwrite existing config
liquidai config import --force

Command Reference

Call liquidai [command] --help to get the detailed usage reference.