llmboost-hub 0.4.2

A lightweight CLI tool for managing LLMBoost™ model images and environments.

LLMBoost Hub (lbh)

Manage LLMBoost™ model containers and environments to run, serve, and tune large language models.

Note: This is proprietary software and requires a valid LLMBoost™ license to use. Request a license at [e-mail].

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Pre-requisites

Dependencies:

• Python 3.10+
• Docker 27.3.1+
• NVIDIA GPU: nvidia-docker2 or AMD GPU: ROCm 6.3+

Install LLMBoost Hub:

pip install llmboost_hub

# Verify installation
lbh --version

Upgrade:

pip install --upgrade llmboost_hub

Note: This document uses lbh interchangeably with llmboost_hub.

Login to Hugging Face and Docker:

huggingface-cli login     # or set HF_TOKEN env var
docker login -u <your_docker_username>

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Quick start

Fetch list of supported models from remote (automatically authenticates LLMBoost license):

lbh fetch # only needed once a day

One-liner to start serving a model (automatically downloads image and model, if needed):

lbh serve <Repo/Model-Name> # Full model name (including repository or organization name) must match the name from https://huggingface.co

For example:

lbh serve meta-llama/Llama-3.2-1B-Instruct

Basic workflow:

lbh fetch # authenticate LLMBoost license
lbh list # list models you've prepared (from model_paths.yaml)
lbh list --discover /path # discover models in a directory and add to model_paths.yaml
lbh prep <Repo/Model-Name> # download image and model assets
lbh run <Repo/Model-Name> # start container
lbh serve <Repo/Model-Name> # start LLMBoost server inside container
lbh test <Repo/Model-Name> # send test request
lbh stop <Repo/Model-Name> # stop container

For more details, see the Command Reference section below. For more details, see the Configuration Options section below.

Shell completions (auto-complete commands and model names):

eval "$(lbh completions)"                 # current shell
lbh completions [--venv|--profile]        # persist for venv or profile

Note: Model name completion shows all supported models from lbh list (includes wildcard-expanded models).

Configuration Options

llmboost_hub uses the following environment variables:

• LBH_HOME: base directory for all llmboost_hub data. (defaults: (host) ~/.llmboost_hub <- (container) /llmboost_hub)
• LBH_MODELS: directory for storing and retrieving model assets. (default: $LBH_HOME/models)
• LBH_MODEL_PATHS: YAML file mapping model names to their paths. Automatically updated by prep and run --model_path. (default: $LBH_HOME/model_paths.yaml)
• LBH_LOCAL_DB: persistent local database for tuning results. Survives container restarts, system reboots, and LLMBoost version upgrades. (default: $LBH_HOME/local_inference.db)
• LBH_WORKSPACE: mounted user workspace for manually transferring files out of containers. (defaults: (host) $LBH_HOME/workspace <- (container) /user_workspace)

Notes:

• A configuation file is stored at $LBH_HOME/config.yaml with all the above mentioned settings (and other advanced settings).
  • Precedence order for settings: Environment variables > Configuration file > Defaults
• LBH_HOME can only be changed by setting the env var (or in ~/.bashrc).
  • WARNING: Changing LBH_HOME will cause a new data directory to be used, and all configuration will be reset.
• HF_TOKEN is injected automatically when set.

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Command Reference

Use lbh -h for a summary of all commands, and lbh [COMMAND] -h for help with a specific command and all available options.

Use lbh -v [COMMAND] for verbose output with any command; shows useful diagnostic info for troubleshooting.

• lbh login

  • If EULA not yet accepted, displays a full-screen scrollable End User License Agreement; exits if rejected.
  • Reads $LBH_LICENSE_PATH if valid.
  • Else asks for license file path (or use --license-file).
  • Imports JSON-style .skm file, validates, saves to $LBH_LICENSE_PATH (simultaneously generating legacy_license.skm for backwards image compatibility).

• lbh fetch

  • Requires EULA acceptance (run lbh login first).
  • Fetches latest models supported by LLMBoost.
  • Filters to available GPU.

• lbh list [query] [--discover PATH]

  • Lists models you've prepared (tracked in model_paths.yaml).
  • GPU matching follows same rule as lbh fetch, but filters based on local model availability.
  • Default mode: Shows only models prepared via lbh prep.
  • Discovery mode (--discover /path): Scans directory for models and prompts to add them to model_paths.yaml.
  • Status meanings:
    • pending: model path doesn't exist or is empty
    • stopped: model exists but container not running
    • running: container running but idling
    • initializing: container running and starting LLMBoost server
    • serving: LLMBoost server ready to accept requests
    • tuning: autotuner running
  • Supports query filtering (case-insensitive, e.g., lbh list llama)
  • Works correctly even when LBH_MODELS changes (paths in model_paths.yaml are absolute)

• lbh prep <Repo/Model-Name> [--only-verify] [--fresh]

  • Pulls the image and downloads HF assets.
  • Automatically saves model path to LBH_MODEL_PATHS after successful preparation.
  • --only-verify checks digests and sizes.
  • --fresh removes existing image and re-downloads model assets from Hugging Face.

• lbh run <Repo/Model-Name> [OPTIONS] -- [DOCKER FLAGS...]

  • Resolves and starts the container detached.
  • Mounts $LBH_HOME and $LBH_WORKSPACE. Injects HF_TOKEN.
  • NVIDIA GPUs use --gpus all. AMD maps /dev/dri and /dev/kfd.
  • Path resolution: checks LBH_MODEL_PATHS first, then falls back to $LBH_MODELS/<repo>/<model>.
  • Useful options:
    • --image <image>: override docker image.
    • --model_path <model_path>: override model assets path (saved to LBH_MODEL_PATHS for future use).
    • --restart: restarts container, if already running.
    • --use-local-db: merge persistent local database (~/.llmboost_hub/local_inference.db) into container to leverage historical tuning data.
    • Pass extra docker flags after --.

• lbh serve <Repo/Model-Name> [--host 0.0.0.0] [--port 8011] [--detached] [--force] -- [LLMBOOST ARGS...]

  • Requires EULA acceptance (run lbh login first).
  • Starts LLMBoost server inside the container.
  • Waits until ready, unless --detached.
  • --force skips GPU utilization checks (use if GPU utilization is incorrectly reported by NVidia or AMD GPU drivers).
  • --use-local-db: merge persistent local database (~/.llmboost_hub/local_inference.db) into container to leverage historical tuning data.
  • Pass extra llmboost serve arguments after --.

• lbh test <Repo/Model-Name> [--query "..."] [-t N] [--host 127.0.0.1] [--port 8011]

  • Sends a test request to /v1/chat/completions.

• lbh attach <Repo/Model-Name> [-c <container name or ID>]

  • Opens a shell in the running container.

• lbh stop <Repo/Model-Name> [-c <container name or ID>]

  • Stops the container.

• lbh status [model]

  • Shows status and model.

• lbh tune <Repo/Model-Name> [--metrics throughput] [--detached] [--image <image>]

  • Runs the autotuner. - Results are automatically saved to persistent local database ($LBH_LOCAL_DB) and will survive container restarts, system reboots, and LLMBoost version upgrades.
  • Use lbh serve --use-local-db to leverage tuning results from previous sessions.

Cluster Commands (Multi-Node Deployments)

• lbh cluster install [--kubeconfig PATH] [--docker-username USER] [--docker-pat TOKEN] [--docker-email EMAIL] [-- EXTRA_HELM_ARGS]

  • Install LLMBoost Helm chart and Kubernetes infrastructure for multi-node deployments.
  • Displays access credentials for management and monitoring UIs after installation.
  • Requires running Kubernetes cluster and helm installed.
  • Docker authentication options:
    • --docker-username, --docker-pat, --docker-email: Provide credentials directly (all three required together)
    • Alternatively, run docker login and credentials will be read from ~/.docker/config.json
    • If neither provided, cluster will be installed without Docker registry secret

• lbh cluster deploy [-f CONFIG_FILE] [--kubeconfig PATH]

  • Deploy models across cluster nodes based on configuration file.
  • Generates and applies Kubernetes CRD manifests.
  • Config template: $LBH_HOME/utils/template_cluster_config.jsonc

• lbh cluster status [--kubeconfig PATH] [--show-secrets]

  • Show status of all model deployments and management services.
  • Displays summary statistics: Models: / and Mgmt.: /
  • Shows model deployment table with pod status, restarts, and error messages.
  • Service URLs for management UI and monitoring (Grafana).
  • Use --show-secrets to display access credentials (masked).
  • Use -v --show-secrets for full unmasked credentials.

• lbh cluster logs [--models|--management] [--pod POD_NAME] [--tail TAIL_ARGS...] [--grep GREP_ARGS...] [--kubeconfig PATH]

  • View logs from model deployment or management pods.
  • --models: Show logs from model deployment pods.
  • --management: Show logs from management/monitoring pods (displays as table).
  • --pod POD_NAME: Filter to specific pod by name.
  • --tail TAIL_ARGS: Show last N lines from workspace logs (default: 10).
  • --grep GREP_ARGS: Filter logs by pattern (uses awk for pattern matching).
  • Defaults to showing both model and management logs if no filter specified.

• lbh cluster remove <MODEL_NAME> [--all] [--kubeconfig PATH]

  • Remove specific model deployments from the cluster.
  • Deletes LLMBoostDeployment custom resources by name.
  • --all: Remove all model deployments (requires confirmation unless used with --force).
  • Example: lbh cluster remove facebook/opt-125m or lbh cluster remove --all

• lbh cluster uninstall [--kubeconfig PATH] [--force]

  • Uninstall LLMBoost cluster resources.
  • Prompts for confirmation unless --force is used.
  • Does not automatically delete the namespace.

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Support

• Docs: https://llmboost.mangoboost.io/docs/
• Website: https://llmboost.mangoboost.io/
• Email: [e-mail]