harbor

Harbor CLI

Harbor is a containerized LLM toolkit — a Docker Compose project with a CLI for managing 250+ AI services (backends, frontends, APIs, tools). Install via npm i -g @avcodes/harbor or clone from GitHub.

Core Workflow

1. Start services: harbor up ollama webui
2. Check status: harbor ps
3. Configure: harbor config set OLLAMA_MODEL llama3.2
4. Use: harbor open webui or harbor url webui
5. Stop: harbor down

harbor up ollama webui
harbor ps
harbor open webui
harbor down

Service Lifecycle

# Start / stop
harbor up <service> [service...]      # Start service(s)
harbor up --tail                       # Start and tail logs
harbor up --open                       # Start and open in browser
harbor up --no-defaults                # Start without default services
harbor down                            # Stop and remove all containers
harbor restart [service]               # Down then up

# Inspect
harbor ps                              # List running containers
harbor logs <service>                  # Tail logs (WARNING: hangs in non-interactive shells)
harbor stats                           # Resource usage statistics

# Build / pull
harbor build <service>                 # Build a service image
harbor pull <service>                  # Pull latest Docker images
harbor pull <model>                    # Pull Ollama or llama.cpp model

# Execute
harbor exec <service> <cmd>            # Run command in running container
harbor shell <service>                 # Interactive shell in container
harbor run <service> [cmd]             # One-off command in new container
harbor run <alias>                     # Run a saved alias
harbor attach <service>                # Attach to running container

Configuration

Harbor uses a layered config system. Never edit .env directly.

# Global config
harbor config ls                       # List all config values
harbor config get <KEY>                # Get a value
harbor config set <KEY> <VALUE>        # Set a value
harbor config unset <KEY>              # Remove a value
harbor config search <query>           # Search keys and values
harbor config reset                    # Reset to defaults
harbor config update                   # Merge upstream default.env changes

# Per-service environment overrides
harbor env <service>                   # List override vars
harbor env <service> <key>             # Get a specific var
harbor env <service> <key> <value>     # Set a specific var
harbor env <service> unset <key>       # Remove a specific var

Common Config Keys

# Default model for a service
harbor config set HARBOR_OLLAMA_MODEL llama3.2
harbor config set HARBOR_LLAMACPP_MODEL "bartowski/Llama-3.2-3B-Instruct-GGUF:Q4_K_M"
harbor config set HARBOR_VLLM_MODEL "Qwen/Qwen2.5-3B-Instruct"

# Default services started with bare "harbor up"
harbor defaults ls
harbor defaults add ollama
harbor defaults add webui
harbor defaults rm webui

Service Discovery

harbor ls                              # List all 250+ available services
harbor ls --active                     # List only active/configured services
harbor url <service>                   # Get localhost URL
harbor url --lan <service>             # Get LAN-accessible URL
harbor url --internal <service>        # Get Docker-internal URL
harbor open <service>                  # Open service in browser
harbor qr <service>                    # Print QR code for service URL

Profiles

Save and restore full service configurations.

harbor profile ls                      # List saved profiles
harbor profile save <name>             # Save current config as profile
harbor profile load <name>             # Load a profile
harbor profile rm <name>               # Remove a profile

Aliases

Define reusable command shortcuts.

harbor alias ls                        # List aliases
harbor alias get <name>                # Get an alias
harbor alias set <name> <command>      # Set an alias
harbor alias rm <name>                 # Remove an alias
harbor run <alias>                     # Execute an alias

Tunnels

Expose services to the internet via Cloudflare tunnels.

harbor tunnel <service>                # Expose a service
harbor tunnel down                     # Stop all tunnels
harbor tunnels ls                      # List auto-tunnel services
harbor tunnels add <service>           # Add to auto-tunnel list
harbor tunnels rm <service>            # Remove from auto-tunnel list

Volumes

Mount custom host directories into service containers.

harbor volumes ls                      # Show all custom volumes
harbor volumes ls <service>            # Show volumes for a service
harbor volumes add <svc> <src>:<dest>  # Add a volume mount
harbor volumes rm <service> <index>    # Remove by index
harbor volumes clear <service>         # Remove all for a service

Model Management

Unified model management across backends.

harbor models                          # Manage models across Ollama, HuggingFace, llama.cpp, DMR, MLX
harbor pull <model>                    # Pull a model (auto-detects backend)
harbor ollama <cmd>                    # Run Ollama CLI commands

Service-Specific Configuration

Many services have dedicated subcommands for configuration.

# Backend configuration
harbor ollama <cmd>                    # Ollama CLI
harbor llamacpp <cmd>                  # llama.cpp config
harbor vllm <cmd>                      # vLLM config
harbor litellm <cmd>                   # LiteLLM config
harbor tgi <cmd>                       # Text Generation Inference config
harbor aphrodite <cmd>                 # Aphrodite config
harbor tabbyapi <cmd>                  # TabbyAPI config
harbor mistralrs <cmd>                 # mistral.rs config
harbor sglang <cmd>                    # SGLang CLI
harbor dmr <cmd>                       # Docker Model Runner config
harbor mlx <cmd>                       # MLX backend config
harbor kobold <cmd>                    # Koboldcpp config
harbor ktransformers <cmd>             # ktransformers config

# Frontend configuration
harbor webui <cmd>                     # Open WebUI config
harbor chatui <cmd>                    # HuggingFace ChatUI config
harbor comfyui <cmd>                   # ComfyUI config
harbor langflow <cmd>                  # Langflow config

# Tool configuration
harbor boost <cmd>                     # Harbor Boost LLM proxy
harbor openai <cmd>                    # OpenAI API keys/URLs
harbor jupyter <cmd>                   # Jupyter config
harbor mcp <cmd>                       # MCP service config
harbor hermes <cmd>                    # Hermes Agent config

Harbor Boost — Agentic Modules

Harbor Boost is an LLM proxy (harbor up boost) that chains modules before the downstream completion. Agentic modules add web research, task anchoring, deliverable audits, and scope guards for coding agents. Full reference: docs/5.2.3-Harbor-Boost-Modules.md.

Modules

Pairs: quickhop for speed, deephop for depth. caveman + ponytail for terse/YAGNI style. autocheck + diffscope for scoped deliverable audits.

harbor launch --workflow

One-shot wiring for Boost module workflows. Put launch options before the tool name; everything after the tool name passes through unchanged.

--web and --workflow cannot be combined. claude does not support Boost workflows (Anthropic API); use OpenAI-compatible host tools (codex, opencode, copilot, droid, hermes, mi, openclaw, pi, pool).

harbor launch --workflow quickhop --backend ollama --model qwen2.5-coder:7b codex
harbor launch --workflow autocheck --backend ollama --model qwen2.5-coder:7b opencode

Workflows that include autocheck or diffscope need a workspace bind mount (see Setup). Add write_workspace_file to HARBOR_BOOST_TOOLS and pass --sandbox workspace-write when you want the model to write files.

Setup

# Start Boost with backend
harbor up ollama boost

# Enable agentic modules
harbor boost modules add tools quickhop deephop autocheck caveman ponytail

# Web research backend (pick one)
harbor config set HARBOR_BOOST_SEARXNG_URL http://searxng:8080
harbor up searxng
# or
harbor config set HARBOR_BOOST_TAVILY_API_KEY <key>

# Workspace bind mount + in-container jail root (Boost runs in Docker)
harbor config set boost.workspace "$(pwd)"
harbor config set boost.workspace.root /workspace

# Workspace tools for coding sandbox sessions
harbor config set HARBOR_BOOST_TOOLS 'read_workspace_file;grep_workspace;list_workspace_files;write_workspace_file'
harbor config update
harbor restart boost

# Point a coding agent at Boost (manual config)
harbor url boost   # OpenAI-compatible; model: <workflow-or-module>-<backend-model>

Notes: autocheck triggers only on deliverable turns (≥2 signals, e.g. coding keyword + file path). Define multi-step custom workflows via HARBOR_BOOST_WORKFLOWS or workflows.yaml.

Debug Metrics (Troubleshooting)

When agentic modules skip or trigger unexpectedly, enable compact per-module debug metrics. Boost emits a one-line summary before the final completion so you can see what each module did on that turn.

Global (all requests):

harbor config set HARBOR_BOOST_DEBUG true
harbor restart boost

Per request — overrides HARBOR_BOOST_DEBUG for a single completion:

# OpenAI-compatible body (harbor url boost)
curl "$BOOST_URL/chat/completions" \
  -H "Authorization: Bearer $BOOST_KEY" \
  -d '{
    "model": "llama3.2",
    "messages": [{"role": "user", "content": "Fix the auth bug in src/api.ts"}],
    "@boost_debug": true
  }'

# Anthropic / Responses API — put @boost_ keys in metadata instead

Accepted truthy values: true, 1, yes, on. Use @boost_debug: false to silence metrics when global debug is on.

Example status line:

Debug: quickhop skipped (acknowledgment) 3ms | deephop skipped (implementation) 2ms | autocheck triggered 840ms +2calls [verdict=pass,outcome=delivered]

Each segment is one module: triggered or skipped, optional (reason), wall-clock duration_ms, optional +Ncalls for extra LLM/tool hops, and [key=value,...] extras (e.g. gate_reason, verdict, outcome, grounding_mode).

Common skip reasons:

Related: @boost_show_audit (or HARBOR_BOOST_AUTOCHECK_SHOW_AUDIT=true) appends an autocheck audit footer and HTML findings artifact — use when you need full audit detail, not just the compact debug line.

Launching Service CLIs

harbor launch starts a service CLI pre-configured to use running Harbor services. Runs from the directory you invoke it (preserves project context).

harbor launch <tool> [args]            # Launch with auto-detected backends
harbor launch --backend <svc> <tool>   # Override backend
harbor launch --model <model> <tool>   # Override model
harbor launch --workflow <module> <tool>  # Single Boost module workflow — see Harbor Boost section
harbor launch --web <tool>             # Generated boost-web workflow + SearXNG (mutually exclusive with --workflow)
harbor launch --config <tool>          # Print/write config without starting tool

# Direct CLI shortcuts (service must be running)
harbor aider                           # Aider coding assistant
harbor aichat                          # aichat CLI
harbor fabric                          # Fabric CLI
harbor opint                           # Open Interpreter
harbor plandex                         # Plandex CLI
harbor gptme                           # gptme CLI
harbor nanobot                         # nanobot CLI
harbor repopack                        # Repopack CLI
harbor facts                           # facts CLI
harbor mi                              # mi agent CLI

HuggingFace Integration

harbor hf <cmd>                        # HuggingFace CLI (extended)
harbor hf dl <spec>                    # Download model files
harbor hf find <query>                 # Search HF Hub
harbor hf path <spec>                  # Print local cache path
harbor hf token [value]                # Get/set HF token
harbor hf cachedir [path]              # Get/set HF cache path
harbor hf parse-url <url>              # Parse HF file URL

Diagnostics and Utilities

harbor info                            # System information for debugging
harbor doctor                          # Troubleshooting checks
harbor smi                             # NVIDIA GPU information
harbor top                             # GPU usage monitor (nvtop)
harbor size                            # Cache size report
harbor find <file>                     # Find file in Harbor caches
harbor how <question>                  # Ask questions about Harbor CLI
harbor history                         # Command history (interactive)
harbor eject                           # Output standalone Compose config
harbor home                            # Print Harbor workspace path
harbor vscode                          # Open workspace in VS Code
harbor fixfs                           # Fix file system ACLs

Compose Integration

Harbor generates Docker Compose configurations dynamically. Use harbor cmd and harbor eject for direct Compose access.

$(harbor cmd <service>)                # Raw docker compose command for a service
harbor eject                           # Standalone Compose config for current selection

Common Patterns

Quick Start with Ollama + Web UI

harbor up ollama webui
harbor pull llama3.2
harbor open webui

Run llama.cpp with a Specific Model

harbor config set HARBOR_LLAMACPP_MODEL "bartowski/Llama-3.2-3B-Instruct-GGUF:Q4_K_M"
harbor up llamacpp webui
harbor open webui

Multi-Backend Setup

harbor up ollama vllm litellm webui
harbor config set HARBOR_VLLM_MODEL "Qwen/Qwen2.5-3B-Instruct"
harbor pull llama3.2
harbor open webui

Expose a Service to the Internet

harbor up ollama webui
harbor tunnel webui

Use a Profile for Reproducible Setups

harbor up ollama webui
harbor config set HARBOR_OLLAMA_MODEL llama3.2
harbor profile save my-setup

# Later, restore everything
harbor profile load my-setup
harbor up

Run Evaluations

harbor eval                            # Run promptfoo evaluation
harbor bench                           # Run Harbor Bench
harbor k6                              # Run K6 load testing
harbor promptfoo <cmd>                 # Promptfoo CLI
harbor lmeval <cmd>                    # LM Evaluation Harness

Launch Coding Assistants

harbor up ollama
harbor pull qwen2.5-coder:7b
harbor launch --model qwen2.5-coder:7b aider
harbor launch --workflow quickhop --backend ollama --model qwen2.5-coder:7b codex
harbor launch --workflow autocheck --backend ollama --model qwen2.5-coder:7b opencode

Important Notes

• Logs hang: harbor logs tails by default — in scripts/agents, use docker logs <container> with --tail flag instead.
• Config not .env: Never edit .env directly. Use harbor config get/set.
• Default services: harbor up with no args starts services listed in harbor defaults ls.
• Service names: Use harbor ls to discover exact service handles.
• Docker required: Harbor requires Docker and Docker Compose. Run harbor doctor to verify.