Docs

Everything you need to install, run, and customise a local AI stack with Llanite.

Install

Llanite is distributed via npm. The package exposes both llanite and the short alias lla. Node 20+ required.

$ npm install -g @llanite/cli$ llanite --version$ llanite doctor

llanite doctor checks Ollama CLI, server reachability, and the registry cache. Run it first if anything looks wrong.

Quickstart

Three commands get you from zero to a running local AI agent.

$ # Install Llanite$ npm install -g @llanite/cli$ $ # Install a stack (pulls the model, configures runtime)$ llanite install standard$ $ # Launch the TUI agent session$ llanite run standard

Not sure which stack fits your machine? Run llanite stacks to browse the catalog, or llanite inspect standard to see the full manifest before committing.

Local LLM Setup

Most local AI failures are integration failures, not just model failures. Llanite treats setup as a full stack: model, runtime, agentic layer, context budget, hardware fit, and policy owner.

Backend wiring

Local agents often need a provider URL, model ID, runtime process, and agent config to agree. Stacks keep those choices together so they can be inspected and cloned.

Tool calling

A model can be good at chat but poor at structured tool use. Prefer stacks that pair a tool-capable model with an agent layer known to use it well.

Context latency

Local runs slow down when the agent sends too much context. Keep context budgets intentional and clear the session when the transcript stops helping.

RAM vs VRAM

System RAM, VRAM, and Apple unified memory behave differently. Use model fit as a starting point, then watch live RAM/swap pressure during real work.

Policy ownership

Access policy belongs to the selected agent layer unless you add an outer sandbox. OpenClaw stacks are OpenClaw-managed; llanite-agent stacks are Llanite-enforced.

Repeatability

If a setup works once, it should not require rediscovery in another workspace. Clone the stack and keep the working model/runtime/agent choices together.

Policy by agent layer

llanite-agent

Llanite enforces stack permissions before file writes, shell commands, network access, or denied tools run.

openclaw

OpenClaw manages tool visibility, sandboxing, and access through its own configuration. Llanite labels this explicitly and can package sane defaults.

custom agent

Effective policy is owned by that agent unless you run it inside an outer OS/container sandbox.

Guides

Short explainers for common search questions about Llanite and local AI agent workflows.

What is Llanite?

Llanite is an open-source CLI for installing complete local AI agent stacks with models, runtimes, agents, permissions, and hardware requirements.

Local AI agents

Learn what a local AI agent is, how Llanite packages one, and why local agents are useful for private and repeatable developer workflows.

Llanite vs Ollama

Understand the difference between Llanite and Ollama: Ollama serves local models, while Llanite packages complete local AI agent stacks on top of Ollama.

Local coder: local LLM coding agents

Use Llanite local-coder to run a private local LLM coding agent with explicit models, tool access, git workflows, and permission boundaries.

Local AI agent on Mac

How to install and run a local AI agent on a Mac with Apple Silicon. Llanite and Ollama make it three commands to get a full local model stack running.

Local AI agent with Ollama

Learn how to run a local AI agent with Ollama. Llanite adds the agent loop, tools, and permissions on top of Ollama's model serving in a single install command.

Private AI coding assistant

Run a private AI coding assistant locally with Llanite and Ollama. Your code stays on your machine — no cloud API, no subscription, and three commands to get started.

Open source coding agent

Set up a fully open source coding agent with Llanite, Ollama, and open-weights models. The whole stack is inspectable, free to use, and three commands to install.

Llanite vs Continue.dev

Understand how Llanite and Continue.dev differ. Continue is an IDE extension for inline completions; Llanite is a CLI for installing and running complete local model stacks.

Commands

Full CLI reference.

Setup

llanite install <stack>

Pull the model, configure the runtime, and save the stack locally.

llanite run <stack>

Launch the TUI agent session for a stack.

Discovery

llanite stacks

Browse the prebuilt stack catalog.

llanite inspect <stack>

Show the full resolved manifest: model, runtime, agent, tools, permissions, hardware requirements.

llanite doctor [stack]

Check Llanite, Ollama, model availability, and stack compatibility.

llanite models

List models in the registry with parameter counts and hardware requirements.

Customisation

llanite set <stack> model <model>

Swap the model for a stack.

llanite set <stack> runtime <runtime>

Swap the runtime for a stack.

llanite set <stack> agent <agent>

Swap the agent for a stack.

llanite clone <stack> <name>

Fork a stack into a custom local copy.

Cleanup

llanite remove <stack>

Remove a stack config and unlink the agent.

llanite uninstall <model>

Remove a model from the Ollama cache.

Registry

llanite fetch

Fetch and validate the Llanite registry cache.

llanite catalog

List all registry entries.

llanite search <query>

Search the local registry cache.

The TUI

llanite run opens a fully animated terminal UI built with Ink. It has four parts:

Status line

Pinned at the top. Shows stack ID, model name and size, runtime, agent, and workspace directory.

Transcript

Scrolling conversation history. User messages, assistant responses, and tool call results all appear here.

Working indicator

Appears while the agent is active. Shows a cycling status phrase (thinking → weighing options → deciding), a live token counter (↑ N) during response generation, and elapsed time.

System stats footer

Live RAM and swap usage, pressure level (normal / tight / high), and model size. RAM and swap have a shimmer animation to show they are refreshing every 3 seconds. Type /stats to toggle.

Slash Commands

Type any slash command in the input box during a session. Autocomplete shows matches as you type.

/help

List available slash commands.

/tools

List the built-in tools the agent can call.

/clear

Clear the conversation transcript.

/status

Show current session status.

/model

Show current model name, parameter count, and disk size.

/runtime

Show runtime info (Ollama URL, status).

/context

Show context window usage and remaining tokens.

/permissions

Show current permission settings for the stack.

/fit

Toggle the model fit panel (RAM requirements vs. system RAM).

/stats

Toggle the system stats footer.

/plan auto

Agent decides when to plan (default).

/plan on

Always plan before every turn.

/plan off

Skip planning, go straight to execution.

/ram

Show RAM usage broken down by top processes, with a bar chart.

/exit

End the session.

Agent & Planning

The Llanite agent is a ReAct-style loop: it reads your prompt, decides which tool to call (or whether to answer directly), executes the tool, observes the result, and repeats. Before each response it may optionally plan.

Planning modes

Planning produces a short step-by-step breakdown before execution. Three modes are available:

/plan auto

The agent decides whether to plan based on prompt complexity (default).

/plan on

Always produce a plan. Good for complex multi-file tasks.

/plan off

Skip planning. Fastest for simple one-shot requests.

Permission prompts

When a tool requires a confirmed permission (e.g. file_write: confirm), the TUI pauses and presents a prompt before execution. You can allow once, allow for the session, or deny. Denied tools return an error the agent can observe and recover from.

Model Fit

Llanite reads your system RAM at install time and classifies each model candidate against it.

Comfortable

Model disk size is well under your available RAM. No pressure expected.

Recommended

Model fits within recommended RAM range. Good performance.

Tight

Model is at the edge of your RAM. May cause swapping under load.

Incompatible

Model requires more RAM than your system has. Not installable.

During a session, type /fit to toggle the model fit panel, which shows the full hardware breakdown for your current stack. The system stats footer shows live RAM and swap pressure.

On macOS, Ollama loads model weights into Metal GPU buffers (unified memory). These don't appear in the standard process RSS count — the /ram command accounts for this by adding the model as a separate line labelled ·Metal·.

Stack Customization

Every component of a stack can be swapped with a single command. Changes are saved immediately.

$ # Swap the model$ llanite set standard model qwen3:14b$ $ # Swap the runtime$ llanite set standard runtime ollama$ $ # Swap the agent$ llanite set standard agent llanite-agent$ $ # Fork a stack into a custom copy$ llanite clone standard my-coder

After changing the model, run llanite doctor standard to confirm the new model is available on your Ollama instance, and llanite inspect standard to verify the updated manifest.

Concepts

Stack

The user-facing package: model, runtime, agentic layer, policy owner, context window config, and hardware requirements. Stacks are inspectable before anything runs.

Registry

A metadata layer that tells Llanite where components come from and how they fit together. Validated locally — no account required.

Runtime

The local model server. Llanite targets Ollama. The runtime is declared per-stack and can be swapped with llanite set.

Agent

The prompt loop and tool orchestration layer. Llanite ships llanite-agent and can package external agents such as OpenClaw.

Policy Owner

The layer responsible for effective tool access. Llanite-agent stacks use Llanite-enforced permissions; OpenClaw stacks use OpenClaw tool and sandbox configuration.

Doctor

A health check for Llanite, Ollama, the registry, and a specific stack's hardware compatibility. Run it before installing.

Model Fit

Llanite reads your system RAM and classifies each model as comfortable, recommended, tight, or incompatible. Shown during install and in the TUI fit panel.

Contributing

Stacks, models, runtimes, and agents are defined as YAML files in the registry. To contribute a new entry, open a pull request at github.com/lachlanforgan/llanite.

Stack schema (minimum fields)

$ id: my-stack$ name: My Stack$ summary: One-line description.$ runtime: ollama$ model: qwen3:8b$ agent: llanite-agent$ tools:$   - id: filesystem$     access: read-only$ permissions:$   file_write: deny$   shell: deny$   network: deny$   secrets: block$ hardware:$   min_ram_gb: 8$   recommended_ram_gb: 16

Troubleshooting

Start with llanite doctor. It checks Ollama CLI, server reachability, registry cache, and model availability in one pass.

$ llanite doctor$ llanite doctor standard$ llanite inspect standard

Ollama not found

Install Ollama from ollama.com, then run ollama serve and retry llanite doctor.

Model not available

Run ollama pull <model> manually, or llanite install <stack> which pulls it automatically.

High RAM pressure during a session

Type /ram to see which processes are consuming memory. The model weights are loaded into Metal GPU buffers on macOS and appear as ·Metal· in the breakdown.

Agent not responding

Press Esc to interrupt the current turn. Type /status to check session state.

Context window full

Type /context to see usage. Use /clear to reset the conversation, or use a stack with a larger context token setting.