Lean AI

Your codebase already has an architect. It just needs tools.

Lean AI is an agentic coding assistant that reads your project, plans changes, and executes them — all inside your editor. Give it a task in plain English, review the plan, and watch it work.

Run it fully local with Ollama, or connect to OpenAI and Anthropic when you need heavier reasoning. No cloud account required to get started.

Features

• No prompt engineering needed — describe what you want in plain English. A built-in chat assistant helps you refine your idea into a detailed task before the 6-phase planning pipeline takes over.
• Plan first, then execute — a 6-phase planning pipeline reads your codebase, traces data flow, and produces a structured plan. You approve before anything changes. Thinking and content tokens stream live during each phase so you can watch the agent reason in real-time.
• Three workflow modes — /agent for full planning, /fix for quick bug fixes, /request for open-ended research and documentation tasks.
• Multi-provider — Ollama (free, local), OpenAI, and Anthropic. Switch from the settings panel without restarting.
• Dual-model pipeline — use a fast local model for exploration and implementation, hand off to a cloud model for reasoning-heavy planning phases.
• Built-in code quality — auto-runs your linter and tests after every change, with LLM self-correction on failure.
• Knowledge base — drop internal docs (PDF, EPUB, Word, Markdown) into .lean_ai/knowledge/ for context-aware plans.
• Git-native — every task runs on its own branch. Approve to merge, reject to discard.
• 19 scaffold recipes — bootstrap new projects with /scaffold.

Quick Start

1. Install the extension

Install from the VS Code Marketplace or OpenVSX. On first activation, the extension automatically creates a Python virtual environment and installs the backend server — no manual setup required.

2. Install Ollama

Download Ollama and pull a model:

ollama pull qwen3-coder:30b

3. Open a project and run /init

Type /init in the chat panel to index your workspace and generate project context. Then describe what you want built.

Manual backend setup (advanced)

If you prefer to manage the backend yourself, set lean-ai.backendDir or lean-ai.pythonPath in settings. The automatic installer is skipped when either setting is explicitly configured. See the GitHub repository for details.

Slash Commands

Configuration

Open the settings panel (gear icon in the chat header) to configure:

• LLM Provider — Ollama, OpenAI, or Anthropic
• Model selection — primary, expert, and request models with independent sampling parameters (temperature, top-p, top-k, repeat penalty, context window, max tokens) and thinking mode per model
• Post-validation — lint, test, and format commands
• Search provider — DuckDuckGo, SearXNG, Google, or Bing

API keys for OpenAI and Anthropic are stored securely in your OS keychain.

Requirements

• Python 3.10+ (for the backend server, installed automatically)
• Ollama with a capable model (e.g., qwen3-coder:30b) — or an OpenAI/Anthropic API key

Links

• GitHub Repository — source code, backend setup, and full documentation
• Changelog — release history and recent changes
• Configuration Guide — all environment variables and settings

License

MIT