Monastery

The homelab's vibe coding center for creating and deploying your projects on your infrastructure.

A self-hosted sanctuary for AI-assisted coding. Monastery is a fully self-hosted, browser-based AI coding environment where you prompt local or frontier LLMs to generate, edit, run, debug, and deploy full applications. The harness runs as a standalone service (Docker-first) and connects to LLM backends over the network.

This is an ever changing work in progress.

• I'm piecing this together and implementing as I can test.

Key Features

• Decoupled Architecture: Harness runs independently of LLM servers. Auto-discovery or manual config for local endpoints.
• 100% Self-Hosted: Everything containerized, network-aware, and privacy-focused.
• Lightweight: Harness container <1GB RAM idle; works on low-power nodes.
• Homelab Native: Deploy to Coolify or Dokploy, route through Cloudflare tunnels, back apps with a shared PocketBase, and keep projects in your own git forge.
• OpenAI-Compatible: Works with Ollama, vLLM, llama.cpp, OpenAI, Groq, and more.
• Build & Discuss: Build mode writes and edits files; Discuss mode answers questions and drafts a plan without touching anything — then Build this plan hands it over.
• Live Preview + Undo: the preview reloads as files land, and every AI edit is snapshotted first so one click abandons it.

Quick Start

Prerequisites

• Docker and Docker Compose
• An LLM endpoint (e.g., Ollama, vLLM, or OpenAI API key)

1. Clone and Configure

git clone https://github.com/jherforth/Monastery.git
cd Monastery
cp .env.example .env (optional - you can enter keys in the UI)

Edit .env to configure your LLM endpoint:

# For Ollama on same host (Linux/Mac):
LLM_BASE_URL=http://host.docker.internal:11434

# For Ollama in separate container:
LLM_BASE_URL=http://ollama:11434

# For OpenAI:
LLM_BASE_URL=https://api.openai.com/v1
OPENAI_API_KEY=sk-...

2. Run with Docker Compose

docker compose up -d

The harness will be available at http://localhost:3091.

3. Connect to Your LLM

1. Open the web UI at http://localhost:3091
2. Navigate to Settings → LLM Endpoints
3. Add your LLM endpoint or use auto-discovery to find Ollama on your LAN
4. Test the connection and start prompting!

Architecture

┌─────────────┐  HTTP + SSE   ┌──────────────┐
│   Browser   │ ◄──────────► │   Harness    │
│   (Web UI)  │               │   (Rust)     │
└─────────────┘               └──────┬───────┘
                                     │
                          ┌──────────┼──────────┐
                          │          │          │
                          ▼          ▼          ▼
                   ┌──────────┐ ┌────────┐ ┌─────────┐
                   │  Ollama  │ │ vLLM   │ │ OpenAI  │
                   │ (local)  │ │(local) │ │(cloud)  │
                   └──────────┘ └────────┘ └─────────┘

Tech Stack

• Backend: Rust (Axum) - lightweight, safe, performant
• Frontend: React + TypeScript with Vite - modern, responsive UI with Monaco editor
• Database: SQLite - embedded, easy backup
• LLM Client: OpenAI-compatible protocol
• Styling: Tailwind CSS with custom Monastery theme

Configuration

Environment Variable	Description	Default
PORT	API server port (in Docker, nginx serves the UI on 3091 and proxies /api to it)	8080
DATA_DIR	Data directory path	./data
LOG_LEVEL	Logging level	info
LLM_BASE_URL	Default LLM endpoint	-
DISABLE_DISCOVERY	Disable mDNS discovery	false

API Endpoints

The full route table lives in crates/harness-api/src/main.rs. By area:

Area	Routes
Health & models	GET /api/health, GET /api/models
Chat	POST /api/projects/:id/chat — one turn: streams the reply and applies its file changes (SSE)
LLM endpoints	GET/POST /api/endpoints, DELETE /api/endpoints/:id, POST /api/endpoints/:id/test, GET /api/discovery
Projects & files	/api/projects, /api/starters, /api/projects/:id/files (+ read, write, dir, upload, move), shell (user-run only), preview/*path
Sessions	/api/projects/:project_id/sessions (+ :session_id, messages)
Snapshots	/api/projects/:project_id/snapshots (+ checkpoint, restore, diff)
Git	/api/git/connections, status, commit-push, pull, push, clone
Hosting	/api/hosting/connections, deploy, preview, deployment-log

Development

Build from Source

# Install Rust
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh

# Build
cargo build --release

# Run
cargo run

Run Tests

cargo test

Self-Hosting Wizard

The built-in wizard (History & Ship → Deploy to your homelab) helps you:

1. Detect the project's framework and generate a Dockerfile if it has none
2. Deploy it to your Coolify or Dokploy instance, redeploying in place on later runs
3. Optionally route it through a Cloudflare tunnel and inject a shared PocketBase URL
4. Hand a failed build's log back to the chat to fix

Deploying to Coolify? See Coolify Deployment — Requirements & Setup for the HTTPS-hostname/TLS prerequisites, how updates redeploy in place, and troubleshooting.

Security

• Minimal outbound connectivity by default
• Model output never executes on its own: shell blocks only run when you click Run, without a shell, from an allowlist, with project-relative arguments only
• File APIs refuse paths outside the project before touching disk
• No Docker socket or other host access required

License

AGPL v3 - see LICENSE for details.

Contributing

Contributions welcome! Please read our contributing guidelines before submitting PRs.

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Built with intention for the homelab community

With a little (LOT/ALL) of help from my frields - Qwen, Claude, and DeepSeek - For AI by AI