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Monastery - Project Vision

Core Purpose

A calm, focused, self-hosted sanctuary for AI-assisted coding. Monastery is a fully self-hosted, browser-based AI coding environment where users 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.

Tagline: "Build in silence. Deploy with purpose."

Key Differentiators

  • Decoupled Architecture: Harness runs independently of LLM servers. Auto-discovery or manual config for local endpoints (e.g., http://ollama:11434 or IP:port on LAN).
  • 100% self-hosted by default with built-in Self-Hosting Wizard (per ODT).
  • Native priority for local models via OpenAI-compatible proxy.
  • Deep homelab integrations: Proxmox, Coolify, PocketBase, MQTT, etc.
  • Resource-aware and low-overhead: Harness itself is lightweight; offload heavy inference.

Deployment Flexibility

  • Single docker compose up for the harness.
  • Users run LLMs separately (same host, separate container, or different machine on LAN).
  • Wizard helps configure network connections, service discovery (mDNS/Avahi), and proxying.

Success Metrics

  • Match/exceed bolt.diy UX while being lighter and more homelab-native.
  • Harness container <1GB RAM idle; works on low-power nodes.
  • Seamless connection to Ollama/vLLM/etc. with zero extra config in common setups.