This repository provides a one-command Docker Compose installation for a self-hosted AI automation platform. It bundles over 30 tools, including n8n, Ollama, Flowise, RAG engines, and vector databases, pre-configured with Caddy for automatic HTTPS. It targets users seeking a private AI homelab or a free alternative to commercial automation services.

How It Works

The project uses Docker Compose to orchestrate a multi-service environment. An interactive wizard simplifies deployment, allowing users to select components like n8n, Ollama, and Flowise. Caddy handles automatic SSL certificates for secure access. The setup includes core infrastructure (PostgreSQL, Redis) and optional monitoring (Prometheus, Grafana), creating a robust, scalable, self-contained AI workshop.

Quick Start & Requirements

• Install Command:

  git clone https://github.com/kossakovsky/n8n-install && cd n8n-install && sudo bash ./scripts/install.sh
  

• Prerequisites:
  • A registered domain with a wildcard DNS A-record pointing to the server's IP.
  • Server OS: Ubuntu 24.04 LTS (64-bit).
  • Hardware: Minimum 4 GB RAM / 2 CPU / 40 GB Disk (minimal); 20 GB RAM / 4 CPU / 60 GB Disk (full deployment).
• Setup: Single-command script initiates an interactive wizard for configuration, Docker installation, and service deployment. Optional import of 300+ community workflows adds 20-30 minutes.
• Links: Cloudflare Tunnel integration docs at cloudflare-instructions.md.

Highlighted Details

• Extensive Toolset: Integrates over 30 services: n8n, Ollama, Flowise, ComfyUI, Dify, Supabase, Qdrant, Weaviate, Grafana, Prometheus, Open WebUI.
• Scalable n8n: Configured in queue mode with Redis/Postgres, supporting dynamic worker scaling for parallel execution.
• Automated Deployment: One-command install with interactive wizard, auto secrets, and Caddy for auto-HTTPS.
• Pre-built Workflows: Option to import 300+ community n8n workflows during setup.

Maintenance & Community

The project acknowledges contributions via its GitHub Contributors Page. It builds upon work from the n8n team and other contributors. Specific community channels (Discord/Slack) or a roadmap are not detailed in the README.

Licensing & Compatibility

• License: Apache License 2.0.
• Compatibility: Permissive license suitable for commercial use and integration into closed-source projects.

Limitations & Caveats

Full deployment requires substantial server resources (20GB RAM, 4 CPU, 60GB Disk). Initial access may show temporary browser security warnings ("Dangerous Site") during SSL acquisition. The make clean command removes unused Docker resources; use with caution to avoid data loss. Anonymous telemetry via Scarf is enabled by default but can be disabled.