Self-hosted AI starter kit (by the n8n team)
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About Self-hosted AI starter kit (by the n8n team)
pydantic agent workflow using mcp servers to test out advanced retrieval of linked data
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Overview
What is Self-hosted AI starter kit (by the n8n team)?
The Self-hosted AI starter kit is an open Docker Compose template that quickly bootstraps a fully featured Local AI and Low Code development environment. It combines the self-hosted n8n platform with curated AI products including Ollama, Open WebUI, Flowise, Qdrant, and PostgreSQL. This version by coleam00 adds Open WebUI and Flowise improvements and includes a pre-configured local RAG AI Agent workflow.
How to use Self-hosted AI starter kit (by the n8n team)?
Clone the repository, navigate to the local-ai-packaged directory, and run docker compose with the appropriate profile (--profile gpu-nvidia, --profile cpu, or without a profile for Mac). Then open http://localhost:5678/ to set up n8n and http://localhost:3000/ to set up Open WebUI. Configure credentials for Ollama, Postgres, Qdrant, and optionally Google Drive, then activate the included workflow and paste the n8n_pipe.py code into Open WebUI’s Functions.
Key features of Self-hosted AI starter kit (by the n8n team)
- Includes self-hosted n8n with over 400 integrations and AI components
- Bundles Ollama for running local LLMs like Llama3.1
- Provides Open WebUI for interacting with models and n8n agents
- Includes Flowise for no/low code AI agent building
- Ships with Qdrant vector store and PostgreSQL database
- Pre-loaded local RAG AI Agent workflow auto-installed on first run
Use cases of Self-hosted AI starter kit (by the n8n team)
- Building and testing self-hosted AI workflows with local language models
- Creating a private ChatGPT-like interface for interacting with n8n agents
- Developing proof-of-concept AI applications that keep data entirely on-premises
- Experimenting with RAG pipelines using local vector stores and LLMs
FAQ from Self-hosted AI starter kit (by the n8n team)
What hardware do I need?
The kit supports Nvidia GPUs (via Docker profile), Mac/Apple Silicon (CPU-only or with external Ollama), and CPU-only environments for all other setups.
How do I upgrade the starter kit?
Run docker compose --profile <profile> pull followed by docker compose create && docker compose --profile <profile> up, using the same profile as your initial installation.
Where are local files stored?
A shared folder is mounted to the n8n container at /data/shared. Nodes like Read/Write Files from Disk, Local File Trigger, and Execute Command can access files there.
How do I connect to Ollama from n8n?
For Docker-based setups, use http://ollama:11434 as the Ollama URL. For Mac users running Ollama natively, use http://host.docker.internal:11434/.
Is this production-ready?
The starter kit is designed to help get started with self-hosted AI workflows for proof-of-concept projects and is not fully optimized for production environments, though it uses robust components.
Frequently asked questions
What hardware do I need?
The kit supports Nvidia GPUs (via Docker profile), Mac/Apple Silicon (CPU-only or with external Ollama), and CPU-only environments for all other setups.
How do I upgrade the starter kit?
Run `docker compose --profile <profile> pull` followed by `docker compose create && docker compose --profile <profile> up`, using the same profile as your initial installation.
Where are local files stored?
A shared folder is mounted to the n8n container at `/data/shared`. Nodes like Read/Write Files from Disk, Local File Trigger, and Execute Command can access files there.
How do I connect to Ollama from n8n?
For Docker-based setups, use `http://ollama:11434` as the Ollama URL. For Mac users running Ollama natively, use `http://host.docker.internal:11434/`.
Is this production-ready?
The starter kit is designed to help get started with self-hosted AI workflows for proof-of-concept projects and is not fully optimized for production environments, though it uses robust components.
Basic information
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