Self-hosted AI starter kit (by the n8n team)

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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README

Self-hosted AI starter kit (by the n8n team)

Self-hosted AI Starter Kit is an open, docker compose template that quickly bootstraps a fully featured Local AI and Low Code development environment including Open WebUI for an interface to chat with your N8N agents.

This is Cole's version with a couple of improvements and the addition of Open WebUI and Flowise! Also, the local RAG AI Agent workflow from the video will be automatically in your n8n instance if you use this setup instead of the base one provided by n8n!

Original Local AI Starter Kit

Download my N8N + OpenWebUI integration directly on the Open WebUI site. (more instructions below)

n8n.io - Screenshot

Curated by https://github.com/n8n-io and https://github.com/coleam00, it combines the self-hosted n8n platform with a curated list of compatible AI products and components to quickly get started with building self-hosted AI workflows.

What’s included

Self-hosted n8n - Low-code platform with over 400 integrations and advanced AI components

Ollama - Cross-platform LLM platform to install and run the latest local LLMs

Open WebUI - ChatGPT-like interface to privately interact with your local models and N8N agents

Flowise - No/low code AI agent builder that pairs very well with n8n

Qdrant - Open-source, high performance vector store with an comprehensive API

PostgreSQL - Workhorse of the Data Engineering world, handles large amounts of data safely.

Installation

For Nvidia GPU users

git clone https://github.com/coleam00/ai-agents-masterclass.git
cd ai-agents-masterclass/local-ai-packaged
docker compose --profile gpu-nvidia up

[!NOTE] If you have not used your Nvidia GPU with Docker before, please follow the Ollama Docker instructions.

For Mac / Apple Silicon users

If you’re using a Mac with an M1 or newer processor, you can't expose your GPU to the Docker instance, unfortunately. There are two options in this case:

  1. Run the starter kit fully on CPU, like in the section "For everyone else" below
  2. Run Ollama on your Mac for faster inference, and connect to that from the n8n instance

If you want to run Ollama on your mac, check the Ollama homepage for installation instructions, and run the starter kit as follows:

git clone https://github.com/coleam00/ai-agents-masterclass.git
cd ai-agents-masterclass/local-ai-packaged
docker compose up

After you followed the quick start set-up below, change the Ollama credentials by using http://host.docker.internal:11434/ as the host.

For everyone else

git clone https://github.com/coleam00/ai-agents-masterclass.git
cd ai-agents-masterclass/local-ai-packaged
docker compose --profile cpu up

⚡️ Quick start and usage

The main component of the self-hosted AI starter kit is a docker compose file pre-configured with network and disk so there isn’t much else you need to install. After completing the installation steps above, follow the steps below to get started.

  1. Open http://localhost:5678/ in your browser to set up n8n. You’ll only have to do this once. You are NOT creating an account with n8n in the setup here, it is only a local account for your instance!

  2. Open the included workflow: http://localhost:5678/workflow/vTN9y2dLXqTiDfPT

  3. Create credentials for every service:

    Ollama URL: http://ollama:11434

    Postgres: use DB, username, and password from .env. Host is postgres

    Qdrant URL: http://qdrant:6333 (API key can be whatever since this is running locally)

    Google Drive: Follow this guide from n8n. Don't use localhost for the redirect URI, just use another domain you have, it will still work! Alternatively, you can set up local file triggers.

  4. Select Test workflow to start running the workflow.

  5. If this is the first time you’re running the workflow, you may need to wait until Ollama finishes downloading Llama3.1. You can inspect the docker console logs to check on the progress.

  6. Make sure to toggle the workflow as active and copy the "Production" webhook URL!

  7. Open http://localhost:3000/ in your browser to set up Open WebUI. You’ll only have to do this once. You are NOT creating an account with Open WebUI in the setup here, it is only a local account for your instance!

  8. Go to Workspace -> Functions -> Add Function -> Give name + description then paste in the code from n8n_pipe.py

    The function is also published here on Open WebUI's site.

  9. Click on the gear icon and set the n8n_url to the production URL for the webhook you copied in a previous step.

  10. Toggle the function on and now it will be available in your model dropdown in the top left!

To open n8n at any time, visit http://localhost:5678/ in your browser. To open Open WebUI at any time, visit http://localhost:3000/.

With your n8n instance, you’ll have access to over 400 integrations and a suite of basic and advanced AI nodes such as AI Agent, Text classifier, and Information Extractor nodes. To keep everything local, just remember to use the Ollama node for your language model and Qdrant as your vector store.

[!NOTE] This starter kit is designed to help you get started with self-hosted AI workflows. While it’s not fully optimized for production environments, it combines robust components that work well together for proof-of-concept projects. You can customize it to meet your specific needs

Upgrading

For Nvidia GPU users

docker compose --profile gpu-nvidia pull
docker compose create && docker compose --profile gpu-nvidia up

For Mac / Apple Silicon users

docker compose pull
docker compose create && docker compose up

For everyone else

docker compose --profile cpu pull
docker compose create && docker compose --profile cpu up

👓 Recommended reading

n8n is full of useful content for getting started quickly with its AI concepts and nodes. If you run into an issue, go to support.

🎥 Video walkthrough

🛍️ More AI templates

For more AI workflow ideas, visit the official n8n AI template gallery. From each workflow, select the Use workflow button to automatically import the workflow into your local n8n instance.

Learn AI key concepts

Local AI templates

Tips & tricks

Accessing local files

The self-hosted AI starter kit will create a shared folder (by default, located in the same directory) which is mounted to the n8n container and allows n8n to access files on disk. This folder within the n8n container is located at /data/shared -- this is the path you’ll need to use in nodes that interact with the local filesystem.

Nodes that interact with the local filesystem

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