/self-hosted-ai-starter-kit

The Self-hosted AI Starter Kit is an open-source template that quickly sets up a local AI environment. Curated by n8n, it provides essential tools for creating secure, self-hosted AI workflows.

Apache License 2.0Apache-2.0

Self-hosted AI starter kit

Self-hosted AI Starter Kit is an open-source Docker Compose template designed to swiftly initialize a comprehensive local AI and low-code development environment.

n8n.io - Screenshot

Curated by https://github.com/n8n-io, 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

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

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

What you can build

⭐️ AI Agents for scheduling appointments

⭐️ Summarize Company PDFs securely without data leaks

⭐️ Smarter Slack Bots for enhanced company communications and IT operations

⭐️ Private Financial Document Analysis at minimal cost

Installation

Cloning the Repository

git clone https://github.com/n8n-io/self-hosted-ai-starter-kit.git
cd self-hosted-ai-starter-kit

Running n8n using Docker Compose

For Nvidia GPU users

git clone https://github.com/n8n-io/self-hosted-ai-starter-kit.git
cd self-hosted-ai-starter-kit
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/n8n-io/self-hosted-ai-starter-kit.git
cd self-hosted-ai-starter-kit
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/n8n-io/self-hosted-ai-starter-kit.git
cd self-hosted-ai-starter-kit
docker compose --profile cpu up

⚡️ Quick start and usage

The core of the Self-hosted AI Starter Kit is a Docker Compose file, pre-configured with network and storage settings, minimizing the need for additional installations. After completing the installation steps above, simply 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.
  2. Open the included workflow: http://localhost:5678/workflow/srOnR8PAY3u4RSwb
  3. Select Test workflow to start running the workflow.
  4. If this is the first time you’re running the workflow, you may need to wait until Ollama finishes downloading Llama3.2. You can inspect the docker console logs to check on the progress.

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

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 setups:

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 Non-GPU setups:

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

📜 License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

💬 Support

Join the conversation in the n8n Forum, where you can:

  • Share Your Work: Show off what you’ve built with n8n and inspire others in the community.
  • Ask Questions: Whether you’re just getting started or you’re a seasoned pro, the community and our team are ready to support with any challenges.
  • Propose Ideas: Have an idea for a feature or improvement? Let us know! We’re always eager to hear what you’d like to see next.