https://github.com/mashb1t/ai-starterkit-docker
Starterkit for local AI / LLM development
https://github.com/mashb1t/ai-starterkit-docker
ai docker docker-compose n8n ollama open-webui starterkit
Last synced: 3 months ago
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Starterkit for local AI / LLM development
- Host: GitHub
- URL: https://github.com/mashb1t/ai-starterkit-docker
- Owner: mashb1t
- License: mit
- Created: 2025-04-07T23:26:08.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-04-12T19:09:29.000Z (about 1 year ago)
- Last Synced: 2025-04-14T18:38:50.475Z (about 1 year ago)
- Topics: ai, docker, docker-compose, n8n, ollama, open-webui, starterkit
- Language: CSS
- Homepage:
- Size: 132 KB
- Stars: 1
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# AI Starterkit (Docker)
## Included Tools
- [GetHomepage](https://gethomepage.dev/): customizable application dashboard
- [n8n](https://n8n.io/): workflow automation tool
- [Open WebUI](https://github.com/open-webui/open-webui): web-based UI for AI models
- [Ollama](https://ollama.com/): local LLMs (does not support GPU acceleration on MacOS, use ollama via homebrew instead)
## Setup
### Install Docker Desktop
- [Docker Desktop for Mac](https://www.docker.com/products/docker-desktop/)
- [Docker Desktop for Windows](https://www.docker.com/products/docker-desktop/)
- [Docker Desktop for Linux](https://docs.docker.com/desktop/install/linux-install/)
### Clone the repository
```bash
git clone https://github.com/mashb1t/ai-starterkit-docker.git
cd ai-starterkit-docker
```
### Modify environment variables
- create a `.env` file in the root directory of the project
- copy the contents of `.env.example` to `.env`
- modify the values as needed
> [!NOTE]
> If you have not used your GPU with Docker before, please follow the
> [Ollama Docker instructions](https://github.com/ollama/ollama/blob/main/docs/docker.md).
### For Nvidia GPU users
```
docker compose --profile gpu-nvidia up -d
```
### For AMD GPU users
```
docker compose --profile gpu-amd up -d
```
### 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](https://ollama.com/)
for installation instructions, and run the starter kit as follows:
```
docker compose up -d
```
### For Mac users running OLLAMA locally
See install instructions below.
```bash
docker compose up -d
```
Then run either `ollama serve` or the ollama app to start the server.
### For everyone else
```
docker compose --profile cpu up -d
```
## Open Dashboard
Open your browser and go to [http://localhost:3000](http://localhost:3000) to access the dashboard.
## Update Tools
To update all tools, you can use the following commands:
```bash
docker-compose pull
```
## Install Ollama (optional, best for MacOS users)
### ollama app
Download from the [ollama website](https://ollama.com/download)
### OR Install via homebrew (MacOS only)
1. install brew if not already installed
2. install ollama via homebrew
```bash
brew install ollama
```
3. verify the installation
```bash
ollama -v
```
4. start ollama server
```bash
ollama serve
```
5. pull a LLM, e.g. llama3.2
```bash
ollama pull llama3.2:3b
```
## Set up n8n widget
To display statistics such as workflow count and execution count, you can follow these steps:
1. copy file from copy_me_to_workflows_once/homepage-widget.json to workflows/homepage-widget.json
2. docker compose up -d
3. delete file workflows/homepage-widget.json
4. go to ... > Settings > n8n API, create a new key, copy to clipboard
5. create new credential "homepage-widget", type: n8n, API Key: value from before, URL: http://127.0.0.1:5678/api/v1
6. adjust workflow, use credential "homepage-widget", save and set active
7. uncomment widget in services.yaml
8. reload localhost:3000