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🚀 AI Stack: n8n, MLflow & Open WebUI

A complete, self-hosted AI infrastructure stack featuring workflow automation, experiment tracking, and a ChatGPT-like interface.

License: MITDockerPRs Welcome

🌟 Features

  • n8n: Powerful workflow automation with 200+ integrations
  • MLflow: End-to-end machine learning lifecycle management
  • Open WebUI: Beautiful, responsive web interface for LLMs
  • Ollama: Local LLM runner supporting multiple models
  • Nginx: Secure reverse proxy with Let's Encrypt SSL
  • Docker Compose: Easy deployment and scaling

📋 Prerequisites

  • Docker and Docker Compose installed
  • Minimum 8GB RAM (16GB+ recommended for LLMs)
  • Linux-based system (Ubuntu 20.04+ recommended)
  • Domain name (or subdomains) pointing to your server

🛠️ Project Structure

ai-stack/
├── docker-compose.yml # Main Docker Compose configuration
├── docker-compose.override.yml # Development overrides
├── docker-compose.prod.yml # Production overrides
├── nginx/ # Nginx configurations
│ ├── nginx.conf # Main Nginx config
│ └── conf.d/ # Server blocks
│ ├── default.conf # Default catch-all
│ ├── n8n.conf # n8n proxy config
│ ├── mlflow.conf # MLflow proxy config
│ └── openwebui.conf # Open WebUI proxy config
├── n8n/ # n8n data
│ └── data/ # Workflows and credentials
├── mlflow/ # MLflow data
│ └── artifacts/ # Model artifacts
├── openwebui/ # Open WebUI data
│ └── data/ # Chat history and models
├── certs/ # SSL certificates
├── .env.example # Example environment variables
├── setup.sh # Setup script
├── LICENSE # MIT License
└── README.md # This file

🚀 Quick Start

  1. Clone the repository:

    git clone https://github.com/jomasego/ai-stack.git
cd ai-stack

  2. Copy the example environment file:

    cp .env.example .env

  3. Edit the .env file with your configuration:

    nano .env
    • Set your domain (e.g., DOMAIN=example.com)
    • Set your email for Let's Encrypt
    • Update passwords and secrets

  4. Run the setup script:

    chmod +x setup.sh
./setup.sh

    This will:

    • Install Docker and Docker Compose if needed
    • Set up SSL certificates
    • Configure Nginx
    • Start all services

  5. Access the services:

🔧 Configuration

Environment Variables

Edit the .env file to configure the stack:

# Domain configuration
DOMAIN=yourdomain.com
# n8n
N8N_HOST=n8n.yourdomain.com
N8N_USER_EMAIL=admin@yourdomain.com
N8N_USER_PASSWORD=your-secure-password
# Open WebUI
WEBUI_SECRET_KEY=your-secure-secret-key
# Let's Encrypt
EMAIL=your-email@example.com
STAGING=0 # Set to 1 for testing

Ports

By default, the following ports are used:

  • 80/443: Nginx (HTTP/HTTPS)
  • 5678: n8n (internal)
  • 5000: MLflow (internal)
  • 8080: Open WebUI (internal)
  • 11434: Ollama (internal)

🐳 Docker Commands

Start services:

docker-compose up -d

Stop services:

docker-compose down

View logs:

# All services
docker-compose logs -f
# Specific service
docker-compose logs -f n8n

Update services:

docker-compose pull
docker-compose up -d --force-recreate

🔒 Security

  1. Change all default passwords in the .env file
  2. Use strong passwords for all services
  3. Enable authentication for all services
  4. Keep Docker and images updated
  5. Back up your data regularly

🤝 Contributing

Contributions are welcome! Please read our Contributing Guide for details on how to contribute.

📄 License

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

🙏 Acknowledgments

About

My personal setup for a cloud server with AI/ML services ranging from n8n, through MLFlow and Ollama, to the user interface to interact with my LLMs, open-webui

Resources

Readme
MIT license

Contributing

Contributing
Activity

Stars

0 stars

Watchers

0 watching

Forks

0 forks
Report repository

Releases

Packages

Contributors

Languages

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GitHub - jomasego/ai-stack: My personal setup for a cloud server with AI/ML services ranging from n8n, through MLFlow and Ollama, to the user interface to interact with my LLMs, open-webui · GitHub
Skip to content
BranchesTags
Repository files navigation
🚀 AI Stack: n8n, MLflow & Open WebUI
A complete, self-hosted AI infrastructure stack featuring workflow automation, experiment tracking, and a ChatGPT-like interface.
License: MITDockerPRs Welcome
🌟 Features
  • n8n: Powerful workflow automation with 200+ integrations
  • MLflow: End-to-end machine learning lifecycle management
  • Open WebUI: Beautiful, responsive web interface for LLMs
  • Ollama: Local LLM runner supporting multiple models
  • Nginx: Secure reverse proxy with Let's Encrypt SSL
  • Docker Compose: Easy deployment and scaling
📋 Prerequisites
  • Docker and Docker Compose installed

  • Minimum 8GB RAM (16GB+ recommended for LLMs)
  • Linux-based system (Ubuntu 20.04+ recommended)
  • Domain name (or subdomains) pointing to your server
🛠️ Project Structure
ai-stack/
├── docker-compose.yml # Main Docker Compose configuration
├── docker-compose.override.yml # Development overrides
├── docker-compose.prod.yml # Production overrides
├── nginx/ # Nginx configurations
│ ├── nginx.conf # Main Nginx config
│ └── conf.d/ # Server blocks
│ ├── default.conf # Default catch-all
│ ├── n8n.conf # n8n proxy config
│ ├── mlflow.conf # MLflow proxy config
│ └── openwebui.conf # Open WebUI proxy config
├── n8n/ # n8n data
│ └── data/ # Workflows and credentials
├── mlflow/ # MLflow data
│ └── artifacts/ # Model artifacts
├── openwebui/ # Open WebUI data
│ └── data/ # Chat history and models
├── certs/ # SSL certificates
├── .env.example # Example environment variables
├── setup.sh # Setup script
├── LICENSE # MIT License
└── README.md # This file

🚀 Quick Start
  1. Clone the repository:
    git clone https://github.com/jomasego/ai-stack.git
cd ai-stack
  2. Copy the example environment file:
    cp .env.example .env
  3. Edit the .env file with your configuration:
    nano .env
    • Set your domain (e.g., DOMAIN=example.com)
    • Set your email for Let's Encrypt
    • Update passwords and secrets
  4. Run the setup script:
    chmod +x setup.sh
./setup.sh
    This will:
    • Install Docker and Docker Compose if needed
    • Set up SSL certificates
    • Configure Nginx
    • Start all services
  5. Access the services:
🔧 Configuration
Environment Variables
Edit the .env file to configure the stack:
# Domain configuration
DOMAIN=yourdomain.com
# n8n
N8N_HOST=n8n.yourdomain.com
N8N_USER_EMAIL=admin@yourdomain.com
N8N_USER_PASSWORD=your-secure-password
# Open WebUI
WEBUI_SECRET_KEY=your-secure-secret-key
# Let's Encrypt
EMAIL=your-email@example.com
STAGING=0 # Set to 1 for testing
Ports
By default, the following ports are used:
  • 80/443: Nginx (HTTP/HTTPS)
  • 5678: n8n (internal)
  • 5000: MLflow (internal)
  • 8080: Open WebUI (internal)
  • 11434: Ollama (internal)
🐳 Docker Commands
Start services:
docker-compose up -d
Stop services:
docker-compose down
View logs:
# All services
docker-compose logs -f
# Specific service
docker-compose logs -f n8n
Update services:
docker-compose pull
docker-compose up -d --force-recreate
🔒 Security
  1. Change all default passwords in the .env file
  2. Use strong passwords for all services
  3. Enable authentication for all services
  4. Keep Docker and images updated
  5. Back up your data regularly
🤝 Contributing
Contributions are welcome! Please read our Contributing Guide for details on how to contribute.
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
🙏 Acknowledgments
About
My personal setup for a cloud server with AI/ML services ranging from n8n, through MLFlow and Ollama, to the user interface to interact with my LLMs, open-webui
Resources
Readme
MIT license
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
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GitHub - jomasego/ai-stack: My personal setup for a cloud server with AI/ML services ranging from n8n, through MLFlow and Ollama, to the user interface to interact with my LLMs, open-webui · GitHub
Skip to content
BranchesTags
Repository files navigation
🚀 AI Stack: n8n, MLflow & Open WebUI
A complete, self-hosted AI infrastructure stack featuring workflow automation, experiment tracking, and a ChatGPT-like interface.
License: MITDockerPRs Welcome
🌟 Features
  • n8n: Powerful workflow automation with 200+ integrations
  • MLflow: End-to-end machine learning lifecycle management
  • Open WebUI: Beautiful, responsive web interface for LLMs
  • Ollama: Local LLM runner supporting multiple models
  • Nginx: Secure reverse proxy with Let's Encrypt SSL
  • Docker Compose: Easy deployment and scaling
📋 Prerequisites
  • Docker and Docker Compose installed

  • Minimum 8GB RAM (16GB+ recommended for LLMs)
  • Linux-based system (Ubuntu 20.04+ recommended)
  • Domain name (or subdomains) pointing to your server
🛠️ Project Structure
ai-stack/
├── docker-compose.yml # Main Docker Compose configuration
├── docker-compose.override.yml # Development overrides
├── docker-compose.prod.yml # Production overrides
├── nginx/ # Nginx configurations
│ ├── nginx.conf # Main Nginx config
│ └── conf.d/ # Server blocks
│ ├── default.conf # Default catch-all
│ ├── n8n.conf # n8n proxy config
│ ├── mlflow.conf # MLflow proxy config
│ └── openwebui.conf # Open WebUI proxy config
├── n8n/ # n8n data
│ └── data/ # Workflows and credentials
├── mlflow/ # MLflow data
│ └── artifacts/ # Model artifacts
├── openwebui/ # Open WebUI data
│ └── data/ # Chat history and models
├── certs/ # SSL certificates
├── .env.example # Example environment variables
├── setup.sh # Setup script
├── LICENSE # MIT License
└── README.md # This file

🚀 Quick Start
  1. Clone the repository:
    git clone https://github.com/jomasego/ai-stack.git
cd ai-stack
  2. Copy the example environment file:
    cp .env.example .env
  3. Edit the .env file with your configuration:
    nano .env
    • Set your domain (e.g., DOMAIN=example.com)
    • Set your email for Let's Encrypt
    • Update passwords and secrets
  4. Run the setup script:
    chmod +x setup.sh
./setup.sh
    This will:
    • Install Docker and Docker Compose if needed
    • Set up SSL certificates
    • Configure Nginx
    • Start all services
  5. Access the services:
🔧 Configuration
Environment Variables
Edit the .env file to configure the stack:
# Domain configuration
DOMAIN=yourdomain.com
# n8n
N8N_HOST=n8n.yourdomain.com
N8N_USER_EMAIL=admin@yourdomain.com
N8N_USER_PASSWORD=your-secure-password
# Open WebUI
WEBUI_SECRET_KEY=your-secure-secret-key
# Let's Encrypt
EMAIL=your-email@example.com
STAGING=0 # Set to 1 for testing
Ports
By default, the following ports are used:
  • 80/443: Nginx (HTTP/HTTPS)
  • 5678: n8n (internal)
  • 5000: MLflow (internal)
  • 8080: Open WebUI (internal)
  • 11434: Ollama (internal)
🐳 Docker Commands
Start services:
docker-compose up -d
Stop services:
docker-compose down
View logs:
# All services
docker-compose logs -f
# Specific service
docker-compose logs -f n8n
Update services:
docker-compose pull
docker-compose up -d --force-recreate
🔒 Security
  1. Change all default passwords in the .env file
  2. Use strong passwords for all services
  3. Enable authentication for all services
  4. Keep Docker and images updated
  5. Back up your data regularly
🤝 Contributing
Contributions are welcome! Please read our Contributing Guide for details on how to contribute.
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
🙏 Acknowledgments
About
My personal setup for a cloud server with AI/ML services ranging from n8n, through MLFlow and Ollama, to the user interface to interact with my LLMs, open-webui
Resources
Readme
MIT license
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Highlight search terms from Google/DuckDuckGo/Bing referrer
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var ref = document.referrer;
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(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - jomasego/ai-stack: My personal setup for a cloud server with AI/ML services ranging from n8n, through MLFlow and Ollama, to the user interface to interact with my LLMs, open-webui · GitHub
Skip to content
BranchesTags
Repository files navigation
🚀 AI Stack: n8n, MLflow & Open WebUI
A complete, self-hosted AI infrastructure stack featuring workflow automation, experiment tracking, and a ChatGPT-like interface.
License: MITDockerPRs Welcome
🌟 Features
  • n8n: Powerful workflow automation with 200+ integrations
  • MLflow: End-to-end machine learning lifecycle management
  • Open WebUI: Beautiful, responsive web interface for LLMs
  • Ollama: Local LLM runner supporting multiple models
  • Nginx: Secure reverse proxy with Let's Encrypt SSL
  • Docker Compose: Easy deployment and scaling
📋 Prerequisites
  • Docker and Docker Compose installed

  • Minimum 8GB RAM (16GB+ recommended for LLMs)
  • Linux-based system (Ubuntu 20.04+ recommended)
  • Domain name (or subdomains) pointing to your server
🛠️ Project Structure
ai-stack/
├── docker-compose.yml # Main Docker Compose configuration
├── docker-compose.override.yml # Development overrides
├── docker-compose.prod.yml # Production overrides
├── nginx/ # Nginx configurations
│ ├── nginx.conf # Main Nginx config
│ └── conf.d/ # Server blocks
│ ├── default.conf # Default catch-all
│ ├── n8n.conf # n8n proxy config
│ ├── mlflow.conf # MLflow proxy config
│ └── openwebui.conf # Open WebUI proxy config
├── n8n/ # n8n data
│ └── data/ # Workflows and credentials
├── mlflow/ # MLflow data
│ └── artifacts/ # Model artifacts
├── openwebui/ # Open WebUI data
│ └── data/ # Chat history and models
├── certs/ # SSL certificates
├── .env.example # Example environment variables
├── setup.sh # Setup script
├── LICENSE # MIT License
└── README.md # This file

🚀 Quick Start
  1. Clone the repository:
    git clone https://github.com/jomasego/ai-stack.git
cd ai-stack
  2. Copy the example environment file:
    cp .env.example .env
  3. Edit the .env file with your configuration:
    nano .env
    • Set your domain (e.g., DOMAIN=example.com)
    • Set your email for Let's Encrypt
    • Update passwords and secrets
  4. Run the setup script:
    chmod +x setup.sh
./setup.sh
    This will:
    • Install Docker and Docker Compose if needed
    • Set up SSL certificates
    • Configure Nginx
    • Start all services
  5. Access the services:
🔧 Configuration
Environment Variables
Edit the .env file to configure the stack:
# Domain configuration
DOMAIN=yourdomain.com
# n8n
N8N_HOST=n8n.yourdomain.com
N8N_USER_EMAIL=admin@yourdomain.com
N8N_USER_PASSWORD=your-secure-password
# Open WebUI
WEBUI_SECRET_KEY=your-secure-secret-key
# Let's Encrypt
EMAIL=your-email@example.com
STAGING=0 # Set to 1 for testing
Ports
By default, the following ports are used:
  • 80/443: Nginx (HTTP/HTTPS)
  • 5678: n8n (internal)
  • 5000: MLflow (internal)
  • 8080: Open WebUI (internal)
  • 11434: Ollama (internal)
🐳 Docker Commands
Start services:
docker-compose up -d
Stop services:
docker-compose down
View logs:
# All services
docker-compose logs -f
# Specific service
docker-compose logs -f n8n
Update services:
docker-compose pull
docker-compose up -d --force-recreate
🔒 Security
  1. Change all default passwords in the .env file
  2. Use strong passwords for all services
  3. Enable authentication for all services
  4. Keep Docker and images updated
  5. Back up your data regularly
🤝 Contributing
Contributions are welcome! Please read our Contributing Guide for details on how to contribute.
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
🙏 Acknowledgments
About
My personal setup for a cloud server with AI/ML services ranging from n8n, through MLFlow and Ollama, to the user interface to interact with my LLMs, open-webui
Resources
Readme
MIT license
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

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})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '
GitHub - jomasego/ai-stack: My personal setup for a cloud server with AI/ML services ranging from n8n, through MLFlow and Ollama, to the user interface to interact with my LLMs, open-webui · GitHub
Skip to content
BranchesTags
Repository files navigation
🚀 AI Stack: n8n, MLflow & Open WebUI
A complete, self-hosted AI infrastructure stack featuring workflow automation, experiment tracking, and a ChatGPT-like interface.
License: MITDockerPRs Welcome
🌟 Features
  • n8n: Powerful workflow automation with 200+ integrations
  • MLflow: End-to-end machine learning lifecycle management
  • Open WebUI: Beautiful, responsive web interface for LLMs
  • Ollama: Local LLM runner supporting multiple models
  • Nginx: Secure reverse proxy with Let's Encrypt SSL
  • Docker Compose: Easy deployment and scaling
📋 Prerequisites
  • Docker and Docker Compose installed

  • Minimum 8GB RAM (16GB+ recommended for LLMs)
  • Linux-based system (Ubuntu 20.04+ recommended)
  • Domain name (or subdomains) pointing to your server
🛠️ Project Structure
ai-stack/
├── docker-compose.yml # Main Docker Compose configuration
├── docker-compose.override.yml # Development overrides
├── docker-compose.prod.yml # Production overrides
├── nginx/ # Nginx configurations
│ ├── nginx.conf # Main Nginx config
│ └── conf.d/ # Server blocks
│ ├── default.conf # Default catch-all
│ ├── n8n.conf # n8n proxy config
│ ├── mlflow.conf # MLflow proxy config
│ └── openwebui.conf # Open WebUI proxy config
├── n8n/ # n8n data
│ └── data/ # Workflows and credentials
├── mlflow/ # MLflow data
│ └── artifacts/ # Model artifacts
├── openwebui/ # Open WebUI data
│ └── data/ # Chat history and models
├── certs/ # SSL certificates
├── .env.example # Example environment variables
├── setup.sh # Setup script
├── LICENSE # MIT License
└── README.md # This file

🚀 Quick Start
  1. Clone the repository:
    git clone https://github.com/jomasego/ai-stack.git
cd ai-stack
  2. Copy the example environment file:
    cp .env.example .env
  3. Edit the .env file with your configuration:
    nano .env
    • Set your domain (e.g., DOMAIN=example.com)
    • Set your email for Let's Encrypt
    • Update passwords and secrets
  4. Run the setup script:
    chmod +x setup.sh
./setup.sh
    This will:
    • Install Docker and Docker Compose if needed
    • Set up SSL certificates
    • Configure Nginx
    • Start all services
  5. Access the services:
🔧 Configuration
Environment Variables
Edit the .env file to configure the stack:
# Domain configuration
DOMAIN=yourdomain.com
# n8n
N8N_HOST=n8n.yourdomain.com
N8N_USER_EMAIL=admin@yourdomain.com
N8N_USER_PASSWORD=your-secure-password
# Open WebUI
WEBUI_SECRET_KEY=your-secure-secret-key
# Let's Encrypt
EMAIL=your-email@example.com
STAGING=0 # Set to 1 for testing
Ports
By default, the following ports are used:
  • 80/443: Nginx (HTTP/HTTPS)
  • 5678: n8n (internal)
  • 5000: MLflow (internal)
  • 8080: Open WebUI (internal)
  • 11434: Ollama (internal)
🐳 Docker Commands
Start services:
docker-compose up -d
Stop services:
docker-compose down
View logs:
# All services
docker-compose logs -f
# Specific service
docker-compose logs -f n8n
Update services:
docker-compose pull
docker-compose up -d --force-recreate
🔒 Security
  1. Change all default passwords in the .env file
  2. Use strong passwords for all services
  3. Enable authentication for all services
  4. Keep Docker and images updated
  5. Back up your data regularly
🤝 Contributing
Contributions are welcome! Please read our Contributing Guide for details on how to contribute.
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
🙏 Acknowledgments
About
My personal setup for a cloud server with AI/ML services ranging from n8n, through MLFlow and Ollama, to the user interface to interact with my LLMs, open-webui
Resources
Readme
MIT license
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
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, 'i');
if (__m === '*' || __re.test(location.href)) {
// Auto-enable theater mode on YouTube
(function() {
function tryTheater() {
var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]');
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lastUrl = location.href;
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(function(){
try {
var __m = "*";
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GitHub - jomasego/ai-stack: My personal setup for a cloud server with AI/ML services ranging from n8n, through MLFlow and Ollama, to the user interface to interact with my LLMs, open-webui · GitHub
Skip to content
BranchesTags
Repository files navigation
🚀 AI Stack: n8n, MLflow & Open WebUI
A complete, self-hosted AI infrastructure stack featuring workflow automation, experiment tracking, and a ChatGPT-like interface.
License: MITDockerPRs Welcome
🌟 Features
  • n8n: Powerful workflow automation with 200+ integrations
  • MLflow: End-to-end machine learning lifecycle management
  • Open WebUI: Beautiful, responsive web interface for LLMs
  • Ollama: Local LLM runner supporting multiple models
  • Nginx: Secure reverse proxy with Let's Encrypt SSL
  • Docker Compose: Easy deployment and scaling
📋 Prerequisites
  • Docker and Docker Compose installed

  • Minimum 8GB RAM (16GB+ recommended for LLMs)
  • Linux-based system (Ubuntu 20.04+ recommended)
  • Domain name (or subdomains) pointing to your server
🛠️ Project Structure
ai-stack/
├── docker-compose.yml # Main Docker Compose configuration
├── docker-compose.override.yml # Development overrides
├── docker-compose.prod.yml # Production overrides
├── nginx/ # Nginx configurations
│ ├── nginx.conf # Main Nginx config
│ └── conf.d/ # Server blocks
│ ├── default.conf # Default catch-all
│ ├── n8n.conf # n8n proxy config
│ ├── mlflow.conf # MLflow proxy config
│ └── openwebui.conf # Open WebUI proxy config
├── n8n/ # n8n data
│ └── data/ # Workflows and credentials
├── mlflow/ # MLflow data
│ └── artifacts/ # Model artifacts
├── openwebui/ # Open WebUI data
│ └── data/ # Chat history and models
├── certs/ # SSL certificates
├── .env.example # Example environment variables
├── setup.sh # Setup script
├── LICENSE # MIT License
└── README.md # This file

🚀 Quick Start
  1. Clone the repository:
    git clone https://github.com/jomasego/ai-stack.git
cd ai-stack
  2. Copy the example environment file:
    cp .env.example .env
  3. Edit the .env file with your configuration:
    nano .env
    • Set your domain (e.g., DOMAIN=example.com)
    • Set your email for Let's Encrypt
    • Update passwords and secrets
  4. Run the setup script:
    chmod +x setup.sh
./setup.sh
    This will:
    • Install Docker and Docker Compose if needed
    • Set up SSL certificates
    • Configure Nginx
    • Start all services
  5. Access the services:
🔧 Configuration
Environment Variables
Edit the .env file to configure the stack:
# Domain configuration
DOMAIN=yourdomain.com
# n8n
N8N_HOST=n8n.yourdomain.com
N8N_USER_EMAIL=admin@yourdomain.com
N8N_USER_PASSWORD=your-secure-password
# Open WebUI
WEBUI_SECRET_KEY=your-secure-secret-key
# Let's Encrypt
EMAIL=your-email@example.com
STAGING=0 # Set to 1 for testing
Ports
By default, the following ports are used:
  • 80/443: Nginx (HTTP/HTTPS)
  • 5678: n8n (internal)
  • 5000: MLflow (internal)
  • 8080: Open WebUI (internal)
  • 11434: Ollama (internal)
🐳 Docker Commands
Start services:
docker-compose up -d
Stop services:
docker-compose down
View logs:
# All services
docker-compose logs -f
# Specific service
docker-compose logs -f n8n
Update services:
docker-compose pull
docker-compose up -d --force-recreate
🔒 Security
  1. Change all default passwords in the .env file
  2. Use strong passwords for all services
  3. Enable authentication for all services
  4. Keep Docker and images updated
  5. Back up your data regularly
🤝 Contributing
Contributions are welcome! Please read our Contributing Guide for details on how to contribute.
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
🙏 Acknowledgments
About
My personal setup for a cloud server with AI/ML services ranging from n8n, through MLFlow and Ollama, to the user interface to interact with my LLMs, open-webui
Resources
Readme
MIT license
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Remove or un-stick sticky/fixed headers that block content
(function() {
function unstick() {
document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) {
if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {
el.style.position = 'static';
el.style.top = 'auto';
el.style.zIndex = 'auto';
}
});
}
unstick();
var observer = new MutationObserver(unstick);
observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });
})();
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - jomasego/ai-stack: My personal setup for a cloud server with AI/ML services ranging from n8n, through MLFlow and Ollama, to the user interface to interact with my LLMs, open-webui · GitHub
Skip to content
BranchesTags
Repository files navigation
🚀 AI Stack: n8n, MLflow & Open WebUI
A complete, self-hosted AI infrastructure stack featuring workflow automation, experiment tracking, and a ChatGPT-like interface.
License: MITDockerPRs Welcome
🌟 Features
  • n8n: Powerful workflow automation with 200+ integrations
  • MLflow: End-to-end machine learning lifecycle management
  • Open WebUI: Beautiful, responsive web interface for LLMs
  • Ollama: Local LLM runner supporting multiple models
  • Nginx: Secure reverse proxy with Let's Encrypt SSL
  • Docker Compose: Easy deployment and scaling
📋 Prerequisites
  • Docker and Docker Compose installed

  • Minimum 8GB RAM (16GB+ recommended for LLMs)
  • Linux-based system (Ubuntu 20.04+ recommended)
  • Domain name (or subdomains) pointing to your server
🛠️ Project Structure
ai-stack/
├── docker-compose.yml # Main Docker Compose configuration
├── docker-compose.override.yml # Development overrides
├── docker-compose.prod.yml # Production overrides
├── nginx/ # Nginx configurations
│ ├── nginx.conf # Main Nginx config
│ └── conf.d/ # Server blocks
│ ├── default.conf # Default catch-all
│ ├── n8n.conf # n8n proxy config
│ ├── mlflow.conf # MLflow proxy config
│ └── openwebui.conf # Open WebUI proxy config
├── n8n/ # n8n data
│ └── data/ # Workflows and credentials
├── mlflow/ # MLflow data
│ └── artifacts/ # Model artifacts
├── openwebui/ # Open WebUI data
│ └── data/ # Chat history and models
├── certs/ # SSL certificates
├── .env.example # Example environment variables
├── setup.sh # Setup script
├── LICENSE # MIT License
└── README.md # This file

🚀 Quick Start
  1. Clone the repository:
    git clone https://github.com/jomasego/ai-stack.git
cd ai-stack
  2. Copy the example environment file:
    cp .env.example .env
  3. Edit the .env file with your configuration:
    nano .env
    • Set your domain (e.g., DOMAIN=example.com)
    • Set your email for Let's Encrypt
    • Update passwords and secrets
  4. Run the setup script:
    chmod +x setup.sh
./setup.sh
    This will:
    • Install Docker and Docker Compose if needed
    • Set up SSL certificates
    • Configure Nginx
    • Start all services
  5. Access the services:
🔧 Configuration
Environment Variables
Edit the .env file to configure the stack:
# Domain configuration
DOMAIN=yourdomain.com
# n8n
N8N_HOST=n8n.yourdomain.com
N8N_USER_EMAIL=admin@yourdomain.com
N8N_USER_PASSWORD=your-secure-password
# Open WebUI
WEBUI_SECRET_KEY=your-secure-secret-key
# Let's Encrypt
EMAIL=your-email@example.com
STAGING=0 # Set to 1 for testing
Ports
By default, the following ports are used:
  • 80/443: Nginx (HTTP/HTTPS)
  • 5678: n8n (internal)
  • 5000: MLflow (internal)
  • 8080: Open WebUI (internal)
  • 11434: Ollama (internal)
🐳 Docker Commands
Start services:
docker-compose up -d
Stop services:
docker-compose down
View logs:
# All services
docker-compose logs -f
# Specific service
docker-compose logs -f n8n
Update services:
docker-compose pull
docker-compose up -d --force-recreate
🔒 Security
  1. Change all default passwords in the .env file
  2. Use strong passwords for all services
  3. Enable authentication for all services
  4. Keep Docker and images updated
  5. Back up your data regularly
🤝 Contributing
Contributions are welcome! Please read our Contributing Guide for details on how to contribute.
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
🙏 Acknowledgments
About
My personal setup for a cloud server with AI/ML services ranging from n8n, through MLFlow and Ollama, to the user interface to interact with my LLMs, open-webui
Resources
Readme
MIT license
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Universal Dark Mode - works on any site
(function() {
var enabled = true;
function applyDarkMode() {
if (!enabled) return;
// Create style element if it doesn't exist
var style = document.getElementById('universal-dark-mode-style');
if (!style) {
style = document.createElement('style');
style.id = 'universal-dark-mode-style';
document.head.appendChild(style);
}
// Dark mode CSS - inverts colors but preserves images/video
style.textContent = '
/* Invert everything except media */
html {
filter: invert(1) hue-rotate(180deg) !important;
background: #1a1a2e !important;
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/* Restore images, videos, iframes, canvas */
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filter: invert(1) hue-rotate(180deg) !important;
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.monaco-editor, .monaco-editor *,
.markdown-body pre, .markdown-body pre *,
.highlight, .highlight *,
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filter: none !important;
}
/* Fix common UI elements */
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background: #2d2d44 !important;
border-color: #444 !important;
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::-webkit-scrollbar-thumb { background: #444 !important; }
::-webkit-scrollbar-thumb:hover { background: #555 !important; }
/* Selection */
::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
';
}
function removeDarkMode() {
var style = document.getElementById('universal-dark-mode-style');
if (style) style.remove();
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// Toggle with Alt+Shift+D
document.addEventListener('keydown', function(e) {
if (e.altKey && e.shiftKey && e.key === 'D') {
e.preventDefault();
enabled = !enabled;
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applyDarkMode();
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console.log('[Universal Dark Mode] Disabled');
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console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');
})();
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} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
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})();
GitHub - jomasego/ai-stack: My personal setup for a cloud server with AI/ML services ranging from n8n, through MLFlow and Ollama, to the user interface to interact with my LLMs, open-webui · GitHub
Skip to content
BranchesTags
Repository files navigation
🚀 AI Stack: n8n, MLflow & Open WebUI
A complete, self-hosted AI infrastructure stack featuring workflow automation, experiment tracking, and a ChatGPT-like interface.
License: MITDockerPRs Welcome
🌟 Features
  • n8n: Powerful workflow automation with 200+ integrations
  • MLflow: End-to-end machine learning lifecycle management
  • Open WebUI: Beautiful, responsive web interface for LLMs
  • Ollama: Local LLM runner supporting multiple models
  • Nginx: Secure reverse proxy with Let's Encrypt SSL
  • Docker Compose: Easy deployment and scaling
📋 Prerequisites
  • Docker and Docker Compose installed

  • Minimum 8GB RAM (16GB+ recommended for LLMs)
  • Linux-based system (Ubuntu 20.04+ recommended)
  • Domain name (or subdomains) pointing to your server
🛠️ Project Structure
ai-stack/
├── docker-compose.yml # Main Docker Compose configuration
├── docker-compose.override.yml # Development overrides
├── docker-compose.prod.yml # Production overrides
├── nginx/ # Nginx configurations
│ ├── nginx.conf # Main Nginx config
│ └── conf.d/ # Server blocks
│ ├── default.conf # Default catch-all
│ ├── n8n.conf # n8n proxy config
│ ├── mlflow.conf # MLflow proxy config
│ └── openwebui.conf # Open WebUI proxy config
├── n8n/ # n8n data
│ └── data/ # Workflows and credentials
├── mlflow/ # MLflow data
│ └── artifacts/ # Model artifacts
├── openwebui/ # Open WebUI data
│ └── data/ # Chat history and models
├── certs/ # SSL certificates
├── .env.example # Example environment variables
├── setup.sh # Setup script
├── LICENSE # MIT License
└── README.md # This file

🚀 Quick Start
  1. Clone the repository:
    git clone https://github.com/jomasego/ai-stack.git
cd ai-stack
  2. Copy the example environment file:
    cp .env.example .env
  3. Edit the .env file with your configuration:
    nano .env
    • Set your domain (e.g., DOMAIN=example.com)
    • Set your email for Let's Encrypt
    • Update passwords and secrets
  4. Run the setup script:
    chmod +x setup.sh
./setup.sh
    This will:
    • Install Docker and Docker Compose if needed
    • Set up SSL certificates
    • Configure Nginx
    • Start all services
  5. Access the services:
🔧 Configuration
Environment Variables
Edit the .env file to configure the stack:
# Domain configuration
DOMAIN=yourdomain.com
# n8n
N8N_HOST=n8n.yourdomain.com
N8N_USER_EMAIL=admin@yourdomain.com
N8N_USER_PASSWORD=your-secure-password
# Open WebUI
WEBUI_SECRET_KEY=your-secure-secret-key
# Let's Encrypt
EMAIL=your-email@example.com
STAGING=0 # Set to 1 for testing
Ports
By default, the following ports are used:
  • 80/443: Nginx (HTTP/HTTPS)
  • 5678: n8n (internal)
  • 5000: MLflow (internal)
  • 8080: Open WebUI (internal)
  • 11434: Ollama (internal)
🐳 Docker Commands
Start services:
docker-compose up -d
Stop services:
docker-compose down
View logs:
# All services
docker-compose logs -f
# Specific service
docker-compose logs -f n8n
Update services:
docker-compose pull
docker-compose up -d --force-recreate
🔒 Security
  1. Change all default passwords in the .env file
  2. Use strong passwords for all services
  3. Enable authentication for all services
  4. Keep Docker and images updated
  5. Back up your data regularly
🤝 Contributing
Contributions are welcome! Please read our Contributing Guide for details on how to contribute.
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
🙏 Acknowledgments
About
My personal setup for a cloud server with AI/ML services ranging from n8n, through MLFlow and Ollama, to the user interface to interact with my LLMs, open-webui
Resources
Readme
MIT license
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages