How to Run MoneyPrinterTurbo as a Service: Docker and Systemd Deployment Guide

Run MoneyPrinterTurbo as a persistent background service using either Docker Compose for containerized deployments or systemd for native Linux process management, exposing the API on port 8080 and the Web UI on port 8501.

MoneyPrinterTurbo is an open-source AI video generation platform that ships with two distinct runtime components. Deploying it as a service requires orchestrating both the FastAPI backend and the Streamlit frontend to run continuously and restart automatically on failure. This guide covers production-ready deployment strategies using the official source files from the harry0703/MoneyPrinterTurbo repository.

Architecture Overview

MoneyPrinterTurbo operates as two independent processes that share the same codebase but serve different traffic patterns.

The Two-Process Architecture

Component	Entry Point	Default Port	Protocol
API Service	main.py	8080	HTTP REST (Uvicorn/FastAPI)
Web UI	webui/Main.py	8501	Streamlit interactive interface

The API service defined in main.py launches a Uvicorn ASGI server that mounts the FastAPI application from app/asgi:app. It exposes REST endpoints under app/controllers/v1/*.py for programmatic video generation. The Web UI defined in webui/Main.py renders a browser-based interface that imports services directly from app.services.llm and app.services.voice, though it can optionally be configured to call the external API.

Key Source Files

Understanding the entry points is critical for service configuration:

• main.py – Executes uvicorn.run() with the ASGI app, reading configuration from app/config/config.py which loads config.toml.
• webui/Main.py – The Streamlit entry point that renders the graphical interface.
• docker-compose.yml – Orchestrates both services with shared volumes for configuration persistence.
• webui.sh – Convenience shell script that wraps the streamlit run command with default flags.

Method 1: Docker Compose Deployment

Docker Compose is the recommended approach for production deployments, as the Dockerfile pre-installs system dependencies including ffmpeg and ImageMagick, ensuring consistent runtime environments.

Prerequisites and Setup

Clone the repository and prepare the configuration:

git clone https://github.com/harry0703/MoneyPrinterTurbo.git
cd MoneyPrinterTurbo

# Create runtime configuration from template

cp config.example.toml config.toml

Edit config.toml to configure your LLM provider API keys and storage paths according to the settings defined in app/config/config.py.

Building and Starting Services

Build the image and launch both services in detached mode:

docker compose build
docker compose up -d

The docker-compose.yml defines two services:

• api – Runs python main.py exposing port 8080
• webui – Runs streamlit run webui/Main.py exposing port 8501

Both services mount the host's config.toml and storage/ directory as volumes, ensuring that video outputs and configuration changes persist across container restarts.

Verification

Confirm both containers are healthy:

docker ps
curl http://localhost:8080/docs  # Access Swagger UI

open http://localhost:8501       # Access Streamlit interface

To stop the services:

docker compose down

Method 2: Systemd Service Deployment

For bare-metal Linux servers, systemd provides native process supervision with automatic restart capabilities and log aggregation via journalctl.

Installation Steps

Install the code and dependencies to a dedicated directory:

sudo mkdir -p /opt/moneyprinterturbo
sudo chown $(whoami):$(whoami) /opt/moneyprinterturbo
git clone https://github.com/harry0703/MoneyPrinterTurbo.git /opt/moneyprinterturbo

# Create unprivileged service user

sudo useradd -r -s /usr/sbin/nologin moneyprinter

# Install system dependencies

sudo apt-get update && sudo apt-get install -y ffmpeg imagemagick

# Install Python dependencies in virtual environment

cd /opt/moneyprinterturbo
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

# Copy and edit configuration

cp config.example.toml config.toml

# Edit config.toml with your API keys

API Service Unit

Create /etc/systemd/system/moneyprinterturbo-api.service:

[Unit]
Description=MoneyPrinterTurbo API Service
After=network.target

[Service]
WorkingDirectory=/opt/moneyprinterturbo
ExecStart=/opt/moneyprinterturbo/venv/bin/python /opt/moneyprinterturbo/main.py
Environment="PYTHONPATH=/opt/moneyprinterturbo"
Restart=on-failure
User=moneyprinter
Group=moneyprinter

[Install]
WantedBy=multi-user.target

Web UI Service Unit

Create /etc/systemd/system/moneyprinterturbo-webui.service:

[Unit]
Description=MoneyPrinterTurbo Web UI (Streamlit)
After=network.target

[Service]
WorkingDirectory=/opt/moneyprinterturbo
ExecStart=/opt/moneyprinterturbo/venv/bin/streamlit run ./webui/Main.py \
    --browser.serverAddress=0.0.0.0 \
    --server.enableCORS=True \
    --browser.gatherUsageStats=False
Environment="PYTHONPATH=/opt/moneyprinterturbo"
Restart=on-failure
User=moneyprinter
Group=moneyprinter

[Install]
WantedBy=multi-user.target

Managing Systemd Services

Enable and start both services:

sudo cp moneyprinterturbo-api.service /etc/systemd/system/
sudo cp moneyprinterturbo-webui.service /etc/systemd/system/
sudo systemctl daemon-reload

sudo systemctl enable --now moneyprinterturbo-api.service
sudo systemctl enable --now moneyprinterturbo-webui.service

Monitor status and logs:

sudo systemctl status moneyprinterturbo-api.service
journalctl -u moneyprinterturbo-webui.service -f

Essential Commands Reference

Task	Docker Compose	Systemd
Start services	docker compose up -d	sudo systemctl start moneyprinterturbo-api.service
View logs	docker compose logs -f	journalctl -u moneyprinterturbo-api.service -f
Restart	docker compose restart	sudo systemctl restart moneyprinterturbo-api.service
Stop	docker compose down	sudo systemctl stop moneyprinterturbo-api.service

Summary

• MoneyPrinterTurbo consists of two distinct services: a FastAPI backend (main.py) on port 8080 and a Streamlit frontend (webui/Main.py) on port 8501.
• Docker Compose provides the simplest deployment path, handling dependency installation via the Dockerfile and ensuring consistent environments across hosts.
• Systemd offers tighter integration with Linux host systems, providing automatic startup on boot and centralized logging through journalctl.
• Both methods require the config.toml file for LLM API keys and ffmpeg paths, loaded at runtime by app/config/config.py.

Frequently Asked Questions

What ports does MoneyPrinterTurbo use by default?

The API service binds to port 8080 and serves the REST API with Swagger documentation available at /docs. The Web UI service binds to port 8501 and provides the Streamlit graphical interface. These ports are hardcoded in the default startup commands but can be modified via environment variables or command-line arguments in your service definitions.

Can I run only the API without the Web UI?

Yes. The components are decoupled by design. To run only the API service, start main.py directly without launching webui/Main.py. This is useful for headless deployments where you intend to interact with MoneyPrinterTurbo programmatically via the REST API rather than through the browser interface.

How do I persist data when using Docker Compose?

The docker-compose.yml mounts the ./storage directory from the host into the container. All generated videos, audio files, and temporary assets are written to this directory by the service layer (app/services). Ensure this directory has appropriate permissions for the container user or bind-mount to a specific host path in your compose override file.

Where are the logs stored when running as a systemd service?

Systemd captures stdout and stderr from both the API and Web UI processes in the system journal. Access logs using journalctl -u moneyprinterturbo-api.service for the backend and journalctl -u moneyprinterturbo-webui.service for the frontend. Add the -f flag to follow logs in real-time, similar to tail -f.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}