How to Self-Host AI Fusion Video with Docker: A Step-by-Step Tutorial

In our overview we explained what AI Fusion Video can do — now it is time to actually run it. This tutorial walks you through a full self-hosted deployment with Docker, from pulling the official image to opening your own AI video studio in the browser.

Step 1: Check the Requirements

AI Fusion Video is a multi-agent system that orchestrates language models and video-generation backends, so give it real resources. A 2-core / 4 GB machine is the practical minimum; for comfortable performance with model inference, plan for 4 cores and 8 GB of RAM.

Step 2: Deploy with Docker

Create a docker-compose.yml file:

services:
  ai-fusion-video:
    image: stonewuu/ai-fusion-video:latest
    restart: unless-stopped
    ports:
      - "8080:8080"
    volumes:
      - ./data/ai-fusion-video:/data

Then start the stack:

docker compose up -d

Step 3: Open Your Studio

Once the container reports healthy, open http://YOUR_SERVER:8080 in your browser. You should see the AI Fusion Video workspace where you can start a new project, paste or write a script, and let the agent pipeline take it from storyboard to finished video.

First Run Checklist

• ✅ Port 8080 reachable from your network / reverse proxy
• ✅ API keys or endpoints configured for the LLM and image/video backends
• ✅ Persistent volume mounted so projects survive updates
• ✅ Enough disk for generated video output

That is it — a complete, agent-powered AI short-drama and comic production studio, running on your own hardware with the MIT-licensed open-source stack.