SD XL Deforum Docker Image

This repository provides a Docker-based setup for SD XL Deforum featuring GPU-accelerated inference and a RunPod deployment handler.

Features

• Stable Diffusion XL Deforum: Animation toolkit with advanced Deforum scripting.
• Automatic Model + Deforum CLI Download: On first GPU run, the Deforum code and required model checkpoints are fetched automatically.
• Docker Image: Based on nvidia/cuda:12.4.1-cudnn-devel-ubuntu22.04 for seamless GPU support.
• OpenCV Headless Enforcement: Ensures only the headless OpenCV wheel is used to avoid GUI dependencies.
• RunPod Handler: Serverless function for hosting on RunPod's serverless framework, with optional Cloudflare R2 upload support.
• RunPod Network Storage: Uses RunPod's network storage to serve models efficiently across serverless instances.

Prerequisites

• Docker Engine with GPU support (NVIDIA Docker).
• NVIDIA drivers and CUDA Toolkit on host.
• Python 3.10+ for local testing (optional).
• RunPod account for serverless deployment.

Repository Structure

├── Dockerfile-build                  # Base Docker build for Deforum
├── entrypoint.sh                     # Runtime entrypoint to enforce OpenCV headless
├── build-deforum-deploy.sh           # Build and deploy script
├── comprehensive-requirements.txt    # Pinned Python dependencies
└── README.md                         # This document

CI/CD Build Process

Automated Builds via GitHub Actions

This repository uses GitHub Actions to automatically build and push Docker images to Docker Hub:

1. Trigger: Automatic builds occur on every commit to the main branch
2. Build Process:
   • Uses the Dockerfile-build to create the image
   • Tags the image as edreamai/deforum-studio:<timestamp>-<branch>
   • Also creates a latest tag for the most recent build
   • Pushes both tags to Docker Hub registry

Deployment Flow

The deployment process follows this workflow:

1. Code Commit: Push changes to the main branch
2. Automated Build: GitHub Actions automatically builds and pushes the Docker image to docker.io/edreamai/deforum-studio
3. Image Tag: Note the generated image tag from the GitHub Actions output (format: <timestamp>-<branch>)
4. Serverless Deployment: Update your serverless pod configuration to use the new image tag
5. Release: Deploy the updated configuration to your desired serverless environment

Finding the Latest Image Tag

To find the correct image tag for deployment:

1. GitHub Actions: Check the latest successful workflow run in the "Actions" tab
2. Docker Hub: Visit Docker Hub to see all available tags

Local Building (Development)

For local development and testing:

1. Build with GPU support:

   chmod +x build-deforum-deploy.sh
   ./build-deforum-deploy.sh

   • <deforum-branch> defaults to dev.
   • [settings-file] defaults to test-settings.txt.

2. Result:

   • Docker image tagged as deforum-studio/animation-toolkit:<timestamp>-<branch>.
   • Optional comprehensive-requirements.txt generated.

Local Usage

Run a container manually:

docker run --gpus all -v $(pwd):/input \
  -e ROOT_PATH=/deforum_storage \
  edreamai/deforum-studio:<tag> \
  deforum runsingle --file /input/your-settings.json

Output will be available in /deforum_storage/output/video and copied to ./output by the build script.

Deploying on RunPod

This deployment uses RunPod Network Storage to serve models efficiently across serverless instances, eliminating the need to download models on each cold start.

1. Install dependencies:

   pip install runpod

2. Prepare handler:

   • Ensure runpod_handler.py is present in project root.

3. Configure RunPod:

   export RUNPOD_API_KEY=YOUR_API_KEY_HERE

   • (Optional) Configure Cloudflare R2 bucket credentials in handler.py.
   • Network Storage: The deployment leverages RunPod's network storage to cache models and dependencies, significantly reducing startup times for serverless functions.

4. Deploy:

   Use the image tag from the GitHub Actions build output:

   runpod serverless deploy \
     --name sd-xl-deforum \
     --handler runpod_handler.handler \
     --image edreamai/deforum-studio:<timestamp>-<branch> \
     --memory 16384 \
     --gpu-count 1 \
     --region <your-region>

   Replace <timestamp>-<branch> with the actual tag from the GitHub Actions build (e.g., 20250215123456-main).

5. Invoke:

   runpod serverless invoke \
     --name sd-xl-deforum \
     --input '{"input": {"prompt": "A cinematic landscape", "steps": 30}}'

The response will include a video URL to your generated MP4.

Advanced Configuration

• Settings File: Pass settings_file in payload to override JSON parameters.
• Cloudflare R2 Upload: Configure the following environment variables for R2 access:

Cloudflare R2 Configuration

To enable video uploads to Cloudflare R2, set these environment variables:

export R2_BUCKET_NAME=your-bucket-name
export R2_ENDPOINT_URL=https://your-account-id.r2.cloudflarestorage.com
export R2_ACCESS_KEY_ID=your-r2-access-key-id
export R2_SECRET_ACCESS_KEY=your-r2-secret-access-key
export R2_PUBLIC_DOMAIN=your-custom-domain.com  # Optional: for public URLs

Getting R2 Credentials:

1. Log in to your Cloudflare dashboard
2. Go to R2 Object Storage
3. Create a bucket if you haven't already
4. Go to "Manage R2 API tokens"
5. Create a new API token with R2 permissions
6. Your endpoint URL format: https://<account-id>.r2.cloudflarestorage.com

Public Access (Optional):

If you want public URLs for your videos, you can either:

• Set up a custom domain for your R2 bucket
• Use R2's public URL format (uncomment the appropriate line in handler.py)

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Happy animating with SD XL Deforum on Docker and RunPod!