Sure! Here's your README modified according to the recommendations, with improved structure, clarity, and visual enhancements:

---

Stable Diffusion Web UI in Docker with NVIDIA GPU 🖥️🚀

A comprehensive guide to running Stable Diffusion with Automatic1111’s Web UI in a Docker container on a host equipped with an NVIDIA GPU.

---

Table of Contents

• Problem
• Solution
• Prerequisites
• Installation Process
  • Step 1: Install NVIDIA Drivers (if necessary)
  • Step 2: Install Docker
  • Step 3: Install NVIDIA Docker Toolkit
  • Step 4: Docker Image Setup
• Accessing the Web UI
• Usage
• Contributing
• License

---

🚧 Problem

When installing the Stable Diffusion Web UI (Automatic1111) in Docker, we encounter a limitation: the Web UI listens only on 127.0.0.1:7860, which restricts access to localhost. Adding the --listen argument when starting the Web UI makes it listen on 0.0.0.0:7860, allowing connections from any source. However, this can block certain extensions during installation.

💡 Solution

To enable external access without restricting extensions:

1. Install Nginx within the Docker container.
2. Configure Nginx to redirect traffic from port 3002 to 127.0.0.1:7860.

This setup will:

• Have Nginx listen on port 3002 within the container and forward requests to the Web UI on 127.0.0.1:7860.
• Allow you to access the Web UI externally via http://localhost:3002, routing traffic through Nginx on port 3002 to the Web UI inside the container.

---

📝 Prerequisites

• NVIDIA Drivers: Ensure NVIDIA drivers are installed on your host system. This guide assumes Pop!_OS (with pre-installed NVIDIA drivers). If you're using a different OS, install NVIDIA drivers as needed.
• Docker: Installed on your host system.
• NVIDIA Docker Toolkit: Installed and configured.

---

🛠️ Installation Process

Step 1: Install NVIDIA Drivers (if necessary)

Refer to the NVIDIA driver installation guide.

Step 2: Install Docker

Follow the official Docker installation guide.

Step 3: Install NVIDIA Docker Toolkit

Complete instructions are available in the NVIDIA Container Toolkit installation guide. Below are key steps:

NVIDIA Toolkit Installation Commands

Add the NVIDIA GPG Key and Repository

# Add the NVIDIA GPG key
curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | \
sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg

Purpose: Downloads the NVIDIA GPG key, converts it to binary, and saves it to /usr/share/keyrings/.

# Add the NVIDIA package list with the signed GPG key
curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list | \
sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \
sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list

Purpose: Adds the NVIDIA repository with the signed GPG key to the system’s package list.

Enable Experimental Packages in the NVIDIA Repo

sudo sed -i -e '/experimental/ s/^#//g' /etc/apt/sources.list.d/nvidia-container-toolkit.list

Purpose: Uncomments lines containing experimental in the NVIDIA repository to enable additional packages.

Install NVIDIA Container Toolkit

sudo apt-get update
sudo apt-get install -y nvidia-container-toolkit

Purpose: Installs the NVIDIA Container Toolkit, enabling Docker to use NVIDIA GPUs.

Configure NVIDIA Runtime for Docker

sudo nvidia-ctk runtime configure --runtime=docker

Purpose: Configures Docker to use the NVIDIA runtime.

sudo systemctl restart docker

Purpose: Restarts Docker to apply changes.

Optional configuration for user-specific daemon.json

nvidia-ctk runtime configure --runtime=docker --config=$HOME/.config/docker/daemon.json

Verify Installation

nvidia-ctk -v

Expected output: NVIDIA Container Toolkit CLI version 1.12.1

Step 4: Docker Image Setup

Prepare Files

• Create a project directory:

  mkdir stable-diffusion-docker
  cd stable-diffusion-docker

• Place your Dockerfile and nginx.conf inside this folder.

Build Docker Image

sudo docker build -t <imagename> .

Replace <imagename> with your desired image name.

Run the Docker Image

sudo docker run -d \
  --add-host=host.docker.internal:host-gateway \
  --gpus all \
  --name <containername> \
  --restart always \
  -p 3002:3002 \
  <imagename>:latest

Replace <containername> with your desired container name.

Explanation of the command:

• -d: Run container in detached mode (in the background).
• --add-host=host.docker.internal:host-gateway: Allows the container to access the host machine.
• --gpus all: Grants the container access to all GPUs.
• --name <containername>: Assigns a name to the container.
• --restart always: Automatically restarts the container if it stops.
• -p 3002:3002: Maps port 3002 of the host to port 3002 of the container.

---

🌐 Accessing the Web UI

You can now access the Stable Diffusion Web UI at:

http://localhost:3002 

WARNING First Time Starting Web UI Take Som time because its Downloading Base SD 1.5 Image

This routes traffic through Nginx on port 3002 to 127.0.0.1:7860 inside the container.

---

📄 Usage

Common Command-Line Arguments for Automatic1111

Here are some useful command-line arguments you might use when running the Web UI:

Argument	Description
--listen	Makes the Web UI accessible from any IP address.
--port <PORT>	Sets the port for the Web UI (default is 7860).
--xformers	Enables memory-efficient attention using the xformers library.
--api	Enables the API, allowing programmatic access to the Web UI.
--ckpt <path>	Specifies the checkpoint model to use.
--gradio-auth <username:password>	Enables authentication for the Web UI.
--medvram	Optimizes VRAM usage for GPUs with limited memory.

---

🤝 Contributing

Contributions are welcome! Please feel free to open issues, submit pull requests, or suggest improvements.

---

📄 License

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

---

Note: Replace placeholders like <imagename> and <containername> with your actual image and container names. Also, update the badge links at the top with your actual Docker Hub username and repository, and ensure the LICENSE file is included in your repository.

Additional Enhancements

• Badges: The badges at the top provide quick visual information about your project's build status and license.
• Table of Contents: Helps users navigate through the README quickly.
• Clear Steps with Headings: Each installation step is clearly marked and explained.
• Command Syntax Highlighting: Improves readability of command-line instructions.
• Usage Examples: Provides helpful command-line arguments for users to customize their experience.
• Contributing Section: Encourages community involvement.
• License Section: Clearly states the licensing of your project.

Let me know if you'd like to add anything else or make further adjustments!