Discord Stable Diffusion Bot

This is a Discord bot that generates images using the Stable Diffusion Pipeline. The bot takes a prompt and generates an image based on the prompt using the Stable Diffusion Pipeline. The generated image is then sent back to the Discord chat.

Getting Started

Prerequisites

• Python 3.6 or higher
• PyTorch 1.6 or higher
• Discord.py
• Diffusers
• dotenv
• Install CUDA

Installation

To set up the Discord Stable Diffusion Bot, follow the steps below:

1. Clone the repository

   git clone <repository_url>

2. Install the dependencies with

   pip install -r requirements.txt

3. Install CUDA for Windows (except if you are using WSL - in that case go to the WSL section)

4. Create a Discord bot and get its token

• Go to the Discord Developer Portal

• Create a new application

• Under the "Token" section, click on "Copy" to copy the token

  For more informations go the Discord documentation and search for Bot Creation

5. Create a .env.config file and add the Discord token

   DISCORD_TOKEN=<your_discord_token_here>

Usage

1. Run the bot

   python3 stablebot.py

2. Use the /generate command followed by a prompt enclosed in double quotes to generate an image. For example:

   /generate "A beautiful sunset over the ocean"

   To customize the resolution and the number of iterations, you can provide additional arguments:

   /generate "[YOUR_PROMPT]" [WIDTH] [HEIGHT] [ITERATION]

   Example:

   /generate "A beautiful sunset over the ocean" 1920 1080 100

WSL (Windows Subsystem for Linux) Setup

If you are using WSL to run the Discord Stable Diffusion Bot, follow these additional steps:

1. Install WSL on your Windows machine. You can find detailed instructions on the official Microsoft documentation: WSL Installation Guide.

2. Install CUDA for WSL: https://learn.microsoft.com/en-us/windows/ai/directml/gpu-cuda-in-wsl

3. Open the WSL terminal and navigate to the project directory.

4. Create a Python virtual environment (recommended but optional)

• If you are running WSL with Ubuntu or Debian, install python venv

  apt install python3.10-venv

• Create the virtual environment

  python3 -m venv .env

• Use the created environment

  source .env/bin/activate

5. Install Python and other dependencies in the WSL environment. Follow the same installation steps mentioned above in the "Installation" section.

Possible errors

• Error: Could not load library libcudnn_cnn_infer.so.8. Error: libcuda.so: cannot open shared object file: No such file or directory Please make sure libcudnn_cnn_infer.so.8 is in your library path!, libcuda.so not found
  Solution: add export LD_LIBRARY_PATH=/usr/lib/wsl/lib:$LD_LIBRARY_PATH to your .bashrc file

Running with GPU

To run the Discord Stable Diffusion Bot with GPU, ensure that you have the following prerequisites:

• A compatible NVIDIA GPU
• CUDA Toolkit installed (refer to the CUDA installation guide for instructions)

Follow these steps to run the bot with GPU:

1. Ensure that the correct CUDA device is specified in the cuda parameter of the StableDiffusionGenerator class within the stablebot.py file. For example:

   cuda = "cuda:0"

   Adjust the device identifier (cuda:0, cuda:1, etc.) as needed based on your GPU configuration. The bot will utilize the GPU for generating images.

Running with CPU

If you want to run the Discord Stable Diffusion Bot using CPU instead of GPU, follow these steps:

1. Modify the cuda parameter in the StableDiffusionGenerator class within the stablebot.py file. Change it to:

   cuda = "cpu"

   You can uncomment the line and comment the one with cuda = "cuda:0".

   The bot will now use CPU for generating images.

Changing the model

It is as simple as commenting/keeping the model you want to use:

# model="prompthero/openjourney",  # "andite/anything-v4.0",
# model="dreamlike-art/dreamlike-photoreal-2.0",
# model="prompthero/openjourney-v4",
model="MirageML/lowpoly-world",

If you want to select another model, chose one from Hugging Face and copy its name like so model=<model_name>

When running the bot your selected model will be downloaded automatically.