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13E498CE010AC6FD
@ -1,6 +1,7 @@
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import subprocess
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import sys
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import os
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import platform
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def install_dependencies():
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"""Install the required dependencies for Stable Diffusion."""
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@ -11,7 +12,9 @@ def install_dependencies():
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"torch",
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"diffusers",
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"transformers",
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"accelerate"
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"accelerate",
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"tqdm",
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"safetensors"
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]
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# Check if CUDA is available
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@ -20,29 +23,71 @@ def install_dependencies():
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cuda_available = torch.cuda.is_available()
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if cuda_available:
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cuda_version = torch.version.cuda
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print(f"CUDA is available (version {cuda_version})")
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print(f"✅ CUDA is available (version {cuda_version})")
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print(f"GPU: {torch.cuda.get_device_name(0)}")
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else:
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print("CUDA is not available. Stable Diffusion will run on CPU (very slow).")
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print("⚠️ CUDA is not available. Stable Diffusion will run on CPU (very slow).")
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except ImportError:
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print("PyTorch not installed yet. Will install with CUDA support.")
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cuda_available = False
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# Install each package
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# Install PyTorch with CUDA support if not already installed
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if "torch" not in sys.modules:
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print("Installing PyTorch with CUDA support...")
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if platform.system() == "Windows":
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# For Windows, use the PyTorch website command
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try:
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subprocess.check_call([
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sys.executable, "-m", "pip", "install",
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"torch", "torchvision", "torchaudio",
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"--index-url", "https://download.pytorch.org/whl/cu118"
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])
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print("✅ Successfully installed PyTorch with CUDA support")
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except subprocess.CalledProcessError as e:
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print(f"❌ Error installing PyTorch: {e}")
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print("Continuing with other dependencies...")
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else:
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# For Linux/Mac, use pip
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try:
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subprocess.check_call([sys.executable, "-m", "pip", "install", "torch"])
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print("✅ Successfully installed PyTorch")
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except subprocess.CalledProcessError as e:
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print(f"❌ Error installing PyTorch: {e}")
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print("Continuing with other dependencies...")
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# Install xformers for memory efficiency if on Windows with CUDA
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if platform.system() == "Windows" and cuda_available:
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try:
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print("Installing xformers for memory efficiency...")
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subprocess.check_call([
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sys.executable, "-m", "pip", "install",
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"xformers", "--index-url", "https://download.pytorch.org/whl/cu118"
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])
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print("✅ Successfully installed xformers")
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packages.append("xformers") # Add to the list of installed packages
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except subprocess.CalledProcessError as e:
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print(f"⚠️ Error installing xformers: {e}")
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print("Continuing without xformers (memory usage may be higher)...")
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# Install other packages
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for package in packages:
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if package == "torch": # Skip torch as we've already handled it
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continue
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print(f"Installing {package}...")
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try:
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subprocess.check_call([sys.executable, "-m", "pip", "install", package])
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print(f"Successfully installed {package}")
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print(f"✅ Successfully installed {package}")
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except subprocess.CalledProcessError as e:
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print(f"Error installing {package}: {e}")
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return False
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print(f"❌ Error installing {package}: {e}")
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print(f"You may need to install {package} manually.")
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print("\nAll dependencies installed successfully!")
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print("\nTo use the Stable Diffusion command:")
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print("1. Restart your bot")
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print("2. Use the /generate command with a text prompt")
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print("3. Wait for the image to be generated (this may take some time)")
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print("\n✅ All dependencies installed successfully!")
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print("\nNext steps:")
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print("1. Download the Illustrious XL model by running: python download_illustrious.py")
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print("2. Restart your bot")
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print("3. Use the /generate command with a text prompt")
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print("4. Wait for the image to be generated (this may take some time)")
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return True
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@ -1,6 +1,6 @@
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# Stable Diffusion Discord Bot Command
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This feature adds a Stable Diffusion image generation command to your Discord bot, running locally on your GPU.
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This feature adds a Stable Diffusion image generation command to your Discord bot, running locally on your GPU. It includes support for the Illustrious XL model from Civitai.
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## Installation
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@ -9,9 +9,14 @@ This feature adds a Stable Diffusion image generation command to your Discord bo
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python install_stable_diffusion.py
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```
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2. Make sure you have a compatible GPU with CUDA support. The command will work on CPU but will be extremely slow.
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2. Download the Illustrious XL model from Civitai:
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```
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python download_illustrious.py
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```
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3. Restart your bot after installing the dependencies.
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3. Make sure you have a compatible GPU with CUDA support. The command will work on CPU but will be extremely slow.
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4. Restart your bot after installing the dependencies and downloading the model.
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## Commands
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@ -23,8 +28,8 @@ Generate an image using Stable Diffusion running locally on your GPU.
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- `negative_prompt` (optional): Things to avoid in the generated image
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- `steps` (optional, default: 30): Number of inference steps (higher = better quality but slower)
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- `guidance_scale` (optional, default: 7.5): How closely to follow the prompt (higher = more faithful but less creative)
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- `width` (optional, default: 512): Image width (must be a multiple of 8)
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- `height` (optional, default: 512): Image height (must be a multiple of 8)
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- `width` (optional, default: 1024): Image width (must be a multiple of 8)
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- `height` (optional, default: 1024): Image height (must be a multiple of 8)
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- `seed` (optional): Random seed for reproducible results (leave empty for random)
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- `hidden` (optional, default: false): Whether to make the response visible only to you
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@ -36,21 +41,44 @@ List available Stable Diffusion models or change the current model (owner only).
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## Available Models
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- **Illustrious XL** (Local) - A high-quality SDXL model from Civitai
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- Stable Diffusion 1.5 (`runwayml/stable-diffusion-v1-5`)
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- Stable Diffusion 2.1 (`stabilityai/stable-diffusion-2-1`)
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- Stable Diffusion XL (`stabilityai/stable-diffusion-xl-base-1.0`)
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## About Illustrious XL
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Illustrious XL is a high-quality SDXL model from Civitai that produces excellent results for a wide range of prompts. It's particularly good at:
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- Detailed illustrations
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- Realistic images
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- Fantasy and sci-fi scenes
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- Character portraits
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- Landscapes and environments
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The model is automatically downloaded and set up by the `download_illustrious.py` script. You can find more information about the model at [Civitai](https://civitai.com/models/795765/illustrious-xl).
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## Requirements
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- CUDA-compatible GPU with at least 4GB VRAM (8GB+ recommended for larger images)
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- CUDA-compatible GPU with at least 8GB VRAM (12GB+ recommended for SDXL models at 1024x1024)
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- Python 3.8+
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- PyTorch with CUDA support
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- diffusers library
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- transformers library
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- accelerate library
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- safetensors library
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- xformers library (optional, for memory efficiency)
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## Troubleshooting
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- If you encounter CUDA out-of-memory errors, try reducing the image dimensions or using a smaller model.
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- The first generation might take longer as the model needs to be loaded into memory.
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- If you encounter CUDA out-of-memory errors, try:
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- Reducing the image dimensions (e.g., 768x768 instead of 1024x1024)
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- Switching to a smaller model (SD 1.5 instead of SDXL)
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- Closing other applications that use GPU memory
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- Using the `--enable_attention_slicing` option when loading the model
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- The first generation might take longer as the model needs to be downloaded and loaded into memory.
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- If you're getting "CUDA not available" errors, make sure your GPU drivers are up to date and PyTorch is installed with CUDA support.
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- If the Illustrious XL model fails to download, you can try downloading it manually from [Civitai](https://civitai.com/models/795765/illustrious-xl) and placing it in the `discordbot/models/illustrious_xl/unet` directory as `diffusion_pytorch_model.safetensors`.
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