Visionatrix
AI Media processing using ComfyUI
Stars: 122
Visionatrix is a project aimed at providing easy use of ComfyUI workflows. It offers simplified setup and update processes, a minimalistic UI for daily workflow use, stable workflows with versioning and update support, scalability for multiple instances and task workers, multiple user support with integration of different user backends, LLM power for integration with Ollama/Gemini, and seamless integration as a service with backend endpoints and webhook support. The project is approaching version 1.0 release and welcomes new ideas for further implementation.
README:
Simplify your AI image generation workflows with Visionatrixβan intuitive interface built on top of ComfyUI
- π§ Easy Setup & Updates: Quick setup with simple installation and seamless version updates.
- π₯οΈ Minimalistic UI: Clean, user-friendly interface designed for daily workflow usage.
- π Prompt Translation Support: Automatically translate prompts for media generation.
- π οΈ Stable Workflows: Versioned and upgradable workflows.
- π Scalability: Run multiple instances with simultaneous task workers for increased productivity.
- π₯ Multi-User Support: Configure for multiple users with ease and integrate different user backends.
- π€ LLM Integration: Effortlessly incorporate Ollama/Gemini as your LLM for ComfyUI workflows.
- π Seamless Integration: Run as a service with backend endpoints for smooth project integration.
- π LoRA Integration: Easy integrate LoRAs from CivitAI into your flows.
- π³ Docker Compose: Official Docker images and a pre-configured Docker Compose file.
Access the Visionatrix UI at http://localhost:8288 (default).
Note: Starting from version 1.10 Visionatrix launches ComfyUI webserver at http://127.0.0.1:8188
-
Python
3.10or higher. (3.12recommended) -
GPU with at least
8 GBof memory (12GB recommended)
Install prerequisites (Python, Git, etc.)
For Ubuntu 22.04:
sudo apt install wget curl python3-venv python3-pip build-essential gitIt is also recommended to install FFMpeg dependencies with:
sudo apt install ffmpeg libsm6 libxext6Download and run the easy_install.py script:
Note: This script will clone the Visionatrix repository into your current folder and perform the installation. After installation, you can always run
easy_installfrom the "scripts" folder.
Using wget:
wget -O easy_install.py https://raw.githubusercontent.com/Visionatrix/Visionatrix/main/scripts/easy_install.py && python3 easy_install.pyUsing curl:
curl -o easy_install.py https://raw.githubusercontent.com/Visionatrix/Visionatrix/main/scripts/easy_install.py && python3 easy_install.pyFollow the prompts during installation. In most cases, everything should work smoothly.
To launch Visionatrix from the activated virtual environment:
python -m visionatrix run --uiWe offer a portable version to simplify installation (no need for Git or Visual Studio compilers).
Currently, we provide versions for CUDA/CPU. If there's demand, we can add a DirectML version.
- Download: Visit our Releases page.
-
Get the Portable Archive: Download
vix_portable_cuda.7z. -
Unpack and Run: Extract the archive and run
run_nvidia_gpu.batorrun_cpu.bat.
For manual installation steps, please refer to our detailed documentation.
The easiest way to set up paths is through the user interface, by going to Settings->ComfyUI.
In most cases, the easiest way is to set ComfyUI base data folder to some absolute path where you want to store models, task results, and settings.
This will allow you to freely reinstall everything from scratch without losing data or models.
Note: For easy Windows portable upgrades, we assume you have
ComfyUI base data folderparameter set.
We highly recommend filling in both the CivitAI token and the HuggingFace token in the settings.
Many models cannot be downloaded by public users without a token.
Run the easy_install script and select the "Update" option.
python3 easy_install.pyUpdating the portable version involves:
- Unpacking the new portable version.
- Moving
visionatrix.dbfrom the old version to the new one.
Hint
Alternatively, you can specify a custom path for visionatrix.db using the DATABASE_URI environment variable. This allows you to keep the database file outside the portable archive and skip step 2.
For example, setting DATABASE_URI to:
`sqlite+aiosqlite:///C:/Users/alex/visionatrix.db`
will direct Visionatrix to use the C:\Users\alex\visionatrix.db file.
Starting with Visionatrix version 2, we provide official Docker images along with a pre-configured docker-compose.yml file, making deployment faster and easier. The file is located at the root of the Visionatrix repository.
-
visionatrix_nvidia: Visionatrix with
NVIDIA GPUsupport. -
visionatrix_amd: Visionatrix with
AMD GPUsupport. -
visionatrix_cpu: Visionatrix running on
CPUonly. - pgsql: A PostgreSQL 17 container for the database.
-
For NVIDIA GPU support:
docker compose up -d visionatrix_nvidia
-
For AMD GPU support:
docker compose up -d visionatrix_amd
-
For CPU mode:
docker compose up -d visionatrix_cpu
By default, visionatrix-data directory will be created in the current directory in the host and used for the models, user, input and output files.
You can easily customize the configuration by modifying environment variables or volume mounts in the docker-compose.yml file.
If you have any questions or need assistance, we're here to help! Feel free to start a discussion or explore our resources:
-
Documentation
- Available Flows
- Admin Manual
- Flows Developing
- Common Information
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