Visionatrix

Visionatrix

AI Media processing using ComfyUI

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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:

Visionatrix

Analysis & Coverage Documentation Models Catalog PythonVersion

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Simplify your AI image generation workflows with Visionatrixβ€”an intuitive interface built on top of ComfyUI

πŸš€ Features

  • πŸ”§ Easy Setup & Updates: Quick setup with simple installation and seamless version updates.
  • πŸ–₯️ Minimalistic UI: Clean, user-friendly interface designed for daily workflow usage.
  • 🌐 Prompt Translation Support: Automatically translate prompts for media generation.
  • πŸ› οΈ Stable Workflows: Versioned and upgradable workflows.
  • πŸ“ˆ Scalability: Run multiple instances with simultaneous task workers for increased productivity.
  • πŸ‘₯ Multi-User Support: Configure for multiple users with ease and integrate different user backends.
  • πŸ€– LLM Integration: Effortlessly incorporate Ollama/Gemini as your LLM for ComfyUI workflows.
  • πŸ”Œ Seamless Integration: Run as a service with backend endpoints for smooth project integration.
  • 😎 LoRA Integration: Easy integrate LoRAs from CivitAI into your flows.
  • 🐳 Docker Compose: Official Docker images and a pre-configured Docker Compose file.

πŸ–ΌοΈ User Interface

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

Visionatrix UI Light Mode

Visionatrix UI Light Mode

πŸ“Ή Click to see a short video demo

Visionatrix Demo

πŸ“₯ Installation

Requirements

  • Python 3.10 or higher. (3.12 recommended)
  • GPU with at least 8 GB of memory (12GB recommended)

Quick Start (Linux/macOS/WSL)

Install prerequisites (Python, Git, etc.)

For Ubuntu 22.04:

sudo apt install wget curl python3-venv python3-pip build-essential git

It is also recommended to install FFMpeg dependencies with:

sudo apt install ffmpeg libsm6 libxext6

Download 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_install from the "scripts" folder.

Using wget:

wget -O easy_install.py https://raw.githubusercontent.com/Visionatrix/Visionatrix/main/scripts/easy_install.py && python3 easy_install.py

Using curl:

curl -o easy_install.py https://raw.githubusercontent.com/Visionatrix/Visionatrix/main/scripts/easy_install.py && python3 easy_install.py

Follow the prompts during installation. In most cases, everything should work smoothly.

To launch Visionatrix from the activated virtual environment:

python -m visionatrix run --ui

Quick Start (Windows)

We 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.

  1. Download: Visit our Releases page.
  2. Get the Portable Archive: Download vix_portable_cuda.7z.
  3. Unpack and Run: Extract the archive and run run_nvidia_gpu.bat or run_cpu.bat.

Manual Installation

For manual installation steps, please refer to our detailed documentation.

βš™οΈ Post-setup Configuration

Paths Configurations

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 folder parameter set.

HuggingFace and CivitAI Tokens

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.

πŸ”„ Updating Visionatrix

For Linux/macOS

Run the easy_install script and select the "Update" option.

python3 easy_install.py

For Windows (Portable Version)

Updating the portable version involves:

  1. Unpacking the new portable version.
  2. Moving visionatrix.db from 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.

Docker Compose

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.

Available Services

  • visionatrix_nvidia: Visionatrix with NVIDIA GPU support.
  • visionatrix_amd: Visionatrix with AMD GPU support.
  • visionatrix_cpu: Visionatrix running on CPU only.
  • pgsql: A PostgreSQL 17 container for the database.

Usage

  • 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.

πŸ“š Documentation and Support

If you have any questions or need assistance, we're here to help! Feel free to start a discussion or explore our resources:

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