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FrameFamily

A modular AI ecosystem focused on frame-based image generation, training, and visualization.

Components

  • Training
    FrameForge
    AI training, dataset preparation, and orchestration within the Frame ecosystem.

  • Viewing
    FrameView
    Visualization, inspection, and analysis of generated frames and training results.

  • Generating
    FrameCreate
    Generative image AI of the Frame ecosystem.
    Work in Progress

FrameCreate

License Node Postgres

FrameCreate is the generative core of the FrameFamily. It gives you a clean, fast image generator with a calm UI, model control, and a clear history of every output.

Work in Progress

Notice: Right now only SDXL-based models are supported. Embeddings are not wired yet.

FrameCreate is built for creative, synthetic, and stylized content. Use on real individuals without consent is explicitly discouraged.

Support and Questions -> Discord
https://discord.gg/TB5DHMNa5J

Why you might like it

  • One place to generate, manage models, and review results.
  • A clear, uncluttered workflow that stays consistent with FrameFamily.
  • Fast queue handling so the machine stays focused on generation.
  • Built to stay fully open and self-hosted.

What you can do

  • Generate images with live preview and stop running jobs when needed.
  • Manage base models, LoRAs, and VAEs in one place.
  • Stack up to three LoRAs and control each strength.
  • Browse history with metadata, reuse prompts, and delete what you do not need.
  • Use preset styles and wildcard prompts to speed up prompting.
  • Set default sampling and live preview settings in System.

Quick Start

./scripts/setup.sh

Open the Web UI at http://localhost:5174. The setup script installs dependencies, prepares the database, runs migrations, and enables systemd services.

What you need: Node.js + npm, Python 3, and Postgres. A GPU is recommended for generation.

First steps

  1. Run the setup command above.
  2. Open the web UI.
  3. Drop your models into the storage/ folders (see below).
  4. Use the Model Manager to rescan.
  5. Generate your first image.

Storage Layout

FrameCreate stores everything it needs under the storage/ folder. You can drop your models there and FrameCreate will find them.

storage/
  models/       # base checkpoints (.safetensors)
  loras/        # LoRA adapters (.safetensors)
  vaes/         # VAE weights
  embeddings/   # text embeddings
  outputs/      # generated images
  thumbnails/   # UI thumbnails
  wildcards/    # prompt wildcard lists (.txt)

Tip: After adding models, open the Model Manager and click Rescan.

Wildcard prompts

Drop a text file into storage/wildcards/. Each line is one option. Use it in your prompt like __colors__.

Example:

  • storage/wildcards/colors.txt
    red
    blue
    green
    
  • Prompt: a __colors__ car
    Each image in a series uses the next line from the file; when the batch exceeds the list, values cycle from the top. Lines without letters are ignored.

Optional: send wildcard_strategy in the job request (sequential, cycle, random) to control selection.

Optional: advanced setup

If you want to change ports, database settings, or runtime options, edit .env. You can start from .env.example.

License

MIT

About

FrameCreate is the 3rd part of the Frame Family and Focus on Image Generation. Text to Image.

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