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The pack object

A pack represents a list of grouped prompts, as well as the fine-tune to be created from the training images.


  1. Test new prompts, ideas and themes on a bulk of models quickly to assure consistent high-quality results.
  2. Move fast from the creative process of creating prompts to the deployment of new themes in production.
  3. Avoid mismatch between hard-coded JSONs and the actual prompts.
  4. Decouple the creative process from your code and avoid mirroring inference API details in your codebase.
  5. Run user tests in production for new prompts and quickly iterate.
  6. Aggregate likes for prompts to improve the quality of the generated images and tighten the feedback loop.
  7. Sort packs by aggregated likes to present the best packs to the user.

Example user flow

  1. GET /packs Display a list of packs to the user. See docs
  2. User selects a pack, a class name (man/woman) and training images
  3. Call POST /p/:id/tunes with title, (training) images, and class name - to create a new fine-tune model using a pack. See docs
  4. GET /tunes/:id/prompts to get a list of prompts and their status
  5. POST /prompts/:id/likes to send feedback to the API. See docs
  6. Sort prompts by likes
  7. Present packs sorted by aggregated likes

Getting started

  1. Create your first pack from the GUI packs page.
  2. Assign prompts to the pack from the prompts tab.