metadata

title: AI Comic Factory
emoji: 👩‍🎨
colorFrom: red
colorTo: yellow
sdk: docker
pinned: true
app_port: 3000

AI Comic Factory

Running the project at home

First, I would like to highlight that everything is open-source (see here, here, here, here).

However the project isn't a monolithic Space that can be duplicated and ran immediately: it requires various components to run for the frontend, backend, LLM, SDXL etc.

If you try to duplicate the project, you will see it requires some variables:

LLM_ENGINE: can be either "INFERENCE_API" or "INFERENCE_ENDPOINT"
HF_API_TOKEN: necessary if you decide to use an inference api model or a custom inference endpoint
HF_INFERENCE_ENDPOINT_URL: necessary if you decide to use a custom inference endpoint
RENDERING_ENGINE: can only be "VIDEOCHAIN" for now, unless you code your custom solution
VIDEOCHAIN_API_URL: url to the VideoChain API server
VIDEOCHAIN_API_TOKEN: secret token to access the VideoChain API server

Please read the .env default config file for more informations. To customise a variable locally, you should create a .env.local (do not commit this file as it will contain your secrets).

-> If you intend to run it with local, cloud-hosted and/or proprietary models you are going to need to code 👨‍💻.

The LLM API (Large Language Model)

Currently the AI Comic Factory uses Llama-2 70b through an Inference Endpoint.

You have three options:

Option 1: Use an Inference API model

This is a new option added recently, where you can use one of the models from the Hugging Face Hub. By default we suggest to use CodeLlama.

To activate it, create a .env.local configuration file:

LLM_ENGINE="INFERENCE_API"

HF_API_TOKEN="Your Hugging Face token"

# codellama/CodeLlama-7b-hf" is used by default, but you can change this
# note: You should use a model able to generate JSON responses
HF_INFERENCE_API_MODEL="codellama/CodeLlama-7b-hf"

Option 2: Use an Inference Endpoint URL

If your would like to run the AI Comic Factory on a private LLM running on the Hugging Face Inference Endpoint service, create a .env.local configuration file:

LLM_ENGINE="INFERENCE_ENDPOINT"

HF_API_TOKEN="Your Hugging Face token"

HF_INFERENCE_ENDPOINT_URL="path to your inference endpoint url"

To run this kind of LLM locally, you can use TGI (Please read this post for more information about the licensing).

Option 3: Fork and modify the code to use a different LLM system

Another option could be to disable the LLM completely and replace it with another LLM protocol and/or provider (eg. OpenAI, Replicate), or a human-generated story instead (by returning mock or static data).

Notes

It is possible that I modify the AI Comic Factory to make it easier in the future (eg. add support for OpenAI or Replicate)

The Rendering API

This API is used to generate the panel images. This is an API I created for my various projects at Hugging Face.

I haven't written documentation for it yet, but basically it is "just a wrapper ™" around other existing APIs:

The hysts/SD-XL Space by @hysts
And other APIs for making videos, adding audio etc.. but you won't need them for the AI Comic Factory

Option 1: Deploy VideoChain yourself

You will have to clone the source-code

Unfortunately, I haven't had the time to write the documentation for VideoChain yet. (When I do I will update this document to point to the VideoChain's README)

Option 2: Use another SDXL API

If you fork the project you will be able to modify the code to use the Stable Diffusion technology of your choice (local, open-source, your custom HF Space etc)

Notes

It is possible that I modify the AI Comic Factory to make it easier in the future (eg. add support for Replicate)