title | emoji | colorFrom | colorTo | sdk | pinned | app_port |
---|---|---|---|---|---|---|
AI Comic Factory |
👩🎨 |
red |
yellow |
docker |
true |
3000 |
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 and open the .env
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 endpointHF_INFERENCE_ENDPOINT_URL
: necessary if you decide to use a custom inference endpointRENDERING_ENGINE
: can only be "VIDEOCHAIN" or "REPLICATE" for now, unless you code your custom solutionVIDEOCHAIN_API_URL
: url to the VideoChain API serverVIDEOCHAIN_API_TOKEN
: secret token to access the VideoChain API serverREPLICATE_API_TOKEN
: in case you want to use Replicate.comREPLICATE_API_MODEL
: optional, defaults to "stabilityai/sdxl"REPLICATE_API_MODEL_VERSION
: optional, in case you want to change the version
In addition, there are some community sharing variables that you can just ignore. Those variables are not required to run the AI Comic Factory on your own website or computer (they are meant to create a connection with the Hugging Face community, and thus only make sense for official Hugging Face apps):
NEXT_PUBLIC_ENABLE_COMMUNITY_SHARING
: you don't need thisCOMMUNITY_API_URL
: you don't need thisCOMMUNITY_API_TOKEN
: you don't need thisCOMMUNITY_API_ID
: you don't need this
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 👨💻.
Currently the AI Comic Factory uses Llama-2 70b through an Inference Endpoint.
You have three options:
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 34b as it will provide better results than the 7b model.
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,
# so it is storngly suggested to use at least the 34b model
HF_INFERENCE_API_MODEL="codellama/CodeLlama-7b-hf"
If you 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).
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).
It is possible that I modify the AI Comic Factory to make it easier in the future (eg. add support for OpenAI or Replicate)
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
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)
To use Replicate, create a .env.local
configuration file:
RENDERING_ENGINE="REPLICATE"
REPLICATE_API_TOKEN="Your Replicate token"
REPLICATE_API_MODEL="stabilityai/sdxl"
REPLICATE_API_MODEL_VERSION="da77bc59ee60423279fd632efb4795ab731d9e3ca9705ef3341091fb989b7eaf"
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, proprietary, your custom HF Space etc).
It would even be something else, such as Dall-E.