Based on repository activity, growth velocity and community engagement.
35
Growth10/30
Activity3/25
Popularity13/25
Trust9/20
1,345
Stars
High
Sentiment
Is this actually an AI agent?
1,345
README.md
title: AI Comic Factory
emoji: 👩🎨
colorFrom: red
colorTo: yellow
sdk: docker
pinned: true
app_port: 3000
disable_embedding: false
short_description: Create your own AI comic with a single prompt
hf_oauth: true
hf_oauth_expiration_minutes: 43200
hf_oauth_scopes: [inference-api]
For more information about my other projects please check linktr.ee/FLNGR.
Funding
If you like the AI Comic Factory, let me know!
I am always creating new spaces and exploring new ideas for demos, meaning I don't have much time to take care of all of them (I wish I could clone myself or ask robots to do it).
If you appreciate the AI Comic Factory and would like to leave a tip, that would be very kind 🫶
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, open the .env you will see it requires some variables.
Provider config:
LLM_ENGINE: can be one of INFERENCE_API, INFERENCE_ENDPOINT, OPENAI, ,
GROQ
ANTHROPIC
RENDERING_ENGINE: can be one of: "INFERENCE_API", "INFERENCE_ENDPOINT", "REPLICATE", "VIDEOCHAIN", "OPENAI" for now, unless you code your custom solution
Auth config:
AUTH_HF_API_TOKEN: if you decide to use Hugging Face for the LLM engine (inference api model or a custom inference endpoint)
AUTH_OPENAI_API_KEY: to use OpenAI for the LLM engine
AUTH_GROQ_API_KEY: to use Groq for the LLM engine
AUTH_ANTHROPIC_API_KEY: to use Anthropic (Claude) for the LLM engine
AUTH_VIDEOCHAIN_API_TOKEN: secret token to access the VideoChain API server
AUTH_REPLICATE_API_TOKEN: in case you want to use Replicate.com
Rendering config:
RENDERING_HF_INFERENCE_ENDPOINT_URL: necessary if you decide to use a custom inference endpoint
RENDERING_REPLICATE_API_MODEL_VERSION: url to the VideoChain API server
RENDERING_HF_INFERENCE_ENDPOINT_URL: optional, default to nothing
RENDERING_HF_INFERENCE_API_BASE_MODEL: optional, defaults to "stabilityai/stable-diffusion-xl-base-1.0"
RENDERING_HF_INFERENCE_API_REFINER_MODEL: optional, defaults to "stabilityai/stable-diffusion-xl-refiner-1.0"
RENDERING_REPLICATE_API_MODEL: optional, defaults to "stabilityai/sdxl"
RENDERING_REPLICATE_API_MODEL_VERSION: optional, in case you want to change the version
Language model config (depending on the LLM engine you decide to use):
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 this
COMMUNITY_API_URL: you don't need this
COMMUNITY_API_TOKEN: you don't need this
COMMUNITY_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 👨💻.
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 zephyr-7b-beta 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"
# "HuggingFaceH4/zephyr-7b-beta" 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="HuggingFaceH4/zephyr-7b-beta"
Option 2: Use an Inference Endpoint URL
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).
Option 3: Use an OpenAI API Key
This is a new option added recently, where you can use OpenAI API with an OpenAI API Key.
To activate it, create a .env.local configuration file:
LLM_ENGINE="OPENAI"
# default openai api base url is: https://api.openai.com/v1
LLM_OPENAI_API_BASE_URL="A custom OpenAI API Base URL if you have some special privileges"
LLM_OPENAI_API_MODEL="gpt-4-turbo"
AUTH_OPENAI_API_KEY="Yourown OpenAI API Key"
Option 4: (new, experimental) use Groq
LLM_ENGINE="GROQ"
LLM_GROQ_API_MODEL="mixtral-8x7b-32768"
AUTH_GROQ_API_KEY="Your own GROQ API Key"
Option 5: (new, experimental) use Anthropic (Claude)
LLM_ENGINE="ANTHROPIC"
LLM_ANTHROPIC_API_MODEL="claude-3-opus-20240229"
AUTH_ANTHROPIC_API_KEY="Your own ANTHROPIC API Key"
Option 6: 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. Claude, 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 Claude 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:
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 Replicate
To use Replicate, create a .env.local configuration file:
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.
Ecosystem Role
Standard MoltPulse indexed agent.
Embed Badge
Show off your Pulse Score in your GitHub README to build trust and rank higher.