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FableForge

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Generate a picture book from a single prompt using OpenAI function calling, replicate, and Deep Lake

파일 탐색기

최종 버전 다운로드 (.zip)

- .gitignore
- bookcreator.iml
- ArchitectsDaughter.ttf
- KGNeatlyPrinted.ttf
- 1.png
.gitignore
api_utils.py
deep_lake_utils.py
example.pdf
keys.env
LICENSE
main.py
pdf_gen_utils.py
prompts.py
README.md
requirements.txt

# 설치 가이드

1. 코드 내려받기

git clone https://github.com/e-johnstonn/FableForge

깃허브에서 프로젝트 코드 전체를 내 컴퓨터로 내려받습니다.

cd FableForge

방금 내려받은 프로젝트 폴더 안으로 이동합니다.

2. Python

쉬움 추천

사전 준비물

Git GitHub에서 프로젝트 코드를 내려받으려면 필요합니다.
Python 3 설치 시 'Add Python to PATH' 옵션을 꼭 체크하세요 (Windows).

pip install -r requirements.txt

requirements.txt 등에 명시된 파이썬 라이브러리를 설치합니다.

python main.py

파이썬 스크립트(또는 모듈)를 실행합니다.

✅ 에러 메시지 없이 실행되고 터미널에 안내 문구가 출력되면 정상입니다.

// repository documentation

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#  📚 FableForge

## 📄 Description

Generate a picture book from a single prompt using [OpenAI's new function calling](https://openai.com/blog/function-calling-and-other-api-updates) and [Replicate's API](https://replicate.com/) for Stable Diffusion. Store all your generated images and corresponding prompts in [Deep Lake](https://www.activeloop.ai/). Check `example.pdf` or watch the video below for a peek at the output.

Built with [LangChain](https://github.com/hwchase17/langchain), [Deep Lake](https://www.deeplake.ai/), and [Replicate](https://replicate.com/).

## :tv: Demo

https://github.com/e-johnstonn/FableForge/assets/30129211/f9523905-342e-4a33-914d-acd13bd168ec

## 🛠 Install
1. Clone the repository
2. Install requirements.txt
3. Set up your OpenAI and Replicate API keys in `keys.env` - More on this below
4. To save your images and prompts, set up your Activeloop Deep Lake token and dataset path in `keys.env` - More on this below
5. Run `streamlit run main.py` to start the app!

## 🧠 Deep Lake Setup
During the creation of this project, I used Deep Lake to store the generated pictures and prompts in the cloud, as it makes it easy to work with multiple modalities of data (image/text), and displays them in a web UI. To set this up yourself, go to the [Deep Lake website](https://www.activeloop.ai/) and make an account. Once logged in, you can click "Train deep learning models", then "Create dataset", which will guide you through getting an API token and dataset link. Put the token and dataset path in the `keys.env` file and you're good to go.

## 🖼️ Replicate Setup
A Replicate API key is necessary for this app. To get one, go to the [Replicate website](https://replicate.com/) and create an account, then take your API key and put it in `keys.env`. Replicate provides free image generation for new users.

## 📐Architecture

![architecture](https://github.com/e-johnstonn/FableForge/assets/30129211/54dbaa98-5a89-4af4-8ff2-9640a40e773c)

## Improvements
- This demo uses Replicate for image generation due to its ease of use. Connect it to your own Stable Diffusion setup (local or cloud-based) for better results. I recommend some combination of [Diffusers](https://github.com/huggingface/diffusers) and [FastAPI](https://github.com/tiangolo/fastapi) as a starting point.

## License
[MIT License](LICENSE)