git clone https://github.com/AstraBert/everything-ai.git
cd everything-ai
Modify the VOLUME
variable in the .env file so that you can mount your local file system into Docker container.
An example could be:
VOLUME="c:/Users/User/:/User/"
This means that now everything that is under "c:/Users/User/" on your local machine is under "/User/" in your Docker container.
docker pull astrabert/everything-ai
docker pull qdrant/qdrant
docker compose up
You will see something like this:
Choose the task among:
- retrieval-text-generation: use
qdrant
backend to build a retrieval-friendly knowledge base, which you can query and tune the response of your model on. You have to pass either a pdf/a bunch of pdfs specified as comma-separated paths or a directory where all the pdfs of interest are stored (DO NOT provide both); you can also specify the language in which the PDF is written, using ISO nomenclature - MULTILINGUAL - agnostic-text-generation: ChatGPT-like text generation (no retrieval architecture), but supports every text-generation model on HF Hub (as long as your hardware supports it!) - MULTILINGUAL
- text-summarization: summarize text and pdfs, supports every text-summarization model on HF Hub - ENGLISH ONLY
- image-generation: stable diffusion, supports every text-to-image model on HF Hub - MULTILINGUAL
- image-generation-pollinations: stable diffusion, use Pollinations AI API; if you choose 'image-generation-pollinations', you do not need to specify anything else apart from the task - MULTILINGUAL
- image-classification: classify an image, supports every image-classification model on HF Hub - ENGLISH ONLY
- image-to-text: describe an image, supports every image-to-text model on HF Hub - ENGLISH ONLY
- image-retrieval-search: search an image database uploading a folder as database input. The folder should have the following structure:
./
├── test/
| ├── label1/
| └── label2/
└── train/
├── label1/
└── label2/
You can query the database starting from your own pictures.
Once everything is ready, you can head over to localhost:7860
and start using your assistant: