screenshot 1	screenshot 2

💡 Conceptarium

The conceptarium is an experimental personal knowledge base designed to weave AI capabilities into knowledge work. Its main features include:

• powerful multi-modal search across ideas
• sharing microverses of knowledge with peers
• ranking items by Anki-like activation, so as to promote serendipity

Installation

Docker

After installing docker and docker-compose, run:

# install with:
curl -fsS https://raw.githubusercontent.com/paulbricman/conceptarium/main/docker-compose.yml -o docker-compose.yml
mkdir knowledge
docker-compose up -d

# stop with:
docker-compose stop

# update with:
docker-compose stop
docker-compose rm -f
docker-compose pull
docker-compose up -d

Note that you'll have to wait a bit initially for the models to be downloaded in the docker container. Use docker logs <backend container ID> or watch the process's memory for feedback on that. Or just try using it until it via the API or UI until it works (see usage).

Source

After pulling this repo run:

python3 -m pip install -r frontend/requirements.txt
python3 -m pip install -r backend/requirements.txt
streamlit run frontend/main.py

# in a separate session:
cd backend
python3 -m uvicorn main:app --reload

# update by pulling from repo again

Missing dependencies? Please have a look at frontend/Dockerfile and backend/Dockerfile. ARM architecture (e.g. Raspberry Pi)? Remove the torch entries from requirements.txt, and install a custom-built version.

Usage

The web app should then be available at localhost:8501, while the API at localhost:8000 (with docs at localhost:8000/docs). The backend component takes a few minutes to get the ML models at first.

To access your local instance, enter the conceptarium URL (i.e. localhost:8000 if you ran from source, backend.docker:8000 if you used docker), and your desired token. Remember your token, as you'll have to use it to authenticate in future sessions.