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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

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).

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.

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.