|screenshot 1|screenshot 2|
|-|-|
|![Screenshot from 2022-02-01 12-19-30](https://user-images.githubusercontent.com/20104026/151968818-df3521d8-ea04-48a1-a21b-8cbb54f84bea.png)|![Screenshot from 2022-02-01 12-24-48](https://user-images.githubusercontent.com/20104026/151970146-2895a808-26af-4761-b087-57314b59a3b3.png)

# 💡 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](https://paulbricman.com/reflections/sharing-searches) with peers
- ranking items by Anki-like activation, so as to promote serendipity


## installation

#### docker

After installing docker and docker-compose, run:

```
curl -fsS https://raw.githubusercontent.com/paulbricman/conceptarium/main/docker-compose.yml | docker-compose -f - up -d
```

#### from 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
```

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](https://github.com/ljk53/pytorch-rpi).

## 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` if you ran from source, `backend.docker` if you used docker), and your desired token. Remember your token, as you'll have to use it to authenticate in future sessions.