This repository contains the biochatter Python package, a generic backend
library for the connection of biomedical applications to conversational AI.
Described in this preprint and used in
ChatGSE, which is being developed at
https://github.com/biocypher/ChatGSE. More to come, so stay tuned!
To use the package, install it from PyPI, for instance using pip (pip install biochatter) or Poetry (poetry add biochatter).
The package has some optional dependencies that can be installed using the
following extras (e.g. pip install biochatter[streamlit]):
streamlit: support for streamlit UI functions (used in ChatGSE)podcast: support for podcast text-to-speech
Due to some incompatibilities of pymilvus with Apple Silicon, we have created
a dev container for this project. To use it, you need to have Docker installed
on your machine. Then, you can run the devcontainer setup as recommended by
VSCode
here
or using Docker directly.
The dev container expects an environment file (there are options, but the basic
one is .devcontainer/local.env) with the following variables:
OPENAI_API_KEY=(sk-...)
DOCKER_COMPOSE=true
DEVCONTAINER=true
To test vector database functionality, you also need to start a Milvus
standalone server. You can do this by running docker-compose up as described
here on the host machine
(not from inside the devcontainer).