Open-source framework for molecular and materials discovery
Open Accelerated Discovery (aka OpenAD) is an open-source framework for molecular and materials discovery developed at IBM Research.
The OpenAD client is accessible from our command line interface, via Jupyter Notebook or our API. It provides unified access to a variety of tools and AI models for literature knowledge extraction, forward and retrosynthesis prediction, generative methods and property inference. OpenAD lets you train models on your own data, to then visualize and filter your candidate molecules.
INSTALLATION GETTING STARTED COMMANDS MODELS SERVICE
PLUGINS AI ASSISTANT DEVELOPERS
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[!IMPORTANT] This will install OpenAD in your global space. If you wish to use a virtual environment (recommended), please refer to the Installation page.
pip install openad
openad
Get started with Jupyter Notebook examples:
init_magic
init_examples
jupyter lab ~/openad_notebooks/Table_of_Contents.ipynb
If you get an error when running init_magic
, you may first need to setup the default iPython profile for magic commands.
ipython profile create
%Openadd
has been added to the magic commands for commands that return data.You’ll need an AWS account and the ability to launch your own EC2 instances and catalog a remote service via URL. Instructions provided.
init_examples
under installation
Stay tuned for detailed instructions on how to build your own OpenAD plugins.
Check the Developers section for guidance with other contributions.