NP Classifier

We typically will deploy this locally. To bring everything up, you need docker and docker-compose.

Local Server

Downloading NP Classifier Models

cd Classifier/models_folder/models
sh ./get_models.sh

NOTE: Make sure you have python installed and tensorflow version 2.3.0 installed to convert the keras models into HDF5 TF2 models.

Building Dockerized Server

If you didn't do it already, you will need a network.

docker network create nginx-net

make server-compose

Checking Model Metadata

We pass through tensorflow serving at this url:

/model/metadata

If the model input names change, then we need to change it in the code

Checking input/output layer names.

Input layers' names should be "input_2048" and "input_4096"

Output layer's name should be "output"

APIs

Classify programmatically

/classify?smiles=<>

You can also provide cached flag to the params to get the cached version so make it faster

License

The license as included for the software is MIT. Additionally, all data, models, and ontology are licensed as CC0.

Privacy

We try our best to balance privacy and understand how users are using our tool. As such, we keep in our logs which structures were classified but not which users queried the structure.