Codecs

Codecs are used to encapsulate the logic required to encode / decode payloads following the Open Inference Protocol into high-level Python types. You can read more about the high-level concepts behind codecs in thesection of the docs, as well as how to use them.

Base Codecs

All the codecs within MLServer extend from either the {class}InputCodec <mlserver.codecs.base.InputCodec> or the {class}RequestCodec <mlserver.codecs.base.RequestCodec> base classes. These define the interface to deal with input (outputs) and request (responses) respectively.

.. automodule:: mlserver.codecs
   :members: InputCodec, RequestCodec

Built-in Codecs

The mlserver package will include a set of built-in codecs to cover common conversions. You can learn more about these in thesection of the docs.

.. automodule:: mlserver.codecs
   :members: NumpyCodec, NumpyRequestCodec, StringCodec, StringRequestCodec, Base64Codec, DatetimeCodec, PandasCodec