Considerations for the Embedding Service

• Available Embedding Models
  A number of embedding models are available to be used with the Private AI Services Container, including some that are shipped with the container. There are also pre-built models available for download as well as models that are known to work with the container but must be built using Oracle Machine Learning for Python (OML4Py) Client 2.1.
• Container Input Validation
  Inputs to the Private AI Services Container can come from a variety of sources, each of which are validated using different methods.
• Container Automatic Image Conversion
  The request header x-convert-images can be used to instruct the container to examine the format of input images and convert them as necessary. The JPEG format is supported by default.
• Multi-threaded Scaling
  The ONNX Runtime enables multi-threading and can benefit from multiple CPU cores.