- Server VS server-less Or just define the protocol?: Protocol, and up to the vendor to take care of the actual implementation, server or server-less
- Data file type: What type of data we are supporting: e.g. for Delta needs to be parquet, RDBMS? Can modify the Jeffrey init cut below to support multiple data types, depending on the use case.
- Inference: Pass by value should be good enough if it's only for predicting
- Train: not immediate, maybe later in Phase 2
- Do we upload the data to AI (passed by value) and keep the data in the same location (pass by reference)?
- Metadata structure, what kind of JSON schema do we need
- Do we support training or just inference?
- Do we only support a specific model type (ONNX) or arbitrary number of frameworkDo we upload the data to AI and keep the data in the same location and pass by reference?
- Decouple model (asking the model to predict and train) and data (listing, upload, download)
- Tableau version of OBAIC https://tableau.github.io/analytics-extensions-api/docs/ae_example_tabpy.html
- Qlik version of OBAIC: https://github.com/qlik-oss/server-side-extension
- Finalize Logo