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Every author of an inference provider is free to choose their own API. The selected API design can follow existing conventions or choose their own. A formal schema would greatly help in establishing and following conventions.
Moreover every API user would prefer to use strongly-typed code which follows their language's conventions rather than composing and reading frames from raw bytes. Even with our current use of the Dict helper, we still prefer using the C++ schema definition when we write examples, demos, and tests. A schema can be used to generate code.
Documenting an API can be hard and cumbersome. There is a risk in divergence between the implementation and documentation. A schema can be used to generate the docs, and if it's also used to generate the code, the risk of divergence becomes zero.
We need to invest in schemas: codegen, documentation generation, tooling
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Every author of an inference provider is free to choose their own API. The selected API design can follow existing conventions or choose their own. A formal schema would greatly help in establishing and following conventions.
Moreover every API user would prefer to use strongly-typed code which follows their language's conventions rather than composing and reading frames from raw bytes. Even with our current use of the
Dict
helper, we still prefer using the C++ schema definition when we write examples, demos, and tests. A schema can be used to generate code.Documenting an API can be hard and cumbersome. There is a risk in divergence between the implementation and documentation. A schema can be used to generate the docs, and if it's also used to generate the code, the risk of divergence becomes zero.
We need to invest in schemas: codegen, documentation generation, tooling
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