Add explicit codable implementation to ChatMessage and new OpenAIEndpointModelType #107
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Fixes adamrushy#100 `sendChat is failing because ChatMessage has extra property`
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@adamrushy any idea when you may get the opportunity to review and merge this? 😄 |
The current model enum and methods that have models as parameters could easily cause errors as any model could be chosen for any of those methods. By adding the new `OpenAIEndpointModel` type that corresponds to the compatibility list in the OpenAI docs, it’s much easier to select the fitting model. The new type does contain duplicate model strings, which is intended to make it easier to maintain. Backward compatibility is assured by marking the previous methods as deprecated. https://platform.openai.com/docs/models/model-endpoint-compatibility
marcoboerner
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@marcoboerner I may be missing something, but I don't think this is needed. Specifying CodingKeys should be sufficient. I have a fork with a commit here that fixes this issue.
(Same goes for encode() method below.)
For what it's worth I'll open up a PR with the "one line" solution that only solves the reported problem (maybe that'll get merged sooner?).
That said the other changes you made are also useful...
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...nevermind, I won't open a PR because I see there are several already. :)
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Fixes #100
Add explicit codable implementation to ChatMessagewithout removing theIdentifiableconformance by implementing an explicit codable implementation that ignores theidproperty when encoding, and creates a new UUID when decoding.This should fix the regular chat and streaming chat as both have not been working with the encoded
id.I've also added a new
OpenAIEndpointModelTypewith the currently available OpenAI models, to replace theOpenAIModelType. The currentOpenAIModelTypemodel enum and methods that have models as parameters could easily cause errors as any model could be chosen for any of those methods. By adding the newOpenAIEndpointModeltype that corresponds to the compatibility list in the OpenAI docs, it’s much easier to select the fitting model.The new type does contain duplicate model strings, which is intended to make it easier to maintain.
Backward compatibility is assured by marking the previous methods as deprecated. and using the old methods as wrappers around the new methods.