feature: custom ai executor

[YousefED]

This adds support for a custom AI executor instead of always relying on the Vercel AI SDK to execute requests.

See this example code for usage.

You can test this using npm i https://pkg.pr.new/TypeCellOS/BlockNote/@blocknote/xl-ai@1766

TODO:

• Implement an easier way to create LLMResponse from a custom streaming response (for now, use LLMResponse.fromArray for testing
• We could move "model", "stream", "maxRetries" etc. to become responsibilities of the executor

Alternatives

This PR basically kind of lets you "opt out" from using the AI SDK as layer to call underlying LLMs.

We can also explore:
a) (lean in on AI SDK) making it easy to implement a custom Model / Provider which you can then use as "executor". (i.e.: we consider the Model to be the point that defines how LLMs are called
b) (lean "out" of AI SDK on client side): instead of using the AI SDK heavily on the client and a lightweight proxy on the server, we could follow their default design more closely and recommend users to expose REST endpoints that can then in turn use the AI SDK

[vercel]

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Name	Status	Preview	Updated (UTC)
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commit: 2040f86

[nperez0111]

I would prefer for the client to do less work, and given that backends will have a lot more context than a frontend would, I'd personally ease more toward moving the work into the backend & making that easier.

Also worth documenting what the format should look like over the wire even if only examples