Comment by AaronFriel

Oh, this is quite similar to an online parser I'd written a few years ago[1]. I have some worked examples on how to use it with the now-standard Chat Completions API for LLMs to stream and filter structured outputs (aka JSON). This is the underlying technology for a "Copilot" or "AI" application I worked on in my last role.

Like yours, I'm sure, these incremental or online parser libraries are orders of magnitude faster[2] than alternatives for parsing LLM tool calls for the very simple reason that alternative approaches repeatedly parse the entire concatenated response, which requires buffering the entire payload, repeatedly allocating new objects, and for an N token response, you parse the first token N times! All of the "industry standard" approaches here are quadratic, which is going to scale quite poorly as LLMs generate larger and larger responses to meet application needs, and users want low latency outputs.

One of the most useful features of this approach is filtering LLM tool calls on the server and passing through a subset of the parse events to the client. This makes it relatively easy to put moderation, metadata capture, and other requirements in a single tool call, while still providing low latency streaming UI. It also avoids the problem with many moderation APIs where for cost or speed reasons, one might delegate to a smaller, cheaper model to generate output in a side-channel of the normal output stream. This not only doesn't scale, but it also means the more powerful model is unaware of these requirements, or you end up with a "flash of unapproved content" due to moderation delays, etc.

I found that it was extremely helpful to work at the level of parse events, but recognize that building partial values is also important, so I'm working on something similar in Rust[3], but taking a more holistic view and building more of an "AI SDK" akin to Vercel's, but written in Rust.

[1] https://github.com/aaronfriel/fn-stream

[2] https://github.com/vercel/ai/pull/1883

[3] https://github.com/aaronfriel/jsonmodem

(These are my own opinions, not those of my employer, etc. etc.)