pydantic VS reason

First, note the method prefix_allowed_tokens_fn. This method applies a Pydantic model to constrain/guide how the LLM generates tokens. Next, see how that constrain can be applied to txtai's LLM pipeline.

utype is a concise alternative of pydantic with simplified parameters and usages, supporting both sync/async functions and generators parsing, and capable of using native logic operators to define logical types like AND/OR/NOT, also provides custom type parsing by register mechanism that supports libraries like pydantic, attrs and dataclasses

I like some of the changes from v1 to v2. But then you have something like this [0] removed from the library without proper documentation or replacement, resulting in ugly workarounds in the link that wont' work properly.

[0]: https://github.com/pydantic/pydantic/discussions/6337

The easiest implementation I found was to use a PyDantic class for my target schema — and use that as a parameter for the method call to “ChatCompletion.create()”. Here’s a fragment of the GinAI Python classes used.

Also, FastStream uses Pydantic to parse input JSON-encoded data into Python objects, making it easy to work with structured data in your applications, so you can serialize your input messages just using type annotations.

Pydantic Validation: Leverage Pydantic's validation capabilities to serialize and validate incoming messages

Not sure if it is exactly related, but there is an open issue on Github for that exact message.

Well the performance increase is so huge because pydantic1 is really really slow. And for using rust, I'd have expected more tbh…

I've been benchmarking pydantic v2 against typedload (which I write) and despite the rust, it still manages to be slower than pure python in some benchmarks.

The ones on the website are still about comparing to v1 because v2 was not out yet at the time of the last release.

pydantic's author will refuse to benchmark any library that is faster (https://github.com/pydantic/pydantic/pull/3264 https://github.com/pydantic/pydantic/pull/1525 https://github.com/pydantic/pydantic/pull/1810) and keep boasting about amazing performances.

On pypy, v2 beta was really really really slow.

Hey HN, at Ahrefs we have been working on an online book that hopefully helps React developers get up and running with Melange, an OCaml to JavaScript compiler. You can read more about Melange here: https://melange.re/.

There are still a few chapters that we'd like to add before considering it "complete", but it might be already helpful for some folks out there, that's why we decided to publish it early.

The book uses Reason syntax to implement React components using ReasonReact components. You can read more about both in:

https://reasonml.github.io/

ReScript is "Fast, Simple, Fully Typed JavaScript from the Future". What that means is that ReScript has a lightning fast compiler, an easy to learn JS like syntax, strong static types, with amazing features like pattern matching and variant types. Until 2020 it was called "BuckleScript" and is closely related to ReasonML.

This tracks with how I've seen "normal" languages converge on similar, flawed imitations of better type systems through tools and repurposed syntax. Thank you for confirming.

Do you have any recommendations or warnings regarding general languages which reach in the opposite direction? Reason[1] and F#[2] are both examples: they attach pre-existing ecosystems and compile-for-$PLATFORM tools to OCaml-like typing.

OCaml itself is also intriguing for personal projects. However, I'm worried the "GPL" in its standard library's LGPL license might scare people despite both the linking exception and Jane Street's MIT alternative.

1. https://reasonml.github.io/

ReasonML purely as a syntax layer on top of OCaml is still being updated and released[1]. Incidentally, I'm one of the maintainers of that project too :-)

With this Melange release, we're hoping to somewhat revive ReasonML and channel some folks back to the community from the perspective of a vertically integrated platform that has seen major investment in the past few years.

[1]: https://github.com/reasonml/reason

Why not use https://reasonml.github.io/ instead? Or just use Typescript?

Quieted down, but I depend on projects with worst graphs:

https://github.com/reasonml/reason/graphs/contributors

There is also reasonml for Web development.