pydantic VS mathesar

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.

Congratulations on launching, it's nice to see more open source products in this area (I work on https://mathesar.org/). Feel free to reach out if you'd like to talk and compare notes.

This is what we're trying to do with [Mathesar](https://github.com/centerofci/mathesar). We probably don't meet your needs yet because we don't support real-time concurrent editing, but we're actively working on the project and it is early days.

I'm an engineer on the Mathesar core team and I'd just like to clarify that Mathesar does support grouping to some extent. Here is a screenshot[1] that demonstrates the grouping functionality. Grouping levels are unlimited. You can play with this functionality on our live demo[2]. It's worth mentioning that Mathesar does not yet have the capability to expand and collapse groups, but that feature is planned[3].

Best of luck building Visual DB! Nice to see more innovation in this space!

[1]: https://mathesar.org/assets/crm-table-zoomed.png

[2]: https://demo.mathesar.org/

[3]: https://github.com/centerofci/mathesar/issues/475

I’m not sure if it’s okay to plug my project, but I work on Mathesar (https://github.com/centerofci/mathesar) which can be used as a Postgres GUI. We’re putting a lot of product/design effort into making it nice to use for non technical users.

Otherwise, I just use the command line.

We're trying to do this with Mathesar: https://github.com/centerofci/mathesar. Some feedback would be great!

We're trying to build a community driven project in this space - https://github.com/centerofci/mathesar. We just did our alpha release a couple of months ago.

I'm philosophically opposed to open core (Mathesar is run out of a non-profit), but I can see why other projects do it – finding funding for a big project like this is difficult without VCs (who expect returns).

I'm working on https://mathesar.org/ – it's an open source database solution built on Postgres, you can import data, connect to multiple databases, edit data and build reports. It can't connect to non-Postgres databases, so it may not work for you.

We've just released Mathesar v0.1.2. Major new features are support for multiple databases in the UI and more options for installing Mathesar. We also made a bunch of smaller UX improvements and fixed a few bugs. Our full release notes are here: https://github.com/centerofci/mathesar/releases/tag/0.1.2

We did this for our open source project, Mathesar (https://github.com/centerofci/mathesar), which also uses Django. It's a lot of work. You can take a look at our code if it's helpful.