amqp VS pydantic

Basically this code, connects to our rabbitmQ using the streadway/amqp package which is the golang standard library for communicating with rabbitmQ, next we declare a unique channel to enable us pass across message to a specific queue. Then we call the Consume function which takes in a parameter of *amqp.Channel which is the channel we created previously.

For rabbitmq I used -> https://github.com/streadway/amqp which is deprecated now for -> https://github.com/rabbitmq/amqp091-go

"github.com/streadway/amqp"

I’d also recommend looking into learning Go. I’ve been using this library and it’s great.

We're currently using streadway/amqp as RabbitMQ client library. It is well-documented and very stable on the one hand, but on the other hand, it is pretty low-level and leaves up a lot of things to the user. For example, we're in charge of handling the connections and channels ourselves and implemented our very own error handling and reconnection logic as well.

AMQP is a messaging protocol most commonly used by RabbitMQ. As I discuss in the README, the officially sanctioned RabbitMQ driver, streadway/amqp isamazing but does not support automatic redials. If your connection to the message broker goes down, you have to find a way to distribute a new connection to all routines utilizing it. It's always a tedious exercisee, especially when you have multiple projects that work with RabbitMQ.

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.