MeiliSearch VS rust-gpu

We needed to introduce a new service for search. As we settled on using meilisearch, we needed a way to sync updates on our models with the records in meilisearch. We could've continued to use callbacks but we needed something better.

Meilisearch

In this case, a good strategy is to use vector search only when the keyword/prefix search returns none or just a small number of results. A good candidate for this is MeiliSearch. It uses custom ranking rules to provide results as fast as the user can type.

With the VertexAI endpoint set up and tested, our next step is to work with LibreChat. LibreChat is an open-source ChatGPT clone that can integrate with various AI models, including the PaLM 2 models via the VertexAI API. It's built using React, MongoDB, and Meilisearch technologies.

Meilisearch seems like it is the best open source option.

https://www.meilisearch.com/

Starting with v1.3, you can use Meilisearch as a vector store. Meilisearch allows you to store vector embeddings alongside your documents conveniently. You will need to create the vector embeddings using your third-party tool of choice (Hugging Face, OpenAI). As we published the first v1.3 release candidate, you can try out vector search today.

I work at Meilisearch, an open-source search engine built in Rust. 🦀

https://www.meilisearch.com/ https://github.com/meilisearch

Sounds cool, but this requires yet another language to learn[0]. As someone who only has limited knowledge in this space, could someone tell me how comparable is the compute functionality of rust-gpu[1], where I can just write rust?

[0] https://github.com/Hugobros3/shady#language-syntax

[1] https://github.com/EmbarkStudios/rust-gpu

I don't do anything related to data science, but I feel like doing it in Rust would be nice.

You get operator overloading, so you can have ergonomic matrix operations that are typed also. Processing data on the CPU is fast, and crates like https://github.com/EmbarkStudios/rust-gpu make it very ergonomic to leverage the GPU.

I like this library for creating typed coordinate spaces for graphics programming (https://github.com/servo/euclid), I imagine something similar could be done to create refined types for matrices so you don't do matrix multiplication matrices of invalid sizes

Do you mean rust-gpu?

And https://github.com/EmbarkStudios/rust-gpu/tree/main/examples with the wgpu runner (here it runs the compute shader)

I don't know how major they are considered, but Embark Studios is doing quite a bit of Rust in the open source space, most notably (IMO) rust-gpu and kajiya

The examples in the rust-gpu repository are a good place to start

There's another project that's similar that's being used by an actual game company: https://github.com/EmbarkStudios/rust-gpu

They see specific advantages here that would outweigh that negative. It's not my space (I play games, but know next to nothing about graphics programming), but there's at least one argument in the other direction.

Could this approach work for compute shaders (GPGPU) as well? So far, I think https://github.com/EmbarkStudios/rust-gpu is the state of the art in that area, but it adds a specific Rust compiler backend for generating SPIR-V rather than leaving that up to the driver. That seems more complicated than it needs to be... but maybe it has advantages too? Thoughts?

https://github.com/embarkstudios/rust-gpu Allows you to create shaders (kernals) in Rust.

Also Embark Studios (formers DICE people) is doing a lot of work with Rust, all open source like Rust GPU https://github.com/EmbarkStudios/rust-gpu