rustc_codegen_gcc VS MeiliSearch

Alternatively, there's another initiative called codegen_gcc which is about using GCC as a backend for the rustc compiler. It's (much) more advanced in Rust support, but I am not sure how easy it would be to use a modified libgccjit from there.

In addition to what others have said about platform support, Rust is also on its way to gaining more platform support through rustc_codegen_gcc, the GCC codegen backend for rustc, as an alternative to the LLVM backend. That means many of the platforms GCC supports will suddenly become available with Rust.

Yeah, rustc_codegen_gcc is a GCC backend for rustc, and its making a lot of good regular progress.

gcc-rs is one of two projects for bringing Rust to gcc. gcc-rs is the more ambitious of the two, with an entirely new frontend. There is also rustc_codegen_gcc (https://github.com/rust-lang/rustc_codegen_gcc) that keeps the rustc frontend, and only swaps out LLVM for GCC at the codegen stage.

Fixing unwinding in release mode is still ungoing. I could use some help here, so anyone with some understanding of unwinding, landing pads or GCC, please come on this issue to discuss this.

Additionally, there is gcc codegen for rustc (https://github.com/rust-lang/rustc_codegen_gcc), which is not a compiler per se, but an alternative code generator, with more architectures supported and other nice things. It's also coming along, but there's still a lot of work to do there too. There's also Cranelift codegen (https://github.com/bjorn3/rustc_codegen_cranelift), which is designed to make debug builds faster, but this is not as exciting/useful as the other 2.

Good idea. I added the tag "help wanted" to the issue.

Also, there are indeed ABI issues, e.g. for 128-bit integers and NaN.

I'm excited about both the backend & the frontend.

There is also a project for rustc to use GCC instead of LLVM for codegen.

https://github.com/rust-lang/rustc_codegen_gcc

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