vst-rs VS MeiliSearch

https://github.com/RustAudio/vst-rs this what you mean?

I hate to "uhhmm ackchyually" this, but unless you need native VST3 support* (which uses the C++ ABI directly) other options are available, a favourite of mine would be Rust!

VST2 bindings exist (https://github.com/RustAudio/vst-rs) but the VST3 and AU situation is rougher around the edges. There is work being done on abstracting over different plugin standards and easing parameter handling, notably https://github.com/wrl/baseplug and https://github.com/robbert-vdh/nih-plug, but nothing completely stable yet.

One limitation that they mention is "Only one GFX and one LFX APO can be registered for an output device and only one LFX APO can be registered for an input device." which could be a problem for people who are already using one like Equalizer APO. What you could do is make a VST version of your limiter using vst-rs and use Equalizer APO to handle the APO part.

I agree with the first half. For the second half, I think for beginners, the examples are very important. From this perspective, many Rust projects comes with examples:

https://github.com/RustAudio/vst-rs

Once following the readme, it is very easy to get it work in your own machine. Then beginners can edit things while learning new stuffs with books or online resources.

Rust audio has also got a very helpful Discord community where beginners can always ask questions.

For the GUI part, I am not an expert, but there are more and more Rust GUI libraries (egui, iced, druid, rui): among them, egui-rs and iced-rs can all be used for VST. Still, there are some examples to get started with.

https://youtu.be/yFKH9ou_XyQ

If you want your own vst (with your name on the author and you can sell),you can start with vst-rs:

https://github.com/RustAudio/vst-rs

Wanna some GUI, here is a template:

When I came across the vst-rs, I realised that I could try out writing an audio plugin. Since I was already familiar with FM synthesis from Elektron Monomachine and FM8, I decided to go with it. It has worked out pretty well.

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