redis-rs VS MeiliSearch

The goto Redis client for Rust is called redis-rs. It has over 3k stars on Github. but I found it very annoying to use because I quickly found out that if you want to set any value you had to get a mutable reference to the underlying client. Which meant great pain to store Redis client in the global scope. People who do not know what a mutable reference is consider the let keyword in JavaScript. you can mutate or change a variable that is initiated with let.

staticpi, is a websocket forwarding service. Basically, it enables one to keep a Raspberry pi, or any computer, “connected”, in order to send and receive messages to and from any client, without having to deal with a static IP address, open ports on your router, or similar. Built in Rust, using axum, which in turn uses tungestine-rs for the websocket connections, tokio, sqlx, redis-rs and others.

redis (use streams and pubsub)

Are you addressing the long-standing issue that the redis client has related to dropped connections?

I switched to LALRPOP for gluon but I still use combine in https://github.com/mitsuhiko/redis-rs and some other projects which need to parse "protocols" (less need for good error messages/error recovery and more need for speed).

The project is implemented with MongoDB Rust driver and redis-rs crate.

redis-rs, a Rust library for Redis with both high and low-level APIs

I think the redis crate was a well-organized API library. It's still sometimes hard to know the right things to make public and I think they nailed it.

We have been using it before it got merged in redis-rs (we upvoted the PR here https://github.com/mitsuhiko/redis-rs/pull/319 a while back ;-))

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