[feat] add binary quantization support vector search

[jonathanpv]

Problem Description

Currently it seems like vector search applies cosine similarity search and may be good for other embedding types (binary or int8) support via other search algorithms like hamming_distance

Proposed Solution

We should implement SIMSIMD or this vanilla js function that is discussed here

https://github.com/xenova/transformers.js/issues/681

Alternatives

No response

Additional Context

It will be beneficial for local-first applications to use binary quantized embeddings to reduce the load on memory and support vector search that way. Will be interesting to see stress test on this.

[jonathanpv]

I've seen some of the source code for orama and seems like this can be supported via an extension so I perhaps could tackle this.

However given its a single function + proposal to add types to the API it may be a simple 30 line change.

[micheleriva]

We can make this happen via plugins, but it will likely require running a model on your browser, which will slow down a lot the initialization process. For now, we're providing fast vector/hybrid search support on Orama Cloud (https://cloud.orama.com) and won't be focusing on supporting local models... but this may change in the future. PRs are obviously welcome even as a PoC!