While semantic search shine at various tasks including advanced search engine and recommender systems, it did not shine that much on coding task so far appart from benchmarks available in papers. We think standard semantic code search tools lack of advanced filtering features. A key element to code search is to be able to reduce "search space", i.e reduce the set of likely candidates given the intent of the user or the coding agent. We think semantic search alone is not enough and needs to be paired with advanced filters such as GREP filters to succeed.
Blog introducing late-interaction models with max-similarity scoring function visualization. pylate-rs is a rust crate providing python and wasm bindings.
Very interesting work! Starred the project. Would love to see such features integrated into the compiler itself
Anyway, fully agree with you on the complementarity of ML and Rust
I created my personnal search engine to index and retrieve content I like. I like the idea of keeping track of content you like without too much effort.
Author here, I like the idea to have a public and personal search-engine. I'd love to deep dive in some people bookmarks such as expert in NLP field in order to get clue / a point of view on problem I want to solve but those informations are not available most of the time
