An incremental build cache for Rust on GHA
Hi HN, I'm Kyle, the creator of Clipper, a container registry with 7x faster builds via lazy pulls and cache mount exports. In the process of implementing cache mount exports I ended up with a FUSE mounted filesystem backed by a remote content defined store. I went looking for fun things to do with it and found that there's not really a good way to keep Rust incremental build state around on ephemeral runners, so here we are. Rust generally uses https://github.com/mozilla/sccache for caching, but sccache disables itself when incremental compilation is enabled…
What it does
In the maker’s words, at launch
Hi HN, I'm Kyle, the creator of Clipper, a container registry with 7x faster builds via lazy pulls and cache mount exports. In the process of implementing cache mount exports I ended up with a FUSE mounted filesystem backed by a remote content defined store. I went looking for fun things to do with it and found that there's not really a good way to keep Rust incremental build state around on ephemeral runners, so here we are. Rust generally uses https://github.com/mozilla/sccache for caching, but sccache disables itself when incremental compilation is enabled (https://github.com/mozilla/sccache/issues/236) and it isn't on Mozilla's roadmap to fix. It unfortunately doesn't really work on stable Rust (which uses mtime to decide when files have changed, rather than file contents), but maybe once https://github.com/rust-lang/cargo/issues/14136 is stable it will be useful to someone.
Does the same job
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Have a look at my semantic caching project! It's built to easily integrate in existing LLM workflows, you can use it as a proxy where the cache forwards missed requests without modification to a specified upstream, automatically updating it's cache with the response. You can also use it as a cache-aside cache with a provided python library. It works by computing embedding vectors of input queries, and matches them to seen query + response pairs using a vector store. Everything is in-memory, so it should be blazing fast :)
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