A manual macOS job that builds GUFI and exercises its vector stack - #337
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Run by hand rather than on every push, since the AI dependency path compiles llama.cpp and takes far longer than the test suite. It builds GUFI at a chosen ref on a clean macOS runner, indexes a small tree and queries it, then does exactly what the Studio does with the vector extensions: load the embedding model, embed a phrase with lembed, store vectors in a vec0 table, and take the nearest by distance. Finally it points the built server at that index to confirm it finds the binaries. What this answers that a local build cannot is whether GUFI works on a machine nobody has configured, which is the state a new Mac user is in.
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Manual (
workflow_dispatch) with inputs for the GUFI ref and whether to build the AI dependencies, since that path compiles llama.cpp and takes far longer than the test suite.It builds GUFI on a clean
macos-15runner throughindexer/setup_gufi.sh, indexes a small tree and queries it withgufi_query, then exercises the vector stack exactly as the Studio does: load the model, embed a phrase withlembed, store vectors in avec0table, and take the nearest by distance. It ends by pointing the built server at that index to confirm binary discovery.The value is independent verification on a machine nobody has configured, which is the state a new Mac user is in, and it gives us a way to check a GUFI branch on macOS without owning a Mac.