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Integrate llama.cpp via Go bindings for local embedding generation. Add sqlite-vec for vector storage and similarity search. Include schema migrations, daemon API changes, and proto updates.
…build - Fix sqlite-vec compilation on Alpine/musl by guarding BSD type aliases with __GLIBC__ - Dockerfile: switch to CPU-only llama.cpp build (Vulkan shaders fail on Alpine) - Dockerfile: add llama-go go.mod copy for replace directive support - CI workflows: add GGUF model caching and download steps - CI workflows: add llama.cpp build steps (CPU-only for tests, GPU for desktop releases) - CI workflows: add LIBRARY_PATH/C_INCLUDE_PATH env vars for CGO linking - ci-setup action: add Vulkan SDK and llama.cpp build per platform
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This will bring to our system a vectorized table and a embedding model to use with seed data. The embeddings would be stored in a new table (it internally generates 5 more shadow tables) and then we could perform semantic search, RAG (with an external llm model) pipelines. We also support GPU acceleration and throttling