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//! Clark Hash: stateless sparse-JL quantization for neural embeddings.
//!
//! The library centers around [`ClarkHash`], a deterministic codec that projects an
//! input vector into a low-dimensional sparse signed sketch and then applies a fixed
//! scalar quantizer. The resulting code can be scored asymmetrically against
//! floating-point queries while staying fully online and fully stateless.
//!
//! The original codec and configuration names, [`SQuaJL`] and [`SQuaJLConfig`], remain
//! public for compatibility with earlier experiments and papers.
//!
//! See the crate-level `README.md` for motivation, design notes, and usage examples.
/// Configuration types and similarity-mode selection.
/// Error types returned by the crate.
/// A simple exact-scan index over quantized vectors.
/// Encoded database vectors and prepared query sketches.
/// The core stateless codec implementation.
/// Optional local text-embedding integration powered by `fastembed`.
pub use ;
pub use ;
pub use FastEmbedQuantizer;
pub use ;
pub use ;
pub use SQuaJL;
/// Package-level name for the stateless sparse-JL codec.
pub type ClarkHash = SQuaJL;
/// Package-level name for the codec configuration.
pub type ClarkHashConfig = SQuaJLConfig;
/// Package-level name for errors returned by this crate.
pub type ClarkHashError = SQuaJLError;