osobhandClaude Opus 5.5
b55b24b7ba
Every crate under crates/ now has a README (android, bench, cli, napi and wasm had none), each saying what the crate is, its main types and functions (names checked against the code), its cargo features with defaults and which ones build C (checked with `cargo tree`), and links to the top-level docs. Corrections to the old stubs: - clawhdf5-derive: the derive is `H5Type`, not `HDF5Type`, and it needs clawhdf5-format as a dependency. - clawhdf5-filters: deflate backends only, and no library crate depends on it; the filter pipeline and every other codec are in -format. - clawhdf5-gpu: vector distance compute, not I/O; not used by HDF5Memory::search. - clawhdf5-io: MpiVol is root-read + broadcast, not collective MPI-IO. - clawhdf5-ann: from_hdf5/search(q, k) did not exist; load_from_hdf5 and search(q, k, ef). - clawhdf5-accel: checksum::crc32_simd did not exist; the SSE4 and wasm backends are reported but run the scalar kernels. - clawhdf5-gpu: the old example called l2_distances, which does not exist (l2_search). - clawhdf5-agent: it described a "vector store" with "GPU acceleration"; it now covers HDF5Memory, search options, WAL, signing, the graph. - crates.io/docs.rs badges removed and `cargo install <crate>` replaced: nothing is published; depend on git. - fuzz: the opt-in CLAWHDF5_FUZZ_SECONDS smoke run in ci-test.sh. - tools: the FileEditor interop tests that live in this crate. - remote, py: license, other front ends, limits, File.mode/flush/chunks. The Rust examples of the facade, format, filters, accel, ann, derive and agent READMEs were compiled and run as tests (netcdf4, gpu and remote compiled only) in a scratch crate; the CLI example was run. Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
2.6 KiB
2.6 KiB
clawhdf5-ann
An HNSW (Hierarchical Navigable Small World) approximate nearest-neighbour
index in pure Rust, with cosine or L2 distance, optional int8 storage of
the vectors, deletions, and persistence as an HDF5 file. It is the vector
stage of clawhdf5-agent's search (the
agent's hnsw feature, on by default); distances run on
clawhdf5-accel's SIMD kernels.
Neighbours are chosen with the HNSW paper's diversity heuristic, not plain closest-M (which capped recall on clustered data at 0.31 recall@10 at 100K vectors).
Not on crates.io yet; depend on it from git:
[dependencies]
clawhdf5-ann = { git = "https://git.redclaw.dev/quantumclaw/clawhdf5" }
Usage
use clawhdf5_ann::{DistanceMetric, HnswIndex, Storage};
let vectors: Vec<Vec<f32>> = (0..500)
.map(|i| (0..16).map(|j| ((i * 31 + j * 7) % 97) as f32 / 97.0).collect())
.collect();
// m = 16 connections per node, ef_construction = 200
let mut index = HnswIndex::build_with(&vectors, 16, 200, DistanceMetric::Cosine, Storage::Int8);
let hits = index.search(&vectors[42], 10, 64); // (id, distance), closest first; ef >= k
assert!(hits[0].1 < 1e-3); // vector 42 itself (or an identical one)
let id = index.insert(vec![0.5; 16]);
index.mark_deleted(id);
// Persist as HDF5 (a self-contained file: graph and vectors) and load it back
let bytes = index.to_hdf5_bytes().unwrap();
let loaded = HnswIndex::load_from_hdf5(&bytes).unwrap();
assert_eq!(loaded.len(), index.len());
HnswIndex::build(L2),build_with_metric,build_with(metric and storage);new/new_withplusinsertfor an index built incrementally.Storage::Int8keeps each vector asi8, a quarter of the memory; it applies toCosineonly (an L2 index keepsFloat32). Distances are then approximate, so a caller that needs exact ranking re-scores the candidates, as the agent does.mark_deleted,is_deleted,deleted_count,active_len,compact(returns the old-to-new id map).save_to_hdf5(&mut writer)/to_hdf5_bytes/load_from_hdf5store the whole index;graph_to_bytes/from_graph_bytesstore only the graph (with a CRC32) for a caller that keeps the vectors elsewhere — the agent's<store>.h5.annsidecar.
Features
| Feature | Default | What | Builds C |
|---|---|---|---|
parallel |
no | build the graph on a rayon pool; the graph is identical with or without it | no |
Recall and speed against exact search, for the index alone and in the
agent: BENCHMARKS.md, measured with
cargo run --release -p clawhdf5-bench --bin search_harness.
License
MIT