osobhandClaude Fable 5.1
0ee698accd
open() marked the HNSW index dirty, so the first search of every session
rebuilt it from scratch — 36 s at 100K records with the (better, slower)
heuristic build. First query after open is now 1.7 / 15 / 159 ms at
1K / 10K / 100K; what remains is the one-off keyword index build.
- clawhdf5-ann: HnswIndex::graph_to_bytes / from_graph_bytes serialize the
graph only (levels, tombstones, adjacency as u32, CRC32). The existing HDF5
serializer embeds a full copy of every vector, which would double a store
that already holds them. Loading validates everything — counts, levels vs
layer count, connection limits, every neighbour id and the layer it must
exist on — so a damaged graph, or a hostile one with a valid checksum, is an
error rather than an out-of-bounds walk during search.
- clawhdf5-agent: each checkpoint writes the graph to <store>.h5.ann (synced,
atomic, before the .h5) and records a fresh generation id in /meta. open()
loads the sidecar only if its generation matches that checkpoint; missing,
stale, damaged or mismatched sidecars are ignored and the index rebuilt.
Records appended through WAL replay join the loaded index incrementally; a
replayed Update or Tombstone invalidates it. snapshot() copies it. Only an
index that exactly mirrors the cache is saved; otherwise a stale sidecar is
removed.
- ensure_hnsw_fresh inserts records appended since the last sync instead of
rebuilding, so save_batch no longer marks the whole index dirty.
- CheckpointMeta { wal_applied, ann_generation } with *_with_meta build/write/
read functions; the *_with_mark ones delegate.
- Harness reports the one-off cold index build separately from the first query
after a reopen.
Co-Authored-By: Claude Fable 5.1 <[email protected]>
clawhdf5-agent
HDF5-backed persistent memory store for on-device AI agents.
Built on clawhdf5, clawhdf5-agent provides a vector-searchable memory backend optimized for edge AI workloads. Store embeddings, text chunks, and metadata in a single HDF5 file with SIMD-accelerated similarity search.
Features
- Persistent vector store in HDF5 format
- Cosine similarity and L2 distance search
- SIMD-accelerated via clawhdf5-accel (AVX2, NEON)
- Optional GPU acceleration via clawhdf5-gpu
- Memory-mapped access for large stores
- f16 storage support for compact embeddings
Usage
[dependencies]
clawhdf5-agent = "2.1.0"
License
MIT