osobhandClaude Opus 5.5
db9af7972c
Makes the README's "cryptographically verifiable memory" true. With HDF5Memory::set_signing_key(key), every checkpoint stores a signed manifest of the store: a SHA-256 per memory record (text, embedding as stored, channel, timestamp, session, tags, deleted flag, activation) in a Merkle tree, plus hashes of the settings (and WAL mark), sessions and knowledge graph. The signature, public key and manifest hashes go in /meta; the per-record hashes in /integrity/record_hashes, so HDF5Memory::verify(path, &public_key) can say which records changed, not just that something did. A forged manifest fails the signature. Decisions, as agreed: - the key is set on the open store and never persisted; - a signed store refuses to checkpoint without its key (MemoryError::SigningKeyRequired); remove_signature() is the deliberate way back to unsigned; - checkpoints only: saves still in the WAL are not covered, and verify reports how many there are. The hashes cover exactly what the file persists, in the form the loader returns it (strings lose trailing NULs; an empty WAL mark is not written), so untouched stores verify across any number of reopen and checkpoint cycles. MemoryError becomes #[non_exhaustive] (it already gains variants in this unreleased version). CLI: keygen (owner-only key file), --signing-key / CLAWHDF5_SIGNING_KEY on writing commands (create signs immediately), verify --public-key (JSON; exit 2 if not valid), `signed` in create/stats output. Tests: reopen/checkpoint cycles with awkward strings (f16 and f32), refusal without the key, wrong and rotated keys, eight kinds of edit each detected and located, a forged manifest, unsigned stores, NULs in text, and an edit made in place with h5py that verify pinpoints. Cost on tank (search_harness --signing-study --full, 3 runs): ~20% of a checkpoint (+9 ms at 10K, +89-112 ms at 100K), verify 18.6 ms / 247 ms, 32 bytes per record in the file. New deps ed25519-dalek, sha2, rand_core: pure Rust, the no-C check passes. Co-Authored-By: Claude Opus 5.5 (1M context) <[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