ClawHDF5 PlannerandClaude Sonnet 4.6
87039e926c
INT-11 (clawhdf5-agent/src/encryption.rs): - AES-256-GCM seal/open with PBKDF2-HMAC-SHA256 key derivation (200k iters) - Passphrase-based and raw-key APIs; envelope format with magic+version+salt+nonce - `encryption` feature gate (ring 0.17); 9 unit tests covering roundtrips, wrong-key, tampered-data, malformed-envelope, and empty-plaintext cases INT-12 (clawhdf5-agent/src/signing.rs): - Ed25519 keypair generation, in-memory sign/verify, and file-level sidecar API - `.sig` sidecar format: magic + version + public-key + signature - `sign_file` / `verify_file` helpers for .brain file trust verification - `signing` feature gate (ring 0.17); 8 unit tests including file-level tamper detection INT-13 (clawhdf5-ann/src/hnsw.rs): - `HnswIndex::batch_insert`: parallel neighbor search (rayon) + serial edge wiring - `find_neighbors_for` standalone helper (also used by the `parallel` cfg path) - Parallelism via existing `parallel` feature; degrades to serial without it - 5 new tests: empty noop, sequential IDs, existing-index append, quality, save/load Co-Authored-By: Claude Sonnet 4.6 <[email protected]>
66 lines
2.3 KiB
TOML
66 lines
2.3 KiB
TOML
[package]
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name = "clawhdf5-agent"
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version = "2.1.0"
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edition = "2024"
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description = "HDF5-backed persistent memory store for on-device AI agents"
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license = "MIT"
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repository = "https://github.com/redclawsystems/clawhdf5"
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readme = "README.md"
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keywords = ["agent", "memory", "hdf5", "vector-search", "embedding"]
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categories = ["database", "science", "algorithms"]
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[dependencies]
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clawhdf5-format = { path = "../clawhdf5-format", version = "2.1.0", features = ["parallel", "fast-checksum"] }
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clawhdf5 = { path = "../clawhdf5", version = "2.1.0" }
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clawhdf5-io = { path = "../clawhdf5-io", version = "2.1.0", features = ["mmap"] }
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clawhdf5-accel = { path = "../clawhdf5-accel", version = "2.1.0" }
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clawhdf5-ann = { path = "../clawhdf5-ann", version = "2.1.0", optional = true }
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clawhdf5-gpu = { path = "../clawhdf5-gpu", version = "2.1.0", optional = true, default-features = false }
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serde = { workspace = true }
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byteorder = "1"
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half = { workspace = true, optional = true }
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rayon = { version = "1", optional = true }
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matrixmultiply = { version = "0.3", optional = true }
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cblas-sys = { version = "0.1", optional = true }
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tokio = { version = "1", features = ["rt", "sync", "macros", "time"], optional = true }
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ring = { version = "0.17", optional = true }
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[target.'cfg(target_os = "macos")'.dependencies]
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accelerate-src = { version = "0.3", optional = true }
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[target.'cfg(not(target_os = "macos"))'.dependencies]
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openblas-src = { version = "0.10", optional = true, features = ["cblas"] }
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[dev-dependencies]
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tempfile = { workspace = true }
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criterion = { workspace = true }
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rayon = "1"
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tokio = { version = "1", features = ["rt-multi-thread", "sync", "macros"] }
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[[bench]]
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name = "bench"
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harness = false
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[[bench]]
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name = "memory_bench"
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harness = false
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[features]
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default = ["float16", "hnsw"]
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float16 = ["half"]
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parallel = ["rayon"]
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# HNSW approximate-nearest-neighbour acceleration for the vector stage of
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# hybrid_search. On by default; the index is rebuilt from the cache on demand
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# and stays self-consistent with the persisted memory store. Disable with
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# `--no-default-features` (plus re-enabling other defaults) to force the exact
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# linear cosine scan.
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hnsw = ["clawhdf5-ann"]
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agent = []
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gpu = ["clawhdf5-gpu/gpu-wgpu"]
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fast-math = ["matrixmultiply"]
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accelerate = ["accelerate-src", "cblas-sys"]
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openblas = ["openblas-src", "cblas-sys"]
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async = ["tokio"]
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encryption = ["ring"]
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signing = ["ring"]
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