Extract the shared JS+wgpu substrate (verified by the alknet-desktop POCs)
as alknet-runtime — the generalized QuickJS-NG + wgpu runtime that both
alknet-desktop (render) and alknet-compute (tensor compute) build on. Key
property driving the split: wgpu on llvmpipe is genuinely useful compute
with no physical GPU (WGSL → optimized SIMD beats JS for non-trivial
workloads), so wgpu is unconditional in the runtime rather than a feature
flag.
Reframes the original alknet-tensor architecture-summary as alknet-compute
(builds on alknet-runtime + alknet-tensor) with ShaderGenerator as a trait
(WGSL first impl, SPIR-V/GLSL/naga-IR later per wgpu multi-input-language
support). alknet-tensor/metatensor-format.md is now clearly the pure binary
format crate (no JS or wgpu dep), usable standalone by a pure-Rust model
server.
Layering: alknet-runtime depends on alknet-call (registry authority stays
per ADR-013); alknet-compute and alknet-desktop depend on alknet-runtime;
alknet-tensor is a pure-format sibling.
Documents the metatensor format: a binary data format where a TypeBox/jsonschema
schema describes the layout of binary data at schema-computed offsets. Extends
safetensors (fixed TensorRef schema) to arbitrary schemas, enabling struct tensors
(records), blob tensors (variable-length via indirection), and nested layouts.
Key points:
- TypeBox schemas render to standard JSON Schema; the jsonschema Rust crate
validates them with zero translation. Custom typedef.ts kinds (TFloat32,
TInt32, TStruct) map to jsonschema custom keywords via with_keyword().
- This eliminates typebox-rs as a schema engine — replaced by jsonschema +
a small offset-computation module + ~50 lines of custom keyword impls.
- Three tensor kinds: flat (safetensor today), struct (record of typed fields),
blob (struct tensor as index + flat tensor as data store, for variable-length)
- Memory-mappable: parse header, compute offsets, mmap data, typed views per
schema. No copy, no deserialization.
- QUIC-streamable: header is one small JSON message, each tensor is a separate
stream. Lazy loading, parallel transfer, incremental compute.
- ujsx-authorable: <Tensor>, <Struct>, <Field> as layout components, same
reconciler that diffs UI trees diffs model schemas. Model versioning is
tree diffing.
- Category-theory foundation: ujsx as universal typed-tree IR, HostConfig as
interpreter. <Tensor> is no stranger than <div>.
