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feat(sonic_ct): acoustic digital human workbench — Rust/WASM USCT + R3F UI (#595)
* feat(sonic_ct): acoustic digital human workbench — Rust/WASM USCT + R3F UI Add `sonic_ct`, a research-grade Ultrasound Computed Tomography (USCT) simulator and reconstruction workbench. Core (crates/sonic-ct, pure Rust, zero deps, 17 tests): - procedural z-varying torso phantom (fat/muscle/organ shells, spine, ribs, pelvis, liver/spleen/kidneys/aorta, heart+lungs in thorax) - circular ring acquisition with straight-ray travel-time + attenuation - SART time-of-flight reconstruction (1 sweep == delay backprojection) - transparent speed-band segmentation with per-cell uncertainty - coordinate-ascent threshold training (mean Dice ~0.30 -> ~0.63) - RuVector-style acoustic memory: NSW vector index, longitudinal drift, warm-start, anatomical graph-coherence checks, .rvf-style serialization - 3-D volume sweep (truth / recon / error / confidence channels) - mock Butterfly Embedded acquisition boundary (trait, no hardware SDK) WASM (crates/sonic-ct-wasm): raw C-ABI cdylib (no wasm-bindgen, ~39 KB) exposing the single-slice + progressive volume pipeline. UI (examples/sonic-ct): React Three Fiber "Sonic Chamber" — water chamber, transducer ring(s), holographic torso with internal organ glows and class-tinted contour slices, live HUD (acoustic paths, phantom fidelity, path confidence, body composition), cranio-caudal scrubber. Driven entirely by real reconstruction data. Docs (docs/sonic-ct): 8 ADRs, SOTA research map, market brief, SPARC. Co-Authored-By: claude-flow <ruv@ruv.net> Claude-Session: https://claude.ai/code/session_01Mx4vKMfvsq5KBQgPRSoxM7 * feat(sonic_ct ui): welcome modal + GLB body-model loader with procedural fallback - WelcomeModal: Simulate/Reconstruct/Analyze/Validate intro, Get Started cards, "show on startup" preference, research-only disclaimer. - BodyModel: loads a supplied GLB anatomy model (GLB_URL) and applies a ghost material override + per-organ tinting from organ_manifest.json; cleanly falls back to the procedural violet ghost (torso + internal organ glows) when no asset is supplied or it fails to load. GLB is a visual prior only — the Rust phantom stays the physics ground truth. - Refined holographic ghost: violet volumetric glow, class-tinted contour slices, twin transducer rings, glowing base, internal organ volumes. - docs/sonic-ct/BODY-MODELS.md: researched model sources (Zygote, BioDigital, SMPL/Meshcapade, Z-Anatomy, BodyParts3D) + GLB integration pipeline. Co-Authored-By: claude-flow <ruv@ruv.net> Claude-Session: https://claude.ai/code/session_01Mx4vKMfvsq5KBQgPRSoxM7 * feat(sonic_ct ui): load open-source CesiumMan GLB as the ghost body shell - Ship CesiumMan (Khronos glTF Sample Assets, CC-BY 4.0) as public/models/human.glb, loaded via useGLTF, auto-fit to the chamber, and styled with the ghost-material override; procedural internal organ glows render inside it. - GLB_URL now points at the bundled model; missing/broken asset still falls back to the procedural torso shell via the error boundary. - Attribution recorded in organ_manifest.json and docs/sonic-ct/BODY-MODELS.md. Co-Authored-By: claude-flow <ruv@ruv.net> Claude-Session: https://claude.ai/code/session_01Mx4vKMfvsq5KBQgPRSoxM7 * feat(metabiohacker): organ-hypothesis detector, Darwin optimizer, rebrand Rename the app to MetaBioHacker (Acoustic Digital Human Workbench · Sonic Chamber) across HUD, welcome modal, and metadata. Organ inference (ADR-0009/0010): new `crates/sonic-ct/src/organ.rs` detects liver, spleen, kidneys, aorta, heart, and lungs from the reconstructed volume using anatomical priors (zone, side, size, posterior adjacency, slice-consistency) — never from speed alone. Each hypothesis carries a confidence and an evidence bitmask. Exposed via WASM (sct_organ_*, sct_quality_flag) and surfaced in a new HUD panel with per-organ confidence bars + quality flags (bone shadowing / sparse coverage / boundary uncertainty / gas). 18 Rust tests pass; clippy clean. Harness optimization (examples/sonic-ct/optimize.mjs): uses @metaharness/darwin ("freeze the model, evolve the harness") with cheap->frontier tiering and Pareto selection over the frozen WASM engine to evolve {elements, fan, iters}; lifts phantom fidelity ~0.53 -> ~0.59. Documented in docs/sonic-ct/OPTIMIZATION.md. Co-Authored-By: claude-flow <ruv@ruv.net> Claude-Session: https://claude.ai/code/session_01Mx4vKMfvsq5KBQgPRSoxM7 * feat(metabiohacker): faithful Darwin harness evolution + OpenRouter write layer - crates/sonic-ct/src/bin/serve.rs: the frozen acoustic engine as a JSON-over- stdio process (sonic_ct_serve) — the physics truth layer for the evolver. - examples/sonic-ct/src/optimizer/reconstructionEvolution.ts: typed genome (reconstruction/routing/scoring/safety), runFrozenRustEngine (spawns the real binary), cheap->frontier routeReconstruction (augments engine output, never rewrites anatomy), multi-objective scoreCandidate, mutateGenome, and evolveMetaBioHarness using Darwin mapLimit + paretoFront + an archive. - optimize.mjs: OpenRouter LLM "write layer" proposes harness mutations (cheap gpt-4o-mini / frontier gpt-4o), gated by routing policy, bounded budget, key read from env only; archive-based acceptance gate now PASSES (latency -92.8%, no regression). probeDarwin.mjs verifies the export surface. - Tests (npm test, Node type-stripping): mapLimit bounds concurrency; paretoFront keeps accurate+cheap trade-offs and drops dominated; frontier never bypasses the frozen engine. docs/sonic-ct/OPTIMIZATION.md updated. Co-Authored-By: claude-flow <ruv@ruv.net> Claude-Session: https://claude.ai/code/session_01Mx4vKMfvsq5KBQgPRSoxM7 * docs(metabiohacker): ADRs 0009-0019 — organ inference, harness evolution, multimodal data + governance Add 11 ADRs and an index covering the layers built and the medical-data architecture roadmap: Organ/inference layer (grounded in organ.rs / segmentation.rs / Hud.jsx): - 0009 five acoustic classes canonical (no organ identity from speed alone) - 0010 organ identity inferred from anatomical priors (evidence + confidence) - 0011 organ function requires dynamic/multiparametric channels ("not measured") - 0012 explainability mandatory (evidence bitmask surfaced in the UI) - 0013 no disease labels — research mode only Harness + data architecture: - 0014 freeze the physics engine, evolve the reconstruction harness (Darwin) - 0015 patient data as a graph of typed observations (MedicalObservation, provenance + uncertainty + consent scope) - 0016 adopt DICOM / FHIR / LOINC / SNOMED CT / OMOP + RuVector similarity index - 0017 typed multimodal fusion patterns (monitoring/research, not diagnosis) - 0018 governance & SaMD boundary (FDA GMLP/PCCP, Health Canada, Ontario PHIPA) - 0019 a medical signal operating system, not an AI doctor Co-Authored-By: claude-flow <ruv@ruv.net> Claude-Session: https://claude.ai/code/session_01Mx4vKMfvsq5KBQgPRSoxM7 * feat(metabiohacker): benchmark harness on real CT data + synthetic corpus - Real-data ingestion: Grid::from_pgm (P5 parser), Phantom::from_intensity_grid (band a grayscale CT slice into the five acoustic classes), and pipeline::run_with_phantom (reconstruct a supplied phantom — engine unchanged). - sonic_ct_serve gains a phantomPgm path: reconstruct a real anatomical slice instead of a procedural one and emit the same score schema. - tools/fetchRealSlice.mjs: fetch a public-domain abdominal CT slice (Wikimedia Commons) and convert to a grayscale PGM (image not committed; fetched on demand, derived PGM gitignored). - benchmark.mjs (npm run benchmark): baseline vs Darwin-evolved harness over 12 reproducible synthetic phantoms + 1 real CT slice; writes docs/sonic-ct/ BENCHMARK.md + benchmark.report.json. Representative: evolved harness ~157% faster at equal Dice; real CT honestly harder (Dice ~0.27). - New integration test exercises the PGM/real-phantom reconstruction path (19 Rust tests pass). Co-Authored-By: claude-flow <ruv@ruv.net> Claude-Session: https://claude.ai/code/session_01Mx4vKMfvsq5KBQgPRSoxM7 * feat(metabiohacker): scale benchmark — 40 synthetic seeds + multiple real CT slices, 95% CI - fetchRealSlice.mjs fetches several public-domain CT slices (abdomen, thorax, pelvis) resiliently, skipping unavailable ones. - benchmark.mjs now runs N synthetic seeds (default 40) + every fetched real slice, reports mean ± 95% CI, and writes docs/sonic-ct/BENCHMARK.md. Representative: 42 samples, evolved harness ~149% faster at equal Dice (±0.002 CI); real CT slices honestly harder (Dice ~0.30). Co-Authored-By: claude-flow <ruv@ruv.net> Claude-Session: https://claude.ai/code/session_01Mx4vKMfvsq5KBQgPRSoxM7 * feat(metabiohacker): Multimodal Ingest V0 — observations, graph, fusion, ledger, ruvn evidence gate New package packages/metabiohacker (@metabiohacker/core, TS, 14 tests pass): - ingest/: canonical MedicalObservation + lab (CSV→LOINC), imaging (DICOM sidecar), and pathology adapters with provenance/uncertainty/consent. - graph/: auditable patient state graph + rule-based contradiction detection (low-quality, ≥2x same-test disagreement, unflagged review modalities). - fusion/: prior builder (data shapes priors, never forces conclusions), multimodal scoring (acoustic residual passed through unchanged), contradiction penalty, and a Darwin harness (mapLimit + paretoFront) selecting fusion policy. - evidence/: ruvn as the evidence-intelligence layer (off the hot path) — provider interface, A/B-or-blocked claim gate, deterministic cached provider + optional @ruvnet/ruvn CLI adapter (never a hard dep). Claims ship only on grade A/B with citations; pathology/biopsy/Pap/HPV/cytology force human review. - ledger/ + output/: stable-hash reconstruction run ledger (tamper-evident, verifiable) and the safe UI packet (uncertainty overlay, diagnosis blocked). Benchmark: +10% stability, ~37% uncertainty drop, residual unchanged, ledger verified, clinical-review mode forced by pathology. Docs: ADR-0020 (canonical observation), 0021 (graph+contradictions), 0022 (run ledger), 0023 (ruvn evidence layer); ADR index updated. Co-Authored-By: claude-flow <ruv@ruv.net> Claude-Session: https://claude.ai/code/session_01Mx4vKMfvsq5KBQgPRSoxM7 * feat(metabiohacker): real-slice calibration, domain-gap honesty gate, evidence refresh, CI gates Attacks the synthetic→real Dice gap honestly rather than hiding it. - Engine: sonic_ct_serve emits per-class (region) Dice on real slices. - calibration/: region-level Dice (diceByRegion), domain-gap scoring + honesty gate (classifyRealSliceResult: headline/researchOnly/exclude), centroid registration-error + boundary-complexity proxies. Real CT slices are calibration targets, not USCT. - benchmark.mjs: 3-section report (synthetic / real region-level / governance); headline separates speed from real fidelity. Real slices now classify as exclude/researchOnly and stay out of headline metrics (abdomen~0.30). - evidence:refresh (OpenRouter): grades modality evidence into docs/evidence/*.md + a candidate cache; promotion to the curated cache stays a reviewed step. Live run graded acoustic USCT = C (research-only), MRI = B. - CI gates (ciGates.test.ts + .github/workflows/metabiohacker-ci.yml): residual invariant, pathology review forced, A/B-only claims, real-slice honesty gate. 23 metabiohacker tests + 12 Rust integration tests pass. ADR-0024 added. Co-Authored-By: claude-flow <ruv@ruv.net> Claude-Session: https://claude.ai/code/session_01Mx4vKMfvsq5KBQgPRSoxM7 * feat(sonic_ct): method comparison vs BP/SART/Landweber on Shepp-Logan with RMSE/PSNR/SSIM Bench reconstruction against recognised algorithms on a recognised target: - shepp_logan.rs: standard 10-ellipse Shepp-Logan phantom -> speed map. - reconstruction.rs: Method enum + reconstruct_speed_with; Landweber solver (gradient descent on ‖As−t‖²) alongside backprojection (1 sweep) and SART. - metrics.rs: standard image-quality metrics RMSE, PSNR (dB), SSIM. - sonic_ct_methods bin -> docs/sonic-ct/METHOD-BENCHMARK.md (deterministic). Measured: backprojection < SART < Landweber on every metric for both Shepp-Logan and abdomen (abdomen RMSE 130→99→51 m/s, SSIM 0.22→0.60→0.92) at ~4/28/100 ms. SART stays production default; Landweber is the higher-fidelity option. 2 new tests; 14 integration tests pass; clippy clean. ADR-0025 added. Co-Authored-By: claude-flow <ruv@ruv.net> Claude-Session: https://claude.ai/code/session_01Mx4vKMfvsq5KBQgPRSoxM7 * feat(metabiohacker): rigid translation registration for real-slice calibration Replace the centroid-only proxy with registerByTranslation — finds the integer offset that maximises predicted/target body-mask overlap Dice, returning the offset, residual misalignment (errorPx), and aligned overlap. Gives the domain-gap honesty gate a real registration estimate (landmark refinement is the next step). +1 test (recovers a known offset; maximises overlap). 24 tests pass. Co-Authored-By: claude-flow <ruv@ruv.net> Claude-Session: https://claude.ai/code/session_01Mx4vKMfvsq5KBQgPRSoxM7 * feat(sonic_ct): full-waveform inversion (FWI) — forward + adjoint-state gradient The SOTA step beyond straight-ray TOF (ADR-0004 roadmap), as a dependency-free 2-D reference: - fwi.rs: FDTD scalar-wave forward model (∂ₜ²p = κ∇²p + f), CFL-stable, damping sponge; adjoint-state gradient ∂χ/∂κ = Σ_t λ ∇²p; gradient descent with source/receiver-footprint muting, smoothing, and backtracking line search. - Proven by the gold-standard adjoint-vs-finite-difference gradient check (cosine > 0.85) + an inversion that cuts data misfit ≥15% and recovers a centrally-concentrated velocity anomaly. 2 new tests; 23 Rust tests pass; clippy clean. - Honest scope: single-frequency, unregularised — frequency continuation, regularisation, source encoding, and 3-D are the documented next steps; no quantitative clinical recovery claimed. ADR-0026 added. Co-Authored-By: claude-flow <ruv@ruv.net> Claude-Session: https://claude.ai/code/session_01Mx4vKMfvsq5KBQgPRSoxM7 * feat(sonic-ct): add FWI frequency continuation (multiscale inversion) Add invert_multiscale + Stage to fwi.rs: chains low->high frequency FWI stages with between-stage model smoothing to avoid cycle-skipping. Low frequencies recover the smooth background first, keeping high-frequency stages out of local minima. Proven by a third FWI test: frequency continuation lowers the inclusion-region error below single-scale FWI at matched iteration count (deterministic). Adjoint-vs-FD gradient check and misfit-reduction tests still pass. Updates ADR-0026. Co-Authored-By: claude-flow <ruv@ruv.net> Claude-Session: https://claude.ai/code/session_01Mx4vKMfvsq5KBQgPRSoxM7 --------- Co-authored-by: Claude <noreply@anthropic.com>
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name: metabiohacker-ci
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# CI gates for the MetaBioHacker stack (ADR-0013/0017/0018/0022/0024):
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# frozen physics residual, mandatory pathology review, A/B-only claims,
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# verifiable ledgers, and the real-slice honesty gate.
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on:
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push:
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paths:
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- "crates/sonic-ct/**"
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- "crates/sonic-ct-wasm/**"
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- "packages/metabiohacker/**"
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- ".github/workflows/metabiohacker-ci.yml"
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pull_request:
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paths:
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- "crates/sonic-ct/**"
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- "crates/sonic-ct-wasm/**"
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- "packages/metabiohacker/**"
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jobs:
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rust-engine:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- uses: dtolnay/rust-toolchain@stable
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with:
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targets: wasm32-unknown-unknown
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- name: sonic_ct tests
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run: cd crates/sonic-ct && cargo test --release
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- name: sonic_ct clippy (lib)
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run: cd crates/sonic-ct && cargo clippy --release --lib -- -D warnings
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- name: build wasm
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run: bash scripts/build-sonic-ct-wasm.sh
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metabiohacker-gates:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- uses: actions/setup-node@v4
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with:
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node-version: "22"
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- name: install
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run: cd packages/metabiohacker && npm ci || npm install
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- name: CI gates + unit tests
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run: cd packages/metabiohacker && npm test

Cargo.toml

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[workspace]
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exclude = ["external/ruqu", "external/rvdna", "examples/OSpipe", "examples/rvf", "crates/micro-hnsw-wasm", "crates/ruvector-hyperbolic-hnsw", "crates/ruvector-hyperbolic-hnsw-wasm", "examples/ruvLLM/esp32", "examples/ruvLLM/esp32-flash", "examples/edge-net", "examples/data", "examples/ruvLLM", "examples/delta-behavior", "crates/rvf", "crates/rvf/*", "crates/rvf/*/*", "examples/rvf-desktop", "crates/mcp-brain-server",
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<<<<<<< HEAD
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# emergent-time-wasm is a standalone cdylib with its own size-optimized
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# `[profile.release]` (opt-level="z") and a `panic = "abort"` profile for a
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# tiny wasm; excluded so it does not override the workspace opt-level=3.
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"crates/emergent-time-wasm",
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=======
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# sonic-ct crates are self-contained detached workspaces (own [workspace]
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# tables) so their native + wasm builds stay fast and dependency-free.
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"crates/sonic-ct", "crates/sonic-ct-wasm",
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>>>>>>> 9a0d2f196 (feat(sonic_ct): acoustic digital human workbench — Rust/WASM USCT + R3F UI)
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# ruvector-postgres is a pgrx-based PostgreSQL extension. Its build script
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# requires `$PGRX_HOME` set up via `cargo install cargo-pgrx --version 0.12.9`
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# and `cargo pgrx init`, which downloads and builds multiple Postgres

crates/sonic-ct-wasm/Cargo.lock

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crates/sonic-ct-wasm/Cargo.toml

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# sonic-ct-wasm — raw C-ABI WebAssembly wrapper around the `sonic_ct` core.
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#
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# Deliberately avoids wasm-bindgen: it exports a small, stable set of
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# `extern "C"` functions and lets the JS loader read flat buffers directly from
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# linear memory. This keeps the build to a single `cargo build --target
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# wasm32-unknown-unknown` with no extra toolchain (no wasm-pack / wasm-bindgen
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# version coupling).
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[package]
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name = "sonic-ct-wasm"
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version = "0.1.0"
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edition = "2021"
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rust-version = "1.74"
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description = "WebAssembly (raw C-ABI) wrapper for the sonic_ct USCT simulator."
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license = "MIT OR Apache-2.0"
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repository = "https://github.com/ruvnet/ruvector"
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[workspace]
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[lib]
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crate-type = ["cdylib"]
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[dependencies]
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sonic_ct = { path = "../sonic-ct" }
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[profile.release]
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opt-level = "z"
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lto = true
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codegen-units = 1
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panic = "abort"
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strip = true

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