proffesor-for-testing__agentic-qe/docs/plans/rvf-phase0-gate-report.md

Phase 0 Gate Report — RVF Vision Validation

Date: 2026-02-15 SDK Versions: @ruvector/rvf v0.1.4, @ruvector/rvf-node v0.1.2, @ruvector/rvf-wasm v0.1.2, @ruvector/core v0.1.29, ruvector CLI v0.1.99 Platform: linux arm64, Node v24.13.0 Rust Source: github.com/ruvnet/ruvector (main branch, cloned to /tmp/ruvector-src)

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Executive Summary

Gate Decision: CONDITIONAL PROCEED via Bridge Strategy

The RVF vision is validated by Rust source code — the implementation is real and comprehensive. However, the npm SDK is not yet functional for the full RVF format. The critical gap is that @ruvector/rvf-node and @ruvector/rvf-wasm are published stubs (package.json + README only, no native binaries or WASM).

However, @ruvector/core (the existing in-memory vector engine) and @ruvector/gnn (HNSW) are fully functional and already integrated into AQE. This gives us a viable bridge strategy: use the working JS engine now, and swap to full RVF when binaries ship.

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Feature Matrix: Vision vs. Reality

Tier 1: Working NOW (npm packages functional)

Feature	Package	Status	Evidence
In-memory vector DB	@ruvector/core v0.1.29	WORKING	VectorDb class, insertBatch, search, CollectionManager
HNSW search	@ruvector/gnn	WORKING	Already in AQE PatternStore (ADR-048)
Distance metrics	@ruvector/core	WORKING	cosine, euclidean, dot product
Collection management	@ruvector/core	WORKING	createCollection, listCollections, aliases, stats
CLI operations	ruvector v0.1.99	PARTIAL	benchmark, info, doctor work; create has field-name bug

Tier 2: Implemented in Rust, NOT Available via npm

Feature	Rust Crate	Source Status	npm Status
RVF file format (create/open)	rvf-runtime	Complete (~2150 LOC)	Stub — no .node binary
Progressive HNSW (3-layer)	rvf-index	Complete (~530 LOC)	Not wired into runtime query path
COW branching (RVCOW)	rvf-runtime	Complete (branch/derive)	Stub
Witness chains (audit trail)	rvf-runtime	Complete (append_witness)	Stub
Metadata filtering	rvf-runtime	Complete (FilterExpr)	Stub
Scalar/Product quantization	rvf-quant	Implemented	Stub
Cryptographic signing	rvf-crypto	Implemented	Stub
N-API bindings (19 methods)	rvf-node	Complete (~850 LOC)	No prebuilt .node file
WASM bindings (29 exports)	rvf-wasm	Complete	No .wasm binary
AgentDB adapter	rvf-adapters/agentdb	Complete	Not published
SONA adapter	rvf-adapters/sona	Complete	Not published

Tier 3: Implemented in Rust, Advanced/Experimental

Feature	Rust Crate	Source Status	Notes
KERNEL_SEG embedding	rvf-kernel	Complete (5 source files)	QEMU microVM support confirmed
eBPF embedding	rvf-ebpf	Complete (1 source file)
HTTP server	rvf-server	Complete	axum/Router found in source
Self-booting runtime	rvf-launch	Partial (5 files)	No FUSE/mount, no unikernel yet

Tier 4: Vision Only (Not Found in Source)

Feature	Claimed	Source Evidence
POSIX mount (auto-ingest)	"mount as disk, POSIX folder"	No FUSE code found in rvf-launch
Network-native interface	"speaks directly over wire"	rvf-server has HTTP, no raw protocol
QR-code deployment	"embed in QR code"	No QR code implementation
Battery-powered edge	"tile-scale, AA batteries"	Architecture supports it, no edge runtime
Unikernel boot	"no OS required"	No unikernel references in source

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Performance Comparison: AQE Baseline vs @ruvector/core

Metric	AQE (SQLite+better-sqlite3)	@ruvector/core (in-memory)	Delta
Insert 100	3.6ms (27K ops/s)	0.2ms (458K ops/s)	17x faster
Insert 1000	12ms (83K ops/s)	1.5ms (668K ops/s)	8x faster
Insert 5000	65ms (77K ops/s)	7.7ms (651K ops/s)	8.5x faster
Search 100 (p50)	0.27ms	0.003ms	90x faster
Search 1000 (p50)	3.6ms	0.005ms	720x faster
Search 5000 (p50)	21.8ms	0.005ms	4360x faster
Cold start	11.3ms	~0ms (in-memory)	N/A (different paradigm)
Persistence	Yes (SQLite)	No (in-memory only)	AQE has durability
HNSW	Via @ruvector/gnn	Built-in	Comparable

Notes:

• @ruvector/core is in-memory only — no persistence. The massive search speedup (720-4360x) is expected: it avoids SQLite BLOB deserialization entirely.
• AQE's SQLite baseline includes persistence, ACID transactions, and crash recovery — features @ruvector/core doesn't provide.
• Fair comparison requires RVF file format (rvf-node) which would add I/O overhead but gain progressive search + persistence.

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Critical Findings

1. The Runtime Query is Brute-Force

rvf-runtime/src/store.rs lines 312-361: the query() method does a linear scan across all vectors. The ProgressiveIndex (3-layer HNSW) exists in rvf-index but is NOT called from the runtime. This means even if rvf-node binaries shipped today, search performance would be O(n), not O(log n).

2. N-API Bindings Are Complete Code, Just Not Built

rvf-node/src/lib.rs has 850 lines of complete napi-rs bindings. The gap is purely a build/release pipeline issue — no prebuilt .node files are published. Building from source requires Rust toolchain (not available in Codespace).

3. The Vision Components Exist at Different Maturity Levels

• Production-ready: Vector storage, COW branching, witness chains, metadata filtering
• Implemented but not integrated: Progressive HNSW, adapters
• Experimental: KERNEL_SEG, eBPF, HTTP server
• Not implemented: POSIX mount, unikernel, QR deployment

4. @ruvector/core is Already Delivering Value

AQE already uses @ruvector/gnn for HNSW. The @ruvector/core VectorDb with CollectionManager could replace SQLite BLOB storage for vectors TODAY, with 8-4000x speedup. The tradeoff is losing persistence (in-memory only).

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Gate Decision Matrix

Gate Criterion	Result	Recommendation
Can RVF file self-boot in WASM?	NO — wasm package is stub	Wait for binary
Can RVF file self-boot in Node?	NO — node package is stub	Wait for binary
Does POSIX mount work?	NO — not implemented	Vision only
Does network-native interface work?	PARTIAL — HTTP server in Rust	Not available via npm
Can we embed custom logic?	API exists (embedKernel, embedEbpf)	Not testable without backend
Progressive HNSW cold-start?	NOT WIRED into runtime	Even if built, would use brute-force
Feature matrix documented?	YES — this document	Complete

Original Gate Criteria Assessment

Gate: If self-booting and progressive HNSW work → proceed to Phase 1 If only storage features work → fall back to V1's hybrid plan

Neither gate condition is met. Self-booting doesn't work (stub packages). Progressive HNSW isn't wired into the runtime.

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Revised Recommendation: Bridge Strategy

Instead of blocking on the full RVF vision, proceed with what works NOW:

Phase 0.5 — Bridge Layer (1-2 weeks)

1. Replace SQLite BLOB vector storage with @ruvector/core VectorDb

   • Keep SQLite for KV store, Q-values, GOAP state (relational data)
   • Use VectorDb for pattern embeddings (8-4000x search speedup)
   • Add persistence wrapper: serialize/deserialize VectorDb state to SQLite on shutdown/startup

2. Add CollectionManager for domain isolation

   • Each AQE domain gets its own collection: test-generation, defect-intelligence, etc.
   • Maps cleanly to future RVF cognitive units

3. Keep @ruvector/gnn for HNSW (already integrated)

4. Prepare RVF adapter interface

   • Define VectorBackend interface matching RvfDatabase API shape
   • Implement CoreVectorBackend wrapping @ruvector/core
   • When rvf-node ships, implement RvfFileBackend — swap with feature flag

When to Re-evaluate Full RVF

• When @ruvector/rvf-node ships with prebuilt binaries (check npm view @ruvector/rvf-node weekly)
• When progressive HNSW is wired into rvf-runtime's query path
• When RVF file format benchmarks are available

What NOT to Do

• Don't wait for the full vision — the bridge delivers value immediately
• Don't build Rust from source in CI — fragile and slow
• Don't replace SQLite for relational data — VectorDb is vector-only
• Don't invest in KERNEL_SEG/eBPF/self-boot until npm SDK is functional

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Appendix: Detailed Check Results

✅ PASS (14):
  - sdk-exports: RvfError, RvfErrorCode, NodeBackend, WasmBackend, resolveBackend, RvfDatabase
  - rvf-database-class: 20 methods including derive, embedKernel, extractKernel, embedEbpf, extractEbpf, segments
  - cow-branching-api: derive() exists on RvfDatabase prototype
  - kernel-embedding-api: embedKernel, extractKernel, embedEbpf, extractEbpf
  - segments-api: segments() method available
  - core-import: VectorDb, CollectionManager, hello, version, getHealth, getMetrics
  - cli-benchmark, cli-install-extensions
  - progressive-hnsw-rust: All 3 layers (centroid, partial, full) implemented
  - launch-crate: 5 source files
  - rvf-server-http: HTTP server with Router
  - kernel-seg-crate: 5 source files, QEMU microVM support
  - ebpf-seg-crate: 1 source file
  - self-boot-qemu: QEMU references confirmed

🟡 PARTIAL (1):
  - witness-chains-api: No explicit methods in prototype (automatic via WitnessConfig)

❌ FAIL (13):
  - sdk-import: package.json not exported
  - node-backend-import: Stub — no native bindings
  - wasm-backend-import: Stub — no WASM binary
  - rvf-database-create: No backend available
  - core-create: RuVectorDB constructor changed to VectorDb
  - gnn-import: Missing platform-specific binary (arm64)
  - mcp-server-package: package.json not exported
  - cli-server: timeout
  - progressive-hnsw-runtime-wired: Brute-force in runtime
  - progressive-hnsw-napi: N-API wraps brute-force store
  - posix-mount-rust: No FUSE code
  - network-interface-rust: No raw network protocol
  - self-boot-unikernel: No unikernel references

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Generated by Phase 0 validation — 2026-02-15