ruvector/docs
ruvnet 4922b034fb feat(adr-183..190): integrate ruvllm_sparse_attention crate + implement ADRs 183-188
Integrates the ruvllm_sparse_attention prototype into crates/ and applies
all accepted ADRs (183-188) in a single coordinated change.

ADR-183: move rand to [dev-dependencies] — zero runtime dep footprint
ADR-184: one-pass online softmax in forward() — single traversal with
         running-max + correction factor, ~2× FLOPs reduction on Pi 5 NEON
ADR-185: skip current_block in non-causal landmark candidates — prevents
         double-counting token i through its window edge + own block mean
ADR-186: 7 edge-case tests as CI gate (seq=0, seq=1, out-of-range global
         tokens, block_size=1, self-attention-only, non-causal correctness,
         estimate regression guard); all 11 tests pass
ADR-187: checked overflow in Tensor3::zeros — panics with structured
         diagnostic message instead of silent wraparound in release builds
ADR-188: stamp scheme comments in forward() and estimate_sparse_edges()

ADRs 189 (KV cache decode_step) and 190 (GQA/MQA forward_gqa) remain
Proposed; their code is fully specified in the ADR docs and depends on
this foundation landing first.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-05-06 11:14:50 -04:00
..
adr feat(adr-183..190): integrate ruvllm_sparse_attention crate + implement ADRs 183-188 2026-05-06 11:14:50 -04:00
analysis fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
api fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
architecture fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
benchmarks fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
cloud-architecture fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
cnn feat(demo): add Self-Learning tab with 6 interactive training demos 2026-03-11 19:31:23 -04:00
code-reviews docs: reorganize into subfolders 2026-01-21 23:43:50 -05:00
dag docs(dag): add comprehensive Neural DAG Learning implementation plan 2025-12-29 22:15:55 +00:00
development feat(micro-hnsw-wasm): Add Neuromorphic HNSW v2.3 with SNN Integration (#40) 2025-12-01 22:30:15 -05:00
examples feat(musica): structure-first audio separation via dynamic mincut (#337) 2026-04-08 12:23:48 -05:00
gnn fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
guides docs: add missing capabilities to advanced features guide 2026-02-26 16:09:06 +00:00
hailo feat(ruvector-hailo): NPU embedding backend + multi-Pi cluster (ADRs 167-170) (#413) 2026-05-04 08:30:40 -04:00
hnsw fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
hooks feat(cli): Implement full hooks system in Rust CLI 2025-12-27 01:08:36 +00:00
implementation fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
integration fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
nervous-system docs: reorganize into subfolders 2026-01-21 23:43:50 -05:00
optimization fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
plans/subpolynomial-time-mincut chore(docs): Clean up and reorganize documentation structure 2025-12-25 19:39:44 +00:00
postgres fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
project-phases Clean up repository structure and organize documentation 2025-11-20 19:50:03 +00:00
publishing fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
research research(nightly): ACORN — predicate-agnostic filtered HNSW (#391) 2026-04-27 00:29:37 -04:00
reviews perf(ruvllm): optimize MoE routing with buffer reuse and optional metrics 2026-03-12 23:27:00 -04:00
ruvllm docs: reorganize into subfolders 2026-01-21 23:43:50 -05:00
rvagent feat(rvAgent): Complete DeepAgents Rust Conversion (ADR-093 → ADR-103) (#262) 2026-03-16 09:52:32 -04:00
sdk docs(sdk): add deep planning review for ruvector Python SDK 2026-04-25 20:28:54 -04:00
security feat(rvAgent): Complete DeepAgents Rust Conversion (ADR-093 → ADR-103) (#262) 2026-03-16 09:52:32 -04:00
sparse-inference feat: Add PowerInfer-style sparse inference engine with precision lanes (#106) 2026-01-04 23:40:31 -05:00
sql feat(postgres): Add ruvector-postgres extension with SIMD optimizations (#42) 2025-12-02 09:55:07 -05:00
testing Clean up repository structure and organize documentation 2025-11-20 19:50:03 +00:00
training fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
.gitkeep Clean up repository structure and organize documentation 2025-11-20 19:50:03 +00:00
.nojekyll fix: add .nojekyll to disable Jekyll processing 2026-03-11 17:53:19 -04:00
agi-container.md feat(rvAgent): Complete DeepAgents Rust Conversion (ADR-093 → ADR-103) (#262) 2026-03-16 09:52:32 -04:00
C2-shell-execution-hardening.md feat(rvAgent): Complete DeepAgents Rust Conversion (ADR-093 → ADR-103) (#262) 2026-03-16 09:52:32 -04:00
C8_RESULT_VALIDATION_IMPLEMENTATION.md feat(rvAgent): Complete DeepAgents Rust Conversion (ADR-093 → ADR-103) (#262) 2026-03-16 09:52:32 -04:00
consciousness-api.md feat(consciousness): SOTA IIT Φ, causal emergence, quantum collapse crate (ADR-131) 2026-03-31 16:36:25 -04:00
IMPLEMENTATION-C5.md feat(rvAgent): Complete DeepAgents Rust Conversion (ADR-093 → ADR-103) (#262) 2026-03-16 09:52:32 -04:00
index.html refactor: move CNN demo to docs/cnn/ for shorter URL 2026-03-11 17:52:13 -04:00
INDEX.md fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
moe-routing-optimization-analysis.md perf(ruvllm): optimize MoE routing with buffer reuse and optional metrics 2026-03-12 23:27:00 -04:00
README.md fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
REPO_STRUCTURE.md fix(brain): defer sparsifier build on startup for large graphs 2026-03-24 12:29:52 +00:00
research-openfang.md Add OpenFang project research document 2026-02-26 14:14:58 +00:00

RuVector Documentation

Complete documentation for RuVector, the high-performance Rust vector database with global scale capabilities.

📚 Documentation Structure

docs/
├── adr/                    # Architecture Decision Records
├── analysis/               # Research & analysis docs
├── api/                    # API references (Rust, Node.js, Cypher)
├── architecture/           # System design docs
├── benchmarks/             # Performance benchmarks & results
├── cloud-architecture/     # Cloud deployment guides
├── code-reviews/           # Code review documentation
├── dag/                    # DAG implementation
├── development/            # Developer guides
├── examples/               # SQL examples
├── gnn/                    # GNN/Graph implementation
├── guides/                 # User guides & tutorials
├── hnsw/                   # HNSW index documentation
├── hooks/                  # Hooks system documentation
├── implementation/         # Implementation details & summaries
├── integration/            # Integration guides
├── nervous-system/         # Nervous system architecture
├── optimization/           # Performance optimization guides
├── plans/                  # Implementation plans
├── postgres/               # PostgreSQL extension docs
├── project-phases/         # Development phases
├── publishing/             # NPM publishing guides
├── research/               # Research documentation
├── ruvllm/                 # RuVLLM documentation
├── security/               # Security audits & reports
├── sparse-inference/       # Sparse inference docs
├── sql/                    # SQL examples
├── testing/                # Testing documentation
└── training/               # Training & LoRA docs

Getting Started

Architecture & Design

API Reference

Performance & Benchmarks

Security

Implementation

Specialized Topics

Development

Research

  • research/ - Research documentation
    • cognitive-frontier/ - Cognitive frontier research
    • gnn-v2/ - GNN v2 research
    • latent-space/ - HNSW & attention research
    • mincut/ - MinCut algorithm research

For New Users

  1. Start with Getting Started Guide
  2. Try the Basic Tutorial
  3. Review API Documentation

For Cloud Deployment

  1. Read Architecture Overview
  2. Follow Deployment Guide
  3. Apply Performance Optimizations

For Contributors

  1. Read Contributing Guidelines
  2. Review Architecture Decisions
  3. Check Migration Guide

For Performance Tuning

  1. Review Optimization Guide
  2. Run Benchmarks
  3. Check Analysis

📊 Documentation Status

Category Directory Status
Getting Started guides/ Complete
Architecture architecture/, adr/ Complete
API Reference api/ Complete
Performance benchmarks/, optimization/, analysis/ Complete
Security security/ Complete
Implementation implementation/, integration/ Complete
Development development/, testing/ Complete
Research research/ 📚 Ongoing

Total Documentation: 460+ documents across 60+ directories


🔗 External Resources


Last Updated: 2026-02-26 | Version: 2.0.4 (core) / 0.1.100 (npm) | Status: Production Ready