mirror of
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e188a613a9
* research: add nightly survey for hybrid-sparse-dense Three-pass research survey selecting hybrid sparse-dense (BM25 + ANN + RRF/RSF) as nightly topic. Covers SOTA, gap analysis vs. ruvector-core, industry comparison (Qdrant, Weaviate, Milvus, Vespa, LanceDB), practical and exotic applications, deep research notes, benchmark methodology, and full reference list. Co-Authored-By: claude-flow <ruv@ruv.net> Claude-Session: https://claude.ai/code/session_01NFp4fjSarGCp2xpqJtqP2Z * feat: add ruvector-hybrid crate with BM25 + ANN + RRF/RSF fusion New standalone crate implementing three hybrid sparse-dense search strategies: ScoreFusion (backward-compat with ruvector-core), RRF (Cormack 2009, k=60, rank-only), and RSF (Weaviate-style per-list min-max + configurable α). BM25 pre-computes TF at index time (O(|q|×P) query) fixing the re-tokenisation-at-query-time bug in ruvector-core (O(N×|d|)). Benchmark: 10K docs × 128-D, 20 topics, 500 queries, k=10. BM25: 77.3% recall@10, 57,174 QPS RSF: 76.6% recall@10, 360 QPS RRF: 50.5% recall@10, 360 QPS Score: 68.8% recall@10, 357 QPS Dense: 7.5% recall@10, 371 QPS No unsafe code. Compiles to WASM. 19 unit tests. Co-Authored-By: claude-flow <ruv@ruv.net> Claude-Session: https://claude.ai/code/session_01NFp4fjSarGCp2xpqJtqP2Z * docs: add ADR-256 for hybrid sparse-dense search (RRF and RSF) Architecture Decision Record for adding Reciprocal Rank Fusion and Relative Score Fusion to RuVector's hybrid search infrastructure. Documents: gap in ruvector-core (global normalisation + re-tokenisation bug), industry comparison, benchmark evidence, three-phase implementation plan, failure modes, security considerations, and migration path. Status: proposed. PoC in crates/ruvector-hybrid. Co-Authored-By: claude-flow <ruv@ruv.net> Claude-Session: https://claude.ai/code/session_01NFp4fjSarGCp2xpqJtqP2Z * docs: add SEO gist for hybrid-sparse-dense research Public technical article covering RRF and RSF hybrid search fusion in Rust. Includes feature comparison table, Mermaid architecture diagram, real benchmark results, comparison with 9 vector databases, 8 practical + 8 exotic applications, deep research notes on BM25 dominance and normalisation theory, usage guide, optimization guide, and roadmap. Co-Authored-By: claude-flow <ruv@ruv.net> Claude-Session: https://claude.ai/code/session_01NFp4fjSarGCp2xpqJtqP2Z * fix(ruvector-hybrid): clippy + fmt for CI - centres[t] loop index → iter().enumerate() - percentile cast: drop .max(0) (usize is never negative, clippy::unnecessary_min_or_max) - percentile cast: #[allow] remaining cast lints (intentional saturating cast) - print_row: &mut Vec → &mut [_] - fusion.rs: 3.14 → 3.0 (clippy::approx_constant) - cargo fmt on entire crate Co-Authored-By: claude-flow <ruv@ruv.net> --------- Co-authored-by: Claude <noreply@anthropic.com> Co-authored-by: ruvnet <ruvnet@gmail.com> |
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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
- guides/GETTING_STARTED.md - Getting started guide
- guides/BASIC_TUTORIAL.md - Basic tutorial
- guides/INSTALLATION.md - Installation instructions
- guides/AGENTICDB_QUICKSTART.md - AgenticDB quick start
- guides/wasm-api.md - WebAssembly API documentation
Architecture & Design
- architecture/ - System architecture details
- cloud-architecture/ - Global cloud deployment
- adr/ - Architecture Decision Records
- nervous-system/ - Nervous system architecture
API Reference
- api/RUST_API.md - Rust API reference
- api/NODEJS_API.md - Node.js API reference
- api/CYPHER_REFERENCE.md - Cypher query reference
Performance & Benchmarks
- benchmarks/ - Performance benchmarks & results
- optimization/ - Performance optimization guides
- analysis/ - Research & analysis docs
Security
- security/ - Security audits & reports
Implementation
- implementation/ - Implementation details & summaries
- integration/ - Integration guides
- code-reviews/ - Code review documentation
Specialized Topics
- gnn/ - GNN/Graph implementation
- hnsw/ - HNSW index documentation
- postgres/ - PostgreSQL extension docs
- ruvllm/ - RuVLLM documentation
- training/ - Training & LoRA docs
Development
- development/CONTRIBUTING.md - Contribution guidelines
- development/MIGRATION.md - Migration guide
- testing/ - Testing documentation
- publishing/ - NPM publishing guides
Research
- research/ - Research documentation
- cognitive-frontier/ - Cognitive frontier research
- gnn-v2/ - GNN v2 research
- latent-space/ - HNSW & attention research
- mincut/ - MinCut algorithm research
🚀 Quick Links
For New Users
- Start with Getting Started Guide
- Try the Basic Tutorial
- Review API Documentation
For Cloud Deployment
- Read Architecture Overview
- Follow Deployment Guide
- Apply Performance Optimizations
For Contributors
- Read Contributing Guidelines
- Review Architecture Decisions
- Check Migration Guide
For Performance Tuning
- Review Optimization Guide
- Run Benchmarks
- 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
- GitHub Repository: https://github.com/ruvnet/ruvector
- Main README: ../README.md
- Changelog: ../CHANGELOG.md
- License: ../LICENSE
Last Updated: 2026-02-26 | Version: 2.0.4 (core) / 0.1.100 (npm) | Status: Production Ready