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f6c684aba0
Seven-file design review at docs/sdk/ covering the binding strategy,
API surface, M1-M4 milestones, risks, and a one-page decision record
for shipping a Python SDK.
Recommended path: **PyO3 + maturin, single in-tree
`crates/ruvector-py/` cdylib, abi3-py39 wheel via cibuildwheel,
`pyo3-asyncio` over a singleton tokio runtime.**
Why:
- The existing `*-node` NAPI templates (e.g.
`crates/ruvector-diskann-node/src/lib.rs`) already prove out the
opaque-handle + `Arc<RwLock<…>>` shape PyO3 mirrors line-for-line —
~70% port, ~30% lifetime gymnastics.
- abi3 collapses the wheel matrix from ~25 (cpython36 × 5 platforms)
to 5 (one wheel per platform, all py3.9+).
- Singleton tokio runtime avoids the "one runtime per call" overhead
while remaining compatible with asyncio + uvloop.
Milestone shape (each with explicit scope + acceptance tests):
M1 — RaBitQ-only Python wheel. Just the published
`ruvector-rabitq` crate exposed via PyO3. Smallest possible
useful surface. ~600 LoC, 3 weeks.
M2 — ruLake. Async via pyo3-asyncio. Witness verify exposed.
~900 LoC, 4 weeks.
M3 — Embeddings + ML helpers. Wrap consumer-facing parts of
`ruvector-cnn` / `ruvllm`. ~700 LoC, 3 weeks.
M4 — A2A agent client. Wrap `rvagent-a2a` so Python apps can
dispatch tasks to A2A peers, including signed AgentCard
discovery. ~800 LoC, 4 weeks.
Three acceptance gates that gate the whole effort:
1. A Python user can do RAG over 1 M vectors in <5 lines.
2. An asyncio user can stream A2A task updates without thread
fights.
3. `pip install ruvector` takes <10 s on a stock machine.
Top 3 risks identified:
R1 — tokio runtime + PyO3 + asyncio/uvloop interop. Mitigation:
single lazy runtime, `pyo3-asyncio` shim.
R3 — wheel size. M4 budget is 22 MB; A2A deps (axum + reqwest +
rustls) could blow it. Mitigation: feature-gate axum/reqwest
behind `agent` extra; default install is rabitq + rulake only.
R7 — PyPI name squat on `ruvector`. Mitigation: register placeholder
before M1 ships.
Nuance discovered: `ruvector-rabitq` has **no** sibling `*-node` or
`*-wasm` crate — unlike most consumer crates. M1 is therefore clean
greenfield: no parity-pressure to match a flaky NAPI signature, and
it confirms rabitq alone is the right starter target rather than the
umbrella `ruvector` crate the npm package wraps.
Planning doc only; no implementation.
Co-Authored-By: claude-flow <ruv@ruv.net>
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| development | ||
| examples | ||
| gnn | ||
| guides | ||
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| hooks | ||
| implementation | ||
| integration | ||
| nervous-system | ||
| optimization | ||
| plans/subpolynomial-time-mincut | ||
| postgres | ||
| project-phases | ||
| publishing | ||
| research | ||
| reviews | ||
| ruvllm | ||
| rvagent | ||
| sdk | ||
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| sparse-inference | ||
| sql | ||
| testing | ||
| training | ||
| .gitkeep | ||
| .nojekyll | ||
| agi-container.md | ||
| C2-shell-execution-hardening.md | ||
| C8_RESULT_VALIDATION_IMPLEMENTATION.md | ||
| consciousness-api.md | ||
| IMPLEMENTATION-C5.md | ||
| index.html | ||
| INDEX.md | ||
| moe-routing-optimization-analysis.md | ||
| README.md | ||
| REPO_STRUCTURE.md | ||
| research-openfang.md | ||
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