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- Add Dockerfiles for 8 RuVector components: - ruvector-core: Core vector database engine with HNSW indexing - ruvector-server: REST API server (port 8080) - ruvector-cli: CLI + MCP server for AI integration (port 3000) - ruvector-gnn: Graph Neural Networks (GCN, GAT, GIN) - ruvector-graph: Neo4j-compatible Cypher graph DB (ports 7687, 7474) - ruvector-attention: 39 attention mechanisms (MHA, GQA, MoA) - ruvector-cluster: Raft consensus distributed clustering - ruvector-sona: Self-Optimizing Neural Architecture - Add comprehensive README.md for each image with: - Docker Hub badges - Features and quickstart guides - Configuration tables - Performance benchmarks - Add docker-compose.full.yml for 9-service orchestration - Add build/publish/test scripts in docker/scripts/ - Add GitHub Actions workflow for multi-arch Docker publishing 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> |
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RuVector Graph
Distributed Neo4j-compatible hypergraph database with SIMD optimization. Combines vector similarity search with Cypher queries for powerful knowledge graphs.
Features
- 🔗 Cypher queries - Neo4j-compatible syntax
- 🌐 Bolt protocol - Standard graph protocol (port 7687)
- 📊 Hypergraph support - Multi-edge relationships
- ⚡ SIMD optimization - Hardware-accelerated traversal
Quick Start
docker run -d --name ruvector-graph \
-p 7687:7687 -p 7474:7474 \
ruvnet/ruvector-graph:latest
Example Queries
CREATE (a:Person {name: 'Alice', embedding: [0.1, 0.2, ...]})
MATCH (a:Person)-[:KNOWS]->(b) RETURN b.name
Configuration
| Variable | Default | Description |
|---|---|---|
BOLT_PORT |
7687 | Bolt protocol |
HTTP_PORT |
7474 | HTTP API |
NEO4J_AUTH |
none | Authentication |
License
MIT License