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## Major Features - WASM crate (ruvllm-wasm) for browser-compatible LLM inference - Multi-platform support with #[cfg] guards for CPU-only environments - npm packages updated to v2.0.0 with WASM integration - Workspace version bump to 2.0.0 ## Performance Improvements - GEMV: 6 → 35.9 GFLOPS (6x improvement) - GEMM: 6 → 19.2 GFLOPS (3.2x improvement) - Flash Attention 2: 840us for 256-seq (2.4x better than target) - RMSNorm: 620ns for 4096-dim (16x better than target) - Rayon parallelization: 12.7x speedup on M4 Pro ## New Capabilities - INT8/INT4/Q4_K quantized inference (4-8x memory reduction) - Two-tier KV cache (FP16 tail + Q4 cold storage) - Arena allocator for zero-alloc inference - MicroLoRA with <1ms adaptation latency - Cross-platform test suite ## Fixes - Removed hardcoded version constraints from path dependencies - Fixed test syntax errors in backend_integration.rs - Widened INT4 tolerance to 40% (realistic for 4-bit precision) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> |
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Ruvector Server
High-performance REST API server for Ruvector vector databases.
ruvector-server provides a production-ready HTTP API built on Axum with CORS support, compression, and OpenAPI documentation. Exposes full Ruvector functionality via RESTful endpoints. Part of the Ruvector ecosystem.
Why Ruvector Server?
- Fast: Built on Axum and Tokio for high throughput
- Production Ready: CORS, compression, tracing built-in
- RESTful API: Standard HTTP endpoints for all operations
- OpenAPI: Auto-generated API documentation
- Multi-Collection: Support multiple vector collections
Features
Core Capabilities
- Vector CRUD: Insert, get, update, delete vectors
- Search API: k-NN search with filtering
- Batch Operations: Bulk insert and search
- Collection Management: Create and manage collections
- Health Checks: Liveness and readiness probes
Advanced Features
- CORS Support: Configurable cross-origin requests
- Compression: GZIP response compression
- Tracing: Request tracing with tower-http
- Rate Limiting: Request rate limiting (planned)
- Authentication: API key auth (planned)
Installation
Add ruvector-server to your Cargo.toml:
[dependencies]
ruvector-server = "0.1.1"
Quick Start
Start Server
use ruvector_server::{Server, ServerConfig};
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
// Configure server
let config = ServerConfig {
host: "0.0.0.0".to_string(),
port: 8080,
cors_origins: vec!["*".to_string()],
enable_compression: true,
..Default::default()
};
// Create and start server
let server = Server::new(config)?;
server.run().await?;
Ok(())
}
API Endpoints
# Health check
GET /health
# Collections
POST /collections # Create collection
GET /collections # List collections
GET /collections/{name} # Get collection info
DELETE /collections/{name} # Delete collection
# Vectors
POST /collections/{name}/vectors # Insert vector(s)
GET /collections/{name}/vectors/{id} # Get vector
DELETE /collections/{name}/vectors/{id} # Delete vector
# Search
POST /collections/{name}/search # k-NN search
POST /collections/{name}/search/batch # Batch search
Example Requests
# Create collection
curl -X POST http://localhost:8080/collections \
-H "Content-Type: application/json" \
-d '{
"name": "documents",
"dimensions": 384,
"distance_metric": "cosine"
}'
# Insert vector
curl -X POST http://localhost:8080/collections/documents/vectors \
-H "Content-Type: application/json" \
-d '{
"id": "doc-1",
"vector": [0.1, 0.2, 0.3, ...],
"metadata": {"title": "Hello World"}
}'
# Search
curl -X POST http://localhost:8080/collections/documents/search \
-H "Content-Type: application/json" \
-d '{
"vector": [0.1, 0.2, 0.3, ...],
"k": 10,
"filter": {"category": "tech"}
}'
API Overview
Server Configuration
pub struct ServerConfig {
pub host: String,
pub port: u16,
pub cors_origins: Vec<String>,
pub enable_compression: bool,
pub max_body_size: usize,
pub request_timeout: Duration,
}
Response Types
// Search response
pub struct SearchResponse {
pub results: Vec<SearchResult>,
pub took_ms: u64,
}
pub struct SearchResult {
pub id: String,
pub score: f32,
pub vector: Option<Vec<f32>>,
pub metadata: Option<serde_json::Value>,
}
// Collection info
pub struct CollectionInfo {
pub name: String,
pub dimensions: usize,
pub count: usize,
pub distance_metric: String,
}
Error Handling
// API errors return standard format
pub struct ApiError {
pub code: String,
pub message: String,
pub details: Option<serde_json::Value>,
}
// HTTP status codes:
// 200 - Success
// 201 - Created
// 400 - Bad Request
// 404 - Not Found
// 500 - Internal Error
Docker Deployment
FROM rust:1.77 as builder
WORKDIR /app
COPY . .
RUN cargo build --release -p ruvector-server
FROM debian:bookworm-slim
COPY --from=builder /app/target/release/ruvector-server /usr/local/bin/
EXPOSE 8080
CMD ["ruvector-server"]
docker build -t ruvector-server .
docker run -p 8080:8080 ruvector-server
Related Crates
- ruvector-core - Core vector database engine
- ruvector-collections - Collection management
- ruvector-cli - Command-line interface
Documentation
- Main README - Complete project overview
- API Documentation - Full API reference
- GitHub Repository - Source code
License
MIT License - see LICENSE for details.