mirror of https://github.com/ruvnet/RuVector.git synced 2026-07-22 15:43:48 +00:00

History

ruv e709718b64 feat(tiny-dancer): real FastGRNN training pipeline (ADR-252) Closes the three gaps that made tiny-dancer inference-only: 1. Real gradients: FastGRNN::forward_cached + backward implement single-step analytic backprop (h0=0); gradient-checked vs central finite differences. 2. Real Adam step: train_batch accumulates mean batch gradients; apply_gradients does L2 + global-norm clip + bias-corrected Adam update on the existing optimizer state. Model now actually learns (test: loss down, acc>0.9). 3. safetensors persistence: model.rs save/load serialize every tensor (f32 LE) with config in __metadata__; round-trip is bit-exact. 4. DRACO adapter: TrainingDataset::from_draco consumes the {embedding, scores} + prices shape (same as @metaharness/router) so one dataset trains both. Runnable example train_from_draco demonstrates DRACO -> train -> save -> load -> route end to end. 31 core tests green (gradient check, convergence, round-trip, adapter). Co-Authored-By: claude-flow <ruv@ruv.net>		2026-06-15 10:50:14 -04:00
..
admin-server.rs	fix(ci): Fix formatting and workflow permission issues	2025-12-26 22:11:57 +00:00
full_observability.rs	fix(ci): Fix formatting and workflow permission issues	2025-12-26 22:11:57 +00:00
metrics_example.rs	fix(ci): Fix formatting and workflow permission issues	2025-12-26 22:11:57 +00:00
OBSERVABILITY_EXAMPLES.md	fix: Fix case sensitivity bug preventing native module from loading	2025-11-21 21:34:52 +00:00
README.md	fix: Fix case sensitivity bug preventing native module from loading	2025-11-21 21:34:52 +00:00
tracing_example.rs	fix: Resolve unresolved imports in ruvector-tiny-dancer-core examples	2025-11-26 22:48:12 +00:00
train-model.rs	fix: Resolve CI build failures	2025-11-26 15:25:47 +00:00
train_from_draco.rs	feat(tiny-dancer): real FastGRNN training pipeline (ADR-252)	2026-06-15 10:50:14 -04:00

README.md

Tiny Dancer Examples

This directory contains example applications demonstrating how to use Tiny Dancer.

Admin Server Example

File: admin-server.rs

A production-ready admin API server with health checks, metrics, and administration endpoints.

Features

Health check endpoints (K8s liveness & readiness probes)
Prometheus metrics export
Hot model reloading
Configuration management
Circuit breaker monitoring
Optional bearer token authentication

Running

cargo run --example admin-server --features admin-api

Testing

Once running, test the endpoints:

# Health check
curl http://localhost:8080/health

# Readiness check
curl http://localhost:8080/health/ready

# Prometheus metrics
curl http://localhost:8080/metrics

# System information
curl http://localhost:8080/info

Admin Endpoints

Admin endpoints support optional authentication:

# Reload model (if auth enabled)
curl -X POST http://localhost:8080/admin/reload \
  -H "Authorization: Bearer your-token-here"

# Get configuration
curl http://localhost:8080/admin/config \
  -H "Authorization: Bearer your-token-here"

# Circuit breaker status
curl http://localhost:8080/admin/circuit-breaker \
  -H "Authorization: Bearer your-token-here"

Configuration

Edit the example to configure:

Bind address and port
Authentication token
CORS settings
Router configuration

Production Deployment

For production use:

Enable authentication:

auth_token: Some("your-secret-token".to_string())

Use environment variables:

let token = std::env::var("ADMIN_AUTH_TOKEN").ok();

Deploy behind HTTPS proxy (nginx, Envoy, etc.)

Set up Prometheus scraping:

scrape_configs:
  - job_name: 'tiny-dancer'
    static_configs:
      - targets: ['localhost:8080']

Configure Kubernetes probes:

livenessProbe:
  httpGet:
    path: /health
    port: 8080
readinessProbe:
  httpGet:
    path: /health/ready
    port: 8080