research(nightly): semantic-drift-detector — in-database embedding drift detection for agent memory

Cargo.toml

@@ -233,6 +233,8 @@ members = [
     "crates/ruvllm_retrieval_diffusion",
     # RAIRS IVF: Redundant Assignment + Amplified Inverse Residual (ADR-193)
     "crates/ruvector-rairs",
+    # Semantic drift detection for agent memory and vector index health (ADR-194)
+    "crates/ruvector-drift",
 ]
 resolver = "2"
 

crates/ruvector-drift/Cargo.toml

@@ -0,0 +1,26 @@
+[package]
+name = "ruvector-drift"
+version = "0.1.0"
+edition = "2021"
+description = "Semantic drift detection for agent memory and vector index health in RuVector"
+license = "MIT OR Apache-2.0"
+keywords = ["vector", "drift", "embedding", "agent-memory", "anomaly"]
+
+[lib]
+name = "ruvector_drift"
+path = "src/lib.rs"
+
+[[bin]]
+name = "benchmark"
+path = "src/bin/benchmark.rs"
+
+[dependencies]
+rand = { version = "0.8", features = ["small_rng"] }
+rand_distr = "0.4"
+
+[dev-dependencies]
+criterion = { version = "0.5", features = ["html_reports"] }
+
+[[bench]]
+name = "drift_bench"
+harness = false

crates/ruvector-drift/benches/drift_bench.rs

@@ -0,0 +1,85 @@
+use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion};
+use rand::{rngs::SmallRng, SeedableRng};
+use rand_distr::{Distribution, Normal};
+use ruvector_drift::{
+    centroid::CentroidDriftDetector, graph::GraphDriftDetector, mmd::MmdDriftDetector,
+    DriftDetector,
+};
+
+fn make_vecs(n: usize, dims: usize, mean: f32, seed: u64) -> Vec<Vec<f32>> {
+    let mut rng = SmallRng::seed_from_u64(seed);
+    let dist = Normal::new(mean, 1.0f32).unwrap();
+    (0..n)
+        .map(|_| (0..dims).map(|_| dist.sample(&mut rng)).collect())
+        .collect()
+}
+
+fn bench_observe(c: &mut Criterion) {
+    let mut group = c.benchmark_group("observe_latency");
+
+    for dims in [64usize, 128, 256] {
+        let ref_data = make_vecs(500, dims, 0.0, 1);
+        let query = make_vecs(1, dims, 0.0, 99);
+        let v = &query[0];
+
+        let sigma = (dims as f32).sqrt();
+
+        group.bench_with_input(BenchmarkId::new("centroid", dims), &dims, |b, _| {
+            let mut det = CentroidDriftDetector::new(&ref_data, 200, 0.3);
+            b.iter(|| det.observe(criterion::black_box(v)));
+        });
+
+        group.bench_with_input(BenchmarkId::new("mmd-rff/D=128", dims), &dims, |b, _| {
+            let mut det = MmdDriftDetector::new(&ref_data, 128, sigma, 200, 0.05);
+            b.iter(|| det.observe(criterion::black_box(v)));
+        });
+
+        group.bench_with_input(BenchmarkId::new("graph-knn/k=7", dims), &dims, |b, _| {
+            let ref_small = make_vecs(100, dims, 0.0, 1);
+            let mut det = GraphDriftDetector::new(&ref_small, 7, 50, 0.25);
+            b.iter(|| det.observe(criterion::black_box(v)));
+        });
+    }
+
+    group.finish();
+}
+
+fn bench_report(c: &mut Criterion) {
+    let mut group = c.benchmark_group("report_latency");
+    let dims = 128;
+
+    let ref_data = make_vecs(500, dims, 0.0, 1);
+    let query = make_vecs(100, dims, 1.0, 77);
+
+    group.bench_function("centroid/report", |b| {
+        let mut det = CentroidDriftDetector::new(&ref_data, 200, 0.3);
+        for v in &query {
+            det.observe(v);
+        }
+        b.iter(|| det.report());
+    });
+
+    group.bench_function("mmd-rff/report", |b| {
+        let sigma = (dims as f32).sqrt();
+        let mut det = MmdDriftDetector::new(&ref_data, 128, sigma, 200, 0.05);
+        for v in &query {
+            det.observe(v);
+        }
+        b.iter(|| det.report());
+    });
+
+    group.bench_function("graph-knn/report", |b| {
+        let ref_small = make_vecs(100, dims, 0.0, 1);
+        let cur = make_vecs(50, dims, 1.0, 77);
+        let mut det = GraphDriftDetector::new(&ref_small, 7, 50, 0.25);
+        for v in &cur {
+            det.observe(v);
+        }
+        b.iter(|| det.report());
+    });
+
+    group.finish();
+}
+
+criterion_group!(benches, bench_observe, bench_report);
+criterion_main!(benches);