Eval Drift — Guardrails and Fix Pattern

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When evaluation metrics swing unpredictably across runs (precision, recall, ΔS, coverage) even though the data and index appear unchanged.
This signals eval drift: your evaluation harness is not structurally stable.

Open these first

Recovery overview: RAG Architecture & Recovery
Retrieval knobs: Retrieval Playbook
Eval acceptance rules: Eval — Quality & Readiness Gates
Precision & recall contract: Eval RAG Precision/Recall
Ordering control: Bootstrap Ordering
Pre-deploy safety: Predeploy Collapse

Core acceptance

ΔS(question, retrieved) ≤ 0.45 across 3 paraphrases
Coverage ≥ 0.70 per target section
λ convergent on 2 seeds, stable across runs
Variance of metrics ≤ 0.05 across replays

Typical symptoms → exact fix

Symptom	Likely cause	Open this
Precision/recall varies ±0.20 each run	eval harness non-deterministic	Eval Precision/Recall
Identical queries give different metrics	bootstrap not fenced	Bootstrap Ordering
Eval metrics collapse on fresh deploy	index not fully warmed	Predeploy Collapse
Coverage < 0.50 despite gold answers	embedding or chunk drift	Embedding ≠ Semantic, Chunking Checklist

Fix in 60 seconds

Lock seeds
Fix random seeds at retrieval, reranker, and eval harness layers.
Fence bootstrap
Require VECTOR_READY==true and index hash match before eval begins.
Replay 3 paraphrases
Eval the same question with 3 paraphrases. Require ΔS variance < 0.05.
Cross-seed check
Run two seeds. λ must remain convergent across both.
Regression gate
Ship only if coverage ≥ 0.70 and precision/recall stable within 0.05.

Copy-paste eval harness snippet

def eval_guardrails(question, retrieved, gold):
    ds_qr = deltaS(question, retrieved)
    ds_rg = deltaS(retrieved, gold)

    assert ds_qr <= 0.45, "ΔS drift detected"
    assert coverage(retrieved, gold) >= 0.70, "Coverage too low"
    assert lambda_state(retrieved) in {"→","←","<>"} , "λ divergent"

    return {
        "ΔS_qr": ds_qr,
        "ΔS_rg": ds_rg,
        "coverage": coverage(retrieved, gold),
        "λ": lambda_state(retrieved)
    }

Diagnostic probes

Re-run variance test: run eval 5 times, log precision/recall. Stddev >0.05 → unstable harness.
Anchor comparison: compare ΔS to gold anchor vs decoy. If both similar, re-embed.
Deploy warm-up: log VECTOR_READY and index hash before eval.

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