WFGY/ProblemMap/GlobalFixMap/RAG/eval_drift.md

Eval Drift — Guardrails and Fix Pattern

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.

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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

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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

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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

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Fix in 60 seconds

1. Lock seeds
   Fix random seeds at retrieval, reranker, and eval harness layers.

2. Fence bootstrap
   Require VECTOR_READY==true and index hash match before eval begins.

3. Replay 3 paraphrases
   Eval the same question with 3 paraphrases. Require ΔS variance < 0.05.

4. Cross-seed check
   Run two seeds. λ must remain convergent across both.

5. Regression gate
   Ship only if coverage ≥ 0.70 and precision/recall stable within 0.05.

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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)
    }

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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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🧭 Explore More

Module	Description	Link
WFGY Core	WFGY 2.0 engine is live: full symbolic reasoning architecture and math stack	View →
Problem Map 1.0	Initial 16-mode diagnostic and symbolic fix framework	View →
Problem Map 2.0	RAG-focused failure tree, modular fixes, and pipelines	View →
Semantic Clinic Index	Expanded failure catalog: prompt injection, memory bugs, logic drift	View →
Semantic Blueprint	Layer-based symbolic reasoning & semantic modulations	View →
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