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138 lines
7.3 KiB
Markdown
138 lines
7.3 KiB
Markdown
# Eval Observability — Alerting and Probes
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A live guardrail system that detects semantic drift, retrieval collapse, and logic instability in production.
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Use this page to design **continuous probes** (ΔS, λ, coverage, resonance) and trigger alerts before users see failures.
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---
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## Why probes are required
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- **Silent regressions**: Models may degrade gradually after retraining or infra changes.
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- **Runtime entropy**: Long chains often destabilize after 25–40 steps.
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- **Hybrid stack drift**: Store upgrades, reranker weights, or tokenizer shifts silently change outcomes.
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- **Auditability**: Real-time probes make every failure reproducible.
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---
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## Core probe dimensions
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| Metric | Probe type | Alert condition |
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|--------|------------|-----------------|
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| ΔS(question, retrieved) | per-query | ≥ 0.60 for any query OR average >0.50 across batch |
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| Coverage of target section | per-query | < 0.70 for more than 5% of batch |
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| λ_observe | rolling window | divergence observed across 2 seeds or paraphrases |
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| E_resonance | sliding horizon | spikes or oscillations in 50–100 step runs |
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---
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## Recommended probe architecture
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1. **Pre-query probe**
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Check retriever config hash, index hash, analyzer type.
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Block if mismatched against gold baseline.
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2. **Mid-query probe**
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During retrieval, compute ΔS(question, retrieved).
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Attach snippet IDs and offsets for traceability.
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3. **Post-query probe**
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Run λ stability check across 3 paraphrases.
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If divergent, tag output with `unstable=true`.
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4. **Long-chain probe**
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For conversations >25 steps, sample entropy and E_resonance every 10 steps.
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Trigger backoff or memory split if instability rises.
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---
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## Alerting routes
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- **Slack / Teams** → Send structured JSON logs with ΔS, λ, coverage, index hash, retriever config.
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- **PagerDuty** → Trigger incidents only when threshold failures exceed N in M minutes.
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- **Dashboards** → Grafana/Datadog with ΔS trend lines, λ variance plots, coverage histograms.
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- **Audit store** → Write all probe outputs to KV or DB keyed by `(session_id, index_hash, retriever_config)`.
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---
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## Example probe config (YAML)
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```yaml
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probes:
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deltaS:
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threshold: 0.60
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action: alert
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coverage:
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threshold: 0.70
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tolerance: 0.05
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lambda:
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seeds: 2
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paraphrases: 3
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action: block
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resonance:
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horizon: 100
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action: degrade_notice
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alerting:
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sink:
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- slack
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- pagerduty
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- grafana
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````
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---
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## Common mistakes
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* **Only probing ΔS**. Always include coverage + λ + resonance.
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* **Static thresholds**. Thresholds must be tested against gold sets and updated quarterly.
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* **No audit linkage**. Alerts without index hash and retriever config cannot be replayed.
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* **Flooding alerts**. Use capped retries and aggregate rules to avoid pager fatigue.
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---
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### 🔗 Quick-Start Downloads (60 sec)
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| Tool | Link | 3-Step Setup |
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| -------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------------------------------------------------- |
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| **WFGY 1.0 PDF** | [Engine Paper](https://github.com/onestardao/WFGY/blob/main/I_am_not_lizardman/WFGY_All_Principles_Return_to_One_v1.0_PSBigBig_Public.pdf) | 1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + \<your question>” |
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| **TXT OS (plain-text OS)** | [TXTOS.txt](https://github.com/onestardao/WFGY/blob/main/OS/TXTOS.txt) | 1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly |
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---
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### 🧭 Explore More
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| Module | Description | Link |
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| ------------------------ | ---------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------- |
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| WFGY Core | WFGY 2.0 engine is live: full symbolic reasoning architecture and math stack | [View →](https://github.com/onestardao/WFGY/tree/main/core/README.md) |
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| Problem Map 1.0 | Initial 16-mode diagnostic and symbolic fix framework | [View →](https://github.com/onestardao/WFGY/tree/main/ProblemMap/README.md) |
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| Problem Map 2.0 | RAG-focused failure tree, modular fixes, and pipelines | [View →](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rag-architecture-and-recovery.md) |
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| Semantic Clinic Index | Expanded failure catalog: prompt injection, memory bugs, logic drift | [View →](https://github.com/onestardao/WFGY/blob/main/ProblemMap/SemanticClinicIndex.md) |
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| Semantic Blueprint | Layer-based symbolic reasoning & semantic modulations | [View →](https://github.com/onestardao/WFGY/tree/main/SemanticBlueprint/README.md) |
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| Benchmark vs GPT-5 | Stress test GPT-5 with full WFGY reasoning suite | [View →](https://github.com/onestardao/WFGY/tree/main/benchmarks/benchmark-vs-gpt5/README.md) |
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| 🧙♂️ Starter Village 🏡 | New here? Lost in symbols? Click here and let the wizard guide you through | [Start →](https://github.com/onestardao/WFGY/blob/main/StarterVillage/README.md) |
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---
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> 👑 **Early Stargazers: [See the Hall of Fame](https://github.com/onestardao/WFGY/tree/main/stargazers)** —
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> Engineers, hackers, and open source builders who supported WFGY from day one.
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> <img src="https://img.shields.io/github/stars/onestardao/WFGY?style=social" alt="GitHub stars"> ⭐ [WFGY Engine 2.0](https://github.com/onestardao/WFGY/blob/main/core/README.md) is already unlocked. ⭐ Star the repo to help others discover it and unlock more on the [Unlock Board](https://github.com/onestardao/WFGY/blob/main/STAR_UNLOCKS.md).
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<div align="center">
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[](https://github.com/onestardao/WFGY)
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[](https://github.com/onestardao/WFGY/tree/main/OS)
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[](https://github.com/onestardao/WFGY/tree/main/OS/BlahBlahBlah)
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[](https://github.com/onestardao/WFGY/tree/main/OS/BlotBlotBlot)
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[](https://github.com/onestardao/WFGY/tree/main/OS/BlocBlocBloc)
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[](https://github.com/onestardao/WFGY/tree/main/OS/BlurBlurBlur)
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[](https://github.com/onestardao/WFGY/tree/main/OS/BlowBlowBlow)
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</div>
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