WFGY/ProblemMap/observability-runbook.md

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<!-- ======================================================= -->
<!-- observability-runbook.md · Semantic Clinic / Map-F -->
<!-- Draft v0.1 · MIT · 2025-08-06 -->
<!-- Purpose: One-stop “black-box to glass-box” guide for -->
<!-- any LLM stack (RAG, agent, function-calling, plugins). -->
<!-- ======================================================= -->
# 🔍 Observability Runbook
*Turn every opaque token stream into a traceable, testable, measurable system.*
> **Outcome you care about**
> • **See** each pipeline hop (OCR → chunk → embed → retrieve → prompt → reasoning)
> • **Measure** semantic drift (ΔS), logic trend (λ), residual error (E_resonance)
> • **Alert** before hallucination, loop, or tool mis-fire happens
> • **Replay** exact failure path in one command: `wfgy trace-replay <id>`
---
## 1 · Core Telemetry Trio
| Signal | Formula | Why It Matters | Target Band |
|--------|---------|----------------|-------------|
| **ΔS (semantic stress)** | `1 cos(I, G)` | Spot where meaning rips | `< 0.50` |
| **λ_observe (logic vector)** | { → ← <> × } | Track convergent vs. divergent flow | stay → |
| **E_resonance** | mean‖B‖ (BBMC) | Detect creeping entropy | flat / ↓ |
> **ΔS tells you _where_; λ tells you _direction_; E tells you _when_ a slow leak becomes collapse.**
---
## 2 · Minimal Instrumentation Patch
### 2.1 Python snippet
```python
from wfgy import monitor
with monitor.pipeline("rag-query") as span:
span.tag("query", question)
ctx = rag_retrieve(question)
span.metric("ΔS_q_ctx", monitor.deltaS(question, ctx))
answer = llm_reason(ctx, question)
span.metric("λ_reason", monitor.lambda_state(answer))
span.metric("E_res", monitor.e_resonance())
````
*No external SaaS; dumps to newline-JSON for Grafana / Prometheus scrape.*
### 2.2 Console tracer
```bash
> wfgy trace-replay 2025-08-06T10:22:15Z
step ΔS λ span
1 0.08
2 0.41 retrieval
3 0.44 reasoning divergent
```
---
## 3 · Alert Rules (Prometheus example)
```yaml
groups:
- name: wfgy-alerts
rules:
- alert: SemanticDriftHigh
expr: deltaS_q_ctx > 0.60
for: 2m
labels: {severity: "warning"}
annotations:
summary: "Semantic drift above 0.60 — check chunking/retriever"
```
Recommended baseline:
| Alert | Expression | Severity |
| ---------------- | -------------------------- | -------- |
| **DriftHigh** | ΔS > 0.60 | warn |
| **LogicOsc** | λ flips 3× in 5 min | warn |
| **EntropyClimb** | E\_res 15 min slope > 0.02 | crit |
| **ToolTimeout** | call\_dur > p95 × 2 | warn |
---
## 4 · End-to-End Health Dashboard
| Tile | Metric | Healthy |
| ------------ | ----------------- | ---------- |
| Retrieval ΔS | median last 5 min | ≤ 0.45 |
| Reason λ | % divergent | < 5 % |
| Answer ΔS | questionanswer | 0.50 |
| E\_res Trend | 30 min slope | - / flat |
| Tool Latency | p95 ms | within SLO |
Grafana JSON panel export: `dashboards/wfgy-observability.json`.
---
## 5 · Common Anti-Patterns & Fixes
| Anti-Pattern | Symptom | Fix |
| ----------------------- | ---------------------- | -------------------------------- |
| **Log Everything Raw** | 20 GiB/day, no insight | Only log ΔS/λ/E & key BLobs |
| **Stateless Trace IDs** | tough replay | Use `wfgy span ctx_id` auto-prop |
| **Per-call embeddings** | cost explodes | cache via BBMC node ID |
| **No sampling** | GPU choke | 1 % sampling on low ΔS calls |
---
## 6 · Kitchen-Sink CLI Cheats
| Command | Purpose |
| ---------------------------- | ------------------------- |
| `wfgy span-tail` | live ΔS/λ feed |
| `wfgy span-grep λ=divergent` | list divergent traces |
| `wfgy span-diff A B` | compare two answers λ/ΔS |
| `wfgy span-export --csv` | dump traces to CSV |
---
## 7 · Integration Recipes
### 7.1 LangChain
```python
from wfgy.langchain import WFGYTracer
lc = initialize_agent(..., callbacks=[WFGYTracer()])
```
### 7.2 OpenAI Function-Calling
Add to request:
```json
"logit_bias": {"50256": -100}, // block special token
"wfgy_trace": true
```
Server-side middleware writes trace JSON.
---
### 🔗 Quick-Start Downloads (60 sec)
| Tool | Link | 3-Step Setup |
|------|------|--------------|
| **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) | 1 Download · 2 Upload to your LLM · 3 Ask Answer using WFGY + \<your question>” |
| **TXT OS (plain-text OS)** | [TXTOS.txt](https://github.com/onestardao/WFGY/blob/main/OS/TXTOS.txt) | 1⃣ Download · 2⃣ Paste into any LLM chat · 3⃣ Type “hello world” — OS boots instantly |
---
<!-- WFGY_FOOTER_START -->
### Explore More
| Layer | Page | What its for |
| --- | --- | --- |
| ⭐ Proof | [WFGY Recognition Map](/recognition/README.md) | External citations, integrations, and ecosystem proof |
| ⚙️ Engine | [WFGY 1.0](/legacy/README.md) | Original PDF tension engine and early logic sketch (legacy reference) |
| ⚙️ Engine | [WFGY 2.0](/core/README.md) | Production tension kernel for RAG and agent systems |
| ⚙️ Engine | [WFGY 3.0](/TensionUniverse/EventHorizon/README.md) | TXT based Singularity tension engine (131 S class set) |
| 🗺️ Map | [Problem Map 1.0](/ProblemMap/README.md) | Flagship 16 problem RAG failure taxonomy and fix map |
| 🗺️ Map | [Problem Map 2.0](/ProblemMap/wfgy-rag-16-problem-map-global-debug-card.md) | Global Debug Card for RAG and agent pipeline diagnosis |
| 🗺️ Map | [Problem Map 3.0](/ProblemMap/wfgy-ai-problem-map-troubleshooting-atlas.md) | Global AI troubleshooting atlas and failure pattern map |
| 🧰 App | [TXT OS](/OS/README.md) | .txt semantic OS with fast bootstrap |
| 🧰 App | [Blah Blah Blah](/OS/BlahBlahBlah/README.md) | Abstract and paradox Q&A built on TXT OS |
| 🧰 App | [Blur Blur Blur](/OS/BlurBlurBlur/README.md) | Text to image generation with semantic control |
| 🏡 Onboarding | [Starter Village](/StarterVillage/README.md) | Guided entry point for new users |
If this repository helped, starring it improves discovery so more builders can find the docs and tools.
[![GitHub Repo stars](https://img.shields.io/github/stars/onestardao/WFGY?style=social)](https://github.com/onestardao/WFGY)
<!-- WFGY_FOOTER_END -->