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175 lines
9 KiB
Markdown
175 lines
9 KiB
Markdown
# Apache Airflow — Guardrails and Fix Patterns
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<details>
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<summary><strong>🧭 Quick Return to Map</strong></summary>
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<br>
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> You are in a sub-page of **Automation Platforms**.
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> To reorient, go back here:
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>
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> - [**Automation Platforms** — stabilize no-code workflows and integrations](./README.md)
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> - [**WFGY Global Fix Map** — main Emergency Room, 300+ structured fixes](../README.md)
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> - [**WFGY Problem Map 1.0** — 16 reproducible failure modes](../../README.md)
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>
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> Think of this page as a desk within a ward.
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> If you need the full triage and all prescriptions, return to the Emergency Room lobby.
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</details>
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Use this when your workflow is orchestrated by **Apache Airflow** (DAGs with PythonOperators, Sensors, KubernetesPodOperator, etc.). If pipelines succeed but the **answers are wrong**, citations miss, or behavior differs between **ad-hoc runs** and **scheduled runs**, anchor your diagnosis here.
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**Acceptance targets**
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- ΔS(question, retrieved) ≤ 0.45
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- Coverage ≥ 0.70 to the intended section or record
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- λ stays convergent across 3 paraphrases
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---
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## Typical breakpoints → exact fixes
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- Output sounds right but cites the wrong snippet/section
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Fix No.1: **Hallucination & Chunk Drift** →
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[Hallucination](https://github.com/onestardao/WFGY/blob/main/ProblemMap/hallucination.md) ·
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[Retrieval Playbook](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md)
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- High vector similarity yet wrong meaning
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Fix No.5: **Embedding ≠ Semantic** →
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[Embedding ≠ Semantic](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md)
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- Facts are indexed but never show up in top-k (prod vs. local)
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Pattern: **Vectorstore Fragmentation** →
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[Vectorstore Fragmentation](https://github.com/onestardao/WFGY/blob/main/ProblemMap/patterns/pattern_vectorstore_fragmentation.md)
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- “Why this snippet?” is untraceable across tasks/pods
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Fix No.8: **Retrieval Traceability** + snippet/citation schema →
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[Retrieval Traceability](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md) ·
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[Data Contracts](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md)
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- Long multi-task chains drift or flatten over time
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Fix No.3/No.9: **Context Drift** and **Entropy Collapse** →
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[Context Drift](https://github.com/onestardao/WFGY/blob/main/ProblemMap/context-drift.md) ·
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[Entropy Collapse](https://github.com/onestardao/WFGY/blob/main/ProblemMap/entropy-collapse.md)
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- DAG runs succeed but first “cold start” call fails after deploy
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Infra family: **Pre-Deploy / Bootstrap / Deadlock** →
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[Pre-Deploy Collapse](https://github.com/onestardao/WFGY/blob/main/ProblemMap/predeploy-collapse.md) ·
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[Bootstrap Ordering](https://github.com/onestardao/WFGY/blob/main/ProblemMap/bootstrap-ordering.md) ·
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[Deployment Deadlock](https://github.com/onestardao/WFGY/blob/main/ProblemMap/deployment-deadlock.md)
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- Confident tone with wrong claims
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Fix No.4: **Bluffing / Overconfidence** →
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[Bluffing](https://github.com/onestardao/WFGY/blob/main/ProblemMap/bluffing.md)
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---
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## Minimal Airflow pattern with WFGY checks
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A compact pattern that preserves **cite-first schema**, **observable retrieval**, and **ΔS/λ** validation across tasks and pods.
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```txt
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Task A — Ingest/OCR (PythonOperator or KubernetesPodOperator)
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- Normalize PDFs/images. Drop low-confidence OCR lines.
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- Emit: doc_id, section_id, text, anchors
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Task B — Chunk & Index (PythonOperator)
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- Semantic chunking by section/sentence. Unit-normalize embeddings.
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- Persist with explicit metric flag (cosine vs inner product).
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Task C — Retrieve (PythonOperator)
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- Input: { question, k }
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- Output: snippets[] = { snippet_id, text, source, section_id }
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- Store in durable cache keyed by run_id/request_id.
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Task D — Assemble & Call LLM (PythonOperator)
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SYSTEM:
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Cite lines before explanation. Per-source fences. No cross-section reuse.
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CONTEXT:
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<joined snippets with snippet_id + source + text>
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QUESTION:
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<user question>
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Task E — WFGY Post-check (PythonOperator)
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- Body: { question, context, answer }
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- Compute ΔS and λ; measure coverage.
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- Emit: { deltaS, lambda, coverage, notes }
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Task F — Gate & Notify (BranchPythonOperator)
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IF deltaS ≥ 0.60 OR lambda != "→"
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→ route to remediation with trace table (snippet_id↔citation)
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ELSE
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→ deliver { answer, citations[], deltaS, lambda, coverage }
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````
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Reference specs:
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[RAG Architecture & Recovery](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rag-architecture-and-recovery.md) ·
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[Retrieval Playbook](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md) ·
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[Retrieval Traceability](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md) ·
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[Data Contracts](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md)
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---
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## Airflow-specific gotchas
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* **K8sPodOperator image skew**: embeddings or tokenizers differ between images. Pin exact versions and verify unit normalization at write/read.
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See [Embedding ≠ Semantic](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md)
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* **Race between retriever warm-up and first LLM call**: scheduled runs start before vectorstore is hydrated. Add bootstrap fences and health checks.
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See [Bootstrap Ordering](https://github.com/onestardao/WFGY/blob/main/ProblemMap/bootstrap-ordering.md) ·
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[Pre-Deploy Collapse](https://github.com/onestardao/WFGY/blob/main/ProblemMap/predeploy-collapse.md)
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* **Unbounded prompt assembly** inside operators: prompt fields drift. Centralize schema in one utility and import it across tasks to keep order stable.
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See [Retrieval Traceability](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md)
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* **Large artifacts in XCom**: truncate prompts or lose attachments. Store blobs (snippets, PDFs) in object storage; pass only `request_id` through XCom.
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* **MMR/rerank differences** by environment: ensure identical tokenizer/analyzer across retriever and reranker, then lock ordering after per-source ΔS ≤ 0.50.
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See [Rerankers](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rerankers.md)
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---
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## When to escalate
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* ΔS remains ≥ 0.60 after chunk/retrieval fixes → rebuild index with explicit metric flag, verify cosine vs. IP end-to-end, and re-probe ΔS vs k (aim ≤ 0.45).
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[Retrieval Playbook](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md)
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* Session-to-session flips between backfills and scheduled runs → stamp and check `mem_rev`/`mem_hash` and pin image digests per task.
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[Patterns: Memory Desync](https://github.com/onestardao/WFGY/blob/main/ProblemMap/patterns/pattern_memory_desync.md)
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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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<!-- WFGY_FOOTER_START -->
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### Explore More
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| Layer | Page | What it’s for |
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| --- | --- | --- |
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| Proof | [WFGY Recognition Map](/recognition/README.md) | External citations, integrations, and ecosystem proof |
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| Engine | [WFGY 1.0](/legacy/README.md) | Original PDF based tension engine |
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| Engine | [WFGY 2.0](/core/README.md) | Production tension kernel and math engine for RAG and agents |
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| Engine | [WFGY 3.0](/TensionUniverse/EventHorizon/README.md) | TXT based Singularity tension engine, 131 S class set |
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| Map | [Problem Map 1.0](/ProblemMap/README.md) | Flagship 16 problem RAG failure checklist and fix map |
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| Map | [Problem Map 2.0](/ProblemMap/rag-architecture-and-recovery.md) | RAG focused recovery pipeline |
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| Map | [Problem Map 3.0](/ProblemMap/wfgy-rag-16-problem-map-global-debug-card.md) | Global Debug Card, image as a debug protocol layer |
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| Map | [Semantic Clinic](/ProblemMap/SemanticClinicIndex.md) | Symptom to family to exact fix |
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| Map | [Grandma’s Clinic](/ProblemMap/GrandmaClinic/README.md) | Plain language stories mapped to Problem Map 1.0 |
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| Onboarding | [Starter Village](/StarterVillage/README.md) | Guided tour for newcomers |
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| App | [TXT OS](/OS/README.md) | TXT semantic OS, fast boot |
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| App | [Blah Blah Blah](/OS/BlahBlahBlah/README.md) | Abstract and paradox Q and A built on TXT OS |
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| App | [Blur Blur Blur](/OS/BlurBlurBlur/README.md) | Text to image with semantic control |
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| App | [Blow Blow Blow](/OS/BlowBlowBlow/README.md) | Reasoning game engine and memory demo |
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If this repository helped, starring it improves discovery so more builders can find the docs and tools.
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[](https://github.com/onestardao/WFGY)
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<!-- WFGY_FOOTER_END -->
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