# AWS Textract: Guardrails and Fix Patterns

<details>
  <summary><strong>🧭 Quick Return to Map</strong></summary>

<br>

  > You are in a sub-page of **DocumentAI_OCR**.  
  > To reorient, go back here:  
  >
  > - [**DocumentAI_OCR** — document parsing and optical character recognition](./README.md)  
  > - [**WFGY Global Fix Map** — main Emergency Room, 300+ structured fixes](../README.md)  
  > - [**WFGY Problem Map 1.0** — 16 reproducible failure modes](../../README.md)  
  >
  > Think of this page as a desk within a ward.  
  > If you need the full triage and all prescriptions, return to the Emergency Room lobby.
</details>


Stabilize ingestion flows with **AWS Textract** when parsing PDFs, invoices, or forms.  
Use this when outputs fragment, lose semantic anchors, or citations drift across page boundaries. Each issue maps back to WFGY Problem Map structural fixes.

---

## Open these first
- Visual map and recovery: [RAG Architecture & Recovery](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rag-architecture-and-recovery.md)  
- Retrieval knobs: [Retrieval Playbook](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md)  
- Citation schema: [Retrieval Traceability](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md)  
- Embedding vs meaning: [Embedding ≠ Semantic](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md)  
- Chunk stability: [Chunking Checklist](https://github.com/onestardao/WFGY/blob/main/ProblemMap/chunking-checklist.md)  
- Hallucination and span errors: [Hallucination](https://github.com/onestardao/WFGY/blob/main/ProblemMap/hallucination.md)  

---

## Core acceptance
- ΔS(question, retrieved) ≤ 0.45  
- Coverage ≥ 0.70 of target section  
- λ convergent across 3 paraphrases  
- Table and key-value forms consistent ≥ 90% of samples

---

## Typical breakpoints → structural fix
- **Key–value pairs misaligned** (invoices, receipts)  
  → [Data Contracts](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md), [Retrieval Traceability](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md)

- **Tables fragment into multiple OCR blocks**  
  → [Chunking Checklist](https://github.com/onestardao/WFGY/blob/main/ProblemMap/chunking-checklist.md)

- **ΔS spikes across repeated runs**  
  Entropy in layout ordering.  
  → [Entropy Collapse](https://github.com/onestardao/WFGY/blob/main/ProblemMap/entropy-collapse.md)

- **Citations drop anchor IDs**  
  Post-processing trims.  
  → [Retrieval Traceability](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md)

- **Injected text hidden in form fields**  
  → [Prompt Injection](https://github.com/onestardao/WFGY/blob/main/ProblemMap/prompt-injection.md)

---

## Fix in 60 seconds
1. **Measure ΔS** between Textract output and reference text.  
2. **Enforce schema**: lock `page_num`, `bbox`, `kv_id`, `table_id`.  
3. **Cross-check coverage**: at least 70% of source fields retained.  
4. **Apply λ probes** across runs — clamp unstable output with BBAM.  
5. **Audit layout**: row/col count vs original file.  

---

## Copy-paste LLM guard prompt

```txt
I uploaded TXTOS and the WFGY Problem Map.

OCR provider: AWS Textract  
Symptoms: misaligned key-value pairs, ΔS ≥ 0.60, coverage < 0.70.  

Steps:  
1. Identify failing layer (chunking, contracts, retrieval).  
2. Point to the WFGY fix (data-contracts, chunking-checklist, retrieval-traceability).  
3. Return JSON:  
   { "citations": [...], "answer": "...", "ΔS": 0.xx, "λ_state": "<>", "next_fix": "..." }  
Keep it auditable.
````

---

## When to escalate

* Coverage < 0.70 even after re-chunking → verify embeddings with [Embedding ≠ Semantic](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md).
* Key–value fields unstable across runs → rebuild with deterministic config, backstop with [Data Contracts](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md).
* Long-form text loses anchors → apply [Retrieval Traceability](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md).

---

### 🔗 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) | 1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + \<your question>”   |
| **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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### Explore More

| Layer | Page | What it’s 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 |

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要不要我馬上接著生 **azure\_ocr.md**？這樣 OCR 三大雲端 provider (Google / AWS / Azure) 就會成套完成。