WFGY/ProblemMap/GlobalFixMap/DocumentAI_OCR/azure_ocr.md

# Azure OCR (Computer Vision): 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>


Use this page when **Azure OCR** (part of Azure Cognitive Services / Computer Vision) drives ingestion for PDFs, scanned images, or mixed-language docs.  
Typical failures involve layout instability, multilingual tokenization errors, or coverage gaps in table/handwriting recognition.

---

## 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)  
- Hallucination and drift: [Context Drift](https://github.com/onestardao/WFGY/blob/main/ProblemMap/context-drift.md), [Hallucination](https://github.com/onestardao/WFGY/blob/main/ProblemMap/hallucination.md)  
- Chunk stability: [Chunking Checklist](https://github.com/onestardao/WFGY/blob/main/ProblemMap/chunking-checklist.md)  

---

## Core acceptance
- ΔS(question, retrieved) ≤ 0.45  
- Coverage ≥ 0.70 to target section  
- λ convergent across 3 paraphrases and 2 seeds  
- Multilingual tokens ≥ 90% fidelity (baseline against source)  

---

## Typical breakpoints → structural fix
- **Language mixing errors** (Chinese + English, Arabic + Latin text)  
  → [Embedding ≠ Semantic](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md), [Chunking Checklist](https://github.com/onestardao/WFGY/blob/main/ProblemMap/chunking-checklist.md)

- **Table recognition drops column anchors**  
  → [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)

- **Handwriting recognition unstable across runs**  
  → [Entropy Collapse](https://github.com/onestardao/WFGY/blob/main/ProblemMap/entropy-collapse.md)

- **ΔS > 0.60 when OCR normalizes accents/diacritics**  
  → [Context Drift](https://github.com/onestardao/WFGY/blob/main/ProblemMap/context-drift.md), clamp with BBAM  

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

---

## Fix in 60 seconds
1. **Measure ΔS** between OCR tokens and reference text.  
2. **Enforce schema**: page, block, line, word. Require `bbox` and language tag.  
3. **Cross-check coverage**: at least 70% of expected lines present.  
4. **Apply λ probes** — vary recognition mode (printed, handwriting, mixed).  
5. **Clamp variance** with BBAM if multilingual drift repeats.  

---

## Copy-paste LLM guard prompt

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

OCR provider: Azure OCR (Computer Vision).  
Symptoms: unstable multilingual recognition, ΔS ≥ 0.60, coverage < 0.70.

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

---

## When to escalate

* Multilingual drift remains after re-chunking → verify with [Embedding ≠ Semantic](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md).
* Tables drop anchors repeatedly → rebuild layout with [Data Contracts](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md).
* Handwriting ΔS unstable across seeds → clamp with BBAM, audit using [Entropy Collapse](https://github.com/onestardao/WFGY/blob/main/ProblemMap/entropy-collapse.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 |

---

### 🧭 Explore More

| Module                   | Description                                                                  | Link                                                                                               |
| ------------------------ | ---------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------- |
| 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)                              |
| Problem Map 1.0          | Initial 16-mode diagnostic and symbolic fix framework                        | [View →](https://github.com/onestardao/WFGY/tree/main/ProblemMap/README.md)                        |
| 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) |
| Semantic Clinic Index    | Expanded failure catalog: prompt injection, memory bugs, logic drift         | [View →](https://github.com/onestardao/WFGY/blob/main/ProblemMap/SemanticClinicIndex.md)           |
| Semantic Blueprint       | Layer-based symbolic reasoning & semantic modulations                        | [View →](https://github.com/onestardao/WFGY/tree/main/SemanticBlueprint/README.md)                 |
| 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)      |
| 🧙‍♂️ 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)                   |

---

> 👑 **Early Stargazers: [See the Hall of Fame](https://github.com/onestardao/WFGY/tree/main/stargazers)** —
> Engineers, hackers, and open source builders who supported WFGY from day one.

> <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).

<div align="center">

[![WFGY Main](https://img.shields.io/badge/WFGY-Main-red?style=flat-square)](https://github.com/onestardao/WFGY)
 
[![TXT OS](https://img.shields.io/badge/TXT%20OS-Reasoning%20OS-orange?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS)
 
[![Blah](https://img.shields.io/badge/Blah-Semantic%20Embed-yellow?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS/BlahBlahBlah)
 
[![Blot](https://img.shields.io/badge/Blot-Persona%20Core-green?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS/BlotBlotBlot)
 
[![Bloc](https://img.shields.io/badge/Bloc-Reasoning%20Compiler-blue?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS/BlocBlocBloc)
 
[![Blur](https://img.shields.io/badge/Blur-Text2Image%20Engine-navy?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS/BlurBlurBlur)
 
[![Blow](https://img.shields.io/badge/Blow-Game%20Logic-purple?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS/BlowBlowBlow)
 

</div>


要不要我接著直接幫你寫 **abbyy.md**？這樣 OCR 四大主流 (Tesseract、Google、AWS、Azure + ABBYY) 就全到齊。