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ProblemMap/GlobalFixMap/DocumentAI_OCR/google_docai.md
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# Google Document AI OCR: Guardrails and Fix Patterns
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A compact guide to stabilize ingestion flows using **Google Cloud Document AI OCR**.
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Use this when PDF or scanned document parsing produces unstable tokens, missing tables, or broken citations. Each failure is mapped to a structural fix in the WFGY Problem Map.
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---
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## Open these first
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- Visual map and recovery: [RAG Architecture & Recovery](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rag-architecture-and-recovery.md)
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- End-to-end knobs: [Retrieval Playbook](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md)
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- Citation schema: [Retrieval Traceability](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md)
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- Embedding vs meaning: [Embedding ≠ Semantic](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md)
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- OCR text boundaries: [Chunking Checklist](https://github.com/onestardao/WFGY/blob/main/ProblemMap/chunking-checklist.md)
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- Injection and schema locks: [Prompt Injection](https://github.com/onestardao/WFGY/blob/main/ProblemMap/prompt-injection.md)
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---
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## Core acceptance
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- ΔS(question, retrieved) ≤ 0.45
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- Coverage ≥ 0.70 of target section
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- λ remains convergent across three paraphrases and two seeds
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- Table and form layout preserved in ≥ 85% of samples
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---
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## Typical breakpoints → structural fix
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- **Lost tables or merged columns**
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Payload schema drift.
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→ [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)
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- **OCR output differs across runs of the same PDF**
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Non-deterministic layout parse.
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→ [Chunking Checklist](https://github.com/onestardao/WFGY/blob/main/ProblemMap/chunking-checklist.md), [Entropy Collapse](https://github.com/onestardao/WFGY/blob/main/ProblemMap/entropy-collapse.md)
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- **Citations drop page anchors**
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Post-processing trims.
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→ [Retrieval Traceability](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md)
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- **Injection vectors inside scanned forms**
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Malicious text embedded in OCR’d images.
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→ [Prompt Injection](https://github.com/onestardao/WFGY/blob/main/ProblemMap/prompt-injection.md)
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---
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## Fix in 60 seconds
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1. **Measure ΔS** on OCR’d snippets vs reference text.
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2. **Lock schemas** with Data Contracts (force `page_num`, `bbox`, `tokens`).
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3. **Enforce cite-then-explain** at retrieval time.
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4. **Add λ probes** across multiple OCR calls — if divergent, clamp with BBAM.
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5. **Audit tables**: cross-check row count and column headers against source PDF.
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---
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## Copy-paste LLM guard prompt
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```txt
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I uploaded TXTOS and the WFGY Problem Map.
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OCR provider: Google Document AI
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Symptoms: lost tables, ΔS ≥ 0.60, λ diverges across 3 paraphrases.
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Steps:
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1. Identify which structural fix applies (chunking-checklist, data-contracts, retrieval-traceability).
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2. Return a JSON plan:
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{ "citations": [...], "answer": "...", "λ_state": "<>", "ΔS": 0.xx, "next_fix": "..." }
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Keep it auditable and short.
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````
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---
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## When to escalate
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* ΔS stays ≥ 0.60 even after chunk / schema fixes → rebuild pipeline with [Semantic Chunking Checklist](https://github.com/onestardao/WFGY/blob/main/ProblemMap/chunking-checklist.md).
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* Coverage < 0.70 across paraphrases → verify embeddings with [Embedding ≠ Semantic](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md).
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* Inconsistent runs across identical files → enforce deterministic parser config, or switch to dual-engine validation (DocAI + Tesseract).
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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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要不要我直接幫你下一步補 **aws\_textract.md**？這樣 OCR MVP 會更快成形。
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