PaddleOCR: Guardrails and Fix Patterns

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DocumentAI_OCR — document parsing and optical character recognition

WFGY Global Fix Map — main Emergency Room, 300+ structured fixes

WFGY Problem Map 1.0 — 16 reproducible failure modes

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.

Use this page when your stack integrates PaddleOCR (from Baidu PaddlePaddle).
It’s widely used for open-source OCR pipelines, especially in Chinese / multilingual contexts.
Common risks: unstable detection boxes, segmentation drift, and mixed-language confusion.

Open these first

Visual map and recovery: RAG Architecture & Recovery
End-to-end knobs: Retrieval Playbook
Traceability schema: Retrieval Traceability
Schema contracts: Data Contracts
Embedding vs meaning: Embedding ≠ Semantic
Chunking rules: Chunking Checklist
Injection risks: Prompt Injection

Core acceptance

ΔS(question, retrieved) ≤ 0.45
Coverage ≥ 0.70 across multilingual tokens
λ convergent across 3 paraphrases
BBox coverage ≥ 95% on gold set images

Typical breakpoints → structural fix

Chinese / English mix mis-segmented
→ Embedding ≠ Semantic, Data Contracts
Bounding boxes drift (word cropped or merged incorrectly)
→ Retrieval Traceability, enforce field anchors
Long text lines wrapped unpredictably
→ Chunking Checklist
Injected noise from non-text graphics
→ Prompt Injection
Low recall on handwriting or distorted fonts
→ Entropy Collapse

Fix in 60 seconds

Normalize text direction (LTR vs RTL) before feeding embeddings.
Apply schema: bbox, text, lang, confidence, rev_id.
Measure ΔS(question, retrieved). Threshold ≥ 0.60 → suspect segmentation or index.
Clamp λ with BBAM if paraphrases diverge.
Re-chunk with stride windows for multilingual pages.

Copy-paste guard prompt

I uploaded TXTOS and the WFGY Problem Map.

OCR provider: PaddleOCR.  
Symptoms: multilingual mis-segmentation, ΔS ≥ 0.60, bbox drift.

Steps:
1. Identify failing layer (chunk, retrieval, schema).  
2. Point to correct WFGY page.  
3. Return JSON:  
   { "bbox_checked": [...], "answer": "...", "ΔS": 0.xx, "λ_state": "<>", "next_fix": "..." }  
Keep it short, reproducible, auditable.

When to escalate

Persistent bbox drift → Retrieval Traceability
Schema mismatch across languages → Data Contracts
ΔS unstable across seeds → Embedding ≠ Semantic

🔗 Quick-Start Downloads (60 sec)

Tool	Link	3-Step Setup
WFGY 1.0 PDF	Engine Paper	1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + <your question>”
TXT OS (plain-text 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	Canonical framework entry point	View
Problem Map	Diagnostic map and navigation hub	View
Tension Universe Experiments	MVP experiment field	View
Recognition	Where WFGY is referenced or adopted	View
AI Guide	Anti-hallucination reading protocol for tools	View

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