WFGY/ProblemMap/LongContext_Problems.md

📒 Map-E · Long‑Context Stress Problem Map

Mega‑prompts—>100 k tokens, entire book dumps, OCR‑noisy PDFs—overwhelm ordinary LLM pipelines.
WFGY keeps reasoning stable with adaptive ΔS, chunk‑mapping, and sliding Tree windows.

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🤔 Typical Long‑Context Crashes

Stressor	What Standard Systems Do
100 k+ tokens	Memory wipe or truncated output
Mixed domains	Topic bleed, incoherent jumps
Duplicate sections	Infinite loops / “as mentioned above” spam
OCR noise	Hallucination or garbage sentences

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🛡️ WFGY Countermeasures

Stressor	WFGY Module	Remedy	Status
100 k+ tokens	Chunk‑Mapper + Sliding Tree	Splits doc into ΔS‑balanced chunks, streams into window	🛠 Beta
Mixed domains	Per‑domain ΔS fork	Separate Tree branch per domain; no bleed	✅
Duplicate sections	BBMC dedupe scan	Detects near‑identical residue, collapses	✅
PDF OCR noise	BBMC noise filter	Drops >80 % low‑entropy lines	✅

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✍️ Demo — 150 k‑Token PDF Dump

1️⃣  Start
> Start

2️⃣  Upload huge PDF text
> [paste or stream]

WFGY process:
• Chunk‑Mapper splits into 8 k‑token slices  
• For each slice: ΔS calc → Tree node → sliding window  
• Duplicate residue removed (413 sections merged)  
• OCR noise filtered (ΔS noise gate at 0.8)  
• Final summary or Q&A runs with stable context

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🛠 Module Cheat‑Sheet

Module	Role
Chunk‑Mapper	Adaptive split by semantic tension
Sliding Tree Window	Keeps only relevant slices active
ΔS Metric	Guides chunk size & window hop
BBMC	Dedupe + noise filter
BBPF	Forks domain branches if needed

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📊 Implementation Status

Feature	State
Chunk‑Mapper	🛠 Beta (public soon)
Sliding Tree window	✅ Stable
Cross‑domain fork	✅ Stable
OCR noise filter	✅ Stable
GUI chunk viewer	🔜 Planned

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📝 Tips & Limits

• For >150 k tokens, set chunk_max = 6k for faster pass.
• Use tree pause to inspect each domain branch before auto‑merge.
• Share monster PDFs in Discussions—they stress‑test Chunk‑Mapper.

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🔗 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

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🧭 Explore More

Module	Description	Link
WFGY Core	WFGY 2.0 engine is live: full symbolic reasoning architecture and math stack	View →
Problem Map 1.0	Initial 16-mode diagnostic and symbolic fix framework	View →
Problem Map 2.0	RAG-focused failure tree, modular fixes, and pipelines	View →
Semantic Clinic Index	Expanded failure catalog: prompt injection, memory bugs, logic drift	View →
Semantic Blueprint	Layer-based symbolic reasoning & semantic modulations	View →
Benchmark vs GPT-5	Stress test GPT-5 with full WFGY reasoning suite	View →
🧙‍♂️ Starter Village 🏡	New here? Lost in symbols? Click here and let the wizard guide you through	Start →

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Engineers, hackers, and open source builders who supported WFGY from day one.

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