📒 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.
🤔 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 |
🛡️ 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 |
✅ |
✍️ 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
🛠 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 |
📊 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 |
📝 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.
🔗 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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