Memory & Long-Context
March 6, 2026 · View on GitHub
🏥 Quick Return to Emergency Room
You are in a specialist desk.
For full triage and doctors on duty, return here:
- 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 sub-room.
If you want full consultation and prescriptions, go back to the Emergency Room lobby.
Stabilize long windows and multi-session memory.
This map helps you repair drift, collapse, forks, and ghost contexts when conversations or documents stretch far beyond the usual size.
What this page is
- A beginner-friendly checklist for long contexts and multi-day sessions.
- Copy-paste guardrails that stop drift and collapse before they spread.
- Concrete metrics with ΔS and λ_observe so you know if your system is stable.
When to use
- Dialog grows past 50k–100k tokens and answers degrade.
- Facts flip after tab refresh or model switch.
- Citations look right but reasoning goes flat or chaotic.
- OCR transcripts look fine but capitalization or spacing drift.
- Multi-day support threads lose task state or rewrite history.
Orientation: quick routes
| Page | What it solves | Typical symptom |
|---|---|---|
| memory-coherence.md | Memory fences & continuity | Threads repeat or contradict |
| entropy-collapse.md | Attention melt in long windows | Outputs drift into filler |
| context-drift.md | Long reasoning drift | Correct early, wrong later |
| pattern_memory_desync.md | Cross-tab & cache hazards | State flips after refresh |
| ghost-context.md | Stale buffers & residue | Model recalls “phantom” text |
| state-fork.md | Divergent memory forks | Same task_id, different answers |
| ocr-parsing-checklist.md, ocr-jitter.md | OCR-specific noise | Exported text drifts vs. original |
| retrieval-traceability.md, data-contracts.md | Traceability & audit | Citations break or vanish |
| chunking-checklist.md | Chunk stability at joins | Mid-sentence cuts or overlaps |
Acceptance targets
- Retrieval coverage ≥ 0.70 to the intended section
- ΔS(question, retrieved) ≤ 0.45 and joins ≤ 0.50
- λ_observe remains convergent across 3 paraphrases
- No state fork across tabs or agents for the same
task_id
60-second fix checklist
- Lock metrics — same analyzer & embeddings across sessions.
- Enforce memory fences — require
task_id,session_id, andsnippet_id. - Probe ΔS and λ — run 3 paraphrases × 2 seeds.
- Patch drift — realign chunks, re-check OCR, drop ghost spans.
- Audit consistency — run traceability logs and verify continuity across restarts.
🔗 Quick-Start Downloads (60 sec)
| Tool | Link | 3-Step Setup |
|---|---|---|
| WFGY 1.0 PDF | Engine Paper | 1️⃣ Download · 2️⃣ Upload · 3️⃣ Ask “Answer using WFGY + |
| TXT OS (plain-text OS) | TXTOS.txt | 1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly |
Explore More
| Layer | Page | What it’s for |
|---|---|---|
| ⭐ Proof | WFGY Recognition Map | External citations, integrations, and ecosystem proof |
| ⚙️ Engine | WFGY 1.0 | Original PDF tension engine and early logic sketch (legacy reference) |
| ⚙️ Engine | WFGY 2.0 | Production tension kernel for RAG and agent systems |
| ⚙️ Engine | WFGY 3.0 | TXT based Singularity tension engine (131 S class set) |
| 🗺️ Map | Problem Map 1.0 | Flagship 16 problem RAG failure taxonomy and fix map |
| 🗺️ Map | Problem Map 2.0 | Global Debug Card for RAG and agent pipeline diagnosis |
| 🗺️ Map | Problem Map 3.0 | Global AI troubleshooting atlas and failure pattern map |
| 🧰 App | TXT OS | .txt semantic OS with fast bootstrap |
| 🧰 App | Blah Blah Blah | Abstract and paradox Q&A built on TXT OS |
| 🧰 App | Blur Blur Blur | Text to image generation with semantic control |
| 🏡 Onboarding | Starter Village | Guided entry point for new users |
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