🧭 Quick Return to Map
You are in a sub-page of MemoryLongContext.
To reorient, go back here:
- MemoryLongContext — extended context windows and memory retention
- 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.
Keep multi-turn and multi-session dialogs stable by fencing memory state.
This page shows how to prevent forks, desync, and ghost buffers when conversations span long contexts or multiple agents.
- Long support chats (~days) forget earlier task context.
- Model switches or tab refreshes flip prior facts.
- Two agents on the same ticket give inconsistent answers.
- OCR transcripts look fine but later steps rewrite history.
- Persona or role change contaminates state with old context.
- Each turn stamped with
mem_revandmem_hash. - No forks across sessions for the same
task_id. - ΔS(question, retrieved) ≤ 0.45 with joins ≤ 0.50.
- λ remains convergent across three paraphrases.
- All claims cite snippet_id, no orphans.
-
Stamp and fence
Requiremem_rev,mem_hash, andtask_idat every turn.
Forbid writes if stamps mismatch. -
Shard state
Partition prompts as{system | task | constraints | snippets | answer}.
Forbid snippet reuse across sections. -
Normalize consistently
Enforce Unicode NFC, strip zero width marks, unify full/half width.
Block OCR lines below confidence threshold. -
Recover forks
If two agents diverge, reconcile by ΔS triangulation and pick the lower-entropy path. -
Bridge collapse
Apply BBCR if attention melt or desync detected mid-chain.
- At turn start, echo {mem_rev, mem_hash, task_id}.
- If stamps mismatch, reject write and request sync.
- Split snippets by section, forbid cross-reuse.
- Normalize all inputs.
- Apply BBAM/BBCR if λ drifts or collapse appears.
- Verify ΔS(question, retrieved) ≤ 0.45 and joins ≤ 0.50.
You have TXT OS and the WFGY Problem Map.
Goal: Keep memory coherent across multi-session dialogs.
Protocol:
1. Print {mem\_rev, mem\_hash, task\_id}.
2. Assemble prompt as {system | task | constraints | snippets | answer}.
3. Enforce guardrails:
* cite then answer
* forbid cross-section reuse
* reject orphan claims without snippet\_id
4. If λ flips, apply BBAM. If collapse, insert BBCR bridge.
5. Report ΔS(question, retrieved), ΔS across joins, λ states, and final answer.
- State fork: two parallel tabs rewrite history differently.
- Ghost buffer: old role text leaks into new session.
- Desync: memory IDs mismatch after refresh.
- OCR drift: spacing or casing breaks snippet alignment.
| 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 |
| 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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