WFGY/ProblemMap/README.md
2025-08-31 16:04:53 +08:00

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WFGY Problem Map 1.0 — bookmark it. youll need it

🛡️ reproducible ai bugs, permanently fixed at the reasoning layer


BigBig Question — If AI bugs are not random but mathematically inevitable, can we finally define and prevent them?
(this repo is one experiment toward that direction)


WFGY Problem Map = a reasoning layer for your AI.
load TXT OS or WFGY Core, then ask: “which problem map number am i hitting?”
youll get a diagnosis and exact fix steps — no infra changes required.

16 reproducible failure modes, each with a clear fix (MIT). (e.g. rag drift, broken indexes)
A semantic firewall you install once, and every failure stays fixed.

⏱️ 30 seconds: Why WFGY Works as a Semantic Firewall

Most fixes today happen after generation:

  • The model outputs something wrong, then we patch it with retrieval, chains, or tools.
  • This means the same failures reappear again and again.

WFGY inverts the sequence.

  • Before generation, it inspects the semantic field (tension, residue, drift signals).
  • If the state is unstable, it loops, resets, or redirects the path.
  • Only a stable semantic state is allowed to generate output.

This is why every failure mode, once mapped, stays fixed.
Youre not firefighting after the fact—youre installing a reasoning firewall at the entry point.

thanks everyone — WFGY reached 800 stars in 70 days.
next milestone: at 1000 stars well unlock Blur Blur Blur.
if this page saves you time, a helps others discover it. GitHub stars


WFGY Core is live: a 30-line reasoning engine for recovery and resilience.
fixing rag hallucinations? it makes models reason before answering.
coming next: Semantic Surgery Room and Global Fix Map (n8n, GHL, Make, more). planned by Sep 1.

semantic memory & reasoning fix in action

quick access

dont worry if this looks long. with TXT OS loaded, simply ask your LLM:
“which Problem Map number fits my issue?” it will point you to the right page.

tip: if youre new, skip scrolling — use the minimal quick-start below.


quick-start downloads (60 sec)

new here? skip the map. grab TXT OS or the WFGY PDF, boot, then ask your model:
“answer using WFGY: ” or “which Problem Map number am i hitting?”

tool link 3-step setup
WFGY 1.0 PDF engine paper 1) download 2) upload to your LLM 3) ask: “answer using WFGY + ”
TXT OS TXTOS.txt 1) download 2) paste into any LLM chat 3) type “hello world” to boot

why this matters long-term

these 16 errors are not random. they are structural weak points every ai pipeline hits eventually.
with WFGY as a semantic firewall you dont just fix todays issue — you shield tomorrows.

this isnt just a bug list. its an x-ray for your pipeline, so you stop guessing and start repairing.

see the end-to-end view: RAG Architecture & Recovery


🧪 one-click sandboxes — run WFGY instantly

run lightweight diagnostics with zero install and zero api key. powered by colab.

these tools map directly to the problem classes. others are handled inside WFGY and will surface in later CLIs.

ΔS diagnostic (mvp) — measure semantic drift

open in colab

detects: No.2 — Interpretation Collapse
steps: run all, paste prompt+answer, read ΔS and fix tip

λ_observe checkpoint — mid-step re-grounding

open in colab

fixes: No.6 — Logic Collapse & Recovery
steps: run all, compare ΔS before/after, fallback to BBCR if needed

ε_resonance — domain-level harmony

open in colab

explains: No.12 — Philosophical Recursion
steps: run, tune anchors, read ε

λ_diverse — answer-set diversity

open in colab

detects: No.3 — Long Reasoning Chains
steps: run, supply ≥3 answers, read score


failure catalog (with fixes)

if you are unsure which one applies, ask your LLM with TXT OS loaded:
“which Problem Map number matches my trace?” it will route you.

legend

[IN] Input & Retrieval [RE] Reasoning & Planning
[ST] State & Context [OP] Infra & Deployment
{OBS} Observability/Eval {SEC} Security {LOC} Language/OCR

# problem domain (with layer/tags) what breaks doc
1 [IN] hallucination & chunk drift {OBS} retrieval returns wrong/irrelevant content hallucination.md
2 [RE] interpretation collapse chunk is right, logic is wrong retrieval-collapse.md
3 [RE] long reasoning chains {OBS} drifts across multi-step tasks context-drift.md
4 [RE] bluffing / overconfidence confident but unfounded answers bluffing.md
5 [IN] semantic ≠ embedding {OBS} cosine match ≠ true meaning embedding-vs-semantic.md
6 [RE] logic collapse & recovery {OBS} dead-ends, needs controlled reset logic-collapse.md
7 [ST] memory breaks across sessions lost threads, no continuity memory-coherence.md
8 [IN] debugging is a black box {OBS} no visibility into failure path retrieval-traceability.md
9 [ST] entropy collapse attention melts, incoherent output entropy-collapse.md
10 [RE] creative freeze flat, literal outputs creative-freeze.md
11 [RE] symbolic collapse abstract/logical prompts break symbolic-collapse.md
12 [RE] philosophical recursion self-reference loops, paradox traps philosophical-recursion.md
13 [ST] multi-agent chaos {OBS} agents overwrite or misalign logic Multi-Agent_Problems.md
14 [OP] bootstrap ordering services fire before deps ready bootstrap-ordering.md
15 [OP] deployment deadlock circular waits in infra deployment-deadlock.md
16 [OP] pre-deploy collapse {OBS} version skew / missing secret on first call predeploy-collapse.md

for No.13 deep dives:
• role drift → multi-agent-chaos/role-drift.md
• cross-agent memory overwrite → multi-agent-chaos/memory-overwrite.md


minimal quick-start

  1. open Beginner Guide and follow the symptom checklist.
  2. use the Visual RAG Guide to locate the failing stage.
  3. open the matching page and apply the patch.

ask any LLM to apply WFGY (TXT OS makes it smoother):


ive uploaded TXT OS / WFGY notes.
my issue: \[e.g., OCR tables look fine but answers point to wrong sections]
which WFGY modules should i apply and in what order?

status & difficulty
# problem (with layer/tags) difficulty* implementation
1 [IN] hallucination & chunk drift {OBS} medium stable
2 [RE] interpretation collapse high stable
3 [RE] long reasoning chains {OBS} high stable
4 [RE] bluffing / overconfidence high stable
5 [IN] semantic ≠ embedding {OBS} medium stable
6 [RE] logic collapse & recovery {OBS} very high stable
7 [ST] memory breaks across sessions high stable
8 [IN] debugging black box {OBS} medium stable
9 [ST] entropy collapse high stable
10 [RE] creative freeze medium stable
11 [RE] symbolic collapse very high stable
12 [RE] philosophical recursion very high stable
13 [ST] multi-agent chaos {OBS} very high stable
14 [OP] bootstrap ordering medium stable
15 [OP] deployment deadlock high ⚠️ beta
16 [OP] pre-deploy collapse {OBS} medium-high stable

*distance from default LLM behavior to a production-ready fix.


🔬 Behind the Map

The Problem Map is practical and ready to use.
But if you wonder why these fixes work, and how were defining physics inside embedding space:
The Hidden Value Engine (WFGY Physics)


🔮 coming soon: global fix map

a universal layer above providers, agents, and infra.
Problem Map is step one. Global Fix Map expands the same reasoning-first firewall to RAG, infra boot, agents, evals, and more. same zero-install experience. launching around Sep.


contributing / support

  • open an issue with a minimal repro (inputs → calls → wrong output).
  • PRs for clearer docs, repros, or patches are welcome.
  • project home: github.com/onestardao/WFGY
  • TXT OS: browse the OS
  • if this map helped you, a helps more devs find it.

🧭 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 →

👑 Early Stargazers: See the Hall of Fame
Engineers, hackers, and open source builders who supported WFGY from day one.

GitHub stars WFGY Engine 2.0 is already unlocked. Star the repo to help others discover it and unlock more on the Unlock Board.

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