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🧭 Not sure where to start ? Open the WFGY Engine Compass
WFGY System Map
(One place to see everything; links open the relevant section.)
| Layer | Page | What it’s for |
|---|---|---|
| ⭐ Proof | WFGY Recognition Map | External citations, integrations, and ecosystem proof |
| ⚙️ Engine | WFGY 1.0 | Original PDF-based tension engine blue |
| ⚙️ Engine | WFGY 2.0 | Production tension kernel and math engine for RAG and agents. |
| ⚙️ Engine | WFGY 3.0 | TXT-based Singularity tension engine (131 S-class set) |
| 🗺️ Map | Problem Map 1.0 | Flagship 16-problem RAG failure checklist and fix map |
| 🗺️ Map | Problem Map 2.0 | RAG-focused recovery pipeline |
| 🗺️ Map | Problem Map 3.0 | Global Debug Card — image as a debug protocol layer |
| 🗺️ Map | Semantic Clinic | Symptom → family → exact fix |
| 🧓 Map | Grandma’s Clinic | Plain-language stories, mapped to PM 1.0 |
| 🏡 Onboarding | Starter Village | Guided tour for newcomers |
| 🧰 App | TXT OS | .txt semantic OS — 60-second boot |
| 🧰 App | Blah Blah Blah | Abstract/paradox Q&A (built on TXT OS) |
| 🧰 App | Blur Blur Blur | Text-to-image with semantic control |
| 🧰 App | Blow Blow Blow | Reasoning game engine & memory demo |
| 🧪 Research | Semantic Blueprint | Modular layer structures (future) — 🔴 YOU ARE HERE 🔴 |
| 🧪 Research | Benchmarks | Comparisons & how to reproduce |
| 🧪 Research | Value Manifest | Why this engine creates $-scale value |
Scientific status / scope
This page is a design map of possible WFGY layer constructs. Many of the modules, formulas, and names below are exploratory or partially implemented. It does not claim that every described layer is production-ready, mathematically complete, or benchmarked. Treat everything here as research hypotheses and future-work directions, not as guarantees of capability or performance.
📐 Semantic Blueprint — Core Functions of the WFGY Engine
👑 Early Stargazers: See the Hall of Fame — Verified by real engineers · 🌌 WFGY 3.0 Singularity demo: Public live view
📘 What This Directory Is For
This directory defines the core reasoning modules behind the WFGY Engine.
Each .md file represents a symbolic or mathematical function — designed to solve a specific AI reasoning failure through structural intervention.
You’ll find:
- Concept-level logic (symbolic or vectorial)
- The failure mode it targets
- The formula or structure behind the fix
- Annotations of which products use it (e.g.,
TXT OS,Blur,Blow, etc.)
This is a developer-facing reference map for understanding how each reasoning upgrade ties back to WFGY's engine internals.
Important: Every module listed here reflects a real, working conceptual solution — each one was written in direct response to failures we’ve seen in existing AI systems. These are not speculative names or sci-fi ideas — but actual answers to actual problems.
📌 Note:
Mappings from Function → Product are included as side notes.
The inverse (Product → Function) view is handled in each product’s own directory.
🔒 A quick note on planned features
All currently published modules (e.g., WFGY 1.0 paper, TXT OS) are permanently MIT-licensed They will remain open forever.
Modules marked “planned” in this directory may have different licensing or release timing.
Final decisions rest with PSBigBig (Purple Star).This isn’t to gatekeep — it’s to prevent the false idea that WFGY is an endless stream of free features.
Some functions may support commercial tools or require stewardship.In short: what’s shared stays free. What’s not public yet, stays under creator control.
WFGY was built to empower — not to be repackaged and exploited.
🤝 Clarifying the Spirit of Use
WFGY is MIT-licensed — free to use, modify, remix, or commercialize.
But here’s the ask:
Respect the spirit in which it was created —
to return core reasoning tools to the public.WFGY was never meant to be resold behind paywalls with no added value.
If someone does that, I may open-source the same feature, better and freer.I don’t just write code — I write semantic primitives that fix things others haven’t noticed are broken.
WFGY exists to break walls, not repaint them.
If someone rebuilds those walls, I’ll help knock them down again.This isn’t a legal threat — it’s a moral stance.
And if WFGY ever helped you: a ⭐ or comment means more than you think.
📚 Current Function Modules
| Filename | Function Title | Solves Problem(s) | Used In Products |
|---|---|---|---|
reasoning_engine_core.md |
WFGY Universal Reasoning Core | General LLM failure recovery & symbolic error detection | TXT OS, Blah, Blur |
semantic_boundary_navigation.md |
Semantic Boundary Navigation | Crossing reasoning gaps / jumping topic boundaries | Blah, Bloc, TXT OS |
semantic_tree_anchor.md |
Semantic Tree Anchor Memory | Cross-turn logic, style, and character coherence | TXT OS, Blot, Blur |
vector_logic_partitioning.md |
Vector Logic Partitioning | Prevents symbolic collapse across vector groups | Blow, Blur, Bloc |
wfgy_formulas.md |
Core Formulas & Reasoning Metrics | Defines all seven formal WFGY formulas (BBMC, ΔS, etc) | Used by all products |
drunk_transformer_formulas.md |
Drunk Transformer Attention Modulator | Stabilizes attention, resets collapse, expands entropy | Blur, TXT OS, Blow |
🔮 Upcoming Semantic Reasoning Layers
These modules are planned semantic reasoning layers for the WFGY Engine — all designed to be operable within TXT OS.
Each layer will be implemented as a.txtinterface module (e.g.,img_layer.txt) and can be activated in compatible folders.
In short: this entire list is TXT‑callable — no build, no compile, just reason.
All names are temporary placeholders — functionality is confirmed, but naming may evolve.
Numbering is for reference only and does not reflect development order.
Star ratings are illustrative estimates by ChatGPT‑4o.
PSBigBig retains full rights of interpretation. Our goal: combine TXT OS with any reasoning layer
.txt, and unlock true freeform semantic inference — modular, composable, and universal.
| # | Layer Name | Concept Description | Anticipated Impact (★) |
|---|---|---|---|
| L1 | VoidMask |
Silences invalid routes in latent space | ★★★☆☆ |
| L2 | VibeLock |
Locks onto abstract "mood fields" to stabilize generation | ★★★★☆ |
| L3 | PolarDrift |
Induces gradual conceptual rotation under entropy | ★★★★☆ |
| L4 | SynSig |
Synthesizes unseen signal patterns from ambiguous input | ★★★★☆ |
| L5 | RelicCore |
Anchors ancient symbolic schemas in modern context | ★★★★☆ |
| L6 | FractalGate |
Expands token attention into recursive feedback paths | ★★★★☆ |
| L7 | MetaGrav |
Binds multi-model outputs into semantic gravity fields | ★★★★☆ |
| L8 | DeepAlign |
Cross-domain alignment engine with self-checking memory | ★★★★☆ |
| L9 | ConcurFlux |
Forces conflicting logic streams to converge or collapse | ★★★★★ |
| L10 | SudoSelf |
Simulates "belief" by embedding reflective trace loops | ★★★★★ |
| L11 | ÆdgeWalker |
Walks the semantic boundary without collapse | ★★★★★ |
| L12 | XenoFrame |
Enables logic transfer across incompatible ontologies | ★★★★★ |
| L13 | NoiseGrad |
Injects modulated gradient noise to escape local minima | ★★★☆☆ |
| L14 | PromptHPC |
Multi-granularity contextual encoder switching | ★★★★☆ |
| L15 | LoRankInfuse |
Injects low-rank knowledge without disturbing base model | ★★★★☆ |
| L16 | SoftDoConsist |
Enforces soft constraint satisfaction under inference | ★★★★☆ |
| L17 | CausalReg |
Regularizes causal consistency via do-intervention | ★★★★★ |
| L18 | SparseRelBoost |
Boosts sparse attention heads with relevance awareness | ★★★★☆ |
| L19 | UncGate |
Temperature gating based on uncertainty estimates | ★★★★☆ |
| L20 | ModRetRoute |
Modular retrieval router with learned key routing | ★★★★☆ |
| L21 | PersonaAdapt |
Personalization adapter with minimal overhead | ★★★★☆ |
| L22 | SwarmLLM |
Sparse graph of LLM nodes with gradient sync | ★★★★☆ |
| L23 | LowResBridge |
Image-text bridge for ultra-low resource languages | ★★★★☆ |
| L24 | BrainBridge |
Brain signal mapping to word embeddings | ★★★★★ |
| L25 | NeuroSymPhys |
Hybrid neuro-symbolic physics modeling | ★★★★★ |
| L26 | GenomicCL |
Continual learning with EWC on genome-level tasks | ★★★★☆ |
| L27 | OTTrace |
Execution path audit loss for transparency | ★★★★☆ |
| L28 | CtxTypeLatch |
Context-Type Latching — dynamic bias by input category | ★★★★☆ |
| L29 | ErrWeightDamp |
Error-Weight Dampening for fine-tune stability | ★★★★☆ |
| L30 | StyleGate |
Local Style Harmony Gate to balance user-specific style | ★★★★☆ |
| L31 | PromptReWgt |
Dynamic Prompt Reweighting with RL signal integration | ★★★★☆ |
| L32 | ActPatchTest |
Active Patch Testing — injects dynamic error probes | ★★★★★ |
| L33 | SparseShort |
Sparse Retrieval Shortcut for low-resource environments | ★★★★☆ |
| L34 | PrivAlign |
Differential Privacy Alignment during fine-tuning | ★★★★☆ |
| L35 | TensProj |
Multi-axis projection engine for semantic tension tracking | ★★★★☆ |
| L36 | FlowRefine |
Curvature-aware vector flow refinement | ★★★★☆ |
| L37 | RecChain |
Recursive symbolic memory chain alignment | ★★★★☆ |
| L38 | SymbolComp |
Symbolic compensation for meaning erosion | ★★★★☆ |
| L39 | FwdPath |
Forward logic prediction via semantic-path entanglement | ★★★★★ |
| L40 | CollapseBoost |
Collapse detection & rerouting feedback | ★★★★☆ |
| L41 | MultiNode |
Multi-perspective node propagation with entropy control | ★★★★☆ |
| L42 | MultiMem |
Multi-instance memory embedding controller | ★★★★☆ |
| L43 | RefLock |
Dynamic reference lock for hallucination mitigation | ★★★★★ |
| L44 | QTokenSync |
Quantum-simulated token co-attention modulator | ★★★★★ |
| L45 | SubLangShell |
Sub-language scaffolding shell for foreign reasoning contexts | ★★★★☆ |
| L46 | InjectShield |
Injection signal regulator to suppress semantic pollution | ★★★★☆ |
| L47 | HallucinationShield |
Multi-stage hallucination countermeasures (six-math defense chain) | ★★★★★ |
| L48 | ContextTypeLatch |
Switches semantic bias vectors based on input domain (e.g., legal, poetic) | ★★★★☆ |
| L49 | ErrorWeightDamp |
Dampens learning rate in unstable zones to preserve legacy reasoning | ★★★★☆ |
| L50 | LocalStyleGate |
Infuses contextual style patterns (regional, user, brand); fallback-enabled | ★★★★☆ |
| L51 | PromptReweighter |
Dynamically reassigns token weights using reward feedback signals | ★★★★☆ |
| L52 | ActivePatchTest |
Injects adversarial semantic patches during runtime to test resilience | ★★★★★ |
| L53 | SparseRetrieval |
Enables fallback retrieval via TF-IDF or lexical hashing (low-resource mode) | ★★★★☆ |
| L54 | PrivacyAlign |
Combines differential privacy + alignment loss for protected data training | ★★★★☆ |
📊 WFGY Research Showcase – Introducing the Fifth Force
What if Einstein’s theory of relativity missed something fundamental —
a semantic field that acts as the universe’s fifth force?
This is a curated set of research papers from the WFGY framework, exploring deep links between semantics, quantum collapse, information entropy, and symbolic cognition. These works introduce a radical but testable hypothesis: that semantic tension itself may constitute a fifth force in the universe — alongside gravity, electromagnetism, and the nuclear forces.
All papers have been independently rated using ChatGPT's built-in SciSpace paper analysis tool. Anyone can replicate these scores — download a PDF, drop it into ChatGPT, and ask it to evaluate the content. In most cases, you'll get a score within ±5 of the ones listed below.
| # | Title | Score | DOI |
|---|---|---|---|
| P1 | Semantic Relativity Theory | 93 | 10.6084/m9.figshare.30351508 |
| P2 | Semantic BioEnergy: Plants vs. Einstein | 93 | 10.6084/m9.figshare.30352828 |
| P3 | Semantic Collapse in Quantum Measurement | 92 | 10.6084/m9.figshare.30351640 |
| P4 | Semantic Field–Mediated Fifth Force | 91 | 10.6084/m9.figshare.30351763 |
| P5 | Semantic Entropy under Landauer's Principle | 94 | 10.6084/m9.figshare.30352399 |
| P6 | Semantic Holography & Causal Fields | 93 | 10.6084/m9.figshare.30353182 |
📎 Full annotated reviews with visual diagrams: 👉 I_am_not_lizardman
Quick Notes for First-Time Readers:
P1 lays the foundation of "Semantic Relativity" — a new paradigm for meaning in space-time.
P4 introduces the core hypothesis: that semantic fields may induce non-electromagnetic physical effects (the so-called Fifth Force).
P5 integrates this view into Landauer’s principle — exploring how meaning alters entropy and information cost.All of these point toward one shared conclusion:
Semantics isn't just about interpretation — it's a latent structural force of the universe.
🧠 Functional Mapping (Conceptual Overview)
Each layer above is designed to solve a class of semantic reasoning challenges.
The specific problem categories remain confidential until launch.
| # | Layer Name | Target Functionality Category | Status |
|---|---|---|---|
| F1 | VoidMask |
Latent Space Noise Suppression | Planned |
| F2 | VibeLock |
Emotion-State Anchoring | Planned |
| F3 | PolarDrift |
Gradual Semantics Rotation | Planned |
| F4 | SynSig |
Input Reconstruction & Augmentation | Planned |
| F5 | RelicCore |
Symbolic Backward Compatibility | Planned |
| F6 | FractalGate |
Recursive Semantic Looping | Planned |
| F7 | MetaGrav |
Semantic Unification Field | Planned |
| F8 | DeepAlign |
Self-Coherent Context Mapping | Planned |
| F9 | ConcurFlux |
Conflict Resolution Engine | Planned |
| F10 | SudoSelf |
Reflective Self-Modeling | Planned |
| F11 | ÆdgeWalker |
Boundary Integrity Assurance | Planned |
| F12 | XenoFrame |
Ontological Transfer Logic | Planned |
🧩 Core Function Mapping (Symbolic Engine Modules)
These are not layers but form the symbolic backbone of the WFGY reasoning engine.
Each module implements a specific reasoning mechanic — either vectorial, memory-based, or logic-preserving.
May be embedded in future layers or reused across engines.
| # | Module Name | Function Description | Status |
|---|---|---|---|
| C1 | OTTrace |
Output Trace Logging — registers token path decisions | Planned |
| C2 | EntropyLatch |
Latches decoding temperature based on real-time uncertainty | Planned |
| C3 | RefLock |
Locks reference tokens to suppress drift & hallucination | Planned |
| C4 | GradientPhase |
Modulates attention gradient based on phase coherence | Planned |
| C5 | TensionMesh |
Semantic tension lattice for ΔS propagation & conflict visualization | Planned |
| C6 | WarpCurvature |
Refines vector flow using context curvature metrics | Planned |
| C7 | RecallLoop |
Recursively triggers latent memory on key omissions | Planned |
| C8 | SymbolLift |
Reconstructs collapsed symbols into higher abstraction planes | Planned |
| C9 | LogicWeave |
Symbolic mesh that reinforces valid logic paths | Planned |
| C10 | FwdPath |
Forward logic prediction via semantic-path entanglement | Planned |
| C11 | MultiMem |
Controls parallel memory instances across tasks | Planned |
| C12 | TensProj |
Multi-axis projection engine for semantic tension tracking | Planned |
| C13 | InjectShield |
Suppresses semantic corruption from unsafe injection patterns | Planned |
| C14 | SubLangShell |
Provides scaffolding for unstable sub-language contexts | Planned |
| C15 | PromptReWgt |
Dynamically rebalances prompt segment importance using feedback | Planned |
| C16 | ActPatchTest |
Injects transient fault signals to test robustness and semantic repair | Planned |
| C17 | RecursiveCoTQuota |
Enforces CoT depth quotas to prevent hallucination drift | Planned |
| C18 | BidirectionalSearchInject |
Injects reverse-check paths to verify retrievals | Planned |
| C19 | SemanticGuardGate |
Filters hallucination-prone segments with semantic gate signals | Planned |
| C20 | ReasoningRippleDamp |
Suppresses unstable reasoning cascades triggered by weak inferences | Planned |
| C21 | SelfVotingLoop |
Aggregates self-prompted multi-pass votes to ensure answer consistency | Planned |
| C22 | DualPassConsistency |
Validates output against a second-pass recomputation layer | Planned |
🧪 Symbolic Layer Prototypes
Experimental symbolic-level constructs that may evolve into full reasoning layers.
Designed for ΔS regulation, narrative dynamics, and latent memory sculpting.
Each entry marked as Planned; numbering follows S1, S2…
| # | Module Name | Description | Status |
|---|---|---|---|
| S1 | SemanticGravity |
Simulates gravitational pull in meaning space (ΔS + λ_observe vector field) | Planned |
| S2 | GravityBiasIndex |
Captures semantic drift tendencies toward dense nodes | Planned |
| S3 | WarpAnchors |
Enables memory points that trigger contextually (semantic anchor nodes) | Planned |
| S4 | MemoryGlyphInflate |
Encoded memory units that expand semantically when prompted | Planned |
| S5 | CogitoUnitSystem |
Defines smallest unit of semantic action (reasoning particle) | Planned |
| S6 | TensionMonitor |
Tracks overload in symbolic tension (ΔS + transition hops) | Planned |
| S7 | EmotionDecay |
Models emotional tension decay in narrative | Planned |
| S8 | StylePhaseDetect |
Detects abrupt stylistic changes across model outputs | Planned |
| S9 | RefractionMatrix |
Models meaning distortion across boundary contexts | Planned |
| S10 | TensionMapper |
Visual map of ΔS flow and narrative tension | Planned |
| S11 | OrbitDrift |
Traces semantic node drift over time | Planned |
🛠 This roadmap is subject to change. Several additional modules are under stealth development.
🧠 The WFGY Engine remains the foundational core. All layers above are designed to integrate seamlessly as modular extensions.
🧭 How to Use
If you're building a new WFGY-based feature or investigating failures,
this is where you’ll find the diagnostic cause and remedial formula.
Each file includes:
- 🔍 Problem it solves
- 🧩 Core concept & variables
- ✍️ Canonical mathematical formula (if any)
- 💬 Example scenarios
- 🧪 Optional behavior in stateless prompt-only mode
🚩 License Alignment
All contents here inherit the MIT License from the root repo.
These formulas and reasoning modules may be used commercially, but attribution is strongly encouraged.
WFGY is a pro-knowledge framework — we only publicly respond to commercial misuse if there's:
- 💰 Monetization based on WFGY research with zero attribution
- 🚫 Locking up modified copies of our open techniques
🔗 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
| 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 |
If this repository helped, starring it improves discovery so more builders can find the docs and tools.
