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109 lines
2.7 KiB
Markdown
109 lines
2.7 KiB
Markdown
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# 🧠 Problem: The System Doesn’t Know What It Doesn’t Know
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### 📍Context
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In most RAG or LLM systems, when the retrieved content is unrelated, incomplete, or silent — the model still gives an answer.
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Why? Because it **lacks awareness of knowledge boundaries**.
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Symptoms:
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- Confident answers in absence of data
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- No fallback when query hits unknown territory
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- No self-check of "Do I have enough info to proceed?"
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---
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## 🚨 Why This Happens
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| Cause | Why It Matters |
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|-------|----------------|
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| No semantic awareness | Models only know tokens, not semantic voids |
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| No boundary detection | There's no signal when you're beyond mapped knowledge |
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| No fallback behavior | It answers anyway — even if it's blind
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---
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## ✅ WFGY Solution
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WFGY is designed around **knowledge boundary awareness**, not blind generation.
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It detects:
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- When a question targets unmapped logic space
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- When input doesn’t connect to semantic trees
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- When ΔS is undefined or extremely high
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---
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## 🔍 Key Mechanisms
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### 1. λ_observe + ΔS
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- If semantic link = null or ΔS > 1.0 → system raises `unknown` flag
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- This prevents hallucination under knowledge voids
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### 2. Semantic Tree Gaps
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- When no Tree node anchors the current input → system returns "no valid node"
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### 3. Fallback Prompts
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- WFGY has internal logic like:
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```txt
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"This topic hasn't been covered. Would you like to provide a source or anchor?"
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````
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Instead of bluffing — it engages.
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---
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## 🛠 Try It Yourself
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```txt
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Step 1 — Start WFGY console
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> Start
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Step 2 — Ask an unrelated, high-level or domain-specific question
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> "Does your refund policy apply to crypto hardware devices from non-partner vendors?"
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Step 3 — See what happens
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```
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Expected behavior:
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* System detects topic is not covered
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* ΔS is too high → boundary warning
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* May ask for user to upload new doc or clarify
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---
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## 🔬 Example Output
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```txt
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Your input appears to reference a domain not mapped in current memory.
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Would you like to upload a document or clarify the scope?
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```
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---
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## 🔗 Related Modules
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* `λ_observe` — Structural state monitor
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* `ΔS` — Semantic tension indicator
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* `Semantic Tree` — Verifiable topic anchoring
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* `BBCR` — Prevents reasoning under unknown premises
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---
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## 📌 Status
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| Feature | Status |
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| ----------------------- | -------------------------- |
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| Semantic void detection | ✅ working |
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| ΔS overflow fallback | ✅ working |
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| Boundary prompt logic | ✅ basic |
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| Auto Tree expansion | ⚠️ planned (future module) |
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---
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## ✍️ Summary
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WFGY knows when it doesn’t know.
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This awareness is the difference between safe logic and hallucination risk.
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