WFGY/ProblemMap/GlobalFixMap/LLM_Providers/meta_llama.md

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Meta Llama: Guardrails and Fix Patterns

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This page gives an operational checklist for Meta Llama based assistants inside RAG and agent stacks. It maps the usual failure modes to concrete WFGY fixes and acceptance targets.

Acceptance targets

  • ΔS(question, retrieved_context) ≤ 0.45
  • Coverage of retrieved vs target section ≥ 0.70
  • λ_observe stays convergent across 3 paraphrases
  • E_resonance flat on long windows

Common failure patterns seen with Llama setups

  1. Plausible but wrong answers even when chunks look fine
    Map to: Interpretation Collapse and Hallucination & Chunk Drift.
    Check also Embedding ≠ Semantic and the Retrieval Playbook.

  2. Degradation in long dialogs or large context
    Map to: Context Drift and Entropy Collapse.

  3. Role loss after tool calls or agent hops
    Map to: Multi-Agent Problems and deep dive Role Drift.

  4. Overconfident answers without citations
    Map to: Bluffing / Overconfidence. Enforce traceable schemas with Retrieval Traceability and Data Contracts.

  5. Hybrid retrieval oscillation, high similarity but wrong meaning
    Map to: Embedding ≠ Semantic and Rerankers. Tune using the Retrieval Playbook.

  6. Cross-source merging and leakage
    Map to: Symbolic Constraint Unlock pattern
    SCU pattern with strict Data Contracts.

  7. Tokenizer or locale mismatch on non-English corpora
    Map to: Multilingual Guide and re-probe with Embedding ≠ Semantic.


WFGY repair map for Llama


Quick triage steps

  1. Probe ΔS(question, retrieved_context). If ≥ 0.60 open:
    Embedding ≠ Semantic and Hallucination.

  2. Vary k in {5, 10, 20} and chart ΔS vs k. Flat-high curve points to index or metric mismatch
    Retrieval Playbook.

  3. If chunks are correct but logic is wrong, mark λ at reasoning and apply BBCR + BBAM
    Interpretation Collapse and Logic Collapse.

  4. For long dialogs, verify joins with ΔS ≤ 0.50 and clamp variance
    Context Drift and Entropy Collapse.

  5. If sources bleed, enforce SCU and per-section fences
    SCU pattern and Retrieval Traceability.


Minimal safe prompt you can paste


I uploaded TXT OS. Read WFGY formulas and Problem Map pages.
My stack runs on Meta Llama.

symptom: \[describe]
traces: \[ΔS probes, λ states, short logs]

Tell me:

1. the failing layer and why,
2. the exact WFGY page to open next,
3. the minimal steps to push ΔS ≤ 0.45 with convergent λ,
4. how to verify the fix with a reproducible test.


Escalation and ops


🔗 Quick-Start Downloads (60 sec)

Tool Link 3-Step Setup
WFGY 1.0 PDF Engine Paper 1 Download · 2 Upload to your LLM · 3 Ask “Answer using WFGY + <your question>”
TXT OS (plain-text OS) TXTOS.txt 1 Download · 2 Paste into any LLM chat · 3 Type “hello world” — OS boots instantly

Explore More

Module Description Link
WFGY Core Canonical framework entry point View
Problem Map Diagnostic map and navigation hub View
Tension Universe Experiments MVP experiment field View
Recognition Where WFGY is referenced or adopted View
AI Guide Anti-hallucination reading protocol for tools View

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