Rasa: Guardrails and Fix Patterns

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Chatbots & CX — customer dialogue flows and conversational stability

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.

A focused guide to stabilize Rasa bots that call retrieval, tools, or external LLMs. Use this page to localize the failing layer and jump to the exact WFGY fix page with measurable targets.

Open these first

Visual map and recovery: rag-architecture-and-recovery.md
End-to-end retrieval knobs: retrieval-playbook.md
Why this snippet (traceability schema): retrieval-traceability.md
Ordering control: rerankers.md
Embedding vs meaning: embedding-vs-semantic.md
Hallucination and chunk boundaries: hallucination.md
Long chains and entropy: context-drift.md, entropy-collapse.md
Structural collapse and recovery: logic-collapse.md
Prompt injection and schema locks: prompt-injection.md
Multi-agent conflicts and tool loops: Multi-Agent_Problems.md
Boot order issues: bootstrap-ordering.md, deployment-deadlock.md, predeploy-collapse.md
Snippet and citation schema: data-contracts.md

Core acceptance

ΔS(question, retrieved) ≤ 0.45
Coverage ≥ 0.70 to the target section
λ remains convergent across three paraphrases and two seeds
E_resonance stays flat on long windows

Fix in 60 seconds

Measure ΔS
Compute ΔS(question, retrieved) and ΔS(retrieved, expected anchor).
Stable < 0.40, transitional 0.40–0.60, risk ≥ 0.60.
Probe λ_observe
Vary k in retrieval (5, 10, 20). If ΔS stays flat and high, suspect metric or index mismatch.
Reorder prompt headers; if ΔS spikes, lock the schema.
Apply the module

Retrieval drift → BBMC + data-contracts.md
Reasoning collapse → BBCR bridge + BBAM, verify with logic-collapse.md
Dead ends in long plans → BBPF alternates, verify with context-drift.md

Typical Rasa breakpoints and the right fix

NLU confidence thrash after new training data. Ambiguous intents route to the wrong retrieval path.
Open: embedding-vs-semantic.md ·
Schema locks: data-contracts.md
Rules vs stories conflict causes looped actions or skipped tool calls.
Open: Multi-Agent_Problems.md ·
Entropy guard: entropy-collapse.md
Forms never complete or slots stay stale across sessions.
Open: retrieval-traceability.md ·
Contract the payload: data-contracts.md
Action server timeouts right after deploy or on cold starts.
Open: bootstrap-ordering.md, predeploy-collapse.md
Hybrid retrieval underperforms compared to single retriever.
Open: patterns/pattern_query_parsing_split.md, rerankers.md
Tracker store duplicates or missing events after channel reconnects.
Open: deployment-deadlock.md
Knowledge base hits look similar but mean different things.
Open: embedding-vs-semantic.md ·
Fragmented store: patterns/pattern_vectorstore_fragmentation.md
Tool output bleeds into user turns and corrupts state.
Open: prompt-injection.md

Deep diagnostics

Three-paraphrase probe
Ask the same user need three ways. Log ΔS and λ per step. If λ flips on harmless paraphrase, clamp with BBAM and tighten the citation-first schema.
Anchor triangulation
Compare ΔS to the expected anchor section and to a decoy section. If both are close, re-chunk and re-embed, verify with a tiny gold set.
Chain length audit
If entropy rises after 25–40 steps across stories, split the plan and re-join with a BBCR bridge. See context-drift.md.

Minimal ops checklist for Rasa

NLU thresholds: set fallback and ambiguity handling so low-confidence intents route to a safe clarify path.
Action server: health probe plus backoff. Respect readiness gates from bootstrap-ordering.md.
Event schema: store snippet_id, section_id, source_url, offsets, tokens, ΔS, λ_state, index_hash. Enforce cite-then-explain.
Retriever parity: keep metric, analyzer, and normalization identical between training and runtime.

Copy-paste prompt for the LLM step behind Rasa

You have TXT OS and the WFGY Problem Map loaded.

My Rasa issue:
- symptom: [one line]
- traces: ΔS(question,retrieved)=..., ΔS(retrieved,anchor)=..., λ states across 3 paraphrases

Tell me:
1) failing layer and why,
2) the exact WFGY page to open from this repo,
3) the minimal steps to push ΔS ≤ 0.45 and keep λ convergent,
4) how to verify with a reproducible test.
Use BBMC/BBPF/BBCR/BBAM when relevant.

When to escalate

ΔS stays ≥ 0.60 after chunking and retrieval fixes → rebuild index with explicit metric and normalization. See retrieval-playbook.md.
Answers alternate across identical dialogs → investigate memory desync or version skew. See predeploy-collapse.md.

🔗 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 based tension engine
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 to family to exact fix
Map	Grandma’s Clinic	Plain language stories mapped to Problem Map 1.0
Onboarding	Starter Village	Guided tour for newcomers
App	TXT OS	TXT semantic OS, fast boot
App	Blah Blah Blah	Abstract and paradox Q and A built on TXT OS
App	Blur Blur Blur	Text to image with semantic control
App	Blow Blow Blow	Reasoning game engine and memory demo

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