Ollama: Guardrails and Fix Patterns

Field guide for stabilizing Ollama-based local inference pipelines. Use these checks when models run fine on API providers but collapse, stall, or drift when containerized with Ollama.

Open these first

Architecture recovery: RAG Architecture & Recovery
End-to-end retrieval knobs: Retrieval Playbook
Embedding vs semantic: embedding-vs-semantic.md
Ordering and deploy race conditions: bootstrap-ordering.md, deployment-deadlock.md, predeploy-collapse.md
Container observability: eval_observability.md

Core acceptance

ΔS(question, retrieved) ≤ 0.45
Coverage ≥ 0.70 on the target section
λ remains convergent across 3 paraphrases
Local runs reproducible across 2+ seeds

Typical Ollama breakpoints and fix

Symptom	Likely cause	Fix
Model boots but stalls on first request	Container not warmed / secrets missing	bootstrap-ordering.md
Fast API returns, but snippets wrong	Index/hash drift across containers	retrieval-traceability.md, data-contracts.md
Answers diverge run-to-run	λ flips due to context serialization	context-drift.md, entropy-collapse.md
Works on GPU API, fails locally	Metric / embedding mismatch in Ollama runtime	embedding-vs-semantic.md, vectorstore-fragmentation.md
Container OOM or deadlock	Parallel inference with no fence	deployment-deadlock.md, predeploy-collapse.md

Fix in 60 seconds

Measure ΔS between retrieved and anchor.
Probe λ across 3 paraphrases. If flips, apply BBAM.
Warm boot with a delay + healthcheck before first request.
Lock index schema via data-contracts.md.
Verify reproducibility with two seeds before going live.

Copy-paste local test prompt

I have WFGY + TXTOS loaded.  
Running Ollama locally with container {hash}.  
Question: "{user_question}"  

Return:
1. ΔS(question,retrieved) and λ across 3 paraphrases  
2. Whether index schema matches contract  
3. Minimal structural fix if ΔS ≥ 0.60

🔗 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

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 →
🧙‍♂️ Starter Village 🏡	New here? Lost in symbols? Click here and let the wizard guide you through	Start →

👑 Early Stargazers: See the Hall of Fame ⭐ WFGY Engine 2.0 is already unlocked. ⭐ Star the repo to help others discover it and unlock more on the Unlock Board.