WFGY/ProblemMap/GlobalFixMap/LocalDeploy_Inference/tgi.md

Hugging Face TGI: Guardrails and Fix Patterns

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• LocalDeploy_Inference — on-prem deployment and model inference
• WFGY Global Fix Map — main Emergency Room, 300+ structured fixes
• WFGY Problem Map 1.0 — 16 reproducible failure modes

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Stabilization guide for Text Generation Inference (TGI), the Hugging Face high-throughput serving stack. Use these checks when local inference works in notebooks but collapses when deployed via TGI servers.

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Open these first

• Visual recovery: RAG Architecture & Recovery
• Retrieval tuning knobs: Retrieval Playbook
• Snippet traceability: retrieval-traceability.md
• Ordering & race fixes: bootstrap-ordering.md, deployment-deadlock.md, predeploy-collapse.md
• Embedding issues: embedding-vs-semantic.md

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Core acceptance

• ΔS(question, retrieved) ≤ 0.45
• Coverage ≥ 0.70 for target section
• λ remains convergent across 3 paraphrases and 2 seeds
• Responses remain stable across concurrent clients (no flip-flops)

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Typical TGI breakpoints and fix

Symptom	Likely cause	Fix
Logs show healthy, outputs differ across replicas	Worker desync / weight loading skew	bootstrap-ordering.md, predeploy-collapse.md
Citations disappear under concurrent load	Async merge loses trace offsets	retrieval-traceability.md, data-contracts.md
ΔS rises >0.60 when concurrency >10	Context fragmentation across shards	context-drift.md, entropy-collapse.md
Errors vanish in dry run, appear in production	Race condition in warm-up path	deployment-deadlock.md
JSON outputs invalid at scale	Schema loosening during parallel decode	logic-collapse.md, data-contracts.md

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Fix in 60 seconds

1. Batch probe: Run same query at concurrency=1 and concurrency=16. If ΔS only rises at higher concurrency, lock async merging.
2. λ probe: Test 3 paraphrases, 2 seeds. If λ flips, apply BBAM variance clamp.
3. Contracts: Require snippet_id, offsets, tokens in every response.
4. Warm-up fencing: Run dummy batch before live serve to sync workers.
5. Verify: Replay test dataset at concurrency=32. Expect stable ΔS ≤ 0.45.

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Copy-paste test prompt

I am running Hugging Face TGI for local inference.  
Concurrent clients sometimes cause unstable answers.  
Question: "{user_question}"  

Please return:
1. ΔS at concurrency=1 vs concurrency=16  
2. λ across paraphrases  
3. Whether citations are preserved  
4. Minimal fix module if ΔS ≥ 0.60  

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🔗 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

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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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