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130 lines
9 KiB
Markdown
130 lines
9 KiB
Markdown
# Llama.cpp: Guardrails and Fix Patterns
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<details>
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<summary><strong>🧭 Quick Return to Map</strong></summary>
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<br>
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> You are in a sub-page of **LocalDeploy_Inference**.
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> To reorient, go back here:
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>
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> - [**LocalDeploy_Inference** — on-prem deployment and model inference](./README.md)
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> - [**WFGY Global Fix Map** — main Emergency Room, 300+ structured fixes](../README.md)
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> - [**WFGY Problem Map 1.0** — 16 reproducible failure modes](../../README.md)
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>
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> Think of this page as a desk within a ward.
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> If you need the full triage and all prescriptions, return to the Emergency Room lobby.
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</details>
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[Llama.cpp](https://github.com/ggerganov/llama.cpp) is the most widely used local inference runtime for GGML/GGUF models.
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It enables CPU/GPU inference across diverse hardware but often introduces fragile states: mismatched quantization, KV-cache drift, and long-context instability.
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This page defines reproducible WFGY-based guardrails and direct fixes.
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---
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## Open these first
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* Visual recovery map: [RAG Architecture & Recovery](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rag-architecture-and-recovery.md)
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* Retrieval knobs: [Retrieval Playbook](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md)
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* Embedding alignment: [embedding-vs-semantic.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md)
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* Context stability: [context-drift.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/context-drift.md), [entropy-collapse.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/entropy-collapse.md)
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* Schema and injection fences: [prompt-injection.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/prompt-injection.md), [logic-collapse.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/logic-collapse.md)
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* Deploy fences: [bootstrap-ordering.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/bootstrap-ordering.md), [predeploy-collapse.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/predeploy-collapse.md)
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---
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## Core acceptance
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* ΔS(question, retrieved) ≤ 0.45
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* Coverage ≥ 0.70
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* λ convergent across three paraphrases × two seeds
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* KV cache stability for context >8k tokens
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* JSON schema compliance enforced when using tools
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---
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## Common Llama.cpp breakpoints
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| Symptom | Likely Cause | Fix |
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| ------------------------------------------- | ------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| Wrong answers despite high similarity | Embedding metric mismatch with GGUF/quant variant | [embedding-vs-semantic.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md) |
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| Model slows or collapses after 8–16k tokens | KV cache drift | [context-drift.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/context-drift.md), [entropy-collapse.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/entropy-collapse.md) |
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| Output alternates between runs | Prompt header drift | [retrieval-traceability.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md) |
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| Invalid JSON or schema drift | Missing tool schema lock | [prompt-injection.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/prompt-injection.md), [logic-collapse.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/logic-collapse.md) |
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| Crash at first inference call | Boot order not fenced | [bootstrap-ordering.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/bootstrap-ordering.md) |
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| Segfault when mixing quantized weights | Pre-deploy mismatch | [predeploy-collapse.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/predeploy-collapse.md) |
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---
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## Fix in 60 seconds
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1. **Pre-flight warmup**: run a dummy prompt (e.g., `"hello"`) to allocate memory.
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2. **Schema lock** all JSON tool outputs; reject free text where structured arguments expected.
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3. **Measure ΔS** across 3 paraphrases, require ≤0.45.
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4. **Rotate cache** or reset every 8–16k tokens.
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5. **Ensure quantization match** between build and model weights (GGUF flags).
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---
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## Diagnostic prompt (copy-paste)
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```txt
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I am running Llama.cpp with model={gguf/quant}, context={n}.
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Question: "{user_question}"
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Return:
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- ΔS(question, retrieved)
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- λ states across 3 paraphrases × 2 seeds
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- KV cache drift beyond 8k tokens
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- JSON schema compliance
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- Minimal WFGY page to open if ΔS ≥ 0.60
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```
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---
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### 🔗 Quick-Start Downloads (60 sec)
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| Tool | Link | 3-Step Setup |
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|------|------|--------------|
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| **WFGY 1.0 PDF** | [Engine Paper](https://github.com/onestardao/WFGY/blob/main/I_am_not_lizardman/WFGY_All_Principles_Return_to_One_v1.0_PSBigBig_Public.pdf) | 1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + \<your question>” |
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| **TXT OS (plain-text OS)** | [TXTOS.txt](https://github.com/onestardao/WFGY/blob/main/OS/TXTOS.txt) | 1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly |
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---
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### 🧭 Explore More
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| Module | Description | Link |
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|-----------------------|----------------------------------------------------------|----------|
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| WFGY Core | WFGY 2.0 engine is live: full symbolic reasoning architecture and math stack | [View →](https://github.com/onestardao/WFGY/tree/main/core/README.md) |
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| Problem Map 1.0 | Initial 16-mode diagnostic and symbolic fix framework | [View →](https://github.com/onestardao/WFGY/tree/main/ProblemMap/README.md) |
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| Problem Map 2.0 | RAG-focused failure tree, modular fixes, and pipelines | [View →](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rag-architecture-and-recovery.md) |
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| Semantic Clinic Index | Expanded failure catalog: prompt injection, memory bugs, logic drift | [View →](https://github.com/onestardao/WFGY/blob/main/ProblemMap/SemanticClinicIndex.md) |
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| Semantic Blueprint | Layer-based symbolic reasoning & semantic modulations | [View →](https://github.com/onestardao/WFGY/tree/main/SemanticBlueprint/README.md) |
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| Benchmark vs GPT-5 | Stress test GPT-5 with full WFGY reasoning suite | [View →](https://github.com/onestardao/WFGY/tree/main/benchmarks/benchmark-vs-gpt5/README.md) |
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| 🧙♂️ Starter Village 🏡 | New here? Lost in symbols? Click here and let the wizard guide you through | [Start →](https://github.com/onestardao/WFGY/blob/main/StarterVillage/README.md) |
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---
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> 👑 **Early Stargazers: [See the Hall of Fame](https://github.com/onestardao/WFGY/tree/main/stargazers)** —
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> Engineers, hackers, and open source builders who supported WFGY from day one.
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> <img src="https://img.shields.io/github/stars/onestardao/WFGY?style=social" alt="GitHub stars"> ⭐ [WFGY Engine 2.0](https://github.com/onestardao/WFGY/blob/main/core/README.md) is already unlocked. ⭐ Star the repo to help others discover it and unlock more on the [Unlock Board](https://github.com/onestardao/WFGY/blob/main/STAR_UNLOCKS.md).
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<div align="center">
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[](https://github.com/onestardao/WFGY)
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[](https://github.com/onestardao/WFGY/tree/main/OS)
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[](https://github.com/onestardao/WFGY/tree/main/OS/BlahBlahBlah)
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[](https://github.com/onestardao/WFGY/tree/main/OS/BlotBlotBlot)
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[](https://github.com/onestardao/WFGY/tree/main/OS/BlocBlocBloc)
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[](https://github.com/onestardao/WFGY/tree/main/OS/BlurBlurBlur)
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[](https://github.com/onestardao/WFGY/tree/main/OS/BlowBlowBlow)
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</div>
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