# FAISS: Guardrails and Fix Patterns
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> - [**VectorDBs_and_Stores** — vector indexes and storage backends](./README.md)
> - [**WFGY Global Fix Map** — main Emergency Room, 300+ structured fixes](../README.md)
> - [**WFGY Problem Map 1.0** — 16 reproducible failure modes](../../README.md)
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A compact repair guide for FAISS retrieval stacks. Use this when recall looks fine but meaning drifts, or when IVF/HNSW tuning flips answers across seeds. The checks below route you to the exact WFGY fix pages and give a minimal recipe you can paste into a runbook.
## Open these first
- Visual map and recovery: [RAG Architecture & Recovery](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rag-architecture-and-recovery.md)
- End-to-end retrieval knobs: [Retrieval Playbook](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md)
- Traceability schema: [Retrieval Traceability](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md)
- Embedding ≠ meaning: [Embedding vs Semantic](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md)
- Vectorstore health: [Vectorstore Fragmentation](https://github.com/onestardao/WFGY/blob/main/ProblemMap/patterns/pattern_vectorstore_fragmentation.md)
- Query split (HyDE vs BM25): [Query Parsing Split](https://github.com/onestardao/WFGY/blob/main/ProblemMap/patterns/pattern_query_parsing_split.md)
- Ordering control: [Rerankers](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rerankers.md)
- Snippet and citation schema: [Data Contracts](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md)
- Evaluating RAG: [RAG Precision/Recall](https://github.com/onestardao/WFGY/blob/main/ProblemMap/eval/eval_rag_precision_recall.md)
- FAISS specifics: [Vectorstore Metrics & FAISS Pitfalls](https://github.com/onestardao/WFGY/blob/main/ProblemMap/vectorstore-metrics-and-faiss-pitfalls.md)
- Live checks: [Live Monitoring](https://github.com/onestardao/WFGY/blob/main/ProblemMap/ops/live_monitoring_rag.md)
## Fix in 60 seconds
1) **Measure ΔS**
- Compute ΔS(question, retrieved) and ΔS(retrieved, expected anchor).
- Thresholds: stable < 0.40, transitional 0.40–0.60, risk ≥ 0.60.
2) **Probe with λ_observe**
- Sweep `k ∈ {5, 10, 20}` and for IVF sweep `nprobe ∈ {1, 4, 8, 16}`.
- For HNSW, sweep `efSearch ∈ {32, 64, 128}`.
- If ΔS flattens high across k, suspect metric/index mismatch.
3) **Apply the module**
- Retrieval drift → **BBMC** + [Data Contracts](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md).
- Reasoning collapse after retrieval → **BBCR** bridge + **BBAM** variance clamp, see [Logic Collapse](https://github.com/onestardao/WFGY/blob/main/ProblemMap/logic-collapse.md).
- Dead ends in long runs → **BBPF** alternate path + [Context Drift](https://github.com/onestardao/WFGY/blob/main/ProblemMap/context-drift.md).
4) **Verify**
- Coverage to target section ≥ 0.70, ΔS ≤ 0.45 on three paraphrases, λ stays convergent across seeds.
## Typical breakpoints and the right fix
| Symptom | Likely cause | Open this | Minimal fix |
|---|---|---|---|
| High cosine similarity but wrong meaning | IP vs L2 mixup, un-normalized embeddings | [Embedding vs Semantic](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md) | Normalize vectors; match metric to embedder; re-index |
| Good recall, messy top-k order | Rerank missing or weak | [Rerankers](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rerankers.md) | Add cross-encoder rerank, k=50→top-10 |
| Some facts never show up | Shards or label fragmentation | [Vectorstore Fragmentation](https://github.com/onestardao/WFGY/blob/main/ProblemMap/patterns/pattern_vectorstore_fragmentation.md) | Merge shards; rebuild IVF lists; verify dim |
| Answers flip between runs | IVF `nlist/nprobe` underfit, PQ over-aggressive | [FAISS Pitfalls](https://github.com/onestardao/WFGY/blob/main/ProblemMap/vectorstore-metrics-and-faiss-pitfalls.md) | Raise `nprobe`, enlarge training set, reduce PQ |
| Hybrid gets worse than single retriever | Query split and prompt coupling | [Query Parsing Split](https://github.com/onestardao/WFGY/blob/main/ProblemMap/patterns/pattern_query_parsing_split.md) | Split semantic vs lexical prompts; fuse post-retrieval |
## FAISS quick checklist
- Confirm **dimension** matches the embedding model output exactly.
- Confirm **metric**: IP with normalized vectors, or L2 with raw vectors. Do not mix.
- For IVF, set `nlist` based on corpus size, train with at least `100× nlist` examples.
- Start with `nprobe ≈ sqrt(nlist)` and tune upward until ΔS stabilizes.
- For HNSW, raise `efConstruction` and `efSearch` until ΔS stops improving.
- Rebuild the index after changing normalization or metric.
- Lock the snippet schema and citations using [Data Contracts](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md).
## Copy-paste repair prompt
```
audit FAISS retrieval with ΔS and λ\_observe.
report: metric choice (IP/L2), normalization, dim, index type, nlist/nprobe or HNSW ef.
run three paraphrases, k in {5,10,20}. if ΔS stays >0.45, switch to normalized IP and rebuild.
apply BBMC + Data Contracts; add reranker for top-50→10. show before/after ΔS table.
```
## Acceptance targets
- Coverage ≥ 0.70 to the target section.
- ΔS ≤ 0.45 across three paraphrases.
- λ remains convergent across seeds.
- E_resonance flat under long windows.
---
### 🔗 Quick-Start Downloads (60 sec)
| Tool | Link | 3-Step Setup |
|------|------|--------------|
| **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 + ” |
| **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 |
---
### 🧭 Explore More
| Module | Description | Link |
|-----------------------|----------------------------------------------------------|----------|
| 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) |
| Problem Map 1.0 | Initial 16-mode diagnostic and symbolic fix framework | [View →](https://github.com/onestardao/WFGY/tree/main/ProblemMap/README.md) |
| 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) |
| Semantic Clinic Index | Expanded failure catalog: prompt injection, memory bugs, logic drift | [View →](https://github.com/onestardao/WFGY/blob/main/ProblemMap/SemanticClinicIndex.md) |
| Semantic Blueprint | Layer-based symbolic reasoning & semantic modulations | [View →](https://github.com/onestardao/WFGY/tree/main/SemanticBlueprint/README.md) |
| 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) |
| 🧙♂️ 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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> Engineers, hackers, and open source builders who supported WFGY from day one.
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⭐ [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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