# Metric Mismatch — Guardrails and Fix Pattern
🧭 Quick Return to Map
> You are in a sub-page of **RAG_VectorDB**.
> To reorient, go back here:
>
> - [**RAG_VectorDB** — vector databases for retrieval and grounding](./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)
>
> 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.
Use this page when **nearest neighbors look similar in cosine space but your VectorDB runs L2 or dot**, or the reverse.
This failure appears often in FAISS, Milvus, pgvector, Weaviate, Redis, Vespa, and similar stores.
---
## 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)
- Embedding vs meaning: [embedding-vs-semantic.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md)
- Chunking checklist: [chunking-checklist.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/chunking-checklist.md)
---
## Core acceptance
- ΔS(question, retrieved) ≤ 0.45
- Coverage ≥ 0.70 for the target section
- λ remains convergent across three paraphrases and two seeds
- Store metric matches embedding training metric (cosine ↔ cosine, L2 ↔ L2, dot ↔ dot)
---
## Typical breakpoints and the right fix
- **High cosine similarity in logs but wrong meaning**
→ [embedding-vs-semantic.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md)
- **Top-k neighbors inconsistent across runs** (vector drift between L2 and cosine)
→ [retrieval-playbook.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md)
- **Switching embedding models breaks index** (new default metric not aligned with store)
→ [predeploy-collapse.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/predeploy-collapse.md)
- **Hybrid dense+BM25 loses semantic signal** (wrong weighting due to metric scaling)
→ [hybrid_failure.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/RAG/hybrid_failure.md)
---
## Store defaults reference
| Store | Default metric | Notes |
|---------------|----------------------|----------------------------------------|
| FAISS | L2 (can set IP or cosine) | Normalize vectors before cosine search |
| Milvus | L2 / IP | Cosine requires explicit normalization |
| pgvector | L2 / cosine / IP | Must choose at index creation |
| Weaviate | cosine | Dot/IP optional |
| Redis-Vector | cosine | Normalize mandatory |
| Vespa | dot | Needs scaling to emulate cosine |
---
## Fix in 60 seconds
1. **Log current metric**
Run a probe query (`SELECT metric FROM index_metadata`). Verify it matches embedding doc.
2. **Check normalization**
If metric=cosine but vectors are raw, ΔS will inflate. Normalize to unit length.
3. **Re-index with explicit metric**
Drop and rebuild index with the same metric as embedding training.
4. **Hybrid sanity check**
If using BM25+dense, reweight so ΔS ≤ 0.45 and coverage ≥ 0.70.
---
## Copy-paste test query
```sql
-- Example: pgvector
SELECT id, embedding <=> query_embedding
FROM documents
ORDER BY embedding <=> query_embedding
LIMIT 5;
````
Ensure `<=>` operator matches the chosen metric (`cosine`, `L2`, or `IP`).
---
### 🔗 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) |
---
> 👑 **Early Stargazers: [See the Hall of Fame](https://github.com/onestardao/WFGY/tree/main/stargazers)** —
> Engineers, hackers, and open source builders who supported WFGY from day one.
> 
⭐ [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).
[](https://github.com/onestardao/WFGY)
[](https://github.com/onestardao/WFGY/tree/main/OS)
[](https://github.com/onestardao/WFGY/tree/main/OS/BlahBlahBlah)
[](https://github.com/onestardao/WFGY/tree/main/OS/BlotBlotBlot)
[](https://github.com/onestardao/WFGY/tree/main/OS/BlocBlocBloc)
[](https://github.com/onestardao/WFGY/tree/main/OS/BlurBlurBlur)
[](https://github.com/onestardao/WFGY/tree/main/OS/BlowBlowBlow)