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ProblemMap/GlobalFixMap/RAG_VectorDB/hybrid_retriever_weights.md

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+# Hybrid Retriever Weights — Guardrails and Fix Pattern
+
+Use this page when **hybrid retrieval underperforms a single retriever** or when results look noisy after fusing BM25, dense vectors, HyDE, or filters. Failures usually come from **score scale mismatch**, **duplicate dominance**, or **query-type priors** not reflected in weights.
+
+---
+
+## Open these first
+
+- Visual map and recovery: [RAG Architecture & Recovery](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rag-architecture-and-recovery.md)  
+- Retrieval knobs: [retrieval-playbook.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md)  
+- Ordering control: [rerankers.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rerankers.md)  
+- Query parsing split (HyDE, BM25): [patterns/pattern_query_parsing_split.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/patterns/pattern_query_parsing_split.md)  
+- Embedding vs meaning: [embedding-vs-semantic.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md)  
+- Vector store fragmentation: [GlobalFixMap/RAG_VectorDB/vectorstore_fragmentation.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/RAG_VectorDB/vectorstore_fragmentation.md)  
+- Metric mismatch: [GlobalFixMap/RAG_VectorDB/metric_mismatch.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/RAG_VectorDB/metric_mismatch.md)  
+- Normalization and scaling: [GlobalFixMap/RAG_VectorDB/normalization_and_scaling.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/RAG_VectorDB/normalization_and_scaling.md)  
+- Tokenization and casing: [GlobalFixMap/RAG_VectorDB/tokenization_and_casing.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/RAG_VectorDB/tokenization_and_casing.md)
+
+---
+
+## Core acceptance
+
+- ΔS(question, retrieved) ≤ 0.45 on 3 paraphrases and 2 seeds.  
+- Coverage ≥ 0.70 to the target section after fusion and rerank.  
+- λ remains convergent when weights are perturbed within ±10 percent.  
+- Jaccard overlap against the best single retriever’s top-k ≥ 0.60.  
+- No single source type or domain exceeds 40 percent of the final top-k unless configured.
+
+---
+
+## Symptoms → likely cause → open this
+
+- Hybrid is worse than dense alone  
+  → raw scores on different scales or rank fusion mis-tuned  
+  → [normalization_and_scaling.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/RAG_VectorDB/normalization_and_scaling.md), [rerankers.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rerankers.md)
+
+- BM25 dominates multilingual queries  
+  → tokenizer or casing divergence for CJK or mixed scripts  
+  → [tokenization_and_casing.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/RAG_VectorDB/tokenization_and_casing.md)
+
+- HyDE helps recall yet increases wrong-meaning hits  
+  → HyDE prompts off-domain, no rerank clamp  
+  → [patterns/pattern_query_parsing_split.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/patterns/pattern_query_parsing_split.md), [rerankers.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rerankers.md)
+
+- Same snippet appears many times and crowds others  
+  → duplicate and near-duplicate collapse missing  
+  → (next page) `duplication_and_near_duplicate_collapse.md`
+
+- Fusion order unstable across shards  
+  → partial index rollout or fragmented store  
+  → [vectorstore_fragmentation.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/RAG_VectorDB/vectorstore_fragmentation.md)
+
+---
+
+## Fix in 60 seconds
+
+1) **Normalize each retriever’s scores inside the candidate pool**  
+   Use one of: min-max to 0–1 per retriever, z-score per retriever, or pure rank-based RRF.
+
+2) **De-duplicate by snippet identity**  
+   Collapse near-duplicates using stable keys: `{doc_id, section_id, hash_64}`.
+
+3) **Fuse with a simple, auditable rule**  
+   Start with RRF: `score = Σ 1 / (rank_i + k)` with `k ∈ [50, 100]`.  
+   Then try weighted sum on normalized scores: `S = wdense*sdense + wbm25*sbm25 + whyde*shyde`.
+
+4) **Rerank with a cross-encoder**  
+   Rerank top 50–100 to top 10–20. Enforce cite-then-explain in the prompt.
+
+5) **Measure ΔS and λ**  
+   If λ flips when weights move by ±10 percent, clamp with BBAM and lock schema headers.
+
+---
+
+## Minimal reference recipe
+
+```
+
+retrievers:
+
+* name: dense
+  k: 60
+  norm: z
+  weight: 0.55
+* name: bm25
+  k: 200
+  norm: rank   # convert to ranks 1..k
+  weight: 0.35
+* name: hyde
+  k: 60
+  norm: z
+  weight: 0.10
+
+fusion:
+method: RRF
+rrf\_k: 60
+dedupe: snippet\_id  # or doc\_id+section\_id+hash64
+
+rerank:
+model: cross-encoder-v2
+take\_top: 15
+
+accept:
+deltaS\_max: 0.45
+coverage\_min: 0.70
+jitter\_weight: 0.10   # weights +/- 10 percent must keep λ convergent
+
+```
+
+---
+
+## Weighting heuristics that actually work
+
+- **Short factual queries**  
+  Increase dense weight to 0.6–0.7. Keep BM25 at 0.3–0.4. HyDE optional.
+
+- **Long verbose queries or code**  
+  Push BM25 to 0.5. Keep dense at 0.4. Use reranker to clean length bias.
+
+- **Multilingual or mixed-script**  
+  Reduce BM25 weight if tokenizer mismatch is suspected. Verify casing and analyzer.
+
+- **Highly structured data**  
+  Use BM25 boost on fielded terms. Keep dense for semantic recall.
+
+- **Safety or policy queries**  
+  HyDE at most 0.15. Prefer deterministic BM25 plus strict reranker.
+
+---
+
+## Observability probes you must log
+
+- Per retriever: raw score mean and stdev before normalization.  
+- After fusion: source mix histogram and duplicate collapse count.  
+- ΔS(question, retrieved) and λ states at steps: retrieve, fuse, rerank, answer.  
+- A/B against best single retriever and report ΔS improvement or regression.
+
+---
+
+## Common gotchas
+
+- Mixing **cosine** dense scores with **BM25 raw scores** without normalization.  
+- HyDE prompts built with a different tokenizer than the dense model.  
+- Reranker trained on passages while you fuse at document level.  
+- Language-specific analyzers differ across shards and you fuse their outputs.  
+- Latency cutoffs truncate candidate lists unevenly and bias the fusion.
+
+---
+
+## Verification
+
+- Gold set of 100 queries with 3 paraphrases.  
+- Require ΔS ≤ 0.45 and coverage ≥ 0.70 after fusion plus rerank.  
+- Jaccard with best single retriever ≥ 0.60.  
+- Weight jitter ±10 percent must keep λ convergent and citations stable.
+
+---
+
+### 🔗 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 + \<your question>” |
+| **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.
+
+> <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).
+
+<div align="center">
+
+[![WFGY Main](https://img.shields.io/badge/WFGY-Main-red?style=flat-square)](https://github.com/onestardao/WFGY)
+&nbsp;
+[![TXT OS](https://img.shields.io/badge/TXT%20OS-Reasoning%20OS-orange?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS)
+&nbsp;
+[![Blah](https://img.shields.io/badge/Blah-Semantic%20Embed-yellow?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS/BlahBlahBlah)
+&nbsp;
+[![Blot](https://img.shields.io/badge/Blot-Persona%20Core-green?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS/BlotBlotBlot)
+&nbsp;
+[![Bloc](https://img.shields.io/badge/Bloc-Reasoning%20Compiler-blue?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS/BlocBlocBloc)
+&nbsp;
+[![Blur](https://img.shields.io/badge/Blur-Text2Image%20Engine-navy?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS/BlurBlurBlur)
+&nbsp;
+[![Blow](https://img.shields.io/badge/Blow-Game%20Logic-purple?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS/BlowBlowBlow)
+&nbsp;
+
+</div>