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ProblemMap/GlobalFixMap/Retrieval/README.md
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# Retrieval — Global Fix Map
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Make your retriever correct, predictable, and auditable.
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Use this when recall looks random, hybrid behaves worse than single, or k-tuning never stabilizes.
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## What this page is
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- A short, practical path to stabilize recall and ordering
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- Exact knobs for dense, sparse, and hybrid without guesswork
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- How to prove fixes with ΔS curves and citation tables
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## When to use
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- Top-k results feel unrelated or change on every run
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- Hybrid merge hurts more than single retriever
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- Raising k only adds noise, does not surface the right snippet
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- Filters, analyzers, or languages do not align with your corpus
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- HyDE or query rewriting helps sometimes then flips back
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## Open these first
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- End to end knobs: [Retrieval Playbook](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md)
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- Ordering after recall: [Rerankers](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rerankers.md)
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- Why this snippet, trace schema: [Retrieval Traceability](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md)
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- Hybrid tokenization split: [Query Parsing Split](https://github.com/onestardao/WFGY/blob/main/ProblemMap/patterns/pattern_query_parsing_split.md)
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- Hallucination from bad boundaries: [Hallucination](https://github.com/onestardao/WFGY/blob/main/ProblemMap/hallucination.md)
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- Cosine match is not meaning: [Embedding ≠ Semantic](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md)
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- Some facts never retrieve: [Vectorstore Fragmentation](https://github.com/onestardao/WFGY/blob/main/ProblemMap/patterns/pattern_vectorstore_fragmentation.md)
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- Visual pipeline and recovery: [RAG Architecture & Recovery](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rag-architecture-and-recovery.md)
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- Eval targets: [RAG Precision and Recall](https://github.com/onestardao/WFGY/blob/main/ProblemMap/eval/eval_rag_precision_recall.md)
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- Snippet and citation schema: [Data Contracts](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md)
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## Fix in 60 seconds
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1) **Probe ΔS vs k**
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- Record `ΔS(question, retrieved)` for k in {5, 10, 20} for each retriever separately.
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- Flat and high for all k indicates index or metric mismatch or population gaps. Fix store first.
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2) **Establish a strong single baseline**
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- Pick the retriever with the lowest stable ΔS at small k.
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- Freeze its tokenizer, analyzer, language, stopword set. Save params to disk.
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3) **Unify query parsing**
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- Ensure the same analyzer and lowercasing for write and read.
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- If using HyDE or rewrites, log the final string sent to each retriever and keep it identical across them.
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4) **Hybrid only after per retriever stability**
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- Do not mix until each single retriever yields ΔS ≤ 0.50.
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- Start with a simple weighted sum and a light reranker. Keep citations to audit the change.
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5) **Filters and fields**
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- Disable filters first to confirm baseline recall.
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- Reapply with exact field weights and language settings. Check for case and tokenizer mismatches.
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6) **Dedupe and diversity**
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- Apply MMR or novelty at the rerank stage if results cluster.
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- Keep a per source fence so different documents do not merge.
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7) **Prompt assembly sanity**
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- Use citation first schema from traceability.
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- Do not reorder sections once stable.
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8) **Warm up and cache**
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- Run a deterministic warm up after deploy.
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- Verify repeatability across restarts.
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## Copy paste prompt
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```
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I uploaded TXT OS and WFGY ProblemMap pages.
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My retrieval bug:
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* symptom: \[brief]
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* ΔS vs k per retriever: {...}
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* single retriever baselines: \[dense], \[BM25], \[hybrid attempt]
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* analyzers/tokenizers: write=\[...], read=\[...], lowercasing=\[on|off], stopwords=\[profile]
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* filters/fields: \[list]
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* HyDE or rewrites: \[yes/no], final query strings logged: \[examples]
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Tell me:
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1. which parsing or configuration mismatch explains the failure,
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2. which exact WFGY pages to open,
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3. minimal steps to push ΔS ≤ 0.45 at k=10 without overfitting,
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4. how to verify with precision/recall and a snippet ↔ citation table.
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Use rerankers only after recall is stable.
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```
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## Minimal checklist
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- Same analyzer, language, and case handling on write and read
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- Log the exact query string per retriever including HyDE output
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- Stabilize a single retriever before mixing hybrids
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- Keep field weights explicit and versioned
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- Do not change k and temperature together when measuring ΔS
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- Add reranker only after recall metrics pass
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- Enforce per source fences to avoid cross document blending
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- Persist a warm up routine for post deploy parity
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## Acceptance targets
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- ΔS(question, retrieved) ≤ 0.45 across three paraphrases
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- Precision and recall meet your eval sheet with traceable citations
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- ΔS vs k descends then stabilizes, no oscillation when k grows
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- Same answers across restarts after warm up
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- λ at retrieval remains convergent while reasoning proceeds
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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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