WFGY/ProblemMap/GlobalFixMap/VectorDBs_and_Stores

Vector DBs & Stores — Global Fix Map

A hub to stabilize retrieval pipelines across popular vector stores.
Use this page to jump to per-tool guardrails and verify fixes with the same acceptance targets.

---

Quick routes to per-store pages

• FAISS → faiss.md
• Chroma → chroma.md
• Qdrant → qdrant.md
• Weaviate → weaviate.md
• Milvus → milvus.md
• pgvector → pgvector.md
• Redis (Search/Vec) → redis.md
• Elasticsearch (kNN / dense) → elasticsearch.md
• Pinecone → pinecone.md

---

When to use this folder

• High similarity but wrong meaning.
• Citations don’t line up with the retrieved section.
• Hybrid retrievers underperform a single retriever.
• Query casing / analyzer / metric mismatches after deploy.
• Index looks healthy yet coverage remains low.

---

Acceptance targets for any store

• ΔS(question, retrieved) ≤ 0.45
• Coverage of target section ≥ 0.70
• λ_observe stays convergent across 3 paraphrases
• E_resonance flat on long windows

---

Map symptoms → structural fixes (Problem Map)

• Embedding ≠ Semantic
  Wrong-meaning hits despite high similarity.
  → embedding-vs-semantic.md

• Retrieval traceability
  Snippet/section mismatch or unverifiable citations.
  → retrieval-traceability.md
  Payload schema: → data-contracts.md

• Ordering / version skew
  Old index or analyzer used at runtime.
  → bootstrap-ordering.md · predeploy-collapse.md

• Hybrid collapse / query split
  HyDE vs BM25 disagreement, reranker blind spots.
  → Pattern: patterns/pattern_query_parsing_split.md
  → Knobs: rerankers.md

---

60-second fix checklist (store-agnostic)

1. Lock metrics & analyzers
   Pin distance metric, tokenizer/casing, and normalization on both write and read.

2. Contract the snippet
   Require {snippet_id, section_id, source_url, offsets, tokens}.

3. Probe ΔS and λ
   Log ΔS(question, retrieved) and λ per step; alert at ΔS ≥ 0.60.

4. Verify coverage
   Run a 10-question eval on the target section; require coverage ≥ 0.70.

5. Reranking pass
   If hybrid disagrees, add a rerank step and re-measure ΔS.

---

Copy-paste prompt for a quick audit

I uploaded TXT OS and the WFGY Problem Map pages.
My stack uses <store> with metric \<cosine|l2|dot>, analyzer <...>, and normalization <...>.

Do:

1. Report ΔS(question, retrieved) and λ states across retrieve → rerank → reason.
2. If ΔS ≥ 0.60, point to one minimal structural fix:
   embedding-vs-semantic, retrieval-traceability, data-contracts, rerankers.
3. Return JSON:
   { "citations":\[...], "ΔS":0.xx, "λ":"→|←|<>|×", "next\_fix":"..." }

---

🔗 Quick-Start Downloads (60 sec)

Tool	Link	3-Step Setup
WFGY 1.0 PDF	Engine Paper	1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + ”
TXT OS (plain-text 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 →
Problem Map 1.0	Initial 16-mode diagnostic and symbolic fix framework	View →
Problem Map 2.0	RAG-focused failure tree, modular fixes, and pipelines	View →
Semantic Clinic Index	Expanded failure catalog: prompt injection, memory bugs, logic drift	View →
Semantic Blueprint	Layer-based symbolic reasoning & semantic modulations	View →
Benchmark vs GPT-5	Stress test GPT-5 with full WFGY reasoning suite	View →
🧙‍♂️ Starter Village 🏡	New here? Lost in symbols? Click here and let the wizard guide you through	Start →

---

👑 Early Stargazers: See the Hall of Fame —
⭐ WFGY Engine 2.0 is already unlocked. ⭐ Star the repo to help others discover it and unlock more on the Unlock Board.