# Dimension Mismatch and Projection — 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 **embeddings break because vector dimensions do not match the store or runtime index**. This happens if you switch models (e.g. 1536 → 1024 dims) or if the store silently coerces vectors. --- ## Open these first - Visual map and recovery: [RAG Architecture & Recovery](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rag-architecture-and-recovery.md) - Embedding drift vs semantic mismatch: [embedding-vs-semantic.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md) - Chunking and index alignment: [chunking-checklist.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/chunking-checklist.md) - Retrieval knobs: [retrieval-playbook.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md) --- ## Core acceptance - All embeddings in a store share identical dimension length. - ΔS(question, retrieved) ≤ 0.45 after dimension fix. - Coverage ≥ 0.70 across three paraphrases. - λ remains convergent when switching embedding models. --- ## Typical breakpoints and the right fix - **Store rejects insert** with `dimension mismatch` error. → Rebuild index with correct `dim` parameter. - **Store accepts but pads/truncates silently**. → Causes random retrieval drift. → Explicitly validate vector length on every ingestion. - **Multiple models used** → Some 1024-d, some 1536-d vectors. → Project to common dimension space with PCA/linear map. - **Migration between providers** (e.g. OpenAI → Cohere). → Use adapter layer: re-embed corpus or apply projection matrix. --- ## Fix in 60 seconds 1. **Probe corpus** Sample 100 embeddings, assert uniform `len(vec)`. 2. **Detect hidden coercion** Compute L2 norm variance. If unusually high, store is truncating. 3. **Apply projection** If mixing models, fit PCA/linear map on overlap dataset. 4. **Rebuild index** Always reset store with explicit `dim=…` before production. --- ## Example projection (Python, pseudo) ```python from sklearn.decomposition import PCA import numpy as np # Fit projection from 1536-d → 1024-d pca = PCA(n_components=1024) pca.fit(corpus_vecs_1536) projected = pca.transform(new_vecs_1536) ```` Target: after projection, ΔS variance ≤ 0.05 vs original gold set. --- ## Common gotchas * Store CLI defaults to wrong dimension (FAISS index built at 768, model outputs 1024). * Silent fallback in wrappers (LangChain auto-pads zeros). * Mixing sparse + dense without explicit projection weights. --- ### 🔗 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 | Canonical framework entry point | [View](https://github.com/onestardao/WFGY/tree/main/core/README.md) | | Problem Map | Diagnostic map and navigation hub | [View](https://github.com/onestardao/WFGY/tree/main/ProblemMap/README.md) | | Tension Universe Experiments | MVP experiment field | [View](https://github.com/onestardao/WFGY/tree/main/TensionUniverse/Experiments) | | Recognition | Where WFGY is referenced or adopted | [View](https://github.com/onestardao/WFGY/blob/main/recognition/README.md) | | AI Guide | Anti-hallucination reading protocol for tools | [View](https://github.com/onestardao/WFGY/blob/main/AI_GUIDE.md) | > If this repository helps, starring it improves discovery for other builders. > [![GitHub Repo stars](https://img.shields.io/github/stars/onestardao/WFGY?style=social)](https://github.com/onestardao/WFGY)