index_types

Complete guide to choosing and using FAISS index types.

Skills
AI research
0

What it does and how to use it

A skill that teaches Claude Code to do ai research tasks well. It is packaged knowledge the model uses whenever it is relevant.

Install the skill (command above).
In Claude Code, describe what you need - the skill turns on by itself when the context fits.
No commands to memorize: you talk in plain language and the skill does the rest.

Install (Claude Code)

mkdir -p .claude/skills/index-types && curl -fsSL https://doutorai.pt/data/lib/skills__index-types.md -o .claude/skills/index-types/SKILL.md

Paste this command into the terminal, in your project folder, and the component installs automatically.

Content

# FAISS Index Types Guide

Complete guide to choosing and using FAISS index types.

## Index selection guide

| Dataset Size | Index Type | Training | Accuracy | Speed |
|--------------|------------|----------|----------|-------|
| < 10K | Flat | No | 100% | Slow |
| 10K-1M | IVF | Yes | 95-99% | Fast |
| 1M-10M | HNSW | No | 99% | Fastest |
| > 10M | IVF+PQ | Yes | 90-95% | Fast, low memory |

## Flat indices (exact search)

### IndexFlatL2 - L2 (Euclidean) distance

```python
import faiss
import numpy as np

d = 128  # Dimension
index = faiss.IndexFlatL2(d)

# Add vectors
vectors = np.random

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