Skill · em Dados, IA e pesquisa
faiss
Facebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HNSW). Use for fast k-NN search, large-scale vector retrieval, or when you need pure similarity search without metadata. Best for…
Procedência
- Origem: davila7/claude-code-templates
- Caminho:
cli-tool/components/skills/ai-research/rag-faiss - Versão fixada:
57f899e5394bb8ca166f38eacae8f0853cbfe033 - Licença: MIT
- Espelhado em 25/09/2026
- 1 download no Claude Code Templates (lido em 25/09/2026)
Antes de instalar
2 arquivos · 11 KB · só texto, nenhum script
Instalar na sua CLI
O comando baixa a versão fixada (commit 57f899e) direto da origem, para a pasta que a CLI lê. Precisa de curl (macOS e Linux); no Windows não há comando, porque o Rook Labs é para macOS.
Claude Code
Neste projeto: instala em .claude/skills/faiss/.
d=".claude/skills/faiss" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/rag-faiss" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/index_types.md" "$u/references/index_types.md"
Global: instala em ~/.claude/skills/faiss/.
d="$HOME/.claude/skills/faiss" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/rag-faiss" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/index_types.md" "$u/references/index_types.md"
Codex
Neste projeto: instala em .agents/skills/faiss/.
d=".agents/skills/faiss" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/rag-faiss" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/index_types.md" "$u/references/index_types.md"
Global: instala em ~/.agents/skills/faiss/.
d="$HOME/.agents/skills/faiss" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/rag-faiss" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/index_types.md" "$u/references/index_types.md"
Antigravity
Neste projeto: instala em .agents/skills/faiss/.
d=".agents/skills/faiss" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/rag-faiss" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/index_types.md" "$u/references/index_types.md"
Global: instala em ~/.gemini/antigravity-cli/skills/faiss/.
d="$HOME/.gemini/antigravity-cli/skills/faiss" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/rag-faiss" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/index_types.md" "$u/references/index_types.md"
Peça ao Rook
Já usa o Rook Labs? Cole no chat do Rook: instale a skill https://rooklabs.sh/marketplace/cct.faiss
Prévia do SKILL.md
---
name: faiss
description: Facebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HNSW). Use for fast k-NN search, large-scale vector retrieval, or when you need pure similarity search without metadata. Best for high-perf…
version: 1.0.0
author: Orchestra Research
license: MIT
tags: [RAG, FAISS, Similarity Search, Vector Search, Facebook AI, GPU Acceleration, Billion-Scale, K-NN, HNSW, High Performance, Large Scale]
dependencies: [faiss-cpu, faiss-gpu, numpy]
---
# FAISS - Efficient Similarity Search
Facebook AI's library for billion-scale vector similarity search.
## When to use FAISS
**Use FAISS when:**
- Need fast similarity search on large vector datasets (millions/billions)
- GPU acceleration required
- Pure vector similarity (no metadata filtering needed)
- High throughput, low latency critical
- Offline/batch processing of embeddings
**Metrics**:
- **31,700+ GitHub stars**
- Meta/Facebook AI Research
- **Handles billions of vectors**
- **C++** with Python bindings
**Use alternatives instead**:
- **Chroma/Pinecone**: Need metadata filtering
- **Weaviate**: Need full database features
- **Annoy**: Simpler, fewer features
## Quick start
### Installation
```bash
# CPU only
…