faiss

21.8k

davila7

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-performance applications.

architecture

324

Zilliztech Knowhere Architecture

Use when exploring codebase structure, understanding index implementations (HNSW, IVF, DISKANN, Sparse, MinHash), working with third-party libraries (faiss, hnswlib, DiskANN, Cardinal), or locating specific functionality

cdr3clustering

20

pwwang

Cluster TCR/BCR clones by CDR3 sequences using GIANA or ClusTCR (both Faiss-based). Adds `CDR3_Cluster` column to metadata for clonotype analysis.

rag-retrieval

4

gitwalter

Patterns for using FAISS MCP tools to ingest documents and perform semantic retrieval.

retrieving-rag-context-adv

4

gitwalter

Patterns for using FAISS MCP tools to ingest documents and perform semantic retrieval.

LangChain RAG Pipeline

3

jackjin1997

INVOKE THIS SKILL when building ANY retrieval-augmented generation (RAG) system. Covers document loaders, RecursiveCharacterTextSplitter, embeddings (OpenAI), and vector stores (Chroma, FAISS, Pinecone).

ArXivKB

camopel

Local arXiv paper manager with semantic search. Crawls arXiv categories, downloads PDFs, chunks content, and indexes with FAISS + Ollama embeddings. No cloud API keys required — everything runs locally.

vector-composition

ExoPriors

Compose semantic vectors in Scry -- embed concepts as @handles, search by cosine distance, debias with vector algebra, and diagnose signal loss. Use when the task involves: semantic search, embedding, vector, cosine distance, <=>, "X but not Y", debias, embed this concept, @handle, vibe algebra, concept vector. NOT for: word2vec training, fine-tuning embeddings, local vector databases (FAISS, Pinecone, Chroma), or plain keyword/SQL search (use scry).