Distributed vector search for AI-native applications
-
Updated
Nov 19, 2024 - Go
Distributed vector search for AI-native applications
Go library for embedded vector search and semantic embeddings using llama.cpp
Embeddable vector database for Go with Chroma-like interface and zero third-party dependencies. In-memory with optional persistence.
Access Gemini LLMs from the command-line
Go Bindings for BERT NLP Models
The Go client for Chroma vector database
Go implementation of @qdrant/fastembed.
Go module for fetching embeddings from embeddings providers
A lightweight, production-ready RAG (Retrieval Augmented Generation) library in Go.
go native port of annoy. Approximate Nearest Neighbors in optimized for memory usage and loading/saving to disk.
🧬🔍🗄️ Unlock the power of vector indexing and search in your Go applications with the HNSW algorithm for approximate nearest neighbor search, seamlessly embedded within your application.
Kikiola is a high-performance vector database written in Go.
Metadata management in Go
DocsGPT is a powerful web app that allows you to embed your documents then query them using natural language
Go wrapper for bert.cpp embeddings library using cgo/dll approach.
Add a description, image, and links to the embeddings topic page so that developers can more easily learn about it.
To associate your repository with the embeddings topic, visit your repo's landing page and select "manage topics."