Distributed vector search for AI-native applications
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Updated
Oct 12, 2024 - Go
Distributed vector search for AI-native applications
Go wrapper for bert.cpp embeddings library using cgo/dll approach.
The Go client for Chroma vector database
Access Gemini LLMs from the command-line
Fast & less costly AI decision making and intelligent processing of multi-modal data.
Chroma DB vector database, with embedding and reranker models to implement a Retrieval Augmented Generation (RAG) system.
Embeddable vector database for Go with Chroma-like interface and zero third-party dependencies. In-memory with optional persistence.
Call Gemini (https://ai.google.dev) embedding models with OpenAI-compatible endpoints
Telegram bot that allows users to create and chat with multiple personalized AI assistants each with a relevant history
Go library for document management and vector-based querying, ideal for NLP and AI applications.
Go module for fetching embeddings from embeddings providers
Go implementation of @qdrant/fastembed.
go native port of annoy. Approximate Nearest Neighbors in optimized for memory usage and loading/saving to disk.
Kikiola is a high-performance vector database written in Go.
🧬🔍🗄️ 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.
DocsGPT is a powerful web app that allows you to embed your documents then query them using natural language
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