{"repo":"teilomillet/raggo","free":true,"listed":false,"github":"https://github.com/teilomillet/raggo","clone":"git clone https://github.com/teilomillet/raggo.git","description":"A lightweight, production-ready RAG (Retrieval Augmented Generation) library in Go.","language":"Go","stars":222,"topics":["ai","document-search","embeddings","golang","llm","milvus","openai","question-answering","rag","vector-database"],"license":"Apache-2.0","category":"ai-agents","readme_excerpt":"Raggo - Retrieval Augmented Generation Library A flexible RAG (Retrieval Augmented Generation) library for Go, designed to make document processing and context-aware AI interactions simple and efficient. 🔍 Smart Document Search • 💬 Context-Aware Responses • 🤖 Intelligent RAG Quick Start Configuration Raggo provides a flexible configuration system that can be loaded from multiple sources (environment variables, JSON files, or programmatic defaults): Configuration can be saved for reuse: Environment variables (take precedence over config files): - RAGGO PROVIDER : Service provider - RAGGO MODEL : Model identifier - RAGGO COLLECTION : Collection name - RAGGO API KEY : Default API key Table of Contents Part 1: Core Components 1. Quick Start 2. Building Blocks - Document Loading - Text Parsing - Text Chunking - Embeddings - Vector Storage Part 2: RAG Implementations 1. Simple RAG - Basic Usage - Document Q&A - Configuration 2. Contextual RAG - Advanced Features - Context Window - Hybrid Search 3. Memory Context - Chat Applications - Memory Management - Context Enhancement 4. Advanced Use Cases - Full Processing Pipeline - Concurrent Processing - Rate Limiting Part 1: Core Components Quick Start Prerequisites Building Blocks Document Loading Text Parsing Text Chunking Embeddings Vector Storage Part 2: RAG Implementations Simple RAG Best for straightforward document Q&A: Contextual RAG For complex document understanding and context-aware responses: Advanced Configuration Memory C","default_branch":null,"files":null,"tree":[],"storefront":"/r/teilomillet","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/teilomillet/raggo/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}