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LlamaIndex

Open-source data framework for building LLM-powered RAG applications

★ 36,000 GitHub MIT ragllmdata-frameworkpythonagentsretrievalembeddings RAG & Knowledge

Overview

LlamaIndex is a powerful open-source data framework that connects LLMs to your data. With 36,000+ GitHub stars, it provides data connectors for over 160 sources, flexible index structures, and powerful query engines for building production-ready RAG (Retrieval-Augmented Generation) applications. Whether you’re building a simple Q&A bot over documents or a complex multi-agent system, LlamaIndex offers the tools you need: document parsing, chunking, embedding management, vector store integration, advanced retrieval strategies, and agentic reasoning. It supports Python and TypeScript, integrates with LangChain, and is used by thousands of developers worldwide.

Requirements

Min vCPU
1
Min RAM
2048 MB
Min Disk
10 GB
Rec vCPU
2
Rec RAM
4096 MB
Rec Disk
20 GB

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