LlamaIndex

A simple, flexible data framework for connecting custom data sources to large language models. LlamaParse is the world. LlamaIndex helps developers build LLM applications that connect large language models to private or domain-specific data, with a strong focus on Retrieval-Augmented Generation (RAG), document parsing, intelligent agents, and multi-step workflows. While RAG remains a core strength, LlamaIndex also supports building autonomous agents, event-driven workflows, multi-modal applications, chat engines, and document automation tools beyond simple question-answering. It supports over 90 unstructured file types through LlamaParse, including PDFs with complex layouts, tables, images, spreadsheets, handwritten notes, and more, plus connectors for APIs, databases, and other sources. LlamaIndex focuses primarily on data indexing, ingestion, and high-accuracy retrieval (especially for documents), while LangChain offers broader modular orchestration for complex chains, tools, and multi-step reasoning; many teams combine both for best results. Basic Python knowledge helps a lot since it's a developer-first framework, though managed services like LlamaCloud and pre-built templates make it more accessible for getting started quickly. It integrates with a wide range of models including local ones via Ollama or other providers, giving you flexibility beyond just commercial APIs like OpenAI.