LlamaIndex Has a Free Data Framework for Building RAG Applications With LLMs

LlamaIndex is the leading data framework for building RAG (Retrieval-Augmented Generation) applications. It connects your data to LLMs with minimal code. What You Get for Free Data connectors — 160+ sources (PDF, SQL, APIs, Notion, Slack) Indexing — automatic chunking, embedding, and storage Query engine — natural language over your data Agents — data-aware autonomous agents Workflows — event-driven orchestration Evaluation — built-in RAG evaluation metrics LlamaParse — best PDF/document parsing Simple RAG from llama_index.core import VectorStoreIndex , SimpleDirectoryReader documents = SimpleDirectoryReader ( ' data ' ). load_data () index = VectorStoreIndex . from_documents ( documents ) query_engine = index . as_query_engine () response = query_engine . query ( ' What is our refund policy? ' ) print ( response ) 3 lines to build a RAG app over your documents. LlamaIndex vs LangChain Feature LlamaIndex LangChain Focus RAG/data General LLM Data connectors 160+ Fewer Simplicity Higher