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LlamaIndex

Leading data framework for LLMs — RAG, document Q&A, and knowledge retrieval

½
4.5(876 reviews)
open-sourceDR 81Open source (MIT). LlamaCloud from $97/mo for managed indexingView full pricing →

Visit LlamaIndex

https://llamaindex.ai

About LlamaIndex

LlamaIndex (formerly GPT Index) is the leading data framework for LLM applications, specializing in connecting large language models to any data source. Where LangChain covers general agent orchestration, LlamaIndex excels at data ingestion, indexing, and retrieval — making it the go-to for enterprise RAG, document Q&A, and knowledge graph applications. LlamaCloud provides managed indexing infrastructure for production deployments.

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Key Features

Document loaders for 100+ formats (PDF, Word, Notion, Confluence)
Advanced chunking and indexing strategies
Vector store integrations (Pinecone, Weaviate, Qdrant, etc.)
Query engines with sub-question decomposition
Knowledge graph indexing (KnowledgeGraph Index)
Multi-document agents
LlamaCloud: managed parsing and indexing
Evaluation toolkit for RAG pipelines

LlamaIndex Pros & Cons

Pros

  • +Best-in-class data ingestion and preprocessing
  • +Superior RAG pipeline performance vs raw implementations
  • +Handles complex document structures (tables, figures, nested headers)
  • +LlamaParse for enterprise document parsing (PDFs especially)
  • +Strong academic research backing and benchmarks

⚠️ Cons

  • More specialized than LangChain — less good for general agents
  • LlamaCloud can get expensive at scale
  • Steeper learning curve than simple embed-and-retrieve
  • Documentation can lag behind releases

Who Is LlamaIndex Best For?

👤Teams building enterprise document Q&A systems
👤Developers implementing production RAG pipelines
👤Anyone needing to query large proprietary knowledge bases
👤Data engineers connecting LLMs to structured/unstructured data

Tags

llamaindexragllm frameworkdata indexingdocument aiknowledge retrievaldeveloper tools
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Public API

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Auth

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