LangChain vs LlamaIndex

Choose LangChain if…

Best for developers building custom applications on top of large language models, and its edge is composable chains, agents, and memory abstractions that cut LLM app code from hundreds of lines to dozens. The standard starting framework for LLM app development, expect the API to keep shifting under you. Lean toward LlamaIndex instead if a wide library of data connectors that ingest PDFs, wikis, and databases into a queryable index matters more for your use case.

Choose LlamaIndex if…

Best for developers building retrieval-augmented generation apps that need to query private or enterprise data, and its edge is a wide library of data connectors that ingest PDFs, wikis, and databases into a queryable index. The strongest RAG-specific framework available, expect real overlap and some redundant decisions against LangChain. Lean toward LangChain instead if composable chains, agents, and memory abstractions that cut LLM app code from hundreds of lines to dozens matters more for your use case.