LangChain vs LlamaIndex

LangChain is a free, MIT-licensed open-source framework for building agents with models and tools. Its create_agent harness combines a model, tools, prompt and middleware, with templates for common uses and a ReAct pattern. Middleware can add human approval, conversation compression, sensitive-data removal, guardrails, retries, routing and custom tool policies. Agents run on LangGraph’s durable runtime, which supports persistence, rewind, checkpointing and human-in-the-loop workflows. LangChain documents more than 1,000 integrations across chat and embedding models, tools, toolkits, document loaders and vector stores. Standard interfaces for chat models and embeddings support switching providers with minimal code changes. Documentation covers Python and JavaScript/TypeScript. LangSmith adds tracing, debugging and output evaluation. The framework supports API and self-hosted use. LangChain was started in 2023 and is headquartered in San Francisco.

LlamaIndex is a freemium platform for developers and enterprises automating document processing and AI workflows. LlamaParse handles more than 50 unstructured file types, including files with embedded images, complex layouts, multi-page tables and handwritten notes. Schema-based, language-model extraction agents convert unstructured content into structured insights without training. Workflows can divide documents into logical sections and classify them using natural-language descriptions and rules. Chunking and embedding pipelines support indexing and retrieval in RAG workflows. Community integrations cover data loaders, agent tools, language models, vector stores, observability and application frameworks. LlamaCloud connectors currently include Google Drive, SharePoint, S3 and Confluence. Free and Starter plans allow five concurrent parse, extract, classify and split jobs; Pro allows 20 and Enterprise 100. The Free plan has no listed price; Starter costs $50.00 per month. LlamaParse is commercial, while LlamaIndex and Workflows are open-source.