LangChain vs LlamaIndex: Which Should You Use?
Two frameworks dominate the LLM application space. Here's an honest comparison to help you choose the right one.
Quick Answer
LangChain is a general-purpose orchestration framework best for complex agent workflows. LlamaIndex is specialized for data indexing and retrieval, making it ideal for RAG-focused applications. Many teams use both.
Philosophy & Focus
LangChain aims to be the Swiss Army knife of LLM development — it handles everything from prompts to agents. LlamaIndex focuses specifically on connecting LLMs to data, with sophisticated indexing strategies.
Developer Experience
LangChain has a steeper learning curve due to its breadth. LlamaIndex gets you to a working RAG system faster. Both have excellent documentation and active communities.
Use Cases
- Choose LangChain for complex multi-step agent workflows
- Choose LlamaIndex for data-heavy retrieval applications
- Use both together for production RAG with agent capabilities
When Not to Use
- Don't use either if a simple API call solves your problem
- Avoid LangChain if you only need document retrieval
- Avoid LlamaIndex if you need complex tool-using agents
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