AI / LlamaIndex Interview Questions
What is the difference between LlamaIndex and LangChain?
LlamaIndex and LangChain both help build LLM applications, but they grew out of different core focuses. LlamaIndex started as a data framework specialized in ingestion, indexing, and retrieval, with deep tooling around chunking strategies, index types, and RAG-specific evaluation.
LangChain started as a broader orchestration framework for chaining LLM calls, tools, and agents together across many integrations, with retrieval being one capability among many rather than the central focus.
| LlamaIndex | LangChain |
| Deep, specialized RAG/indexing tooling | Broad chain and agent orchestration |
| Strong built-in evaluation for retrieval quality | Large ecosystem of integrations across many task types |
In practice the two overlap and are sometimes combined, for example using a LlamaIndex query engine as a retrieval tool inside a LangChain agent, so the choice often comes down to which framework's abstractions fit the team's mental model better rather than one being strictly superior.
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