agent framework
LangChain vs LlamaIndex
LangChain and LlamaIndex are the two most popular Python frameworks for LLM applications. They overlap, but they started from different mental models: agents vs data.
Contender A
LangChain
General-purpose agent framework
Contender B
LlamaIndex
Data-first RAG framework
Side-by-side comparison
Metric
LangChain
LlamaIndex
Primary focus
Agents + chains
Indexing + retrieval
Composability
LCEL / LangGraph
Workflows + Agents
Observability
LangSmith
Arize / custom
Best doc depth
Agents + tools
RAG patterns
When LangChain is the right pick
Multi-step agents, tool orchestration, production guardrails.
When LlamaIndex is the right pick
Deep RAG pipelines where the hard problem is the retrieval, not the agent loop.
Verdict
Use LangChain when the problem is orchestration; use LlamaIndex when the problem is retrieval quality. Many teams use both.
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