LangChain vs LlamaIndex: AI Framework Comparison
Comparing two major AI application frameworks. Use cases, strengths, choosing.
LangChain
Broader scope. Chains, agents, memory, tools. Larger community. Some criticism for complexity.
LlamaIndex
Specialized in RAG and retrieval. Strong document handling. Often combined with LangChain.
Combination
Many use both. LangChain for orchestration, LlamaIndex for retrieval.
Bottom line
Not exclusive. Match to use case. Combine where appropriate.
Frequently asked questions
LangChain or LlamaIndex?
Different scopes. LangChain broader (agents, chains). LlamaIndex retrieval-focused (RAG). Many use both.
Are they competing?
Overlapping but different focus. Some teams prefer one. Many combine. Not zero-sum.
Learning curve?
Both substantial. LangChain criticized for complexity. LlamaIndex more focused. Documentation matters.
Production-ready?
Both used in production. LangChain especially mature. LlamaIndex growing rapidly.
Alternatives?
Direct API integration possible without frameworks. Microsoft Semantic Kernel. Pydantic AI. Growing options.
Related guides
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