langchain vs llama_index

Common questions

When would neither LangChain nor LlamaIndex be the best choice?

Neither LangChain nor LlamaIndex would be the best choice if a project requires enterprise-level features such as agentic OCR, as LlamaIndex's focus has shifted towards LlamaParse, an enterprise platform. Additionally, if a developer prefers a framework that does not offer built-in capabilities for common usage patterns such as planning and subagents, LangChain might not be the best fit.

What is the difference between langchain and llama_index?

langchain: The agent engineering platform.. llama_index: Document processing platform for AI. See the comparison table for live GitHub stats and shared categories.

When should I choose langchain over llama_index?

Choose langchain over llama_index when LlamaIndex can integrate with LangChain to bring enhanced capabilities and flexibility when designing complex multi-agent systems, leveraging the strength of both frameworks; Tags unique to langchain: ai-agents, langchain, multiagent, open-source; Also covers LLM Frameworks; When you need a framework that simplifies chaining together interoperable components and third-party integrations for AI application development.

When should I choose llama_index over langchain?

Choose llama_index over langchain when LlamaIndex can integrate with LangChain to bring enhanced capabilities and flexibility when designing complex multi-agent systems, leveraging the strength of both frameworks; Tags unique to llama_index: application, data, fine-tuning, llamaindex; Also covers Data & Retrieval, Developer Tools, Model Training; When you need a framework that focuses on document parsing and extraction, as LlamaIndex has evolved to prioritize these capabilities.

When should I avoid langchain?

If you prefer a framework that does not offer built-in capabilities for common usage patterns such as planning and subagents, as LangChain's Deep Agents provide these features. When you need a higher-level abstraction that does not require detailed agent orchestration, as LangChain's LangGraph is designed for low-level control over agent workflows.

When should I avoid llama_index?

If your project requires enterprise-level features such as agentic OCR, as LlamaIndex's primary focus has shifted towards LlamaParse, an enterprise platform When you need a tool that is actively developed and maintained as the primary focus of the company has shifted towards LlamaParse and LiteParse, and the OSS framework is now a secondary focus

Is langchain or llama_index more popular on GitHub?

langchain has more GitHub stars (146,576 vs 52,207). Stars measure visibility, not whether either tool fits your constraints.

Are langchain and llama_index open source?

Yes - both are open-source projects on GitHub (langchain: MIT, llama_index: MIT).

Where can I find alternatives to langchain or llama_index?

GraphCanon lists graph-backed alternatives at langchain alternatives and llama_index alternatives (langchain markdown twin, llama_index markdown twin), ranked by typed relationship edges rather than popularity votes.

Is there a machine-readable version of this comparison?

Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

Which is better maintained, langchain or llama_index?

langchain: Very active. llama_index: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.

Where are the full trust reports for langchain and llama_index?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: langchain trust report; llama_index trust report.