langchain vs llama_index

Common questions

When should one choose LangChain over LlamaIndex?

Choose LangChain for building sophisticated agents with high-level capabilities like planning. Use it if third-party integrations for chat and embeddings are needed.

In what scenarios is LlamaIndex more suitable than LangChain?

Select LlamaIndex when advanced OCR or document indexing features are critical to the project, thanks to its robust extraction tools and integration options.

What is the difference between langchain and llama_index?

langchain: The agent engineering platform.. llama_index: Leading document agent and OCR platform. 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 Pricing: LangChain itself is open-source and free to use. However, it might rely on paid services or premium models from external platforms like OpenAI.; 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, anthropic, chatgpt, deepagents; Also covers LLM Frameworks; * When aiming to build complex AI-powered agents or applications requiring high-level capabilities like planning, subagent interaction, and file system operations.

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, framework; Also covers Data & Retrieval; - When you need to work with document agents or require advanced OCR capabilities involving multiple formats.

When should I avoid langchain?

* When working on smaller, less complex projects where full-scale integration with sophisticated components is not necessary as LangChain's extensive features might introduce unnecessary complexity. * If you are primarily focused on JavaScript or TypeScript development as the primary focus of LangChain is Python. Although there is a JS/TS equivalent (LangChain.js), it may not offer the same depth * For projects requiring heavy customization at lower levels, where a more granular control over individual components is required rather than working with an integrated framework.

When should I avoid llama_index?

- Avoid using if your primary need is a simple, lightweight solution that doesn't require the extensive OCR or agentic capabilities provided by LlamaIndex. - If specific features like 'Parse', 'Extract', and 'Index' are not necessary for your project, simpler alternatives might be more suitable. - In scenarios where customization beyond integrating existing plugins isn't required; LlamaIndex's strength lies in its integration library, which may not cover all niche needs without modification.

Is langchain or llama_index more popular on GitHub?

langchain has more GitHub stars (143,615 vs 51,442). 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.