LangChain vs LlamaIndex
Compare LangChain and LlamaIndex on deployment, pricing, model support, and more.
LangChain
- Tagline
- Open-source LLM application framework — chains, agents, RAG, and 700+ integrations with 127K GitHub stars
- Description
- LangChain is the most widely used open-source framework for building LLM-powered applications. It provides composable abstractions for chains (sequencing LLM calls), agents (tool-using AI that can browse, run code, and call APIs), and RAG (retrieval-augmented generation with 700+ data and tool integrations). Available in Python and JavaScript, with LangSmith for observability and LangGraph for complex multi-agent workflows.
- Category
- LLM Frameworks
- Pricing
- Free
- Metric
- 139,957 GitHub stars (source)
- Link
- Visit
LlamaIndex
- Tagline
- Python RAG framework — connect LLMs to 160+ data sources with production-grade retrieval pipelines
- Description
- LlamaIndex is a Python data framework for connecting LLMs to external data sources and building retrieval-augmented generation (RAG) applications. It provides 160+ data connectors (PDFs, Notion, Slack, databases, APIs), multiple index types (vector, tree, keyword), query engines, and agent tools. LlamaIndex's focus on data ingestion and retrieval makes it the preferred framework for RAG-heavy applications, complementing LangChain's agent and chain ecosystem.
- Category
- LLM Frameworks
- Pricing
- Free
- Metric
- 50,307 GitHub stars (source)
- Link
- Visit
| Attribute | LangChain | LlamaIndex |
|---|---|---|
| Tagline | Open-source LLM application framework — chains, agents, RAG, and 700+ integrations with 127K GitHub stars | Python RAG framework — connect LLMs to 160+ data sources with production-grade retrieval pipelines |
| Category | LLM Frameworks | LLM Frameworks |
| Pricing | Free | Free |
| Description | LangChain is the most widely used open-source framework for building LLM-powered applications. It provides composable abstractions for chains (sequencing LLM calls), agents (tool-using AI that can browse, run code, and call APIs), and RAG (retrieval-augmented generation with 700+ data and tool integrations). Available in Python and JavaScript, with LangSmith for observability and LangGraph for complex multi-agent workflows. | LlamaIndex is a Python data framework for connecting LLMs to external data sources and building retrieval-augmented generation (RAG) applications. It provides 160+ data connectors (PDFs, Notion, Slack, databases, APIs), multiple index types (vector, tree, keyword), query engines, and agent tools. LlamaIndex's focus on data ingestion and retrieval makes it the preferred framework for RAG-heavy applications, complementing LangChain's agent and chain ecosystem. |
| Metric | 139,957 GitHub stars (source) | 50,307 GitHub stars (source) |
| Link | Visit | Visit |