Learn ↗

Documentation Index#

Fetch the complete documentation index at: https://docs.langchain.com/llms.txt Use this file to discover all available pages before exploring further.

Tutorials, conceptual guides, and resources to help you get started.

In the Learn section of the documentation, you’ll find a collection of tutorials, conceptual overviews, and additional resources to help you build powerful applications with LangChain and LangGraph.

Use cases#

Below are tutorials for common use cases, organized by framework.

Deep Agents#

Deep agents include built-in functionality for managing context, a virtual filesystem, and other common agent requirements.

Build a data analysis agent that sends reports to Slack.

LangChain#

LangChain agent implementations make it easy to get started for simple use cases.

Build a semantic search engine over a PDF with LangChain components.

Create a Retrieval Augmented Generation (RAG) agent.

Build a SQL agent to interact with databases with human-in-the-loop review.

Build an agent you can speak and listen to.

LangGraph#

LangChain’s agent implementations use LangGraph primitives. If deeper customization is required, agents can be implemented directly in LangGraph.

Build a RAG agent using LangGraph primitives for fine-grained control.

Multi-agent#

These tutorials demonstrate multi-agent patterns, blending LangChain agents with LangGraph workflows.

Conceptual overviews#

These guides explain the core concepts and APIs underlying LangChain and LangGraph.

Understand persistence of interactions within and across threads.

Learn methods for providing AI applications the right information and tools to accomplish a task.

Explore LangGraph’s declarative graph-building API.

Build agents as a single function.

Additional resources#

Courses and exercises to level up your LangChain skills.

See how teams are using LangChain and LangGraph in production.

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Connect these docs to Claude, VSCode, and more via MCP for real-time answers.