---
title: Tutorials
---

# Tutorials

Welcome to the LangGraph.js Tutorials! These notebooks introduce LangGraph through building various language agents and applications.

## Quick Start

Learn the basics of LangGraph through a comprehensive quick start in which you will build an agent from scratch.

- [Quick Start](quickstart.ipynb)
- [Common Workflows](workflows/index.md): Overview of the most common workflows using LLMs implemented with LangGraph.
- [LangGraph Cloud Quick Start](/langgraphjs/cloud/quick_start/): In this tutorial, you will build and deploy an agent to LangGraph Cloud.

## Use cases

Learn from example implementations of graphs designed for specific scenarios and that implement common design patterns.

#### Chatbots

- [Customer support with a small model](chatbots/customer_support_small_model.ipynb)

#### RAG

- [Agentic RAG](rag/langgraph_agentic_rag.ipynb)
- [Corrective RAG](rag/langgraph_crag.ipynb)
- [Self-RAG](rag/langgraph_self_rag.ipynb)

#### Multi-Agent Systems

- [Collaboration](multi_agent/multi_agent_collaboration.ipynb): Enabling two agents to collaborate on a task
- [Supervision](multi_agent/agent_supervisor.ipynb): Using an LLM to orchestrate and delegate to individual agents
- [Hierarchical Teams](multi_agent/hierarchical_agent_teams.ipynb): Orchestrating nested teams of agents to solve problems

#### Planning Agents

- [Plan-and-Execute](plan-and-execute/plan-and-execute.ipynb): Implementing a basic planning and execution agent

#### Reflection & Critique

- [Basic Reflection](reflection/reflection.ipynb): Prompting the agent to reflect on and revise its outputs
- [Rewoo](rewoo/rewoo.ipynb): Reducing re-planning by saving observations as variables

### Evaluation

- [Agent-based](chatbot-simulation-evaluation/agent-simulation-evaluation.ipynb): Evaluate chatbots via simulated user interactions
