LangGraph

LangGraph is a framework for building stateful, multi-step, and agentic AI workflows using a graph-based architecture.

LangGraph is closely related to LangChain, but it focuses more on complex AI workflows and agents.

Think of a normal AI application as:

Input → AI → Output

But an AI agent may need to perform multiple steps:

User Question
      ↓
Understand Question
      ↓
Search Information
      ↓
Analyze Information
      ↓
Call Tool
      ↓
Check Result
      ↓
If necessary → Search Again
      ↓
Final Answer

This type of workflow can involve loops, decisions, multiple agents, and persistent state.

LangGraph represents these operations as a graph.

For example:

             ┌──────────────┐
             │ User Request │
             └──────┬───────┘
                    ↓
             ┌──────────────┐
             │   Analyze   │
             └──────┬───────┘
                    ↓
             ┌──────────────┐
             │ Search Data  │
             └──────┬───────┘
                    ↓
             ┌──────────────┐
             │ Check Result │
             └──────┬───────┘
                    ↓
             ┌──────────────┐
             │ Good Result? │
             └───┬──────┬───┘
                 │      │
                Yes     No
                 ↓      │
              Answer ←──┘

The important concept is state.

An agent can remember what it has already done during a workflow and use that information in later steps.

LangChain vs LangGraph

LangChain	LangGraph
Framework for LLM applications	Framework for complex AI workflows
Components and integrations	Graph-based workflows
Chains and tools	Nodes, edges, state
Good for straightforward workflows	Good for agents and complex workflows
Can be used to build AI applications	Useful for controlling agent behavior

Imagine an AI research assistant.

It receives:

“Research electric vehicles and prepare a report.”

It could:

Start
 ↓
Search Web
 ↓
Collect Information
 ↓
Analyze Information
 ↓
Identify Missing Information
 ↓
Search Again
 ↓
Write Report
 ↓
Review Report
 ↓
Final Answer

LangGraph is useful for controlling this type of multi-step process.

LangGraph = Framework for building controlled, stateful, multi-step AI agents and workflows.