# LangGraph — Build Stateful AI Agents as Graphs

> LangChain framework for building resilient, stateful AI agents as graphs. Supports cycles, branching, persistence, human-in-the-loop, and streaming. 28K+ stars.

## Install

Save as a script file and run:

## Quick Use

```bash
pip install langgraph
```

```python
from langgraph.graph import StateGraph, START, END

def chatbot(state):
    return {"messages": [llm.invoke(state["messages"])]}

graph = StateGraph({"messages": list})
graph.add_node("chatbot", chatbot)
graph.add_edge(START, "chatbot")
graph.add_edge("chatbot", END)
app = graph.compile()
```

---

## Intro

LangGraph is a framework by LangChain for building stateful, multi-actor AI agent applications modeled as graphs. Unlike simple chain-based workflows, LangGraph supports cycles, conditional branching, state persistence, human-in-the-loop interactions, and streaming — essential for production agents. 28,000+ GitHub stars.

**Best for**: Developers building complex, stateful AI agents that need persistence and human oversight
**Works with**: OpenAI, Anthropic, Google, any LangChain-supported model

---

## Key Concepts

### State Graphs
Define agent logic as a directed graph with nodes (functions) and edges (transitions):
```python
graph.add_node("research", research_fn)
graph.add_node("write", write_fn)
graph.add_conditional_edges("research", route_fn, {"done": "write", "more": "research"})
```

### Persistence & Checkpoints
Save and resume agent state across sessions:
```python
from langgraph.checkpoint.memory import MemorySaver
app = graph.compile(checkpointer=MemorySaver())
```

### Human-in-the-Loop
Pause execution for human approval before critical actions:
```python
graph.add_node("approve", interrupt_before=True)
```

### Streaming
Stream intermediate results, tool calls, and token-by-token output.

### LangGraph Platform
Deploy agents as scalable APIs with built-in monitoring via LangGraph Cloud.

---

### FAQ

**Q: What is LangGraph?**
A: A LangChain framework for building stateful AI agents as directed graphs, with support for cycles, persistence, human-in-the-loop, and streaming. 28K+ GitHub stars.

**Q: Do I need LangChain to use LangGraph?**
A: LangGraph can work standalone, but integrates seamlessly with LangChain for model providers, tools, and retrievers.

---

## Source & Thanks

> Created by [LangChain](https://github.com/langchain-ai). Licensed under MIT.
> [langchain-ai/langgraph](https://github.com/langchain-ai/langgraph) — 28,000+ GitHub stars

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Source: https://tokrepo.com/en/workflows/cc1a6ed2-0d82-4379-94f4-15632b4d4967
Author: TokRepo Curated