> ## Documentation Index
> Fetch the complete documentation index at: https://docs-preprod.sambanova.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# LangGraph

LangGraph provides low-level infrastructure for building long-running, stateful workflows and agents.

## Prerequisites

* A SambaCloud API key\
  Create a [SambaCloud account](https://cloud.sambanova.ai/apis) and generate an API key from the **API Keys** tab.
* Python 3.11.5 or later

## Installation and setup

1. Create a virtual environment:

```bash
python -m venv .venv
source .venv/bin/activate
```

2. install the required libraries

```bash
pip install langchain-sambanova langchain langgraph
```

## Example use cases

You can use LangGraph with SambaCloud to create multi-agent workflows such as:

* Web search
* Retrieval-Augmented Generation (RAG)
* SQL agents

## Example notebooks

[Agentic Search](https://github.com/sambanova/integrations/blob/main/langgraph/agentic_search.ipynb): Build a chatbot that integrates a web search tool with SambaCloud LLM.

### **LangGraph documentation**

See [LangGraph documentation](https://langchain-ai.github.io/langgraph/) for more details.