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

# LangGraph integration guide

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

## Prerequisites

* A [SambaCloud](http://cloud.sambanova.ai/?utm_source=langgraph\&utm_medium=external\&utm_campaign=cloud_signup) account with an API key
* Python 3.11.5 or higher installed

## Installation and setup

1. Create a virtual environment:

```bash theme={null}
python -m venv .venv
source .venv/bin/activate
```

2. install the required libraries

```bash theme={null}
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://docs.langchain.com/oss/python/langgraph/overview) for more details.