# LangGraph

{% embed url="<https://www.youtube.com/watch?v=_ZiQ-3p93PM>" %}
Chatbot example using Verida PersonalAgentKit with Langchain
{% endembed %}

Our first release supports typescript LangGraph tools to easily integrate with any LangChain / LangGraph application.

You can locally run the [Command Line Chat Bot](https://github.com/verida/personal-agent-kit/tree/main/typescript/examples/chatbot) to access your data stored in your [Verida Vault](/resources/verida-vault.md) to experiment and learn what is possible.

You can integrate these tools into your existing LangGraph / LangChain project, see the [README file for the LangGraph typescript tools library](https://github.com/verida/personal-agent-kit/blob/main/typescript/extensions/langchain/README.md) for example code snippets and instructions.

{% hint style="info" %}
We currently only support typescript, but will gladly award a [grant](/resources/grants.md) to anyone who implements a Python library.
{% endhint %}


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.verida.ai/integrations/langgraph.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.