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

# LAS data lake

## Overview

`las` (`from veadk.tools.builtin_tools.las import las`) is built on the AI multimodal data lake service LAS, providing creation, preview, query/analysis, editing, and cleaning of multimodal datasets.

## Environment & prerequisites

<Warning>
  Requirements:

  1. Configure the API key for the agent's reasoning model.
  2. [Create a LAS general dataset](https://console.volcengine.com/las/region:las+cn-beijing/next/dataset/common/create) in advance and obtain its DatasetId.
  3. Configure the LAS service DatasetId and URL ([how to get the URL](https://www.volcengine.com/mcp-marketplace/detail?name=LAS%20MCP)).
</Warning>

Environment variables (**must be set as environment variables**):

* `MODEL_AGENT_API_KEY`: API key for the agent's reasoning model
* `TOOL_LAS_URL`: LAS MCP Server service address
* `TOOL_LAS_DATASET_ID`: dataset ID used by the LAS service

## Usage

```python title="examples/tools/las/agent.py" lines theme={null}
import asyncio

from veadk import Agent, Runner
from veadk.memory.short_term_memory import ShortTermMemory
from veadk.tools.builtin_tools.las import las

agent = Agent(
    name="las_agent",
    model_name="doubao-seed-2-1-pro-260628",
    description="Answer using data in LAS.",
    instruction=(
        "You are a poet. First use the las tool to search the ds_public dataset for "
        "relevant content, then write a poem based on the results."
    ),
    tools=[las],
)

runner = Runner(agent=agent, short_term_memory=ShortTermMemory())


async def main():
    response = await runner.run("Write a Chinese-style poem about wood and love")
    print(response)


if __name__ == "__main__":
    asyncio.run(main())
```