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

Requirements:

Configure the API key for the agent’s reasoning model.
Create a LAS general dataset in advance and obtain its DatasetId.
Configure the LAS service DatasetId and URL (how to get the URL).

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

examples/tools/las/agent.py

import asyncio
import os

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=(
        f"You are a poet. First search dataset {os.environ['TOOL_LAS_DATASET_ID']} 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())

Dataset and connection checks

Set the service URL before importing las. TOOL_LAS_DATASET_ID is not automatically applied as a filter to every tool call. Select the dataset explicitly in instructions or tool arguments, and enforce access permissions on the server. Ingest searchable content into the configured dataset before running the example. This check only lists tools exposed by the service. If discovery succeeds but retrieval is empty, check the selected dataset, ingested content, and permissions. The endpoint comes from TOOL_LAS_URL and is not switched automatically by CLOUD_PROVIDER.

import asyncio

from veadk.tools.builtin_tools.las import las


async def main():
    try:
        tools = await las.get_tools()
        print([tool.name for tool in tools])
    finally:
        await las.close()


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

Overview

Get started

Core components

Observability

Extensions

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Security

Deployment

Overview

Environment & prerequisites

Usage

Dataset and connection checks

​Overview

​Environment & prerequisites

​Usage

​Dataset and connection checks

Overview

Environment & prerequisites

Usage

Dataset and connection checks