> ## 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.

# Volcengine search

## Overview

Tool identifier `vesearch`.

`vesearch` searches via Volcengine's [web-aware Q\&A Agent](https://www.volcengine.com/docs/85508/1512748). The tool reads its own credentials from environment variables — you do not pass an `api_key` on the `Agent`.

Import path: `from veadk.tools.builtin_tools.vesearch import vesearch`

## Environment & prerequisites

<Warning>
  Requirements:

  1. Configure the API key for the agent's reasoning model.
  2. Configure the Q\&A Agent ID (create an agent in the [console](https://console.volcengine.com/ask-echo/my-agent), then copy its ID) into the `TOOL_VESEARCH_ENDPOINT` environment variable.
  3. Configure the Q\&A Agent API key into the `TOOL_VESEARCH_API_KEY` environment variable.
</Warning>

Environment variables:

* `MODEL_AGENT_API_KEY`: API key for the agent's reasoning model
* `TOOL_VESEARCH_ENDPOINT`: the Q\&A Agent ID (**must be set as an environment variable**)
* `TOOL_VESEARCH_API_KEY`: the Q\&A Agent API key

## Usage

```python title="examples/tools/vesearch/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.vesearch import vesearch

agent = Agent(
    name="vesearch_agent",
    model_name="doubao-seed-2-1-pro-260628",
    description="An agent that answers questions with veSearch.",
    instruction="You are a helpful assistant. Use the vesearch tool to look things up online.",
    tools=[vesearch],
)

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


async def main():
    response = await runner.run("What's the weather in Hangzhou today?")
    print(response)


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