> ## Documentation Index
> Fetch the complete documentation index at: https://docs-v1.agno.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Async Tools

Agno Agents can execute multiple tools concurrently, allowing you to process function calls that the model makes efficiently. This is especially valuable when the functions involve time-consuming operations. It improves responsiveness and reduces overall execution time.

Here is an example:

```python async_tools.py theme={null}
import asyncio
import time

from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.utils.log import logger

async def atask1(delay: int):
    """Simulate a task that takes a random amount of time to complete
    Args:
        delay (int): The amount of time to delay the task
    """
    logger.info("Task 1 has started")
    for _ in range(delay):
        await asyncio.sleep(1)
        logger.info("Task 1 has slept for 1s")
    logger.info("Task 1 has completed")
    return f"Task 1 completed in {delay:.2f}s"


async def atask2(delay: int):
    """Simulate a task that takes a random amount of time to complete
    Args:
        delay (int): The amount of time to delay the task
    """
    logger.info("Task 2 has started")
    for _ in range(delay):
        await asyncio.sleep(1)
        logger.info("Task 2 has slept for 1s")
    logger.info("Task 2 has completed")
    return f"Task 2 completed in {delay:.2f}s"


async def atask3(delay: int):
    """Simulate a task that takes a random amount of time to complete
    Args:
        delay (int): The amount of time to delay the task
    """
    logger.info("Task 3 has started")
    for _ in range(delay):
        await asyncio.sleep(1)
        logger.info("Task 3 has slept for 1s")
    logger.info("Task 3 has completed")
    return f"Task 3 completed in {delay:.2f}s"


async_agent = Agent(
    model=OpenAIChat(id="gpt-4o-mini"),
    tools=[atask2, atask1, atask3],
    show_tool_calls=True,
    markdown=True,
)

asyncio.run(
    async_agent.aprint_response("Please run all tasks with a delay of 3s", stream=True)
)
```

Run the Agent:

```bash theme={null}
pip install -U agno openai

export OPENAI_API_KEY=***

python async_tools.py
```

How to use:

1. Provide your Agent with a list of tools, preferably asynchronous for optimal performance. However, synchronous functions can also be used since they will execute concurrently on separate threads.
2. Run the Agent using either the `arun` or `aprint_response` method, enabling concurrent execution of tool calls.

<Note>
  Concurrent execution of tools requires a model that supports parallel function
  calling. For example, OpenAI models have a `parallel_tool_calls` parameter
  (enabled by default) that allows multiple tool calls to be requested and
  executed simultaneously.
</Note>

In this example, `gpt-4o` makes three simultaneous tool calls to `atask1`, `atask2` and `atask3`. Normally these tool calls would execute sequentially, but using the `aprint_response` function, they run concurrently, improving execution time.

<img height="200" src="https://mintcdn.com/agno/0omqNXZ9CSqcNU7_/images/async-tools.png?fit=max&auto=format&n=0omqNXZ9CSqcNU7_&q=85&s=342d0568f47ed2d008e91a87394cd4b6" style={{ borderRadius: "8px" }} data-path="images/async-tools.png" />