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

# Airflow

## Example

The following agent will use Airflow to save and read a DAG file.

```python cookbook/tools/airflow_tools.py theme={null}
from phi.agent import Agent
from phi.tools.airflow import AirflowToolkit

agent = Agent(
    tools=[AirflowToolkit(dags_dir="dags", save_dag=True, read_dag=True)], show_tool_calls=True, markdown=True
)


dag_content = """
from airflow import DAG
from airflow.operators.python import PythonOperator
from datetime import datetime, timedelta
default_args = {
    'owner': 'airflow',
    'depends_on_past': False,
    'start_date': datetime(2024, 1, 1),
    'email_on_failure': False,
    'email_on_retry': False,
    'retries': 1,
    'retry_delay': timedelta(minutes=5),
}
# Using 'schedule' instead of deprecated 'schedule_interval'
with DAG(
    'example_dag',
    default_args=default_args,
    description='A simple example DAG',
    schedule='@daily',  # Changed from schedule_interval
    catchup=False
) as dag:
    def print_hello():
        print("Hello from Airflow!")
        return "Hello task completed"
    task = PythonOperator(
        task_id='hello_task',
        python_callable=print_hello,
        dag=dag,
    )
"""

agent.run(f"Save this DAG file as 'example_dag.py': {dag_content}")


agent.print_response("Read the contents of 'example_dag.py'")
```

## Toolkit Params

| Parameter  | Type            | Default          | Description                                      |
| ---------- | --------------- | ---------------- | ------------------------------------------------ |
| `dags_dir` | `Path` or `str` | `Path.cwd()`     | Directory for DAG files                          |
| `save_dag` | `bool`          | `True`           | Whether to register the save\_dag\_file function |
| `read_dag` | `bool`          | `True`           | Whether to register the read\_dag\_file function |
| `name`     | `str`           | `"AirflowTools"` | The name of the tool                             |

## Toolkit Functions

| Function        | Description                                        |
| --------------- | -------------------------------------------------- |
| `save_dag_file` | Saves python code for an Airflow DAG to a file     |
| `read_dag_file` | Reads an Airflow DAG file and returns the contents |

## Information

* View on [Github](https://github.com/agno-agi/phidata/blob/main/phi/tools/airflow.py)