Source code for airflow.providers.common.ai.example_dags.example_agent_durable

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"""Example DAGs demonstrating durable execution with AgentOperator and @task.agent."""

from __future__ import annotations

from datetime import timedelta

from airflow.providers.common.ai.operators.agent import AgentOperator
from airflow.providers.common.ai.toolsets.sql import SQLToolset
from airflow.providers.common.compat.sdk import dag, task

# ---------------------------------------------------------------------------
# 1. Durable AgentOperator: resumes from last model call on retry
# ---------------------------------------------------------------------------


# [START howto_operator_agent_durable]
@dag(default_args={"retries": 3, "retry_delay": timedelta(seconds=30)})

[docs]
def example_agent_durable_operator():
    """Agent with durable execution -- resumes from the last model call on retry."""
    AgentOperator(
        task_id="durable_analyst",
        prompt="What are the top 5 customers by order count?",
        llm_conn_id="pydanticai_default",
        system_prompt=(
            "You are a SQL analyst. Use the available tools to explore "
            "the schema and answer the question with data."
        ),
        durable=True,
        toolsets=[
            SQLToolset(
                db_conn_id="postgres_default",
                allowed_tables=["customers", "orders"],
                max_rows=20,
            )
        ],
    )



# [END howto_operator_agent_durable]

example_agent_durable_operator()


# ---------------------------------------------------------------------------
# 2. Durable @task.agent decorator
# ---------------------------------------------------------------------------


# [START howto_decorator_agent_durable]
@dag(default_args={"retries": 3, "retry_delay": timedelta(seconds=30)})

[docs]
def example_agent_durable_decorator():
    @task.agent(
        llm_conn_id="pydanticai_default",
        system_prompt="You are a data analyst. Use tools to answer questions.",
        durable=True,
        toolsets=[
            SQLToolset(
                db_conn_id="postgres_default",
                allowed_tables=["orders"],
            )
        ],
    )
    def analyze(question: str):
        return f"Answer this question about our orders data: {question}"

    analyze("What was our total revenue last month?")



# [END howto_decorator_agent_durable]

example_agent_durable_decorator()