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# to you under the Apache License, Version 2.0 (the
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#
#   http://www.apache.org/licenses/LICENSE-2.0
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from __future__ import annotations

import pendulum

# This example uses common.compat for Airflow 2.x/3.x compatibility.
# If you only need Airflow 3+, you can use: from airflow.sdk import dag, task, teardown
from airflow.providers.common.compat.sdk import dag, task, teardown
from airflow.providers.openai.operators.openai import OpenAIEmbeddingOperator
from airflow.providers.pgvector.operators.pgvector import PgVectorIngestOperator

TABLE_NAME = "my_table"
POSTGRES_CONN_ID = "postgres_default"


@dag(
    "example_openai_pgvector_dag",
    schedule=None,
    start_date=pendulum.datetime(2021, 1, 1, tz="UTC"),
    catchup=False,
    tags=["example", "pgvector"],
)
def example_pgvector_dag():
    """Example pgvector DAG demonstrating usage of the PgVectorIngestOperator."""

    @task()
    def create_postgres_objects():
        """
        Example task to create PostgreSQL objects including table and installing the vector extension using
        the PgVectorHook.
        """
        from airflow.providers.pgvector.hooks.pgvector import PgVectorHook

        pg_hook = PgVectorHook(postgres_conn_id=POSTGRES_CONN_ID)

        # Create a table
        columns = [
            "id SERIAL PRIMARY KEY",
            "name VARCHAR(255)",
            "value INTEGER",
            "vector_column vector(1536)",
        ]
        pg_hook.create_table(TABLE_NAME, columns)

        # Create vector extension
        extension_name = "vector"
        pg_hook.create_extension(extension_name)

    embedd_query = OpenAIEmbeddingOperator(
        task_id="embedding_using_xcom_data",
        conn_id="openai_default",
        input_text="123",
        model="text-embedding-ada-002",
    )

    pgvector_ingest = PgVectorIngestOperator(
        task_id="pgvector_ingest",
        conn_id=POSTGRES_CONN_ID,
        sql=f"INSERT INTO {TABLE_NAME} (name, value, vector_column) "
        f"VALUES ('John Doe', '123' ,'{embedd_query.output}')",
    )

    @teardown()
    @task()
    def cleanup_postgres_objects():
        """
        Cleanup Postgres objects created in the earlier task.
        """
        from airflow.providers.pgvector.hooks.pgvector import PgVectorHook

        pg_hook = PgVectorHook(postgres_conn_id=POSTGRES_CONN_ID)
        pg_hook.truncate_table(TABLE_NAME)
        pg_hook.drop_table(TABLE_NAME)

    create_postgres_objects() >> pgvector_ingest >> cleanup_postgres_objects()


example_pgvector_dag()

from tests_common.test_utils.system_tests import get_test_run  # noqa: E402

# Needed to run the example DAG with pytest (see: contributing-docs/testing/system_tests.rst)
test_run = get_test_run(dag)
