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#
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from __future__ import annotations

from datetime import timedelta

import pendulum
from weaviate.classes.config import DataType, Property
from weaviate.collections.classes.config import Configure

try:
    from airflow.sdk import dag, task, teardown
except ImportError:
    # Airflow 2 path
    from airflow.decorators import dag, task, teardown  # type: ignore[attr-defined,no-redef]

COLLECTION_NAME = "QuestionWithOpenAIVectorizerUsingHook"

default_args = {
    "retries": 5,
    "retry_delay": timedelta(seconds=15),
    "pool": "weaviate_pool",
}


@dag(
    schedule=None,
    start_date=pendulum.datetime(2021, 1, 1, tz="UTC"),
    default_args=default_args,
    catchup=False,
    tags=["example", "weaviate"],
)
def example_weaviate_dag_using_hook():
    """Example Weaviate DAG demonstrating usage of the hook."""

    @task()
    def create_collection_with_vectorizer():
        """
        Example task to create collection with OpenAI Vectorizer responsible for vectorining data using Weaviate cluster.
        """
        from airflow.providers.weaviate.hooks.weaviate import WeaviateHook

        weaviate_hook = WeaviateHook()
        weaviate_hook.create_collection(
            COLLECTION_NAME,
            description="Information from a Jeopardy! question",
            properties=[
                Property(name="question", description="The question", data_type=DataType.TEXT),
                Property(name="answer", description="The answer", data_type=DataType.TEXT),
                Property(name="category", description="The category", data_type=DataType.TEXT),
            ],
            vectorizer_config=Configure.Vectorizer.text2vec_openai(),
        )

    @task()
    def create_collection_without_vectorizer():
        """
        Example task to create collection without any Vectorizer. You're expected to provide custom vectors for your data.
        """
        from airflow.providers.weaviate.hooks.weaviate import WeaviateHook

        weaviate_hook = WeaviateHook()
        # collection definition object. Weaviate's autoschema feature will infer properties when importing.
        weaviate_hook.create_collection(
            "QuestionWithoutVectorizerUsingHook",
            vectorizer_config=None,
        )

    @task(trigger_rule="all_done")
    def store_data_without_vectors_in_xcom():
        import json
        from pathlib import Path

        data = json.load(Path("jeopardy_data_without_vectors.json").open())
        return data

    @task(trigger_rule="all_done")
    def store_data_with_vectors_in_xcom():
        import json
        from pathlib import Path

        data = json.load(Path("jeopardy_data_with_vectors.json").open())
        return data

    @task(trigger_rule="all_done")
    def batch_data_without_vectors(data: list):
        from airflow.providers.weaviate.hooks.weaviate import WeaviateHook

        weaviate_hook = WeaviateHook()
        weaviate_hook.batch_data(COLLECTION_NAME, data)

    @task(trigger_rule="all_done")
    def batch_data_with_vectors(data: list):
        from airflow.providers.weaviate.hooks.weaviate import WeaviateHook

        weaviate_hook = WeaviateHook()
        weaviate_hook.batch_data("QuestionWithoutVectorizerUsingHook", data)

    @teardown
    @task
    def delete_weaviate_collection_vector():
        """
        Example task to delete a weaviate collection
        """
        from airflow.providers.weaviate.hooks.weaviate import WeaviateHook

        weaviate_hook = WeaviateHook()
        # collection definition object. Weaviate's autoschema feature will infer properties when importing.

        weaviate_hook.delete_collections([COLLECTION_NAME])

    @teardown
    @task
    def delete_weaviate_collection_without_vector():
        """
        Example task to delete a weaviate collection
        """
        from airflow.providers.weaviate.hooks.weaviate import WeaviateHook

        weaviate_hook = WeaviateHook()
        # collection definition object. Weaviate's autoschema feature will infer properties when importing.

        weaviate_hook.delete_collections(["QuestionWithoutVectorizerUsingHook"])

    data_with_vectors = store_data_with_vectors_in_xcom()
    (
        create_collection_without_vectorizer()
        >> batch_data_with_vectors(data_with_vectors["return_value"])
        >> delete_weaviate_collection_vector()
    )

    data_without_vectors = store_data_without_vectors_in_xcom()
    (
        create_collection_with_vectorizer()
        >> batch_data_without_vectors(data_without_vectors["return_value"])
        >> delete_weaviate_collection_without_vector()
    )


example_weaviate_dag_using_hook()

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

# Needed to run the example DAG with pytest (see: tests/system/README.md#run_via_pytest)
test_run = get_test_run(dag)
