Source code for tests.system.weaviate.example_weaviate_vectorizer_dag

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from __future__ import annotations

import pendulum
from weaviate.collections.classes.config import Configure

from airflow.decorators import dag, setup, task, teardown
from airflow.providers.weaviate.operators.weaviate import WeaviateIngestOperator

[docs]COLLECTION_NAME = "Weaviate_with_vectorizer_example_collection"
@dag( schedule=None, start_date=pendulum.datetime(2021, 1, 1, tz="UTC"), catchup=False, tags=["example", "weaviate"], )
[docs]def example_weaviate_vectorizer_dag(): """ Example DAG which uses WeaviateIngestOperator to insert embeddings to Weaviate with vectorizer and then query to verify the response . """ @setup @task def create_weaviate_collection(): """ 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( COLLECTION_NAME, vectorizer_config=Configure.Vectorizer.text2vec_openai(), ) @setup @task def get_data_to_ingest(): import json from pathlib import Path data = json.load(Path("jeopardy_data_without_vectors.json").open()) return data data_to_ingest = get_data_to_ingest() perform_ingestion = WeaviateIngestOperator( task_id="perform_ingestion", conn_id="weaviate_default", collection_name=COLLECTION_NAME, input_data=data_to_ingest["return_value"], ) @task def query_weaviate(): from airflow.providers.weaviate.hooks.weaviate import WeaviateHook weaviate_hook = WeaviateHook() properties = ["question", "answer", "category"] response = weaviate_hook.query_with_text( "biology", "Weaviate_with_vectorizer_example_collection", properties=properties ) assert "In 1953 Watson & Crick built a model" in response.objects[0].properties["question"] @teardown @task def delete_weaviate_collection(): """ 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]) create_weaviate_collection() >> perform_ingestion >> query_weaviate() >> delete_weaviate_collection()
example_weaviate_vectorizer_dag() 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)
[docs]test_run = get_test_run(dag)

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