Source code for tests.system.weaviate.example_weaviate_without_vectorizer_dag

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from __future__ import annotations

import pendulum

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

[docs]COLLECTION_NAME = "Weaviate_example_without_vectorizer_collection"
@dag( schedule=None, start_date=pendulum.datetime(2021, 1, 1, tz="UTC"), catchup=False, tags=["example", "weaviate"], )
[docs]def example_weaviate_without_vectorizer_dag(): """ Example DAG which uses WeaviateIngestOperator to insert embeddings to Weaviate without 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=None) @setup @task def get_data_without_vectors(): import json from pathlib import Path data = json.load(Path("jeopardy_data_with_vectors.json").open()) return data data_to_ingest = get_data_without_vectors() perform_ingestion = WeaviateIngestOperator( task_id="perform_ingestion", conn_id="weaviate_default", collection_name=COLLECTION_NAME, input_data=data_to_ingest["return_value"], ) embedd_query = OpenAIEmbeddingOperator( task_id="embedd_query", conn_id="openai_default", input_text="biology", model="text-embedding-ada-002", ) @task def query_weaviate(**kwargs): from airflow.providers.weaviate.hooks.weaviate import WeaviateHook ti = kwargs["ti"] query_vector = ti.xcom_pull(task_ids="embedd_query", key="return_value") weaviate_hook = WeaviateHook() properties = ["question", "answer", "category"] response = weaviate_hook.query_with_vector( query_vector, "Weaviate_example_without_vectorizer_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 >> embedd_query >> query_weaviate() >> delete_weaviate_collection() )
example_weaviate_without_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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