Source code for tests.system.weaviate.example_weaviate_cohere
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from __future__ import annotations
import pendulum
from airflow.decorators import dag, setup, task, teardown
from airflow.providers.cohere.operators.embedding import CohereEmbeddingOperator
from airflow.providers.weaviate.operators.weaviate import WeaviateIngestOperator
[docs]COLLECTION_NAME = "weaviate_cohere_example_collection"
@dag(
schedule=None,
start_date=pendulum.datetime(2021, 1, 1, tz="UTC"),
catchup=False,
tags=["example", "weaviate", "cohere"],
)
[docs]def example_weaviate_cohere():
"""
Example DAG which creates embeddings using CohereEmbeddingOperator and the uses WeaviateIngestOperator to insert embeddings to Weaviate .
"""
@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(name=COLLECTION_NAME, vectorizer_config=None)
@setup
@task
def get_data_to_embed():
import json
from pathlib import Path
data = json.load(Path("jeopardy_data_without_vectors.json").open())
return [[item["Question"]] for item in data]
data_to_embed = get_data_to_embed()
embed_data = CohereEmbeddingOperator.partial(
task_id="embedding_using_xcom_data",
).expand(input_text=data_to_embed["return_value"])
@task
def update_vector_data_in_json(**kwargs):
import json
from pathlib import Path
ti = kwargs["ti"]
data = json.load(Path("jeopardy_data_without_vectors.json").open())
embedded_data = ti.xcom_pull(task_ids="embedding_using_xcom_data", key="return_value")
for i, vector in enumerate(embedded_data):
data[i]["Vector"] = vector[0]
return data
update_vector_data_in_json = update_vector_data_in_json()
perform_ingestion = WeaviateIngestOperator(
task_id="perform_ingestion",
conn_id="weaviate_default",
collection_name=COLLECTION_NAME,
input_data=update_vector_data_in_json["return_value"],
)
embed_query = CohereEmbeddingOperator(
task_id="embed_query",
input_text=["biology"],
)
@teardown
@task
def delete_weaviate_collections():
"""
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()
>> embed_data
>> update_vector_data_in_json
>> perform_ingestion
>> embed_query
>> delete_weaviate_collections()
)
example_weaviate_cohere()
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)