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Collection name under test is equal to the test module name, without `.py` suffix. * Helps by debugging/tracing failed tests and find relevant logs lines in qdrant log files * Opens up a possibility to run tests in parallel, given that there are no data sharing between test modules Change details: * defined module scoped `collection_name` fixture in `conftest.py` * removed `collection_name` module variable * each test signature modified to declare the dependency to `collection_name` fixture * `@pytest.mark.parametrize` migrated to `@pytest-cases.parametrize` in cases when `collection_name` was used as the value
213 lines
6.0 KiB
Python
213 lines
6.0 KiB
Python
import pytest
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from .helpers.collection_setup import drop_collection
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from .helpers.helpers import request_with_validation
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@pytest.fixture(autouse=True)
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def setup(on_disk_vectors, collection_name):
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multivector_collection_setup(collection_name=collection_name, on_disk_vectors=on_disk_vectors)
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yield
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drop_collection(collection_name=collection_name)
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def multivector_collection_setup(
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collection_name='test_collection',
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on_disk_vectors=False):
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drop_collection(collection_name=collection_name)
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response = request_with_validation(
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api='/collections/{collection_name}',
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method="PUT",
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path_params={'collection_name': collection_name},
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body={
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"vectors": {
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"size": 2,
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"distance": "Dot",
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"on_disk": on_disk_vectors,
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"multivector_config": {
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"comparator": "max_sim"
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}
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},
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}
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)
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assert response.ok
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# batch upsert
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response = request_with_validation(
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api='/collections/{collection_name}/points',
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method="PUT",
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path_params={'collection_name': collection_name},
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query_params={'wait': 'true'},
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body={
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"points": [
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{
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"id": 1,
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"vector": [
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[-1, 1],
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[-2, 2],
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[-3, 3]
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]
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},
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{
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"id": 2,
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"vector": [
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[-1.5, 1.5],
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[-2.5, 2.5],
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[-3.5, 3.5]
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]
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},
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{
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"id": 3,
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"vector": [
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[-1.7, 1.7],
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[-2.7, 2.7],
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[-3.7, 3.7]
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]
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},
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]
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}
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)
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assert response.ok
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response = request_with_validation(
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api='/collections/{collection_name}',
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method="GET",
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path_params={'collection_name': collection_name},
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)
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assert response.ok
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def test_multi_default_is_avg_vector(collection_name):
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params = {
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"positive": [[1, 2]],
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"negative": [[3, 4]],
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"exact": True,
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"limit": 10,
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}
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default_response = request_with_validation(
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api="/collections/{collection_name}/points/recommend",
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method="POST",
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path_params={"collection_name": collection_name},
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body={
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**params,
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},
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)
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assert default_response.ok
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# we should only get 3 because we don't have more
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assert len(default_response.json()["result"]) == 3
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avg_response = request_with_validation(
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api="/collections/{collection_name}/points/recommend",
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method="POST",
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path_params={"collection_name": collection_name},
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body={
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**params,
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"strategy": "average_vector",
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},
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)
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assert avg_response.ok
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assert len(avg_response.json()["result"]) == 3
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assert default_response.json()["result"] == avg_response.json()["result"]
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def test_multi_single_vs_batch(collection_name):
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# Bunch of valid examples
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params_list = [
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{
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"positive": [1],
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"negative": [3],
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"limit": 1,
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},
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{
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# no negative because it's optional with this strategy
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"negative": [1, 2],
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"exact": True,
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"strategy": "best_score",
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"limit": 1,
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},
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{
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"positive": [1],
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"negative": [],
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"exact": True,
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"strategy": "average_vector",
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"limit": 1,
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},
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]
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batch_response = request_with_validation(
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api="/collections/{collection_name}/points/recommend/batch",
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method="POST",
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path_params={"collection_name": collection_name},
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body={"searches": params_list},
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)
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assert batch_response.ok
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assert len(batch_response.json()["result"]) == len(params_list)
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# Compare against sequential single searches
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for i, params in enumerate(params_list):
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single_response = request_with_validation(
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api="/collections/{collection_name}/points/recommend",
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method="POST",
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path_params={"collection_name": collection_name},
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body=params,
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)
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assert single_response.ok
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assert single_response.json()["result"] == batch_response.json()["result"][i]
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def test_multi_without_positives(collection_name):
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def req_with_positives(positive, strategy=None):
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if strategy is None:
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strat_dict = {}
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else:
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strat_dict = {"strategy": strategy}
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return request_with_validation(
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api="/collections/{collection_name}/points/recommend",
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method="POST",
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path_params={"collection_name": collection_name},
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body={
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"positive": positive,
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**strat_dict,
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"limit": 2,
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},
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)
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# Assert this is valid
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response = req_with_positives([[1, 2]])
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assert response.ok
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# But all these are not
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response = req_with_positives([[]])
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assert response.status_code == 400
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response = req_with_positives([[]], "average_vector")
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assert response.status_code == 400
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# Also no negative and no positive is invalid with best_score
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response = req_with_positives([], "best_score")
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assert response.status_code == 400
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def test_multi_best_score_works_with_only_negatives(collection_name):
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response = request_with_validation(
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api="/collections/{collection_name}/points/recommend",
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method="POST",
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path_params={"collection_name": collection_name},
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body={
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"negative": [[1, 2]],
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"strategy": "best_score",
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"limit": 5,
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},
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)
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assert response.ok
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assert len(response.json()["result"]) == 3
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# All scores should be negative
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for result in response.json()["result"]:
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assert result["score"] < 0
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