upstream-archive/qdrant-client
1
0
Fork 0
mirror of https://github.com/qdrant/qdrant-client.git synced 2026-08-02 16:10:59 -05:00
Code Issues Packages Projects Releases Wiki Activity

tests: Add more test cases

Browse Source
This commit is contained in:
tellet-q
2024-06-28 12:50:19 +02:00
parent 2a4a6bdb9a
commit bc2d47276b
1 changed files with 146 additions and 3 deletions
Download Patch File Download Diff File Expand all files Collapse all files

149
tests/congruence_tests/test_query.py
View File

@@ -309,7 +309,9 @@ class TestSimpleSearcher:
limit=10,
)
def dense_queries_rescore_filtered(self, client: QdrantBase, query_filter: models.Filter) -> Union[List[models.ScoredPoint], models.QueryResponse]:
def dense_queries_prefetch_filtered(
self, client: QdrantBase, query_filter: models.Filter
) -> Union[List[models.ScoredPoint], models.QueryResponse]:
return client.query_points(
collection_name=COLLECTION_NAME,
prefetch=[
@@ -330,6 +332,54 @@ class TestSimpleSearcher:
limit=10,
)
def dense_queries_prefetch_score_threshold(
self, client: QdrantBase
) -> Union[List[models.ScoredPoint], models.QueryResponse]:
return client.query_points(
collection_name=COLLECTION_NAME,
prefetch=[
models.Prefetch(
query=self.dense_vector_query_text, using="text", score_threshold=0.9
),
models.Prefetch(
query=self.dense_vector_query_code,
using="code",
score_threshold=0.1,
),
],
query=self.dense_vector_query_image,
using="image",
with_payload=True,
limit=10,
)
def dense_queries_prefetch_parametrized(
self, client: QdrantBase, search_params: models.SearchParams
) -> Union[List[models.ScoredPoint], models.QueryResponse]:
return client.query_points(
collection_name=COLLECTION_NAME,
prefetch=[
models.Prefetch(
query=self.dense_vector_query_text, using="text", params=search_params
),
],
query=self.dense_vector_query_image,
using="image",
with_payload=True,
limit=10,
)
def dense_queries_parametrized(
self, client: QdrantBase, search_params: models.SearchParams
) -> Union[List[models.ScoredPoint], models.QueryResponse]:
return client.query_points(
collection_name=COLLECTION_NAME,
query=self.dense_vector_query_image,
using="image",
limit=10,
search_params=search_params,
)
def dense_queries_orderby(self, client: QdrantBase) -> List[models.ScoredPoint]:
return client.query_points(
collection_name=COLLECTION_NAME,
@@ -572,7 +622,7 @@ def test_no_query_no_prefetch():
compare_client_results(local_client, remote_client, searcher.no_query_no_prefetch)
def test_filtered_prefetch():
def test_dense_query_filtered_prefetch():
fixture_points = generate_fixtures()
searcher = TestSimpleSearcher()
@@ -587,13 +637,106 @@ def test_filtered_prefetch():
query_filter = one_random_filter_please()
try:
compare_client_results(
local_client, remote_client, searcher.dense_queries_rescore_filtered, query_filter=query_filter
local_client,
remote_client,
searcher.dense_queries_prefetch_filtered,
query_filter=query_filter,
)
except AssertionError as e:
print(f"\nFailed with filter {query_filter}")
raise e
def test_dense_query_prefetch_score_threshold():
fixture_points = generate_fixtures()
searcher = TestSimpleSearcher()
local_client = init_local()
init_client(local_client, fixture_points)
remote_client = init_remote()
init_client(remote_client, fixture_points)
compare_client_results(
local_client, remote_client, searcher.dense_queries_prefetch_score_threshold
)
def test_dense_query_prefetch_parametrized():
fixture_points = generate_fixtures()
searcher = TestSimpleSearcher()
local_client = init_local()
init_client(local_client, fixture_points)
remote_client = init_remote()
init_client(remote_client, fixture_points)
compare_client_results(
local_client,
remote_client,
searcher.dense_queries_prefetch_parametrized,
search_params={"exact": True},
)
compare_client_results(
local_client,
remote_client,
searcher.dense_queries_prefetch_parametrized,
search_params={"hnsw_ef": 128},
)
compare_client_results(
local_client,
remote_client,
searcher.dense_queries_prefetch_parametrized,
search_params={"indexed_only": True},
)
compare_client_results(
local_client,
remote_client,
searcher.dense_queries_prefetch_parametrized,
search_params={"quantization": {"ignore": True, "rescore": True, "oversampling": 2.0}},
)
def test_dense_query_parametrized():
fixture_points = generate_fixtures()
searcher = TestSimpleSearcher()
local_client = init_local()
init_client(local_client, fixture_points)
remote_client = init_remote()
init_client(remote_client, fixture_points)
compare_client_results(
local_client,
remote_client,
searcher.dense_queries_parametrized,
search_params={"exact": True},
)
compare_client_results(
local_client,
remote_client,
searcher.dense_queries_parametrized,
search_params={"hnsw_ef": 128},
)
compare_client_results(
local_client,
remote_client,
searcher.dense_queries_parametrized,
search_params={"indexed_only": True},
)
compare_client_results(
local_client,
remote_client,
searcher.dense_queries_parametrized,
search_params={"quantization": {"ignore": True, "rescore": True, "oversampling": 2.0}},
)
def test_sparse_query():
fixture_points = generate_sparse_fixtures()