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Merged
davidsbatista merged 4 commits into from
Mar 20, 2026
Merged

test: PGVectorDocumentStoree use Mixin tests #3003

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a740227
overwriting some mixin tests due to different internal implementation
davidsbatista Mar 17, 2026
3866471
chore: update haystack-ai dependency to >=2.26.1
davidsbatista Mar 19, 2026
e669c22
Merge branch 'main' into test/pgvector-use-mixin-tests
davidsbatista Mar 20, 2026
fef7c7c
removing duplicated tests
davidsbatista Mar 20, 2026
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2 changes: 1 addition & 1 deletion integrations/pgvector/pyproject.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -23,7 +23,7 @@ classifiers = [
"Programming Language :: Python :: Implementation :: PyPy",
]
dependencies = [
"haystack-ai>=2.24.0",
"haystack-ai>=2.26.1",
"pgvector>=0.3.0",
"psycopg[binary]"
]
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167 changes: 24 additions & 143 deletions integrations/pgvector/tests/test_document_store.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,11 +10,16 @@
from haystack.document_stores.errors import DocumentStoreError, DuplicateDocumentError
from haystack.document_stores.types import DuplicatePolicy
from haystack.testing.document_store import (
CountDocumentsByFilterTest,
CountDocumentsTest,
CountUniqueMetadataByFilterTest,
DeleteAllTest,
DeleteByFilterTest,
DeleteDocumentsTest,
FilterableDocsFixtureMixin,
GetMetadataFieldMinMaxTest,
GetMetadataFieldsInfoTest,
GetMetadataFieldUniqueValuesTest,
UpdateByFilterTest,
WriteDocumentsTest,
)
Expand All @@ -32,7 +37,26 @@ class TestDocumentStore(
FilterableDocsFixtureMixin,
UpdateByFilterTest,
WriteDocumentsTest,
CountDocumentsByFilterTest,
CountUniqueMetadataByFilterTest,
GetMetadataFieldsInfoTest,
GetMetadataFieldMinMaxTest,
GetMetadataFieldUniqueValuesTest,
):
def test_get_metadata_fields_info_empty_collection(self, document_store: PgvectorDocumentStore):
"""PgvectorDocumentStore always includes 'content' in fields info, even for empty stores."""
assert document_store.count_documents() == 0

fields_info = document_store.get_metadata_fields_info()
assert fields_info == {"content": {"type": "text"}}

def test_get_metadata_field_min_max_empty_collection(self, document_store: PgvectorDocumentStore):
"""PgvectorDocumentStore raises ValueError when the field doesn't exist in the store."""
assert document_store.count_documents() == 0

with pytest.raises(ValueError, match="not found in document store"):
document_store.get_metadata_field_min_max("priority")

def test_write_documents(self, document_store: PgvectorDocumentStore):
docs = [Document(id="1")]
assert document_store.write_documents(docs) == 1
Expand Down Expand Up @@ -280,151 +304,8 @@ def test_update_by_filter_empty_meta_raises_error(document_store: PgvectorDocume
document_store.update_by_filter(filters={"field": "meta.category", "operator": "==", "value": "A"}, meta={})


@pytest.mark.integration
def test_count_documents_by_filter(document_store: PgvectorDocumentStore):
docs = [
Document(content="Doc 1", meta={"category": "A", "status": "active"}),
Document(content="Doc 2", meta={"category": "B", "status": "active"}),
Document(content="Doc 3", meta={"category": "A", "status": "inactive"}),
Document(content="Doc 4", meta={"category": "A", "status": "active"}),
]
document_store.write_documents(docs)

count_a = document_store.count_documents_by_filter(
filters={"field": "meta.category", "operator": "==", "value": "A"}
)
assert count_a == 3

count_a_active = document_store.count_documents_by_filter(
filters={
"operator": "AND",
"conditions": [
{"field": "meta.category", "operator": "==", "value": "A"},
{"field": "meta.status", "operator": "==", "value": "active"},
],
}
)
assert count_a_active == 2


@pytest.mark.integration
def test_count_unique_metadata_by_filter(document_store: PgvectorDocumentStore):
docs = [
Document(content="Doc 1", meta={"category": "A", "status": "active", "priority": 1}),
Document(content="Doc 2", meta={"category": "B", "status": "active", "priority": 2}),
Document(content="Doc 3", meta={"category": "A", "status": "inactive", "priority": 1}),
Document(content="Doc 4", meta={"category": "A", "status": "active", "priority": 3}),
Document(content="Doc 5", meta={"category": "C", "status": "active", "priority": 2}),
]
document_store.write_documents(docs)

distinct_counts = document_store.count_unique_metadata_by_filter(
filters={}, metadata_fields=["category", "status", "priority"]
)
assert distinct_counts["category"] == 3 # A, B, C
assert distinct_counts["status"] == 2 # active, inactive
assert distinct_counts["priority"] == 3 # 1, 2, 3

# distinct values for documents with category="A"
distinct_counts_a = document_store.count_unique_metadata_by_filter(
filters={"field": "meta.category", "operator": "==", "value": "A"},
metadata_fields=["category", "status", "priority"],
)
assert distinct_counts_a["category"] == 1 # Only A
assert distinct_counts_a["status"] == 2 # active, inactive
assert distinct_counts_a["priority"] == 2 # 1, 3

# distinct values with complex filter (category="A" AND status="active")
distinct_counts_a_active = document_store.count_unique_metadata_by_filter(
filters={
"operator": "AND",
"conditions": [
{"field": "meta.category", "operator": "==", "value": "A"},
{"field": "meta.status", "operator": "==", "value": "active"},
],
},
metadata_fields=["category", "status", "priority"],
)
assert distinct_counts_a_active["category"] == 1 # Only A
assert distinct_counts_a_active["status"] == 1 # Only active
assert distinct_counts_a_active["priority"] == 2 # 1, 3

# with only a subset of fields
distinct_counts_subset = document_store.count_unique_metadata_by_filter(
filters={}, metadata_fields=["category", "status"]
)
assert distinct_counts_subset["category"] == 3
assert distinct_counts_subset["status"] == 2
assert "priority" not in distinct_counts_subset

# with field name normalization (with "meta." prefix)
distinct_counts_normalized = document_store.count_unique_metadata_by_filter(
filters={}, metadata_fields=["meta.category", "status", "meta.priority"]
)
assert distinct_counts_normalized["category"] == 3
assert distinct_counts_normalized["status"] == 2
assert distinct_counts_normalized["priority"] == 3


@pytest.mark.integration
def test_get_metadata_fields_info(document_store: PgvectorDocumentStore):
docs = [
Document(content="Doc 1", meta={"category": "A", "status": "active", "priority": 1}),
Document(content="Doc 2", meta={"category": "B", "status": "inactive"}),
]
document_store.write_documents(docs)

fields_info = document_store.get_metadata_fields_info()

# Verify that fields_info contains expected fields
assert "content" in fields_info
assert "category" in fields_info
assert "status" in fields_info
assert "priority" in fields_info

assert fields_info["content"]["type"] == "text"
assert fields_info["category"]["type"] == "text"
assert fields_info["status"]["type"] == "text"
assert fields_info["priority"]["type"] == "integer"


@pytest.mark.integration
def test_get_metadata_field_min_max(document_store: PgvectorDocumentStore):
# Test with integer values
docs = [
Document(content="Doc 1", meta={"priority": 1, "age": 10}),
Document(content="Doc 2", meta={"priority": 5, "age": 20}),
Document(content="Doc 3", meta={"priority": 3, "age": 15}),
Document(content="Doc 4", meta={"priority": 10, "age": 5}),
Document(content="Doc 6", meta={"rating": 10.5}),
Document(content="Doc 7", meta={"rating": 20.3}),
Document(content="Doc 8", meta={"rating": 15.7}),
Document(content="Doc 9", meta={"rating": 5.2}),
]
document_store.write_documents(docs)

# Test with "meta." prefix for integer field
min_max_priority = document_store.get_metadata_field_min_max("meta.priority")
assert min_max_priority["min"] == 1
assert min_max_priority["max"] == 10

# Test with "meta." prefix for another integer field
min_max_age = document_store.get_metadata_field_min_max("meta.age")
assert min_max_age["min"] == 5
assert min_max_age["max"] == 20

# Test with single value
single_doc = [Document(content="Doc 5", meta={"single_value": 42})]
document_store.write_documents(single_doc)
min_max_single = document_store.get_metadata_field_min_max("meta.single_value")
assert min_max_single["min"] == 42
assert min_max_single["max"] == 42

# Test with float values
min_max_rating = document_store.get_metadata_field_min_max("meta.rating")
assert min_max_rating["min"] == pytest.approx(5.2)
assert min_max_rating["max"] == pytest.approx(20.3)

# Test with text/string values - lexicographic comparison
text_docs = [
Document(content="Doc 1", meta={"category": "Zebra", "status": "active"}),
Expand Down
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