Fixing tests

This commit is contained in:
Cyber MacGeddon 2026-03-09 10:27:14 +00:00
parent 8d25f4d4a8
commit b7894c7088
2 changed files with 24 additions and 20 deletions

View file

@ -126,27 +126,27 @@ class TestPineconeGraphEmbeddingsStorageProcessor:
message.metadata = MagicMock()
message.metadata.user = 'test_user'
message.metadata.collection = 'test_collection'
entity = EntityEmbeddings(
entity=Value(value="http://example.org/entity1", is_uri=True),
vectors=[[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]]
vector=[0.1, 0.2, 0.3]
)
message.entities = [entity]
# Mock index operations
mock_index = MagicMock()
processor.pinecone.Index.return_value = mock_index
processor.pinecone.has_index.return_value = True
with patch('uuid.uuid4', side_effect=['id1', 'id2']):
with patch('uuid.uuid4', side_effect=['id1']):
await processor.store_graph_embeddings(message)
# Verify index name and operations (with dimension suffix)
expected_index_name = "t-test_user-test_collection-3" # 3 dimensions
processor.pinecone.Index.assert_called_with(expected_index_name)
# Verify upsert was called for each vector
assert mock_index.upsert.call_count == 2
# Verify upsert was called for the single vector
assert mock_index.upsert.call_count == 1
# Check first vector upsert
first_call = mock_index.upsert.call_args_list[0]
@ -262,23 +262,27 @@ class TestPineconeGraphEmbeddingsStorageProcessor:
@pytest.mark.asyncio
async def test_store_graph_embeddings_different_vector_dimensions(self, processor):
"""Test storing graph embeddings with different vector dimensions to same index"""
"""Test storing graph embeddings with different vector dimensions"""
message = MagicMock()
message.metadata = MagicMock()
message.metadata.user = 'test_user'
message.metadata.collection = 'test_collection'
entity = EntityEmbeddings(
entity=Value(value="test_entity", is_uri=False),
vectors=[
[0.1, 0.2], # 2D vector
[0.3, 0.4, 0.5, 0.6], # 4D vector
[0.7, 0.8, 0.9] # 3D vector
]
# Each entity has a single vector of different dimensions
entity1 = EntityEmbeddings(
entity=Value(value="entity1", is_uri=False),
vector=[0.1, 0.2] # 2D vector
)
message.entities = [entity]
entity2 = EntityEmbeddings(
entity=Value(value="entity2", is_uri=False),
vector=[0.3, 0.4, 0.5, 0.6] # 4D vector
)
entity3 = EntityEmbeddings(
entity=Value(value="entity3", is_uri=False),
vector=[0.7, 0.8, 0.9] # 3D vector
)
message.entities = [entity1, entity2, entity3]
# All vectors now use the same index (no dimension in name)
mock_index = MagicMock()
processor.pinecone.Index.return_value = mock_index
processor.pinecone.has_index.return_value = True