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Fixing tests

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Cyber MacGeddon 2026-03-09 10:36:52 +00:00
parent 9782421b1f
commit d8a4a8c57f
3 changed files with 59 additions and 54 deletions
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22
tests/unit/test_query/test_doc_embeddings_pinecone_query.py
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@ -103,7 +103,7 @@ class TestPineconeDocEmbeddingsQueryProcessor:
async def test_query_document_embeddings_single_vector(self, processor):
"""Test querying document embeddings with a single vector"""
message = MagicMock()
message.vectors = [[0.1, 0.2, 0.3]]
message.vector = [0.1, 0.2, 0.3]
message.limit = 3
message.user = 'test_user'
message.collection = 'test_collection'
@ -179,7 +179,7 @@ class TestPineconeDocEmbeddingsQueryProcessor:
async def test_query_document_embeddings_limit_handling(self, processor):
"""Test that query respects the limit parameter"""
message = MagicMock()
message.vectors = [[0.1, 0.2, 0.3]]
message.vector = [0.1, 0.2, 0.3]
message.limit = 2
message.user = 'test_user'
message.collection = 'test_collection'
@ -208,7 +208,7 @@ class TestPineconeDocEmbeddingsQueryProcessor:
async def test_query_document_embeddings_zero_limit(self, processor):
"""Test querying with zero limit returns empty results"""
message = MagicMock()
message.vectors = [[0.1, 0.2, 0.3]]
message.vector = [0.1, 0.2, 0.3]
message.limit = 0
message.user = 'test_user'
message.collection = 'test_collection'
@ -226,7 +226,7 @@ class TestPineconeDocEmbeddingsQueryProcessor:
async def test_query_document_embeddings_negative_limit(self, processor):
"""Test querying with negative limit returns empty results"""
message = MagicMock()
message.vectors = [[0.1, 0.2, 0.3]]
message.vector = [0.1, 0.2, 0.3]
message.limit = -1
message.user = 'test_user'
message.collection = 'test_collection'
@ -285,7 +285,7 @@ class TestPineconeDocEmbeddingsQueryProcessor:
async def test_query_document_embeddings_empty_vectors_list(self, processor):
"""Test querying with empty vectors list"""
message = MagicMock()
message.vectors = []
message.vector = []
message.limit = 5
message.user = 'test_user'
message.collection = 'test_collection'
@ -304,7 +304,7 @@ class TestPineconeDocEmbeddingsQueryProcessor:
async def test_query_document_embeddings_no_results(self, processor):
"""Test querying when index returns no results"""
message = MagicMock()
message.vectors = [[0.1, 0.2, 0.3]]
message.vector = [0.1, 0.2, 0.3]
message.limit = 5
message.user = 'test_user'
message.collection = 'test_collection'
@ -325,7 +325,7 @@ class TestPineconeDocEmbeddingsQueryProcessor:
async def test_query_document_embeddings_unicode_content(self, processor):
"""Test querying document embeddings with Unicode content results"""
message = MagicMock()
message.vectors = [[0.1, 0.2, 0.3]]
message.vector = [0.1, 0.2, 0.3]
message.limit = 2
message.user = 'test_user'
message.collection = 'test_collection'
@ -351,7 +351,7 @@ class TestPineconeDocEmbeddingsQueryProcessor:
async def test_query_document_embeddings_large_content(self, processor):
"""Test querying document embeddings with large content results"""
message = MagicMock()
message.vectors = [[0.1, 0.2, 0.3]]
message.vector = [0.1, 0.2, 0.3]
message.limit = 1
message.user = 'test_user'
message.collection = 'test_collection'
@ -377,7 +377,7 @@ class TestPineconeDocEmbeddingsQueryProcessor:
async def test_query_document_embeddings_mixed_content_types(self, processor):
"""Test querying document embeddings with mixed content types"""
message = MagicMock()
message.vectors = [[0.1, 0.2, 0.3]]
message.vector = [0.1, 0.2, 0.3]
message.limit = 5
message.user = 'test_user'
message.collection = 'test_collection'
@ -409,7 +409,7 @@ class TestPineconeDocEmbeddingsQueryProcessor:
async def test_query_document_embeddings_exception_handling(self, processor):
"""Test that exceptions are properly raised"""
message = MagicMock()
message.vectors = [[0.1, 0.2, 0.3]]
message.vector = [0.1, 0.2, 0.3]
message.limit = 5
message.user = 'test_user'
message.collection = 'test_collection'
@ -425,7 +425,7 @@ class TestPineconeDocEmbeddingsQueryProcessor:
async def test_query_document_embeddings_index_access_failure(self, processor):
"""Test handling of index access failure"""
message = MagicMock()
message.vectors = [[0.1, 0.2, 0.3]]
message.vector = [0.1, 0.2, 0.3]
message.limit = 5
message.user = 'test_user'
message.collection = 'test_collection'

16
tests/unit/test_query/test_doc_embeddings_qdrant_query.py
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@ -94,7 +94,7 @@ class TestQdrantDocEmbeddingsQuery(IsolatedAsyncioTestCase):
# Create mock message
mock_message = MagicMock()
mock_message.vectors = [[0.1, 0.2, 0.3]]
mock_message.vector = [0.1, 0.2, 0.3]
mock_message.limit = 5
mock_message.user = 'test_user'
mock_message.collection = 'test_collection'
@ -208,7 +208,7 @@ class TestQdrantDocEmbeddingsQuery(IsolatedAsyncioTestCase):
# Create mock message with limit
mock_message = MagicMock()
mock_message.vectors = [[0.1, 0.2, 0.3]]
mock_message.vector = [0.1, 0.2, 0.3]
mock_message.limit = 3 # Should only return 3 results
mock_message.user = 'limit_user'
mock_message.collection = 'limit_collection'
@ -248,7 +248,7 @@ class TestQdrantDocEmbeddingsQuery(IsolatedAsyncioTestCase):
# Create mock message
mock_message = MagicMock()
mock_message.vectors = [[0.1, 0.2]]
mock_message.vector = [0.1, 0.2]
mock_message.limit = 5
mock_message.user = 'empty_user'
mock_message.collection = 'empty_collection'
@ -343,7 +343,7 @@ class TestQdrantDocEmbeddingsQuery(IsolatedAsyncioTestCase):
# Create mock message
mock_message = MagicMock()
mock_message.vectors = [[0.1, 0.2]]
mock_message.vector = [0.1, 0.2]
mock_message.limit = 5
mock_message.user = 'utf8_user'
mock_message.collection = 'utf8_collection'
@ -379,7 +379,7 @@ class TestQdrantDocEmbeddingsQuery(IsolatedAsyncioTestCase):
# Create mock message
mock_message = MagicMock()
mock_message.vectors = [[0.1, 0.2]]
mock_message.vector = [0.1, 0.2]
mock_message.limit = 5
mock_message.user = 'error_user'
mock_message.collection = 'error_collection'
@ -413,7 +413,7 @@ class TestQdrantDocEmbeddingsQuery(IsolatedAsyncioTestCase):
# Create mock message with zero limit
mock_message = MagicMock()
mock_message.vectors = [[0.1, 0.2]]
mock_message.vector = [0.1, 0.2]
mock_message.limit = 0
mock_message.user = 'zero_user'
mock_message.collection = 'zero_collection'
@ -459,7 +459,7 @@ class TestQdrantDocEmbeddingsQuery(IsolatedAsyncioTestCase):
# Create mock message with large limit
mock_message = MagicMock()
mock_message.vectors = [[0.1, 0.2]]
mock_message.vector = [0.1, 0.2]
mock_message.limit = 1000 # Large limit
mock_message.user = 'large_user'
mock_message.collection = 'large_collection'
@ -508,7 +508,7 @@ class TestQdrantDocEmbeddingsQuery(IsolatedAsyncioTestCase):
# Create mock message
mock_message = MagicMock()
mock_message.vectors = [[0.1, 0.2]]
mock_message.vector = [0.1, 0.2]
mock_message.limit = 5
mock_message.user = 'payload_user'
mock_message.collection = 'payload_collection'

75
tests/unit/test_storage/test_doc_embeddings_qdrant_storage.py
View file

@ -89,7 +89,7 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
mock_chunk = MagicMock()
mock_chunk.chunk_id = 'doc/c1' # chunk_id instead of chunk bytes
mock_chunk.vectors = [[0.1, 0.2, 0.3]] # Single vector with 3 dimensions
mock_chunk.vector = [0.1, 0.2, 0.3] # Single vector with 3 dimensions
mock_message.chunks = [mock_chunk]
@ -143,11 +143,11 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
mock_chunk1 = MagicMock()
mock_chunk1.chunk_id = 'doc/c1'
mock_chunk1.vectors = [[0.1, 0.2]]
mock_chunk1.vector = [0.1, 0.2]
mock_chunk2 = MagicMock()
mock_chunk2.chunk_id = 'doc/c2'
mock_chunk2.vectors = [[0.3, 0.4]]
mock_chunk2.vector = [0.3, 0.4]
mock_message.chunks = [mock_chunk1, mock_chunk2]
@ -175,8 +175,8 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
@patch('trustgraph.storage.doc_embeddings.qdrant.write.QdrantClient')
@patch('trustgraph.storage.doc_embeddings.qdrant.write.uuid')
async def test_store_document_embeddings_multiple_vectors_per_chunk(self, mock_uuid, mock_qdrant_client):
"""Test storing document embeddings with multiple vectors per chunk"""
async def test_store_document_embeddings_multiple_chunks(self, mock_uuid, mock_qdrant_client):
"""Test storing document embeddings with multiple chunks"""
# Arrange
mock_qdrant_instance = MagicMock()
mock_qdrant_instance.collection_exists.return_value = True
@ -196,41 +196,45 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
# Add collection to known_collections (simulates config push)
processor.known_collections[('vector_user', 'vector_collection')] = {}
# Create mock message with chunk having multiple vectors
# Create mock message with multiple chunks, each having a single vector
mock_message = MagicMock()
mock_message.metadata.user = 'vector_user'
mock_message.metadata.collection = 'vector_collection'
mock_chunk = MagicMock()
mock_chunk.chunk_id = 'doc/multi-vector'
mock_chunk.vectors = [
[0.1, 0.2, 0.3],
[0.4, 0.5, 0.6],
[0.7, 0.8, 0.9]
]
mock_chunk1 = MagicMock()
mock_chunk1.chunk_id = 'doc/c1'
mock_chunk1.vector = [0.1, 0.2, 0.3]
mock_message.chunks = [mock_chunk]
mock_chunk2 = MagicMock()
mock_chunk2.chunk_id = 'doc/c2'
mock_chunk2.vector = [0.4, 0.5, 0.6]
mock_chunk3 = MagicMock()
mock_chunk3.chunk_id = 'doc/c3'
mock_chunk3.vector = [0.7, 0.8, 0.9]
mock_message.chunks = [mock_chunk1, mock_chunk2, mock_chunk3]
# Act
await processor.store_document_embeddings(mock_message)
# Assert
# Should be called 3 times (once per vector)
# Should be called 3 times (once per chunk)
assert mock_qdrant_instance.upsert.call_count == 3
# Verify all vectors were processed
upsert_calls = mock_qdrant_instance.upsert.call_args_list
expected_vectors = [
[0.1, 0.2, 0.3],
[0.4, 0.5, 0.6],
[0.7, 0.8, 0.9]
expected_data = [
([0.1, 0.2, 0.3], 'doc/c1'),
([0.4, 0.5, 0.6], 'doc/c2'),
([0.7, 0.8, 0.9], 'doc/c3')
]
for i, call in enumerate(upsert_calls):
point = call[1]['points'][0]
assert point.vector == expected_vectors[i]
assert point.payload['chunk_id'] == 'doc/multi-vector'
assert point.vector == expected_data[i][0]
assert point.payload['chunk_id'] == expected_data[i][1]
@patch('trustgraph.storage.doc_embeddings.qdrant.write.QdrantClient')
async def test_store_document_embeddings_empty_chunk_id(self, mock_qdrant_client):
@ -256,7 +260,7 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
mock_chunk_empty = MagicMock()
mock_chunk_empty.chunk_id = "" # Empty chunk_id
mock_chunk_empty.vectors = [[0.1, 0.2]]
mock_chunk_empty.vector = [0.1, 0.2]
mock_message.chunks = [mock_chunk_empty]
@ -299,7 +303,7 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
mock_chunk = MagicMock()
mock_chunk.chunk_id = 'doc/test-chunk'
mock_chunk.vectors = [[0.1, 0.2, 0.3, 0.4, 0.5]] # 5 dimensions
mock_chunk.vector = [0.1, 0.2, 0.3, 0.4, 0.5] # 5 dimensions
mock_message.chunks = [mock_chunk]
@ -351,7 +355,7 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
mock_chunk = MagicMock()
mock_chunk.chunk_id = 'doc/test-chunk'
mock_chunk.vectors = [[0.1, 0.2]]
mock_chunk.vector = [0.1, 0.2]
mock_message.chunks = [mock_chunk]
@ -389,7 +393,7 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
mock_chunk1 = MagicMock()
mock_chunk1.chunk_id = 'doc/c1'
mock_chunk1.vectors = [[0.1, 0.2, 0.3]]
mock_chunk1.vector = [0.1, 0.2, 0.3]
mock_message1.chunks = [mock_chunk1]
@ -407,7 +411,7 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
mock_chunk2 = MagicMock()
mock_chunk2.chunk_id = 'doc/c2'
mock_chunk2.vectors = [[0.4, 0.5, 0.6]] # Same dimension (3)
mock_chunk2.vector = [0.4, 0.5, 0.6] # Same dimension (3)
mock_message2.chunks = [mock_chunk2]
@ -446,19 +450,20 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
# Add collection to known_collections (simulates config push)
processor.known_collections[('dim_user', 'dim_collection')] = {}
# Create mock message with different dimension vectors
# Create mock message with chunks of different dimensions
mock_message = MagicMock()
mock_message.metadata.user = 'dim_user'
mock_message.metadata.collection = 'dim_collection'
mock_chunk = MagicMock()
mock_chunk.chunk_id = 'doc/dim-test'
mock_chunk.vectors = [
[0.1, 0.2], # 2 dimensions
[0.3, 0.4, 0.5] # 3 dimensions
]
mock_chunk1 = MagicMock()
mock_chunk1.chunk_id = 'doc/c1'
mock_chunk1.vector = [0.1, 0.2] # 2 dimensions
mock_message.chunks = [mock_chunk]
mock_chunk2 = MagicMock()
mock_chunk2.chunk_id = 'doc/c2'
mock_chunk2.vector = [0.3, 0.4, 0.5] # 3 dimensions
mock_message.chunks = [mock_chunk1, mock_chunk2]
# Act
await processor.store_document_embeddings(mock_message)
@ -526,7 +531,7 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
mock_chunk = MagicMock()
mock_chunk.chunk_id = 'https://trustgraph.ai/doc/my-document/p1/c3'
mock_chunk.vectors = [[0.1, 0.2]]
mock_chunk.vector = [0.1, 0.2]
mock_message.chunks = [mock_chunk]