mirror of
https://github.com/trustgraph-ai/trustgraph.git
synced 2026-04-25 08:26:21 +02:00
57eda65674
Knowledge core fixed:
- trustgraph-flow/trustgraph/tables/knowledge.py - v.vector, v.chunk_id
- trustgraph-base/trustgraph/messaging/translators/document_loading.py -
chunk.vector
- trustgraph-base/trustgraph/messaging/translators/knowledge.py -
entity.vector
- trustgraph-flow/trustgraph/gateway/dispatch/serialize.py - entity.vector,
chunk.vector
Test fixtures fixed:
- tests/unit/test_storage/conftest.py - All mock entities/chunks use vector
- tests/unit/test_query/conftest.py - All mock requests use vector
- tests/unit/test_query/test_doc_embeddings_pinecone_query.py - All mock
messages use vector
These changes align with commit f2ae0e86 which changed the schema from
vectors: list[list[float]] to vector: list[float].
148 lines
No EOL
4.3 KiB
Python
148 lines
No EOL
4.3 KiB
Python
"""
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Shared fixtures for query tests
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"""
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import pytest
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from unittest.mock import AsyncMock, MagicMock
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@pytest.fixture
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def base_query_config():
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"""Base configuration for query processors"""
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return {
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'taskgroup': AsyncMock(),
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'id': 'test-query-processor'
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}
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@pytest.fixture
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def qdrant_query_config(base_query_config):
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"""Configuration for Qdrant query processors"""
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return base_query_config | {
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'store_uri': 'http://localhost:6333',
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'api_key': 'test-api-key'
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}
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@pytest.fixture
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def mock_qdrant_client():
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"""Mock Qdrant client"""
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mock_client = MagicMock()
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mock_client.query_points.return_value = []
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return mock_client
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# Graph embeddings query fixtures
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@pytest.fixture
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def mock_graph_embeddings_request():
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"""Mock graph embeddings request message"""
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mock_message = MagicMock()
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mock_message.vector = [0.1, 0.2, 0.3]
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mock_message.limit = 5
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mock_message.user = 'test_user'
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mock_message.collection = 'test_collection'
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return mock_message
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@pytest.fixture
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def mock_graph_embeddings_multiple_vectors():
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"""Mock graph embeddings request with multiple vectors (legacy name, now single vector)"""
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mock_message = MagicMock()
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mock_message.vector = [0.1, 0.2, 0.3, 0.4]
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mock_message.limit = 3
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mock_message.user = 'multi_user'
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mock_message.collection = 'multi_collection'
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return mock_message
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@pytest.fixture
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def mock_graph_embeddings_query_response():
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"""Mock graph embeddings query response from Qdrant"""
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mock_point1 = MagicMock()
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mock_point1.payload = {'entity': 'entity1'}
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mock_point2 = MagicMock()
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mock_point2.payload = {'entity': 'entity2'}
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return [mock_point1, mock_point2]
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@pytest.fixture
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def mock_graph_embeddings_uri_response():
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"""Mock graph embeddings query response with URIs"""
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mock_point1 = MagicMock()
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mock_point1.payload = {'entity': 'http://example.com/entity1'}
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mock_point2 = MagicMock()
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mock_point2.payload = {'entity': 'https://secure.example.com/entity2'}
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mock_point3 = MagicMock()
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mock_point3.payload = {'entity': 'regular entity'}
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return [mock_point1, mock_point2, mock_point3]
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# Document embeddings query fixtures
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@pytest.fixture
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def mock_document_embeddings_request():
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"""Mock document embeddings request message"""
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mock_message = MagicMock()
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mock_message.vector = [0.1, 0.2, 0.3]
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mock_message.limit = 5
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mock_message.user = 'test_user'
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mock_message.collection = 'test_collection'
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return mock_message
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@pytest.fixture
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def mock_document_embeddings_multiple_vectors():
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"""Mock document embeddings request with multiple vectors (legacy name, now single vector)"""
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mock_message = MagicMock()
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mock_message.vector = [0.1, 0.2, 0.3, 0.4]
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mock_message.limit = 3
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mock_message.user = 'multi_user'
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mock_message.collection = 'multi_collection'
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return mock_message
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@pytest.fixture
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def mock_document_embeddings_query_response():
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"""Mock document embeddings query response from Qdrant"""
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mock_point1 = MagicMock()
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mock_point1.payload = {'doc': 'first document chunk'}
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mock_point2 = MagicMock()
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mock_point2.payload = {'doc': 'second document chunk'}
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return [mock_point1, mock_point2]
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@pytest.fixture
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def mock_document_embeddings_utf8_response():
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"""Mock document embeddings query response with UTF-8 content"""
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mock_point1 = MagicMock()
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mock_point1.payload = {'doc': 'Document with UTF-8: café, naïve, résumé'}
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mock_point2 = MagicMock()
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mock_point2.payload = {'doc': 'Chinese text: 你好世界'}
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return [mock_point1, mock_point2]
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@pytest.fixture
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def mock_empty_query_response():
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"""Mock empty query response"""
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return []
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@pytest.fixture
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def mock_large_query_response():
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"""Mock large query response with many results"""
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mock_points = []
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for i in range(10):
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mock_point = MagicMock()
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mock_point.payload = {'doc': f'document chunk {i}'}
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mock_points.append(mock_point)
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return mock_points
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@pytest.fixture
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def mock_mixed_dimension_vectors():
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"""Mock request with vector (legacy name suggested mixed dimensions, now single vector)"""
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mock_message = MagicMock()
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mock_message.vector = [0.1, 0.2, 0.3, 0.4, 0.5]
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mock_message.limit = 5
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mock_message.user = 'dim_user'
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mock_message.collection = 'dim_collection'
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return mock_message |