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Knowledge core processing updated for embeddings interface change (#681)

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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].
This commit is contained in:
cybermaggedon 2026-03-10 13:28:16 +00:00 • committed by GitHub
parent 84941ce645
commit 57eda65674
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GPG key ID: B5690EEEBB952194
7 changed files with 32 additions and 46 deletions
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26
tests/unit/test_storage/conftest.py
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@ -53,7 +53,7 @@ def mock_document_embeddings_message():
mock_chunk = MagicMock()
mock_chunk.chunk.decode.return_value = 'test document chunk'
mock_chunk.vectors = [[0.1, 0.2, 0.3]]
mock_chunk.vector = [0.1, 0.2, 0.3]
mock_message.chunks = [mock_chunk]
return mock_message
@ -68,11 +68,11 @@ def mock_document_embeddings_multiple_chunks():
mock_chunk1 = MagicMock()
mock_chunk1.chunk.decode.return_value = 'first document chunk'
mock_chunk1.vectors = [[0.1, 0.2]]
mock_chunk1.vector = [0.1, 0.2]
mock_chunk2 = MagicMock()
mock_chunk2.chunk.decode.return_value = 'second document chunk'
mock_chunk2.vectors = [[0.3, 0.4]]
mock_chunk2.vector = [0.3, 0.4]
mock_message.chunks = [mock_chunk1, mock_chunk2]
return mock_message
@ -87,11 +87,7 @@ def mock_document_embeddings_multiple_vectors():
mock_chunk = MagicMock()
mock_chunk.chunk.decode.return_value = 'multi-vector document chunk'
mock_chunk.vectors = [
[0.1, 0.2, 0.3],
[0.4, 0.5, 0.6],
[0.7, 0.8, 0.9]
]
mock_chunk.vector = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]
mock_message.chunks = [mock_chunk]
return mock_message
@ -106,7 +102,7 @@ def mock_document_embeddings_empty_chunk():
mock_chunk = MagicMock()
mock_chunk.chunk.decode.return_value = "" # Empty string
mock_chunk.vectors = [[0.1, 0.2]]
mock_chunk.vector = [0.1, 0.2]
mock_message.chunks = [mock_chunk]
return mock_message
@ -122,7 +118,7 @@ def mock_graph_embeddings_message():
mock_entity = MagicMock()
mock_entity.entity.value = 'test_entity'
mock_entity.vectors = [[0.1, 0.2, 0.3]]
mock_entity.vector = [0.1, 0.2, 0.3]
mock_message.entities = [mock_entity]
return mock_message
@ -137,11 +133,11 @@ def mock_graph_embeddings_multiple_entities():
mock_entity1 = MagicMock()
mock_entity1.entity.value = 'entity_one'
mock_entity1.vectors = [[0.1, 0.2]]
mock_entity1.vector = [0.1, 0.2]
mock_entity2 = MagicMock()
mock_entity2.entity.value = 'entity_two'
mock_entity2.vectors = [[0.3, 0.4]]
mock_entity2.vector = [0.3, 0.4]
mock_message.entities = [mock_entity1, mock_entity2]
return mock_message
@ -156,7 +152,7 @@ def mock_graph_embeddings_empty_entity():
mock_entity = MagicMock()
mock_entity.entity.value = "" # Empty string
mock_entity.vectors = [[0.1, 0.2]]
mock_entity.vector = [0.1, 0.2]
mock_message.entities = [mock_entity]
return mock_message