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

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].

tests/unit/test_query/conftest.py

@@ -37,7 +37,7 @@ def mock_qdrant_client():
 def mock_graph_embeddings_request():
     """Mock graph embeddings request 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'
@@ -46,9 +46,9 @@ def mock_graph_embeddings_request():
 
 @pytest.fixture
 def mock_graph_embeddings_multiple_vectors():
-    """Mock graph embeddings request with multiple vectors"""
+    """Mock graph embeddings request with multiple vectors (legacy name, now single vector)"""
     mock_message = MagicMock()
-    mock_message.vectors = [[0.1, 0.2], [0.3, 0.4]]
+    mock_message.vector = [0.1, 0.2, 0.3, 0.4]
     mock_message.limit = 3
     mock_message.user = 'multi_user'
     mock_message.collection = 'multi_collection'
@@ -82,7 +82,7 @@ def mock_graph_embeddings_uri_response():
 def mock_document_embeddings_request():
     """Mock document embeddings request 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'
@@ -91,9 +91,9 @@ def mock_document_embeddings_request():
 
 @pytest.fixture
 def mock_document_embeddings_multiple_vectors():
-    """Mock document embeddings request with multiple vectors"""
+    """Mock document embeddings request with multiple vectors (legacy name, now single vector)"""
     mock_message = MagicMock()
-    mock_message.vectors = [[0.1, 0.2], [0.3, 0.4]]
+    mock_message.vector = [0.1, 0.2, 0.3, 0.4]
     mock_message.limit = 3
     mock_message.user = 'multi_user'
     mock_message.collection = 'multi_collection'
@@ -139,9 +139,9 @@ def mock_large_query_response():
 
 @pytest.fixture
 def mock_mixed_dimension_vectors():
-    """Mock request with vectors of different dimensions"""
+    """Mock request with vector (legacy name suggested mixed dimensions, now single vector)"""
     mock_message = MagicMock()
-    mock_message.vectors = [[0.1, 0.2], [0.3, 0.4, 0.5]]  # 2D and 3D
+    mock_message.vector = [0.1, 0.2, 0.3, 0.4, 0.5]
     mock_message.limit = 5
     mock_message.user = 'dim_user'
     mock_message.collection = 'dim_collection'

tests/unit/test_query/test_doc_embeddings_pinecone_query.py

@@ -18,10 +18,7 @@ class TestPineconeDocEmbeddingsQueryProcessor:
     def mock_query_message(self):
         """Create a mock query message for testing"""
         message = MagicMock()
-        message.vectors = [
-            [0.1, 0.2, 0.3],
-            [0.4, 0.5, 0.6]
-        ]
+        message.vector = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6]
         message.limit = 5
         message.user = 'test_user'
         message.collection = 'test_collection'
@@ -242,12 +239,9 @@ class TestPineconeDocEmbeddingsQueryProcessor:
 
     @pytest.mark.asyncio
     async def test_query_document_embeddings_different_vector_dimensions(self, processor):
-        """Test querying with vectors of different dimensions using same index"""
+        """Test querying with single vector (legacy test name, schema now uses single vector)"""
         message = MagicMock()
-        message.vectors = [
-            [0.1, 0.2],  # 2D vector
-            [0.3, 0.4, 0.5, 0.6]  # 4D vector
-        ]
+        message.vector = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6]
         message.limit = 5
         message.user = 'test_user'
         message.collection = 'test_collection'
@@ -437,13 +431,9 @@ class TestPineconeDocEmbeddingsQueryProcessor:
 
     @pytest.mark.asyncio
     async def test_query_document_embeddings_vector_accumulation(self, processor):
-        """Test that results from multiple vectors are properly accumulated"""
+        """Test that results from single vector query are returned (legacy multi-vector test)"""
         message = MagicMock()
-        message.vectors = [
-            [0.1, 0.2, 0.3],
-            [0.4, 0.5, 0.6],
-            [0.7, 0.8, 0.9]
-        ]
+        message.vector = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]
         message.limit = 2
         message.user = 'test_user'
         message.collection = 'test_collection'