Fixing tests

tests/unit/test_query/test_doc_embeddings_milvus_query.py

@@ -77,9 +77,9 @@ class TestMilvusDocEmbeddingsQueryProcessor:
         
         # Mock search results
         mock_results = [
-            {"entity": {"doc": "First document chunk"}},
+            {"entity": {"chunk_id": "First document chunk"}},
-            {"entity": {"doc": "Second document chunk"}},
+            {"entity": {"chunk_id": "Second document chunk"}},
-            {"entity": {"doc": "Third document chunk"}},
+            {"entity": {"chunk_id": "Third document chunk"}},
         ]
         processor.vecstore.search.return_value = mock_results
         
@@ -108,11 +108,11 @@ class TestMilvusDocEmbeddingsQueryProcessor:
         
         # Mock search results - different results for each vector
         mock_results_1 = [
-            {"entity": {"doc": "Document from first vector"}},
+            {"entity": {"chunk_id": "Document from first vector"}},
-            {"entity": {"doc": "Another doc from first vector"}},
+            {"entity": {"chunk_id": "Another doc from first vector"}},
         ]
         mock_results_2 = [
-            {"entity": {"doc": "Document from second vector"}},
+            {"entity": {"chunk_id": "Document from second vector"}},
         ]
         processor.vecstore.search.side_effect = [mock_results_1, mock_results_2]
         
@@ -147,10 +147,10 @@ class TestMilvusDocEmbeddingsQueryProcessor:
         
         # Mock search results - more results than limit
         mock_results = [
-            {"entity": {"doc": "Document 1"}},
+            {"entity": {"chunk_id": "Document 1"}},
-            {"entity": {"doc": "Document 2"}},
+            {"entity": {"chunk_id": "Document 2"}},
-            {"entity": {"doc": "Document 3"}},
+            {"entity": {"chunk_id": "Document 3"}},
-            {"entity": {"doc": "Document 4"}},
+            {"entity": {"chunk_id": "Document 4"}},
         ]
         processor.vecstore.search.return_value = mock_results
         
@@ -217,9 +217,9 @@ class TestMilvusDocEmbeddingsQueryProcessor:
         
         # Mock search results with Unicode content
         mock_results = [
-            {"entity": {"doc": "Document with Unicode: éñ中文🚀"}},
+            {"entity": {"chunk_id": "Document with Unicode: éñ中文🚀"}},
-            {"entity": {"doc": "Regular ASCII document"}},
+            {"entity": {"chunk_id": "Regular ASCII document"}},
-            {"entity": {"doc": "Document with émojis: 😀🎉"}},
+            {"entity": {"chunk_id": "Document with émojis: 😀🎉"}},
         ]
         processor.vecstore.search.return_value = mock_results
         
@@ -244,8 +244,8 @@ class TestMilvusDocEmbeddingsQueryProcessor:
         # Mock search results with large content
         large_doc = "A" * 10000  # 10KB of content
         mock_results = [
-            {"entity": {"doc": large_doc}},
+            {"entity": {"chunk_id": large_doc}},
-            {"entity": {"doc": "Small document"}},
+            {"entity": {"chunk_id": "Small document"}},
         ]
         processor.vecstore.search.return_value = mock_results
         
@@ -268,9 +268,9 @@ class TestMilvusDocEmbeddingsQueryProcessor:
         
         # Mock search results with special characters
         mock_results = [
-            {"entity": {"doc": "Document with \"quotes\" and 'apostrophes'"}},
+            {"entity": {"chunk_id": "Document with \"quotes\" and 'apostrophes'"}},
-            {"entity": {"doc": "Document with\nnewlines\tand\ttabs"}},
+            {"entity": {"chunk_id": "Document with\nnewlines\tand\ttabs"}},
-            {"entity": {"doc": "Document with special chars: @#$%^&*()"}},
+            {"entity": {"chunk_id": "Document with special chars: @#$%^&*()"}},
         ]
         processor.vecstore.search.return_value = mock_results
         
@@ -350,9 +350,9 @@ class TestMilvusDocEmbeddingsQueryProcessor:
         )
         
         # Mock search results for each vector
-        mock_results_1 = [{"entity": {"doc": "Document from 2D vector"}}]
+        mock_results_1 = [{"entity": {"chunk_id": "Document from 2D vector"}}]
-        mock_results_2 = [{"entity": {"doc": "Document from 4D vector"}}]
+        mock_results_2 = [{"entity": {"chunk_id": "Document from 4D vector"}}]
-        mock_results_3 = [{"entity": {"doc": "Document from 3D vector"}}]
+        mock_results_3 = [{"entity": {"chunk_id": "Document from 3D vector"}}]
         processor.vecstore.search.side_effect = [mock_results_1, mock_results_2, mock_results_3]
         
         result = await processor.query_document_embeddings(query)
@@ -378,12 +378,12 @@ class TestMilvusDocEmbeddingsQueryProcessor:
         
         # Mock search results with duplicates across vectors
         mock_results_1 = [
-            {"entity": {"doc": "Document A"}},
+            {"entity": {"chunk_id": "Document A"}},
-            {"entity": {"doc": "Document B"}},
+            {"entity": {"chunk_id": "Document B"}},
         ]
         mock_results_2 = [
-            {"entity": {"doc": "Document B"}},  # Duplicate
+            {"entity": {"chunk_id": "Document B"}},  # Duplicate
-            {"entity": {"doc": "Document C"}},
+            {"entity": {"chunk_id": "Document C"}},
         ]
         processor.vecstore.search.side_effect = [mock_results_1, mock_results_2]
         
@@ -458,5 +458,5 @@ class TestMilvusDocEmbeddingsQueryProcessor:
         
         mock_launch.assert_called_once_with(
             default_ident,
-            "\nDocument embeddings query service.  Input is vector, output is an array\nof chunks\n"
+            "\nDocument embeddings query service.  Input is vector, output is an array\nof chunk_ids\n"
         )

tests/unit/test_query/test_doc_embeddings_qdrant_query.py

@@ -77,9 +77,9 @@ class TestQdrantDocEmbeddingsQuery(IsolatedAsyncioTestCase):
         
         # Mock query response
         mock_point1 = MagicMock()
-        mock_point1.payload = {'doc': 'first document chunk'}
+        mock_point1.payload = {'chunk_id': 'first document chunk'}
         mock_point2 = MagicMock()
-        mock_point2.payload = {'doc': 'second document chunk'}
+        mock_point2.payload = {'chunk_id': 'second document chunk'}
         
         mock_response = MagicMock()
         mock_response.points = [mock_point1, mock_point2]
@@ -132,11 +132,11 @@ class TestQdrantDocEmbeddingsQuery(IsolatedAsyncioTestCase):
         
         # Mock query responses for different vectors
         mock_point1 = MagicMock()
-        mock_point1.payload = {'doc': 'document from vector 1'}
+        mock_point1.payload = {'chunk_id': 'document from vector 1'}
         mock_point2 = MagicMock()
-        mock_point2.payload = {'doc': 'document from vector 2'}
+        mock_point2.payload = {'chunk_id': 'document from vector 2'}
         mock_point3 = MagicMock()
-        mock_point3.payload = {'doc': 'another document from vector 2'}
+        mock_point3.payload = {'chunk_id': 'another document from vector 2'}
         
         mock_response1 = MagicMock()
         mock_response1.points = [mock_point1]
@@ -192,7 +192,7 @@ class TestQdrantDocEmbeddingsQuery(IsolatedAsyncioTestCase):
         mock_points = []
         for i in range(10):
             mock_point = MagicMock()
-            mock_point.payload = {'doc': f'document chunk {i}'}
+            mock_point.payload = {'chunk_id': f'document chunk {i}'}
             mock_points.append(mock_point)
         
         mock_response = MagicMock()
@@ -270,9 +270,9 @@ class TestQdrantDocEmbeddingsQuery(IsolatedAsyncioTestCase):
         
         # Mock query responses
         mock_point1 = MagicMock()
-        mock_point1.payload = {'doc': 'document from 2D vector'}
+        mock_point1.payload = {'chunk_id': 'document from 2D vector'}
         mock_point2 = MagicMock()
-        mock_point2.payload = {'doc': 'document from 3D vector'}
+        mock_point2.payload = {'chunk_id': 'document from 3D vector'}
         
         mock_response1 = MagicMock()
         mock_response1.points = [mock_point1]
@@ -326,9 +326,9 @@ class TestQdrantDocEmbeddingsQuery(IsolatedAsyncioTestCase):
         
         # Mock query response with UTF-8 content
         mock_point1 = MagicMock()
-        mock_point1.payload = {'doc': 'Document with UTF-8: café, naïve, résumé'}
+        mock_point1.payload = {'chunk_id': 'Document with UTF-8: café, naïve, résumé'}
         mock_point2 = MagicMock()
-        mock_point2.payload = {'doc': 'Chinese text: 你好世界'}
+        mock_point2.payload = {'chunk_id': 'Chinese text: 你好世界'}
         
         mock_response = MagicMock()
         mock_response.points = [mock_point1, mock_point2]
@@ -399,7 +399,7 @@ class TestQdrantDocEmbeddingsQuery(IsolatedAsyncioTestCase):
         
         # Mock query response
         mock_point = MagicMock()
-        mock_point.payload = {'doc': 'document chunk'}
+        mock_point.payload = {'chunk_id': 'document chunk'}
         mock_response = MagicMock()
         mock_response.points = [mock_point]
         mock_qdrant_instance.query_points.return_value = mock_response
@@ -442,9 +442,9 @@ class TestQdrantDocEmbeddingsQuery(IsolatedAsyncioTestCase):
         
         # Mock query response with fewer results than limit
         mock_point1 = MagicMock()
-        mock_point1.payload = {'doc': 'document 1'}
+        mock_point1.payload = {'chunk_id': 'document 1'}
         mock_point2 = MagicMock()
-        mock_point2.payload = {'doc': 'document 2'}
+        mock_point2.payload = {'chunk_id': 'document 2'}
         
         mock_response = MagicMock()
         mock_response.points = [mock_point1, mock_point2]
@@ -487,11 +487,11 @@ class TestQdrantDocEmbeddingsQuery(IsolatedAsyncioTestCase):
         mock_qdrant_instance = MagicMock()
         mock_qdrant_client.return_value = mock_qdrant_instance
         
-        # Mock query response with missing 'doc' key
+        # Mock query response with missing 'chunk_id' key
         mock_point1 = MagicMock()
-        mock_point1.payload = {'doc': 'valid document'}
+        mock_point1.payload = {'chunk_id': 'valid document'}
         mock_point2 = MagicMock()
-        mock_point2.payload = {}  # Missing 'doc' key
+        mock_point2.payload = {}  # Missing 'chunk_id' key
         mock_point3 = MagicMock()
         mock_point3.payload = {'other_key': 'invalid'}  # Wrong key
         
@@ -514,7 +514,7 @@ class TestQdrantDocEmbeddingsQuery(IsolatedAsyncioTestCase):
         mock_message.collection = 'payload_collection'
         
         # Act & Assert
-        # This should raise a KeyError when trying to access payload['doc']
+        # This should raise a KeyError when trying to access payload['chunk_id']
         with pytest.raises(KeyError):
             await processor.query_document_embeddings(mock_message)
 

tests/unit/test_storage/test_doc_embeddings_milvus_storage.py

@@ -22,11 +22,11 @@ class TestMilvusDocEmbeddingsStorageProcessor:
         
         # Create test document embeddings
         chunk1 = ChunkEmbeddings(
-            chunk=b"This is the first document chunk",
+            chunk_id="This is the first document chunk",
             vectors=[[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]]
         )
         chunk2 = ChunkEmbeddings(
-            chunk=b"This is the second document chunk",
+            chunk_id="This is the second document chunk",
             vectors=[[0.7, 0.8, 0.9]]
         )
         message.chunks = [chunk1, chunk2]
@@ -84,7 +84,7 @@ class TestMilvusDocEmbeddingsStorageProcessor:
         message.metadata.collection = 'test_collection'
         
         chunk = ChunkEmbeddings(
-            chunk=b"Test document content",
+            chunk_id="Test document content",
             vectors=[[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]]
         )
         message.chunks = [chunk]
@@ -136,7 +136,7 @@ class TestMilvusDocEmbeddingsStorageProcessor:
         message.metadata.collection = 'test_collection'
         
         chunk = ChunkEmbeddings(
-            chunk=b"",
+            chunk_id="",
             vectors=[[0.1, 0.2, 0.3]]
         )
         message.chunks = [chunk]
@@ -148,21 +148,21 @@ class TestMilvusDocEmbeddingsStorageProcessor:
 
     @pytest.mark.asyncio
     async def test_store_document_embeddings_none_chunk(self, processor):
-        """Test storing document embeddings with None chunk (should be skipped)"""
+        """Test storing document embeddings with None chunk_id (should be skipped)"""
         message = MagicMock()
         message.metadata = MagicMock()
         message.metadata.user = 'test_user'
         message.metadata.collection = 'test_collection'
 
         chunk = ChunkEmbeddings(
-            chunk=None,
+            chunk_id=None,
             vectors=[[0.1, 0.2, 0.3]]
         )
         message.chunks = [chunk]
 
         await processor.store_document_embeddings(message)
 
-        # Verify no insert was called for None chunk
+        # Verify no insert was called for None chunk_id
         processor.vecstore.insert.assert_not_called()
 
     @pytest.mark.asyncio
@@ -174,15 +174,15 @@ class TestMilvusDocEmbeddingsStorageProcessor:
         message.metadata.collection = 'test_collection'
         
         valid_chunk = ChunkEmbeddings(
-            chunk=b"Valid document content",
+            chunk_id="Valid document content",
             vectors=[[0.1, 0.2, 0.3]]
         )
         empty_chunk = ChunkEmbeddings(
-            chunk=b"",
+            chunk_id="",
             vectors=[[0.4, 0.5, 0.6]]
         )
         none_chunk = ChunkEmbeddings(
-            chunk=None,
+            chunk_id=None,
             vectors=[[0.7, 0.8, 0.9]]
         )
         message.chunks = [valid_chunk, empty_chunk, none_chunk]
@@ -217,7 +217,7 @@ class TestMilvusDocEmbeddingsStorageProcessor:
         message.metadata.collection = 'test_collection'
         
         chunk = ChunkEmbeddings(
-            chunk=b"Document with no vectors",
+            chunk_id="Document with no vectors",
             vectors=[]
         )
         message.chunks = [chunk]
@@ -236,7 +236,7 @@ class TestMilvusDocEmbeddingsStorageProcessor:
         message.metadata.collection = 'test_collection'
         
         chunk = ChunkEmbeddings(
-            chunk=b"Document with mixed dimensions",
+            chunk_id="Document with mixed dimensions",
             vectors=[
                 [0.1, 0.2],  # 2D vector
                 [0.3, 0.4, 0.5, 0.6],  # 4D vector
@@ -264,46 +264,46 @@ class TestMilvusDocEmbeddingsStorageProcessor:
 
     @pytest.mark.asyncio
     async def test_store_document_embeddings_unicode_content(self, processor):
-        """Test storing document embeddings with Unicode content"""
+        """Test storing document embeddings with Unicode content in chunk_id"""
         message = MagicMock()
         message.metadata = MagicMock()
         message.metadata.user = 'test_user'
         message.metadata.collection = 'test_collection'
 
         chunk = ChunkEmbeddings(
-            chunk="Document with Unicode: éñ中文🚀".encode('utf-8'),
+            chunk_id="chunk/doc/unicode-éñ中文🚀",
             vectors=[[0.1, 0.2, 0.3]]
         )
         message.chunks = [chunk]
 
         await processor.store_document_embeddings(message)
 
-        # Verify Unicode content was properly decoded and inserted with user/collection parameters
+        # Verify Unicode chunk_id was stored correctly with user/collection parameters
         processor.vecstore.insert.assert_called_once_with(
-            [0.1, 0.2, 0.3], "Document with Unicode: éñ中文🚀", 'test_user', 'test_collection'
+            [0.1, 0.2, 0.3], "chunk/doc/unicode-éñ中文🚀", 'test_user', 'test_collection'
         )
 
     @pytest.mark.asyncio
-    async def test_store_document_embeddings_large_chunks(self, processor):
+    async def test_store_document_embeddings_large_chunk_id(self, processor):
-        """Test storing document embeddings with large document chunks"""
+        """Test storing document embeddings with long chunk_id"""
         message = MagicMock()
         message.metadata = MagicMock()
         message.metadata.user = 'test_user'
         message.metadata.collection = 'test_collection'
 
-        # Create a large document chunk
+        # Create a long chunk_id
-        large_content = "A" * 10000  # 10KB of content
+        long_chunk_id = "chunk/doc/" + "a" * 200
         chunk = ChunkEmbeddings(
-            chunk=large_content.encode('utf-8'),
+            chunk_id=long_chunk_id,
             vectors=[[0.1, 0.2, 0.3]]
         )
         message.chunks = [chunk]
 
         await processor.store_document_embeddings(message)
 
-        # Verify large content was inserted with user/collection parameters
+        # Verify long chunk_id was inserted with user/collection parameters
         processor.vecstore.insert.assert_called_once_with(
-            [0.1, 0.2, 0.3], large_content, 'test_user', 'test_collection'
+            [0.1, 0.2, 0.3], long_chunk_id, 'test_user', 'test_collection'
         )
 
     @pytest.mark.asyncio
@@ -315,7 +315,7 @@ class TestMilvusDocEmbeddingsStorageProcessor:
         message.metadata.collection = 'test_collection'
         
         chunk = ChunkEmbeddings(
-            chunk=b"   \n\t   ",
+            chunk_id="   \n\t   ",
             vectors=[[0.1, 0.2, 0.3]]
         )
         message.chunks = [chunk]
@@ -346,7 +346,7 @@ class TestMilvusDocEmbeddingsStorageProcessor:
             message.metadata.collection = collection
             
             chunk = ChunkEmbeddings(
-                chunk=b"Test content",
+                chunk_id="Test content",
                 vectors=[[0.1, 0.2, 0.3]]
             )
             message.chunks = [chunk]
@@ -367,7 +367,7 @@ class TestMilvusDocEmbeddingsStorageProcessor:
         message1.metadata.user = 'user1'
         message1.metadata.collection = 'collection1'
         chunk1 = ChunkEmbeddings(
-            chunk=b"User1 content",
+            chunk_id="User1 content",
             vectors=[[0.1, 0.2, 0.3]]
         )
         message1.chunks = [chunk1]
@@ -378,7 +378,7 @@ class TestMilvusDocEmbeddingsStorageProcessor:
         message2.metadata.user = 'user2'
         message2.metadata.collection = 'collection2'
         chunk2 = ChunkEmbeddings(
-            chunk=b"User2 content",
+            chunk_id="User2 content",
             vectors=[[0.4, 0.5, 0.6]]
         )
         message2.chunks = [chunk2]
@@ -409,7 +409,7 @@ class TestMilvusDocEmbeddingsStorageProcessor:
         message.metadata.collection = 'test-collection.v1'  # Collection with special chars
         
         chunk = ChunkEmbeddings(
-            chunk=b"Special chars test",
+            chunk_id="Special chars test",
             vectors=[[0.1, 0.2, 0.3]]
         )
         message.chunks = [chunk]

tests/unit/test_storage/test_doc_embeddings_qdrant_storage.py

@@ -88,7 +88,7 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
         mock_message.metadata.collection = 'test_collection'
 
         mock_chunk = MagicMock()
-        mock_chunk.chunk.decode.return_value = 'test document chunk'
+        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_message.chunks = [mock_chunk]
@@ -111,7 +111,7 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
 
         point = upsert_call_args[1]['points'][0]
         assert point.vector == [0.1, 0.2, 0.3]
-        assert point.payload['doc'] == 'test document chunk'
+        assert point.payload['chunk_id'] == 'doc/c1'
 
     @patch('trustgraph.storage.doc_embeddings.qdrant.write.QdrantClient')
     @patch('trustgraph.storage.doc_embeddings.qdrant.write.uuid')
@@ -142,11 +142,11 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
         mock_message.metadata.collection = 'multi_collection'
 
         mock_chunk1 = MagicMock()
-        mock_chunk1.chunk.decode.return_value = 'first document chunk'
+        mock_chunk1.chunk_id = 'doc/c1'
         mock_chunk1.vectors = [[0.1, 0.2]]
 
         mock_chunk2 = MagicMock()
-        mock_chunk2.chunk.decode.return_value = 'second document chunk'
+        mock_chunk2.chunk_id = 'doc/c2'
         mock_chunk2.vectors = [[0.3, 0.4]]
 
         mock_message.chunks = [mock_chunk1, mock_chunk2]
@@ -165,13 +165,13 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
         first_call = upsert_calls[0]
         first_point = first_call[1]['points'][0]
         assert first_point.vector == [0.1, 0.2]
-        assert first_point.payload['doc'] == 'first document chunk'
+        assert first_point.payload['chunk_id'] == 'doc/c1'
 
         # Second chunk
         second_call = upsert_calls[1]
         second_point = second_call[1]['points'][0]
         assert second_point.vector == [0.3, 0.4]
-        assert second_point.payload['doc'] == 'second document chunk'
+        assert second_point.payload['chunk_id'] == 'doc/c2'
 
     @patch('trustgraph.storage.doc_embeddings.qdrant.write.QdrantClient')
     @patch('trustgraph.storage.doc_embeddings.qdrant.write.uuid')
@@ -202,7 +202,7 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
         mock_message.metadata.collection = 'vector_collection'
 
         mock_chunk = MagicMock()
-        mock_chunk.chunk.decode.return_value = 'multi-vector document chunk'
+        mock_chunk.chunk_id = 'doc/multi-vector'
         mock_chunk.vectors = [
             [0.1, 0.2, 0.3],
             [0.4, 0.5, 0.6],
@@ -230,11 +230,11 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
         for i, call in enumerate(upsert_calls):
             point = call[1]['points'][0]
             assert point.vector == expected_vectors[i]
-            assert point.payload['doc'] == 'multi-vector document chunk'
+            assert point.payload['chunk_id'] == 'doc/multi-vector'
 
     @patch('trustgraph.storage.doc_embeddings.qdrant.write.QdrantClient')
-    async def test_store_document_embeddings_empty_chunk(self, mock_qdrant_client):
+    async def test_store_document_embeddings_empty_chunk_id(self, mock_qdrant_client):
-        """Test storing document embeddings skips empty chunks"""
+        """Test storing document embeddings skips empty chunk_ids"""
         # Arrange
         mock_qdrant_instance = MagicMock()
         mock_qdrant_instance.collection_exists.return_value = True  # Collection exists
@@ -249,13 +249,13 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
 
         processor = Processor(**config)
 
-        # Create mock message with empty chunk
+        # Create mock message with empty chunk_id
         mock_message = MagicMock()
         mock_message.metadata.user = 'empty_user'
         mock_message.metadata.collection = 'empty_collection'
 
         mock_chunk_empty = MagicMock()
-        mock_chunk_empty.chunk.decode.return_value = ""  # Empty string
+        mock_chunk_empty.chunk_id = ""  # Empty chunk_id
         mock_chunk_empty.vectors = [[0.1, 0.2]]
 
         mock_message.chunks = [mock_chunk_empty]
@@ -264,9 +264,9 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
         await processor.store_document_embeddings(mock_message)
 
         # Assert
-        # Should not call upsert for empty chunks
+        # Should not call upsert for empty chunk_ids
         mock_qdrant_instance.upsert.assert_not_called()
-        # collection_exists should NOT be called since we return early for empty chunks
+        # collection_exists should NOT be called since we return early for empty chunk_ids
         mock_qdrant_instance.collection_exists.assert_not_called()
 
     @patch('trustgraph.storage.doc_embeddings.qdrant.write.QdrantClient')
@@ -298,7 +298,7 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
         mock_message.metadata.collection = 'new_collection'
 
         mock_chunk = MagicMock()
-        mock_chunk.chunk.decode.return_value = 'test chunk'
+        mock_chunk.chunk_id = 'doc/test-chunk'
         mock_chunk.vectors = [[0.1, 0.2, 0.3, 0.4, 0.5]]  # 5 dimensions
 
         mock_message.chunks = [mock_chunk]
@@ -350,7 +350,7 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
         mock_message.metadata.collection = 'error_collection'
 
         mock_chunk = MagicMock()
-        mock_chunk.chunk.decode.return_value = 'test chunk'
+        mock_chunk.chunk_id = 'doc/test-chunk'
         mock_chunk.vectors = [[0.1, 0.2]]
 
         mock_message.chunks = [mock_chunk]
@@ -388,7 +388,7 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
         mock_message1.metadata.collection = 'cache_collection'
 
         mock_chunk1 = MagicMock()
-        mock_chunk1.chunk.decode.return_value = 'first chunk'
+        mock_chunk1.chunk_id = 'doc/c1'
         mock_chunk1.vectors = [[0.1, 0.2, 0.3]]
 
         mock_message1.chunks = [mock_chunk1]
@@ -406,7 +406,7 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
         mock_message2.metadata.collection = 'cache_collection'
 
         mock_chunk2 = MagicMock()
-        mock_chunk2.chunk.decode.return_value = 'second chunk'
+        mock_chunk2.chunk_id = 'doc/c2'
         mock_chunk2.vectors = [[0.4, 0.5, 0.6]]  # Same dimension (3)
 
         mock_message2.chunks = [mock_chunk2]
@@ -452,7 +452,7 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
         mock_message.metadata.collection = 'dim_collection'
 
         mock_chunk = MagicMock()
-        mock_chunk.chunk.decode.return_value = 'dimension test chunk'
+        mock_chunk.chunk_id = 'doc/dim-test'
         mock_chunk.vectors = [
             [0.1, 0.2],          # 2 dimensions
             [0.3, 0.4, 0.5]      # 3 dimensions
@@ -498,8 +498,8 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
 
     @patch('trustgraph.storage.doc_embeddings.qdrant.write.QdrantClient')
     @patch('trustgraph.storage.doc_embeddings.qdrant.write.uuid')
-    async def test_utf8_decoding_handling(self, mock_uuid, mock_qdrant_client):
+    async def test_chunk_id_with_special_characters(self, mock_uuid, mock_qdrant_client):
-        """Test proper UTF-8 decoding of chunk text"""
+        """Test storing chunk_id with special characters (URIs)"""
         # Arrange
         mock_qdrant_instance = MagicMock()
         mock_qdrant_instance.collection_exists.return_value = True
@@ -517,15 +517,15 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
         processor = Processor(**config)
 
         # Add collection to known_collections (simulates config push)
-        processor.known_collections[('utf8_user', 'utf8_collection')] = {}
+        processor.known_collections[('uri_user', 'uri_collection')] = {}
 
-        # Create mock message with UTF-8 encoded text
+        # Create mock message with URI-style chunk_id
         mock_message = MagicMock()
-        mock_message.metadata.user = 'utf8_user'
+        mock_message.metadata.user = 'uri_user'
-        mock_message.metadata.collection = 'utf8_collection'
+        mock_message.metadata.collection = 'uri_collection'
 
         mock_chunk = MagicMock()
-        mock_chunk.chunk.decode.return_value = 'UTF-8 text with special chars: café, naïve, résumé'
+        mock_chunk.chunk_id = 'https://trustgraph.ai/doc/my-document/p1/c3'
         mock_chunk.vectors = [[0.1, 0.2]]
 
         mock_message.chunks = [mock_chunk]
@@ -534,47 +534,10 @@ class TestQdrantDocEmbeddingsStorage(IsolatedAsyncioTestCase):
         await processor.store_document_embeddings(mock_message)
 
         # Assert
-        # Verify chunk.decode was called with 'utf-8'
+        # Verify the chunk_id was stored correctly
-        mock_chunk.chunk.decode.assert_called_with('utf-8')
-        
-        # Verify the decoded text was stored in payload
         upsert_call_args = mock_qdrant_instance.upsert.call_args
         point = upsert_call_args[1]['points'][0]
-        assert point.payload['doc'] == 'UTF-8 text with special chars: café, naïve, résumé'
+        assert point.payload['chunk_id'] == 'https://trustgraph.ai/doc/my-document/p1/c3'
-
-    @patch('trustgraph.storage.doc_embeddings.qdrant.write.QdrantClient')
-    async def test_chunk_decode_exception_handling(self, mock_qdrant_client):
-        """Test handling of chunk decode exceptions"""
-        # Arrange
-        mock_qdrant_instance = MagicMock()
-        mock_qdrant_client.return_value = mock_qdrant_instance
-        
-        config = {
-            'store_uri': 'http://localhost:6333',
-            'api_key': 'test-api-key',
-            'taskgroup': AsyncMock(),
-            'id': 'test-doc-qdrant-processor'
-        }
-
-        processor = Processor(**config)
-
-        # Add collection to known_collections (simulates config push)
-        processor.known_collections[('decode_user', 'decode_collection')] = {}
-
-        # Create mock message with decode error
-        mock_message = MagicMock()
-        mock_message.metadata.user = 'decode_user'
-        mock_message.metadata.collection = 'decode_collection'
-        
-        mock_chunk = MagicMock()
-        mock_chunk.chunk.decode.side_effect = UnicodeDecodeError('utf-8', b'', 0, 1, 'invalid start byte')
-        mock_chunk.vectors = [[0.1, 0.2]]
-        
-        mock_message.chunks = [mock_chunk]
-        
-        # Act & Assert
-        with pytest.raises(UnicodeDecodeError):
-            await processor.store_document_embeddings(mock_message)
 
 
 if __name__ == '__main__':