Pinecone: Namespace and field remapping support

airbyte-integrations/connectors/destination-pinecone/destination_pinecone/indexer.py

@@ -8,7 +8,7 @@
 import pinecone
 from airbyte_cdk.destinations.vector_db_based.document_processor import METADATA_RECORD_ID_FIELD, METADATA_STREAM_FIELD
 from airbyte_cdk.destinations.vector_db_based.indexer import Indexer
-from airbyte_cdk.destinations.vector_db_based.utils import create_chunks, format_exception
+from airbyte_cdk.destinations.vector_db_based.utils import create_chunks, create_stream_identifier, format_exception
 from airbyte_cdk.models.airbyte_protocol import ConfiguredAirbyteCatalog, DestinationSyncMode
 from destination_pinecone.config import PineconeIndexingModel
 
@@ -38,30 +38,32 @@ def pre_sync(self, catalog: ConfiguredAirbyteCatalog):
         self._pod_type = index_description.pod_type
         for stream in catalog.streams:
             if stream.destination_sync_mode == DestinationSyncMode.overwrite:
-                self.delete_vectors(filter={METADATA_STREAM_FIELD: stream.stream.name})
+                self.delete_vectors(
+                    filter={METADATA_STREAM_FIELD: create_stream_identifier(stream.stream)}, namespace=stream.stream.namespace
+                )
 
     def post_sync(self):
         return []
 
-    def delete_vectors(self, filter):
+    def delete_vectors(self, filter, namespace=None):
         if self._pod_type == "starter":
             # Starter pod types have a maximum of 100000 rows
             top_k = 10000
-            self.delete_by_metadata(filter, top_k)
+            self.delete_by_metadata(filter, top_k, namespace)
         else:
-            self.pinecone_index.delete(filter=filter)
+            self.pinecone_index.delete(filter=filter, namespace=namespace)
 
-    def delete_by_metadata(self, filter, top_k):
+    def delete_by_metadata(self, filter, top_k, namespace=None):
         zero_vector = [0.0] * self.embedding_dimensions
-        query_result = self.pinecone_index.query(vector=zero_vector, filter=filter, top_k=top_k)
+        query_result = self.pinecone_index.query(vector=zero_vector, filter=filter, top_k=top_k, namespace=namespace)
         while len(query_result.matches) > 0:
             vector_ids = [doc.id for doc in query_result.matches]
             if len(vector_ids) > 0:
                 # split into chunks of 1000 ids to avoid id limit
                 batches = create_chunks(vector_ids, batch_size=MAX_IDS_PER_DELETE)
                 for batch in batches:
-                    self.pinecone_index.delete(ids=list(batch))
-            query_result = self.pinecone_index.query(vector=zero_vector, filter=filter, top_k=top_k)
+                    self.pinecone_index.delete(ids=list(batch), namespace=namespace)
+            query_result = self.pinecone_index.query(vector=zero_vector, filter=filter, top_k=top_k, namespace=namespace)
 
     def _truncate_metadata(self, metadata: dict) -> dict:
         """
@@ -92,15 +94,15 @@ def index(self, document_chunks, namespace, stream):
         serial_batches = create_chunks(pinecone_docs, batch_size=PINECONE_BATCH_SIZE * PARALLELISM_LIMIT)
         for batch in serial_batches:
             async_results = [
-                self.pinecone_index.upsert(vectors=ids_vectors_chunk, async_req=True, show_progress=False)
+                self.pinecone_index.upsert(vectors=ids_vectors_chunk, async_req=True, show_progress=False, namespace=namespace)
                 for ids_vectors_chunk in create_chunks(batch, batch_size=PINECONE_BATCH_SIZE)
             ]
             # Wait for and retrieve responses (this raises in case of error)
             [async_result.result() for async_result in async_results]
 
     def delete(self, delete_ids, namespace, stream):
         if len(delete_ids) > 0:
-            self.delete_vectors(filter={METADATA_RECORD_ID_FIELD: {"$in": delete_ids}})
+            self.delete_vectors(filter={METADATA_RECORD_ID_FIELD: {"$in": delete_ids}}, namespace=namespace)
 
     def check(self) -> Optional[str]:
         try:

airbyte-integrations/connectors/destination-pinecone/integration_tests/spec.json

@@ -199,6 +199,29 @@
             "type": "array",
             "items": { "type": "string" }
           },
+          "field_name_mappings": {
+            "title": "Field name mappings",
+            "description": "List of fields to rename. Not applicable for nested fields, but can be used to rename fields already flattened via dot notation.",
+            "default": [],
+            "type": "array",
+            "items": {
+              "title": "FieldNameMappingConfigModel",
+              "type": "object",
+              "properties": {
+                "from_field": {
+                  "title": "From field name",
+                  "description": "The field name in the source",
+                  "type": "string"
+                },
+                "to_field": {
+                  "title": "To field name",
+                  "description": "The field name to use in the destination",
+                  "type": "string"
+                }
+              },
+              "required": ["from_field", "to_field"]
+            }
+          },
           "text_splitter": {
             "title": "Text splitter",
             "description": "Split text fields into chunks based on the specified method.",

airbyte-integrations/connectors/destination-pinecone/metadata.yaml

@@ -13,7 +13,7 @@ data:
   connectorSubtype: vectorstore
   connectorType: destination
   definitionId: 3d2b6f84-7f0d-4e3f-a5e5-7c7d4b50eabd
-  dockerImageTag: 0.0.17
+  dockerImageTag: 0.0.18
   dockerRepository: airbyte/destination-pinecone
   documentationUrl: https://docs.airbyte.com/integrations/destinations/pinecone
   githubIssueLabel: destination-pinecone

airbyte-integrations/connectors/destination-pinecone/setup.py

@@ -6,7 +6,7 @@
 from setuptools import find_packages, setup
 
 MAIN_REQUIREMENTS = [
-    "airbyte-cdk[vector-db-based]==0.51.34",
+    "airbyte-cdk[vector-db-based]==0.51.41",
     "pinecone-client[grpc]",
 ]
 

airbyte-integrations/connectors/destination-pinecone/unit_tests/pinecone_indexer_test.py

@@ -51,18 +51,19 @@ def test_pinecone_index_upsert_and_delete(mock_describe_index):
             Mock(page_content="test", metadata={"_ab_stream": "abc"}, embedding=[1, 2, 3]),
             Mock(page_content="test2", metadata={"_ab_stream": "abc"}, embedding=[4, 5, 6]),
         ],
-        None,
+        "ns1",
         "some_stream",
     )
-    indexer.delete(["delete_id1", "delete_id2"], None, "some_stram")
-    indexer.pinecone_index.delete.assert_called_with(filter={"_ab_record_id": {"$in": ["delete_id1", "delete_id2"]}})
+    indexer.delete(["delete_id1", "delete_id2"], "ns1", "some_stram")
+    indexer.pinecone_index.delete.assert_called_with(filter={"_ab_record_id": {"$in": ["delete_id1", "delete_id2"]}}, namespace="ns1")
     indexer.pinecone_index.upsert.assert_called_with(
         vectors=(
             (ANY, [1, 2, 3], {"_ab_stream": "abc", "text": "test"}),
             (ANY, [4, 5, 6], {"_ab_stream": "abc", "text": "test2"}),
         ),
         async_req=True,
         show_progress=False,
+        namespace="ns1",
     )
 
 
@@ -79,21 +80,24 @@ def test_pinecone_index_upsert_and_delete_starter(mock_describe_index):
             Mock(page_content="test", metadata={"_ab_stream": "abc"}, embedding=[1, 2, 3]),
             Mock(page_content="test2", metadata={"_ab_stream": "abc"}, embedding=[4, 5, 6]),
         ],
-        None,
+        "ns1",
         "some_stream",
     )
-    indexer.delete(["delete_id1", "delete_id2"], None, "some_stram")
+    indexer.delete(["delete_id1", "delete_id2"], "ns1", "some_stram")
     indexer.pinecone_index.query.assert_called_with(
-        vector=[0, 0, 0], filter={"_ab_record_id": {"$in": ["delete_id1", "delete_id2"]}}, top_k=10_000
+        vector=[0, 0, 0], filter={"_ab_record_id": {"$in": ["delete_id1", "delete_id2"]}}, top_k=10_000, namespace="ns1"
+    )
+    indexer.pinecone_index.delete.assert_has_calls(
+        [call(ids=["doc_id1", "doc_id2"], namespace="ns1"), call(ids=["doc_id3"], namespace="ns1")]
     )
-    indexer.pinecone_index.delete.assert_has_calls([call(ids=["doc_id1", "doc_id2"]), call(ids=["doc_id3"])])
     indexer.pinecone_index.upsert.assert_called_with(
         vectors=(
             (ANY, [1, 2, 3], {"_ab_stream": "abc", "text": "test"}),
             (ANY, [4, 5, 6], {"_ab_stream": "abc", "text": "test2"}),
         ),
         async_req=True,
         show_progress=False,
+        namespace="ns1",
     )
 
 
@@ -104,15 +108,18 @@ def test_pinecone_index_delete_1k_limit(mock_describe_index):
         MagicMock(matches=[MagicMock(id=f"doc_id_{str(i)}") for i in range(1300)]),
         MagicMock(matches=[]),
     ]
-    indexer.delete(["delete_id1"], None, "some_stream")
+    indexer.delete(["delete_id1"], "ns1", "some_stream")
     indexer.pinecone_index.delete.assert_has_calls(
-        [call(ids=[f"doc_id_{str(i)}" for i in range(1000)]), call(ids=[f"doc_id_{str(i+1000)}" for i in range(300)])]
+        [
+            call(ids=[f"doc_id_{str(i)}" for i in range(1000)], namespace="ns1"),
+            call(ids=[f"doc_id_{str(i+1000)}" for i in range(300)], namespace="ns1"),
+        ]
     )
 
 
 def test_pinecone_index_empty_batch():
     indexer = create_pinecone_indexer()
-    indexer.index([], None, "some_stream")
+    indexer.index([], "ns1", "some_stream")
     indexer.pinecone_index.delete.assert_not_called()
     indexer.pinecone_index.upsert.assert_not_called()
 
@@ -121,7 +128,7 @@ def test_pinecone_index_upsert_batching():
     indexer = create_pinecone_indexer()
     indexer.index(
         [Mock(page_content=f"test {i}", metadata={"_ab_stream": "abc"}, embedding=[i, i, i]) for i in range(50)],
-        None,
+        "ns1",
         "some_stream",
     )
     assert indexer.pinecone_index.upsert.call_count == 2
@@ -150,6 +157,7 @@ def generate_catalog():
                         "supported_sync_modes": ["full_refresh", "incremental"],
                         "source_defined_cursor": False,
                         "default_cursor_field": ["column_name"],
+                        "namespace": "ns1",
                     },
                     "primary_key": [["id"]],
                     "sync_mode": "incremental",
@@ -162,6 +170,7 @@ def generate_catalog():
                         "supported_sync_modes": ["full_refresh", "incremental"],
                         "source_defined_cursor": False,
                         "default_cursor_field": ["column_name"],
+                        "namespace": "ns2",
                     },
                     "primary_key": [["id"]],
                     "sync_mode": "full_refresh",
@@ -175,7 +184,7 @@ def generate_catalog():
 def test_pinecone_pre_sync(mock_describe_index):
     indexer = create_pinecone_indexer()
     indexer.pre_sync(generate_catalog())
-    indexer.pinecone_index.delete.assert_called_with(filter={"_ab_stream": "example_stream2"})
+    indexer.pinecone_index.delete.assert_called_with(filter={"_ab_stream": "ns2_example_stream2"}, namespace="ns2")
 
 
 def test_pinecone_pre_sync_starter(mock_describe_index):
@@ -186,8 +195,10 @@ def test_pinecone_pre_sync_starter(mock_describe_index):
         MagicMock(matches=[]),
     ]
     indexer.pre_sync(generate_catalog())
-    indexer.pinecone_index.query.assert_called_with(vector=[0, 0, 0], filter={"_ab_stream": "example_stream2"}, top_k=10_000)
-    indexer.pinecone_index.delete.assert_called_with(ids=["doc_id1", "doc_id2"])
+    indexer.pinecone_index.query.assert_called_with(
+        vector=[0, 0, 0], filter={"_ab_stream": "ns2_example_stream2"}, top_k=10_000, namespace="ns2"
+    )
+    indexer.pinecone_index.delete.assert_called_with(ids=["doc_id1", "doc_id2"], namespace="ns2")
 
 
 @pytest.mark.parametrize(
@@ -238,4 +249,5 @@ def test_metadata_normalization():
         vectors=((ANY, [1, 2, 3], {"_ab_stream": "abc", "text": "test", "small": "a", "id": 1}),),
         async_req=True,
         show_progress=False,
+        namespace=None,
     )

docs/integrations/destinations/pinecone.md

@@ -30,7 +30,7 @@ You'll need the following information to configure the destination:
 | Full Refresh Sync              | Yes                  |       |
 | Incremental - Append Sync      | Yes                  |       |
 | Incremental - Append + Deduped | Yes                  | Deleting records via CDC is not supported (see issue [#29827](https://github.com/airbytehq/airbyte/issues/29827))  |
-| Namespaces                     | No                   |       |
+| Namespaces                     | Yes                   |       |
 
 ## Data type mapping
 
@@ -74,6 +74,7 @@ OpenAI and Fake embeddings produce vectors with 1536 dimensions, and the Cohere
 
 | Version | Date       | Pull Request                                                  | Subject                                                                                                                                              |
 |:--------| :--------- |:--------------------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------|
+| 0.0.18   | 2023-10-20 | [#31329](https://github.com/airbytehq/airbyte/pull/31373) | Add support for namespaces and fix index cleaning when namespace is defined |
 | 0.0.17 | 2023-10-19 | [31599](https://github.com/airbytehq/airbyte/pull/31599) | Base image migration: remove Dockerfile and use the python-connector-base image |
 | 0.0.16   | 2023-10-15 | [#31329](https://github.com/airbytehq/airbyte/pull/31329) | Add OpenAI-compatible embedder option |
 | 0.0.15   | 2023-10-04 | [#31075](https://github.com/airbytehq/airbyte/pull/31075) | Fix OpenAI embedder batch size |