feat: Adding Pinecone Vector DB option for RAG corpuses to SDK

PiperOrigin-RevId: 675328511

tests/unit/vertex_rag/test_rag_constants.py

@@ -20,6 +20,7 @@
 
 from vertexai.preview.rag import (
     EmbeddingModelConfig,
+    Pinecone,
     RagCorpus,
     RagFile,
     RagResource,
@@ -69,6 +70,14 @@
     collection_name=TEST_WEAVIATE_COLLECTION_NAME,
     api_key=TEST_WEAVIATE_API_KEY_SECRET_VERSION,
 )
+TEST_PINECONE_INDEX_NAME = "test-pinecone-index"
+TEST_PINECONE_API_KEY_SECRET_VERSION = (
+    "projects/test-project/secrets/test-secret/versions/1"
+)
+TEST_PINECONE_CONFIG = Pinecone(
+    index_name=TEST_PINECONE_INDEX_NAME,
+    api_key=TEST_PINECONE_API_KEY_SECRET_VERSION,
+)
 TEST_VERTEX_FEATURE_STORE_RESOURCE_NAME = "test-feature-view-resource-name"
 TEST_GAPIC_RAG_CORPUS = GapicRagCorpus(
     name=TEST_RAG_CORPUS_RESOURCE_NAME,
@@ -106,6 +115,19 @@
         ),
     ),
 )
+TEST_GAPIC_RAG_CORPUS_PINECONE = GapicRagCorpus(
+    name=TEST_RAG_CORPUS_RESOURCE_NAME,
+    display_name=TEST_CORPUS_DISPLAY_NAME,
+    description=TEST_CORPUS_DISCRIPTION,
+    rag_vector_db_config=RagVectorDbConfig(
+        pinecone=RagVectorDbConfig.Pinecone(index_name=TEST_PINECONE_INDEX_NAME),
+        api_auth=api_auth.ApiAuth(
+            api_key_config=api_auth.ApiAuth.ApiKeyConfig(
+                api_key_secret_version=TEST_PINECONE_API_KEY_SECRET_VERSION
+            ),
+        ),
+    ),
+)
 TEST_EMBEDDING_MODEL_CONFIG = EmbeddingModelConfig(
     publisher_model="publishers/google/models/textembedding-gecko",
 )
@@ -130,6 +152,12 @@
     description=TEST_CORPUS_DISCRIPTION,
     vector_db=TEST_VERTEX_FEATURE_STORE_CONFIG,
 )
+TEST_RAG_CORPUS_PINECONE = RagCorpus(
+    name=TEST_RAG_CORPUS_RESOURCE_NAME,
+    display_name=TEST_CORPUS_DISPLAY_NAME,
+    description=TEST_CORPUS_DISCRIPTION,
+    vector_db=TEST_PINECONE_CONFIG,
+)
 TEST_PAGE_TOKEN = "test-page-token"
 
 # RagFiles

tests/unit/vertex_rag/test_rag_data.py

@@ -79,6 +79,21 @@ def create_rag_corpus_mock_vertex_feature_store():
         yield create_rag_corpus_mock_vertex_feature_store
 
 
+@pytest.fixture
+def create_rag_corpus_mock_pinecone():
+    with mock.patch.object(
+        VertexRagDataServiceClient,
+        "create_rag_corpus",
+    ) as create_rag_corpus_mock_pinecone:
+        create_rag_corpus_lro_mock = mock.Mock(ga_operation.Operation)
+        create_rag_corpus_lro_mock.done.return_value = True
+        create_rag_corpus_lro_mock.result.return_value = (
+            tc.TEST_GAPIC_RAG_CORPUS_PINECONE
+        )
+        create_rag_corpus_mock_pinecone.return_value = create_rag_corpus_lro_mock
+        yield create_rag_corpus_mock_pinecone
+
+
 @pytest.fixture
 def list_rag_corpora_pager_mock():
     with mock.patch.object(
@@ -242,6 +257,15 @@ def test_create_corpus_vertex_feature_store_success(self):
 
         rag_corpus_eq(rag_corpus, tc.TEST_RAG_CORPUS_VERTEX_FEATURE_STORE)
 
+    @pytest.mark.usefixtures("create_rag_corpus_mock_pinecone")
+    def test_create_corpus_pinecone_success(self):
+        rag_corpus = rag.create_corpus(
+            display_name=tc.TEST_CORPUS_DISPLAY_NAME,
+            vector_db=tc.TEST_PINECONE_CONFIG,
+        )
+
+        rag_corpus_eq(rag_corpus, tc.TEST_RAG_CORPUS_PINECONE)
+
     @pytest.mark.usefixtures("rag_data_client_mock_exception")
     def test_create_corpus_failure(self):
         with pytest.raises(RuntimeError) as e:

vertexai/preview/rag/__init__.py

@@ -40,6 +40,7 @@
     EmbeddingModelConfig,
     JiraQuery,
     JiraSource,
+    Pinecone,
     RagCorpus,
     RagFile,
     RagResource,
@@ -54,6 +55,7 @@
     "EmbeddingModelConfig",
     "JiraQuery",
     "JiraSource",
+    "Pinecone",
     "RagCorpus",
     "RagFile",
     "RagResource",

vertexai/preview/rag/rag_data.py

@@ -45,6 +45,7 @@
 from vertexai.preview.rag.utils.resources import (
     EmbeddingModelConfig,
     JiraSource,
+    Pinecone,
     RagCorpus,
     RagFile,
     SlackChannelsSource,
@@ -57,7 +58,7 @@ def create_corpus(
     display_name: Optional[str] = None,
     description: Optional[str] = None,
     embedding_model_config: Optional[EmbeddingModelConfig] = None,
-    vector_db: Optional[Union[Weaviate, VertexFeatureStore]] = None,
+    vector_db: Optional[Union[Weaviate, VertexFeatureStore, Pinecone]] = None,
 ) -> RagCorpus:
     """Creates a new RagCorpus resource.
 

vertexai/preview/rag/utils/_gapic_utils.py

@@ -38,6 +38,7 @@
 )
 from vertexai.preview.rag.utils.resources import (
     EmbeddingModelConfig,
+    Pinecone,
     RagCorpus,
     RagFile,
     SlackChannelsSource,
@@ -98,8 +99,8 @@ def convert_gapic_to_embedding_model_config(
 
 def convert_gapic_to_vector_db(
     gapic_vector_db: RagVectorDbConfig,
-) -> Union[Weaviate, VertexFeatureStore]:
-    """Convert Gapic RagVectorDbConfig to Weaviate or VertexFeatureStore."""
+) -> Union[Weaviate, VertexFeatureStore, Pinecone]:
+    """Convert Gapic RagVectorDbConfig to Weaviate, VertexFeatureStore, or Pinecone."""
     if gapic_vector_db.__contains__("weaviate"):
         return Weaviate(
             weaviate_http_endpoint=gapic_vector_db.weaviate.http_endpoint,
@@ -110,6 +111,11 @@ def convert_gapic_to_vector_db(
         return VertexFeatureStore(
             resource_name=gapic_vector_db.vertex_feature_store.feature_view_resource_name,
         )
+    elif gapic_vector_db.__contains__("pinecone"):
+        return Pinecone(
+            index_name=gapic_vector_db.pinecone.index_name,
+            api_key=gapic_vector_db.api_auth.api_key_config.api_key_secret_version,
+        )
     else:
         return None
 
@@ -395,7 +401,7 @@ def set_embedding_model_config(
 
 
 def set_vector_db(
-    vector_db: Union[Weaviate, VertexFeatureStore],
+    vector_db: Union[Weaviate, VertexFeatureStore, Pinecone],
     rag_corpus: GapicRagCorpus,
 ) -> None:
     """Sets the vector db configuration for the rag corpus."""
@@ -423,5 +429,21 @@ def set_vector_db(
                 feature_view_resource_name=resource_name,
             ),
         )
+    elif isinstance(vector_db, Pinecone):
+        index_name = vector_db.index_name
+        api_key = vector_db.api_key
+
+        rag_corpus.rag_vector_db_config = RagVectorDbConfig(
+            pinecone=RagVectorDbConfig.Pinecone(
+                index_name=index_name,
+            ),
+            api_auth=api_auth.ApiAuth(
+                api_key_config=api_auth.ApiAuth.ApiKeyConfig(
+                    api_key_secret_version=api_key
+                ),
+            ),
+        )
     else:
-        raise TypeError("vector_db must be a Weaviate or VertexFeatureStore.")
+        raise TypeError(
+            "vector_db must be a Weaviate, VertexFeatureStore, or Pinecone."
+        )

vertexai/preview/rag/utils/resources.py

@@ -98,6 +98,20 @@ class VertexFeatureStore:
     resource_name: str
 
 
+@dataclasses.dataclass
+class Pinecone:
+    """Pinecone.
+
+    Attributes:
+        index_name: The Pinecone index name.
+        api_key: The SecretManager resource name for the Pinecone DB API token. Format:
+            ``projects/{project}/secrets/{secret}/versions/{version}``
+    """
+
+    index_name: str
+    api_key: str
+
+
 @dataclasses.dataclass
 class RagCorpus:
     """RAG corpus(output only).
@@ -115,7 +129,7 @@ class RagCorpus:
     display_name: Optional[str] = None
     description: Optional[str] = None
     embedding_model_config: Optional[EmbeddingModelConfig] = None
-    vector_db: Optional[Union[Weaviate, VertexFeatureStore]] = None
+    vector_db: Optional[Union[Weaviate, VertexFeatureStore, Pinecone]] = None
 
 
 @dataclasses.dataclass