refactor: tests/unittests -> tests/unit; tests/api -> tests/integration

tests/integration/vector_io/test_vector_io.py

@@ -0,0 +1,86 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+import random
+
+import pytest
+
+INLINE_VECTOR_DB_PROVIDERS = [
+    "faiss",
+    # TODO: add sqlite_vec to templates
+    # "sqlite_vec",
+]
+
+
+@pytest.fixture(scope="function")
+def empty_vector_db_registry(llama_stack_client):
+    vector_dbs = [vector_db.identifier for vector_db in llama_stack_client.vector_dbs.list()]
+    for vector_db_id in vector_dbs:
+        llama_stack_client.vector_dbs.unregister(vector_db_id=vector_db_id)
+
+
+@pytest.fixture(scope="function")
+def single_entry_vector_db_registry(llama_stack_client, empty_vector_db_registry, provider_id):
+    vector_db_id = f"test_vector_db_{random.randint(1000, 9999)}"
+    llama_stack_client.vector_dbs.register(
+        vector_db_id=vector_db_id,
+        embedding_model="all-MiniLM-L6-v2",
+        embedding_dimension=384,
+        provider_id=provider_id,
+    )
+    vector_dbs = [vector_db.identifier for vector_db in llama_stack_client.vector_dbs.list()]
+    return vector_dbs
+
+
+@pytest.mark.parametrize("provider_id", INLINE_VECTOR_DB_PROVIDERS)
+def test_vector_db_retrieve(llama_stack_client, embedding_model_id, empty_vector_db_registry, provider_id):
+    # Register a memory bank first
+    vector_db_id = f"test_vector_db_{random.randint(1000, 9999)}"
+    llama_stack_client.vector_dbs.register(
+        vector_db_id=vector_db_id,
+        embedding_model=embedding_model_id,
+        embedding_dimension=384,
+        provider_id=provider_id,
+    )
+
+    # Retrieve the memory bank and validate its properties
+    response = llama_stack_client.vector_dbs.retrieve(vector_db_id=vector_db_id)
+    assert response is not None
+    assert response.identifier == vector_db_id
+    assert response.embedding_model == embedding_model_id
+    assert response.provider_id == provider_id
+    assert response.provider_resource_id == vector_db_id
+
+
+def test_vector_db_list(llama_stack_client, empty_vector_db_registry):
+    vector_dbs_after_register = [vector_db.identifier for vector_db in llama_stack_client.vector_dbs.list()]
+    assert len(vector_dbs_after_register) == 0
+
+
+@pytest.mark.parametrize("provider_id", INLINE_VECTOR_DB_PROVIDERS)
+def test_vector_db_register(llama_stack_client, embedding_model_id, empty_vector_db_registry, provider_id):
+    vector_db_id = f"test_vector_db_{random.randint(1000, 9999)}"
+    llama_stack_client.vector_dbs.register(
+        vector_db_id=vector_db_id,
+        embedding_model=embedding_model_id,
+        embedding_dimension=384,
+        provider_id=provider_id,
+    )
+
+    vector_dbs_after_register = [vector_db.identifier for vector_db in llama_stack_client.vector_dbs.list()]
+    assert vector_dbs_after_register == [vector_db_id]
+
+
+@pytest.mark.parametrize("provider_id", INLINE_VECTOR_DB_PROVIDERS)
+def test_vector_db_unregister(llama_stack_client, single_entry_vector_db_registry, provider_id):
+    vector_dbs = [vector_db.identifier for vector_db in llama_stack_client.vector_dbs.list()]
+    assert len(vector_dbs) == 1
+
+    vector_db_id = vector_dbs[0]
+    llama_stack_client.vector_dbs.unregister(vector_db_id=vector_db_id)
+
+    vector_dbs = [vector_db.identifier for vector_db in llama_stack_client.vector_dbs.list()]
+    assert len(vector_dbs) == 0