feat(client): migrate MilvusClient to AsyncMilvusClient

The commit makes the follwing changes.
-  Import statements updated: MilvusClient → AsyncMilvusClient
-  Removed asyncio.to_thread() wrappers: All Milvus operations now use native async/await
-  Test compatibility: Mock objects and fixtures updated to work with AsyncMilvusClient

Signed-off-by: Mustafa Elbehery <melbeher@redhat.com>

tests/unit/providers/vector_io/conftest.py

@@ -9,20 +9,26 @@ from unittest.mock import AsyncMock, MagicMock, patch
 
 import numpy as np
 import pytest
+from chromadb import PersistentClient
+from pymilvus import AsyncMilvusClient, connections
 
+from llama_stack.apis.vector_dbs import VectorDB
 from llama_stack.apis.vector_io import Chunk, ChunkMetadata, QueryChunksResponse
 from llama_stack.apis.vector_stores import VectorStore
 from llama_stack.core.storage.datatypes import KVStoreReference, SqliteKVStoreConfig
 from llama_stack.providers.inline.vector_io.faiss.config import FaissVectorIOConfig
 from llama_stack.providers.inline.vector_io.faiss.faiss import FaissIndex, FaissVectorIOAdapter
+from llama_stack.providers.inline.vector_io.milvus.config import MilvusVectorIOConfig
 from llama_stack.providers.inline.vector_io.sqlite_vec import SQLiteVectorIOConfig
 from llama_stack.providers.inline.vector_io.sqlite_vec.sqlite_vec import SQLiteVecIndex, SQLiteVecVectorIOAdapter
+from llama_stack.providers.remote.vector_io.milvus.milvus import MilvusIndex, MilvusVectorIOAdapter
 from llama_stack.providers.remote.vector_io.pgvector.config import PGVectorVectorIOConfig
 from llama_stack.providers.remote.vector_io.pgvector.pgvector import PGVectorIndex, PGVectorVectorIOAdapter
 from llama_stack.providers.utils.kvstore import register_kvstore_backends
 
 EMBEDDING_DIMENSION = 768
 COLLECTION_PREFIX = "test_collection"
+MILVUS_ALIAS = "test_milvus"
 
 
 @pytest.fixture(params=["sqlite_vec", "faiss", "pgvector"])
@@ -141,7 +147,7 @@ async def sqlite_vec_vec_index(embedding_dimension, tmp_path_factory):
     await index.initialize()
     index.db_path = db_path
     yield index
-    index.delete()
+    await index.delete()
 
 
 @pytest.fixture
@@ -170,6 +176,48 @@ async def sqlite_vec_adapter(sqlite_vec_db_path, unique_kvstore_config, mock_inf
     await adapter.shutdown()
 
 
+@pytest.fixture(scope="session")
+def milvus_vec_db_path(tmp_path_factory):
+    db_path = str(tmp_path_factory.getbasetemp() / "test_milvus.db")
+    return db_path
+
+
+@pytest.fixture
+async def milvus_vec_index(milvus_vec_db_path, embedding_dimension):
+    client = AsyncMilvusClient(milvus_vec_db_path)
+    name = f"{COLLECTION_PREFIX}_{np.random.randint(1e6)}"
+    connections.connect(alias=MILVUS_ALIAS, uri=milvus_vec_db_path)
+    index = MilvusIndex(client, name, consistency_level="Strong")
+    index.db_path = milvus_vec_db_path
+    yield index
+    # Proper cleanup: close the async client
+    await client.close()
+
+
+@pytest.fixture
+async def milvus_vec_adapter(milvus_vec_db_path, mock_inference_api):
+    config = MilvusVectorIOConfig(
+        db_path=milvus_vec_db_path,
+        kvstore=SqliteKVStoreConfig(),
+    )
+    adapter = MilvusVectorIOAdapter(
+        config=config,
+        inference_api=mock_inference_api,
+        files_api=None,
+    )
+    await adapter.initialize()
+    await adapter.register_vector_db(
+        VectorDB(
+            identifier=adapter.metadata_collection_name,
+            provider_id="test_provider",
+            embedding_model="test_model",
+            embedding_dimension=128,
+        )
+    )
+    yield adapter
+    await adapter.shutdown()
+
+
 @pytest.fixture
 def faiss_vec_db_path(tmp_path_factory):
     db_path = str(tmp_path_factory.getbasetemp() / "test_faiss.db")