diff --git a/llama_stack/providers/remote/vector_io/qdrant/__init__.py b/llama_stack/providers/remote/vector_io/qdrant/__init__.py
index 54605fcf9..c584e29ef 100644
--- a/llama_stack/providers/remote/vector_io/qdrant/__init__.py
+++ b/llama_stack/providers/remote/vector_io/qdrant/__init__.py
@@ -12,8 +12,8 @@ from .config import QdrantConfig
 
 
 async def get_adapter_impl(config: QdrantConfig, deps: Dict[Api, ProviderSpec]):
-    from .qdrant import QdrantVectorMemoryAdapter
+    from .qdrant import QdrantVectorDBAdapter
 
-    impl = QdrantVectorMemoryAdapter(config, deps[Api.inference])
+    impl = QdrantVectorDBAdapter(config, deps[Api.inference])
     await impl.initialize()
     return impl
diff --git a/llama_stack/providers/remote/vector_io/qdrant/qdrant.py b/llama_stack/providers/remote/vector_io/qdrant/qdrant.py
index 719070528..e7ad136eb 100644
--- a/llama_stack/providers/remote/vector_io/qdrant/qdrant.py
+++ b/llama_stack/providers/remote/vector_io/qdrant/qdrant.py
@@ -55,7 +55,7 @@ class QdrantIndex(EmbeddingIndex):
 
         points = []
         for i, (chunk, embedding) in enumerate(zip(chunks, embeddings)):
-            chunk_id = f"{chunk.document_id}:chunk-{i}"
+            chunk_id = f"{chunk.metadata['document_id']}:chunk-{i}"
             points.append(
                 PointStruct(
                     id=convert_id(chunk_id),
@@ -93,6 +93,9 @@ class QdrantIndex(EmbeddingIndex):
 
         return QueryChunksResponse(chunks=chunks, scores=scores)
 
+    async def delete(self):
+        await self.client.delete_collection(collection_name=self.collection_name)
+
 
 class QdrantVectorDBAdapter(VectorIO, VectorDBsProtocolPrivate):
     def __init__(self, config: QdrantConfig, inference_api: Api.inference) -> None: