diff --git a/langchain/retrievers/milvus.py b/langchain/retrievers/milvus.py
new file mode 100644
index 00000000..915d61d9
--- /dev/null
+++ b/langchain/retrievers/milvus.py
@@ -0,0 +1,43 @@
+"""Milvus Retriever"""
+from typing import Any, Dict, List, Optional
+
+from langchain.embeddings.base import Embeddings
+from langchain.schema import BaseRetriever, Document
+from langchain.vectorstores.milvus import Milvus
+
+# TODO: Update to MilvusClient + Hybrid Search when available
+
+
+class MilvusRetreiver(BaseRetriever):
+    def __init__(
+        self,
+        embedding_function: Embeddings,
+        collection_name: str = "LangChainCollection",
+        connection_args: Optional[Dict[str, Any]] = None,
+        consistency_level: str = "Session",
+        search_params: Optional[dict] = None,
+    ):
+        self.store = Milvus(
+            embedding_function,
+            collection_name,
+            connection_args,
+            consistency_level,
+        )
+        self.retriever = self.store.as_retriever(search_kwargs={"param": search_params})
+
+    def add_texts(
+        self, texts: List[str], metadatas: Optional[List[dict]] = None
+    ) -> None:
+        """Add text to the Milvus store
+
+        Args:
+            texts (List[str]): The text
+            metadatas (List[dict]): Metadata dicts, must line up with existing store
+        """
+        self.store.add_texts(texts, metadatas)
+
+    def get_relevant_documents(self, query: str) -> List[Document]:
+        return self.retriever.get_relevant_documents(query)
+
+    async def aget_relevant_documents(self, query: str) -> List[Document]:
+        raise NotImplementedError
diff --git a/langchain/retrievers/zilliz.py b/langchain/retrievers/zilliz.py
new file mode 100644
index 00000000..6b39a3a0
--- /dev/null
+++ b/langchain/retrievers/zilliz.py
@@ -0,0 +1,43 @@
+"""Zilliz Retriever"""
+from typing import Any, Dict, List, Optional
+
+from langchain.embeddings.base import Embeddings
+from langchain.schema import BaseRetriever, Document
+from langchain.vectorstores.zilliz import Zilliz
+
+# TODO: Update to ZillizClient + Hybrid Search when available
+
+
+class ZillizRetreiver(BaseRetriever):
+    def __init__(
+        self,
+        embedding_function: Embeddings,
+        collection_name: str = "LangChainCollection",
+        connection_args: Optional[Dict[str, Any]] = None,
+        consistency_level: str = "Session",
+        search_params: Optional[dict] = None,
+    ):
+        self.store = Zilliz(
+            embedding_function,
+            collection_name,
+            connection_args,
+            consistency_level,
+        )
+        self.retriever = self.store.as_retriever(search_kwargs={"param": search_params})
+
+    def add_texts(
+        self, texts: List[str], metadatas: Optional[List[dict]] = None
+    ) -> None:
+        """Add text to the Zilliz store
+
+        Args:
+            texts (List[str]): The text
+            metadatas (List[dict]): Metadata dicts, must line up with existing store
+        """
+        self.store.add_texts(texts, metadatas)
+
+    def get_relevant_documents(self, query: str) -> List[Document]:
+        return self.retriever.get_relevant_documents(query)
+
+    async def aget_relevant_documents(self, query: str) -> List[Document]:
+        raise NotImplementedError