diff --git a/langchain/memory/vectorstore.py b/langchain/memory/vectorstore.py
index d5c40f26b99..60e0ae7acc2 100644
--- a/langchain/memory/vectorstore.py
+++ b/langchain/memory/vectorstore.py
@@ -1,6 +1,6 @@
 """Class for a VectorStore-backed memory object."""
 
-from typing import Any, Dict, List, Optional, Union
+from typing import Any, Dict, List, Optional, Sequence, Union
 
 from pydantic import Field
 
@@ -25,6 +25,9 @@ class VectorStoreRetrieverMemory(BaseMemory):
     return_docs: bool = False
     """Whether or not to return the result of querying the database directly."""
 
+    exclude_input_keys: Sequence[str] = Field(default_factory=tuple)
+    """Input keys to exclude in addition to memory key when constructing the document"""
+
     @property
     def memory_variables(self) -> List[str]:
         """The list of keys emitted from the load_memory_variables method."""
@@ -55,10 +58,13 @@ class VectorStoreRetrieverMemory(BaseMemory):
     ) -> List[Document]:
         """Format context from this conversation to buffer."""
         # Each document should only include the current turn, not the chat history
-        filtered_inputs = {k: v for k, v in inputs.items() if k != self.memory_key}
+        exclude = set(self.exclude_input_keys)
+        exclude.add(self.memory_key)
+        filtered_inputs = {k: v for k, v in inputs.items() if k not in exclude}
         texts = [
             f"{k}: {v}"
             for k, v in list(filtered_inputs.items()) + list(outputs.items())
+            if k not in exclude
         ]
         page_content = "\n".join(texts)
         return [Document(page_content=page_content)]