Buffer method of ConversationTokenBufferMemory should be able to return messages as string (#7057)

### Description:
`ConversationBufferTokenMemory` should have a simple way of returning
the conversation messages as a string.

Previously to complete this, you would only have the option to return
memory as an array through the buffer method and call
`get_buffer_string` by importing it from `langchain.schema`, or use the
`load_memory_variables` method and key into `self.memory_key`.

### Maintainer
@hwchase17

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>

libs/langchain/langchain/memory/buffer.py

@@ -4,7 +4,7 @@ from pydantic import root_validator
 
 from langchain.memory.chat_memory import BaseChatMemory, BaseMemory
 from langchain.memory.utils import get_prompt_input_key
-from langchain.schema.messages import get_buffer_string
+from langchain.schema.messages import BaseMessage, get_buffer_string
 
 
 class ConversationBufferMemory(BaseChatMemory):
@@ -29,7 +29,7 @@ class ConversationBufferMemory(BaseChatMemory):
         )
 
     @property
-    def buffer_as_messages(self) -> List[Any]:
+    def buffer_as_messages(self) -> List[BaseMessage]:
         """Exposes the buffer as a list of messages in case return_messages is False."""
         return self.chat_memory.messages
 

libs/langchain/langchain/memory/token_buffer.py

@@ -15,8 +15,22 @@ class ConversationTokenBufferMemory(BaseChatMemory):
     max_token_limit: int = 2000
 
     @property
-    def buffer(self) -> List[BaseMessage]:
+    def buffer(self) -> Any:
         """String buffer of memory."""
+        return self.buffer_as_messages if self.return_messages else self.buffer_as_str
+
+    @property
+    def buffer_as_str(self) -> str:
+        """Exposes the buffer as a string in case return_messages is True."""
+        return get_buffer_string(
+            self.chat_memory.messages,
+            human_prefix=self.human_prefix,
+            ai_prefix=self.ai_prefix,
+        )
+
+    @property
+    def buffer_as_messages(self) -> List[BaseMessage]:
+        """Exposes the buffer as a list of messages in case return_messages is False."""
         return self.chat_memory.messages
 
     @property
@@ -29,16 +43,7 @@ class ConversationTokenBufferMemory(BaseChatMemory):
 
     def load_memory_variables(self, inputs: Dict[str, Any]) -> Dict[str, Any]:
         """Return history buffer."""
-        buffer: Any = self.buffer
-        if self.return_messages:
-            final_buffer: Any = buffer
-        else:
-            final_buffer = get_buffer_string(
-                buffer,
-                human_prefix=self.human_prefix,
-                ai_prefix=self.ai_prefix,
-            )
-        return {self.memory_key: final_buffer}
+        return {self.memory_key: self.buffer}
 
     def save_context(self, inputs: Dict[str, Any], outputs: Dict[str, str]) -> None:
         """Save context from this conversation to buffer. Pruned."""