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

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### 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>
This commit is contained in:
Nikhil Kumar 2023-08-10 21:17:22 -04:00 committed by GitHub
parent 57dd4daa9a
commit 6abb2c2c08
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2 changed files with 18 additions and 13 deletions
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4
libs/langchain/langchain/memory/buffer.py
View File

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

27
libs/langchain/langchain/memory/token_buffer.py
View File

@ -15,8 +15,22 @@ class ConversationTokenBufferMemory(BaseChatMemory):
max_token_limit: int = 2000 max_token_limit: int = 2000
@property @property
def buffer(self) -> List[BaseMessage]: def buffer(self) -> Any:
"""String buffer of memory.""" """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 return self.chat_memory.messages
@property @property
@ -29,16 +43,7 @@ class ConversationTokenBufferMemory(BaseChatMemory):
def load_memory_variables(self, inputs: Dict[str, Any]) -> Dict[str, Any]: def load_memory_variables(self, inputs: Dict[str, Any]) -> Dict[str, Any]:
"""Return history buffer.""" """Return history buffer."""
buffer: Any = self.buffer return {self.memory_key: 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}
def save_context(self, inputs: Dict[str, Any], outputs: Dict[str, str]) -> None: def save_context(self, inputs: Dict[str, Any], outputs: Dict[str, str]) -> None:
"""Save context from this conversation to buffer. Pruned.""" """Save context from this conversation to buffer. Pruned."""