What is Conversation Buffer Memory?
Conversation Buffer Memory is a LangChain memory class that maintains a complete, unmodified history of all messages exchanged between the user and the AI agent during a conversation. It stores both user inputs and AI responses in chronological order, providing full conversational context without any summarization or truncation, making it the simplest form of conversation memory.
This memory type is ideal for short to medium-length conversations where maintaining complete fidelity to what was said is important. It allows the agent to reference any part of the conversation history and ensures no information is lost through summarization. The straightforward implementation makes it easy to understand, debug, and modify, and it guarantees that the agent has access to the exact wording and sequence of all previous exchanges.
However, Conversation Buffer Memory has a significant limitation: it grows unbounded as the conversation continues. Long conversations will eventually exceed the model's context window, at which point the memory either needs to be truncated (losing early context) or the conversation cannot proceed. For applications requiring extended interactions, developers typically use Conversation Token Buffer Memory (which enforces token limits) or Conversation Summary Memory (which compresses older context) instead.