What is Conversation Token Buffer Memory?
Conversation Token Buffer Memory is an enhanced buffer memory implementation that tracks the token count of stored conversation history and automatically truncates older messages to stay within a specified token limit. Unlike basic conversation buffer memory which stores all messages regardless of size, this memory type actively manages its token budget to ensure the conversation history fits within the model's context window constraints.
The system maintains a running count of tokens used by the stored conversation and removes the oldest messages when adding new exchanges would exceed the configured limit. This ensures that the memory never consumes more than a predetermined portion of the available context window, leaving room for the current query, retrieved information, system prompts, and response generation. Some implementations may use more sophisticated strategies than simple FIFO truncation, such as preserving particularly important messages.
This memory type provides a practical solution for production conversational agents that need to handle extended interactions without manual context management. By automatically enforcing token limits, it prevents context overflow errors while maintaining as much recent conversation history as possible within the budget. The token limit can be tuned based on the model's capabilities and the application's needs, balancing between context richness and leaving sufficient space for other prompt components.