SelMem

SelMem is a Rust-based software providing a selective reconstructive memory system designed to augment large language models (LLMs) by sculpting a path-dependent memory that shapes future outputs. It offers configurable memory persistence and runtime options, enabling unique identity formation and divergence in LLM responses beyond standard token prediction.