#memory agent

'Step-by-step guide to building a secure, memory-enabled Cipher workflow that dynamically selects an LLM provider and exposes an API for integration. Includes Python helpers to manage keys, generate cipher.yml, store and retrieve memories, and run Cipher in API mode.'

MemAgent introduces a reinforcement learning-based memory agent that allows large language models to process ultra-long documents efficiently, maintaining high accuracy with linear computational costs.