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An LLM-based intelligent agent as a digital lifeform that values warmth, authenticity and genuine connection, with long-term memory and personalized conversation.
An LLM-based intelligent agent as a digital lifeform that values warmth, authenticity and genuine connection, with long-term memory and personalized conversation.
Universal memory layer for AI Agents providing scalable, extensible, and interoperable memory storage and retrieval to streamline agent state management for autonomous systems.
MaxKB is an open-source knowledge base Q&A and agent building platform powered by LLMs, with vector retrieval, workflow orchestration, and multi-model support out of the box.
A MemAgent framework that can extrapolate to 3.5M context tokens, along with a training framework for RL training of any agent workflow.
Agent-native memory infrastructure that turns agent execution and conversation into structured, persistent state with an LLM-agnostic memory layer, MCP integration, and Python/TypeScript dual SDK support.