Liz is a lightweight framework for building AI agents, inspired by Eliza from AI16Z but rebuilt with a strong focus on developer experience and control. Unlike other agent frameworks that abstract away the complexities, Liz provides direct access to prompts and model interactions, giving developers the power to build exactly what they need.
Liz follows an Express-style architecture, using middleware chains for processing agent interactions. This approach provides a clear, linear flow that developers are already familiar with, making it easy to understand and extend.
We believe the best way to build AI agents is to work closely with the prompts and build a set of composable units that can be strung together to make powerful agentic loops. Our approach is informed by Anthropic's research on constructing reliable AI systems.
Build agents with distinct personalities, capabilities, and interaction styles using a flexible character system.
Process interactions through customizable middleware chains for validation, memory loading, context wrapping, and more.
Built-in Prisma-based memory system for storing and retrieving agent interactions with flexible querying.
Support for multiple LLM providers through a unified interface, with structured outputs and streaming capabilities.
Liz is perfect for developers who: