InterLab User Guide#

InterLab is a research-focused toolkit to facilitate study and experimentation in the realm of agent interactions, particularly those based on Language Learning Models (LLMs). Our primary objective is to simplify the process of crafting, deploying, and inspecting complex and structured queries within the context of agent interactions, while also providing robust support for interaction logging, UI and visualization. While we maintain a broad scope and plan to include game theoretic agents and a variety of scenarios, our main emphasis lies in the sphere of LLM interactions.

Note: This documentation is currently not covering all features and functions of InterLab and is in the process of being revised and expanded. For introduction to Interlab, we recommend to also look at example notebooks that demonstrate the main functions of InterLab and how to create a simple experiment. You can also refer to the API docs, as well as to the source code of the base classes for implementation details.

Interlab is developed at the Alignment of Complex Systems research group at Charles University.