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behaviors is a Python library for building AI evaluations. It provides model adapters, multi-turn conversations, user and tool policies, and structured conversation records. Use it to sample a model, simulate an interaction, or ask a model to judge another model’s output. You control the messages, tools, and stopping conditions of an interaction. behaviors handles the conversation loop and provides configurable retries and failure recording. behaviors works with fxtr: conversation records can be stored as fxtr entities, returned from steps, and inspected in the experiment viewer. fxtr manages the experiment’s execution, caching, and provenance.

Calling language models

Set up behaviors, run conversations, and judge their outputs in fxtr steps.

Install fxtr

Set up the project that runs and stores your experiments.