verifiers v1: Decomposing Tasksets and Harnesses for Agentic RL & Evaluations

Verifiers 0.2.0 introduces a revamped core designed to support composable tasksets and harnesses, facilitating modern agentic training and evaluations. This update allows for more sophisticated evaluations that go beyond simple prompts by incorporating coding agents equipped with tools and custom logic. The new architecture consists of a taskset, harness, and runtime, enabling the execution of arbitrary tasks essential for current evaluations and training. The core features include composable tasksets that can operate with any compatible harness, swappable runtimes for flexible deployment, and first-class branching for non-linear rollouts. Additionally, verifiers v1 introduces an interception server to manage requests between agents and inference servers, supporting multiple dialects to ensure compatibility with different agent languages. With the transition to verifiers.v1, the legacy codebase is deprecated, and emphasis is placed on the new abstraction for scalability and efficiency in training, leading towards a full 1.0.0 release that promises multi-agent environments and comprehensive support for various environment frameworks.

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