Infini-AI-Lab has released Hermit, an open-source adapter framework designed for AI agents. The framework lets developers keep an agent’s model and core program frozen while training an external adapter, allowing agents such as Codex and Claude Code to take on new tasks without fine-tuning. The first release, v0.1.0, went out on Oct. 25, 2026. Hermit uses a reinforcement learning-style training loop, and its adapters can include instructions, skills, memory, tools, and executable code. In the current version, the framework offers five adapter evolution methods, including GEPA, SkillOpt, and MetaWorld Model. The team reported performance gains on benchmarks including OfficeQA and CL-Bench. Carnegie Mellon University postdoctoral researcher Haizhong Zheng announced the release on X on Oct. 27, according to the Techub summary citing MarkTechPost.
Infini-AI-Lab has released Hermit, an open-source adapter framework for AI agents. The framework allows developers to freeze an agent model and its core program while training an external adapter, so agents such as Codex or Claude Code can handle new tasks without fine-tuning.
The first version, v0.1.0, was released on Oct. 25, 2026. Hermit uses a reinforcement learning-style training loop, and the adapter can include instructions, skills, memory, tools, and executable code.
The current release includes five adapter evolution methods, including GEPA, SkillOpt, and MetaWorld Model. The team reported performance improvements on benchmarks including OfficeQA and CL-Bench.
Haizhong Zheng, a postdoctoral researcher at Carnegie Mellon University, announced the release on X on Oct. 27. The item was cited by MarkTechPost in the Techub summary.
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