[KongchangAI]
Product

Hermit

An open-source agent adaptation layer framework from Infini-AI-Lab. Without modifying the base model or harness, it carries instructions, skills, memory and tools through a trainable middleware layer, and is optimized through task feedback.

Timeline (last 90 days)

Oct 29

Hermit's design goal is to improve Agent performance without restructuring existing Agent systems.

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Oct 29

Infini-AI-Lab released Hermit.

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Oct 29

Hermit is open-sourced under the Apache-2.0 license.

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Oct 29

Hermit's core mechanism is to train a separate adaptation layer through task feedback, rather than fine-tuning the model itself.

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Oct 29

Hermit's adaptation layer consists of four types of elements: instructions, skills, memory and tools.

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Oct 29

Hermit does not modify the underlying model or the existing harness; instead, it inserts a trainable adaptation layer between the model and the harness.

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Oct 29

Hermit's adaptation layer training signal comes from task execution results (success/failure, scores, environment rewards, etc.) rather than human-written reference answers.

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Oct 29

The original information does not disclose Hermit's specific adaptation-layer training algorithm, data scale or evaluation results.

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Oct 29

Open questions for Hermit's deployment include the degree of coupling between the adaptation layer and a specific harness, whether retraining is needed when transferring across tasks, and the source of training feedback signals.

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Oct 29

Hermit's approach shifts the focus of Agent improvement from the model and framework to an intermediate adaptation layer.

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