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redaccel-to-relax

Migrates RedAccel reinforcement learning algorithms to Relax-compatible modules and interfaces.

71|Updated May 9, 2026
Search Tags:#reinforcement learning#relax#agent environment#training workflow#redaccel#reward function#algorithm migration
One-click install
npx skills add https://github.com/DeepExperience/HyperEyes --skill redaccel-to-relax-deepexperience
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: redaccel-to-relax
Source: https://github.com/DeepExperience/HyperEyes/tree/main/RL/relax-hypereyes/Relax/skills/redaccel-to-relax
Command: npx skills add https://github.com/DeepExperience/HyperEyes --skill redaccel-to-relax-deepexperience

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill reduces the complexity of porting reinforcement learning algorithms between RedAccel and Relax by providing structured migration guidance for incompatible interfaces, components, and training workflows.

Core Features & Use Cases

  • Reward Function Migration: Converts RedAccel reward classes and registry patterns into Relax async reward functions using Sample-based interfaces.
  • Agent and Training Workflow Conversion: Guides migration of tool environments, rollout logic, LLM-as-judge helpers, and launch scripts into Relax-compatible implementations.
  • Use Case: Help an RL engineer migrate a multimodal search agent training pipeline from RedAccel to Relax while preserving reward logic, environment behavior, and distributed training configuration.

Quick Start

Ask the skill to migrate a RedAccel RL algorithm directory to the Relax framework and generate the required reward, environment, rollout, and launch file changes.

Frequently Asked Questions about redaccel-to-relax

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I migrate reinforcement learning algorithms from RedAccel to Relax?▼

Migrating reinforcement learning algorithms from RedAccel to Relax requires converting incompatible training components and interfaces, mapping RedAccel classes and configurations into Relax-compatible modules and Sample-based APIs.

Can I convert RedAccel reward functions to the Relax framework?▼

Yes, RedAccel reward classes and registry patterns can be converted to Relax by mapping them into async reward functions that utilize the Sample-based interfaces.

What's the best way to port a multimodal agent training pipeline to Relax?▼

Porting a multimodal agent training pipeline to Relax involves migrating tool environments, rollout logic, LLM-as-judge helpers, and distributed training launch scripts into Relax-compatible implementations.

Does this RL migration process support distributed training launch scripts?▼

Yes, the RL migration process supports distributed training by converting RedAccel launch scripts into Relax-compatible example workflows while preserving the original training configuration.

Why do RedAccel agent environments need conversion for Relax?▼

RedAccel agent environments need conversion because Relax requires Sample-based APIs and specific compatible modules, making the original RedAccel classes and interfaces incompatible.

What are the limitations of migrating RL training workflows between frameworks?▼

Limitations involve the complexity of preserving original reward logic and environment behavior during migration, requiring careful mapping of RedAccel classes, tools, and configurations to Relax-compatible modules.

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