Train AI agents with reinforcement learning without modifying existing code.
npx skills add https://github.com/sandmark78/workspace --skill agent-lightning-sandmark78
Please help me install this Agent Skill. Skill: agent-lightning Source: https://github.com/sandmark78/workspace/tree/main/skills/agent-lightning Command: npx skills add https://github.com/sandmark78/workspace --skill agent-lightning-sandmark78
Quickly enable reinforcement learning training for AI agents without modifying your existing agent code, speeding experimentation and deployment.
Initialize the library in your project and wrap your agent function with the provided tracing decorator to start RL training without code changes.
High-intent search queries and answers about installing and using this skill.
Reinforcement learning for AI agents without code changes is achieved by initializing the library in your project and applying a tracing decorator to your agent function, enabling rapid experimentation and deployment.
Yes, zero-code reinforcement learning training works with LangChain, AutoGen, and CrewAI frameworks. It integrates directly with these popular agent frameworks or the OpenAI API without requiring any changes to your existing code.
Yes, you can optimize specific agents within a multi-agent system in parallel. Selective optimization allows you to target specific agents within your multi-agent setups, supporting rapid reinforcement learning experimentation across various environments.
Besides reinforcement learning, supported algorithms for AI agent training include automatic prompt optimization and supervised fine-tuning, with ongoing updates planned to expand available optimization techniques.
Yes, you need a Python environment with the agent-lightning library installed and a configured OpenAI API key. These prerequisites are required to run end-to-end reinforcement learning training for your AI agents.
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