Automate AI agent training setup and optimization with the Agent Lightning framework.
npx skills add https://github.com/rkz91/coco --skill agent-lightning
Please help me install this Agent Skill. Skill: agent-lightning Source: https://github.com/rkz91/coco/tree/main/skills/agent-lightning Command: npx skills add https://github.com/rkz91/coco --skill agent-lightning
Train and optimize AI agents using the Agent Lightning framework to streamline training, tracing, resource management, and reward design across multi-agent pipelines.
Install the package, configure a minimal trainer with a simple store, and run a basic training loop.
High-intent search queries and answers about installing and using this skill.
To set up multi-agent pipelines for AI training and tracing, configure a trainer with LightningStore as the central tracing hub, then execute a basic training loop to automate scalable agent training and resource management.
The best way to instrument agent code for observability and reward signals is to integrate emit_xxx calls directly into your pipeline, enabling detailed logging and evaluation for reinforcement learning workflows.
Yes, you can use GRPO and PPO algorithms for automatic prompt optimization in multi-agent systems by configuring the framework adapters to support both reinforcement learning and APO workflows.
LightningStore supports scalable agent training by acting as a central tracing store for architecture flow, capturing instrumentation data from emit_xxx calls to ensure comprehensive observability and reward signal tracking.
Yes, you need modular framework adapters to run reinforcement learning and APO workflows, as these adapters ensure proper integration with configurable runners, algorithms, and stores for end-to-end trainer customization.
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