In this tutorial, we extend our previous work on building a custom Bash computer-use agent using NVIDIA Nemotron by teaching it to operate the LangGraph Platform CLI safely. Instead of manual commands, this new agent will learn to execute tasks like starting servers and generating Dockerfiles via a human-in-the-loop interface.
We utilize Synthetic Data Generation (SDG) coupled with Reinforcement Learning with Verifiable Rewards (RLVR) to ensure efficient and safe training. SDG produces high-quality training examples from a few seed commands, while RLVR reinforces valid command generation, addressing the data scarcity and safety-accuracy challenges typical of specialized CLI tools.
Optimal results are achieved with Group Relative Policy Optimization (GRPO), which enhances learning efficiency. A human approval loop ensures safety before command execution. This scalable model can adapt to various CLI tools, promising rapid deployment of safe AI-driven agents in enterprise environments.
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