Workplace Assistant is a multi-step agentic tool-use training environment that tests a model’s ability to execute business tasks in a simulated workplace setting.
Goal: Understand the training environment and how tasks are structured and verified.
Time: ~10 minutes (read)
In this section, you will learn:
For each task, the model must:
The model has up to 6 tool calling steps to accomplish each task.
Each task is a natural language request that the model must complete using the available tools. All tasks share the same set of tools that allow the model to retrieve more information or perform actions. Each task instance uses isolated database instances so actions from different rollouts don’t interfere.
All tasks are available in the Workplace Assistant HuggingFace dataset.
User query: “Send an email to john.smith@atlas.com with the subject ‘Team Meeting’ and body ‘Let’s meet tomorrow at 2pm to discuss the project.’”
Expected tool call:
The tool adds a new email to the emails database.
The environment is implemented as a FastAPI-based resources server that executes tools and verification. It uses state-matching verification: instead of requiring exact tool sequences, it compares final database states.
Now that you understand the Workplace Assistant environment, learn how to configure NeMo Gym for training:
Continue to Gym Configuration →