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About NVIDIA NeMo Studio

Note

Studio is still in early development. Many features are missing or should be expected to change.

NeMo Studio is the web app for AI development with NVIDIA NeMo Platform. It provides a workspace-oriented UI for managing local platform resources, reviewing agents, running agent optimization workflows, monitoring agent telemetry, and working with datasets, jobs, and secrets.


Getting Started

NeMo Studio is included with the platform. Follow the Setup guide to start NeMo Platform, then access Studio at /studio on your running server.

Features

Agents

Use the Studio Agents area to review platform-managed NeMo Agent Toolkit workflows, inspect agent details, deploy agents, open a chat session against a running deployment, and clean up deployments that are no longer needed.

For the full workflow, see Studio Agents.

Suggestions

Use Agents > Suggestions to review optimizer suggestions for deployed agents. Studio groups suggestions by workspace or agent and lets you filter by type, priority, scope, and agent.

For the full workflow, see Studio Suggestions.

Monitor

Use Agents > Monitor to inspect agent telemetry stored by the platform, including recent inference logs and token usage summaries.

For the full workflow, see Studio Monitor.

Workspaces

Keep models and data organized in dedicated workspaces.

Filesets

Use Filesets to organize files by purpose, which determines which metadata fields are available. Purpose is chosen at creation time and can't be changed afterward.

Purpose Use for
Generic Default. Files that don't fit the Dataset or Model categories. Doesn't add purpose-specific metadata fields.
Dataset Training and evaluation data. Enables dataset-specific metadata, including schema information. Use built-in tools to transform data schemas with LLM assistance or create train/test splits.
Model Model weights and checkpoints. Enables model-specific metadata, including tool-calling and model configuration fields.

Supported file formats: JSON (.json), JSONL (.jsonl), CSV (.csv), and Parquet (.parquet). PDF, image, and other binary formats are not currently supported.

You can upload any file type into a fileset. However, each service supports specific input file types:

Service Supported File Types
Data Designer .json, .jsonl, .csv, .parquet

Jobs

Track and manage all platform jobs from a single view. The Jobs page aggregates jobs across enabled capabilities, such as Data Designer, so you can monitor progress, view logs, download artifacts, and cancel jobs in one place.

Navigate to Jobs in the workspace sidebar to see all jobs in the current workspace.

Search and filter — Find jobs by name, filter by status, or narrow results by creation or update date range.

Status tracking — Each job displays its current status:

Status Description
Created Job has been created but not yet scheduled
Pending Job is queued and waiting for resources
Active Job is currently running
Completed Job finished successfully
Error Job encountered an error
Cancelled Job was cancelled by a user
Cancelling Cancellation is in progress
Paused Job execution is paused
Pausing Job is transitioning to paused
Resuming Paused job is restarting

Service routing — Clicking a job navigates to its service-specific detail view when one exists. Jobs from services that aren't enabled fall back to the generic job detail view.

Cancelling a job — Active or pending jobs can be cancelled from the job list or the detail page. Cancelling a job permanently stops it and cannot be undone.

Secrets

Store API keys and credentials to securely connect with external providers. See manage-secrets for details.