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Navigator n2 is a computer-use model that looks at desktop screenshots and predicts tool calls — mouse and keyboard actions, or bash commands — to be executed in desktop environments. Daytona provides sandboxes with full desktop environments where the predicted actions can be executed. This guide walks you through how to set up a simple agent loop that wires the two together to set up a complete computer-use agent stack.
To try n2 without building anything, open the Playground. To drive your own Mac, install Yutori MCP — it ships a local loop already wired up.

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Components

The loop is N2ComputerAgent from the Python SDK: it owns the turns, the message history, the screenshot window, and the coordinate math. Everything specific to Daytona lives in one adapter class, DaytonaComputer. Both are in examples/navigator_n2_daytona.py, along with a main that creates the sandbox, runs the agent, and deletes the sandbox. n2 typically answers with one computer_batch call, which chains several actions against a single screenshot. N2ComputerAgent runs whatever comes back and returns a fresh screenshot to the model — plus the command output for bash.

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Prerequisites

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Run it

Download the script from the SDK repository and run it with a task:
Each turn prints the model’s own text and the call it made:
The loop ends when n2 returns a message with no tool calls. The sandbox is deleted in a finally block, so it does not outlive the run even when the run fails.

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Adapting it with a coding agent

Point your coding agent to the script, and describe what needs to change for your setup.

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Adapter details

DaytonaComputer is the class N2ComputerAgent calls to observe and act. Most methods pass through to Daytona unchanged. The exceptions are below:
  • Sandbox lifecycle — wait for computer_use.start() to finish before interacting with the sandbox, and always delete it in a finally block to stop billing.
  • Coordinates — n2 predicts them in a normalized 1000×1000 space. N2ComputerAgent rescales them to the desktop’s native pixel size before calling the adapter, so the adapter does not do any conversions.
  • Typing — keyboard.type fails on control characters and silently truncates long strings, so send \n and \t as key presses and chunk the rest.
  • Scrolling — N2ComputerAgent passes a pixel distance, one notch of the model’s amount being a tenth of the screen; Daytona wants wheel notches, so the adapter converts back.
  • bash results — the command’s output, with the exit code appended on failure. N2ComputerAgent caps each result at 8,000 characters so a large cat cannot push the request over the 10 MB limit.
bash promises a working directory that persists across calls, but every exec is a fresh process, so a cd would be forgotten by the next command. The adapter honors the contract: each command prints its final $PWD on a sentinel line, and the next command starts there through exec’s cwd. run_in_background detaches the command with nohup and returns its pid and output file.

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Knowing when to stop

Without a limit, a loop will keep going on a task it cannot finish. The StepLimit callback in the script caps the number of model turns: N2ComputerAgent calls its on_run_continue before each turn and stops when it returns False. Execution errors are not fatal to the run. A batch stops at the first action that fails, and the tool result tells the model which action failed along with a screenshot of the resulting state; a bash call that cannot run (a timeout, for example) comes back as an [ERROR] bash failed: ... result, and a nonzero exit code is simply part of the output. In every case the model sees what happened and routes around it. For anything unattended on a machine that is not disposable, add an action_confirmation_callback. N2ComputerAgent calls it before every action except screenshot, wait, mouse_move, and scroll, and skips the call if it returns False. The sandbox here is disposable, so the script does not confirm anything. On a harness driving a real machine, keep shell confirmation mandatory.

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Going further

  • Pick a snapshot with the apps you need. daytonaio/sandbox:0.6.0 is a bare XFCE desktop at 1024×768. Build your own to give the model a browser, an editor, or a dataset.
  • Watch the run. (await sandbox.get_preview_link(6080)).url is a noVNC view of the desktop, which is the fastest way to see what a failing run is doing.
  • Send the whole history. N2ComputerAgent keeps every turn and strips only the images outside the two newest image-bearing messages, which is what the server would drop anyway. Trimming messages yourself risks the model repeating work it has already done.

Navigator n2

The model reference — tools, actions, coordinates, and request fields.