Mac (Apple Silicon)
Requires Apple M1 or newer. Open the downloaded DMG and launch TritonAI Installer.
Download for MacApple Silicon · DMGBuild with TritonAI
Download and open the installer, get a TritonAI access key if you need one, then finish setup and try your first prompt.
Already opened the installer? Get your key. For another client or your own code, see other setup options.
Choose the stable installer for your computer. It guides you through access setup and installs TritonAI Harness. You can download it before requesting a key.
TritonAI Harness is the desktop workspace. TritonAI Installer sets it up on your computer and checks your access to campus models.
Requires Apple M1 or newer. Open the downloaded DMG and launch TritonAI Installer.
Download for MacApple Silicon · DMGRequires an x64 processor. Run the downloaded setup file, then open TritonAI Installer. Windows may show a SmartScreen warning.
Download for Windowsx64 · Setup EXEWhen the installer asks for your TritonAI access key, use your existing key or follow the next step to request one. Installation completes after your key is checked.
Already have a TritonAI key? Continue to finish setup. If you need one, select Don’t have a key? in the installer to open the access guidance, or use the Kuali Build form below. If the installer sent you to this page, this is the next step.
Describe your intended use and choose the access you need. Some requests require approval.
The email contains a one-time link to view and copy your key. The key itself is not in the email. Keep the key private and save it securely before leaving that page.
Return to TritonAI Installer with your key, then follow the next step to finish setup.
UC-hosted models carry no recharge for campus administrative work. Cloud models and sponsored research require a departmental or project chartstring. Recharge is the campus term for internal billing to a chartstring.
Let the installer finish setup, then launch TritonAI Harness and try a prompt that contains no sensitive information.
Paste your key into TritonAI Installer and choose Check access & install. Keep it open until setup finishes.
Launch the app and choose a model available to your key. The managed default is GLM 5.3 Flash. TritonAI Harness starts with Auto when there’s no saved override or remembered choice. Before sending a request, select Supervised in the message composer so file changes and write tools pause for approval.
Ask “Help me outline a meeting agenda.” Confirm you receive a response, then review it.
Start with Essentials in the standalone course, then create and check a feedback summary using the fictional practice kit.
If your key is rejected or models do not appear, remove extra spaces around your key. Keep the key private; support will never ask for your secret key.
Email tritonai@ucsd.edu with your operating system and error details. Never include the secret key in email.
For an existing TritonAI Harness installation, open Settings > About > Check for Updates. Version 0.4.1 is the current stable release. Stable and nightly installations use separate update tracks. The guided installer above is the first-time setup and runtime repair path.
Computer use starts off. To enable it, open Settings > General and follow the readiness instructions. On macOS, grant Accessibility and Screen Recording permissions, then restart the TritonAI Harness when prompted. In this stable release, computer use requires the Codex provider on a local desktop backend. Screenshots may be included in model requests; use approved data and review the TritonAI Harness privacy statement.
Using another client or your own code? Request a Gateway key, then configure your chosen client. You do not need TritonAI Installer for this path.
Claude Code and Codex are supported alternatives. Follow the client setup guides for the endpoint and settings your client needs.
https://tritonai-api.ucsd.edu/v1api-glm-5.3Use the OpenAI Python SDK.
from openai import OpenAI
client = OpenAI(
base_url="https://tritonai-api.ucsd.edu/v1",
api_key="YOUR_KEY"
)
resp = client.chat.completions.create(
model="api-glm-5.3",
messages=[{"role":"user","content":"Hi"}]
)
Follow the API quickstart for Python and cURL examples. See TritonAI model catalog for available routes.