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Use Prompt Studio to turn a support ticket into a category, priority, and short summary. You will finish with a saved draft and a recorded model response that you can reopen later.

Before you start

You need a Traceport account with permission to create prompts and run models. Connect a provider integration and make sure a Traceport API key has access to a chat model. Running the example uses the selected provider and incurs its normal model usage cost.

Create and run your prompt

1

Create a prompt

Open Prompts and click New prompt.Set Name to Support ticket triage and leave Slug prefilled. If you already created this example, open that prompt to continue.Paste the following into System Prompt (optional), then click Create Prompt:
System message
The prompt opens in Build as a draft. Studio assigns its final unique slug when you create it. For API calls, return to Prompts and use Copy prompt slug on its row to copy the saved value.
2

Add the ticket variable

Click Add message. Keep the new message’s role set to User and paste:
User message
{{ticket_text}} marks the part you will replace for each run. Build detects it automatically and adds a required string input under Test inputs.
3

Choose a model and save

In Single run, open Model and API key and select an available API key, provider, and chat model.Click Use as default to store that model as the version’s default. Leave Model parameters blank for this first run, then click Save changes.Choosing a model for a run and saving a model default are separate actions. Use as default updates the draft; Save changes persists it.
4

Supply a ticket and run

Paste this synthetic ticket into ticket_text under Test inputs:
Ticket input
Click Run prompt. Test inputs apply to this run; they do not replace the variable in your saved message.
5

Inspect the response

When the run completes, check Output. For this ticket, look for account as the category and high as the priority, with a one-sentence summary. The JSON content should resemble:
Example response content
Your model may use different wording or add formatting, including Markdown code fences. Completed means the model call finished; it does not certify that the response follows your instructions.Review Duration, Input tokens, Output tokens, and Cost beneath the output. A dash for cost means no cost was recorded for that run.Expand Recorded inputs to see the ticket and the messages sent to the model. Use Open trace to inspect the linked request.
Support ticket triage in Build, with system and user messages on the left and a completed account-category, high-priority response on the right.

A recorded support-ticket response in Build. This captured version is read-only because it was later evaluated on a dataset. Your output and usage may differ.

Try another ticket

Click Use inputs for a new run, replace ticket_text with the following, and click Run prompt again:
Another ticket
Look for the category billing and priority normal. The same saved prompt now handles a different ticket without editing its messages. You can reopen either response from Previous runs. See Build prompts for the difference between viewing a recorded run and reusing its inputs.

If the run does not work

Continue with the same example

You now have a saved draft and a recorded response. Saving a draft does not publish it to production. Continue with Build prompts to change variable settings, test unsaved edits, compare models, and create another draft. Then import the eight-ticket dataset, create a rule, and run an evaluation. You can download the sample ticket CSV directly.

Reusable example

This reference contains the messages, variable definition, and first ticket used in this guide. Copy the relevant values into Build; this is not an API request or an import format. The slug identifies the recorded example; use your own saved slug for API calls. The reference output describes the intended answer, not an exact model-response guarantee.
Support-ticket example