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Bruno AI understands the context of your open request or collection and can generate a complete working App for you. You don’t need to write a single line of HTML or JavaScript. This works at both the request level and the collection level. Bruno knows your endpoints, parameters, and variable names, so the generated App is ready to run. It is not just a generic template.
Bruno AI requires a provider key to be configured. See the AI configuration guide to connect your own OpenAI, Anthropic, or other BYOK provider before getting started.

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Request-level App with AI

A request-level App is scoped to a single request. The AI reads your request’s URL, method, body, params, and headers to generate an App that interacts with that specific endpoint.

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How to generate

  1. Enable App Mode from request settings to get App tab visible.
  2. Click the star (✦) icon in the code editor toolbar. A prompt popup appears.
  3. Describe the App you want.
ai-prompt
  1. Click Apply to insert the code into the editor.
  2. Click Preview to render the App in the sandbox and verify the output.
generated-app

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Collection-level App with AI

A collection-level App can see every request in your collection. The AI uses this full context to generate dashboards, workflow runners, and multi-step UIs that chain your requests together.

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How to generate

  1. In the collection sidebar, right-click a collection or folder and choose New App.
Creating a new collection-level App
  1. The dialog box will open, enter a name for the App and click on the Create button. A new editor tab opens with a blank App.
  2. In the code editor, click the star (✦) icon. The AI prompt popup appears. Describe the App you want — for example:
    • “Build a dashboard that lists all requests and lets me run them one by one.”
    • “Create a login-then-fetch-user workflow: log in, store the token, then load the user profile.”
    • “Run all GET requests in the collection and show a pass/fail status for each.”
AI prompt popup in the collection App editor
  1. Bruno AI generates the App code using the names, methods, and paths of every request it can see in the collection. Click Apply to insert the code into the editor.
Applying AI-generated code to the collection App editor
  1. Click Preview to render the App in the sandbox and see the output.
AI-generated collection dashboard rendered in the App preview

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Tips for better results

  • Be specific about the UI. “A form with Email and Password inputs, a Login button, and a status message” gives better output than “a login form”.
  • Mention what to do with the response. “Display the token field from the response” is more precise than “show the result”.
  • For collection Apps, name your requests clearly. The AI uses request names as context - Login, Get Orders, Create User produces better output than req1, req2, req3.
  • Iterate. Accept the first draft, preview it, then re-prompt with refinements: “Add error handling for non-200 responses” or “Style it with Tailwind from a CDN”.