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OpenFrame AI

Ask a question about your project

Type a question, send it and read the answer.

Beginner5 stepsWindows

Before you start

  • OpenFrame AI panel is open and says AI Ready.

Steps

  1. Click the Ask or command box at the bottom of the panel.

    The box shows the example Ask or command… e.g. "Open Scene 42." Send is greyed out while the box is empty. You can type up to 2,000 characters.

  2. Type your question, for example List the characters.

    Send turns orange as soon as there is text. Press Enter to send, or Shift+Enter to start a new line in a longer question. Scope decides which part of the project OpenFrame AI uses. Here it is Whole Project. See Choose what OpenFrame AI looks at.

  3. Click Send and wait.

    Your question moves into a dark bubble and the answer bubble reads Writing the answer with a Cancel button. The first question after OpenFrame AI has been idle also shows Getting Offline AI ready on this computer… above your question while it starts. While it works, the Ask box is switched off. A longer job may show a short line saying what step it is on.

  4. Read the answer.

    The answer is plain text in a light bubble. Here it lists Lakshmi as the Lead character, Venkat Rao and Farooq as Supporting characters and Padma as a Minor character. Under the answer is the See sources link. The Save conversation for review button is now ready to use.

  5. Ask a question about numbers, for example How many scenes are in the script?

    Here the Scope is Current Screenplay and the answer says The project contains 36 scenes and names the screenplay it counted. Every answer follows the same layout: the text first, then See sources.

What you get

You have an answer in the panel, with a See sources link to check it.

Watch out for

  • OpenFrame AI answers only from your project. If something is not in the project, it says so instead of making up a fact.
  • If a question fails, your text is put back in the Ask box so you can send it again.
  • A very long first start can take a little time because the language model is loaded into memory.

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