OpenFn / OpenFn/apollo

Ask user follow-up questions

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Dominant language
Jupyter Notebook
Stars
5
Forks
10
Avg merge
2d 20h
Merged PRs (30d)
17

Description

In our one-shot tests in particular, it isn't clear if we're expecting the assistant to ask the user clarifying questions, make reasonable guesses about missing information, or add in placeholder code. Whichever we pick, it will be the wrong choice in many situations.

Benefits:

  • If there was more back-and-forth interaction with the user, the assistant could adapt to the level of detailed expected in each scenario. The assistant could generate forms and buttons, for filling in details or click "decide later".
  • We wouldn't have to teach users best practices on using the assistant (e.g. "tell AI the entire workflow all the context in one prompt"). It would guide the user if they don't give enough details, but allow them to skip quickly if they're just drafting an outline.
  • This might also make the assistant feel faster when generating more complicated workflows, as the assistant wouldn't go away for such a long time preparing the details in the background.

The implementation might be too slow if we treated each as a conversation turn, and so this should be implemented as tool use responses ideally.

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by reviewing the one-shot tests and the current assistant interaction and tool-use flow. Clarify whether the intended behavior is follow-up questions, reasonable guesses, placeholders, or an explicit user-skip path. Done should include an agreed interaction design and a way to verify the assistant adapts to missing information without requiring every detail in the initial prompt.

Written by the indexing model from the issue text.

Assessment

Domain
ai
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Quiet
Clarity
Needs clarification
Newbie friendliness
35/100

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