Make sure our documentation is EXCELLENT
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- Dominant language
- Jupyter Notebook
- Stars
- 5
- Forks
- 10
- Avg merge
- 2d 20h
- Merged PRs (30d)
- 17
Description
Apollo is a bit of a strange beast, with a mix of production and research code and mixed standards of code quality.
But as part of our Responsible AI policy, we need to ensure that any production AI is clearly and transparently documented.
Imagine a curious user coming over from Lightning to understand how the AI assistant works. It's really important that they can get a good high level overview of the codebase and get a basic understanding.
Stuff like which models are used, and when, and how, and with what prompts, and what data we use (if any) needs to be clearly explained. And not just for AI experts.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No files, tests, or entry points are named. Start by reviewing the codebase to identify production AI models, prompts, usage, and data flows; done means user-facing documentation provides a clear high-level overview of these areas for non-experts.
Written by the indexing model from the issue text.
Assessment
- Domain
- ai, documentation
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100