How to collect prompt/response feedback?!
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- Dominant language
- Python
- Stars
- 12.5k
- Forks
- 998
- Avg merge
- 3d 13h
- Merged PRs (30d)
- 10
Description
Hey llm community. I'd like to share a little plugin that I started: https://github.com/luebken/llm-logs-feedback. The idea is to quickly annotate a prompt/response tuple with feedback. At a later stage, I'd like to learn from the feedback I've stored and possibly adjust my prompts.
WDYT?
This is a preview version to gain feedback (pun intended) on the idea, the CLI design and the database schema. More things to come.
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
Review the linked llm-logs-feedback plugin first, focusing on its CLI design and database schema as described here. Before implementation, clarify whether this issue requests a specific change; done is an agreed scope and acceptance criteria for collecting and learning from prompt/response feedback.
Written by the indexing model from the issue text.
Assessment
- Domain
- ai, cli, databases
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100