I would recommend you make it open source. I've also done this the past as well.
Even if it's a project that is not maintained you don't know how it might help someone else.
Readit Newsonel commented on Build and Host AI-Powered Apps with Claude – No Deployment Needed anthropic.com/news/claude... · Posted by u/davidbarker
I'm building something like this. The value to you would be that you could earn a margin on the token costs. That is, the end user is charged 2x the token cost of the API call. The API provider earns the base cost, the platform owner earns 20% of the remaining cost, and the webapp creator earns 80% of the remaining price.
So for an API call that costs $0.50, the end user is charged $1; and from that AI API earns $0.50, the webapp creator earns $0.40 and the host earns $0.10.
I'm trying this out with https://codeplusequalsai.com right now but it's not clear to me yet that it will take off!
But clearly, the value to you should be that you could earn $ based on the token usage from end-users.
I checked your website I it's an interesting idea. I think you need some additional copy though, because just landing on your homepage you don't really understand what it does. More exactly I don't know what to use it for. Your comment and GP's coming together gave me a better idea.
What's your target audience? developers?
onel commented on America's reputation drops across the world ipsos.com/en/americas-rep... · Posted by u/mrtksn
onel commented on Ask HN: Best open source project that has terrible documentation? · Posted by u/reporangers
Take a look at dspy.ai. Love the project but they need some help with the docs.
onel commented on Improving recommendation systems and search in the age of LLMs eugeneyan.com/writing/rec... · Posted by u/7d7n
Another amazing post from Eugene
I'm interested to know if anyone is using fine-tuning to train a model on proprietary or in-house codebases and documentation.
RAG solutions seem to have their limitations, and fine-tuning might be a more effective approach.
How much effort is required to turn code into something one can use for fine-tuning?
Generally it is recommended that you fine-tune if you want to shape the output style. If you eant ro only output json, or just output jsdoc, etc.
To add knowledge, RAG is a better idea and easier to keep updated on code changes.
If rag does not give back good results then that's a problem with the retrieval part, which can be measured and improved.
We're building documentation + rag systems for enterprise code bases and this is what we saw works best.
How are people using auto-edits and these kind of higher-level abstraction?