nbrad

This is definitely an issue - We're working on an automated code review product (ellipsis.dev), and while we have a lot of happy Swift users, the speed of breaking changes creates issues. Currently we do a mix of letting users put in their own custom rules/feedback, and are working on pulling in latest docs automatically.

The issue doesn't seem to be going away soon though - i expect this actually to put pressure on a lot of projects to have more stable APIs (good and bad, i suppose)

Hi there! I recommend trying them out to see which one you like best :)

You're right; this was my mistake

hi @gillh, sincere apology - that wasn't my intent. No excuse.

@timpetri, i recommend you try both products and choose the one you like

Thanks! Many of our customers actually started with them before switching to us; their feedback is that we have:

- higher quality comments

- better UX (cleaner and more concise)

- more power (tag @ellipsis-dev anywhere in comments to make changes or ask questions)

it's super cool! checkout how the Instructor repo uses it to keep various parts of their docs in sync: https://github.com/jxnl/instructor/blob/main/ellipsis.yaml

interesting, thanks!

thanks!

thanks - which FastAPI lib is that?

I've heard some reports that Nix is very painful to get working with Python/ML stack - do you know if this is this still (ever?) the case?

How is the space trending? Who are the biggest adopters (i've seen a lot of use cases in consultancies, education, and "big gnarly stacks")? What are you most excited about?

nice - I've also found VS Code Remote + SSH to be pretty fantastic

Cool! I've used a similar workflow with teams that SSH into boxes with GPUs, VSCode makes it completely seamless - surprised i don't hear about it more

Nice, thanks! what kind of team are you on (company size, how experienced the engineers, tech stack)? when you say "ironing out some kinks" what were the pain points?

if you're up for quick chat/DM, would love to hear more (link in profile)

In general, just providing a schema and asking for the response in JSON with few-shot examples is extremely (99%+) reliable in my experience.

I've found GPT-3.5 more than adequate at inferring schemas and filling them for conventional use cases like chat-based forms (as an alternative to Google Forms/TypeForm); my code and prompts available at: https://github.com/nsbradford/talkformai - i've also used this to extract structured data from code for LLM coding agents (e.g. "return the names of every function in this file")

In my opinion, more and more APIs are likely to become unstructured and be reduced to LLM agents chatting with each other; I wrote a brief blog about this here: https://nickbradford.substack.com/p/llm-agents-behind-every-...