This is a cool project, and the idea of using LLMs to selectively extract features from open source projects is an interesting concept.
The only thing I take issue with is the phrase "LiteLLM Without the Bloat." A lot of the features that have been removed (like cost tracking, streaming, caching) are... kind of the core value proposition of LiteLLM for many of their users.
LiteLLM doesn't quite live up to its name. With all those features, there is nothing "lite" about it. It is essential for a project to live up to its name.
Imagine Sqlite adding heavy features from Postgresql, e.g. row-level security.
But imagine Sqlite not supporting joins or window functions... sure they are useful but look how many LOC it adds! Who is the arbiter of what Lite actually means?
We run it at my org and it's never been a noticeable resource hog. It's actually the best performer between it, our AI observability stack and the front end.
I have the same complaint about oh-my-pi's readme. The tone is obnoxious. It's somehow jaded and matter-of-fact at the same time. Like it was written by that one guy at work who never misses a chance to brag about how clever he is.
Really? I mean, yeah, it's probably written by an LLM, but it's hardly the worst that I've seen. Looks way more straight forward than the modern README featuring a ton of badges, emojis, confusing out-of-context screenshots, "trust me bro" installation instructions, vague elevator pitches, "used by netflix, nasa, disney, good morning america, alex jones, the church of scientology", and other verbiage to create the illusion that the author won't immediately get bored and abandon their glorified dissertation piece. They all scream "give me your github stars" whereas this one doesn't. But I still get what you mean when it comes to the particular 'isms.
1. Not a tangent, it’s related to the very first content visible on that link.
2. Not a dismissal, an advise from an expert
3. Not complaining, as stated, giving an advise about the optics of using clear LLM prose on the first paragraph
First off, cool project! It's always great to see derivatives that question the efficiency of the established product.
I think the main thing the readme is missing is the core benefits. Reducing LOC and dependencies is cool, but it would be great to understand if this provides some additional benefits like lower latency or memory requirements.
Funny, everything you pruned away is the reason I’m deploying LiteLLM in our platform. Having a reliable way to track token spend per customer across different services is important to us, and LiteLLM handles this well
most software like this will be dematerialized, democratized, and demonetized - companies building in the infra band being increasingly disintermediated
This is a 30 minute project with a frontier LLM. I don’t see why anyone would use anyone else’s router. Techniques are valuable today. Libraries are not.
I'm always confused by LLM proxies that claim to support tool calling. Even for Bifrost that claims to be doing it, at least when I was checking it out, I found out that while it injects the list of MCP tools that's available on the proxy-side, it doesn't actually make the call on client's behalf, and clients get confused by it (response returns MCP call request whose tool doesn't exist on the client-side).
The only thing I take issue with is the phrase "LiteLLM Without the Bloat." A lot of the features that have been removed (like cost tracking, streaming, caching) are... kind of the core value proposition of LiteLLM for many of their users.
Imagine Sqlite adding heavy features from Postgresql, e.g. row-level security.
> Please don't post shallow dismissals
> Please don't complain about tangential annoyances—e.g. article or website formats, name collisions, or back-button breakage.
See: Hacker News Guidelines
I’m biased but I think mine is coded to a higher standard than litelm. https://github.com/s-banach/langchaint
I think the main thing the readme is missing is the core benefits. Reducing LOC and dependencies is cool, but it would be great to understand if this provides some additional benefits like lower latency or memory requirements.
Yes, LLMs can do a great job at writing semi-working MVP. Turning it into a usable project still requires a team.
Yeah, maybe for your toy project you can use a LLM written tool.
Also, I am not saying LiteLLM is good either.