zxt_tzx

I'm glad you found it helpful :)

> And overall, the fewer people use CF (or another provider of their size) the better.

I understand your sentiment, but I vehemently disagree.

The cloud provider space has rapidly become an oligopoly and CloudFlare is one of the few new entrants that (1) has sufficient scale to compete with the incumbents; (2) has new ideas that the incumbents cannot easily match (region earth, durable objects etc.).

For most production workloads, I would not even consider the newer cloud providers, but I sincerely meant it when I said I hope Cloudflare will succeed. They've also been very responsive to the feedback raised in the blogpost when I DM-ed them.

(On a side note re: difficulty for newcomers in this market, I used to be part of a team that would run e.g. staging and testing environments on a new serverless db provider, but would run prod on AWS Aurora. In retrospect, this did not make much sense either as you want your environments to be as similar as possible, which means new cloud providers have an even tougher time getting started.)

After this failed experience with SemHub, I am actually thinking of building something like this, for open source maintainers like you are definitely the ICP! (nuqs seems really cool btw, storing state in the URL param is definitely the way to go)

To elaborate, I was thinking of:

- running a cron that checks repos every X minutes

- for every new issue someone has opened, I will run an agent that (1) checks e.g. SemHub to look for similar issues; (2) checks the project's Discord server or Slack channel to see if anyone has raised something similar; (3) run a general search

- use LLMs to compose a helpful reply pointing the OP to that other issue/Discord discussion etc.

From other OSS maintainers, I've heard that being able to reliably identify duplicates would be a huge plus. Does this sound like something you'd be interested to try? Let me know how I can reach you if/when I have built something like this!

I am personally quite annoyed by all the AI slop being created on social media and even GitHub PRs and would love to use the same technology to do something pro-social.

Thanks for sharing! Do you have more details to share, e.g. did you just have a vector db, or did you have a main db as well?

In my research, Qdrant was also the top contender and I even created an account with them, but the need to sync two dbs put me off

Ah I was doing semantic search of GitHub _issues_, not the actual code on GitHub.

For code search, I have used grep.app, which works reasonably well

> There’s so much complexity that comes with keeping your vector db in sync with you main db (especially once you start filtering with metadata)

Ohh do you speak from experience? I know I will likely never do this, but curious how did you do it? When I looked into this, I found that Airbyte has something to connect the vector db with the main db, but I never bit that bullet (thankfully)

oh wow that's super cool, I tried it and it's very fast indeed. thanks for sharing! will spend more time to understand how it's implemented

Thanks for the feedback, to be honest, my own experience is actually very similar to yours.

The original pain point probably only exists for small minority of open source maintainers who manage multiple repos and actually search across them regularly. Most devs are probably like you and I, and the mediocre GitHub search experience is more than compensated by using Google.

In its current iteration, it's quite hard to get regular devs to change their searching behaviour, and, even for those who experience this pain point, it probably isn't large enough for them to change their behavior.

If I continue to work on this, I would want to (1) solve a bigger + more frequent pain point; (2) build something that requires a smaller change in user behavior.

> Have you looked into chunking (breaking input into smaller chunks and doing vector search on the chunks)?

Ohh I had not seriously considered this until reading this. I could have multiple embeddings per issue and search across those embeddings and if the same issue is matched multiple times, I would probably take the strongest match and dedupe it.

I could create embeddings for comments too and search across those.

Thanks for the suggestion, would be a good think to try!

> Choosing a chunking strategy seems to be a deep rabbit hole of its own.

Yes this is true. In my case, I think the metadata fields like Title and Labels are probably doing a lot of the work (which would be duplicated across chunks?) and, within an issue body, off the top of my head, I can't see any intuitive ways to chunk it.

I have heard that for standard RAG, chunking goes a surprisingly long way!

> it's weird you consider this a failure. you spent a few months and learned how to work with embedding models to build an efficient search. the fact that your search works well is a successful outcome.

Thank you for your encouragement! I take your point that it was not a technical failure, but I think it's still a product failure in the sense that SemHub was not solving a big enough pain point for sufficiently many people.

> if you want to turn your search into a business now that's a new and different effort, mostly marketing and stuff that most self respecting engineers gives zero shits about, but if that's your real goal don't call it a failure yet because you haven't even tried.

Haha to be honest, my goal was even more modest, SemHub is intended to be a free tool for people to use, we don't intend to monetize it. I also did try to market it (DMing people, Show HN), but the initial users who tried it did not stick around.

Sure, I could've marketed SemHub more, but I think the best ideas carry within themselves a certain virality and I don't think this is it.

Ohh apologies, I think there was a bug that led to the Internal Server Error, please try again, I _think_ it should be working now!

> I think a project like yours is going to be helpful to OSS library maintainers to see which features are used in downstream projects and which have issues.

That was indeed the original motivation! Will see if I can convince Ammar to reconsider shutting down the project, but no promises

> For this use case, I deployed my own instance to index all OSS repos implementing OSLC REST or using our Lyo SDK

Ohh, in case it's not clear from the UI, you could create an account and index your own "collection" of repos and search from within that interface. I had originally wanted to build out this "collection" concept a lot more (e.g. mixing private and public repos), but I thought it was more important to see if there's traction for the public search idea at all

Totally fair point. Thanks for taking the time to read through it! I guess I didn't want to use a VPS and then have to switch to something else if the product really worked, but I guess that rhymes with premature optimization.

Some other clarifications:

- I was also surprised with how expensive Supabase turned out to be and only got there because I was trying to sync very big repos ahead of time. I could see an alternative product where the cost here would be minimal too

- I did see this project as an opportunity to try out Cloudflare. as mentioned in the post, as a full stack TypeScript developer, I thought Cloudflare could be a good fit and I still really want it to succeed as a cloud platform

- deploying two separate API server and auth server is actually simpler than it sounds, since each is a Cloudflare Worker! will try to open source this project so this is clearer

- the durable objects rate limiter was wholly experimental and didn't make it into production

> All that being said though, maybe all it would've done is prolong the inevitable death due to the product gap the author concludes with.

Very true :(