A simple search engine from scratch
63 comments
·May 20, 2025franczesko
marginalia_nu
The SeIRP-book, free online as a PDF, is also a fantastic resource on traditional search engines and information retrieval in general.
franczesko
Due to dead links, this is more appropriate url:
StefanBatory
Server not found. Did HN gave it hug of death?
franczesko
Please see links to videos and notes - they still work. Udacity must have removed the course
fuzztester
the actual course link on udacity gives a 404.
ktallett
I always wonder if the days of search engines for specific topics could return. With LLM's providing less than accurate results in some areas, and Google, bing, etc being taken over by adverts or well organised SEO, there feels like a place for accurate, specialised search.
wolfgang42
Yeah, the (relative) rise of Kagi and Marginalia show that from a technical perspective, this is within the grasp of a dedicated hobbyist.[1] If Google continues their current trajectory, and overwhelming numbers of AI crawlers don’t cause an unsurmountable rise in CAPTCHA pages, I hope to see an upsurgence of niche search engines that focus on some specialty small enough that one or a few people can curate the content and produce a much better experience than the current crop of general Web search engines.
Self-plug: I run such a search engine (for programmers) in my living room, at <https://search.feep.dev/>. I don’t spend a ton of time maintaining it, so I’m interested to see what someone really dedicated could do.
[1] I wrote a 2004-vs-2014 comparison, and things have only gotten better since then: https://search.feep.dev/blog/post/2022-07-23-write-your-own
iLoveOncall
Please, Kagi doesn't even have 50,000 active members, it's definitely not "rising" to become a serious contender at any sort of market share, it's a micro-project. You just feel it's bigger than that because for some reason all of its 50,000 users post relentlessly about it on HN.
wolfgang42
Hence the (relative), yes. Did “dedicated hobbyist” not tip you off that I wasn’t thinking about how to maximize market share?
cyanydeez
Just gotta build a search engine that properly contextualizes scams, bait & switch sites, SEO, and the rest, and you're back in business.
To do that, you probably still need humans to properly curate the dataset, essentially hire 100 librarians and setup a work flow for them to continually prune results.
Right now, everything is all batch processes. None of these LLMs use active feedback since there's no real models using updates.
datadrivenangel
The curation of an index of resources is what's needed for niche search
cyanydeez
i know the answer is never distributed services, but if one could build a sufficiently complex SDK to make like a Blue Sky but for niche search indexes, you could chain a bunch of vetted resources together.
dcist
WestLaw and Lexis Nexis provide this for legal search, but quite frankly, these services are subpar. It's amazing that these two companies rake in hundreds of millions but they are both slower than Google, Bing, Yandex, or any LLM service (ChatGPT, Claude, Gemini, etc.) while scouring a universe of text that is orders of magnitude smaller. The user experience is also terrible (you have to login and specify a client each and every time you attempt to use the service and both services log you out after a short -- in my opinion -- period of inactivity, creating friction and needless annoyance to the user). There's an opportunity there.
ahi
LN and Westlaw's real service is their ubiquity. Every law student has access to it and every firm expects proficiency. While they generally suck, the last time I used it (looong time ago), their boolean search was quite nice. That kind of text search has mostly been replaced by non-deterministic black boxes which aren't great for legal research.
ktallett
I haven't personally used the mentioned services as they aren't in my field, however what is the accuracy of their results? Are they double checked? I don't find LLMs particularly accurate in my field (that's being kind), if anything I find they make up sources that simply don't exist.
I mean poor UX has no excuse but slow speed can be reasoned if it makes the quality of the service better.
cosmicgadget
My hope is that content self-indexes so instead curation it just has to be aggregated.
econ
Depends how tiny the niche is. A few dozen domains is easily done by hand and worth having.
raydenvm
Which is not scalable, right?
null
cosmicgadget
It's scalable if you are okay with not searching exhaustively.
fanwood
I already directly search on Wikipedia for most topics (with a search shortcut on URL bar)
ktallett
Wikipedia is useful up to a point for sure. I feel whether it could be a expansion of Wikipedia in it's current use case, but for emerging research and niche topics it can sometimes be less useful.
snowstormsun
Nice idea, but this approach does not handle out of vocabulary words well which is one major motivation for using a vector-based search. It might not perform significantly better compared to lexical matching like tf-idf or BM25, and being slower because of linear complexity. But cool regardless.
netdevphoenix
It is supposed to be a simple search engine. Keyword: simple.
As long as it does what it is meant to, as a simple search engine, it seems fine
snowstormsun
Using tfidf or bm25 would actually be simpler than a vector search.
I understand this is just for fun, just wanted to point that out.
LunaSea
TF/IDF does not support out-of-vocabulary keywords as far as I know.
cosmicgadget
Or since OP has both the cosine similarity matching and naive matching, a heuristic combination of the two since they address each other's weaknesses.
janalsncm
Vector based approaches either don’t handle OOV terms at all or will perform poorly, depending on implementation. If you limit to alphanumeric trigrams for example you can technically cover all terms but badly depending on training data.
haasisnoah
How would you handle those in wordvec?
And isn’t a big advantage that synonyms are handled correctly. This implementation still has that advantage.
leumassuehtam
The author has a nice series on compiling a Lisp [0], but unfortunately his search engine fails to find it by querying it with "lisp" or "Lisp".
tekknolagi
I wonder if that's just not in the top 10k words :/
freilanzer
And it's unfinished since 2020.
sp0rk
The SVG equation is very difficult to read if you're using a dark OS theme because the blog uses the OS preference for dark/light theme (and doesn't seem to give an option to change it manually, either.)
dheera
On the side, not criticizing OP but I hate the word "cosine similarity" and I wish people would just call it a "normalized dot product" because anyone who took sophomore-level university calculus would get it, but instead we all invented another word
kaycebasques
> The idea behind the search engine is to embed each of my posts into this domain by adding up the embeddings for the words in the post.
Ah, OK! I never really grokked how to use word-level embeddings. Makes more sense now.
skarz
Is 'grokked' a common verb now? I had never even heard the word until Musk's AI.
kaycebasques
A common verb "now"??
> Grok (/ˈɡrɒk/) is a neologism coined by the American writer Robert A. Heinlein for his 1961 science fiction novel Stranger in a Strange Land. While the Oxford English Dictionary summarizes the meaning of grok as "to understand intuitively or by empathy, to establish rapport with" and "to empathize or communicate sympathetically (with); also, to experience enjoyment",[1] Heinlein's concept is far more nuanced, with critic Istvan Csicsery-Ronay Jr. observing that "the book's major theme can be seen as an extended definition of the term."[2] The concept of grok garnered significant critical scrutiny in the years after the book's initial publication. The term and aspects of the underlying concept have become part of communities such as computer science.
skarz
Yes, "now". According to Google Trends[0] there was little to no search interest in the term until December 2023.
Usage of 'grokked' on HN: 1,147[1]
Usage of 'hacked' on HN: 37,272[2]
[0] https://trends.google.com/trends/explore?date=all&geo=US&q=g...
[1] https://hn.algolia.com/?dateRange=all&page=0&prefix=false&qu...
[2] https://hn.algolia.com/?dateRange=all&page=0&prefix=false&qu...
kevinsync
I never knew the etymology [0] but always knew the word for as long as I've been into computing (90's) .. apparently it's from the 1960's from a Heinlein novel!
BalinKing
I first learned of from the Jargon File, long before Grok the product existed: https://www.catb.org/jargon/html/G/grok.html
janalsncm
Started hearing about it in ~2022 when some ML researchers accidentally left a model training on over a weekend. For a while the model wasn’t doing much (so they were going to turn it off) and then over the weekend it got surprisingly good.
StefanBatory
It was a word before, as far as I remember. Saw it a few times here.
skarz
What does it even mean?
cosmicgadget
This was a really nice read. Now I have no excuse not to upgrade my blog search. I do feel that I'll have a ton of long tail words like 'prank'.
vojtechrichter
I really like people playing around with technology many take for granted, without understanding its core, underlying princliples
swyx
this embeds words with word2vec, which is like 10 years old. at least use BERT or sentencetransformers :)
gthompson512
I have been thinking a bit lately about how much sense that makes compared to just using word vectors, since traditional queries are super short and often keyword based(like searching for "ground beef" when wanting "ground beef recipes I can cook easily tonight") and so lack most of the context that BERT or similar gives you. I know there are methods like using seperate embeddings for queries and such, but maybe a basic word based search could be more useful, especially with something like fastText for out of vocabulary terms.
curtisszmania
[dead]
potato-peeler
[dead]
On the topic of search engines, I really liked classes by David Evans. The task was also building a simple search engine from scratch. It's really for beginners, as the emphasis is on coding in general, but I've found it to be very approachable.
https://www.cs.virginia.edu/~evans/courses/