Recent submissions

Comment · 4 months ago
Comment · 9 months ago
at the sake of being obvious, do you have a tiny llm gating this decision and classifying and directing the task to its appropriate solution?
Comment · 1 year ago
does the lite version have a faster token output? or time to first token?
Comment · 1 year ago
one point the author seems to be missing as to why we need full self driving everywhere is in the logistics industry. We are talking about interstate driving, from point A to point B, in this case it might involve industria environments such as a truck stop, weighing, loading/unloading etc, something that requires decision making across different environments (urban, highway, dense residential etc). Tesla FSD has the real potential for this unlock, more than just a ride hailing use case of getting people from point A to point B.
Comment · 1 year ago
i have been your user since the early days, I want to say congrats you guys, I have been recommending your framework to everyone. I appreciate the responsive support you gave me on discord (though in the end, my questions are already on the docs lol)
Comment · 1 year ago
Comment · 1 year ago
it used to be the case that graphql requests are in POST, but not anymore: https://nearform.com/open-source/urql/docs/api/core/#:~:text... example for urql

on top of http level caching, you can do any type of caching (redis / fs / etc) just like a regular rest but at a granular level, for ex: user {comments(threadId: abc, page: 1, limit: 20) { body, postedAt} is requested and then cached, another request can come in thread(id: abc) {comments(page: 1, limit: 20) {body, postedAt} you can share the cache.

N+1 is solved by a tighter integration with the database, for ex: https://www.graphile.org/postgraphile/performance/#how-is-it... or maybe a more popular flavor using prisma: https://pothos-graphql.dev/docs/plugins/prisma/relations#:~:...

but of course, there is always the classic dataloader as well.

I am not saying that use graphql and all the problems will be solved, but i am saying that the problem that OP proposed has been solved in an arguably "better" way, as it does not tie the presentation (HTML) with the data for cases of multiplatform apps like web, or native apps.

Comment · 1 year ago
N+1 is a solved problem at the framework level If GraphQL actually affects your performance, congratulations, your application is EXTREMELY popular, more so than Facebook, and they use graphql. There are also persisted queries etc.

Not sure about caching, if anything, graphql offers a more granular level of caching so it can be reused even more?

The only issue I see with graphql is the tooling makes it much harder to get it started on a new project, but the recent projects such as gql.tada makes it much easier, though still could be easier.

Comment · 1 year ago
I was just going to say, all of this has been solved with graphql, elegantly.
Comment · 1 year ago
link to the full pdf?
Comment · 1 year ago
i have been looking for something like this, the closest I could find by googling was celery workflow, i think you should do better marketing, I didn't even realize that hatchet existed!
Comment · 1 year ago
have you considered using remix?
Comment · 1 year ago
I 100% agree with this, I think you can even extend this to any AI, in the end, IMO, as the llm is more commoditized, the surface of which the value is delivered will matter more
Comment · 1 year ago
gemini flash is notorious for hallucinating the output of the OCR, be careful with it. For straight forward, semi-structured, low page count (under 5) it should perform well, but the more the context window is stretched the more the output gets more unreliable

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