sga

well i have learnt something, thanks. i usually just unitalicise names (so here, that would be moon and me, but not N, kg, m). I have seen units italicised a lot (professor notes, even papers), so i assumed it was accepted. i have seen normal ones too, and bold also (that is usually for vector quantities i think).

if i remeber correctly, it just slings most of fast moving things around (roughly equally in all direction), and only slow moving things actually hit it.

slung out of the system.

that seems a bit too strong for jupiter, that seems more like suns behaviour

Jupiter's pull is so great, compared to earth, that the ones that do get past or then pulled more towards the sun.

this seems correct.

but i have not actually done any courses on celestial mechanics, and mostly basing on yt videos that i watch, so you maybe are correct on this one.

but jupiter also slings a lot towards earth too

they kinda are not. it is most likely typeset in latex, where in equation mode all letters by default get italicised. and it is kinda accpeted as appropriate typesetting.

what do you mean by efficient. I am using niri right now, and i do not record increased power/cpu/gpu usage as compared to sway.

and also, how are you getting the wiki? i would first scrape it . if it is something like fandom, then do not scrape directly, first host your own breeze wiki (https://docs.breezewiki.com/Running.html), then use wget with a optimal rate limit. using breeezewiki will remove some junk, and you will get cleaner html to begin with.

for small models, try to keep total input (prompt plus data) to be small, as they general can not reatin there smarts for much (even if they advertise larger contexts).

I am doing something very similar, but for different kinda source (pdfs) and connverting to json (json/yaml do not matter).

what i have done is

• create a good enough template. - this is very important. i can not show my template exactly as it is work related, but it is simple, like define various key value pairs, and how it is meant to be presented. something like

{  
	// charecter description  
	"name": "NAME_OF_CHARACTER",  
	"powers": [{name: "fly"},{name: "see_through_walls"} ]  
}  

and so on. try to cover as many cases you think that can be done.

• install llama cpp (or ollama works too), i am using smollm3 3b (more knowledge, but slower (15-18tps)) and qwen3 1.7b (less knowledge, faster(25 tps)), i am currenty just running stuff on my laptop igpu.

• here is my simplified code ( i have removed some important bits which are work related from promt, but just imagine a detailed prompt aking model to do something)

# assuming pdf with text - if it does not have text, then we might have to perform ocr  
import sys  
import pdftotext  
input_file = sys.argv[1]  
# Load your PDF  
with open(input_file, "rb") as f:  
    pdf = pdftotext.PDF(f)  
pdf_text = "\n\n".join(pdf)  
# print(pdf_text)  

# reading the jsonc template  
with open('./sample-json-skeleton.jsonc', 'r') as f:  
	template = f.read().strip()  
# print(template)  


# creating the prompt - we want to ask the model to fit the given pdf_text into a format sigven by json template 
prompt = "/no_think You have to parse a given text according to given json template. You must not generate false data, or alter sentences much, and must try to keep most things verbatim \n here is the json template. do note the template currently contains comments, but you should try to not generate any comments. Stick very closely to the structure of template, and do not create any new headers. do not create keys which do not exist in template. if you find a key or title from the source, try to fit it to keys/titles from the template. stick with the format. if you are unable to fit something to given template, add the additional section as that is the catch all section. Stick to the template. \n\n``` \n " + template + " \n``` \n\n and here is the data that you have to parse \n\n``` \n " + pdf_text + " \n```"  
# print(prompt)  


# asking llm to parse  
# using openai's python lib to call, but I am not calling openai's servers. instead I am using a locally hosted openai api compatible server (llama.cpp-server ftw)  
from openai import OpenAI  
client = OpenAI(base_url="http://127.0.0.1:11737/", api_key="sk-xxx")  
config = { 'temperature': 0.4, }  
response = client.chat.completions.create(model="", messages=[{"role": "user", "content": [{"type": "text", "text": prompt},],}],)  
print(response.choices[0].message.content)  

it is not perfect, but i get 85+% on the way, and it is simple enough. if you need some more help, please ask.

and this is what a war crime is

it was a straight Soviet invasion, so basically a full role reversal.

while writing, i was confused about this. was it a russian puppet state that was established, or like directly reporting to moscow. so i thought russia influenced was a safer bet.

To make the notifications timely you'd need to request the feed very often, which is super inefficient - 99% of requests would produce no new notification.

I know this, and that is why i do not (my usual pull rate is once in 6-12 hours).

Making a RSS feed is not difficult especially as we already produce them for other content.

thank you. to me rss is one of the best things possible. instead of me manually checking each website, i just get the content i ask for, in cliennt i prefer, from where i can open it however i feel (for example, with threadiverse communities, i diectly subscribe to community's rss from their base instance, which also kinda distributes the load).

I remember their appointment from brodie's video on this, and iirc, they were someone who has been in community for ~20 years, and they also had some kind of vision disability (not 100% sure), because of which there was hope that gnome would do more investments on accessibilty front. Which to gnome's credit, they have the best among other wayland folks, but this feels to sson. if it had been a year or 2, it would have made sense (they already were an old person, so time was not favoring them), because it is reasonable for such posts 2 change in that timeframe. the previous director also left in 5-6 months, then this person in 4, it really speaks something about gnome's board

Also, is it possible to get a feed of user's comments as well. that is the thing even lemmy does not have. (I partially use rss feeds for archival purposes)