The story of how YouTube outpaced Google Videos. Conclusion: type annotations are a plague 😭

Patchwork might be something to keep in mind as an opportunity to install later on if I get overwhelmed by patches. Right now it’d be a complete YAGNI. Also it’s Django.

I like the idea: it doesn’t intrude with the mailing list workflow at all, it’s just an extra “view” of the patches.

Tauthon. Run Python 2 code forever. 🙏🏻

In this tutorial we’ll use reader to download all the episodes of a podcast, and then each new episode as they come up.

Why I’m using the unstructured Python library to handle complex text data while building a private AI assistant, and also explaining its benefits and why it’s the perfect fit for my use case.

“At a glance, this should help fpm users, I think, and fpm should mark things as this new “externally managed” category (pending some code changes to fpm, I assume)”

The gist seems to be that pip will be less inclined to clobberly delete stuff from dpkg, and that’s a good thing. It “tries to steer us towards venvs” which I’m not into compared to just making .deb files but hopefully there will be slightly fewer clashes. 🤞🏻

Auf YouTube findest du die angesagtesten Videos und Tracks. Außerdem kannst du eigene Inhalte hochladen und mit Freunden oder gleich der ganzen Welt teilen.

the pager will, of course, eventually go off at 2AM

pip is not included with python packages, you need to install it.
In general, you should check to see if a ports exists for the python software you want instead (e.g: pkglocate from pkglocatedb, or https://openports.pl are useful).

Contribute to Lightning-AI/lit-llama development by creating an account on GitHub.

const SECRET_KEY = “YOUR API KEY”; const MAX_TOKENS = 800; const TEMPERATURE = 0.9;

function AI_ChatGPT(prompt, temperature = 0.4, model = “gpt-3.5-turbo”) { const url = “https://api.openai.com/v1/chat/completions”; const payload = {

model: model,
messages: [
  { role: "system", content: "You are a helpful assistant." },
  { role: "user", content: prompt },
],
temperature: TEMPERATURE,
max_tokens: MAX_TOKENS,

}; const options = {

contentType: "application/json",
headers: { Authorization: "Bearer " + SECRET_KEY },
payload: JSON.stringify(payload),

}; const res = JSON.parse(UrlFetchApp.fetch(url, options).getContentText()); return res.choices[0].message.content.trim(); }

Screaming-fast Python 3.5 HTTP toolkit integrated with pipelining HTTP server based on uvloop and picohttpparser. - squeaky-pl/japronto: Screaming-fast Python 3.5 HTTP toolkit integrated with pipelining HTTP server based on uvloop and picohttpparser.