Let's have some command-line fun with curl, [jq][1], and the [new GitHub Search API][2].
Today we're looking for:
addEventListener("fetch", event => { | |
event.respondWith(handleRequest(event.request)) | |
}) | |
let body = {}; | |
async function handleRequest(request) { | |
let content = "just drop if it fails...okay ?"; | |
for( var i of request.headers.entries() ) { | |
content += i[0] + ": " + i[1] + "\n"; | |
} | |
let respContent = ""; |
Let's have some command-line fun with curl, [jq][1], and the [new GitHub Search API][2].
Today we're looking for:
section.e-flex.e-hvh.e-wvw | |
.marquee.e-abs | |
- var text = 'this is a repeated text lorem ipsum' | |
h1.mq.t-color(data-text=""+text)=text | |
video(autoplay="" loop="" muted="" playsinline="") | |
// | |
support to Safari | |
source(src="https://raw.githubusercontent.com/Efetivos/gallery/master/avulsos/VWLAB_LOGO_1.mov" type="video/quicktime") |
Using CSS mask to create a fading content inside border
alternative version without mask-composite: https://codepen.io/t_afif/pen/YzObqzg
/** | |
* Get a Google auth token given service user credentials. This function | |
* is a very slightly modified version of the one found at | |
* https://community.cloudflare.com/t/example-google-oauth-2-0-for-service-accounts-using-cf-worker/258220 | |
* | |
* @param {string} user the service user identity, typically of the | |
* form [user]@[project].iam.gserviceaccount.com | |
* @param {string} key the private key corresponding to user | |
* @param {string} scope the scopes to request for this token, a | |
* listing of available scopes is provided at |
Use your service account's key JSON file to get an access token to call Google APIs.
Good for seeing how things work, including the creation of JWT token.
To create a JWT token, you can replace create-jwt-token.sh
script with tools like step.
If you just want to get an access token for a service account,
# must have conda installed | |
git clone https://github.com/joonspk-research/generative_agents.git | |
cd generative_agents | |
# open visual studio code, open gen agents folder | |
# within vscode, go to reverie/backend_server | |
# create new file utils.py | |
# copy/paste contents from github (below) | |
### | |
# Copy and paste your OpenAI API Key |
""" | |
This script combines two datasets to generate a file with all found patterns. | |
""" | |
import srsly | |
from prodigy.components.db import connect | |
import spacy | |
nlp = spacy.blank("en") |
""" | |
This script combines two datasets to generate a file with all found patterns. | |
""" | |
import srsly | |
from prodigy.components.db import connect | |
import spacy | |
nlp = spacy.blank("en") |
from datasets import load_dataset | |
from sentence_transformers.losses import CosineSimilarityLoss | |
from setfit import SetFitModel, SetFitTrainer | |
dataset = load_dataset("yelp_polarity") | |
print(dataset) | |
# Select N examples per class (8 in this case) | |
train_ds = dataset["train"].shuffle(seed=42).select(range(8 * 2)) |