See also:
Service | Type | RAM | Storage | Limitations |
---|---|---|---|---|
👉 Adaptable | PaaS | 256 MB | Non-persistent? (1 GB database storage available) | |
AWS EC2 | IaaS | 1 GB |
import { createAnvil } from '@viem/anvil' | |
import 'dotenv/config' | |
import { $ } from 'bun' | |
import path from 'path' | |
import z from 'zod'; | |
import { fromError } from 'zod-validation-error' | |
////////////////////// | |
// Env validation |
// | |
// ViewController.swift | |
// Journal-Calendar-Demo | |
// | |
// Created by Seb Vidal on 30/04/2024. | |
// | |
import UIKit | |
class ViewController: UIViewController { |
from langchain.chat_models import ChatOpenAI | |
from langchain.prompts import ChatPromptTemplate | |
from langchain.schema.output_parser import StrOutputParser | |
import requests | |
from bs4 import BeautifulSoup | |
from langchain.schema.runnable import RunnablePassthrough, RunnableLambda | |
from langchain.utilities import DuckDuckGoSearchAPIWrapper | |
import json | |
RESULTS_PER_QUESTION = 3 |
import numpy as np | |
import signal | |
import matplotlib.pyplot as plt | |
######################################################################### | |
######################### 3SAT GENERATION ############################### | |
# generate 3sat problems | |
def gen_3sat(c,n): | |
clauses = [((np.random.randint(1, n+1), np.random.randint(0, 2)), |
import numpy as np | |
# given a corpus of sentences & parses, acquires grammar and probabilities for a probabilistic context free grammar | |
def read_corpus(filepath): | |
file = open(filepath, "r") | |
corpus_lines = [] | |
while True: | |
content=file.readline() | |
if not content: | |
break |
<!DOCTYPE html> | |
<html lang="en"> | |
<head> | |
<meta charset="UTF-8"> | |
<meta name="viewport" content="width=device-width, initial-scale=1.0"> | |
<title>Z-Index Example</title> | |
<style> | |
html, body { background-color: #00787F; } | |
.container { | |
position: relative; |
float circ( vec2 p){ | |
return length(p) - 0.3; | |
} | |
void pR(inout vec2 p, float a) { | |
p = cos(a)*p + sin(a)*vec2(p.y, -p.x); | |
} | |
// Repeat in two dimensions | |
vec2 pMod2(inout vec2 p, vec2 size) { | |
vec2 c = floor((p + size*0.5)/size); |