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Install Termux GUI Plugin

Let's install the Termux GUI Plugin, so we can build Android GUI Apps in C and Python... On Android!

Caution: We're installing Experimental Unsigned APKs, be careful!

Install Termux APK and Termux GUI APK

According to the instructions, we should install Termux APK and Termux GUI APK generated by GitHub Actions...

This makes virtualbox works in a portable mode:

if you have any installed virtualbox then uninstall it first
download https://download.virtualbox.org/virtualbox/7.0.8/VirtualBox-7.0.8-156879-Win.exe or any newer or older version
click on Download ZIP above to download the scripts needed
create a folder inside your USB/external drive or whatever, name it myVMBOX (ex. F:\myVMBOX if your USB is in F:\).
inside F:\myVMBOX put the virtualbox exe we just downloaded (VirtualBox-7.0.8-156879-Win.exe) and rename it to VirtualBox.exe.
inside F:\myVMBOX put the following files start_virtualbox.bat and uninstall_virtualbox.bat, you will find them inside the zip you just downloaded.
now everytime you want to start virtualbox use start_virtualbox.bat.

How to setup ssh through https tunnel

... via OpenSSL and Traefik

A HTTPS tunnel for SSH (Secure Shell) is a useful tool for accessing a remote server in a secure manner when the connection is limited or restricted by a firewall or network security measures. It provides a secure way to bypass these restrictions and access the remote server securely over the internet. The HTTPS protocol, which is used to secure web traffic, is utilized to create a secure connection to the remote server. The data transmitted over this connection is

	using System;
	using System.Linq;
	using System.Net.Http;
	using System.Text.Json;
	using System.Text.RegularExpressions;

	var http = new HttpClient();

	// Here is image, i.e. File.ReadAllBytes("smth.png");
	var file = new byte[] {137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82, 0, 0, 0, 44, 0, 0, 0, 44, 8, 6, 0, 0, 0, 30, 132, 90, 1, 0, 0, 0, 9, 112, 72, 89, 115, 0, 0, 11, 19, 0, 0, 11, 19, 1, 0, 154, 156, 24, 0, 0, 5, 194, 105, 84, 88, 116, 88, 77, 76, 58, 99, 111, 109, 46, 97, 100, 111, 98, 101, 46, 120, 109, 112, 0, 0, 0, 0, 0, 60, 63, 120, 112, 97, 99, 107, 101, 116, 32, 98, 101, 103, 105, 110, 61, 34, 239, 187, 191, 34, 32, 105, 100, 61, 34, 87, 53, 77, 48, 77, 112, 67, 101, 104, 105, 72, 122, 114, 101, 83, 122, 78, 84, 99, 122, 107, 99, 57, 100, 34, 63, 62, 32, 60, 120, 58, 120, 109, 112, 109, 101, 116, 97, 32, 120, 109, 108, 110, 115, 58, 120, 61, 34, 97, 100, 111, 98, 101, 58, 110, 115, 58, 109, 101, 116, 97, 47, 34, 32, 120, 58, 120, 109, 112, 116, 107, 61, 34, 65, 100, 111, 98, 101, 32, 88,

	{
	"schema_version": "v1",
	"name_for_model": "twilio",
	"name_for_human": "Twilio Plugin",
	"description_for_model": "Plugin for integrating the Twilio API to send SMS messages and make phone calls. Use it whenever a user wants to send a text message or make a call using their Twilio account.",
	"description_for_human": "Send text messages and make phone calls with Twilio.",
	"auth": {
	"type": "user_http",
	"authorization_type": "basic"
	},

	# STEP 1: Load

	# Load documents using LangChain's DocumentLoaders
	# This is from https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html

	from langchain.document_loaders.csv_loader import CSVLoader
	loader = CSVLoader(file_path='./example_data/mlb_teams_2012.csv')
	data = loader.load()

	"""
	Structlog example configuration with FastAPI.
	Features:
	- async bound logger
	- contextvars to log request-id and other meta data
	- custom format for default logging loggers and structlog loggers
	"""

	import asyncio
	import logging

	# Install bitsandbytes:
	# `nvcc --version` to get CUDA version.
	# `pip install -i https://test.pypi.org/simple/ bitsandbytes-cudaXXX` to install for current CUDA.
	# Example Usage:
	# Single GPU: torchrun --nproc_per_node=1 trainer/diffusers_trainer.py --model="CompVis/stable-diffusion-v1-4" --run_name="liminal" --dataset="liminal-dataset" --hf_token="hf_blablabla" --bucket_side_min=64 --use_8bit_adam=True --gradient_checkpointing=True --batch_size=1 --fp16=True --image_log_steps=250 --epochs=20 --resolution=768 --use_ema=True
	# Multiple GPUs: torchrun --nproc_per_node=N trainer/diffusers_trainer.py --model="CompVis/stable-diffusion-v1-4" --run_name="liminal" --dataset="liminal-dataset" --hf_token="hf_blablabla" --bucket_side_min=64 --use_8bit_adam=True --gradient_checkpointing=True --batch_size=10 --fp16=True --image_log_steps=250 --epochs=20 --resolution=768 --use_ema=True

	import argparse
	import socket
	import sys

	:Init
	@echo off
	set OUTPUT=%1
	set MODELPATH=%2
	set OUTPUTPATH=%3
	if not exist %OUTPUTPATH% mkdir %OUTPUTPATH%
	goto Install

	:Install
	:: Will ensure pytorch is installed.