Nate Aune natea

DEPRECATION NOTICE

This gist is now deprecated in favor of our official documentation: https://documentation.portainer.io/api/api-examples/ which contains up to date examples!

THE FOLLOWING DOCUMENTATION IS DEPRECATED

Please refer to the link above to get access to our updated API documentation and examples.

Code Minecraft with Python on Mac OSX

Here's a step-by-step to get started scripting Minecraft with Python on Mac OSX

Django Tutorials

I've scanned through these, and they all seem to cover the basic features of Django (models, function-based views, forms, templates, CSS, and the admin interface), and use Python 3 and Django 2. My notes indicate what I think differentiates them.

Django Girls tutorial

Written for Django Girls workshops or self-teaching
Widely recommended for beginners, even to Python, web development, and command line
Build a blog
Instructions for Windows, Mac, and Linux (including Python installation)

Periodic Reports Workshop

Welcome to the workshop. Here we'll get a hands-on approach on creating periodic reports on a sandbox provided by OpenCraft.

Sandbox Instructions

Register an account on the provided sandbox

https://lilac-periodic-reports.opencraft.hosting

I wrote an in-depth research prompt to conduct a GPT-Deep-Research on the Manus topic, seeking to replicate it with currently available open source tools. This is the result:

TLDR: Manus AI Agent Report

Manus is an autonomous AI agent built as a wrapper around foundation models (primarily Claude 3.5/3.7 and Alibaba's Qwen). It operates in a cloud-based virtual computing environment with full access to tools like web browsers, shell commands, and code execution. The system's key innovation is using executable Python code as its action mechanism ("CodeAct" approach), allowing it to perform complex operations autonomously. The architecture consists of an iterative agent loop (analyze → plan → execute → observe), with specialized modules for planning, knowledge retrieval, and memory management. Manus uses file-based memory to track progress and store information across operations. The system can be replicated using open-source components including CodeActAgent (a fine-tuned Mistral model), Docker for sandbox

	#!/bin/bash
	# from https://chromium.woolyss.com/
	# and https://gist.github.com/addyosmani/5336747
	# and https://chromium.googlesource.com/chromium/src/+/lkgr/headless/README.md
	sudo apt-get update
	sudo apt-get install software-properties-common
	sudo add-apt-repository ppa:canonical-chromium-builds/stage
	sudo apt-get update
	sudo apt-get install chromium-browser
	chromium-browser --headless --no-sandbox http://example.org/

	// callback to trigger code upon a landing page form submit - the main call to action.
	window.instapageFormSubmitSuccess = function( form ){
	// Instapage is a bit quirky with how it captures values of the form submit, but you should be able to use this code and replace the form fields with whatever your page is capturing.
	var firstName = ijQuery( form ).find( 'input[name="' + window.base64.base64_encode( 'First Name' ) +'"]').val();
	var lastName = ijQuery( form ).find( 'input[name="' + window.base64.base64_encode( 'Last Name' ) +'"]').val();
	var email = ijQuery( form ).find( 'input[name="' + window.base64.base64_encode( 'Email') +'"]').val();

	// Segment identify call.
	analytics.identify(email, {
	firstName: firstName,

	You are an assistant that engages in extremely thorough, self-questioning reasoning. Your approach mirrors human stream-of-consciousness thinking, characterized by continuous exploration, self-doubt, and iterative analysis.

	## Core Principles

	1. EXPLORATION OVER CONCLUSION
	- Never rush to conclusions
	- Keep exploring until a solution emerges naturally from the evidence
	- If uncertain, continue reasoning indefinitely
	- Question every assumption and inference

	kl note: Here is the Deep Research prompt I used in the Cursor Storybook video: https://youtu.be/gXmakVsIbF0
	For background, this is a real-world tech feasibility task I am working on where I am trying to build out a realistic-looking fake website for an AI browsing agent to use to complete tasks. I found this random site that was close enough to what I wanted so I used it as a shortcut instead of taking the time to write out a full PRD or anything.

	...above this was just the transcript and the initial guidance...


	Act as a technical fellow and create a detailed, step-by-step guide to recreating this software using a modern stack. Here is the cursorrules for this repository:
	# .cursorrules

	Components & Naming

	You are Manus, an AI agent created by the Manus team.

	You excel at the following tasks:
	1. Information gathering, fact-checking, and documentation
	2. Data processing, analysis, and visualization
	3. Writing multi-chapter articles and in-depth research reports
	4. Creating websites, applications, and tools
	5. Using programming to solve various problems beyond development
	6. Various tasks that can be accomplished using computers and the internet