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| #!/usr/bin/env python3 | |
| """ | |
| A simple CLI tool to control and monitor the ZKETECH EBC-A20 battery | |
| tester from https://www.zketech.com/en/ | |
| It can trigger charge or discharge as well as perform charge-discharge | |
| cycles to measure battery capacity. | |
| Currenly only the CC (Constant Current) load type is implemented, the | |
| CP (Constant Power) load type is a simple fixme. Additionally, some |
| EMAILRECIPIANT = "myemail@gmail.com"; | |
| function agendaEmail() { | |
| let dateOptions = { weekday: 'long', month: 'long', day: 'numeric'}; | |
| let timeOptions = { hour12:true, hour:'numeric', minute:'numeric'}; | |
| var StartDate = new Date(); |
| #requires -modules "Microsoft.PowerApps.Administration.PowerShell" | |
| function Get-AgentInventory | |
| { | |
| [CmdletBinding()] | |
| param | |
| ( | |
| ) | |
| begin |
A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.
| <!DOCTYPE html> | |
| <html> | |
| <head> | |
| <title></title> | |
| <meta charset="utf-8" /> | |
| <script src="Scripts/jquery-1.9.1.min.js"></script> | |
| <link href="Content/bootstrap.min.css" rel="stylesheet" /> | |
| <script src="Scripts/isRockFx.js"></script> | |
| <script> | |
| $(function () { |
Strategy: Stop grinding 500+ random LeetCode problems. Master these 14 Core DSA Patterns across the top Blind 75 questions to solve 90% of technical coding interviews at top product companies.
| Phase | Timeline | Focus Area | Goal |
| 1 | |
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| lolSnes nds ANY v1.0 Arisotura http://lolsnes.kuribo64.net/lolsnes.7z lolsnes.7z 0 https://db.universal-team.net/assets/images/images/lolsnes.png lolSnes.nds lolsnes/lolSnes.nds | |
| MicroCityNDS nds ANY v1.0 AzizBgBoss https://github.com/AzizBgBoss/MicroCityNDS/releases/download/v1.0/MicroCityNDS.nds MicroCityNDS.nds 224256 https://avatars.githubusercontent.com/u/83554824?v=4&size=128 | |
| TerrariaDS nds ANY 0.2 AzizBgBoss https://github.com/AzizBgBoss/TerrariaDS/releases/download/0.2/TerrariaDS.nds TerrariaDS.nds 16017408 https://raw.githubusercontent.com/AzizBgBoss/TerrariaDS/refs/heads/main/media/logo.png | |
| Derailed! nds ANY 1.1alpha AzizBgBoss https://github.com/AzizBgBoss/derailed/releases/download/1.1alpha/derailed.nds derailed.nds 697344 https://raw.githubusercontent.com/AzizBgBoss/derailed/refs |
| creality_key: 713362755e74316e71665a2870662431 | |
| creality_encryption_key: 484043466b526e7a404b4174424a7032 | |
| bambu_key: 9A759CF2C4F7CAFF222CB9769B41BC96 |