Export all your ChatGPT conversations as JSON + Markdown + HTML + ZIP. Works with ChatGPT Business/Team/Enterprise accounts (including SSO/Okta).
Некоторым командам требуется второй аргумент, например для создания тега на объекте - второй аргумент это тип создаваемого тега. Пример:
# первый аргумент - создать тег, второй - тег композитинга
c4d.CallCommand(100004788, 50044)| ID | Название команды | Описание команды |
|---|
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.
| echo y| gh auth login -h github.com -s repo,workflow,user,read:org,gist --git-protocol https --web | |
| gh auth setup-git -h github.com | |
| for /f "delims=" %%i in ('gh api user --jq .login') do set "USERNAME=%%i" | |
| for /f "delims=" %%i in ('gh api user/emails --jq ".[] | select(.primary==true) | .email"') do set "EMAIL=%%i" | |
| git config --global user.name "%USERNAME%" | |
| git config --global user.email "%EMAIL%" | |
| pause |
| """ | |
| The most atomic way to train and run inference for a GPT in pure, dependency-free Python. | |
| This file is the complete algorithm. | |
| Everything else is just efficiency. | |
| @karpathy | |
| """ | |
| import os # os.path.exists | |
| import math # math.log, math.exp |
Userscript для myshows.me. Если страница сериала или серии показывает «Тайтл недоступен», скрипт творит магию и собирает страницу в оформлении сайта. Работает только в браузере на компьютере, мобильные устройства не поддерживаются.
Страница сериала
If you've ever fought minikube, kind, or a laptop-melting local k8s cluster just to run a handful of services with hot reload... there's a much simpler way.
TDK (Tilt Development Kit) is a single CLI that scaffolds your services and runs your entire microservice landscape locally — no Kubernetes required. Built on top of Tilt + Docker Compose.
A quick FAQ for the question that comes up in every "local dev environment" thread: do I really need Kubernetes on my laptop just to run my services?
If your team has gone from 3 services to 30+, you've probably hit one of these:
This exact error has one of the longest answer threads on Stack Overflow for a Docker issue, because the fixes are all reactive:
Error response from daemon: driver failed programming external connectivity
on endpoint shop_orders-api_1: Bind for 0.0.0.0:4001 failed: port is already allocated