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Docker Commands, Help & Tips

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arianvp

Native Secure Enclave backed ssh keys on MacOS

It turns out that MacOS Tahoe can generate and use secure-enclave backed SSH keys! This replaces projects like https://github.com/maxgoedjen/secretive

There is a shared library /usr/lib/ssh-keychain.dylib that traditionally has been used to add smartcard support to ssh by implementing PKCS11Provider interface. However since recently it also implements SecurityKeyProivder which supports loading keys directly from the secure enclave! SecurityKeyProvider is what is normally used to talk to FIDO2 devices (e.g. libfido2 can be used to talk to your Yubikey). However you can now use it to talk to your Secure Enclave instead!

ndavison

import requests
import yaml
import re
import json
import time
import logging
import sys
from argparse import ArgumentParser

steipete

build swagent swift cli and test it yourself until it works. use this development key for testing with openai API:

---

1) Docs — the exact contract (Responses API, tools, streaming, chaining)

Endpoints

• Create/continue a response: POST https://api.openai.com/v1/responses

tzachbon

Add a codex shell function to ~/.zshrc (or ~/.bashrc) that:

1. Always runs codex in full-auto / yolo mode (--dangerously-bypass-approvals-and-sandbox)
2. Supports a -w [name] flag that creates a git worktree at ~/.worktrees/<name> from the current HEAD, then opens codex inside it. If no name is given, auto-generates one from the current timestamp (e.g. codex-20260307-143022).

Add this to your shell config:

allanjamesvestal

I’m building a browser-based web tool for internal use by journalists in a newsroom. This tool should have a text box where users can enter the text of an article, and it should then extract all the quotes from that article.

Each quote should be displayed, one after the other, and the tool should let users write in the speaker for each one.

The tool should only use HTML, CSS and basic JavaScript. (Do not use any external JavaScript or CSS dependencies.) It should be able to run without needing to send any data to the Internet.

Ask me any additional questions you need to get started creating this code, then generate a draft HTML/JavaScript/CSS tool.

karpathy

"""
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

walkerke

# remotes::install_github("walkerke/mapgl")
library(mapgl)

# CYBERPUNK 2125 - Ultra-striking neon palette
# Deep blacks + electric neons for that Blade Runner / Akira vibe
cyberpunk_2125 <- c(
  "#000000", # Pure black (shadows)
  "#0a0e27", # Deep space blue (dark areas)
  "#1a1a2e", # Dark navy (buildings)
  "#16213e", # Midnight blue

ayuxsec

latest_version=$(curl "https://go.dev/dl/?mode=json" -s | jq -r ".[0].version")
command -v jq || sudo apt install jq
echo "[+] Installing ${latest_version}"
wget "https://go.dev/dl/"${latest_version}".linux-amd64.tar.gz"
sudo rm -rf /usr/local/go
sudo tar -C /usr/local -xzf "${latest_version}".linux-amd64.tar.gz
/usr/local/go/bin/go version

# echo """
# # Added by go installer