alexknowshtml

name	tags	description
plant-seed	project seeds	Plant a seed - context-based instant capture with optional depth

Plant Seed Command

Plant ideas you want to tend - instant capture from context, with optional enrichment.

dhh

# Create a new worktree and branch from within current git directory.
ga() {
  if [[ -z "$1" ]]; then
    echo "Usage: ga [branch name]"
    exit 1
  fi

  local branch="$1"
  local base="$(basename "$PWD")"
  local path="../${base}--${branch}"

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!

vgel

# /// script
# dependencies = [ "transformers", "accelerate" ]
# ///

# run on 2xH200 rented from primeintellect.ai

import gc

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer

Madhav-MKNC

import anthropic
import os
import sys
from termcolor import colored
from dotenv import load_dotenv


class ClaudeAgent:
    def __init__(self, api_key=None, model="claude-3-7-sonnet-20250219", max_tokens=4000):
        """Initialize the Claude agent with API key and model."""

ivanfioravanti

#!/usr/bin/env bash

# Default values for percentages
DEFAULT_WIRED_LIMIT_PERCENT=85
DEFAULT_WIRED_LWM_PERCENT=75

# Read input parameters or use default values
WIRED_LIMIT_PERCENT=${1:-$DEFAULT_WIRED_LIMIT_PERCENT}
WIRED_LWM_PERCENT=${2:-$DEFAULT_WIRED_LWM_PERCENT}

uogbuji

I've been using llama.cpp on Mac Silicon for months now, and my brother, Chimezie has been nudging me to give MLX a go. I finally set aside time today to get started, with an eventual goal of adding support for MLX model loading & usage in OgbujiPT. I've been warned it's rough around the edges, but it's been stimulating to play with. I thought I'd capture some of my notes, including some pitfalls I ran into, which might help anyone else trying to get into MLX in its current state.

As a quick bit of background I'll mention that MLX is very interesting because honestly, Apple has the most coherently engineered consumer and small-business-level hardware for AI workloads, with Apple Silicon and its unified memory. The news lately is all about Apple's AI fumbles, but I suspect their clever plan is to empower a community of developers to take the arrows in their back and build things out for them. The MLX

mmyoji

Install pnpm

see https://pnpm.io/installation

$ pnpm --version

corepack will NOT be distributed with Node.js v25>= https://nodejs.org/docs/latest-v24.x/api/corepack.html

april

#!/bin/bash

# this forces Arena into full screen mode on startup, set back to 3 to reset
# note that if you go into the Arena "Graphics" preference panel, it will reset all of these
# and you will need to run these commands again
defaults write com.wizards.mtga "Screenmanager Fullscreen mode" -integer 0
defaults write com.wizards.mtga "Screenmanager Resolution Use Native" -integer 0

# you can also replace the long complicated integer bit with any other scaled 16:9
# resolution your system supports.

dixneuf19

Setup python, pip, virtualenv and virtualwrapper, with zsh on a new machine

Strongly inspired by https://gist.github.com/heymonkeyriot/9a2f429caff5c091d5429666fa080403.

Installing Python & Pip

On Ubuntu :

sudo apt install python3 python3-pip