lijie2000

April 2026 TLDR setup for Ollama + Gemma 4 on a Mac mini (Apple Silicon) — auto-start, preload, and keep-alive

April 2026 TLDR Setup for Ollama + Gemma 4 on a Mac mini (Apple Silicon)

Prerequisites

• Mac mini with Apple Silicon (M1/M2/M3/M4/M5)
• At least 16GB unified memory for Gemma 4 (default 8B)
• macOS with Homebrew installed

lijie2000

LLM Wiki

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.

The core idea

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.

lijie2000

#!/bin/bash
# 智能session命名：使用当前目录名或自定义名称
if [ -z "$1" ]; then
  SESSION_NAME=$(basename "$PWD" | tr '.' '-' | tr ' ' '-')
else
  SESSION_NAME=$1
fi

# 检查session是否已存在
tmux has-session -t "$SESSION_NAME" 2>/dev/null

lijie2000

WSL 2 + Windows Terminal + Oh My Zsh + Powerlevel10k

This gist takes heavy inspiration from kevin-smets / iterm2-solarized.md gist for iTerm2.

Windows Subsystem for Linux 2 (WSL 2)

The first thing that you will want to do is install WSL 2 and a Linux distro.

lijie2000

"""
The most atomic way to train and inference 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

lijie2000

BOLT.NEW MEGA PROMPT - One-Shot Application Generator

Based on 38,787 words of Bolt.new expert insights and best practices

SYSTEM CONTEXT

You are an expert full-stack developer with deep knowledge of Bolt.new, modern web frameworks, and rapid application development. You have studied extensive tutorials covering authentication, databases, payments, deployment, and AI integration. Your goal is to create production-ready applications in a single prompt using industry best practices.

CORE PRINCIPLES FROM BOLT.NEW EXPERTS

1. ENHANCED PROMPTING STRATEGY

• Always use the "Enhanced Prompt" feature in Bolt.new before building

lijie2000

[Project Name]

Every time you choose to apply a rule(s), explicitly state the rule(s) in the output. You can abbreviate the rule description to a single word or phrase.

Project Context

[Brief description ]

• [more description]
• [more description]
• [more description]

lijie2000

import { useSyncExternalStore } from "react";
// For more on the useSyncExternalStore hook, see https://react.dev/reference/react/useSyncExternalStore

// The code is almost identical to the source code of zustand, without types and some features stripped out.
// Check the links to see the references in the source code.
// The links are referencing the v5 of the library. If you plan on reading the source code yourself v5 is the best way to start. 
// The current v4 version contains lot of deprecated code and extra stuff that makes it hard to reason about if you're new to this.

// https://github.com/pmndrs/zustand/blob/fe47d3e6c6671dbfb9856fda52cb5a3a855d97a6/src/vanilla.ts#L57-L94
function createStore(createState) {

lijie2000

package br.com.zup.edu.app2.xxx.samples.aws.sqs;

import br.com.zup.edu.app2.xxx.samples.aws.sqs.model.Customer;
import br.com.zup.edu.app2.xxx.samples.aws.sqs.model.CustomerRepository;
import io.awspring.cloud.messaging.listener.SqsMessageDeletionPolicy;
import io.awspring.cloud.messaging.listener.annotation.SqsListener;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.boot.autoconfigure.condition.ConditionalOnProperty;
import org.springframework.messaging.handler.annotation.Header;

lijie2000

node: Platform built on V8 to build network applications
git: Distributed revision control system
wget: Internet file retriever
yarn: JavaScript package manager
python3: Interpreted, interactive, object-oriented programming language
coreutils: GNU File, Shell, and Text utilities
pkg-config: Manage compile and link flags for libraries
chromedriver: Tool for automated testing of webapps across many browsers
awscli: Official Amazon AWS command-line interface
automake: Tool for generating GNU Standards-compliant Makefiles