Charles S. Givre cgivre

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.

☕️ Cursor IDE Configuration for Java Development

This guide shows how to configure Cursor IDE specifically for efficient Java development, leveraging powerful AI assistance, optimal settings, and essential extensions.

🧠 1. Enable Cursor AI (LLM Assistant)

Configure AI features via Command Palette (Cmd/Ctrl + K):

Installing PyICU, libpostal, pypostal on Mac OS X 10.14+

libicu-dev (PyICU dependency)

brew reinstall pkg-config icu4c

Apache Superset in the production environment

Visualising data helps in building a much deeper understanding of the data and fastens analytics around the data. There are several mature paid products available in the market. Recently, I explored an open-source product name Apache-Superset which I found a very upbeat product in this space. Some prominent features of Superset are:

A rich set of data visualisations
An easy-to-use interface for exploring and visualising data
Create and share dashboards

After reading about Superset, I wanted to try it, and as Superset is a python programming language based project, we can easily install it using pip, but I decided to set it up as a container based on Docker. Apache-Superset GitHub Repo contains code for building and running Superset as a container. Since I wan

	from flask import Flask, request
	from flask_restful import Api, Resource
	import osquery

	class User(Resource):
	@staticmethod
	def get():
	instance = osquery.SpawnInstance()
	instance.open()
	query = request.args.get('query', default='', type=str)

	public class BaseQueryValidator {
	private static List<String> extractTableAliases(SqlNode node) {
	final List<String> tables = new ArrayList<>();

	// If order by comes in the query.
	if (node.getKind().equals(SqlKind.ORDER_BY)) {
	// Retrieve exact select.
	node = ((SqlSelect) ((SqlOrderBy) node).query).getFrom();
	} else {
	node = ((SqlSelect) node).getFrom();

	import java.io.IOException;

	import ucar.nc2.Attribute;
	import ucar.nc2.Group;
	import ucar.nc2.NetcdfFile;
	import ucar.nc2.Variable;
	import ucar.nc2.iosp.hdf5.H5iosp;
	import ucar.nc2.util.DebugFlags;

	/**

	/**
	* Copyright 2016 Ambud Sharma
	* Licensed under the Apache License, Version 2.0 (the "License");
	* you may not use this file except in compliance with the License.
	* You may obtain a copy of the License at
	*
	* http://www.apache.org/licenses/LICENSE-2.0
	*
	* Unless required by applicable law or agreed to in writing, software
	* distributed under the License is distributed on an "AS IS" BASIS,

	package bdkosher.datetime;

	import java.util.Calendar;
	import static java.util.Calendar.*;
	import java.util.Date;
	import java.util.Locale;
	import java.util.SortedSet;
	import java.util.TimeZone;
	import java.util.TreeSet;


	<textarea name="my-xml-editor" data-editor="xml" rows="15"></textarea>
	...
	<textarea name="my-markdown-editor" data-editor="markdown" rows="15"></textarea>
	...

	<script src="//d1n0x3qji82z53.cloudfront.net/src-min-noconflict/ace.js"></script>
	<script>
	// Hook up ACE editor to all textareas with data-editor attribute
	$(function () {