ichim-david

Implement the following program completley and comprehensively. Meet or exceed the requiremenents. You may want to seperate the implementation into many files.

Overview

This document details the functional, technical, and user interface specifications for a feature-rich, interactive graph analysis and pathfinding tool implemented using HTML, CSS, and JavaScript. The system enables users to create, edit, analyze, and persist weighted graphs while providing powerful pathfinding and traversal algorithms, an advanced visualization interface, and intuitive multi-tab management.

Features Summary

Graph Interaction & Editing

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description
4.1 Beast Mode

You are an agent - please keep going until the user’s query is completely resolved, before ending your turn and yielding back to the user.

Your thinking should be thorough and so it's fine if it's very long. However, avoid unnecessary repetition and verbosity. You should be concise, but thorough.

You MUST iterate and keep going until the problem is solved.

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In-Depth Analysis of GitHub Copilot Chat (OSS)

https://github.com/microsoft/vscode-copilot-chat

This report provides a detailed examination of the Visual Studio Code Copilot Chat extension, based on an extensive review of the provided repository source code. It covers the project's architecture, core services, operational modes, and a granular look at the agent functionality.

1. Architectural Overview

The vscode-copilot-chat repository is a sophisticated monorepo that employs modern software engineering principles to deliver a complex AI-powered extension. Its architecture is designed for modularity, testability, and extensibility.

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╭──────────────────────────────────────────────────────────────╮
│ ● OpenAI Codex (research preview) v0.1.2505172129            │
╰──────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────────────────────────────╮
│ localhost session: b966636e1ecf42a59c8fef1192074e17          │
│ ↳ workdir: ~/vic/dev/bend                                    │
│ ↳ model: o3                                                  │
│ ↳ provider: openai                                           │
│ ↳ approval: suggest                                          │
╰──────────────────────────────────────────────────────────────╯

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// Can you make this faster? Ping me.

const escapeHtml = (function () {
  const serializer = new XMLSerializer ();
  const attr = document.createAttribute ( 'attr' );
  const re = /[&<>"]/;
  return function escapeHtml ( str ) {
    if ( !re.test ( str ) ) return str;
    attr.value = str;
    return serializer.serializeToString ( attr );

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#!/usr/bin/env bash
#
# concat.sh  [root-dir] [output-file]
#
# Squashes a whole codebase into one text file, skipping build artefacts:
#   • ignores node_modules, dist, .git, .turbo, .next, out
#   • omits lockfiles and *.min.* noise
#   • copies the result straight to the macOS clipboard (pbcopy)
#
# Example:

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Project Requirements Document: The Urlist Website

The following table outlines the detailed functional requirements of The Urlist website.

Requirement ID	Description	User Story	Expected Behavior/Outcome
FR001	Creating a New URL List	As a user, I want to be able to start a new, empty list so I can begin adding URLs.	The system should provide a clear way for the user to initiate the creation of a new list, potentially presenting an empty list view or an "add new list" button.
FR002	A

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Auto-Continue Extension for VS Code & Cursor

Quick Install Instructions for Auto-Continue Extension

1. Download the files from the gist (extension.ts, package.json, and README.md)

2. Create a new VS Code extension project:

   npm init vscode-extension

Choose TypeScript when prompted

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Which GGUF is right for me? (Opinionated)

Good question! I am collecting human data on how quantization affects outputs. See here for more information: ggml-org/llama.cpp#5962

In the meantime, use the largest that fully fits in your GPU. If you can comfortably fit Q4_K_S, try using a model with more parameters.

llama.cpp feature matrix

See the wiki upstream: https://github.com/ggerganov/llama.cpp/wiki/Feature-matrix

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<tutor_mode_instructions>
You are a friendly computer science tutor, and I am the student. Your role is to guide me through learning step by step.

- **Assess my knowledge**  
  - First, ask me my name and what I want to learn. Determine where to start based on my experience. Also ask me if there's anything I'm interested in that you can incorporate into the lessons (i.e. shows, hobbies, interests, etc).
  - Ask me these questions one a a time.

- **Teach using code**  
  - Teach me concepts in the chat window, and create files as "lessons" when you need to demonstrate something. Use the naming format 001-lesson-[lesson-slug], like 001-lesson-about-file.py, or whatever the equivalent is in the language I'm learning. Start with a 0-padded 3 digit number.
  - Write code and explain how to run it. When you are teaching me, do not run any commands for me. Just tell me what to run, and once you've taught me how to run something, encourage me to run commands myself. In the beginning, encourage me to share what I sa