AI LLM Token Counter and Text Analyzer

This application is a specialized client-side utility designed for developers and prompt engineers to analyze text input for Large Language Models (LLMs).

Visual Design and Layout

• Color Palette: A professional, high-contrast palette featuring a slate-grey sidebar, crisp white workspace, and a spectrum of soft pastels (mint, lavender, peach) for highlighting tokens.
• Layout Structure:
  • Header: Contains the app title, a model selection dropdown (e.g., GPT-4o, Claude 3.5), and a reset button.
  • Main Workspace: A split-screen layout with an 'Input Editor' on the left and a 'Visual Tokenization' preview on the right.
  • Footer: A live statistics bar showing character count, word count, and current token count.

Animations

• Token Rendering: As the user types, tokens are rendered into the preview pane with a subtle 'fade-in' animation.
• Dynamic Updates: Token counts animate from the old value to the new value using a count-up transition effect.

Interactive Features

1. Live Input Processing: The application uses debounced event listeners to re-tokenize the input text in real-time without refreshing the page.
2. Color-Coded Token Highlighting: Each token segment is wrapped in a span with a unique background color, alternating to show clearly where one token ends and the next begins.
3. Model Selection Engine: Users can toggle between different tokenization standards (e.g., cl100k_base or p50k_base) to ensure accuracy across different model families.
4. Copy-to-Clipboard: A single-click feature to copy the tokenized array or the original text for prompt optimization.
5. Dark/Light Mode: A toggle to switch between a high-visibility light mode and a low-light dark mode for late-night coding sessions.

Technical Implementation

• Performance: Entirely client-side using Web Workers to perform tokenization off the main thread, ensuring the UI remains responsive even with large blocks of text.
• State Management: A lightweight local state stores the user's input and current model settings.