Project P1

Tokenizer Visualizer Studio

Concept: Byte Pair Encoding & Character Offsets

Problem Statement

Users do not understand why short sentences can consume massive token counts, leading to unexpected API bills and context overflow.

What Concept It Teaches

It teaches subword tokenization splits, Byte Pair Encoding algorithms, and character offset mapping mechanics.

Why This Matters

Tokenization is the gateway to any transformer block. Inefficient tokenization causes cost inflation and degrades model performance.

System Architecture

Client-side pipeline taking raw string inputs, processing them through a BPE tokenizer, and displaying visual highlights of character offsets.

User Input StringBPE Tokenizer EngineToken HighlightsToken ID Array

Execution Data Flow

  • 1. User enters string in workspace.
  • 2. Tokenizer maps chars to subword bytes.
  • 3. Tokenizer returns vocabulary IDs and boundaries.
  • 4. UI colors individual tokens dynamically.

Tech Stack

TypeScriptReactCSS Variables

Implementation Plan

  • 1.1. Build a local BPE mapping mock dataset.
  • 2.2. Create custom regex boundaries splits.
  • 3.3. Style token highlights using HSL colors.

Technical Interview Defense

Defense Concept:

Why does a tokenizer vocabulary size mismatch cause out-of-vocabulary errors?

Source & Deployment Links

GitHub Repo:GitHub
Live Demo:Live Demo
Interactive Lab:Lab Route
Verification Audit
Repository Checked: Yes
Repository Exists: Yes
Live Demo Verified: Yes
Demo Exists: Yes