Deblank: Tool to Strip Code Formatting for LLM Token Reduction

What Deblank Does

Deblank is a preprocessing tool that removes code formatting (indentation, whitespace, line breaks) before sending code to LLMs, with a postprocessing step to restore readability. The transformation is bidirectional and AST-safe.

Performance Results

In evaluations across several models (DeepSeek-V3, Claude, Gemini, etc.):

• ~30% token reduction for languages like Java and C++
• ~9% token reduction for Python
• Negligible impact on Pass@1 accuracy for code completion
• Average latency: ~76ms

Supported Languages and Features

• Python, Java, C/C++, C#, JavaScript/TypeScript, and Go
• Handles incomplete snippets reasonably well
• Useful for fill-in-the-middle workflows

Getting Started

The project is open-sourced with these resources:

• GitHub: https://github.com/anpl-code/Deblank
• Paper: https://arxiv.org/abs/2508.13666
• Docker: docker pull zhangcen456/deblank:latest

This type of token optimization can be particularly useful when working with context-limited LLMs or when processing large codebases, though the impact varies by language due to differences in formatting conventions.