mirror of
https://github.com/YerbaPage/LongCodeZip.git
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80 lines
2.9 KiB
Markdown
80 lines
2.9 KiB
Markdown
<div align="center">
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<img src="assets/logo.png" alt="LongCodeZip Logo" width="200"/>
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[](https://arxiv.org/abs/2510.00446) [](https://conf.researchr.org/details/ase-2025/ase-2025-papers/121/LongCodeZip-Compress-Long-Context-for-Code-Language-Models) [](https://www.python.org/downloads/release/python-397/) [](https://github.com/YerbaPage/LongCodeZip) [](LICENSE)
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</div>
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# LongCodeZip
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This repository is the official implementation of LongCodeZip, a novel two-stage long code compression method. Our paper "LongCodeZip: Compress Long Context for Code Language Models" has been accepted to **ASE 2025**.
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## Method Overview
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LongCodeZip introduces a two-stage code compression framework specifically designed for code LLMs:
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1. **Coarse-grained Compression**: Function-based chunking and ranking using conditional perplexity with respect to the query to select the most relevant functions.
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2. **Fine-grained Compression**: Entropy-based block detection combined with 0/1 knapsack optimization to maximize relevance within adaptive token budgets.
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The method is plug-and-play and can be integrated with existing code LLMs to achieve significant compression ratios while maintaining or improving task performance.
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## Installation
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You can install directly from the GitHub repository:
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```bash
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pip install git+https://github.com/YerbaPage/LongCodeZip.git
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```
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Or clone and install in development mode:
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```bash
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git clone https://github.com/YerbaPage/LongCodeZip.git
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cd LongCodeZip
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pip install -e .
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```
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## Quick Demo
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We provide a simple demo (`demo.py`) to help you get started with LongCodeZip:
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```bash
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python demo.py
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```
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## Basic Example
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```python
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from longcodezip import LongCodeZip
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# Initialize the compressor
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compressor = LongCodeZip(model_name="Qwen/Qwen2.5-Coder-7B-Instruct")
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# Compress code with a query
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result = compressor.compress_code_file(
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code=<your_code_string>,
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query=<your_query>,
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instruction=<your_instruction>,
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rate=0.5, # Keep 50% of tokens
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rank_only=False, # Set to True to only rank and select contexts without fine-grained compression
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)
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# Access compressed results
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compressed_code = result['compressed_code']
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compressed_prompt = result['compressed_prompt'] # Full prompt with instruction
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compression_ratio = result['compression_ratio']
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```
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## References
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```bibtex
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@article{shi2025longcodezip,
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title={LongCodeZip: Compress Long Context for Code Language Models},
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author={Shi, Yuling and Qian, Yichun and Zhang, Hongyu and Shen, Beijun and Gu, Xiaodong},
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journal={arXiv preprint arXiv:2510.00446},
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year={2025}
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}
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``` |