Qinyu Luo
2024
RepoAgent: An LLM-Powered Open-Source Framework for Repository-level Code Documentation Generation
Qinyu Luo
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Yining Ye
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Shihao Liang
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Zhong Zhang
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Yujia Qin
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Yaxi Lu
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Yesai Wu
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Xin Cong
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Yankai Lin
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Yingli Zhang
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Xiaoyin Che
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Zhiyuan Liu
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Maosong Sun
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
Generative models have demonstrated considerable potential in software engineering, particularly in tasks such as code generation and debugging. However, their utilization in the domain of code documentation generation remains underexplored. To this end, we introduce RepoAgent, a large language model powered open-source framework aimed at proactively generating, maintaining, and updating code documentation. Through both qualitative and quantitative evaluations, we have validated the effectiveness of our approach, showing that RepoAgent excels in generating high-quality repository-level documentation. The code and results are publicly accessible at https://github.com/OpenBMB/RepoAgent.
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Co-authors
- Yining Ye 1
- Shihao Liang 1
- Zhong Zhang 1
- Yujia Qin 1
- Yaxi Lu 1
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