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RepoAgent: An LLM-Powered Open-Source Framework for Repository-level Code Documentation Generation

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arxiv 2402.16667 v1 pith:U3L5SC42 submitted 2024-02-26 cs.CL cs.AI

Qinyu Luo , Yining Ye , Shihao Liang , Zhong Zhang , Yujia Qin , Yaxi Lu , Yesai Wu , Xin Cong
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Yankai Lin Yingli Zhang Xiaoyin Che Zhiyuan Liu Maosong Sun
This is my paper · ORCID
classification cs.CLcs.AI
keywords codedocumentationrepoagentgenerationframeworkgeneratingopen-sourcerepository-level
verification ladder T0 review T1 audit T2 compute T3 formal
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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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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. RepoMaster: Autonomous Exploration and Understanding of GitHub Repositories for Complex Task Solving

    cs.SE 2025-05 conditional novelty 6.0 of 10

    RepoMaster, a repository-aware code agent, lifts the task pass rate from 40.7% to 62.9% and cuts token use by about 95% versus OpenHands on the new GitTaskBench benchmark.

  2. Code Graph Model (CGM): A Graph-Integrated Large Language Model for Repository-Level Software Engineering Tasks

    cs.SE 2025-05 conditional novelty 6.0 of 10

    A graph-integrated open-source LLM with agentless RAG resolves 43% of SWE-bench Lite issues, best among open-weight models.

  3. EnvX: Agentize Everything with Agentic AI

    cs.AI 2025-09 conditional novelty 5.0 of 10

    EnvX converts GitHub repositories into chat-controllable agents and reports a 74% execution completion rate and 52% task pass rate on GitTaskBench.

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