RPG: A Repository Planning Graph for Unified and Scalable Codebase
  Generation
Authors: name: Jane Luo, name: Xin Zhang, name: Steven Liu, name: Jie Wu, name: Yiming Huang, name: Yangyu Huang, name: Chengyu Yin, name: Ying Xin, name: Jianfeng Liu, name: Yuefeng Zhan, name: Hao Sun, name: Qi Chen, name: Scarlett Li, name: Mao Yang

Large language models excel at function- and file-level code generation, yet
generating complete repositories from scratch remains a fundamental challenge.
This process demands coherent and reliable planning across proposal- and
implementation-level stages, while natural language, due to its ambiguity and
verbosity, is ill-suited for faithfully representing complex software
structures. To address this, we introduce the Repository Planning Graph (RPG),
a persistent representation that unifies proposal- and implementation-level
planning by encoding capabilities, file structures, data flows, and functions
in one graph. RPG replaces ambiguous natural language with an explicit
blueprint, enabling long-horizon planning and scalable repository generation.
Building on RPG, we develop ZeroRepo, a graph-driven framework for repository
generation from scratch. It operates in three stages: proposal-level planning
and implementation-level refinement to construct the graph, followed by
graph-guided code generation with test validation. To evaluate this setting, we
construct RepoCraft, a benchmark of six real-world projects with 1,052 tasks.
On RepoCraft, ZeroRepo produces repositories averaging nearly 36K LOC, roughly
3.9times the strongest baseline (Claude Code) and about 64times other
baselines. It attains 81.5% functional coverage and a 69.7% pass rate,
exceeding Claude Code by 27.3 and 35.8 percentage points, respectively. Further
analysis shows that RPG models complex dependencies, enables progressively more
sophisticated planning through near-linear scaling, and enhances LLM
understanding of repositories, thereby accelerating agent localization.