Zhipu Company has officially launched Zread.ai, a development efficiency tool based on large models, aiming to solve common pain points for developers in taking over old projects, writing documentation, and understanding open-source projects through AI technology. The core features of Zread.ai include one-click code comprehension, knowledge generation, and collaboration facilitation, which can significantly improve development efficiency.
The core functions of Zread.ai are mainly reflected in three aspects: deep learning of open-source projects, quick takeover of historical code repositories, and the construction of team knowledge collaboration systems. Developers can input any GitHub repository link, allowing Zread to generate a Guide that includes architectural analysis, module explanations, and design patterns. It also supports multi-repository comparison, hierarchical interpretation, and the logical decomposition of GitHub Trending projects. In addition, Zread can automatically organize project structure and module dependencies, generating systematic documentation to help developers quickly get up to speed, even with complex code. Zread also provides contributor maps, community comment aggregation, interactive annotations and Q&A, and supports uploading private projects to build an internal knowledge base and technical documentation system for the team.
During the development of Zread.ai, Zhipu Company evaluated multiple large language models and finally chose GLM-4.5 as the core foundation for code analysis and document generation. GLM-4.5 excels in code comprehension capabilities, low hallucination, support for Deep Research, and Agent capability adaptation. It can accurately identify the calling relationships between code modules, architectural hierarchy, and dependency structures, providing a solid foundation for generating high-quality technical documents and project introductions. In complex code scenarios, GLM-4.5 has a high level of output stability, significantly reducing cases where code intent is misunderstood or logic is fabricated, making it especially suitable for code interpretation and technical Q&A tasks. For large code repositories, GLM-4.5 can perform multi-round in-depth analysis, combining context and semantic clues to ask follow-up questions and dig deeper into key technical designs, helping developers obtain more insightful answers. In terms of long-context understanding and response speed and accuracy for technical Q&A, GLM-4.5 also performs stably, enhancing the overall user experience.
Using Zread.ai is very simple, requiring only four steps to get started quickly. First, open Zread.ai and enter a GitHub repository link; the system will automatically identify the code structure and core components. Next, the system will generate a project introduction (Guide), including architectural breakdown, module explanations, and design paradigms. Then, developers can use the "Ask" feature to ask about key technical details, supporting in-depth code Q&A and cross-module tracking. Finally, upload a private project to generate a team-specific knowledge base, building sustainable document assets for the project.
Zhipu Company stated that GLM-4.5 is not only a model provider but also the core support for Zread.ai to achieve "reading code, generating knowledge, and serving collaboration." In the future, Zhipu will continue to explore the deep application of GLM-4.5 in scenarios such as agent integration and team knowledge collaboration, providing developers with more powerful tools to enhance development efficiency.