The GPT Academic Software Project, managed by the organization binary-husky, is designed to enhance the usability of large language models (LLMs) like GPT and GLM for academic purposes. It features a modular architecture that supports custom shortcut buttons, function plugins, and capabilities for analyzing and translating academic papers written in multiple programming languages. The project's integration with various Chinese LLMs indicates its targeted demographic and specialized use cases. With a significant following on GitHub, evidenced by its stars, forks, and watchers, the project maintains a high level of community engagement and interest.
The project is actively developed with a clear focus on expanding its functionalities and improving user experience. Recent issues and pull requests indicate ongoing efforts to integrate more models, enhance interface capabilities, and address user-reported bugs. The trajectory suggests continued enhancements in model handling, user interface improvements, and possibly expanding the scope to include more languages and model types.
The quick closure of issues such as #1721, #1720, and #1719 demonstrates an active response to operational bugs and integration challenges. This responsiveness is crucial for maintaining user trust and software reliability.
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crazy_functions/PDF批量翻译.py demonstrate good software engineering practices such as modular design and robust error handling.The GPT Academic Software Project is robustly maintained with an active community of developers addressing both foundational needs and advanced features. While there are areas requiring attention—such as security practices—the project’s trajectory remains promising with its continuous enhancements aimed at improving functionality and user experience in academic settings.
| Developer | Avatar | Branches | PRs | Commits | Files | Changes |
|---|---|---|---|---|---|---|
| binary-husky |  |
2 | 1/1/0 | 23 | 40 | 2963 |
| Yuki |  |
2 | 2/1/1 | 2 | 1 | 98 |
| zyren123 |  |
1 | 1/1/0 | 1 | 1 | 80 |
| hmp |  |
1 | 0/0/0 | 1 | 3 | 78 |
| OREEkE |  |
1 | 2/2/0 | 2 | 2 | 41 |
| Menghuan1918 |  |
1 | 1/1/0 | 1 | 4 | 22 |
| awwaawwa |  |
1 | 2/1/0 | 1 | 2 | 21 |
| iluem |  |
1 | 0/0/0 | 2 | 2 | 13 |
| XIao |  |
1 | 2/2/0 | 1 | 1 | 9 |
| owo |  |
1 | 2/2/0 | 2 | 2 | 4 |
| jiangfy-ihep |  |
1 | 1/1/0 | 1 | 1 | 2 |
| Wbscript (wbs306) | 0 | 0/0/1 | 0 | 0 | 0 | |
| None (Skyzayre) | 0 | 0/1/0 | 0 | 0 | 0 |
PRs: created by that dev and opened/merged/closed-unmerged during the period
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The GPT Academic Software Project, managed by the organization binary-husky, is a robust and dynamic platform designed to enhance the academic interaction with large language models such as GPT and GLM. It focuses on academic tasks like reading, polishing, and writing papers, and supports a variety of languages including Python and C++. The project's modular design allows for significant customization through plugins and has features like PDF translation and summarization. With a substantial community engagement indicated by its GitHub statistics (55,029 stars, 6,921 forks), the project is well-received and actively maintained.
The current state of the project shows a healthy mix of ongoing development with new features being added and existing issues being addressed promptly. This suggests a positive trajectory with potential for further growth and enhancement, particularly in areas like model integration and user interface improvements.
The project's development is characterized by frequent updates and active issue resolution, which is crucial for keeping up with the fast-paced advancements in AI and machine learning fields. The responsiveness to issues and pull requests indicates a committed team that is focused on improving user experience and expanding the software's capabilities.
Given the focus on academic enhancements, the software has significant potential in educational institutions and among researchers. The ability to integrate with various large language models and handle multiple languages makes it a versatile tool that could be adopted widely across different regions and academic disciplines.
The development team shows a high level of collaboration with multiple members contributing to different aspects of the project. The lead developer, binary-husky, is notably active, suggesting strong leadership and commitment. This collaborative environment is essential for innovative solutions and rapid problem-solving.
While the open-source nature of the project encourages wide adoption and community contributions, it also necessitates ongoing maintenance and support which can be resource-intensive. However, the strategic benefits of establishing a robust platform in the growing field of AI-powered academic tools likely outweigh these costs.
Enhance Documentation: Improving documentation, especially around setup and integration points like CUDA versions or model specifications, could reduce user issues and lower support queries.
Security Enhancements: Addressing security concerns such as hardcoded secrets in pull requests should be a priority to protect user data and maintain trust.
Expand Language Support: While the project already supports multiple languages, further expanding this could increase its applicability in non-English speaking regions, broadening its market.
Increase Community Involvement: Encouraging more community contributions through hackathons or open contribution days could accelerate development and bring in fresh ideas.
Focus on Usability: Simplifying the user interface and enhancing user guides could make the software more accessible to non-technical users, potentially increasing its user base.
The GPT Academic Software Project is well-positioned to become a leading tool in AI-powered academic research and writing. With its active development team, strong community engagement, and continuous improvements, it holds promising potential for widespread adoption in academic settings globally. Strategic enhancements in documentation, security, language support, community involvement, and usability will further solidify its position in the market.
| Developer | Avatar | Branches | PRs | Commits | Files | Changes |
|---|---|---|---|---|---|---|
| binary-husky | |
2 | 1/1/0 | 23 | 40 | 2963 |
| Yuki | |
2 | 2/1/1 | 2 | 1 | 98 |
| zyren123 | |
1 | 1/1/0 | 1 | 1 | 80 |
| hmp | |
1 | 0/0/0 | 1 | 3 | 78 |
| OREEkE | |
1 | 2/2/0 | 2 | 2 | 41 |
| Menghuan1918 | |
1 | 1/1/0 | 1 | 4 | 22 |
| awwaawwa | |
1 | 2/1/0 | 1 | 2 | 21 |
| iluem | |
1 | 0/0/0 | 2 | 2 | 13 |
| XIao | |
1 | 2/2/0 | 1 | 1 | 9 |
| owo | |
1 | 2/2/0 | 2 | 2 | 4 |
| jiangfy-ihep | |
1 | 1/1/0 | 1 | 1 | 2 |
| Wbscript (wbs306) | 0 | 0/0/1 | 0 | 0 | 0 | |
| None (Skyzayre) | 0 | 0/1/0 | 0 | 0 | 0 |
PRs: created by that dev and opened/merged/closed-unmerged during the period
The following issues were closed recently:
Closed 0 days ago. It addressed adding new OpenAI project API key patterns due to changes from OpenAI.
Closed 0 days ago. It fixed an issue where an argument 'a' was missing in the report_exception function definition.
Closed 0 days ago. It resolved an issue where 'schema_str' was used before being defined in an else statement.
Closed 1 day ago. It was about an exception encountered while configuring Azure's GPT4 model.
The open issues show a mix of feature requests and bugs that indicate active development and user engagement with the software. Notably, there are requests for better integration with other tools, improvements in handling AI models (especially vision-related), and enhancements in usability by allowing model specification in basic functionalities. The bugs reported suggest areas where users are facing challenges, particularly with GPU detection, chat history retention, and translation tasks. Addressing these issues would likely improve user satisfaction and broaden the software's applicability.
The recently closed issues indicate responsiveness from maintainers to fix problems quickly, particularly those related to API key patterns and function argument definitions. This responsiveness is crucial for maintaining trust among users and ensuring that the software remains reliable.
report_exceptionThe repository has several open pull requests that address significant updates and feature additions. The most notable concern is the presence of hardcoded secrets in PR #1711, which poses a security risk and needs immediate attention. Closed pull requests indicate active development and maintenance of the project. However, some features have been closed without merging, which may require revisiting if they are still needed. Recent merges show progress in integrating new models and fixing bugs.
The project in question is GPT 学术优化 (GPT Academic), maintained by the organization binary-husky. It is designed to provide a practical interactive interface for large language models such as GPT and GLM, with a particular focus on enhancing the experience of reading, polishing, and writing academic papers. The project boasts a modular design that supports custom shortcut buttons and function plugins, and it can analyze and translate projects written in Python, C++, and other languages. It also features translation and summarization capabilities for PDF/LaTex papers, parallel inquiries to various LLM models, and support for local models like chatglm3. The project integrates with multiple Chinese large language models such as Qwen, GLM, DeepseekCoder, etc. As of the last update, the project has a considerable amount of stars (55029), forks (6921), and watchers (232) on GitHub, indicating a high level of interest and engagement from the community. It is licensed under the GNU General Public License v3.0.
The overall state of the project seems to be active and evolving, with frequent updates and new features being added regularly. The trajectory suggests a focus on expanding compatibility with various language models and improving user experience for academic purposes.
From the recent activities of the development team:
binary-husky appears to be the most active contributor, touching upon many aspects of the project including configuration files, documentation updates, feature enhancements, and bug fixes. This individual's work seems central to maintaining the project's momentum.
Keycatowo, oreeke, binaryYuki, zyren123, Menghuan1918, Kilig947, and jiangfy-ihep have also made significant contributions through commits or pull requests that address specific issues or add new features to the project. Their work often focuses on improving existing functionalities or integrating new models into the system.
There are several contributors like Qhaoduoyu, awwaawwa, and binary-sky who have fewer commits but still contribute important fixes or enhancements to the project.
The team shows collaboration through pull requests that are reviewed and merged by others in the team, indicating a collaborative approach to development.
The pattern of activity suggests a healthy project environment where contributors are actively engaged in both expanding the project's capabilities and ensuring its stability. The focus on integrating new language models and improving user experience is evident from the types of commits being made. There is also attention given to maintaining documentation up-to-date which is crucial for engaging the community effectively.
| Developer | Avatar | Branches | PRs | Commits | Files | Changes |
|---|---|---|---|---|---|---|
| binary-husky | |
2 | 1/1/0 | 23 | 40 | 2963 |
| Yuki | |
2 | 2/1/1 | 2 | 1 | 98 |
| zyren123 | |
1 | 1/1/0 | 1 | 1 | 80 |
| hmp | |
1 | 0/0/0 | 1 | 3 | 78 |
| OREEkE | |
1 | 2/2/0 | 2 | 2 | 41 |
| Menghuan1918 | |
1 | 1/1/0 | 1 | 4 | 22 |
| awwaawwa | |
1 | 2/1/0 | 1 | 2 | 21 |
| iluem | |
1 | 0/0/0 | 2 | 2 | 13 |
| XIao | |
1 | 2/2/0 | 1 | 1 | 9 |
| owo | |
1 | 2/2/0 | 2 | 2 | 4 |
| jiangfy-ihep | |
1 | 1/1/0 | 1 | 1 | 2 |
| Wbscript (wbs306) | 0 | 0/0/1 | 0 | 0 | 0 | |
| None (Skyzayre) | 0 | 0/1/0 | 0 | 0 | 0 |
PRs: created by that dev and opened/merged/closed-unmerged during the period
The repository binary-husky/gpt_academic is a highly active and complex project with a focus on providing practical interaction interfaces for large language models like GPT and GLM, particularly optimized for academic purposes such as reading, polishing, and writing papers. It supports a modular design allowing for custom shortcut buttons and function plugins, and it includes functionalities for PDF/LaTex paper translation and summarization, among others.
crazy_functions/PDF批量翻译.py
批量翻译PDF文档 orchestrates the flow of translating PDF documents by checking dependencies, fetching files, and determining the translation method based on configuration or availability of services like GROBID or DOC2X.yield) to manage state and UI updates, which is suitable for asynchronous operations but might be complex for maintenance.crazy_functions/pdf_fns/report_template_v2.html
request_llms/bridge_chatglm3.py
GetGLM3Handle inheriting from LocalLLMHandle that encapsulates model-specific operations.shared_utils/fastapi_server.py
themes/common.js
The repository exhibits a high level of sophistication with modular design allowing flexibility in extending functionalities. While the code quality is generally high with good practices in software engineering observed, there are areas where improvements could be made such as dependency management in Python scripts and potential localization issues due to mixed-language coding. Overall, the project is well-maintained with clear documentation supporting its complex features.