GPT Academic, an open-source project aimed at optimizing interactions with large language models for academic purposes, has seen a flurry of user-reported issues related to API integrations and plugin functionality, highlighting potential gaps in documentation and stability.
The project is designed to facilitate the reading, editing, and writing of academic papers by leveraging various LLMs such as GPT and GLM. It features a modular architecture allowing for custom plugins and supports functionalities like PDF translation and multi-model querying.
Recent issues predominantly revolve around bugs in plugin operations and API key configurations. For example, #1970 reports significant response delays in the o1-preview model, while #1969 details failures in internet-based plugin responses. These issues suggest integration challenges with third-party services. The development team has been actively addressing these through bug fixes and feature enhancements.
| Timespan | Opened | Closed | Comments | Labeled | Milestones |
|---|---|---|---|---|---|
| 7 Days | 12 | 0 | 12 | 12 | 1 |
| 30 Days | 23 | 3 | 29 | 23 | 1 |
| 90 Days | 84 | 15 | 109 | 82 | 1 |
| All Time | 1574 | 1247 | - | - | - |
Like all software activity quantification, these numbers are imperfect but sometimes useful. Comments, Labels, and Milestones refer to those issues opened in the timespan in question.
| Developer | Avatar | Branches | PRs | Commits | Files | Changes |
|---|---|---|---|---|---|---|
| binary-husky |  |
2 | 1/1/0 | 22 | 97 | 4156 |
| moetayuko |  |
1 | 0/1/0 | 1 | 3 | 54 |
| None (zhuhuahua168) | 0 | 0/0/1 | 0 | 0 | 0 |
PRs: created by that dev and opened/merged/closed-unmerged during the period
The GitHub repository for the project gpt_academic has seen considerable recent activity, with a total of 327 open issues. Notably, several issues have been reported regarding bugs and feature requests, particularly related to the functionality of various plugins and API integrations. There is a recurring theme of users experiencing difficulties with API keys, connection timeouts, and PDF translation failures, indicating potential underlying issues with the project's stability or documentation.
Several issues exhibit significant user engagement, with multiple comments suggesting common problems or solutions. For instance, many users are facing challenges with API key configurations and timeouts when using third-party services. This suggests that while the project is actively developed, there may be gaps in user support and documentation that could be addressed to improve user experience.
Issue #1970: [Bug]: o1-preview响应过久
Issue #1969: [Bug]: 插件查互联网后回答无法使用
Issue #1968: [Bug]: 谷歌学术检索助手插件一直在初始化
Issue #1967: [Feature]: 分享一个使用在海外服务器用ngnix反向代理https访问的方法
Issue #1966: [Feature]: 希望学术检索助手增加对pubmed的支持
Issue #1969: [Bug]: 插件查互联网后回答无法使用
Issue #1962: [Bug]: arkiv论文编译完成后会停住,手动点击停止后才会把后面的成功或失败信息打印出来
Issue #1956: [Bug]: OpenAI以账户额度不足为由拒绝服务
Issue #1948: [Bug]: api_key 验证无效
Issue #1934: [Bug]: Traceback (most recent call last): File ".\request_llms\bridge_chatgpt.py", line 316, in predict raise ValueError(f'无法读取以下数据，请检查配置。\n\n{chunk_decoded}')
Overall, while there is active engagement from users reporting issues and suggesting features, the frequency of bugs related to API interactions and plugin functionalities indicates areas where the project could enhance its robustness and user experience through better documentation and support mechanisms.
The analysis of the pull requests (PRs) for the GPT Academic project reveals a vibrant and active development environment with a focus on enhancing functionality, fixing bugs, and expanding support for various large language models (LLMs). The project's modular design allows for continuous integration of new features and improvements through community contributions.
PR #1918: Updates Latex_Function.py to configure accelerated downloads from arXiv and display a progress bar. This PR is significant as it improves user experience by providing feedback during downloads.
PR #1814: Adds support for Qwen series models, Groq, and Yi Vision, along with interfaces for integrating multimodal LLMs into oneAPI. This PR is notable for expanding the project's compatibility with new models and technologies.
PR #1765: Introduces support for Deepseek online models. This PR highlights the project's commitment to integrating various LLMs and enhancing its capabilities.
PR #1761: Implements a temporary API access method similar to using a temporary key, allowing users to switch APIs without restarting the program. This PR is significant for its flexibility in API management.
PR #1745: Adds multithreaded requests for Qianfan, Gemini, and Moonshot models, along with configurable retry parameters. This PR improves performance and reliability in model interactions.
PR #1734: Adds support for several GROQ models. This PR continues the trend of expanding model support within the project.
PR #1958: A major update merging various branches into frontier, including new features like RAG (Retrieval-Augmented Generation) projects. This PR signifies a substantial enhancement in the project's capabilities.
PR #1942: An unmerged PR that seems to be an accidental creation rather than a functional contribution.
PR #1937: Fixes loading issues with ChatGLM3, showcasing active maintenance and bug fixing efforts within the project.
PR #1926 & #1924: Both PRs attempt to add support for Gemini 1.5 Pro & Flash but only one was merged. This indicates ongoing efforts to keep up with the latest advancements in AI models.
The pull requests reflect several key themes in the development of the GPT Academic project:
Continuous Integration of New Models: There is a consistent effort to integrate support for new LLMs as they become available. PRs like #1814, #1765, and #1734 demonstrate this trend, ensuring that users have access to the latest advancements in AI technology.
Enhancements to User Experience: Several PRs focus on improving user interaction with the software. For instance, PR #1918 enhances download experiences with progress indicators, while PR #1761 allows temporary API switching without restarts. These improvements are crucial for maintaining user satisfaction and engagement.
Performance Optimization: PRs such as #1745 highlight efforts to optimize performance through multithreading and configurable parameters. This is particularly important as the project scales and handles more complex tasks or larger datasets.
Active Maintenance and Bug Fixing: The closure of PRs like #1937 with fixes for specific issues indicates an active maintenance routine, which is vital for any software project to ensure reliability and trustworthiness.
Community Engagement: The variety of contributors and the range of enhancements suggest a healthy level of community involvement. This is further supported by the project's open-source nature, encouraging contributions from developers worldwide.
In conclusion, the GPT Academic project is characterized by its dynamic development environment focused on expanding capabilities, enhancing user experience, optimizing performance, and actively maintaining software quality through community contributions. The project's modular architecture supports these efforts by allowing easy integration of new features and technologies.
binary-husky
moetayuko
zhuhuahua168
The development team is actively engaged in enhancing the GPT Academic project, with a clear focus on bug resolution and feature enhancement. The contributions are largely driven by binary-husky, while collaboration with other members like moetayuko supports ongoing development efforts. The lack of recent activity from zhuhuahua168 may indicate a need for re-engagement or redistribution of tasks within the team.
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