Quantify commits

Quantified Commit Activity Over 14 Days

Developer	Avatar	Branches	PRs	Commits	Files	Changes
binary-husky		2	0/1/0	21	41	3507
None (Menghuan1918)		1	2/2/0	2	12	818
awwaawwa		1	1/1/1	1	2	44
hongyi-zhao		1	0/1/0	1	3	30
alex_xiao		1	0/1/0	1	1	17
QiyuanChen (qychen2001)		1	1/1/0	1	2	7
Shixian Sheng		1	1/1/0	1	1	2
None (AnjiaYe)		0	1/0/0	0	0	0
Fei GAO (Phelixh)		0	1/0/1	0	0	0
GrayArashi (GrayArashiAI)		0	1/0/1	0	0	0

_{PRs: created by that dev and opened/merged/closed-unmerged during the period}

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Project Overview

The project GPT Academic (binary-husky/gpt_academic) is a software initiative designed to provide practical interaction interfaces for large language models (LLMs) like GPT and GLM, with specific optimizations for academic tasks such as paper reading, editing, and writing. The project features a modular design that supports custom shortcut buttons and function plugins, and it can analyze and translate projects in multiple programming languages including Python and C++. Additionally, it offers functionalities like PDF/LaTeX paper translation and summarization. The project is hosted on GitHub under the GNU General Public License v3.0, indicating that it is open-source. It supports multiple LLM models both locally and via API integration, including but not limited to models like ChatGLM3, DeepseekCoder, and Claude2.

The repository has seen substantial community engagement, evidenced by its 59,350 stars and 7,442 forks. It is actively maintained with a total of 2045 commits spread across 23 branches, with the most recent activities focusing on enhancing functionality and integrating new LLM models.

Team Members and Recent Activities

Team Members:

1. Shixian Sheng (KPCOFGS)
2. binary-husky
3. awwaawwa
4. hongyi-zhao
5. Alex4210987
6. AnjiaYe
7. qychen2001
8. Menghuan1918
9. GrayArashiAI
10. Phelixh

Recent Commit Activities:

Shixian Sheng (KPCOFGS)

• Updated README.md.

binary-husky

• Major contributor with extensive commits improving various aspects such as configuration files (config.py), integration of new models (request_llms/bridge_all.py), and frontend enhancements (themes/common.js).
• Worked on integrating text-to-speech functionalities and addressed several bugs related to UI hints and API integrations.

awwaawwa

• Contributed to model override functionalities in core_functional.py allowing more flexibility in model usage within the project.

hongyi-zhao

• Added environment variable configurations and enhanced browser launching functionalities which are crucial for user interaction improvements.

Alex4210987

• Focused on PDF translation features by updating the API key mechanism in crazy_functions/PDF批量翻译.py.

qychen2001

• Added support for ERNIE-Speed and ERNIE-Lite models in config.py and request_llms/bridge_qianfan.py, expanding the project's model support.

Menghuan1918

• Provided significant updates to Docker configurations to include dependencies like FFmpeg required by edge-tts.
• Enhanced API connectivity by introducing a new fast way of accessing APIs such as Yi-models and Deepseek.

Patterns and Conclusions:

The development team is highly active with frequent updates focused on expanding the project’s capabilities, particularly in integrating new LLM models and enhancing user interface elements. There is a strong emphasis on maintaining robust documentation and ensuring compatibility across different systems and configurations, which is evident from the detailed commit messages and collaborative PR reviews.

The project's trajectory suggests a continuous expansion in terms of supported features and integrated models, making it a versatile tool for academic and research applications involving large language models. The team's collaborative efforts are pivotal in driving the project forward, addressing user feedback, and implementing new technologies promptly.

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Recent Activity Analysis

The GitHub project binary-husky/gpt_academic currently has a total of 253 open issues. Recent activity includes a variety of bug reports and feature requests, with several issues created or updated in the past few days.

Notable Issues

• Issue #1830 reports a bug related to automatic updates failing when the program is run via terminal on Windows. The issue appears to be path-related, with the user providing detailed information including error logs and system configurations. This issue is critical as it affects the usability of the software in its current environment.

• Issue #1828 is a feature request for adding support for Gemini-1.5-Pro, indicating a need for updates in line with external API developments.

• Issue #1826 discusses a significant bug with Japanese translation functionality, which is described as nearly unusable. This impacts users relying on the software for accurate translations, highlighting a critical area for improvement.

• Issue #1824 details a bug involving API key configuration errors when attempting to use Baidu's Qianfan API, resulting in failed start-ups and error messages indicating daily request limits.

• Issue #1823 describes an issue with NOUGAT PDF translation failing due to missing GPU resources, which suggests potential improvements in resource handling and error messaging.

Common Themes

A recurring theme across the issues is the struggle with path and configuration settings leading to operational failures. Many users are encountering difficulties with external APIs and dependencies, which suggests that documentation and error handling could be enhanced to facilitate user setup and troubleshooting.

Issue Details

Most Recently Created Issue

• #1830: [Bug]: 使用终端运行的时候自动更新程序会无法运行
  • Priority: High
  • Status: Open
  • Created: 1 day ago by 彭博 (SCWM-P)
  • Updated: Today

Most Recently Updated Issue

• #1830: [Bug]: 使用终端运行的时候自动更新程序会无法运行
  • Priority: High
  • Status: Open
  • Created: 1 day ago by 彭博 (SCWM-P)
  • Updated: Today

Given the current data, these issues reflect ongoing challenges with software stability and functionality that directly impact user experience and operational efficiency. Addressing these issues should be prioritized to improve reliability and user satisfaction.

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Analysis of Pull Requests in binary-husky/gpt_academic Repository

Open Pull Requests Overview

Notable Open PRs:

1. PR #1825: 【插件】批量提问PDF全文，输出JSON文件

   • Issue: This PR aims to enhance the handling of large PDF files by extracting questions and outputting them in JSON format, which could significantly improve data handling and processing within the application.
   • Status: Open and needs review for potential integration or further improvements.

2. PR #1814: Add support for Qwen api

   • Issue: Adds support for a new API, which could expand the capabilities of the application. However, the PR includes changes across multiple files, which might require thorough testing.
   • Status: Open and requires comprehensive testing due to the extensive changes introduced.

3. PR #1765: add deepseek online models

   • Issue: Integration of Deepseek models for enhanced functionality. However, there are issues with token limits and exceptions being thrown, which could affect stability.
   • Status: Open but has critical errors that need resolution before merging.

4. PR #1745: 加入qianfan，gemini-和moonshot-多线程请求;重试次数参数加入设置 (config.py) RETRY_TIMES_AT_UNKNOWN_ERROR=3

   • Issue: Enhances the robustness of the system by allowing multi-threaded requests and configurable retry parameters. This is crucial for improving performance and reliability.
   • Status: Open and appears beneficial but needs review to ensure it doesn't introduce concurrency issues.

5. PR #1734: add groq models support

   • Issue: Attempts to add support for GROQ models but includes hardcoded secrets which pose a significant security risk.
   • Status: Open with critical security concerns due to exposed secrets that must be addressed immediately.

Recently Closed PRs:

1. PR #1821: 添加对ERNIE-Speed和ERNIE-Lite模型的支持

   • Action Taken: Closed without merging.
   • Reason & Impact: The PR was intended to add support for ERNIE models but was closed abruptly without integration. This might have been due to overlapping functionality or unresolved issues.

2. PR #1807: 为docker构建添加FFmpeg依赖

   • Action Taken: Merged.
   • Impact: Successfully adds FFmpeg dependency, which is crucial for handling multimedia content within the application.

3. PR #1800: Update

   • Action Taken: Closed without merging.
   • Reason & Impact: The closure of this PR without merging, especially given its vague title and lack of description, suggests it may have been opened by mistake or contained irrelevant changes.

4. PR #1793: gpt_academic1

   • Action Taken: Closed without merging.
   • Reason & Impact: Similar to PR #1800, its closure without details suggests it was not a substantive contribution.

5. PR #1782: Provide a new fast and simple way of accessing APIs

   • Action Taken: Merged.
   • Impact: This PR simplifies API access within the application, potentially improving both developer experience and system performance by standardizing API interactions.

Summary

The repository has several open pull requests that could significantly impact functionality, such as adding new model supports (e.g., Qwen API, Deepseek models) and enhancing system robustness through multi-threading capabilities. However, some PRs pose security risks (e.g., exposed secrets in PR #1734) or have critical errors that need resolution before they can be safely merged.

The closed pull requests reveal a pattern where non-substantive or problematic PRs are being closed without merging, which is good practice. However, attention is needed to ensure that valuable contributions like PR #1782 are integrated effectively while maintaining security and stability standards.

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File Analysis

1. crazy_functions/Latex_Function.py

Overview

This file is crucial for handling LaTeX-related functionalities, which are a core feature of the project as mentioned in the README.

Details

• Functionality: Expected to contain functions for processing LaTeX documents, such as rendering, editing, or converting LaTeX syntax into other formats.
• Integration: Likely interacts with other modules that handle document processing or user interface to provide a seamless experience in handling LaTeX documents.
• Quality and Structure: Without seeing the actual code, one can expect standard practices like function modularity, error handling, and comments explaining the functionality should be present.

2. crazy_functions/PDF_Translate_Wrap.py

Overview

This file appears to be integral for PDF translation features, enabling users to translate content directly from PDFs—a key feature highlighted in the project documentation.

Details

• Functionality: Should include methods to extract text from PDF files and apply language translation functions.
• Error Handling: Robust error handling would be necessary to deal with various PDF formats and potential translation API errors.
• Performance: Efficiency in processing PDFs and caching results could be critical, given the potentially large size of academic documents.

3. crazy_functions/plugin_template/plugin_class_template.py

Overview

Serves as a template for creating new plugins. Understanding this template is essential for contributors looking to extend the project's capabilities through new plugins.

Details

• Structure: Expected to provide a clear class structure that outlines methods and properties essential for all plugins.
• Documentation: Adequate comments and documentation are crucial in a template to guide developers on how to use it effectively.
• Examples: Ideally includes inline examples or a reference to a simple implementation that uses the template.

4. request_llms/bridge_all.py

Overview

Central management file for interactions with various language models, which is crucial for the project's functionality as it integrates core AI features.

Details

• Functionality: Manages API calls to different language models, handles responses, and possibly retries on failures.
• Security: Must ensure secure handling of API keys and sensitive data during interactions with external services.
• Scalability: The code should be scalable to accommodate additional language models without significant modifications.

5. themes/common.js

Overview

Contains JavaScript functions common across the project's web interface, playing a significant role in UI functionality.

Details

• UI Interactions: Functions here likely control dynamic elements of the UI such as modals, tabs, or custom interactive components.
• Compatibility: Code should be compatible across different browsers and devices considering the diverse user base.
• Performance: Efficient JavaScript coding practices are essential to ensure that the UI remains responsive and fast.

Each of these files plays a pivotal role in their respective areas within the project. Proper documentation, coding standards adherence, and thorough testing would be key considerations in maintaining the quality of these components.