Quantify commits

Quantified Commit Activity Over 30 Days

Developer	Avatar	Branches	PRs	Commits	Files	Changes
Jiayi Zhang (didiforgithub)		1	2/1/0	5	15	11546
liuminhui		1	1/0/1	8	32	1317
莘权 马		1	0/0/0	12	21	216
好好学习的郝		1	0/1/0	4	9	78
hgftrdw45ud67is8o89		1	1/1/0	3	2	11
stone		1	3/1/1	1	1	3
None (femto)		0	2/0/0	0	0	0
None (seehi)		0	1/1/0	0	0	0
Alexander Wu		0	0/0/0	0	0	0
Guess		0	8/7/2	0	0	0
huihui (jschyz)		0	1/0/0	0	0	0
João Galego (JGalego)		0	1/0/0	0	0	0
None (paras55)		0	1/0/0	0	0	0
better629		0	0/0/0	0	0	0
草帽小子 (duanguo108)		0	1/0/0	0	0	0
jasonliao (lanlanguai)		0	1/0/0	0	0	0
Arpit Pathak (Thepathakarpit)		0	1/0/1	0	0	0

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

Quantify Issues

Recent GitHub Issues Activity

_{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.}

Report On: Fetch issues

Recent Activity Analysis

The MetaGPT project has seen significant recent activity, with 294 open issues on GitHub. Among these, several issues highlight ongoing challenges and user inquiries regarding the framework's functionality, particularly in relation to specific roles and integrations with various models. Notably, there are recurring themes around the effectiveness of the "Researcher" role, issues with model configurations, and user experiences with generating code for specific applications like games.

Several issues indicate a lack of clarity or functionality in the system, such as problems with the "Researcher" role not executing correctly or generating expected outputs. There are also mentions of errors related to API keys and configurations, suggesting that users are facing hurdles in setting up their environments properly.

Issue Details

Most Recently Created Issues:

1. Issue #1449: 如何绘制一个折线图或柱状图

   • Created: 3 days ago
   • Priority: Normal
   • Status: Open
   • Comments: Discussion on how to implement a line or bar chart using input data.

2. Issue #1448: Issue loading deepwisdom.ai/

   • Created: 4 days ago
   • Priority: High
   • Status: Open
   • Comments: Bug report about a 404 error when accessing the website.

3. Issue #1445: How to associate inputs and outputs of multiple ActionNodes

   • Created: 8 days ago
   • Priority: Medium
   • Status: Open
   • Comments: Inquiry about best practices for linking outputs from one ActionNode to inputs of another.

4. Issue #1443: 使用本地llama3.1模型，测试metagpt "创建一个 2048 游戏",无法找到本地llama3.1模型。

   • Created: 9 days ago
   • Priority: High
   • Status: Open
   • Comments: Bug report regarding the inability to find a local model during testing.

5. Issue #1439: about ActionNode and the MetaGPT framework

   • Created: 11 days ago
   • Priority: Normal
   • Status: Open
   • Comments: Questions about the functionality and implementation of ActionNodes within the framework.

Most Recently Updated Issues:

1. Issue #1449

   • Last updated: 2 days ago

2. Issue #1448

   • Last updated: 3 days ago

3. Issue #1445

   • Last updated: 2 days ago

4. Issue #1443

   • Last updated: 8 days ago

5. Issue #1439

   • Last updated: 10 days ago

Analysis of Notable Issues

• The issue regarding loading deepwisdom.ai (#1448) is critical as it affects access to documentation and resources essential for users trying to implement or troubleshoot their projects.
• The frequent inquiries about ActionNode associations (#1445) suggest that users may be struggling with understanding how to effectively utilize this feature within their workflows.
• The recurring mention of local model integration issues (#1443) indicates potential gaps in documentation or support for users attempting to set up their environments with specific models.
• The discussions around the Researcher role (#1439) highlight a need for clearer guidelines or enhancements to ensure that this role functions as intended within various contexts.

Overall, these issues reflect broader themes of user support and documentation clarity, indicating areas where improvements could enhance user experience and project adoption.

Report On: Fetch pull requests

Overview

The dataset contains a comprehensive list of pull requests (PRs) from the geekan/MetaGPT repository, including both open and closed PRs. The focus is on recent developments, bug fixes, feature enhancements, and community engagement within the project.

Summary of Pull Requests

1. PR #1450: feat(bedrock) - Introduced support for temporary AWS credentials via environment variables and updated supported models. Notable for improving AWS integration and model support.

2. PR #1446: Adding Unify AI Support - Added support for Unify AI to utilize multiple AI models with a single API key. This enhances usability but has low test coverage.

3. PR #1444: Update Action graph Version 0.1.2 - Updated the action graph for humaneval and other benchmarks, ensuring compatibility with recent changes.

4. PR #1442: fix bug - Fixed a timeout issue in qianfan_api.py, improving stability in API calls.

5. PR #1441: Minion Design - Introduced a new design for the Minion role, allowing for complex task management but raised questions about code organization.

6. PR #1440: Rm sk agent - Removed an unused agent, streamlining the codebase.

7. PR #1434: 新增流式输出的例子 - Added an example of streaming output using FastAPI, showcasing real-time capabilities.

8. PR #1413: Added support for HyDE method - Enhanced query analysis in RAG modules, although it faced criticism for lack of documentation.

9. PR #1421: feat: + write code only - Implemented a feature allowing engineers to write code directly, which could streamline development processes.

10. PR #1415: feat: +git commit history - Added synchronization features for GitLab repositories, enhancing version control capabilities.

11. PR #1411: feat: dashscope llm supports Llama-3.1- - Integrated support for new models in DashScope API, expanding model compatibility.

12. PR #1389: LLM.aask支持流式响应内容外部访问 - Improved LLM response handling for external access, though it faced implementation challenges.

13. PR #1359: feat: add tencent hunyuan api - Added Tencent's Hunyuan API support, broadening the project's capabilities.

14. PR #1348: Add PPTdesigner example script - Introduced an example script for generating PPTs, although it faced execution issues during testing.

15. PR #1300: feat: rename "Required Python packages" - Simplified package naming conventions to enhance compatibility across programming languages.

Analysis of Pull Requests

The pull requests reflect a vibrant development environment within the MetaGPT project, characterized by a mix of feature enhancements, bug fixes, and community-driven improvements.

Common Themes

1. Integration of New Features: Many PRs focus on integrating new functionalities such as support for various AI models (e.g., Llama-3.1) and APIs (e.g., Tencent Hunyuan). This trend indicates a commitment to keeping the framework versatile and relevant in a rapidly evolving AI landscape.

2. Bug Fixes and Stability Improvements: A significant number of PRs address bugs and stability issues (e.g., timeout fixes in qianfan_api.py). This reflects an ongoing effort to enhance user experience by ensuring reliability in various operational contexts.

3. Community Engagement and Feedback Incorporation: The presence of review comments from contributors highlights an active community that engages in discussions about code quality and functionality improvements. For instance, feedback regarding naming conventions and error handling practices demonstrates a collaborative approach to development.

Notable Anomalies

• Low Test Coverage: Several PRs, such as those adding new features or integrations (e.g., PR #1446), report low test coverage percentages (e.g., less than 5%). This raises concerns about the robustness of these features and suggests that additional testing may be required before they can be reliably deployed.

• Contentious Changes: Some changes have sparked debate among contributors regarding their necessity or implementation details (e.g., PR #1441 on Minion design). Such discussions are crucial as they can lead to better-informed decisions but may also slow down the merging process if consensus is not reached quickly.

Features Under Development

The ongoing work on features like streaming outputs (PR #1434) and improved query analysis methods (PR #1413) suggests that the project is not only focused on expanding its capabilities but also on enhancing existing functionalities to meet user needs more effectively.

Conclusion

The dataset showcases an active development cycle with a strong emphasis on feature expansion, bug fixing, and community involvement within the MetaGPT project. However, attention should be given to improving test coverage and addressing contentious changes through collaborative discussions to ensure that enhancements are both robust and aligned with user expectations.

Report On: Fetch commits

Repo Commits Analysis

Development Team and Recent Activity

Team Members and Recent Contributions

1. better629

   • Activity: No recent commits or contributions.

2. 莘权 马

   • Recent Activity:
   • Made 12 commits with 216 changes across 21 files.
   • Notable contributions include bug fixes related to LLM configurations, enhancements in action nodes, and updates to the requirements file.
   • Collaborated with other team members on various features and bug fixes.

3. iorisa

   • Activity: No recent commits; has several open pull requests (8 open, 7 merged).

4. HuiDBK

   • Recent Activity:
   • Contributed 8 commits with 1317 changes across 32 files.
   • Focused on bug fixes and enhancements related to the omniparse feature and action nodes.
   • Merged one pull request and has one open pull request.

5. hgftrdw45ud67is8o89

   • Recent Activity:
   • Contributed 3 commits with 11 changes across 2 files.
   • Worked on bug fixes, particularly addressing issues in project management actions.

6. geekan

   • Activity: No recent commits or contributions.

7. voidking

   • Recent Activity:
   • Made 4 commits with 78 changes across 9 files.
   • Focused on workflow improvements and minor bug fixes.

8. yingfeng2016

   • Recent Activity:
   • Contributed 1 commit with 3 changes.
   • Involved in fixing bugs related to team functionality.

9. didiforgithub

   • Recent Activity:
   • Made 5 commits with significant changes (11546 lines) across 15 files.
   • Focused on updates to action graph solver, including benchmarks and utility functions.

10. duanguo108

    • Activity: No recent commits or contributions.

11. femto

    • Activity: No recent commits or contributions.

12. lanlanguai

    • Activity: No recent commits or contributions.

13. jschyz

    • Activity: No recent commits or contributions.

14. seehi

    • Activity: No recent commits or contributions.

Patterns and Themes

• The development team is actively engaged, with several members contributing to both feature development and bug fixing.
• There is a notable focus on enhancing the framework's capabilities, particularly around LLM integration and action node functionalities.
• Collaboration is evident, as multiple team members are working together on related issues, especially concerning bug fixes and feature enhancements.
• The activity level varies among team members, with some like 莘权 马 and didiforgithub showing high levels of contribution while others have been inactive recently.
• The repository continues to evolve rapidly, reflecting ongoing improvements and community engagement in response to user feedback and issues raised in GitHub discussions.

Conclusion

The development team is demonstrating strong collaborative efforts in enhancing the MetaGPT framework through active contributions focused on both new features and critical bug fixes. The diverse range of activities indicates a responsive approach to community needs and ongoing project evolution.