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.}

Quantify commits

Quantified Commit Activity Over 30 Days

Developer	Avatar	Branches	PRs	Commits	Files	Changes
Eugen Eisler		1	0/0/0	20	20	832
Daniel Miessler		1	0/0/0	32	12	620
Azwar Tamim		1	1/1/0	4	7	236
Noam Siegel		1	0/1/0	2	4	176
Joseph Thacker		1	1/1/0	3	4	155
Martin Riedel		1	1/1/0	1	2	48
Randall Degges		1	1/2/0	1	1	47
Cameron		1	1/1/0	1	2	45
csquarechen		1	0/0/0	3	7	43
ALX99		1	1/3/0	1	7	36
Max Leung		1	0/0/0	1	1	29
Mark Kazakov		1	1/1/0	1	4	27
Rudi Bruchez		1	1/1/0	2	4	24
Ian		1	1/1/0	1	1	22
NerdyPunkDad		1	1/1/0	3	2	21
NeP		1	1/1/0	1	2	18
masai		1	1/1/0	1	1	16
David		1	1/1/0	1	1	9
Jim Manico		1	1/1/0	1	1	4
Pavel Dmytrenko		1	1/1/0	1	2	4
Bin		1	1/1/0	1	1	3
Frederick Ros		1	1/1/0	1	1	2
Aaron Culich (aculich)		0	1/0/0	0	0	0
Charles Twardy (ctwardy)		0	1/0/1	0	0	0
James Craigen (jaycgen)		0	0/1/0	0	0	0
Tomasz Edward Posluszny (alucarded)		0	1/0/0	0	0	0
Chen (quarechen)		0	1/1/0	0	0	0
xssdoctor		0	0/0/0	0	0	0
None (buerbaumer)		0	0/1/0	0	0	0
Josh Medeski (joshmedeski)		0	1/0/0	0	0	0
Riccardo Zanella (riccardo1980)		0	1/0/0	0	0	0
Zo6 (sosacrazy126)		0	1/0/0	0	0	0
Akash Kankariya (akashkankariya)		0	1/0/0	0	0	0
Max Leung (maxleungtszchun)		0	1/1/0	0	0	0

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

Report On: Fetch issues

Recent Activity Analysis

The recent activity on the Fabric GitHub repository indicates a dynamic environment with a total of 128 open issues, reflecting ongoing user engagement and a variety of concerns ranging from bugs to feature requests. Notably, several users have reported issues related to the transition from Python to Go, highlighting challenges with installation and functionality.

A significant theme among the issues is the migration-related complications, particularly concerning API key management and model configurations. Users frequently express confusion over how to set up their environment correctly and utilize different AI models effectively. Additionally, there are recurring mentions of errors related to local model integration and command execution failures.

Issue Details

Most Recently Created Issues

1. Issue #990: [Question]: Google Search API

   • Priority: Low
   • Status: Open
   • Created: 1 day ago
   • Comments: User struggles with configuring the new version to use Google Search API after an upgrade.

2. Issue #988: [Question]: Windows compatible still?

   • Priority: Low
   • Status: Open
   • Created: 2 days ago
   • Comments: User reports installation issues on Windows, seeking advice on proper setup.

3. Issue #986: [Feature request]: --version switch

   • Priority: Medium
   • Status: Open
   • Created: 3 days ago
   • Comments: User requests a command-line switch to display the current version of Fabric.

4. Issue #985: [Bug]: Unable to install to_pdf helper

   • Priority: High
   • Status: Open
   • Created: 3 days ago
   • Comments: User encounters an error while trying to install the to_pdf helper due to package unavailability.

5. Issue #983: [Bug]: yt command doesn't work on Linux (via SSH). Need Help! (2)

   • Priority: High
   • Status: Open
   • Created: 3 days ago
   • Comments: User reports that the yt command works on Windows but fails over SSH on Linux, seeking assistance.

Most Recently Updated Issues

1. Issue #876: [Bug]: Stream error: stream ID 3; CANCEL; received from peer

   • Priority: High
   • Status: Closed (previously open)
   • Last Updated: 12 days ago
   • Comments: Users report connectivity issues with the Ollama server during setup.

2. Issue #958: [Bug]: When using openrouter as vendor, DEFAULT_MODEL in .env file not respected

   • Priority: Medium
   • Status: Closed (previously open)
   • Last Updated: 7 days ago
   • Comments: User faced issues with model configuration not being recognized.

3. Issue #946: [Bug]: yt and ts not installed in RHEL 9.4 with go installation

   • Priority: High
   • Status: Closed (previously open)
   • Last Updated: 12 days ago
   • Comments: User reports missing helper apps after installation.

4. Issue #940: [Bug]: Content seems to be missing in solve_with_cot system.md

   • Priority: Medium
   • Status: Closed (previously open)
   • Last Updated: 14 days ago
   • Comments: User reports incomplete content in documentation files.

5. Issue #922: [Question]: How to launch GUI after latest upgrade

   • Priority: Low
   • Status: Closed (previously open)
   • Last Updated: 18 days ago
   • Comments: User seeks clarification on GUI functionality post-upgrade.

Themes and Commonalities

The issues reflect several key themes:

• Migration Challenges: Many users are struggling with transitioning from the Python version to Go, particularly regarding API key management and model configurations.
• Installation Issues: A significant number of issues revolve around installation failures or missing components, especially for users on Windows or Linux environments.
• Model Integration Problems: Users frequently report difficulties in getting local models recognized or functioning as expected.
• Feature Requests: There is a notable interest in enhancing documentation and usability features, such as version displays and improved error handling.

This analysis highlights the need for clearer documentation and support mechanisms as users navigate through the complexities introduced by the migration to Go and the integration of various AI models.

Report On: Fetch pull requests

Overview

The dataset provided includes a comprehensive list of pull requests (PRs) for the Fabric project, which is an open-source framework designed to augment human capabilities through AI. The PRs cover a wide range of updates, from bug fixes and feature additions to documentation improvements and infrastructure changes.

Summary of Pull Requests

Open Pull Requests

1. PR #991: Fixes GOROOT path for Apple Silicon Macs, ensuring compatibility with M1/M2 Macs by dynamically determining the correct GOROOT path using Homebrew.
2. PR #987: Trims formatting on fabric -l command output, making it easier to combine with other CLI tools like fzf. This is a breaking change and suggests a potential addition of a "raw" flag.
3. PR #984: Adds an optional seed parameter for reproducible results in OpenAI API calls. Includes updates to CLI flags and tests.
4. PR #967: Updates installation path for to_pdf tool in README.md, addressing an issue related to incorrect installation instructions.
5. PR #962: Updates example output topic name in agility_story pattern for clarity.
6. PR #952: Adds support for LM Studio to Fabric, including new documentation, implementation, unit tests, and updates to main README.md.
7. PR #862: Automates setup and usage of Fabric on Windows with a batch script that installs necessary tools and configures the environment.
8. PR #845: Introduces Docker support for Fabric, allowing it to be run in a containerized environment.

Closed Pull Requests

1. PR #976: Corrects the description for -d, --changeDefaultModel flag in README.md and cli/flags.go files.
2. PR #970: Adds support for Mistral AI vendor integration into Fabric.
3. PR #957: Introduces -g command to select the language for responses, addressing multilingual adaptation issues.
4. PR #953: Adds new pattern write_latex and tool to_pdf, expanding Fabric's capabilities in handling LaTeX documents.
5. PR #944: Proposes updating README.md for smoother setup experience by rearranging sections related to environment setup and Fabric setup.
6. PR #943: Adds new pattern extract_skills for extracting skills from job descriptions, enhancing Fabric's utility in recruitment processes.

Analysis of Pull Requests

The pull requests reflect ongoing efforts to enhance the functionality, usability, and accessibility of the Fabric framework. Key themes include:

• Cross-Platform Compatibility: Several PRs address compatibility issues across different operating systems (e.g., PR #991 for Apple Silicon Macs and PR #862 introducing a Windows batch script).
• Feature Expansion: New features are being continuously added (e.g., PR #984 introducing reproducible results with seed parameters and PR #952 adding LM Studio support).
• Community Contributions: The project's active community is evident from the variety of contributions ranging from bug fixes (e.g., PR #976 correcting flag descriptions) to new patterns (e.g., PR #943 extracting skills from job descriptions).
• Infrastructure Improvements: Efforts to improve the project's infrastructure are also notable (e.g., PR #845 adding Docker support), indicating a focus on making deployment and usage easier for end-users.

Overall, the pull requests demonstrate a vibrant development activity aimed at making Fabric a more powerful and user-friendly tool for leveraging AI in various applications. The project's commitment to community involvement and continuous improvement is evident from the diverse range of contributions it receives.

Report On: Fetch commits

Repo Commits Analysis

Development Team and Recent Activity

Team Members and Recent Contributions

1. Eugen Eisler (eugeis)

   • Activity: 20 commits, 832 changes.
   • Recent Work:
   • Added support for configurable base URL for Anthropic.
   • Integrated output language into system/user prompts.
   • Improved Jina AI implementation and added cmd -g for language selection.
   • Updated CI workflows and dependencies.
   • Collaboration: Merged multiple pull requests from various contributors.

2. Pavel Dmytrenko (pavdmyt)

   • Activity: 1 commit, 4 changes.
   • Recent Work: Fixed the description of the changeDefaultModel flag.
   • Collaboration: Worked closely with Eugen Eisler on documentation updates.

3. Noam Siegel (noamsiegel)

   • Activity: 2 commits, 176 changes.
   • Recent Work: Improved Jina AI integration for web scraping and question search.
   • Collaboration: Merged contributions related to Jina AI.

4. Mark Kazakov (mark-kazakov)

   • Activity: 1 commit, 27 changes.
   • Recent Work: Added vendor support for Mistral.
   • Collaboration: Collaborated with Eugen Eisler on merging pull requests.

5. Daniel Miessler (danielmiessler)

   • Activity: 32 commits, 620 changes.
   • Recent Work:
   • Updated README and added multiple patterns including extract_insights_dm.
   • Integrated new scripts for Raycast and improved documentation.
   • Addressed various issues and merged pull requests from other contributors.
   • Collaboration: Actively merged contributions from various developers.

6. Csquare Chen (csquarechen)

   • Activity: 3 commits, 43 changes.
   • Recent Work: Contributed to language command updates and flag descriptions.

7. Joseph Thacker (jthack)

   • Activity: 3 commits, 155 changes.
   • Recent Work: Added functionality for PDF conversion and updated README.

8. Marcel Ritzschke (marcelritzschke)

   • Activity: 1 commit, 16 changes.
   • Recent Work: Minor updates to documentation.

9. Max Leung (maxleungtszchun)

   • Activity: 1 commit, 29 changes.
   • Recent Work: Added a new pattern for extracting skills.

10. Other contributors (sleeper, mrtnrdl, jmanico, CJones-Optics, NerdyPunkDad, verebes1, rudi-bruchez, nep-0, kanaqsasak, rdegges, IanYoung-BO, songzhibin97, ALX99) have also made smaller contributions primarily focused on bug fixes, documentation updates, and adding new patterns.

Patterns and Themes

• The majority of recent activity is driven by Eugen Eisler and Daniel Miessler, indicating a strong leadership presence in development efforts.
• There is a focus on integrating AI capabilities with enhancements to existing features (e.g., Jina AI).
• The team is actively merging community contributions, showcasing a collaborative environment that encourages input from various developers.
• Documentation updates are frequent alongside feature additions, suggesting an emphasis on usability and user guidance as the project evolves.
• The project is transitioning smoothly with ongoing improvements in CI/CD processes and dependency management.

Conclusions

The development team is highly active with a clear focus on enhancing functionality while maintaining robust documentation practices. The collaborative nature of the project fosters community involvement which is essential for its growth and adaptability in the evolving AI landscape.