Quivr, an open-source framework for building Generative AI productivity assistants, faces a slowdown in development due to unresolved critical bugs and integration challenges with Ollama and OpenAI models.
Recent pull requests (PRs) in the QuivrHQ/quivr repository indicate a focus on feature enhancements and maintenance tasks. Notable PRs include #3018, which enhances file integrity checks using SHA1, and #2991, which adds support for a new language model. However, multiple "work in progress" PRs suggest ongoing iterations without finalization. The development team, including Stan Girard, Antoine Dewez, Amine Diro, and Chloé Daems, has been active in both backend and frontend improvements. Recent activities include Stan Girard's release management efforts and Antoine Dewez's UI enhancements.
Developer | Avatar | Branches | PRs | Commits | Files | Changes |
---|---|---|---|---|---|---|
AmineDiro | 7 | 11/11/0 | 33 | 229 | 55552 | |
Stan Girard | 11 | 50/43/4 | 64 | 173 | 20415 | |
Chloé Daems | 6 | 9/8/0 | 36 | 93 | 17130 | |
Antoine Dewez | 3 | 32/31/0 | 65 | 131 | 4764 | |
aminediro | 2 | 0/0/0 | 6 | 29 | 2246 | |
pre-commit-ci[bot] | 1 | 0/0/0 | 1 | 262 | 658 | |
porter-deployment-app[bot] | 1 | 2/2/0 | 2 | 2 | 57 | |
None (renovate[bot]) | 2 | 2/0/1 | 2 | 2 | 8 | |
Dr. Artificial曾小健 (ArtificialZeng) | 0 | 1/0/0 | 0 | 0 | 0 |
PRs: created by that dev and opened/merged/closed-unmerged during the period
Timespan | Opened | Closed | Comments | Labeled | Milestones |
---|---|---|---|---|---|
7 Days | 9 | 8 | 14 | 1 | 1 |
30 Days | 33 | 37 | 77 | 12 | 1 |
90 Days | 103 | 113 | 224 | 27 | 1 |
1 Year | 272 | 200 | 914 | 27 | 1 |
All Time | 1243 | 1169 | - | - | - |
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.
The Quivr project currently has 74 open issues, with recent activity indicating a mix of bug reports and feature requests. Notably, several issues revolve around integration with Ollama and OpenAI, highlighting challenges in model compatibility and user authentication. A recurring theme is the struggle with CORS errors and API connectivity, particularly when deploying in various environments such as AWS or local setups.
Several critical bugs have been reported, including issues with brain creation, user authentication failures, and problems related to file uploads. The community appears engaged, with users actively seeking resolutions and offering insights into potential fixes.
Most Recently Created Issues:
Issue #3012: Fix PDF parsing bug in worker
Issue #3011: [Feature]: Renaming "BRAIN" with "EXPERT"
Issue #3010: [Feature]: JSON Document loader
Issue #2995: Chat with LLM history is reversed
Issue #2989: [Bug]: The brains are not being retrieved....
Most Recently Updated Issues:
Issue #3012: Fix PDF parsing bug in worker
Issue #3011: [Feature]: Renaming "BRAIN" with "EXPERT"
Issue #2995: Chat with LLM history is reversed
Issue #2989: [Bug]: The brains are not being retrieved....
Issue #2979: Async in Notifications
Overall, the project shows active engagement from the community but also highlights critical areas needing attention to improve stability and user experience.
The dataset contains a comprehensive list of pull requests (PRs) from the QuivrHQ/quivr repository, featuring both open and closed PRs. The focus is on recent updates, bug fixes, feature enhancements, and overall project maintenance.
PR #3019: wip
PR #3018: check presence on sha1
PR #3017: feat(frontend): show or hide tokens relative stuff
PR #3016: chore(main): release 0.0.299
PR #2991: feat: Add support for langchain-anthropic in LLMEndpoint completes CORE-144
PR #2988: feat: add knowledge_brain
PR #2970: Release/quivr core 0.1
PR #2945: chore(main): release core 0.0.14
PR #2944: chore(config): migrate renovate config
PR #2943: docs
The recent pull requests in the QuivrHQ/quivr repository reflect a robust development cycle characterized by active feature enhancements, bug fixes, and maintenance tasks aimed at improving the overall user experience and system performance.
Feature Enhancements: Several PRs focus on adding new features or enhancing existing functionalities, such as PRs #3017 (UI improvements) and #2991 (support for new language models). This indicates a commitment to evolving the product based on user needs and technological advancements.
Bug Fixes: A significant number of PRs address bugs or issues identified in previous versions, such as PRs #3018 (file integrity checks) and #2996 (sync worker improvements). This highlights an ongoing effort to maintain system reliability and user satisfaction.
Version Releases: The frequent occurrence of version release PRs (#3016, #2945) suggests a structured approach to software development, where incremental improvements are regularly packaged and deployed to users. This is crucial for maintaining user trust and engagement with the platform.
Documentation Improvements: The inclusion of documentation-focused PRs (#2943) emphasizes the importance of clear communication regarding features, usage, and troubleshooting within the community. This is vital for onboarding new users and ensuring existing users can fully leverage the platform's capabilities.
The presence of multiple "work in progress" (wip) PRs indicates that developers are actively iterating on features before finalizing them for review, which may reflect a collaborative culture where feedback is integrated continuously throughout development cycles.
Some PRs have been marked as "draft," suggesting that there may be ongoing discussions or unresolved issues that need addressing before they can be merged into the main branch. This could point to areas where further refinement or testing is necessary before deployment.
The comments from team members indicate an engaged development community that values peer review and collaborative problem-solving, which is essential for maintaining code quality and fostering innovation.
The analysis of pull requests within the QuivrHQ/quivr repository reveals a dynamic project environment focused on continuous improvement through feature development, bug fixes, and thorough documentation practices. The active engagement among team members further strengthens the project's potential for growth and adaptability in an ever-evolving technological landscape.
Stan Girard (StanGirard)
Antoine Dewez (Zewed)
Amine Diro (AmineDiro)
Chloé Daems (chloedia)
Stan Girard has been involved in backend configuration updates, release management, and implementing new features across both backend and frontend components. His recent work includes the release of version 0.0.298 and enhancements to Azure compatibility.
Antoine Dewez has focused primarily on frontend development, contributing several features aimed at improving user experience, such as the helpbox and help window functionalities. He has also worked on ordering models and fixing UI issues.
Amine Diro has made substantial contributions to backend stability by fixing SQLAlchemy-related bugs, enhancing transaction management, and improving overall code quality through refactoring efforts.
Chloé Daems has concentrated on integrating Notion sync capabilities into the application, working on syncing logic improvements, and addressing issues related to user notifications. Her contributions have been crucial for enhancing the sync functionality.
The development team is actively engaged in both feature development and maintenance tasks, reflecting a balanced approach to evolving the Quivr project while ensuring stability. The collaborative nature of their work suggests a healthy team dynamic focused on delivering quality software.