CopilotKit is a software project under the organization CopilotKit, designed to integrate AI assistants into applications via a React UI and infrastructure. The project is in active development, with significant community engagement and comprehensive documentation. Its trajectory suggests continued growth and feature expansion.
Ran Shemtov (ranst91)
ExperimentalEmptyAdapter
issue and improved error handling.Ariel Weinberger (arielweinberger)
Tyler Slaton (tylerslaton)
Markus Ecker (mme)
Suhas Deshpande (suhasdeshpande)
Renovate[bot]
Timespan | Opened | Closed | Comments | Labeled | Milestones |
---|---|---|---|---|---|
7 Days | 4 | 2 | 2 | 0 | 1 |
30 Days | 17 | 21 | 33 | 1 | 1 |
90 Days | 56 | 83 | 192 | 1 | 1 |
1 Year | 196 | 141 | 856 | 8 | 1 |
All Time | 237 | 158 | - | - | - |
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 |
---|---|---|---|---|---|---|
Markus Ecker | 6 | 8/5/1 | 25 | 183 | 17600 | |
Ariel Weinberger | 5 | 8/4/0 | 93 | 88 | 9824 | |
Tyler Slaton | 6 | 14/12/2 | 16 | 103 | 8401 | |
renovate[bot] | 3 | 3/2/0 | 3 | 51 | 8336 | |
Ran Shemtov | 3 | 15/15/2 | 26 | 67 | 2773 | |
github-actions[bot] | 2 | 5/4/1 | 28 | 41 | 2365 | |
Suhas Deshpande | 4 | 6/6/0 | 12 | 37 | 976 | |
Atai Barkai | 1 | 0/0/0 | 1 | 1 | 4 | |
Savar Bhasin (savarbhasin) | 0 | 1/0/0 | 0 | 0 | 0 |
PRs: created by that dev and opened/merged/closed-unmerged during the period
Risk | Level (1-5) | Rationale |
---|---|---|
Delivery | 3 | The project shows a mixed trend in issue resolution, with a backlog of open issues (79) and pull requests (35), which could impact delivery timelines. Notably, critical bugs like #1252 affecting core functionalities pose risks if not resolved promptly. The high number of branches and commits indicates active development but also potential integration challenges. While community engagement and documentation efforts are strong, the lack of structured prioritization in issue management could hinder timely delivery. |
Velocity | 3 | The project exhibits high development velocity with significant contributions from key developers like Ariel Weinberger and Markus Ecker. However, the disparity between open and merged pull requests suggests potential bottlenecks in code review processes. The presence of numerous open issues and pull requests indicates ongoing development but also potential delays in integration, impacting overall velocity. Automated processes contribute positively to workflow but require careful management to avoid disruptions. |
Dependency | 4 | The project relies heavily on external libraries and automated tools, as seen in the 'use-chat.ts' file and commit activities involving bots. Issues like #1246 and #1236 highlight dependencies on specific frameworks and AI models, posing risks if integrations are not seamless. Frequent changes to package.json files suggest challenges in dependency management, which could affect stability if not addressed. The absence of changeset documentation in some PRs further exacerbates this risk. |
Team | 2 | The project benefits from strong community engagement and collaboration among contributors, as evidenced by active participation in events like Hacktoberfest. This fosters a supportive environment that mitigates team-related risks such as burnout or conflict. However, the high volume of contributions and open issues may strain resources if not managed effectively. The cohesive approach to development across different areas reflects good team dynamics. |
Code Quality | 3 | While there is a strong focus on code quality with efforts to improve error handling and maintainability, the complexity of some integrations necessitates thorough testing. High volumes of changes by contributors like Markus Ecker suggest significant refactoring or feature implementation, which could impact code quality if not adequately reviewed. The presence of minor fixes and documentation improvements indicates maintenance focus but also highlights areas needing attention. |
Technical Debt | 4 | The accumulation of open issues (79) and older pull requests (e.g., #1165) suggests potential technical debt if not addressed. Frequent updates to critical files like 'use-chat.ts' indicate ongoing development but also risk introducing complexity without proper documentation or testing. The lack of changeset management in some PRs poses additional risks for technical debt accumulation. |
Test Coverage | 3 | The project maintains high test coverage with most recent PRs passing all tests before merging, indicating a solid foundation for catching bugs. However, failed tests like those in PR #1251 highlight areas needing improvement. The complexity of some features necessitates comprehensive testing to ensure reliability and prevent regressions. |
Error Handling | 2 | Significant improvements have been made in error handling, such as the introduction of custom error classes by Ran Shemtov and enhanced UI feedback for errors. These efforts indicate robust error management practices, reducing risks related to uncaught errors or application crashes. However, continuous monitoring is necessary to maintain these standards. |
Recent activity in the CopilotKit repository includes a variety of issues, with a mix of feature requests, bug reports, and documentation improvements. The project is actively maintained, as evidenced by the frequent updates and the engagement from both contributors and maintainers.
Bug Reports: Several issues highlight bugs related to integration and functionality, such as #1252 where a hook's state remains true after execution, and #1224 regarding network errors after version updates. These indicate ongoing challenges in maintaining stability across updates.
Feature Requests: There is a strong interest in expanding the capabilities of CopilotKit, with requests for new integrations (#1246 for tsoa runtime), additional connectors (#1236 for AI/ML API provider), and support for more frameworks (#310 for Sveltekit).
Documentation Needs: Multiple issues emphasize the need for improved documentation, such as #1167 on authorization examples and #1151 requesting AWS Lambda examples. This suggests that while the project is robust, users require clearer guidance to fully leverage its capabilities.
Community Engagement: The project encourages community contributions, as seen in issues related to Hacktoberfest (#789 - #785), which aim to engage developers in creating demo applications using CopilotKit.
Technical Challenges: Issues like #941 highlight technical complexities in integrating third-party services or adapting existing functionalities to new environments (e.g., Next.js 15 compatibility).
Overall, CopilotKit's GitHub issues reflect an active development cycle with a focus on expanding features, improving documentation, and addressing integration challenges. The community's involvement through events like Hacktoberfest indicates a healthy ecosystem around the project.
#1254: feat: allows dev mode for cloud onboarding flow
#1251: Load agent state
threadId
is provided. There is a warning about aligning the LangGraph python executor with the Cloud executor.#1248: Feat/trigger cloud deploy action
#1247: chore: dynamic copilotkit cloud qa
#1240: fix: properly handle prereleases with semver instead of treating all lettered versions as latest
#1165: fix: use react 19 for all cpk packages
#1112 and #1108 (Dependency Updates)
#1253: fix: rename ExperimentalEmptyAdapter to EmptyAdapter
#1249 & #1250 (UI Improvements and Documentation)
#1245 & #1244 (Travel Example Fixes)
use-chat.ts
useChat
that encapsulates the chat logic, making it reusable across components.UseChatOptions
and UseChatHelpers
. This enhances code readability and maintainability.useRef
and useState
hooks is appropriate for managing mutable state and asynchronous operations.addErrorToast
suggests user feedback mechanisms are in place for error scenarios.AbortController
for canceling ongoing requests is a good practice for managing network resources. Debouncing logic could be considered for input handling if not already implemented elsewhere.copilot-runtime.ts
CopilotRuntime
) is appropriate for encapsulating runtime logic. It separates concerns by defining interfaces for request and response types.Chat.tsx
useCopilotChat
.onSubmitMessage
. Consider adding user feedback mechanisms for better UX.Presentation.tsx
useState
and useMemo
. Potential performance issues might arise from frequent re-renders if slide data changes rapidly.generate-changelog.js
Overall, the codebase demonstrates strong adherence to modern development practices with effective use of TypeScript for type safety and React hooks for state management. Opportunities exist to enhance inline documentation and error handling further across files.
Ran Shemtov (ranst91)
ExperimentalEmptyAdapter
, improving error handling, and enhancing UI for error messages.Ariel Weinberger (arielweinberger)
Tyler Slaton (tylerslaton)
Markus Ecker (mme)
Suhas Deshpande (suhasdeshpande)
Renovate[bot]
Frequent CI/CD Enhancements: The team is actively working on improving the CI/CD pipeline, focusing on automation of releases, custom prerelease tags, and workflow optimizations. Ariel Weinberger is leading these efforts with significant contributions from Ran Shemtov.
Documentation and Tutorial Improvements: There is a strong emphasis on maintaining up-to-date documentation, particularly for tutorials. Tyler Slaton has been instrumental in refining tutorial content, ensuring clarity and addressing any drift-related issues.
Error Handling Enhancements: The team is focused on improving error handling mechanisms within the project. Ran Shemtov has introduced custom error classes and improved UI feedback for errors.
Feature Development: New features are being actively developed, such as state machine examples by Tyler Slaton and LangGraph state loading by Markus Ecker. These developments indicate ongoing efforts to expand the project's capabilities.
Collaboration Across Team Members: There is notable collaboration among team members across different areas of the project, including CI improvements, feature development, and documentation updates. This collaborative approach helps ensure consistency and quality across the project.
Overall, the recent activities reflect a balanced focus on infrastructure improvements, feature enhancements, documentation quality, and collaborative development practices.