The TEN Agent project is a sophisticated real-time conversational AI agent developed by the TEN-framework organization. It integrates various advanced technologies, including the OpenAI Realtime API and RTC capabilities, to offer features like weather updates, web search, computer vision, and Retrieval-Augmented Generation (RAG). The project is actively maintained and shows a trajectory of continuous enhancement and community engagement.
Ethan Zhang (plutoless)
EC (cyfyifanchen)
czhen (shczhen)
sunshinexcode
TomasBack2Future
Jay Zhang (wangyoucao577)
Ben Weeks (benagora)
Rohit Kadam (rohit-kadam-springct)
Timespan | Opened | Closed | Comments | Labeled | Milestones |
---|---|---|---|---|---|
7 Days | 5 | 5 | 5 | 4 | 1 |
30 Days | 18 | 15 | 15 | 8 | 1 |
90 Days | 49 | 61 | 109 | 21 | 1 |
All Time | 131 | 110 | - | - | - |
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 |
---|---|---|---|---|---|---|
Ben Weeks | 1 | 0/0/0 | 16 | 216 | 20352 | |
Ethan Zhang | 2 | 10/10/0 | 22 | 136 | 10183 | |
TomasBack2Future | 1 | 1/3/0 | 4 | 40 | 3004 | |
Jay Zhang | 2 | 1/1/0 | 6 | 44 | 1480 | |
EC | 1 | 4/4/0 | 9 | 12 | 1128 | |
czhen | 1 | 2/1/0 | 1 | 10 | 337 | |
sunshinexcode | 1 | 3/3/0 | 3 | 5 | 252 | |
Rohit Kadam | 1 | 0/0/0 | 1 | 2 | 13 | |
Girish Talekar (girishg4t) | 0 | 1/0/1 | 0 | 0 | 0 | |
Smaug (pandaBilbo) | 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 faces moderate delivery risks due to several unresolved critical issues and pull requests that are still in draft status. For instance, PR #481, which introduces screenshare support, is still open and requires review, potentially delaying integration. Additionally, critical issues like #476 and #471, focusing on demo enhancements, remain unresolved, impacting delivery timelines. |
Velocity | 3 | The project's velocity is moderate, with a slight backlog of issues over the past 30 days. While the issue closure rate over 90 days is positive, the presence of draft pull requests like PR #461 indicates potential delays in feature integration. The high volume of recent commits suggests active development but may lead to bottlenecks in code review processes. |
Dependency | 4 | There are significant dependency risks due to reliance on external libraries and APIs. For example, the Gemini V2V extension heavily depends on Google's genai library, and the OpenAI ChatGPT extension relies on the 'go-openai' library. Platform-specific issues like #464 also highlight compatibility challenges that could affect project stability. |
Team | 2 | Team-related risks appear low due to active collaboration and communication among team members, as evidenced by the high number of comments on issues and pull requests. However, the backlog of high-priority tasks suggests potential workload management challenges that need monitoring to prevent burnout. |
Code Quality | 3 | Code quality risks are moderate due to the complexity of recent changes and the bundling of large features into single pull requests. PR #434's unconventional approach to environment variable loading and PR #480's substantial code additions without detailed testing information highlight potential quality concerns. |
Technical Debt | 4 | The project faces significant technical debt risks due to complex integrations and substantial code changes without thorough documentation or testing. The Gemini V2V extension and OpenAI ChatGPT integration exemplify areas where technical debt could accumulate if not managed carefully. |
Test Coverage | 3 | Test coverage is moderate but could be improved. Several pull requests lack detailed testing information, such as PR #480 and PR #108, which introduces a ManifestProvider class without comprehensive tests. This gap poses risks for undetected bugs and regressions. |
Error Handling | 3 | Error handling is moderately risky due to insufficient logging and recovery mechanisms in complex extensions like Gemini V2V and OpenAI ChatGPT. While try-except blocks are present, they lack detailed error reporting, which could lead to unhandled exceptions in production environments. |
Recent GitHub issue activity for the TEN Agent project shows a focus on enhancing features and addressing critical bugs. There are several critical issues related to feature enhancements, such as #476, #471, and #470, which aim to improve demo functionality, deployment support, and prebuilt builds. Additionally, there are ongoing efforts to address critical bugs like #464, which involves platform compatibility issues. The project is actively engaging with community contributions and feedback, as seen in discussions around making RTC pluggable (#475) and supporting multiple input languages (#458).
Notable anomalies include the recurring theme of platform-specific issues, particularly with Apple Silicon compatibility (#464). Several issues highlight the need for better documentation and guidance for contributors (#475), indicating a potential gap in onboarding new developers. Additionally, there is a pattern of critical issues being created but not yet resolved, suggesting a backlog of high-priority tasks that require attention.
Common themes among the issues include enhancing multimodal capabilities, improving user experience through UI/UX changes, and expanding language support. The project also emphasizes community involvement in developing extensions and addressing feature requests.
#476: [FEATURE] adjust demo
#475: [FEATURE] make rtc pluggable
#471: [FEATURE] Make Demo prebuilt build instead of relying on local build
#476: [FEATURE] adjust demo
#475: [FEATURE] make rtc pluggable
#348: Can localized services be supported?
The focus on critical feature enhancements and bug fixes indicates an active development phase aimed at improving the core functionalities and user experience of the TEN Agent project.
#481: feat: support screenshare
#480: Add computer tool extension
#461: [DNM]feat(demo): refine header action and support RTM presence
#453: feat: only install requirements from required python extensions to speed up use/build processing
#434: fix: run go serve load env use Overload
Overload
, which has sparked discussion regarding its necessity.Overload
over Load
is debated due to potential security implications and best practices.#422: feat: support vision for multimodel
#365: Dev/vision tool python
#200: update astra server; update transcribe, polly extension.
#108: Add Manifest Provider
#78: Refactor the Server project
#478: Feat/gemini v2v
#477: docs: updating readme
#474: feat: support gemini v2v
#473: fix(demo): header components
#472: Fixed typo in property.json weather api key default examples agents
Overall, while the project is progressing well with numerous enhancements, attention should be given to older or stalled PRs to ensure they align with current project goals or are closed if obsolete.
agents/examples/demo/property.json
Structure and Quality:
${env:AGORA_APP_ID}
) allows for dynamic configuration, enhancing security by not hardcoding sensitive data.Recommendations:
agents/ten_packages/extension/gemini_v2v_python/extension.py
Structure and Quality:
GeminiRealtimeExtension
class is well-defined with methods handling various events (on_init
, on_start
, etc.).send_audio_out
), which might obscure issues during debugging.Recommendations:
docker-compose.yml
Structure and Quality:
ten_agent_dev
, ten_agent_playground
, ten_agent_demo
) with clear specifications for images, ports, volumes, and environment variables.ten_agent_network
) to facilitate communication between services..env
file for environment variables, promoting separation of configuration from code.Recommendations:
server/internal/config.go
Structure and Quality:
startPropMap
provides a mapping from request parameters to properties in a JSON file, which is efficient for dynamic configuration.Recommendations:
playground/src/common/graph.ts
Structure and Quality:
GraphEditor
class provides static methods for manipulating graph nodes and connections, promoting reusability.Recommendations:
addOrUpdateConnection
.Overall, these files demonstrate a high level of complexity appropriate for a sophisticated project like TEN Agent. However, improvements in documentation, error handling, and modularization could enhance maintainability and developer onboarding.
Ethan Zhang (plutoless)
EC (cyfyifanchen)
czhen (shczhen)
sunshinexcode
TomasBack2Future
Jay Zhang (wangyoucao577)
Ben Weeks (benagora)
Rohit Kadam (rohit-kadam-springct)
Overall, the development team is actively engaged in both feature development and maintenance tasks, with a strong focus on documentation and user accessibility.