
Caiteng Wen developed real-time fashion AI capabilities for the TEN-framework repository, focusing on a WebSocket-based extension that processes live video and audio streams while ensuring secure data flow by removing hardcoded credentials. They refactored the extension architecture, modularizing the FashionAIClient and stabilizing asynchronous event handling to improve reliability and maintainability. Caiteng also integrated graph components and Azure/OpenAI services to enhance data analytics and enable scalable AI-assisted workflows. Using Python, asynchronous programming, and data processing techniques, they updated the runtime for compatibility with new features, strengthening both security and stability. The work demonstrated depth in backend and AI integration engineering.

Monthly Performance Summary for 2024-10 (TEN-framework/ten-framework) Key focus: deliver real-time fashion AI capabilities, secure extension architecture, analytics enhancements, and runtime compatibility to drive business value and developer productivity.
Monthly Performance Summary for 2024-10 (TEN-framework/ten-framework) Key focus: deliver real-time fashion AI capabilities, secure extension architecture, analytics enhancements, and runtime compatibility to drive business value and developer productivity.
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