CloudCV

Mentors: Student: Zahed

This project aims to enhance the user experience for both challenge hosts and participants by developing an intelligent, RAG (Retrieval Augmented Generation) based chatbot. The chatbot will efficiently address queries related to challenge hosting, guidelines, troubleshooting, and FAQs. By integrating state-of-the-art NLP techniques with robust retrieval mechanisms, the solution will ensure prompt, accurate, and context-aware responses that reduce support overhead and streamline communication. Using the RAG approach, the chatbot will retrieve relevant information from challenge documentation and combine it with generative models to create coherent and helpful answers. This will empower hosts to manage challenges more effectively and assist participants in resolving queries, ultimately contributing to a smoother and more interactive challenge experience. Deliverables include : RAG Framework Implementation Chat UI Comprehensive Documentation Testing, Feedback, and Continuous Improvement

Mentors: Student: Akshat_Singh

This project is focused on significantly improving EvalAI’s usability by enhancing exsiting comprehensive test suite alongside a series of user experience enhancements. By increasing our test coverage, automating critical workflows, and refining the platform’s interface and documentation, this initiative aims to create a more robust, user-friendly, and resilient environment for both challenge hosts and participants. The enhanced test suite will ensure that all core functionalities, from challenge creation to submission processing are verified, reducing bugs and increasing system reliability. In parallel, targeted user experience improvements will simplify navigation, enhance error reporting, and streamline user interactions, leading to a more intuitive and supportive EvalAI ecosystem.

Mentors: Student: Thieu Nguyen

The proposal targets enhancing CloudCV by improving its admin dashboard, optimizing costs, and enhancing infrastructure monitoring. Key initiatives include developing EC2 admin actions, integrating Slack for streamlined challenge approvals, and automating resource management for cost efficiency and performance optimization.

Mentors: Student: Harshit Jain 2210

This project aims to make EvalAI better for users. It will improve how errors are handled, add more tests to make sure things work properly, provide clearer documentation to help people understand, and make the user interface more user-friendly with new features like a "My Work" tab. The main goals are to create tests for important components like APIs and workers, develop guides for things like API usage and AWS setup, make error messages more clear, and add new features to enhance the overall user experience.

Mentors: Student: Suryansh Pathak

This project aims to enhance and optimize the existing platform by implementing several important features and improvements. These changes include the addition of domains, tags, and a prize and sponsor page, as well as the introduction of a deregister process, a revamped profile page with a new tabular UI design, a participant team approval feature, and the inclusion of GMT time stamps and many more features.