Shoaib Ahmad@shoaibahmad412

Despite growing awareness of the importance of nutrition in overall health and well-being, many individuals struggle to access personalized and accurate dietary guidance. Traditional methods of seeking advice from dietitians or nutritionists can be costly, time-consuming, and often inaccessible to large population segments. to solve this problem we made a nutrition chatbot. Our chatbot is a comprehensive and intelligent Dietitian model that leverages the power of artificial intelligence to deliver personalized dietary guidance. In conclusion, our Dietitian model represents a groundbreaking advancement in the field of personalized nutrition, leveraging cutting-edge AI technologies to deliver accurate, tailored, and accessible dietary guidance to users worldwide. Through the integration of Vectara, Mistral.ai, Langchain, and HuggingFace, we have created a chatbot that sets a new standard for precision, effectiveness, and user experience in the realm of dietary. assistance.

The AI-Powered Competitive Programming Chatbot is designed to assist competitive programmers by efficiently solving coding problems while offering a seamless, user-friendly interface. Developed by a team, the chatbot leverages advanced technologies such as vector embeddings for efficient data retrieval, enabling it to process problem statements and solutions accurately. With memory capabilities, the chatbot can remember previous queries for smoother conversations, enhancing the user experience. The project utilizes the Chroma Vector Database for efficient data storage and retrieval and is built using OpenAI’s o1-preview model. This combination enables the chatbot to address coding challenges from platforms like Meta Hacker Cup and Advent of Code. The development process focused on key components like user registration, login systems, and an intuitive chatbot interface. The team implemented modern UI designs and added features, such as the ability to download chat data in .docx format. Challenges such as data chunking and formatting issues were addressed using custom functions and regular expressions (regex) to properly format and differentiate chat messages. Moving forward, the team plans to expand the dataset and improve the chatbot’s memory for a smoother, more interactive experience. Overall, the chatbot integrates advanced AI techniques and user-friendly features to effectively support competitive programmers in solving complex coding challenges.