AdvisorU

Say Goodbye to Confusion: Welcome to AdvisorU, the AI Mentor You've Always Wanted! Discover our web-based AI Advisor chatbot app, utilizing RAG and LLM technologies with a visual planner and search!

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TEST OUR APP :) EMAIL: test@advisoru.com PASSWORD: advisoru

Tech Specs

  • RAG technology enhanced by embedding over 120 Khoury College courses into Pinecone for efficient data retrieval.
  • AWS EC2 for scalable, cloud-based hosting, ensuring reliable access and performance.
  • RESTful API architecture enables smooth interaction among front-end, back-end, and AI modules.
  • Streamlit-powered admin dashboard for efficient data crawling using Beautiful Soup, embedding information into Pinecone.
  • Course data managed in a server-side MySQL relational database for structured storage and retrieval.
  • Django as the backend framework, known for its scalability and reliability in data in request and response handling
  • Front-end crafted with Vue.js, offering a dynamic and engaging user interface designed from the ground up.

Inspiration

The creation of AdvisorU stemed from the common challenges students like us face in navigating their academic journeys, such as understanding degree requirements, selecting the right courses, and planning their academic future. We were inspired to leverage the power of AI to streamline this process, making academic planning accessible, efficient, and personalized for every student.

What it does

AdvisorU is a web-based application that employs RAG (Retrieval-Augmented Generation) and LLM (Large Language Models) technologies to provide an interactive chatbot. This AI advisor assists students in exploring their required courses, answering academic questions with detailed data, and offering personalized guidance. Additionally, AdvisorU features a comprehensive visual planner for mapping out all four years of college and a search functionality that encompasses every course offered at Northeastern University.

How we built it

Our team developed AdvisorU by harnessing advanced AI technologies. We leveraged RAG to enhance language generation with data retrieval capabilities, enabling our chatbot to deliver precise course information and requirements. By employing Django for the backend and integrating it with Vue.js for the front end, we aimed to create an exceptionally user-friendly experience. Additionally, we incorporated LLM technology to facilitate natural and intuitive interactions with the chatbot. The development of the visual planner and search features involved a synergistic blend of front-end and back-end technologies, ensuring a smooth and cohesive user experience.

Challenges we ran into

One of the primary challenges was ensuring the accuracy and relevance of the information provided by the AI chatbot. Langchain really is a hassle. Developing a system that could understand and process a wide range of academic inquiries required extensive tuning and testing. Additionally, creating a user-friendly visual planner that could handle the complexity of a four-year academic plan was a significant undertaking.

Accomplishments that we're proud of

We are incredibly proud of developing a tool that has the potential to revolutionize how students plan their academic paths. The seamless integration of RAG and LLM technologies to create a responsive and intelligent chatbot stands out as a significant achievement, especially as a first timer. Additionally, the completion of the visual planner, which offers a bird's eye view of a student's academic journey, marks a milestone in our project development.

What we learned

Throughout the development of AdvisorU, we learned about the complexities of natural language processing and the importance of user experience design. We gained insights into how AI can be applied to solve real-world problems, specifically in the educational sector. The project also taught us about teamwork, project management, and the iterative process of testing and refining technological solutions.

What's next for AdvisorU

That depends on you! Looking ahead, we aim to expand AdvisorU's capabilities to include more personalized recommendations, such as course suggestions based on career goals and interests. We plan to incorporate feedback mechanisms to continuously improve the AI's accuracy and relevance.

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