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  UM student advisor chatbot

Welcome to the University of Manitoba Student Advisor Chatbot

Academic Advisor Hackathon Project

Inspiration

Our team was inspired by the difficulties students face when managing their academic schedules and planning future courses. We aimed to create a tool that helps students make informed decisions and communicate effectively with their academic advisors.

What We Learned

Throughout this project, we gained experience in:

• Building a user-friendly interface
  
• Integrating academic data
  
• Applying LLMs for AI-powered applications
  
• Collaborating under time constraints
  
• Overcoming unexpected technical challenges
  

How We Built It

We developed the chatbot using a combination of technologies, including:

• Backend: LangChain, Hugging Face, Flask, SQLite3, Cohere
  
• Frontend: JavaScript (jQuery), HTML/CSS
  
• Infrastructure: ngrok for tunneling
  
• Database: SQL for storing academic information
  

By integrating both backend and frontend seamlessly, we created a smooth and interactive experience for students and advisors.

Challenges Faced

One of the main challenges was integrating the backend with the frontend smoothly. However, through collaboration and persistence, we overcame these obstacles. Tight deadlines and technical issues pushed us to stay focused and iterate until we achieved the desired results.

Running the Project Locally

1. Install dependencies:
   pip install -r requirements.txt python development_server.py

   python app.py

Open index.html as a live server in your browser.

This project will be presented in person.

Built With

• css
• flask
• gemini
• html5
• huggingface
• javascript
• langchain
• ngrok
• python
• splite3