Study Assistant

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  A screenshot of the chat feature explaining cellular respiration.

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  A screenshot of the chat feature quizzing the user about cellular respiration.

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  A screenshot of the study plan feature setting up a study plan about physics.

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  A screenshot of the concept map feature creating links about different topics in quantum physics.

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  A screenshot of the add material feature containing the ability to upload files and take photos directly from the camera.

Inspiration

Inspiration for this project has come from me not wanting to have to rely on tools like Quizlet and NotebookLM to study my notes since I have ADHD and I strongly detest studying and I don't enjoy school outside of computers. This tool is meant to help me and others that want this material to learn material to a depth that hasn't been done before and also improve the speed of learning.

What it does

This AI tool uses imported texts [supports MD files, PDFs, etc] and also image files to extract information to aid studying like a professional RAG would do.

How I built it

I used Python as the framework, utilizing both the CLI aspect and the Web UI application using Streamlit. These both have different features that are available, only the Web UI can upload photos directly from the camera but that may change in later updates if people desire a change.

Challenges I ran into

A challenge for me is always staying motivated in a project. Sticking to this task is definitely the first challenge I ran into but also the thought of using AI to create everything was so tempting! Instead I ended up using the AI to debug my code and also teach me how best to use ChromaDB and how it works.

Accomplishments that I proud of

I am not normally proud of myself for much, though it is an achievement that I have stuck to a project for longer than a week. If you go to my website here, you can see majority of my projects don't get continued as long due to me losing interest or motivation. I am also proud of me learning new tools, ChromaDB and Ollama, since that would be the necessary foundation for improving my most famous tool the finance kit.

What I learned

I learned how to use ChromaDB, a great platform that stores inputted data in a vector database that is then accessed to get a query. I also learned how to query a Ollama local model in this

What's next for Study Assistant

I plan to be adding more and more onto Study Assistant so if you want later versions go to this project's GitHub repo for the updates and for the whole process.

Built With

• pillow
• pytesseract
• python
• questionary
• rich
• streamlit