I built an AI Study Assistant for Fellow Learners

During a recent company hackathon, I developed an AI-powered study assistant designed to streamline the learning process. This project stems from an interest in effective learning methodologies, particularly the Zettelkasten concept, while addressing common frustrations with manual note-taking and traditional Spaced Repetition Systems (SRS). The core idea was to automate the initial note creation phase and enhance the review process, acknowledging that while active writing aids learning, an optimized review can significantly reinforce knowledge.

The AI assistant automatically identifies key concepts from conversations, generating atomic notes in a Zettelkasten-inspired style. These notes are then interconnected within an interactive knowledge graph, visually representing relationships between different pieces of information. For spaced repetition, the system moves beyond static flashcards by using AI to generate varied questions based on the notes, providing a more dynamic and contextual review experience. The tool also integrates with PDF documents, expanding its utility as a comprehensive knowledge management system.

The project leverages multiple AI models, including Llama 8B for efficient note generation and basic interactions, and Qwen 30B for more complex reasoning. OpenRouter facilitates model switching, while Ollama supports local deployment. The entire project is open source and available on GitHub. I’m interested in hearing about others’ experiences and challenges with conventional note-taking and SRS, and what solutions they’ve found effective.