Many students struggle with digesting large amounts of study materials such as PDFs and PowerPoint slides. Manual summarization is time-consuming, and traditional AI models often miss key context or generate summaries that don't match individual learning needs.
This project aims to enhance learning efficiency through AI-powered summarization, personalized study guidance, and interactive features.

• Reduce the time learners need to grasp complex materials by providing AI-generated summaries and guidance.

• Support learners with low background knowledge by breaking down technical terms and providing contextual explanations.

• Offer customized content based on user preferences, interests, and academic levels, enhancing motivation and understanding.

• Contribute to transforming traditional learning methods with AI-driven automation and interactivity.

• Web-based interface for uploading study materials (PDF, PPT).
• Clean UI/UX for seamless upload and result preview.

• Integration with Upstage API for precise parcing documants.
• Extracts essential concepts, keywords, and context-aware summaries.

• Summaries and study guides generated in markdown format.
• Real-time Q&A for clarification and faster knowledge acquisition.
• AI-generated quiz questions for review and active recall.

1. Learning Material Upload

   • Supports PDF and PPT.
   • Optional metadata (subject, topic).

2. AI Analysis Process

   • OCR conversion + text extraction.
   • Importance-based content ranking.
   • Keyword extraction and summarization.

3. Summary & Study Guide Generation

   • Outputs core summary + Q&A formatted guide.
   • Optional: Markdown, slides, or mindmap view.

4. User Feedback

   • Like/dislike rating system.
   • Request further clarification or explanations.

• Supports advanced academic use cases: thesis (Master’s/Ph.D.), paper analysis, and research summaries.
• Helps professionals draft business plans, technical proposals, and project reports.
• Custom mentoring for academic and corporate writing goals.
• Scalable to support institutions, labs, and enterprise-level documentation needs.

# clone the Frontend repo
git clone https://github.com/2025-AI-Seoul-Hackathon-Leafstorm/Frontend.git

# move to working dir
cd Frontend

# move branch to main
git checkout main

# ensure your node is 20.11.1 to run the project
node -v

# install package
npm install

# run project locally
npm run dev

Frontend
Backend / Infra

Full-stack	Full-stack / DevOps	Frontend	Backend	Backend
Jaeah Lee	Hyeonseung Oh	Inhyuk Ryu	Hyewon Kwon	Daehwan Kim

Last updated: 2025-04-13

• This project is licensed under the MIT license.
• See the LICENSE file for more details.