StudyForge — I Built an AI Study Assistant for a Friend Too Lazy to Type Prompts

RishavRajSingh44 — Mon, 05 Oct 2026 12:10:50 +0000

This is a submission for the Hacktoberfest Weekend Challenge: Build for a Friend

What I Built

I built StudyForge, an open-source AI study assistant for my friend, who was struggling with one surprisingly simple problem: he was too lazy to even type prompts into an AI tool to get notes, explanations, and quizzes.
So instead of asking him to figure out the right prompt every time, I built a study workflow around the task itself.
StudyForge lets a student upload course material such as PDFs, PowerPoint presentations, and Word documents and turn that material into structured study content including topic explanations, expected questions, and quizzes.
Core features:

Upload PDF, PPTX, or DOCX lecture slides and past exam papers (up to 20 files)
Enter your university name and course code — the AI calibrates everything to your institution's exam format
Web search augmentation: searches for your syllabus and exam format when a Tavily API key is configured
Streaming UI: results appear in real time as the model generates
PDF export: download notes, questions, or quiz as a branded PDF
No account required — anonymous sessions work out of the box

Demo

Live app: https://studyforge-8cdo.onrender.com

Code

RishavRajSingh44 / StudyForge

Open-source AI study assistant — upload lecture slides, get exam-ready notes, expected questions & quiz tailored to your institution

StudyForge

Open-source AI study assistant — upload your lecture slides and get exam-ready notes, expected questions, and an interactive quiz tailored to your university and course.

No account required. Works offline with a local Ollama model. Self-hostable.

Live Deployment

The public StudyForge demo is deployed on Render:

https://studyforge-8cdo.onrender.com

The hosted deployment uses Google Gemini 3.8 Flash (gemini-3.8-flash) for AI generation.

StudyForge also supports Ollama with configurable local models for self-hosted and offline use.

Why StudyForge?

Every student uploads lecture slides to ChatGPT and asks "make me notes". StudyForge does what that prompt can't.

Tool	Problem
ChatGPT / Gemini (raw)	Generic output — knows nothing about your university, syllabus, or exam style
Notability AI, Adobe AI	Requires an account and subscription; sends your documents to a third-party cloud
Manual prompt engineering	Produces notes, questions, or a quiz — never all three in one structured pass

StudyForge is different…

View on GitHub

How I Built It

StudyForge is built on Next.js 16 + React 19, with Supabase for persistence and
a multi-provider AI waterfall at its core. The open-source AI stack is what makes the
whole thing work:

The AI provider waterfall

Universal (Groq) → OpenAI → Ollama → Gemini → Claude
The first working provider wins. The key open-source piece is Ollama — it runs entirely on the user's machine, with no internet required after the model is downloaded.
The default local model is Qwen3:30B — an open-weight model that produces genuinely academic-quality output for this task.

Why Does Open Innovation Matter?

Open innovation makes StudyForge much more flexible than building the entire application around one closed AI API.
With Ollama and open-weight models, users can run models locally, choose models that fit their hardware and requirements, and experiment with different models without rebuilding the application.
It also means the AI layer can evolve independently of the rest of the product. A student can use a local model, while a hosted deployment can use a compatible cloud provider.
For a tool built around education, that flexibility matters: the goal is to make AI-assisted studying more accessible and adaptable rather than tying the entire experience to one proprietary model.

My Agent Session

The full development history is transparent via the commit log:github.com/RishavRajSingh44/StudyForge/commits

Prize Categories

Ollama — local open-weight inference (Qwen3:30B default, fully configurable)
Open Source AI — built around open-weight models and open-source frameworks
Render — application is deployed on Render, using it to host the Next.js app and make the AI-powered study workflow publicly accessible.
GitHub — Best Use of GitHub Copilot.

DEV Community: RishavRajSingh44