Research Tutor

AI-powered explainer for research papers — built with Streamlit + FastAPI + Gemini

Live App

Built to make reading, understanding, and remembering research papers easier for everyone.

Why have I built this?

In this era, the influx of research papers has exploded : new discoveries, frameworks, and breakthroughs are published daily.
But understanding them has become increasingly difficult.

Research is no longer just for PhDs or academics. It is for developers, students, and professionals across industries now need to interpret research to stay relevant.

Research Tutor bridges that gap.
It breaks down dense academic papers section by section, explains them in plain language, builds analogies for better memory, and offers mini quizzes for quick revision.

The goal: democratize access to knowledge and make complex research understandable for everyone.

Tech Stack

| Layer | Technology | | ----------- | ----------------------------------------------- | | Frontend | Streamlit (Python) | | Backend | FastAPI + Uvicorn | | AI Model | Google Gemini 1.5 Flash (v1beta) | | PDF Parsing | PyPDF | | Hosting | Railway | | Environment | .env (local) / Railway Variables (production) |

Features

Paste any research paper or arXiv link — automatically parsed into logical sections.
Choose your reader level: casual, student, or expert.
Select your language: English or Hindi.
Get structured AI outputs for every section:

| Section | Description | | -------------- | ---------------------------------------------- | | Explain | 2–3 paragraphs summarizing the section clearly | | Analogy | Real-world comparison for easy recall | | Key Points | 3–6 concise, factual takeaways | | Mini Quiz | Quick comprehension checks with answers |

Roadmap

[ ] Add PDF file upload support
[ ] Allow summarizing multiple sections at once
[ ] Export summaries to Markdown / PDF
[ ] Add more regional languages
[ ] “Explain like I’m 15” mode