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solusops/researchmatehackathon

Analysis updated 2026-07-26

4PythonAudience · researcherComplexity · 4/5Setup · hard

TLDR

ResearchMate is a workspace for reading academic papers that uses multiple AI helpers to explain, quiz, and connect ideas, with a memory layer that tracks your learning progress over time.

Mindmap

mindmap
  root((repo))
    What it does
      Paper workspace
      AI study helpers
      Tracks learning
      Citation graph
    Tech stack
      Python
      Cognee memory
      Graph database
      Vector database
    Use cases
      Read papers faster
      Make flashcards
      Study with quizzes
      Connect research ideas
    Audience
      Students
      Researchers
    Features
      Feynman explanations
      Socratic pair reading
      Visual diagram generator
      Memory health tracking

Code map

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What do people build with it?

USE CASE 1

Upload an academic paper and get plain-language explanations of difficult paragraphs.

USE CASE 2

Generate flashcards and quizzes from selected text to study for exams.

USE CASE 3

Visualize how multiple uploaded papers cite and reference each other.

USE CASE 4

Track what you forget over time so future study sessions focus on weak spots.

What is it built with?

PythonCogneeGraph databaseVector database

How does it compare?

solusops/researchmatehackathon1038lab/agnes-ai3eyedtiger/video2vrcemote
Stars444
LanguagePythonPythonPython
Setup difficultyhardeasyeasy
Complexity4/52/51/5
Audienceresearchervibe codervibe coder

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · hard Time to first run · 1h+

Requires running Cognee with local graph and vector databases, plus OpenAI API access, making setup non-trivial.

The explanation does not mention a license, so it is unclear what permissions apply to this code.

In plain English

ResearchMate is a prototype app built for an OpenAI Build Week hackathon. It tries to solve a familiar problem for students and researchers: reading academic papers is a scattered, lonely process. You typically have a PDF open in one window, notes somewhere else, browser tabs for background reading, and a chatbot on the side. ResearchMate wants to collapse all of that into a single workspace centered on the paper itself. Instead of offering one chatbot, the app gives you a set of specialized helpers. One explains paragraphs in plain language, another challenges your understanding, one builds a wiki from what you read, one creates practice quizzes and flashcards, one tracks what you forget over time, and one tries to connect the paper to your broader research goals. You can select any paragraph and turn it into a Feynman-style explanation, a flashcard, a quiz question, a wiki entry, a debate prompt, a search for related papers, or a research idea. The app uses a system called Cognee as its memory layer. Cognee stores what you learn as a combination of a graph and vector database, running locally on your machine. Every helper agent reads this memory before responding and writes back to it after you work. This is what the README says makes ResearchMate a partner rather than a simple question-and-answer tool: it remembers your progress and adjusts future study sessions based on that history. Other features include a citation graph that shows how your uploaded papers reference each other, a pair-reading mode that conducts Socratic conversations, and a sandboxed visual generator that creates diagrams from paper content when it has enough context to do so reliably. The app also tracks memory health and reports when memory is degraded rather than silently falling back to simpler behavior. The README is notably detailed about the development process, explaining that the project was built using specification-driven development with AI coding agents. The full README is longer than what was shown.

Copy-paste prompts

Prompt 1
I have a dense academic paper on machine learning. Help me build a study workflow where I select difficult paragraphs and get plain-language Feynman-style explanations, then turn those into flashcards and quiz questions.
Prompt 2
Act as a Socratic study partner. I'll paste paragraphs from a research paper and I want you to challenge my understanding by asking probing questions before giving me the answer.
Prompt 3
Help me connect a paper I'm reading to my broader research goals. I'll describe my research area, and you should suggest how the paper's methods or findings could inform my work.
Prompt 4
Create a practice quiz with 5 questions based on this paper excerpt, then track which answers I get wrong and suggest follow-up study topics.

Frequently asked questions

What is researchmatehackathon?

ResearchMate is a workspace for reading academic papers that uses multiple AI helpers to explain, quiz, and connect ideas, with a memory layer that tracks your learning progress over time.

What language is researchmatehackathon written in?

Mainly Python. The stack also includes Python, Cognee, Graph database.

What license does researchmatehackathon use?

The explanation does not mention a license, so it is unclear what permissions apply to this code.

How hard is researchmatehackathon to set up?

Setup difficulty is rated hard, with roughly 1h+ to a first successful run.

Who is researchmatehackathon for?

Mainly researcher.

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