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Landing Page

Space Biology Knowledge Engine

A project for the 2025 NASA Space Apps Challenge — “Build a Space Biology Knowledge Engine”

📌 Challenge Overview

Your task is to build a functional web application that leverages AI, knowledge graphs, and/or other tools to summarize and make accessible the vast corpus of NASA bioscience data.

The challenge prompt:

“Build a Space Biology Knowledge Engine” — organize and surface insights from decades of NASA space biology research, making it easier for users (scientists, educators, enthusiasts) to explore life science in space.

You can find the official challenge here:
Build a Space Biology Knowledge Engine (NASA Space Apps 2025)


🎯 Project Goals & Scope

  • Ingest or access NASA bioscience / space biology datasets.
  • Provide an interface (web UI / API) for users to query, browse, and get meaningful summaries.
  • Possibly integrate AI / NLP models to generate summaries or answer domain-specific questions.

Chat Interface


Getting Started

Clone Repository:

git clone https://github.com/Hackathon-Team-WMU/nasa-space-bio

Backend setup

a) Install python:

pip install python3

b) Change directory

cd ./backend

c) Create .env folder and copy this into it. Make sure to add your api key

NEBIUS_API_KEY=

d) Install virtual environment for python:

Linux:

sudo apt install python3-venv -y        # Ubuntu/Debian

sudo dnf install python3-venv -y        # Fedora

Windows:

pip install virtualenv

e) Activate virtual environment

Linux:

python -m venv your_env_name
or

python3 -m venv your_env_name

source your_env_name/bin/activate

Windows:

python -m venv your_env_name

# Command Prompt
your_env_name\Scripts\activate.bat

# Powershell
your_env_name\Scripts\Activate.ps1

e) Install dependencies

pip install -r requirements.txt

or

pip3 install -r requirements.txt

g) Run fetch data script (~ 10 mins)

python scripts/fetchData.py

or

python3 scripts/fetchData.py

h) Generate LLM embeddings (~ 5 mins)

python llm/embeddings_builder.py

or

python3 llm/embeddings_builder.py

i) Launch app on local server

python app.py

or

python3 app.py

Frontend setup

a) Install node js here

https://nodejs.org/en/download

b) Change directories

cd ./frontend

c) Install dependencies

npm i

d) Create .env and link supabase

Copy into .env and fill in own info:

VITE_SUPABASE_PROJECT_ID=
VITE_SUPABASE_PUBLISHABLE_KEY=
VITE_SUPABASE_URL=

e) Run website

npm run dev

Go to local host

http://localhost:8080/

🤖 AI Usage Disclosure

This project utilized AI tools in compliance with NASA Space Apps Challenge guidelines:

  • Code Development: Lovable (base template) and Windsurf/ChatGPT (feature implementation) were used to accelerate development
  • Image Generation: The landing page hero image (frontend/src/assets/space-hero.jpg) was AI-generated and includes a visible "AI GENERATED" watermark
  • Human Oversight: All AI-generated code and content was reviewed, tested, modified, and integrated by the team

📄 For complete details, see AI_DISCLOSURE.md


👥 Team

This project was built for the NASA Space Apps Challenge 2025 by Hackathon-Team-WMU:
https://www.spaceappschallenge.org/2025/find-a-team/team-broncos/

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NASA Space Apps 2025 - Space Biology RAG Chat

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