From Handwriting to Code: The Multimodal STEM Workstation. Built for the Google AI Studio "Vibe Coding" Hackathon.
As Data Science and STEM students, we don't just work with text. We live in a world of handwritten integrals, complex neural network architectures, and messy whiteboard sketches.
Generic AI chatbots fail to understand this visual context. We needed a tool that could "see" the problem, understand the theory, and even write the implementation code. That's why we built Visual Study Buddy.
Visual Study Buddy is a multimodal workstation that combines Deep Reasoning with Code Execution. It operates in three specific modes:
- Input: Upload a photo of a handwritten math problem (e.g., Integration by Parts).
- AI Action: Recognizes handwriting, identifies the mathematical rule, and solves it step-by-step.
- Tech: Gemini Vision + LaTeX Rendering.
- Input: Ask the chat to "Visualize a Neural Network" or "Draw a Logic Circuit."
- AI Action: Instantly generates an accurate technical diagram to explain the concept.
- Tech: Gemini Image Generation.
- Input: Upload a sketch (or generated diagram) of a system architecture.
- AI Action: Analyzes the nodes and connections to write production-ready Python/NumPy/PyTorch code.
- Live Execution: Runs the generated code directly in the browser using a built-in Python environment.
This app was built using Google AI Studio. Follow these steps to run it on your machine.
Prerequisites: Node.js
-
Install dependencies:
npm install
-
Setup API Key:
- Create a file named
.env.localin the root directory. - Add your Gemini API key:
GEMINI_API_KEY=your_api_key_here - Note: You can also enter the API key directly in the app UI via the Settings gear icon.
- Create a file named
-
Run the app:
npm run dev
Open your browser to the local URL provided (usually
http://localhost:5173).
- Education: Reimagining how students learn abstract concepts visually.
- Technology: Pushing the boundaries of code generation from visual inputs.
- Science: Accelerating discovery by solving complex math instantly.
- AI Model: Google Gemini 1.5 Pro & Flash
- Platform: Google AI Studio
- Execution: Pyodide (Python in Browser)
- Frontend: React / Node.js
Built with ❤️ for the Gemini API Developer Competition.
