Socrato

Socrato is a full-stack AI study assistant that turns raw notes into concise summaries and practice questions. Socrato's goal is to help students study faster and more effectively before quizzes or exams. It has a Next.js frontend and FastAPI backend.

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Project Structure

Study-One/
├── frontend/   → Next.js web app
├── backend/    → FastAPI server
├── shared/     → Shared type definitions (API contract)

Both services run locally and communicate over HTTP.

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.env Format

# Backend
DATABASE_URL=
JWT_SECRET=
ENV=development
GEMINI_API_KEY="YOUR_GEMINI_API_KEY"

# Frontend
NEXT_PUBLIC_API_URL=

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Running the Frontend Locally

1. Navigate to the frontend folder:

   cd frontend

2. Install dependencies:

   npm install

3. Start the development server:

   npm run dev

4. Open your browser and go to:

   http://localhost:3000
   

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Running the Backend Locally

1. Navigate to the backend folder:

   cd backend

2. (Optional but recommended) Create a virtual environment:

   python -m venv venv
   source venv/bin/activate   # macOS/Linux
   venv\Scripts\activate      # Windows

3. Install dependencies:

   pip install -r requirements.txt

4. Start the server:

   uvicorn main:app --reload

5. Backend will be available at:

   http://localhost:8000
   

6. Health check endpoint:

   http://localhost:8000/health
   

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Cloning and Getting Started

Clone the repository:

git clone https://github.com/utmgdsc/Study-One.git
cd Study-One

From here you can run the frontend and backend independently using the instructions above.

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API Contract

POST /api/v1/generate

Generates study materials (summary and quiz questions) from user notes.

Request Body:

{
  "text": "string (required, non-empty)"
}

Response:

{
  "summary": ["string", "string", "..."],
  "quiz": [
    {
      "question": "string",
      "options": ["string", "string", "string", "string"],
      "answer": "string"
    }
  ]
}

Schema Files:

Location	Description
shared/types.ts	Canonical TypeScript interface definitions
frontend/src/types/api.ts	Frontend TypeScript types (mirrors shared)
backend/main.py	Pydantic models (mirrors shared contract)

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Notes

• Frontend runs on port 3000
• Backend runs on port 8000
• Make sure both are running for full functionality