🏫 School Reports API

A REST API for managing anonymous school reports. Students can submit complaints about bullying, violence, and other issues — automatically classified by AI and notified to school coordination via email.

🚀 How to run

1. Clone the repository:

git clone https://github.com/broislerdev/school-reports-api.git
cd school-reports-api

2. Create a virtual environment and install dependencies:

python -m venv .venv
.venv\Scripts\activate
pip install -r requirements.txt

3. Set up your .env file based on .env.example:

DATABASE_URL=your_supabase_connection_string
SUPABASE_KEY=your_supabase_key
SECRET_KEY=your_secret_key
GROQ_API_KEY=your_groq_api_key
SENDGRID_API_KEY=your_sendgrid_api_key
SENDGRID_FROM_EMAIL=your_verified_sender_email
COORDINATION_EMAIL=coordination_email

4. Run the server:

uvicorn main:app --reload

5. Access the interactive docs:

http://localhost:8000/docs

🕹️ Endpoints

Method	Endpoint	Description
GET	/reports/	List all reports
GET	/reports/{id}	Get report by ID
POST	/reports/	Submit a new report
PATCH	/reports/{id}/status	Update report status

🔁 Report Flow

1. Student submits a report via POST /reports/
2. Groq AI automatically classifies the complaint
3. Report is saved to Supabase (PostgreSQL)
4. SendGrid sends an email notification to the coordinator
5. Coordinator can view all reports and update their status

✅ Features

• 🕵️ Anonymous reports — student name is optional
• 🤖 AI classification — automatically categorizes complaints using Groq (Llama 3.1)
• 📧 Email notifications — coordinator is notified via SendGrid on every new report
• 📋 Status tracking — reports can be tracked through novo → em_analise → encaminhado → resolvido
• 🛡️ Input validation — Pydantic schemas for all endpoints

🗂️ Project Structure

school-reports-api/
├── database/
│   └── connection.py       # SQLAlchemy engine and session
├── db_models/
│   └── report_model.py     # Report ORM model
├── routers/
│   ├── auth_router.py      # Auth routes
│   └── report_router.py    # Report CRUD routes
├── schemas/
│   └── report_schema.py    # Pydantic validation schemas
├── services/
│   ├── groq_service.py     # AI classification service
│   └── email_service.py    # Email notification service
├── main.py
├── .env.example
└── requirements.txt

🧠 Concepts applied

• REST API with FastAPI
• ORM with SQLAlchemy
• Data validation with Pydantic
• AI integration with Groq (Llama 3.1)
• Email notifications with SendGrid
• PostgreSQL on Supabase
• Environment variables with python-dotenv
• Separation of concerns (routers / services / models / schemas)

🛠️ Built with

• FastAPI
• SQLAlchemy
• Supabase
• Groq
• SendGrid
• python-dotenv