CrimeLink Analyzer Backend

Spring Boot backend service for the CrimeLink platform. This service provides authentication, officer/admin APIs, crime reporting, duty scheduling, weapon and vehicle management, and integrations with AI microservices for call analysis and facial recognition.

Tech Stack

• Java 21
• Spring Boot 3.5.8
• Spring Security (JWT-based auth)
• Spring Data JPA
• PostgreSQL (Supabase-compatible)
• Maven Wrapper (./mvnw)
• Docker (multi-stage build, JRE 21)

Project Structure

• src/main/java/com/crimeLink/analyzer
  • controller/ REST API endpoints
  • service/ business logic
  • repository/ database access
  • entity/ JPA entities
  • config/ security, JWT filter, CORS config
• src/main/resources/application.properties runtime configuration
• .env.example environment variable template
• database/ SQL scripts for schema/data
• Dockerfile container build and runtime setup

Prerequisites

1. Java 21 installed
2. PostgreSQL database available (local or cloud/Supabase)
3. Network access to required Python services:
   • Call Analysis service URL
   • Facial Recognition service URL
4. (Optional) Docker for containerized run

Environment Setup

Create your environment file from template:

cp .env.example .env

Set values in .env (minimum required):

• DB_URL
• DB_USERNAME
• DB_PASSWORD
• JWT_SECRET
• PYTHON_CALL_ANALYSIS_URL
• PYTHON_FACIAL_RECOGNITION_URL
• SUPABASE_URL
• SUPABASE_SERVICE_KEY

Optional values:

• SERVER_PORT (default: 8080)
• JWT_EXPIRATION (default: 900000)
• REFRESH_TOKEN_EXPIRATION (default: 604800000)
• SUPABASE_BUCKET (default: criminal-photos)
• CORS_ALLOWED_ORIGINS (default: *, restrict in production)

Database Initialization

If you are setting up a fresh database, apply SQL scripts from database/ as needed:

• auth_tables.sql
• facial_recognition_tables.sql
• field_officers_data.sql
• test_data.sql

Use your preferred SQL client or psql tool connected to your PostgreSQL database.

Run Locally

From project root:

./mvnw clean spring-boot:run

Windows:

mvnw.cmd clean spring-boot:run

The API starts on:

• http://localhost:8080 (or your SERVER_PORT)

Build and Test

Build:

./mvnw clean package

Run tests:

./mvnw test

Run packaged jar:

java -jar target/*.jar

Run with Docker

Build image:

docker build -t crimelink-analyzer-backend .

Run container with environment file:

docker run --env-file .env -p 8080:8080 --name crimelink-backend crimelink-analyzer-backend

Health check endpoint:

• GET /api/health

API Quick Start

Base URL:

• http://localhost:8080

Health:

curl http://localhost:8080/api/health

Test endpoint:

curl http://localhost:8080/api/test

Login example:

curl -X POST http://localhost:8080/api/auth/login \
  -H "Content-Type: application/json" \
  -d '{"email":"your-email@example.com","password":"your-password"}'

If login succeeds, use the returned access token:

curl http://localhost:8080/api/auth/me \
  -H "Authorization: Bearer <ACCESS_TOKEN>"

Main API Modules

• /api/auth authentication and token refresh
• /api/admin admin users, settings, backups, audit logs
• /api/crime-reports report CRUD, map, evidence upload/download
• /api/criminals criminal profile management
• /api/call-analysis AI call analysis integration
• /api/facial AI facial recognition integration
• /api/duty-schedules OIC duty scheduling
• /api/duties mobile duty retrieval
• /api/leaves leave request workflow
• /api/weapon weapon inventory and issue flows
• /api/vehicles vehicle management
• /api/users officer/user listings
• /api/safety-locations safety location features
• /api/announcements officer announcements

Security Notes

• JWT auth is enabled via Spring Security.
• Some endpoints are public (for example: auth, health checks, selected read APIs).
• Role-based authorization is enforced for many routes (Admin, OIC, Investigator, FieldOfficer).
• Restrict CORS_ALLOWED_ORIGINS in production.
• Never commit real secrets in .env.

Integration Notes

• Call analysis and facial recognition features require external Python services to be running and reachable via configured URLs.
• File/image workflows use Supabase configuration values.

Troubleshooting

• App fails on startup with datasource error:
  • Verify DB_URL, DB_USERNAME, and DB_PASSWORD.
• 401/403 for protected APIs:
  • Ensure valid Authorization: Bearer <token> and correct role permissions.
• AI endpoints fail:
  • Verify PYTHON_CALL_ANALYSIS_URL and PYTHON_FACIAL_RECOGNITION_URL are reachable.
• CORS issues in frontend:
  • Set CORS_ALLOWED_ORIGINS to your frontend origin(s), comma-separated.

Useful Commands

# Dependency check and compile
./mvnw clean compile

# Run only tests
./mvnw test

# Build without tests
./mvnw clean package -DskipTests