Initial PayGuard fraud detection system implementation

- Complete dual-layer architecture for fraud detection
- Phase 1: Docker Compose infrastructure (Kafka, Zookeeper, Redis)
- Phase 2: Mock ML models (Layer 1 fast, Layer 2 deep)
- Phase 3: FastAPI transaction ingestion with JWT auth
- Phase 4: Kafka consumer pipeline with feature extraction
- Phase 5: Test transaction producer with demo scenarios
- Phase 6: Clean code structure and comprehensive documentation
- Phase 7: End-to-end validation and demo readiness

Demonstrates key system design patterns:
- Microservices architecture with decoupled components
- Asynchronous event processing via Kafka
- Tiered decision-making (fast path vs deep analysis)
- Resilience patterns (circuit breaker for graceful degradation)
- Behavioral profiling with Redis caching

Ready for academic demonstration with clear pipeline observability.

Co-authored-by: Copilot <[email protected]>

requirements.txt

@@ -0,0 +1,8 @@
+fastapi==0.104.1
+uvicorn[standard]==0.24.0
+python-jose[cryptography]==3.3.0
+kafka-python==2.0.2
+redis==5.0.0
+pybreaker==1.4.0
+python-dotenv==1.0.0
+numpy==1.24.3