Containerize fraud detection consumer - full Docker integration

- Added consumer/Dockerfile with all dependencies
- Updated consumer pipeline.py to use environment variables
- Updated features.py and decision.py to support env var configuration
- Updated docker-compose.yml to include consumer service
- Consumer now runs automatically with 'docker compose up'
- Proper Kafka and Redis networking for Docker
- Environment variables for ML_MODELS_DIR, KAFKA_BROKER, REDIS_HOST/PORT

Now entire PayGuard system runs with: docker compose up -d

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

consumer/features.py

@@ -15,6 +15,7 @@ context to improve model decision quality.
 import redis
 import numpy as np
 import logging
+import os
 from typing import Dict, List
 
 logger = logging.getLogger(__name__)
@@ -22,7 +23,13 @@ logger = logging.getLogger(__name__)
 class FeatureExtractor:
     """Extracts and engineers features from transactions"""
     
-    def __init__(self, redis_host: str = "localhost", redis_port: int = 6379):
+    def __init__(self, redis_host: str = None, redis_port: int = None):
+        # Support environment variables for Docker deployments
+        if redis_host is None:
+            redis_host = os.getenv("REDIS_HOST", "localhost")
+        if redis_port is None:
+            redis_port = int(os.getenv("REDIS_PORT", "6379"))
+        
         self.redis_client = redis.Redis(
             host=redis_host,
             port=redis_port,
@@ -30,6 +37,7 @@ class FeatureExtractor:
         )
         logger.info(f"[FEATURE EXTRACTOR] Initialized, redis={redis_host}:{redis_port}")
     
+    
     def get_user_profile(self, user_id: str) -> Dict[str, float]:
         """
         Retrieve user's behavioral profile from Redis.