Feature/leaderelection

.env.example

@@ -0,0 +1,14 @@
+# PostgreSQL
+# ------------------------------------------------------------------------------
+POSTGRES_HOST=postgres
+POSTGRES_PORT=5432
+POSTGRES_DB=bookstore
+POSTGRES_USER=debug
+POSTGRES_PASSWORD=debug
+DATABASE_URL="postgresql+psycopg2://${POSTGRES_USER}:${POSTGRES_PASSWORD}@${POSTGRES_HOST}:${POSTGRES_PORT}/${POSTGRES_DB}"
+MODEL_NAME="all-MiniLM-L6-v2"
+ORDER_EXECUTOR_REPLICAS=3
+REDIS_HOST=redis
+REDIS_PORT=6379
+
+

.gitignore

@@ -1 +1,7 @@
-__pycache__
+__pycache__
+.env
+books.csv
+postgres_data/
+ai/
+.vscode/
+logs/

Makefile

@@ -0,0 +1,23 @@
+test_bookstore_post:
+	curl 'http://localhost:8081/checkout' \
+	  -H 'Accept: */*' \
+	  -H 'Accept-Language: en-US,en;q=0.9' \
+	  -H 'Cache-Control: no-cache' \
+	  -H 'Connection: keep-alive' \
+	  -H 'Content-Type: application/json' \
+	  -H 'DNT: 1' \
+	  -H 'Origin: http://localhost:8080' \
+	  -H 'Pragma: no-cache' \
+	  -H 'Referer: http://localhost:8080/' \
+	  -H 'Sec-Fetch-Dest: empty' \
+	  -H 'Sec-Fetch-Mode: cors' \
+	  -H 'Sec-Fetch-Site: same-site' \
+	  -H 'User-Agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/132.0.0.0 Safari/537.36' \
+	  -H 'sec-ch-ua: "Not A(Brand";v="8", "Chromium";v="132", "Google Chrome";v="132"' \
+	  -H 'sec-ch-ua-mobile: ?0' \
+	  -H 'sec-ch-ua-platform: "macOS"' \
+	  --data-raw '{"user":{"name":"John Doe","contact":"john.doe@example.ru"},"creditCard":{"number":"6011111111111117","expirationDate":"12/95","cvv":"123"},"userComment":"Please handle with care.","items":[{"name":"Book A","quantity":1},{"name":"Book B","quantity":2}],"billingAddress":{"street":"123 Main St","city":"Springfield","state":"IL","zip":"62701","country":"USA"},"shippingMethod":"Standard","giftWrapping":true,"termsAndConditionsAccepted":true}'
+proto:
+	python -m grpc_tools.protoc -I=utils/pb --python_out=utils/pb --grpc_python_out=utils/pb utils/pb/order_executor/order_executor.proto --proto_path=utils/pb --python_out=utils/pb --grpc_python_out=utils/pb
+start:
+	docker-compose up --build --scale order_executor=$(ORDER_EXECUTOR_REPLICAS)

data/books.sample.csv

@@ -0,0 +1,2 @@
+Title,Author,Genre,SubGenre,Height,Publisher
+Fundamentals of Wavelets,"Goswami, Jaideva",tech,signal_processing,228,Wiley

db/Dockerfile

@@ -0,0 +1,14 @@
+FROM docker.io/postgres:16
+
+RUN apt-get update && apt-get install -y \
+  git \
+  build-essential \
+  postgresql-server-dev-$PG_MAJOR \
+  && rm -rf /var/lib/apt/lists/*
+
+RUN git clone --branch v0.7.0 https://github.com/pgvector/pgvector.git \
+  && cd pgvector \
+  && make \
+  && make install
+
+COPY ./db/init-extensions.sql /docker-entrypoint-initdb.d/

db/init-extensions.sql

@@ -0,0 +1 @@
+CREATE EXTENSION IF NOT EXISTS vector;

docker-compose.yaml

@@ -14,6 +14,8 @@ services:
       # Mount the frontend directory
       - ./frontend/src:/usr/share/nginx/html
   orchestrator:
+    env_file:
+      - .env
     build:
       # Use the current directory as the build context
       # This allows us to access the files in the current directory inside the Dockerfile
@@ -35,7 +37,10 @@ services:
       - ./utils:/app/utils
       # Mount the orchestrator/src directory in the current directory to the /app/orchestrator/src directory in the container
       - ./orchestrator/src:/app/orchestrator/src
+      - ./orchestrator/logs:/app/orchestrator/logs
   fraud_detection:
+    env_file:
+      - .env
     build:
       # Use the current directory as the build context
       # This allows us to access the files in the current directory inside the Dockerfile
@@ -56,4 +61,108 @@ services:
       # Mount the utils directory in the current directory to the /app/utils directory in the container
       - ./utils:/app/utils
       # Mount the fraud_detection/src directory in the current directory to the /app/fraud_detection/src directory in the container
-      - ./fraud_detection/src:/app/fraud_detection/src
+      - ./fraud_detection/src:/app/fraud_detection/src
+  suggestions:
+    build:
+      context: ./
+      dockerfile: ./suggestions/Dockerfile
+    env_file:
+      - .env
+    ports:
+      - 50053:50053
+    environment:
+      # Pass the environment variables to the container
+      # The PYTHONUNBUFFERED environment variable ensures that the output from the application is logged to the console
+      - PYTHONUNBUFFERED=TRUE
+      # The PYTHONFILE environment variable specifies the absolute entry point of the application
+      - PYTHONFILE=/app/suggestions/src/app.py
+    volumes:
+      # Mount the utils directory in the current directory to the /app/utils directory in the container
+      - ./utils:/app/utils
+      - ./suggestions/src:/app/suggestions/src
+      - ./ai/models:/app/ai/models/
+
+  postgres:
+    build:
+      context: .
+      dockerfile: ./db/Dockerfile
+    image: bookstore_postgres
+    container_name: bookstore_postgres
+    volumes:
+      - ./postgres_data:/var/lib/postgresql/data
+      - ./db/init-extensions.sql:/docker-entrypoint-initdb.d/init-extensions.sql
+      - ./db/dummy_data/bookstore.sql:/docker-entrypoint-initdb.d/bookstore.sql 
+    env_file:
+      - .env
+    ports:
+      - "5432:5432"
+
+  transaction_verification:
+    env_file:
+      - .env
+    build:
+      # Use the current directory as the build context
+      # This allows us to access the files in the current directory inside the Dockerfile
+      context: ./
+      # Use the Dockerfile in the fraud_detection directorys
+      dockerfile: ./transaction_verification/Dockerfile
+    ports:
+      # Expose port 50052 on the host, and map port 50052 of the container to port 50051 on the host
+      - 50052:50052
+    environment:
+      # Pass the environment variables to the container
+      # The PYTHONUNBUFFERED environment variable ensures that the output from the application is logged to the console
+      - PYTHONUNBUFFERED=TRUE
+      # The PYTHONFILE environment variable specifies the absolute entry point of the application
+      # Check app.py in the fraud_detection directory to see how this is used
+      - PYTHONFILE=/app/transaction_verification/src/app.py
+    volumes:
+      # Mount the utils directory in the current directory to the /app/utils directory in the container
+      - ./utils:/app/utils
+      # Mount the transection_verification/src directory in the current directory to the /app/transection_verification/src directory in the container
+      - ./transaction_verification/src:/app/transaction_verification/src
+
+  redis:
+    image: redis:7
+    ports:
+      - "6379:6379"
+    volumes:
+      - redis_data:/data
+    command: ["redis-server", "--appendonly", "yes"]
+
+  order_executor:
+    env_file:
+      - .env
+    build:
+      context: .
+      dockerfile: ./order_executor/Dockerfile
+    depends_on:
+      - suggestions
+      - transaction_verification
+      - fraud_detection
+      - redis
+    environment:
+      - PYTHONUNBUFFERED=TRUE
+      - NODE_ID=${NODE_ID}
+      - PYTHONFILE=/app/order_executor/src/app.py
+    volumes:
+      - ./utils:/app/utils
+      - ./order_executor/src:/app/order_executor/src
+    command: ["python", "order_executor/src/app.py"]
+
+  order_debug:
+    build:
+      context: .
+      dockerfile: ./order_executor/Dockerfile
+    volumes:
+      - ./order_executor/src:/app/order_executor/src
+      - ./utils:/app/utils
+    command: ["python", "order_executor/src/debug.py"]
+
+
+volumes:
+    redis_data:
+
+
+
+

docs/README.md

@@ -1,3 +1,51 @@
-# Documentation
+## Overview
+The Bookstore Application follows a modern microservices-based architecture. The architecture consists of three primary layers:
+1. **Client-Facing Layer**
+2. **Microservices Layer (gRPC Services)**
+3. **Data Layer**
 
-This folder should contain your documentation, explaining the structure and content of your project. It should also contain your diagrams, explaining the architecture. The recommended writing format is Markdown.
+## Client-Facing Layer
+### REST Checkout API
+The **REST Checkout API** serves as the single entry point for client interactions. It handles customer checkout requests and orchestrates calls to the underlying microservices. Key features include:
+- Managing checkout requests efficiently.
+- Doing validation using schemas and data types.
+- Orchestrating multiple microservices to complete the checkout process.
+
+#### Threading Implementation
+The checkout process implements threading to enhance performance by:
+- Processing multiple microservice calls concurrently.
+
+## Microservices Layer (gRPC Services)
+This layer consists of independent services that handle specific tasks and communicate via **gRPC** 
+
+### 1. Suggestions Microservice
+- Connects to a **PostgreSQL database** with the **pgvector** extension.
+- Uses **sentence-transformers** to generate vector embeddings of book descriptions, its title and the author.
+- Provides **personalized book recommendations** based on vector similarity.
+- Enables **efficient semantic search** capabilities for books.
+
+### 2. Fraud Detection Service
+- Analyzes checkout transactions for potential fraud.
+- Returns a **risk assessment score** to the checkout service to prevent fraudulent activities.
+
+### 3. Validation Service
+- Performs **credit card validation** using the **Luhn algorithm** to verify card numbers.
+- Checks **expiration dates** to ensure the card is still valid.
+- Provides a **fast validation layer** before payment processing to prevent invalid transactions.
+
+## Data Layer
+### PostgreSQL Database
+- Serves as the **primary data store** for the application.
+- Stores book metadata, user transactions, and other essential records.
+
+### pgvector Extension
+- A **specialized PostgreSQL extension** that enables efficient **vector operations and similarity searches**.
+
+## Architecture Diagram
+![Architecture Diagram](./images/architecture-diagram.png)
+---
+
+## System Diagram
+![System Diagram](./images/system-diagram.png)
+
+---