### Smart Room Allocation Algorithm

Source: https://context7_llms

Describes the smart room allocation system, which handles couple room bookings, therapist matching based on preferences, load balancing, and conflict resolution.

```APIDOC
Algorithm: Smart Room Allocation

Description: Optimizes room and therapist assignment for bookings.

Features:
  - Couple room flexibility: Can accommodate single bookings.
  - Preference-based therapist matching: Assigns therapists based on client or service preferences.
  - Load balancing: Distributes bookings evenly across available therapists.
  - Conflict resolution: Manages and resolves scheduling conflicts.

Logic:
  1. Process incoming booking requests, identifying service type and customer needs.
  2. Check availability of suitable rooms, considering couple room flexibility.
  3. Query therapist network for matches based on skills, preferences, and availability.
  4. Apply load balancing algorithms to distribute bookings among qualified therapists.
  5. Implement conflict resolution strategies for overlapping or conflicting assignments.
  6. Assign room and therapist, updating availability status.

Dependencies:
  - Therapist database with skills and preferences.
  - Room inventory with capacity and type.
  - Real-time availability data.

Outputs:
  - Assigned room and therapist for a booking.
```

--------------------------------

### React Frontend Stack with TypeScript

Source: https://context7_llms

Details the frontend technology stack, including React version, build tools, UI libraries, 3D rendering capabilities, and styling solutions.

```APIDOC
Technology: React Frontend Stack

Description: Modern and performant user interface built with React and TypeScript.

Key Technologies:
  - React 18+:
    - Latest features including Concurrent Mode and Suspense.
  - TypeScript:
    - Static typing for improved code quality and maintainability.
  - Vite:
    - Fast build tool and development server.
    - Optimized for quick cold starts and Hot Module Replacement (HMR).
  - PrimeReact:
    - Comprehensive suite of React UI components.
    - Provides pre-built components for forms, data display, navigation, etc.
  - Three.js:
    - JavaScript 3D library.
    - Used for rendering interactive 3D gift card previews.
  - TailwindCSS:
    - Utility-first CSS framework.
    - Enables rapid, responsive UI development.
  - Dark Mode Support:
    - Implemented using system preference detection.

Development Practices:
  - Component-based architecture.
  - State management (e.g., Context API, Redux, Zustand - specific choice not detailed).
  - Routing (e.g., React Router - specific choice not detailed).

Example Usage (Conceptual - PrimeReact Button):
import React from 'react';
import { Button } from 'primereact/button';

const MyComponent = () => {
  return (
    <div>
      <Button label="Click Me" icon="pi pi-check" onClick={() => alert('Button clicked!')} />
    </div>
  );
};

export default MyComponent;

Example Usage (Conceptual - Three.js):
// Integration of Three.js for 3D gift card previews would involve setting up a canvas,
// loading 3D models, and managing the scene, camera, and renderer within React components.
```

--------------------------------

### Frontend Dependencies

Source: https://context7_llms

JSON object detailing the frontend dependencies and their versions, including React, TypeScript, Vite, PrimeReact, Three.js, and Tailwind CSS.

```json
{
  "react": "^18.2.0",
  "typescript": "^5.0.0",
  "vite": "^4.4.0",
  "primereact": "^10.0.0",
  "three": "^0.156.0",
  "@react-three/fiber": "^8.0.0",
  "@react-three/drei": "^9.0.0",
  "tailwindcss": "^3.3.0"
}
```

--------------------------------

### Golang Backend REST API Structure

Source: https://context7_llms

Describes the structure and key technologies used for the Golang backend REST API, emphasizing high performance, ORM usage, authentication, and real-time capabilities.

```APIDOC
Technology: Golang REST API

Description: High-performance backend service for the platform.

Key Components:
  - Golang: Programming language for building the API.
  - GORM ORM: Object-Relational Mapping for database interactions.
  - JWT Authentication: Secures API endpoints using JSON Web Tokens.
  - Refresh Tokens: Manages token expiration and renewal.
  - WebSocket Support: Enables real-time communication features.
  - Docker Containerization: Packages the application for deployment.
  - Nginx Reverse Proxy: Manages incoming traffic, SSL termination, and load balancing.

API Design:
  - RESTful principles followed.
  - JSON for request and response payloads.

Authentication Flow:
  1. User logs in, receives JWT access and refresh tokens.
  2. Subsequent requests include JWT in the 'Authorization' header.
  3. API validates JWT signature and expiration.
  4. If expired, client uses refresh token to obtain new tokens.

Real-time Features:
  - WebSockets used for push notifications, live updates, etc.

Dependencies:
  - PostgreSQL database.
  - Redis (potentially for caching or session management).
  - Nginx.

Example Endpoint (Conceptual):
POST /api/v1/bookings
  Request Body:
    {
      "service_id": "uuid-service-123",
      "therapist_id": "uuid-therapist-456",
      "start_time": "2023-10-27T10:00:00Z",
      "duration_minutes": 60
    }
  Headers:
    Authorization: Bearer <jwt_token>
  Response (Success):
    Status: 201 Created
    Body:
      {
        "booking_id": "uuid-booking-789",
        "status": "confirmed"
      }
  Response (Error):
    Status: 400 Bad Request / 401 Unauthorized / 409 Conflict
    Body:
      {
        "error": "message"
      }
```

--------------------------------

### Dynamic Pricing Engine Logic

Source: https://context7_llms

Outlines the dynamic pricing engine's functionality, including time-based adjustments, demand-based surge pricing, discount code validation, and gift card balance calculations.

```APIDOC
Algorithm: Dynamic Pricing Engine

Description: Adjusts service prices based on various real-time factors.

Pricing Factors:
  - Time-based adjustments: Prices vary by time of day, day of week, or season.
  - Demand-based surge pricing: Increases prices during peak demand periods.
  - Discount code validation: Applies specified discounts to bookings.
  - Gift card balance calculations: Deducts value from gift cards.

Logic:
  1. Retrieve base price for the selected service.
  2. Apply time-based adjustments based on booking schedule.
  3. Assess current demand levels and apply surge pricing if applicable.
  4. Validate and apply any provided discount codes.
  5. If a gift card is used, calculate remaining balance after deduction.
  6. Calculate final price for the customer.

Inputs:
  - Service selection
  - Booking date/time
  - Demand indicators
  - Discount codes
  - Gift card details

Outputs:
  - Final calculated price.
  - Updated gift card balance (if applicable).
```

--------------------------------

### O(1) Availability Checker Algorithm

Source: https://context7_llms

Details the logic for an O(1) availability checker, utilizing pre-computed matrices and bitwise operations for efficient slot checking. It includes cache invalidation strategies and specifies a 15-minute time slot granularity.

```APIDOC
Algorithm: O(1) Availability Checker

Description: Checks service availability in constant time.

Components:
  - Pre-computed availability matrix: Stores availability status efficiently.
  - Bitwise operations: Used for rapid slot checking and manipulation.
  - Cache invalidation: Ensures data freshness upon booking changes.

Parameters:
  - Time slot granularity: 15 minutes.

Logic:
  1. Retrieve pre-computed availability data for the requested period.
  2. Apply bitwise operations to check for free slots within the specified granularity.
  3. Invalidate relevant cache entries if a booking or cancellation occurs.

Dependencies:
  - Booking system for change notifications.
  - Caching mechanism.

Limitations:
  - Assumes accurate pre-computation and timely cache invalidation.
```

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