CoCoPlanner - AI-Powered Travel Planning Assistant

AWS Cloud Infrastructure: Here

Project Overview

CoCoPlanner is an intelligent travel planning assistant that combines traditional travel planning with modern AI technology. Built with Python and powered by CrewAI, it provides personalized travel itineraries, real-time flight information, and comprehensive travel management through an interactive command-line interface.

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Key Features

1. Core Components

• CLI Interface: Beautiful ASCII art-based interface for user interaction
• AI Planning Engine: Powered by CrewAI for intelligent travel recommendations
• Flight Integration: Real-time flight data through Amadeus API
• Database System: MongoDB for plan storage and retrieval
• Email System: Automated notifications and updates
• Airport Database: Comprehensive global airport information

2. AI Integration

• CrewAI Framework: Powers the intelligent planning system
• OpenAI Integration: Enhanced natural language processing
• Contextual Understanding: Adapts to user preferences
• Smart Recommendations: AI-driven travel suggestions

3. Application Features

• Travel Planning: Intelligent itinerary creation
• Flight Search: Real-time flight information and booking assistance
• Plan Management: Save and retrieve travel plans
• Email Updates: Automated travel notifications
• Airport Lookup: Global airport database integration

4. Technical Features

• MongoDB Integration: Robust data persistence
• API Integration: Amadeus flight data system
• Docker Support: Containerized deployment
• Email System: SMTP-based notification system

5. Automation

• Automation System through GitHub Actions and AWS
  • Automated Docker builds and ECR pushes
  • Auto-scaling group management
  • Continuous deployment pipeline

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Technical Stack

• Backend: Python 3.8+
• AI Framework: CrewAI
• Database: MongoDB
• APIs: Amadeus Flight API
• Container: Docker
• Data Processing: Pandas
• Orchestration: Kubernetes

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Architecture

The application is built around a command-line interface that integrates with various services:

• AI Planning System powered by CrewAI
• Flight Data System through Amadeus API
• Storage System using MongoDB
• Notification System via SMTP
• Airport Information System using local database
• Automation System through GitHub Actions and AWS
  • Automated Docker builds and ECR pushes
  • Auto-scaling group management
  • Continuous deployment pipeline
• Kubernetes System for container orchestration
  • Deployment configuration for pod management
  • Service setup for load balancing
  • Secrets management for sensitive data

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System Components

1. Interface Layer: Command-line interface (interface.py)
2. Core Logic: Main application engine (main.py)
3. Flight System: Flight search and booking (flight.py)
4. Database Layer: Data persistence (database.py)
5. AI System: CrewAI configuration (my_crew.py)
6. Utility Layer: Helper functions (utils.py)
7. Airport System: Code lookup (airport_lookup.py)
8. Communication: Email system (send_email.py)
9. Plan Management: Retrieval system (retrieve_plan.py)
10. Kubernetes Config: Container orchestration (K8s/*.yaml)

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Security Considerations

• API Key Management: Secure handling of service credentials
• Database Security: MongoDB security best practices
• Email Security: Secure SMTP configuration
• Environment Variables: Sensitive data protection
• Configuration Files: Secure credential management

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Dependencies and Requirements

• Python Environment: Python 3.8 or higher
• Database System: MongoDB instance
• API Access: Amadeus API credentials
• AI Services: OpenAI API key
• Email Service: SMTP server access

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Important Notes

This repository contains the core application code for demonstration purposes. Configuration files and environment variables have been removed for security reasons. To run the application, please proceed to CocoLancer.

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"Old-World Charm, Future-Driven Travel" - CoCoPlanner