🌍 AI Travel Planner

📋 Features

• Travel Recommendations: Get AI-powered suggestions for restaurants, hotels, attractions, activities, and more

• Local Information: View current weather, local time, and currency exchange rates

• Destination Insights: Access cultural and contextual information about your destination

• Modern UI: Dark-themed, responsive interface with smooth animations

• Multiple AI Models: Leverages both Google's Gemini and Ollama's models for enhanced recommendations

  Documentation :

  https://medium.com/@abhayemani8/ai-travel-planner-technical-documentation-bfa4d08e4985

🚀 Installation

Prerequisites

• Python 3.8+
• Flask
• Access to Google's Gemini API
• Ollama installed locally

Environment Setup

1. Clone this repository:

bash

git clone https://github.com/MONARCH1108/Travel_planner.git
cd ai-travel-planner

2. Create a virtual environment:

bash

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

bash

pip install -r requirements.txt

4. Create a .env file in the project root directory with the following variables:

GEMINI_API_KEY=your_gemini_api_key_here

Running the Application

Start the Flask development server:

bash

python app.py

The application will be available at http://localhost:5000.

📊 Project Structure

ai-travel-planner/
├── app.py                  # Main Flask application file
├── .env                      # Environment variables (not tracked in git)
├── requirements.txt        # Python dependencies
├── templates/                # HTML templates
│   └── index.html           # Main application template
└── README.md             # This file

🧩 How It Works

1. User Input: The user selects what they're looking for (restaurants, hotels, attractions, etc.) and their destination.
2. Data Collection: The application gathers relevant information:
   • Current weather data for the location (via Gemini AI)
   • Local time approximation
   • Currency exchange rates
3. AI Processing:
   • Google's Gemini model provides contextual information about the destination
   • Ollama LLM generates personalized recommendations based on the combined data
4. Presentation: Results are displayed in an intuitive, visually appealing interface.

🛠️ Technologies Used

• Backend: Flask (Python)
• AI/ML:
  • Google Generative AI (Gemini-2.0-flash)
  • Ollama (Llama3.2)
• Frontend:
  • HTML5/CSS3
  • JavaScript
  • Font Awesome
  • Animate.css
• APIs:
  • World Time API
  • Open Exchange Rates API

🚦 Version Information

This repository contains two versions of the AI Travel Planner:

• Version 1: A Streamlit-based application using Gemini LLM
• Version 2: A Flask-based web application using both Gemini and Ollama LLMs

The current README focuses on Version 2 (Flask-based).

⚙️ Configuration Options

You can modify the following in the application:

1. AI Models: Change the models in use in app.py:

   python

   # For Gemini
   model = genai.GenerativeModel('gemini-2.0-flash')
   
   # For Ollama
   ollama_response = ollama.generate(model="llama3.2", prompt=enriched_prompt)

2. UI Theme: Modify the CSS variables in templates/index.html to change the color scheme.

🔍 API Endpoints

• GET /: Main application interface
• POST /: Submit travel queries
• GET /api/weather?location={city}: Get weather data for a specific location

🧪 Future Enhancements

• User authentication and saved trips
• Integration with actual booking services
• Offline capability for travel guides
• Multi-language support
• AI-generated travel itineraries
• Social sharing functionality

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.