Smart Travel Planner using Generative AI

An AI-powered application to create personalized, dynamic travel itineraries based on user preferences, real-time data, and natural language interaction.

Dataset Loading Steps

• The Smart Travel Planner utilizes a Kaggle dataset containing airport names, IATA codes, and related information to extract city names, airport codes, and airport names. This data is used for flight searches and destination plotting on Folium maps.

• Additionally, it dynamically gathers real-time information through:

  • Web scraping (using BeautifulSoup) for hotel and flight details.
  • Public APIs and Hugging Face models for AI-driven itinerary generation.

Installation and Execution Process:

Follow these steps to install and set up the Smart Travel Planner project:

1. Download and extract the project folder

   • Download the project folder from the provided drive link.

   • Extract it if it is zipped.

2. Navigate to the project directory

   • Open a terminal or command prompt and move into the project folder:

     cd smart-travel-planner

3. Create a virtual environment (optional but recommended):

   python -m venv venv

4. Activate the virtual environment:

   • On Windows:

   venv\Scripts\activate

• On Mac/Linux:

  source venv/bin/activate

5. Install all required Python libraries from the requirements.txt file:

   pip install -r requirement.txt

6. Generate the Airport Mapping File (needed for flights and city names):

   python flight_names.py

• This will create a airport_mapping.json file inside the project folder.

7. Obtain and Configure Hugging Face Token

• Get model access:

  • Visit Mistral-7B-Instruct-v0.2 on Hugging Face.

  • Request access if required and wait for approval.

• Create a new Access Token:

  • Go to your Hugging Face account settings → Access Tokens.

  • Click New Token, set Read permissions, and generate the token.

  • Copy the token securely.

• Login via Terminal:

  • Open your terminal and enter:

    huggingface-cli login

  • Paste the copied Hugging Face token when prompted

8. Run the Streamlit Application:

   streamlit run app.py

9. Access the application:

   • After running the command, the application will automatically open in your browser at:

     http://localhost:8501

Important Notes

• Python Version:
  Ensure you have Python 3.9 or higher installed on your system.

• Internet Connection Required:
  The application fetches real-time flight, hotel, and itinerary data. Keep your device connected to the internet while running the project.

• Run flight_names.py First:
  Always run flight_names.py before starting the app to generate the airport_mapping.json file necessary for flight and destination searches.

• Hugging Face Token Setup:

  • Make sure you have created and logged in with your Hugging Face Read access token using huggingface-cli login.

  • Access to the Mistral-7B-Instruct-v0.2 model must be granted beforehand from Hugging Face.

• Virtual Environment (Recommended):
  Use a virtual environment to avoid dependency conflicts with other Python projects.

• Browser Compatibility:
  The application is best accessed using Google Chrome or Microsoft Edge.

• Folder Structure:
  Keep all project files in their original folders (like /scraper/, /ai_utils/, /auth/) without renaming or moving them, to ensure smooth execution.

• Common Errors:

  • If streamlit or huggingface_hub command not found → Install using

    pip install streamlit huggingface_hub

  • If ModuleNotFoundError → Double-check that all libraries from requirements.txt are properly installed.