ARIA - Artificial Intelligence Route Information Assistant

ARIA: Effortless flight booking with AI. Voice or text input, sentiment analysis, real-time data. Node.js, React, Python, Amadeus, Google Gemini.

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ARIA - AI Route Information Assistant

ARIA (Artificial Intelligence Route Information Assistant) is a web-based application designed to assist users in finding the most optimal flight options using natural language inputs. With a special feature of speech recognition, ARIA streamlines the flight search process, making it easier and more intuitive for users to find suitable flights based on their preferences.

Key Features

  • Natural Language Processing: Utilizes natural language processing to interpret user inputs and understand their flight preferences.
  • Speech Recognition: Incorporates speech recognition capabilities, allowing users to interact with the application using voice commands.
  • Optimal Flight Selection: Calculates weighted sentiment scores based on user inputs and filters out the optimal flight options from data obtained through Amadeus and Google Gemini APIs.
  • Interactive Web Interface: Provides an interactive web interface built with React, allowing users to input their flight preferences and view the recommended options.
  • Integration with Amadeus and Google Gemini: Scrapes travel-related data using the Amadeus API and utilizes Google Gemini for enhanced flight recommendations.
  • AI-Powered Response Generation: Generates natural language responses to present the optimal flight options to the user in an easy-to-understand format.

Technologies Used

  • Node.js: Backend development and server-side scripting.
  • React: Frontend development for building the interactive user interface.
  • Python: Backend scripting for natural language processing and data processing.
  • Amadeus API: Integration with the Amadeus API for retrieving travel-related data and flight information.
  • Google Gemini: Utilization of Google Gemini for enhanced flight recommendations and data analysis.

How It Works

  1. User Input: Users input their flight preferences using natural language inputs or voice commands.
  2. Natural Language Processing: The input data is processed using Python scripts to calculate weighted sentiment scores based on user preferences.
  3. Optimal Flight Selection: Based on the calculated scores, the application filters out the most optimal flight options from the data obtained through Amadeus and Google Gemini APIs.
  4. Data Presentation: The optimal flight options are presented to the user in a natural language response, generated using AI-powered techniques.
  5. User Interaction: Users can interact with the presented options through the web interface, adjusting preferences as needed.

Python File Description

pyscript.py

This Python script implements a flight recommendation system based on user preferences. It loads flight data from a JSON file, processes user preferences from another JSON file, calculates weights based on sentiment analysis of user preferences, and then finds the best flight options based on these weights.

Dependencies

  • json: Used for reading and writing JSON files.
  • isodate: Utilized for parsing ISO-formatted durations.
  • nltk: Natural Language Toolkit library for sentiment analysis.

FlightSearch Usage

  1. Setup:

    • Ensure Python and dependencies (json, isodate, nltk) are installed.

  2. Data Preparation:

    • Prepare user_preferences.json and flights.json files with relevant data.

  3. Execution:

    • Run the script using Python.

Classes and Functions

  1. Flight Class:

    • Represents a single flight with attributes like flight ID, airline, departure, arrival, departure time, arrival time, price, duration, number of stops, and flight type.
    • Method: parse_iso_duration_to_hours

  2. analyze_sentiment Function:

    • Utilizes the NLTK SentimentIntensityAnalyzer to analyze the sentiment of text.
    • Returns a sentiment score.

  3. load_flights_from_json Function:

    • Loads flight data from a JSON file.
    • Creates Flight objects from the data and returns a list of flights.

  4. load_user_preferences Function:

    • Loads user preferences from a JSON file.
    • Returns preferences as a dictionary.

  5. calculate_weights Function:

    • Calculates weights for user preferences based on sentiment analysis.
    • Returns a dictionary of weights.

  6. find_best_flights Function:

    • Finds the best flights based on calculated weights.
    • Returns a list of flights sorted by score in descending order.

  7. save_flight_info_to_json Function:

    • Saves information about top-flight options to a JSON file.
    • Includes flight ID, airline, price, departure time, duration, stops, and score for each flight.

Example Output

The script saves the best flight options to results.json.

Getting Started

To get started with ARIA, follow these steps:

  1. Clone the repository to your local machine.
  2. Install the necessary dependencies by running npm install.
  3. Set up your Amadeus API and Google Gemini credentials.
  4. Run the application using npm start.
  5. Access ARIA through your web browser and start searching for optimal flight options!
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