Express-Entry-AI-Chatbot

Express Entry AI Chatbot

The Express Entry AI Chatbot is a Python-based application designed to provide information about Canada's Express Entry immigration draws. It uses web scraping to collect data from the official website, processes the data, and integrates an AI-powered chatbot to answer user queries in real-time. The chatbot can be accessed via a graphical user interface (GUI) built with Tkinter.

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Features

1. Web Scraping:

   • Scrapes the latest Express Entry draw data from the official website using Selenium for dynamic content.
   • Handles errors and ensures data consistency through fallback mechanisms.

2. Data Processing:

   • Cleans and transforms scraped data into a structured format.
   • Stores data in a JSON file for efficient querying.

3. AI Chatbot:

   • Answers user queries using custom logic and a Hugging Face question-answering model.
   • Handles queries about:
     • Most recent draws.
     • Maximum and minimum CRS scores.
     • Draws for specific categories.

4. Graphical User Interface (GUI):

   • Provides an intuitive interface for interacting with the chatbot.
   • Displays user and chatbot messages in a conversational style.

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Installation

Prerequisites

• Python 3.8 or higher
• Google Chrome browser
• ChromeDriver (compatible with your Chrome version)

Steps

1. Clone the repository:

   git clone https://github.com/your-username/Express-Entry-AI-Chatbot.git
   cd Express-Entry-AI-Chatbot

2. Create a virtual environment:

   python -m venv .venv

3. Activate the virtual environment:

   • On Windows:

     .venv\Scripts\activate

   • On macOS/Linux:

     source .venv/bin/activate

4. Install dependencies:

   pip install -r requirements.txt

5. Download ChromeDriver:

   • Download ChromeDriver from here.
   • Place the chromedriver executable in your system's PATH or in the project directory.

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Usage

Running the Chatbot

1. Start the chatbot GUI:

   python gui.py

2. The GUI will open, and the chatbot will be ready to answer your queries.

Example Queries

• "What is the most recent draw?"
• "What is the maximum CRS score in the last draw?"
• "What is the minimum CRS score for the Federal Skilled Worker category?"

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Project Structure

Express-Entry-AI-Chatbot/
├── gui.py                  # GUI implementation using Tkinter
├── chatbot.py              # Chatbot logic and AI model integration
├── web_scraper.py          # Web scraping logic using Selenium and BeautifulSoup
├── express_entry_draws.json # JSON file to store scraped data
├── requirements.txt        # Python dependencies
└── README.md               # Project documentation

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How It Works

1. Data Collection

• The web_scraper.py script uses Selenium to scrape the latest Express Entry draw data from the official website.
• Data is cleaned, transformed, and saved to express_entry_draws.json.

2. Data Processing

• The chatbot loads the JSON file and prepares the data for querying.
• Data is indexed and structured for efficient lookups.

3. AI Chatbot

• The chatbot uses custom logic for specific queries (e.g., max/min CRS scores).
• For general queries, it uses a Hugging Face question-answering model (bert-large-uncased-whole-word-masking-finetuned-squad).

4. GUI

• The gui.py script creates a Tkinter-based GUI for user interaction.
• Users can type queries, and the chatbot responds in real-time.

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Error Handling

1. Web Scraping:

   • Fallback to column-based extraction if headers are missing.
   • Logs warnings for invalid or missing data.

2. Data Loading:

   • Attempts to scrape new data if the JSON file is missing or invalid.

3. Chatbot:

   • Provides clear error messages for unsupported queries or technical issues.

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Dependencies

• selenium: For web scraping dynamic content.
• beautifulsoup4: For parsing HTML content.
• transformers: For integrating the Hugging Face question-answering model.
• tkinter: For building the GUI.

Install all dependencies using:

pip install -r requirements.txt

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