IVR Data Collection Web Application

This project is a web-based application designed for efficient collection and management of IVR (Interactive Voice Response) flow data. The application is developed using a Flask backend, MongoDB for database management, and a frontend built with HTML, Bootstrap, and JavaScript. It enables data collectors to input and manage IVR prompts and actions, which are then used by a dialing agent to interact with various insurance companies' IVR systems.

Table of Contents

• Features
• System Requirements
• Installation
• Running the Application
• Usage
• Folder Structure
• Future Improvements
• Contributing
• License

Features

• User-friendly interface for collecting and managing IVR data
• Role-based access control (Admin and Data Collector roles)
• Real-time form validation and dynamic data submission using AJAX
• Search and filter functionality for easy access to collected data
• Secure authentication and session management
• Data stored in MongoDB with encrypted communication over SSL/TLS

System Requirements

To run this project, ensure your system meets the following requirements:

• Python 3.7 or later
• MongoDB 4.4 or later
• Node.js and npm (for any additional frontend dependencies)
• Git (to clone the repository)

Installation

1. Clone the Repository

git clone https://github.com/yourusername/ivr-data-collection.git
cd ivr-data-collection

2. Set Up a Virtual Environment

It's recommended to create a virtual environment for the project dependencies.

To create and activate a virtual environment, follow these steps:

On macOS/Linux:

python3 -m venv venv
source venv/bin/activate

On Windows:

python -m venv venv
venv\Scripts\activate

3. Install the Required Packages

pip install -r requirements.txt

4. Set Up the Environment Variables

Create a .env file in the root directory and add the following environment variables:

FLASK_APP=app.py
FLASK_ENV=development
SECRET_KEY=your_secret_key
MONGO_URI=mongodb://localhost:27017/CureDial

Make sure to replace your SECRET_KEY with a secure key and MONGO_URI with your MongoDB connection URI.

5. Initialize Database

Once MongoDB is running, the application will automatically create the necessary collections upon first run. You do not need to pre-configure the database schema since MongoDB is schema-less.

Running the Application

1. Start the MongoDB Server

Start the MongoDB server by running the following command:

mongod

2. Run the Application

To run the application, execute the following command:

flask run

By default, the application will be accessible at http://127.0.0.1:5000/.

3. Access the Application

Open your web browser and navigate to http://127.0.0.1:5000/. You can now begin using the IVR Data Collection web application.

Usage

Once the application is running:

- Data Collectors can log in and start entering IVR data, including the prompts and actions that the dialing agent needs to perform.

- Administrators can manage users, review collected data, and have access to additional system settings.

Folder Structure

The project directory is structured as follows:

root/                         # Project's root directory
├── app.py                    # Main application entry point
├── README.md                 # Project documentation
├── requirements.txt          # Dependencies list
├── app/                      # Application core
│   ├── config.py             # App configuration
│   └── __init__.py           # Package initializer
│   ├── models/               # Database models
│   ├── routes/               # API routes
│   ├── services/             # Business logic/services
│   ├── static/               # Static assets
│   │   ├── css/              # Stylesheets
│   │   ├── images/           # Image files
│   │   ├── js/               # JavaScript files
│   │   └── jsons/            # JSON data files
│   ├── templates/            # HTML templates
│   └── utils/                # Utility/helper functions

Future Improvements

Some potential improvements for the application include:

• Adding more user roles and permissions
• Implementing additional data validation and error handling
• Enhancing the search and filter functionality
• Integrating automated testing for the application

Contributing

Contributions to this project are welcome. To contribute, follow these steps:

1. Fork the repository
2. Create a new branch (git checkout -b feature-branch)
3. Make your changes
4. Commit your changes (git commit -am 'Add new feature')
5. Push to the branch (git push origin feature-branch)
6. Create a new Pull Request

License

This project is licensed under the MIT License. See the LICENSE file for more details.