Automated Email Customer Support System Using Python, ChatGPT, and Microsoft Email Services

Overview

This is an automated customer support system that leverages the power of OpenAI's ChatGPT and Microsoft's Email Services to offer near real-time email responses. The system ensures data security, quality control, efficient internal review, fast feedback loops, approval and sending with validation, and robust infrastructure with error handling.

Getting Started

These instructions will guide you through the setup process and help you deploy and scale the system.

Prerequisites

• A Microsoft Email account
• OpenAI's API key for using GPT-3/GPT-4
• Python 3.x
• A server where the application will run continuously

Installing

1. Clone the repository.
2. Install the dependencies using pip:

   pip install -r requirements.txt

System Design

The system is broken down into the following components:

1. Email Monitoring with Data Security: The system uses the Microsoft Graph API to monitor the specified Microsoft email account in real-time. Data is encrypted and securely processed.

2. Automated Response Generation with Quality Control: The system uses OpenAI's ChatGPT to generate responses, which are then reviewed using another AI model for quality control. If approved, they're sent to the internal team for further review.

3. Efficient Internal Review: A simple web dashboard is provided for the internal team to review responses. Metrics on the review and edit rates are tracked to improve the system over time.

4. Feedback Loop with Speed: Feedback from the internal team is rapidly processed and applied to the ChatGPT model to refine its responses.

5. Final Approval and Sending with Validation: Upon approval from the internal team, the system sends the response to the customer. It also includes a validation layer to avoid potential spam or repeated messages.

6. Robust Infrastructure and Error Handling: The system uses a webhook system with a secure, encrypted endpoint and has failover mechanisms in place.

Usage

Fill the required API keys and account credentials in the config file and run the main python script.

python main.py

Scalability

The system is designed to be scalable, and you can increase the number of email accounts it monitors by adding them to the configuration file. Furthermore, the system can be easily deployed on cloud servers like AWS or GCP to handle increased traffic and load.

Security and Data Protection

The system has been fortified against potential attacks. Encryption is used to ensure data security, and the system avoids unnecessary storage of sensitive customer data.

Error Handling and Redundancy

The system has robust error handling and redundancy mechanisms. If an error occurs during email processing, the system logs the error and moves to the next email. It also has failover mechanisms in place to ensure continued service even if a component fails.

Improvement and Feedback Loop

The system continuously tracks metrics and feedback to improve over time. The AI review model is retrained periodically based on the feedback from the internal team, and the performance of the AI model is continuously monitored.

Costs

This solution minimizes the usage of third-party APIs to remain cost-effective. The primary costs will be the usage of OpenAI's GPT-3/GPT-4, which is used for response generation and review.

Contributors

If you want to contribute to this project, please create a pull request and i will review your changes.

License

This project is licensed under the MIT License.

Final Notes

This system is designed to automate the email customer support process. It does not replace human customer support but rather assists in providing faster, more efficient responses. Always monitor and review the system's responses to ensure high-quality customer support. It is in development face and can be buggy.