juliemail

This morning, as a joke to show Julie the power of ChatGPT, I quickly wrote an email reply engine to answer her emails. The idea was simple: if the user was in her contacts, ChatGPT would tailor the message to be more specific based on a label Julie uses for the relationship. Adding more weighted labeling gave even more tailored responses.

How It Works

The email reply engine is written in Golang and uses the github.com/emersion/go-imap and net/smtp packages to connect to an email server, fetch incoming messages, and send email replies. The github.com/openai/openai-go/v2 package is used to generate the email reply text using ChatGPT4.

Here's a quick overview of how the code works:

1. The main() function connects to an email server, fetches new messages, and generates email replies using ChatGPT4.
2. The senderInContacts() function checks if the sender's email address is in the user's contacts.
3. The getLabelForSender() function gets the label or tag associated with the sender's email address.
4. The generateReply() function generates the email reply using ChatGPT4 based on the label or tag associated with the sender's email address.
5. The email reply is sent to the sender's email address using the smtp.SendMail() function.

Usage

To use the application, follow these steps:

1. Clone the repository to your local machine.
2. Replace the authentication details for the email server in the auth variable in the main() function.
3. Replace the server details for the email server in the client.DialTLS() and smtp.SendMail() functions in the main() function.
4. Replace YOUR_API_KEY_HERE with your actual OpenAI API key in the generateReply() function.
5. Implement a database or file to store the user's contacts and their labels and modify the senderInContacts() and getLabelForSender() functions to use this data.
6. Run the application using go run main.go.

Improvements

This code was written as a quick proof-of-concept and should not be used in production environments without additional security measures and extensive testing. Here are a few ways that the code could be improved:

1. Add error handling code to gracefully handle any errors that may occur during the email processing.
2. Implement more sophisticated methods for detecting the sender's label or tag, such as using machine learning algorithms to analyze the content of the email.
3. Use a more secure method for storing the user's contacts and their labels, such as a database with encryption and access controls.
4. Implement more advanced email handling features, such as support for attachments, HTML emails, and multiple recipients.
5. Add logging and monitoring features to track the performance and usage of the email reply engine.