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.
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:
- The
main()
function connects to an email server, fetches new messages, and generates email replies using ChatGPT4. - The
senderInContacts()
function checks if the sender's email address is in the user's contacts. - The
getLabelForSender()
function gets the label or tag associated with the sender's email address. - The
generateReply()
function generates the email reply using ChatGPT4 based on the label or tag associated with the sender's email address. - The email reply is sent to the sender's email address using the
smtp.SendMail()
function.
To use the application, follow these steps:
- Clone the repository to your local machine.
- Replace the authentication details for the email server in the auth variable in the
main()
function. - Replace the server details for the email server in the
client.DialTLS()
andsmtp.SendMail()
functions in themain()
function. - Replace
YOUR_API_KEY_HERE
with your actual OpenAI API key in thegenerateReply()
function. - Implement a database or file to store the user's contacts and their labels and modify the
senderInContacts()
andgetLabelForSender()
functions to use this data. - Run the application using
go run main.go
.
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:
- Add error handling code to gracefully handle any errors that may occur during the email processing.
- 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.
- Use a more secure method for storing the user's contacts and their labels, such as a database with encryption and access controls.
- Implement more advanced email handling features, such as support for attachments, HTML emails, and multiple recipients.
- Add logging and monitoring features to track the performance and usage of the email reply engine.