Background

This was a day-project during a hackathon to create an integration for Jira that utilizes an LLM somehow. This example was fully worked to the point of reading in an issue description and posting a comment on the initial Jira ticket.

Setup

High level

Some requirements before we can start

• Node
  • The .nvmrc allows you to use nvm install and nvm use to use this project's supported node version.
• AWS access
  • The terminal the deploy command is run from deploy-all requires AWS auth. In my case this was done using Single Sign On and programatic access environment variable credentials.
• Don't forget to use npm i

Low level

This project used some existant resources and cannot be deployed as is without modification. This project assumes a few things

• A lambda exists that handles prompt forwarding to an LLM generative AI service.
  • This could be rectified by, instead of sending prompts to some assumed LLM forwarding lambda, using the Open AI API or some similar service's interface.
  • My specific recommendation for a replacement would be to use this library as it fits well with this project and would require minimal LOE to implement: https://github.com/openai/openai-node
• A Jira auth token is saved to your .env file.
  • These can be a little tricky as there are many different versions of the Jira API t
    • The one this project uses is v3
  • These two Jira documentation points are a good starting point:
    • https://developer.atlassian.com/cloud/jira/platform/basic-auth-for-rest-apis/#get-an-api-token
    • https://developer.atlassian.com/cloud/jira/platform/basic-auth-for-rest-apis/#supply-basic-auth-headers

Developer Notes

• This project is made fairly functionally, only using one singleton JiraClient (which isn't strictly enforced).
• There are no programatic tests written currently. This was tested in a non-production environment but was never considered for production.
  • Tests could and should be added for the various pieces of this project if development was ever resumed.