Поиск дубликатов задач Jira с эмбеддингами OpenAI

## Try it out ### This n8n template builds a simple automation to ensure no JIRA issues go unassigned for more than a week to prevent them falling through the cracks. It uses AI to perform searching tasks against a Supabase Vector Store. This can be one way to help reduce the amount of manual work in managing the issue backlog for busy teams with little effort. ### How it works * This template contains 2 separate flows which run continuously via schedule triggers. * The first populates our Supabase vector store with resolved issues within the last day. This helps keep our vector store up-to-date and relevant for the purpose of finding similar issues. * It does this by pulling the latest resolved issues from JIRA and populating the Supabase vectorstore with carefully chosen metadata. This will come in handy later. * The second flow watches for stale, unassigned issues for the purpose of aut-assigning to a relevant team member. * It does this by comparing the stale issue against our vector store of resolved issues with the goal of identifying which team member would have best context regarding the issue. * In a busy team, this may net a few team members as possible candidates to assign. Therefore, we can introduce additional logic to count each team member's assigned, in-progress issues. This is intended to not overload our busiest members. * The team member with the least assigned issues is pressumed to have the most capacity and therefore is assigned. A comennt is left in the issue to notify the team member that they've been auto-assigned due to age of issue. ### How to use * Modify the project and interval parameters to match those of your use-case and team members. * Add additional criteria before assigning to a team member eg. department, as required. ### Need Help? Join the [Discord]({{ $env.WEBHOOK_URL }} or ask in the [Forum]({{ $env.WEBHOOK_URL }} Happy Hacking!