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Title: How to Automatically Generate Embedding for Updated Documents in a Confluence Space and Enable Real-Time Question Answering on the Updated Data?
Body: I'm currently working on accessing a Confluence space using Lang chain and performing question answering on its data. The embedding of this data are stored in a Chromadb vector database once I provide user name,API key and Space key.
However, I'm looking for a way to automatically generate embedding for any documents that change in real-time within the Confluence space and enable real-time question answering on the updated data. Any suggestions or solutions on how to achieve this would be greatly appreciated!
I just came across this thread whilst searching the web to find out if anyone has successfully attempted this. Have you made any progress since you posted this?
I don't have admin privileges so I don't think I can create webhooks, but that sounds like a good way to trigger a (re-)creation of a vector embedding when either new content is posted or old one is updated.
In the absence of webhooks, I'm toying with the idea of utilising the RSS feed as a compromise. It does have all the relevant data (URL link, creation time etc.).
It would be interesting to learn where you got to with your project if you were happy to share.
Welcome to the Atlassian Community!
Why are you doing this? Confluence is already a wiki that provides you with real-time access to all of its updated data, and if used as a knowledge base, suggests pages that answers questions to your users.
Could you explain what problem you are trying to solve here?