Updating embeddings in vector databases

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I'm new to how vector databases operate and the underlying concepts, especially when it comes to updating. I'm trying to apply the RAG pattern by combining a self hosted Qdrant database along with ChatGPT API. I'm creating embeddings by executing API calls to ChatGPT and saving them in Qdrant. Let's say I supplied contant of a document that contained proprietary information that was incorrect. How do I update my embeddings. If I only supply it with updated content, it would then contain contradictory information. Do I have to delete the whole collection and recreate it ?

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Erick Ramirez On BEST ANSWER

You are correct. You will need to do two things:

  1. You need to delete the outdated content/collection.
  2. Insert the new content with its [new] associated embedding.