How can I implement a vector storage solution using for my RAG application?

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Using for RPA logs is quite innovative. Since it uses an HNSW index, it is optimized for fast approximate nearest neighbor (ANN) searches. For real-time indexing, you should be aware that while it handles concurrent reads well, heavy write operations can sometimes cause latency spikes. I recommend batching your log entries into small groups before adding them to the collection. This reduces the overhead of index updates and ensures that your bots can retrieve historical error patterns in milliseconds without being blocked by the write process.

   Answered 2025-06-24 by Cynthia Taylor

Does support automatic aging of data, or would we need to write a custom script to purge old RPA logs to keep the index size manageable?

   Answered 2025-06-26 by Brandon Lee

• Brandon, currently it doesn't have an automated TTL or "Time To Live" feature for documents. You would need to use the delete method with a metadata filter on a timestamp field. I suggest running a daily cleanup job to remove logs older than 90 days to maintain optimal query performance.

     Commented 2025-06-27 by Charles Davis

The semantic search capability really helped our bots identify "stuck" processes by comparing current screenshots to historical error states.

   Answered 2025-06-29 by Lisa Perry

• That's a great point, Lisa. Leveraging image embeddings alongside text logs creates a multi-modal approach that significantly increases the accuracy of RPA diagnostic tools.

     Commented 2025-06-30 by Steven Moore