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authorLain Soykaf <lain@lain.com>2024-05-19 13:24:24 +0400
committerLain Soykaf <lain@lain.com>2024-05-19 13:24:24 +0400
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parent6a3a0cc0f5995185428c92f3c53e9c8524ea6856 (diff)
downloadpleroma-6ec306d0684f3c5c05d768a3c431008925f21f15.tar.gz
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Docs: Add more information about index memory consumption.
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@@ -26,7 +26,7 @@ You will also need to create the Qdrant index once by running `mix pleroma.searc
To see the available configuration options, check out the QdrantSearch section in `config/config.exs`.
-The default indexing option work for the default model (`snowflake-arctic-embed-xs`). To optimize for a low memory footprint, adjust the index configuration as described in the [Qdrant docs](https://qdrant.tech/documentation/guides/optimize/).
+The default indexing option work for the default model (`snowflake-arctic-embed-xs`). To optimize for a low memory footprint, adjust the index configuration as described in the [Qdrant docs](https://qdrant.tech/documentation/guides/optimize/). See also [this blog post](https://qdrant.tech/articles/memory-consumption/) that goes into detail.
Different embedding models will need different vector size settings. You can see a list of the models supported by the fastembed server [here](https://qdrant.github.io/fastembed/examples/Supported_Models), including their vector dimensions. These vector dimensions need to be set in the `qdrant_index_configuration`.