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Update pgembedding.ipynb (#7682)

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Correct links to the pg_embedding repository and the Neon documentation.
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Daniel 2023-07-13 20:54:07 -03:00 committed by GitHub
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docs/extras/modules/data_connection/vectorstores/integrations/pgembedding.ipynb
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@ -8,7 +8,7 @@
"source": [ "source": [
"# pg_hnsw\n", "# pg_hnsw\n",
"\n", "\n",
"> [pg_embedding](https://github.com/knizhnik/hnsw) is an open-source vector similarity search for `Postgres` that uses Hierarchical Navigable Small Worlds for approximate nearest neighbor search.\n", "> [pg_embedding](https://github.com/neondatabase/pg_embedding) is an open-source vector similarity search for `Postgres` that uses Hierarchical Navigable Small Worlds for approximate nearest neighbor search.\n",
"\n", "\n",
"It supports:\n", "It supports:\n",
"- exact and approximate nearest neighbor search using HNSW\n", "- exact and approximate nearest neighbor search using HNSW\n",
@ -232,7 +232,7 @@
"\n", "\n",
"- efConstruction: Defines the number of nearest neighbors considered during index construction. The default value is 32.\n", "- efConstruction: Defines the number of nearest neighbors considered during index construction. The default value is 32.\n",
"- efsearch: Defines the number of nearest neighbors considered during index search. The default value is 32.\n", "- efsearch: Defines the number of nearest neighbors considered during index search. The default value is 32.\n",
"For information about how you can configure these options to influence the HNSW algorithm, refer to [Tuning the HNSW algorithm](https://neon-next-git-dprice-hnsw-extension-neondatabase.vercel.app/docs/extensions/hnsw#tuning-the-hnsw-algorithm)." "For information about how you can configure these options to influence the HNSW algorithm, refer to [Tuning the HNSW algorithm](https://neon.tech/docs/extensions/pg_embedding#tuning-the-hnsw-algorithm)."
] ]
}, },
{ {