From e8a7a054ddc3e447fb2f2b7297441e49d0a85b1d Mon Sep 17 00:00:00 2001
From: Jon Skeet <jonskeet@google.com>
Date: Tue, 21 Apr 2026 07:06:31 +0000
Subject: [PATCH] chore: enable librarian generation for
 google-cloud-vectorsearch

---
 librarian.yaml                                |  1 -
 .../.repo-metadata.json                       | 30 +++++++++----------
 2 files changed, 15 insertions(+), 16 deletions(-)

diff --git a/librarian.yaml b/librarian.yaml
index 9bbc855bf06c..f50f11983883 100644
--- a/librarian.yaml
+++ b/librarian.yaml
@@ -3777,7 +3777,6 @@ libraries:
     keep:
       - CHANGELOG.md
       - docs/CHANGELOG.md
-    skip_generate: true
     python:
       name_pretty_override: Vector Search API
       product_documentation_override: https://docs.cloud.google.com/vertex-ai/docs/vector-search-2/overview
diff --git a/packages/google-cloud-vectorsearch/.repo-metadata.json b/packages/google-cloud-vectorsearch/.repo-metadata.json
index 8482c4805565..131ffd9899ea 100644
--- a/packages/google-cloud-vectorsearch/.repo-metadata.json
+++ b/packages/google-cloud-vectorsearch/.repo-metadata.json
@@ -1,16 +1,16 @@
 {
-  "api_description": "The Vector Search API provides a fully-managed, highly performant, and\nscalable vector database designed to power next-generation search,\nrecommendation, and generative AI applications. It allows you to store,\nindex, and query your data and its corresponding vector embeddings through\na simple, intuitive interface. With Vector Search, you can define custom\nschemas for your data, insert objects with associated metadata,\nautomatically generate embeddings from your data, and perform fast\napproximate nearest neighbor (ANN) searches to find semantically similar\nitems at scale.",
-  "api_id": "vectorsearch.googleapis.com",
-  "api_shortname": "vectorsearch",
-  "client_documentation": "https://cloud.google.com/python/docs/reference/google-cloud-vectorsearch/latest",
-  "default_version": "v1",
-  "distribution_name": "google-cloud-vectorsearch",
-  "issue_tracker": "https://issuetracker.google.com/issues/new?component=1899904",
-  "language": "python",
-  "library_type": "GAPIC_AUTO",
-  "name": "google-cloud-vectorsearch",
-  "name_pretty": "Vector Search API",
-  "product_documentation": "https://docs.cloud.google.com/vertex-ai/docs/vector-search-2/overview",
-  "release_level": "preview",
-  "repo": "googleapis/google-cloud-python"
-}
+    "api_description": "The Vector Search API provides a fully-managed, highly performant, and\nscalable vector database designed to power next-generation search,\nrecommendation, and generative AI applications. It allows you to store,\nindex, and query your data and its corresponding vector embeddings through\na simple, intuitive interface. With Vector Search, you can define custom\nschemas for your data, insert objects with associated metadata,\nautomatically generate embeddings from your data, and perform fast\napproximate nearest neighbor (ANN) searches to find semantically similar\nitems at scale.",
+    "api_id": "vectorsearch.googleapis.com",
+    "api_shortname": "vectorsearch",
+    "client_documentation": "https://cloud.google.com/python/docs/reference/google-cloud-vectorsearch/latest",
+    "default_version": "v1",
+    "distribution_name": "google-cloud-vectorsearch",
+    "issue_tracker": "https://issuetracker.google.com/issues/new?component=1899904",
+    "language": "python",
+    "library_type": "GAPIC_AUTO",
+    "name": "google-cloud-vectorsearch",
+    "name_pretty": "Vector Search API",
+    "product_documentation": "https://docs.cloud.google.com/vertex-ai/docs/vector-search-2/overview",
+    "release_level": "preview",
+    "repo": "googleapis/google-cloud-python"
+}
\ No newline at end of file