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chore: enable librarian generation for google-cloud-vectorsearch #16741

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Merged
jskeet merged 1 commit into from
Apr 21, 2026
+15 −16
Merged

chore: enable librarian generation for google-cloud-vectorsearch #16741

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1 change: 0 additions & 1 deletion librarian.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -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
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30 changes: 15 additions & 15 deletions packages/google-cloud-vectorsearch/.repo-metadata.json
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Original file line number Diff line number Diff line change
@@ -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"
}
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@gemini-code-assist gemini-code-assist Bot Apr 21, 2026

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medium

The indentation in this file has been changed from 2 spaces to 4 spaces, and the trailing newline has been removed. To maintain consistency with other packages in this repository and adhere to POSIX standards, please revert to 2-space indentation and ensure the file ends with a newline.

Suggested change
{
"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"
}
{
"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"
}

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