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refactor(Schema): simplify vector index SQL template #3959

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7 changes: 1 addition & 6 deletions src/containers/Tenant/utils/schemaQueryTemplates.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -451,12 +451,7 @@ ADD INDEX \${2:my_vector_index}
GLOBAL USING vector_kmeans_tree
ON (\${3:embedding})
WITH (
distance=cosine,
vector_type="uint8",
vector_dimension=\${4:512},
levels=\${5:2},
clusters=\${6:128},
overlap_clusters=\${7:3}
distance=cosine

@chatgpt-codex-connector chatgpt-codex-connector Bot May 29, 2026

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P2 Badge Preserve vector-index settings for older clusters

When the UI is used against clusters that do not yet implement the new server-side autodetection, this template now generates an ALTER TABLE ... vector_kmeans_tree statement with only distance, while the docs URL embedded in the template still documents vector_type, vector_dimension, clusters, and levels in every vector-index example. In that environment, selecting “Add vector index” produces SQL that users must know how to repair manually, so please either keep the editable placeholders or gate the simplified form on a backend capability/version check.

Useful? React with 👍 / 👎.

@astandrik astandrik Jun 8, 2026

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@copilot is it real?

);`;
};

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4 changes: 2 additions & 2 deletions tests/suites/tenant/queryEditor/queryTemplates.test.ts
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Expand Up @@ -231,7 +231,7 @@ test.describe('Query Templates', () => {
expect(editorValue.trim()).toBe(testQuery.trim());
});

test('Add vector index template contains overlap_clusters parameter', async ({page}) => {
test('Add vector index template only contains distance setting', async ({page}) => {
const objectSummary = new ObjectSummary(page);
const queryEditor = new QueryEditor(page);

Expand All @@ -245,7 +245,7 @@ test.describe('Query Templates', () => {
.toContain('vector_kmeans_tree');

const editorContent = await queryEditor.getEditorContent();
expect(editorContent).toContain('overlap_clusters');
expect(editorContent).toContain('distance=cosine');
});

test('Add fulltext index template contains fulltext_relevance and use_filter_snowball', async ({
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