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[Obs AI Assistant] Attempt to fix flaky KB migration test #206324

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Merged
viduni94 merged 3 commits into from
Jan 13, 2025
Merged

[Obs AI Assistant] Attempt to fix flaky KB migration test #206324

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e3c7e43
[Obs AI Assistant] Attempt to fix flaky KB migration test (#202926)
viduni94 Jan 10, 2025
5a735cf
[Obs AI Assistant] Revert changes to the stateful test (#202926)
viduni94 Jan 10, 2025
6a0a28d
[Obs AI Assistant] Fix merge conflict
viduni94 Jan 13, 2025
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55 changes: 29 additions & 26 deletions ..._agnostic/apis/observability/ai_assistant/knowledge_base/knowledge_base_migration.spec.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -24,6 +24,7 @@ export default function ApiTest({ getService }: DeploymentAgnosticFtrProviderCon
const esArchiver = getService('esArchiver');
const es = getService('es');
const ml = getService('ml');
const retry = getService('retry');

const archive =
'x-pack/test/functional/es_archives/observability/ai_assistant/knowledge_base_8_15';
Expand Down Expand Up @@ -91,32 +92,34 @@ export default function ApiTest({ getService }: DeploymentAgnosticFtrProviderCon
});

it('the docs have semantic_text embeddings', async () => {
const hits = await getKnowledgeBaseEntries();
const hasSemanticTextEmbeddings = hits.every((hit) => hit._source?.semantic_text);
expect(hasSemanticTextEmbeddings).to.be(true);

expect(
orderBy(hits, '_source.title').map(({ _source }) => {
const { text, inference } = _source?.semantic_text!;

return {
text,
inferenceId: inference.inference_id,
chunkCount: inference.chunks.length,
};
})
).to.eql([
{
text: 'To infinity and beyond!',
inferenceId: AI_ASSISTANT_KB_INFERENCE_ID,
chunkCount: 1,
},
{
text: "The user's favourite color is blue.",
inferenceId: AI_ASSISTANT_KB_INFERENCE_ID,
chunkCount: 1,
},
]);
await retry.try(async () => {
const hits = await getKnowledgeBaseEntries();
const hasSemanticTextEmbeddings = hits.every((hit) => hit._source?.semantic_text);
expect(hasSemanticTextEmbeddings).to.be(true);

expect(
orderBy(hits, '_source.title').map(({ _source }) => {
const { text, inference } = _source?.semantic_text!;

return {
text,
inferenceId: inference.inference_id,
chunkCount: inference.chunks.length,
};
})
).to.eql([
{
text: 'To infinity and beyond!',
inferenceId: AI_ASSISTANT_KB_INFERENCE_ID,
chunkCount: 1,
},
{
text: "The user's favourite color is blue.",
inferenceId: AI_ASSISTANT_KB_INFERENCE_ID,
chunkCount: 1,
},
]);
});
});

it('returns entries correctly via API', async () => {
Expand Down