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Update default queries; update quick config fields; misc updates #660

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merged 3 commits into from
Mar 5, 2025
Merged

Update default queries; update quick config fields; misc updates #660

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fbe4b71
Change default to match query
ohltyler Mar 4, 2025
2dcd532
Only show embedding field in quick config if unknown
ohltyler Mar 4, 2025
0f83df9
add gear in header for newhomepage
ohltyler Mar 4, 2025
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9 changes: 8 additions & 1 deletion public/pages/workflow_detail/components/header.tsx
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Original file line number Diff line number Diff line change
Expand Up @@ -297,7 +297,7 @@ export function WorkflowDetailHeader(props: WorkflowDetailHeaderProps) {
} as TopNavMenuIconData,
{
iconType: 'exit',
tooltip: 'Return to projects',
tooltip: 'Return to workflows',
ariaLabel: 'Exit',
href: constructHrefWithDataSourceId(
APP_PATH.WORKFLOWS,
Expand All @@ -312,6 +312,13 @@ export function WorkflowDetailHeader(props: WorkflowDetailHeaderProps) {
run: () => setIntroFlyoutOpened(true),
controlType: 'icon',
} as TopNavMenuIconData,
{
iconType: 'gear',
tooltip: 'Edit workflow settings',
ariaLabel: 'Edit workflow settings',
run: () => setIsEditWorkflowModalOpen(true),
controlType: 'icon',
} as TopNavMenuIconData,
]}
screenTitle={workflowName}
showDataSourceMenu={dataSourceEnabled}
Expand Down
6 changes: 2 additions & 4 deletions public/pages/workflows/new_workflow/quick_configure_modal.tsx
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Original file line number Diff line number Diff line change
Expand Up @@ -223,13 +223,11 @@ export function QuickConfigureModal(props: QuickConfigureModalProps) {
const connector = connectors[selectedModel.connectorId];
if (connector !== undefined) {
const dimensions = getEmbeddingModelDimensions(connector);
if (dimensions === undefined) {
setUnknownEmbeddingLength(true);
}
// dimensions may be undefined. set state vars accordingly
setUnknownEmbeddingLength(dimensions === undefined);
setQuickConfigureFields({
...quickConfigureFields,
embeddingLength: getEmbeddingModelDimensions(connector),
embeddingLength: dimensions,
});
}
}
Expand Down
60 changes: 41 additions & 19 deletions public/pages/workflows/new_workflow/quick_configure_optional_fields.tsx
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Original file line number Diff line number Diff line change
Expand Up @@ -28,7 +28,7 @@ import {
WORKFLOW_TYPE,
} from '../../../../common';
import { AppState } from '../../../store';
import { parseModelInputs } from '../../../utils';
import { getEmbeddingModelDimensions, parseModelInputs } from '../../../utils';

interface QuickConfigureOptionalFieldsProps {
workflowType?: WORKFLOW_TYPE;
Expand Down Expand Up @@ -127,6 +127,24 @@ export function QuickConfigureOptionalFields(
props.setFields({ ...props.fields, ...optionalFieldValues });
}, [optionalFieldValues]);

// Keep track of if an embedding model is selected with an unknown embedding length.
// Only expose the form field if it is unknown, else hide from the user.
const [unknownEmbeddingLength, setUnknownEmbeddingLength] = useState<boolean>(
false
);
useEffect(() => {
const selectedModel = deployedModels.find(
(model) => model.id === props.fields?.embeddingModelId
);
if (selectedModel?.connectorId !== undefined) {
const connector = connectors[selectedModel.connectorId];
if (connector !== undefined) {
const dimensions = getEmbeddingModelDimensions(connector);
setUnknownEmbeddingLength(dimensions === undefined);
}
}
}, [props.fields?.embeddingModelId, deployedModels, connectors]);

return (
<EuiAccordion
id="optionalConfiguration"
Expand Down Expand Up @@ -202,24 +220,28 @@ export function QuickConfigureOptionalFields(
}}
/>
</EuiCompressedFormRow>
<EuiSpacer size="s" />
<EuiCompressedFormRow
fullWidth={true}
label={'Embedding length'}
isInvalid={false}
helpText="The length / dimension of the generated vector embeddings. Autofilled values may be inaccurate."
>
<EuiCompressedFieldNumber
fullWidth={true}
value={props.fields?.embeddingLength || ''}
onChange={(e) => {
setOptionalFieldValues({
...optionalFieldValues,
embeddingLength: Number(e.target.value),
});
}}
/>
</EuiCompressedFormRow>
{unknownEmbeddingLength && (
<>
<EuiSpacer size="s" />
<EuiCompressedFormRow
fullWidth={true}
label={'Embedding length'}
isInvalid={false}
helpText="The length / dimension of the generated vector embeddings."
>
<EuiCompressedFieldNumber
fullWidth={true}
value={props.fields?.embeddingLength || ''}
onChange={(e) => {
setOptionalFieldValues({
...optionalFieldValues,
embeddingLength: Number(e.target.value),
});
}}
/>
</EuiCompressedFormRow>
</>
)}
</>
)}
{(props.workflowType === WORKFLOW_TYPE.RAG ||
Expand Down
10 changes: 5 additions & 5 deletions public/pages/workflows/new_workflow/utils.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -28,7 +28,7 @@ import {
SEMANTIC_SEARCH_QUERY_NEURAL,
MULTIMODAL_SEARCH_QUERY_NEURAL,
HYBRID_SEARCH_QUERY_MATCH_NEURAL,
TERM_QUERY_TEXT,
MATCH_QUERY_TEXT,
} from '../../../../common';
import { generateId } from '../../../utils';
import semver from 'semver';
Expand Down Expand Up @@ -164,7 +164,7 @@ export function fetchSemanticSearchMetadata(version: string): UIState {
});

baseState.config.search.request.value = customStringify(
isPreV219 ? SEMANTIC_SEARCH_QUERY_NEURAL : TERM_QUERY_TEXT
isPreV219 ? SEMANTIC_SEARCH_QUERY_NEURAL : MATCH_QUERY_TEXT
);

baseState.config.search.enrichRequest.processors = isPreV219
Expand Down Expand Up @@ -224,7 +224,7 @@ export function fetchHybridSearchMetadata(version: string): UIState {
});

baseState.config.search.request.value = customStringify(
isPreV219 ? HYBRID_SEARCH_QUERY_MATCH_NEURAL : TERM_QUERY_TEXT
isPreV219 ? HYBRID_SEARCH_QUERY_MATCH_NEURAL : MATCH_QUERY_TEXT
);

baseState.config.search.enrichResponse.processors = [
Expand Down Expand Up @@ -263,9 +263,9 @@ export function fetchVectorSearchWithRAGMetadata(version: string): UIState {
baseState.config.ingest.index.settings.value = customStringify({
[`index.knn`]: true,
});
// Search config: term query => ML inference processor for generating embeddings =>
// Search config: match query => ML inference processor for generating embeddings =>
// ML inference processor for returning LLM-generated response of results
baseState.config.search.request.value = customStringify(TERM_QUERY_TEXT);
baseState.config.search.request.value = customStringify(MATCH_QUERY_TEXT);
baseState.config.search.enrichRequest.processors = [
injectQueryTemplateInProcessor(
new MLSearchRequestProcessor().toObj(),
Expand Down
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