forked from getsentry/sentry
-
Notifications
You must be signed in to change notification settings - Fork 0
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
feat(ai): Add preliminary AI analytics page content (getsentry#69010)
<img width="908" alt="Screenshot 2024-04-16 at 2 36 14 PM" src="https://github.com/getsentry/sentry/assets/161344340/5c1c9d45-774d-42bf-9f15-9de1d5f4b8e7">
- Loading branch information
1 parent
92e8a0c
commit 144ff52
Showing
7 changed files
with
423 additions
and
230 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,181 @@ | ||
import {browserHistory} from 'react-router'; | ||
import type {Location} from 'history'; | ||
|
||
import type {GridColumnHeader} from 'sentry/components/gridEditable'; | ||
import GridEditable, {COL_WIDTH_UNDEFINED} from 'sentry/components/gridEditable'; | ||
import Link from 'sentry/components/links/link'; | ||
import type {CursorHandler} from 'sentry/components/pagination'; | ||
import Pagination from 'sentry/components/pagination'; | ||
import {t} from 'sentry/locale'; | ||
import type {Organization} from 'sentry/types'; | ||
import type {EventsMetaType} from 'sentry/utils/discover/eventView'; | ||
import {getFieldRenderer} from 'sentry/utils/discover/fieldRenderers'; | ||
import type {Sort} from 'sentry/utils/discover/fields'; | ||
import {RATE_UNIT_TITLE, RateUnit} from 'sentry/utils/discover/fields'; | ||
import {VisuallyCompleteWithData} from 'sentry/utils/performanceForSentry'; | ||
import {decodeScalar, decodeSorts} from 'sentry/utils/queryString'; | ||
import {MutableSearch} from 'sentry/utils/tokenizeSearch'; | ||
import {useLocation} from 'sentry/utils/useLocation'; | ||
import useOrganization from 'sentry/utils/useOrganization'; | ||
import {normalizeUrl} from 'sentry/utils/withDomainRequired'; | ||
import {renderHeadCell} from 'sentry/views/starfish/components/tableCells/renderHeadCell'; | ||
import {useSpanMetrics} from 'sentry/views/starfish/queries/useSpanMetrics'; | ||
import type {MetricsResponse} from 'sentry/views/starfish/types'; | ||
import {QueryParameterNames} from 'sentry/views/starfish/views/queryParameters'; | ||
import {DataTitles} from 'sentry/views/starfish/views/spans/types'; | ||
|
||
type Row = Pick< | ||
MetricsResponse, | ||
| 'project.id' | ||
| 'span.description' | ||
| 'span.group' | ||
| 'spm()' | ||
| 'avg(span.self_time)' | ||
| 'sum(span.self_time)' | ||
| 'time_spent_percentage()' | ||
>; | ||
|
||
type Column = GridColumnHeader< | ||
'span.description' | 'spm()' | 'avg(span.self_time)' | 'time_spent_percentage()' | ||
>; | ||
|
||
const COLUMN_ORDER: Column[] = [ | ||
{ | ||
key: 'span.description', | ||
name: t('AI Pipeline name'), | ||
width: COL_WIDTH_UNDEFINED, | ||
}, | ||
{ | ||
key: 'spm()', | ||
name: `${t('Times')} ${RATE_UNIT_TITLE[RateUnit.PER_MINUTE]}`, | ||
width: COL_WIDTH_UNDEFINED, | ||
}, | ||
{ | ||
key: `avg(span.self_time)`, | ||
name: DataTitles.avg, | ||
width: COL_WIDTH_UNDEFINED, | ||
}, | ||
{ | ||
key: 'time_spent_percentage()', | ||
name: DataTitles.timeSpent, | ||
width: COL_WIDTH_UNDEFINED, | ||
}, | ||
]; | ||
|
||
const SORTABLE_FIELDS = ['avg(span.self_time)', 'spm()', 'time_spent_percentage()']; | ||
|
||
type ValidSort = Sort & { | ||
field: 'spm()' | 'avg(span.self_time)' | 'time_spent_percentage()'; | ||
}; | ||
|
||
export function isAValidSort(sort: Sort): sort is ValidSort { | ||
return (SORTABLE_FIELDS as unknown as string[]).includes(sort.field); | ||
} | ||
|
||
export function PipelinesTable() { | ||
const location = useLocation(); | ||
const organization = useOrganization(); | ||
const cursor = decodeScalar(location.query?.[QueryParameterNames.SPANS_CURSOR]); | ||
const sortField = decodeScalar(location.query?.[QueryParameterNames.SPANS_SORT]); | ||
|
||
let sort = decodeSorts(sortField).filter(isAValidSort)[0]; | ||
if (!sort) { | ||
sort = {field: 'time_spent_percentage()', kind: 'desc'}; | ||
} | ||
const {data, isLoading, meta, pageLinks, error} = useSpanMetrics({ | ||
search: new MutableSearch('span.op:ai.pipeline.langchain'), | ||
fields: [ | ||
'project.id', | ||
'span.group', | ||
'span.description', | ||
'spm()', | ||
'avg(span.self_time)', | ||
'sum(span.self_time)', | ||
'time_spent_percentage()', | ||
], | ||
sorts: [sort], | ||
limit: 25, | ||
cursor, | ||
}); | ||
|
||
const handleCursor: CursorHandler = (newCursor, pathname, query) => { | ||
browserHistory.push({ | ||
pathname, | ||
query: {...query, [QueryParameterNames.SPANS_CURSOR]: newCursor}, | ||
}); | ||
}; | ||
|
||
return ( | ||
<VisuallyCompleteWithData | ||
id="PipelinesTable" | ||
hasData={data.length > 0} | ||
isLoading={isLoading} | ||
> | ||
<GridEditable | ||
isLoading={isLoading} | ||
error={error} | ||
data={data} | ||
columnOrder={COLUMN_ORDER} | ||
columnSortBy={[ | ||
{ | ||
key: sort.field, | ||
order: sort.kind, | ||
}, | ||
]} | ||
grid={{ | ||
renderHeadCell: column => | ||
renderHeadCell({ | ||
column, | ||
sort, | ||
location, | ||
sortParameterName: QueryParameterNames.SPANS_SORT, | ||
}), | ||
renderBodyCell: (column, row) => | ||
renderBodyCell(column, row, meta, location, organization), | ||
}} | ||
location={location} | ||
/> | ||
<Pagination pageLinks={pageLinks} onCursor={handleCursor} /> | ||
</VisuallyCompleteWithData> | ||
); | ||
} | ||
|
||
function renderBodyCell( | ||
column: Column, | ||
row: Row, | ||
meta: EventsMetaType | undefined, | ||
location: Location, | ||
organization: Organization | ||
) { | ||
if (column.key === 'span.description') { | ||
if (!row['span.description']) { | ||
return <span>(unknown)</span>; | ||
} | ||
if (!row['span.group']) { | ||
return <span>{row['span.description']}</span>; | ||
} | ||
return ( | ||
<Link | ||
to={normalizeUrl( | ||
`/organizations/${organization.slug}/ai-analytics/pipelines/${row['span.group']}` | ||
)} | ||
> | ||
{row['span.description']} | ||
</Link> | ||
); | ||
} | ||
|
||
if (!meta || !meta?.fields) { | ||
return row[column.key]; | ||
} | ||
|
||
const renderer = getFieldRenderer(column.key, meta.fields, false); | ||
|
||
const rendered = renderer(row, { | ||
location, | ||
organization, | ||
unit: meta.units?.[column.key], | ||
}); | ||
|
||
return rendered; | ||
} |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,168 @@ | ||
import styled from '@emotion/styled'; | ||
|
||
import {t} from 'sentry/locale'; | ||
import {space} from 'sentry/styles/space'; | ||
import {MetricDisplayType} from 'sentry/utils/metrics/types'; | ||
import {useMetricsQuery} from 'sentry/utils/metrics/useMetricsQuery'; | ||
import usePageFilters from 'sentry/utils/usePageFilters'; | ||
import {MetricChartContainer} from 'sentry/views/dashboards/metrics/chart'; | ||
|
||
export function TotalTokensUsedChart() { | ||
const {selection, isReady: isGlobalSelectionReady} = usePageFilters(); | ||
const { | ||
data: timeseriesData, | ||
isLoading, | ||
isError, | ||
error, | ||
} = useMetricsQuery( | ||
[ | ||
{ | ||
name: 'total', | ||
mri: `c:spans/ai.total_tokens.used@none`, | ||
op: 'sum', | ||
}, | ||
], | ||
selection, | ||
{ | ||
intervalLadder: 'dashboard', | ||
} | ||
); | ||
|
||
if (!isGlobalSelectionReady) { | ||
return null; | ||
} | ||
|
||
if (isError) { | ||
return <div>{'' + error}</div>; | ||
} | ||
|
||
return ( | ||
<TokenChartContainer> | ||
<PanelTitle>{t('Total tokens used')}</PanelTitle> | ||
<MetricChartContainer | ||
timeseriesData={timeseriesData} | ||
isLoading={isLoading} | ||
metricQueries={[ | ||
{ | ||
name: 'mql', | ||
formula: '$total', | ||
}, | ||
]} | ||
displayType={MetricDisplayType.AREA} | ||
chartHeight={200} | ||
/> | ||
</TokenChartContainer> | ||
); | ||
} | ||
|
||
export function NumberOfPipelinesChart() { | ||
const {selection, isReady: isGlobalSelectionReady} = usePageFilters(); | ||
const { | ||
data: timeseriesData, | ||
isLoading, | ||
isError, | ||
error, | ||
} = useMetricsQuery( | ||
[ | ||
{ | ||
name: 'number', | ||
mri: `d:spans/exclusive_time@millisecond`, | ||
op: 'count', | ||
query: 'span.op:"ai.pipeline.langchain"', // TODO: for now this is the only AI "pipeline" supported | ||
}, | ||
], | ||
selection, | ||
{ | ||
intervalLadder: 'dashboard', | ||
} | ||
); | ||
|
||
if (!isGlobalSelectionReady) { | ||
return null; | ||
} | ||
|
||
if (isError) { | ||
return <div>{'' + error}</div>; | ||
} | ||
|
||
return ( | ||
<TokenChartContainer> | ||
<PanelTitle>{t('Number of AI pipelines')}</PanelTitle> | ||
<MetricChartContainer | ||
timeseriesData={timeseriesData} | ||
isLoading={isLoading} | ||
metricQueries={[ | ||
{ | ||
name: 'mql', | ||
formula: '$number', | ||
}, | ||
]} | ||
displayType={MetricDisplayType.AREA} | ||
chartHeight={200} | ||
/> | ||
</TokenChartContainer> | ||
); | ||
} | ||
|
||
export function PipelineDurationChart() { | ||
const {selection, isReady: isGlobalSelectionReady} = usePageFilters(); | ||
const { | ||
data: timeseriesData, | ||
isLoading, | ||
isError, | ||
error, | ||
} = useMetricsQuery( | ||
[ | ||
{ | ||
name: 'number', | ||
mri: `d:spans/exclusive_time@millisecond`, | ||
op: 'avg', | ||
query: 'span.op:"ai.pipeline.langchain"', // TODO: for now this is the only AI "pipeline" supported | ||
}, | ||
], | ||
selection, | ||
{ | ||
intervalLadder: 'dashboard', | ||
} | ||
); | ||
|
||
if (!isGlobalSelectionReady) { | ||
return null; | ||
} | ||
|
||
if (isError) { | ||
return <div>{'' + error}</div>; | ||
} | ||
|
||
return ( | ||
<TokenChartContainer> | ||
<PanelTitle>{t('AI pipeline duration')}</PanelTitle> | ||
<MetricChartContainer | ||
timeseriesData={timeseriesData} | ||
isLoading={isLoading} | ||
metricQueries={[ | ||
{ | ||
name: 'mql', | ||
formula: '$number', | ||
}, | ||
]} | ||
displayType={MetricDisplayType.AREA} | ||
chartHeight={200} | ||
/> | ||
</TokenChartContainer> | ||
); | ||
} | ||
|
||
const PanelTitle = styled('h5')` | ||
padding: ${space(3)} ${space(3)} 0; | ||
margin: 0; | ||
`; | ||
|
||
const TokenChartContainer = styled('div')` | ||
overflow: hidden; | ||
border: 1px solid ${p => p.theme.border}; | ||
border-radius: ${p => p.theme.borderRadius}; | ||
height: 100%; | ||
display: flex; | ||
flex-direction: column; | ||
`; |
Oops, something went wrong.