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import { useMemo, useState } from "react";
import { toast } from "sonner";
import { Button } from "@/ahuora-design-system/ui/button";
import { ScrollArea } from "@/ahuora-design-system/ui/scroll-area";
import {
Select,
SelectContent,
SelectGroup,
SelectItem,
SelectSeparator,
SelectTrigger,
SelectValue,
} from "@/ahuora-design-system/ui/select";
import { Separator } from "@/ahuora-design-system/ui/separator";
import { Spinner } from "@/ahuora-design-system/ui/spinner";
import {
ToggleGroup,
ToggleGroupItem,
} from "@/ahuora-design-system/ui/toggle-group";
import {
type ColumnMapping as ApiColumnMapping,
BulkCreateColumnMapping,
MlColumnMappingsRead,
MlModelRead,
PropertyTypeEnum,
useCoreMlCreateSurrogateModelCreateMutation,
useCoreMlcolumnmappingBulkCreateColumnMappingCreateMutation,
useCoreMlcolumnmappingReplaceColumnMappingCreateMutation,
useCoreMlGetCsvHeaderRetrieveQuery,
} from "@/api/apiStore.gen";
import objs from "@/data/unitOpConfigs";
import { useMLTrainRefresh } from "@/hooks/cache/useMLTrainRefresh";
import { useAvailableStreamConnections } from "@/hooks/connections";
import { useFlowsheetAccess } from "@/hooks/flowsheetAccess";
import { useFlowsheetPorts } from "@/hooks/flowsheetObjects";
import type { CsvHeaderPreviewState } from "./UploadCSV";
type ColumnMapping = {
[key: string]: {
type: PropertyTypeEnum | undefined;
portIndex: number | undefined;
propertyKey: string | undefined;
};
};
interface ColumnMappingsProps {
model: MlModelRead;
simulationObject: number;
csvFileName?: string;
csvHeaderPreview?: CsvHeaderPreviewState | null;
columnMappings: MlColumnMappingsRead[];
onResetModelComplete: () => void;
}
export default function ColumnMappings(props: ColumnMappingsProps) {
const access = useFlowsheetAccess();
const canMutate = access?.can_edit ?? true;
const { data: csv_header, isLoading } = useCoreMlGetCsvHeaderRetrieveQuery({
model: props.model.id,
});
const { refreshMLTrainDependencies } = useMLTrainRefresh();
const [bulkCreateMappings] =
useCoreMlcolumnmappingBulkCreateColumnMappingCreateMutation();
const [replaceMappings] =
useCoreMlcolumnmappingReplaceColumnMappingCreateMutation();
const { availableInletStreams, availableOutletStreams } =
useAvailableStreamConnections();
const ports = useFlowsheetPorts();
const [trainModel] = useCoreMlCreateSurrogateModelCreateMutation();
const inletPorts = ports?.filter(
(port) =>
port.unitOp === props.simulationObject && port.direction === "inlet",
);
const inletStreams = availableOutletStreams.filter((stream) =>
inletPorts?.find((port) => port.stream === stream.id),
);
const outletPorts = ports?.filter(
(port) =>
port.unitOp === props.simulationObject && port.direction === "outlet",
);
const outletStreams = availableInletStreams.filter((stream) =>
outletPorts?.find((port) => port.stream === stream.id),
);
const [values, setValues] = useState<ColumnMapping>();
const resolvedHeaders = useMemo(
() => csv_header?.headers ?? props.csvHeaderPreview?.headers ?? [],
[csv_header?.headers, props.csvHeaderPreview?.headers],
);
const isUsingPreviewHeaders =
!csv_header?.headers?.length && resolvedHeaders.length > 0;
// Existings mappings for the current model retrieved from the backend
const existingMappings = useMemo(
() =>
props.columnMappings.filter(
(mapping) => mapping.model === props.model.id,
),
[props.columnMappings, props.model.id],
);
// Initial values for the column mappings based on existing mappings and resolved headers to pre-fill form
const initialValues = useMemo<ColumnMapping>(() => {
return resolvedHeaders.reduce<ColumnMapping>((acc, column, columnIndex) => {
const mapping = existingMappings.find((item) => item.column === column);
if (!mapping) {
return acc;
}
acc[columnIndex] = {
type: mapping.propertyType,
portIndex: mapping.portIndex,
propertyKey: mapping.propertyKey,
};
return acc;
}, {});
}, [existingMappings, resolvedHeaders]);
const currentValues = { ...initialValues, ...values };
const isUpdateMode = existingMappings.length > 0;
const properties = Object.entries(objs.stream.properties);
function handleValueChange(param: string) {
const { columnIndex, key, value } = JSON.parse(param);
setValues((previousValues) => {
const mergedValues = { ...initialValues, ...previousValues };
return {
...mergedValues,
[columnIndex]: {
...mergedValues[columnIndex],
[key]: value,
},
};
});
}
function handleTypeChange(columnIndex: number, nextValue: string) {
setValues((previousValues) => {
const mergedValues = { ...initialValues, ...previousValues };
const currentEntry = mergedValues[columnIndex];
if (nextValue === "") {
return {
...mergedValues,
[columnIndex]: {
...currentEntry,
type: undefined,
portIndex: undefined,
propertyKey: undefined,
},
};
} else {
const { columnIndex, key, value } = JSON.parse(nextValue);
return {
...mergedValues,
[columnIndex]: {
...currentEntry,
[key]: value,
},
};
}
});
}
function getTaskErrorMessage(error: unknown) {
if (typeof error === "string" && error.length > 0) {
return error;
}
if (
error &&
typeof error === "object" &&
"message" in error &&
typeof error.message === "string" &&
error.message.length > 0
) {
return error.message;
}
return "Machine learning training did not start successfully.";
}
async function handleSave() {
if (!canMutate) {
return;
}
if (!csv_header?.headers?.length) {
toast.error("CSV headers are still loading", {
description:
"Wait for the backend-confirmed headers before saving column mappings.",
});
return;
}
const length = csv_header.headers.length;
const valueEntries = Object.entries(currentValues);
console.log("valueEntries", valueEntries);
if (valueEntries.length !== length) {
toast.error("Please complete mappings", {
description: "Some column mapping is missing",
});
return;
}
const inletValues = valueEntries
.filter(([, value]) => value.type === PropertyTypeEnum.InletProperty)
.sort((a, b) => +a[0] - +b[0])
.map(([key, value]) => ({
propertyKey:
value.portIndex === -1
? csv_header?.headers[+key]
: value.propertyKey,
portIndex: value.portIndex,
column: csv_header?.headers[+key],
})) as ApiColumnMapping[];
const outletValues = valueEntries
.filter(([, value]) => value.type === PropertyTypeEnum.OutletProperty)
.sort((a, b) => +a[0] - +b[0])
.map(([key, value]) => ({
propertyKey:
value.portIndex === -1
? csv_header?.headers[+key]
: value.propertyKey,
portIndex: value.portIndex,
column: csv_header?.headers[+key],
})) as ApiColumnMapping[];
try {
const mappingPayload: BulkCreateColumnMapping = {
model: props.model.id,
inlet_mappings: inletValues,
outlet_mappings: outletValues,
};
const res = isUpdateMode
? await replaceMappings({
bulkCreateColumnMapping: mappingPayload,
})
: await bulkCreateMappings({
bulkCreateColumnMapping: mappingPayload,
});
if (res.error) {
toast.error("Error", {
description: "Failed to save column mappings",
});
return;
}
const trainResult = await trainModel({
createSurrogateModelFromColumn: {
model: props.model.id,
},
});
if ("error" in trainResult && trainResult.error) {
refreshMLTrainDependencies();
toast.error("Training failed", {
description: "Machine learning training could not be started.",
});
return;
}
const trainingTask =
"data" in trainResult &&
trainResult.data &&
typeof trainResult.data === "object"
? (trainResult.data as { status?: string; error?: unknown })
: null;
if (trainingTask?.status === "failed") {
refreshMLTrainDependencies();
toast.error("Training failed", {
description: getTaskErrorMessage(trainingTask.error),
});
} else {
refreshMLTrainDependencies();
props.onResetModelComplete();
}
} catch (err) {
toast.error("Error", {
description: "Something went wrong during the process",
});
}
}
return (
<ScrollArea className="min-h-0 flex-1">
<div className="flex flex-col gap-4 pb-4">
<div className="flex flex-col gap-1">
<h1>Column mapping</h1>
<p className="text-sm font-light">
Map columns to according properties
</p>
{props.csvFileName && (
<p className="text-sm text-muted-foreground">
Uploaded file: {props.csvFileName}
</p>
)}
{props.csvHeaderPreview?.delimiter && (
<p className="text-xs text-muted-foreground">
Detected delimiter: {props.csvHeaderPreview.delimiter}
</p>
)}
{props.csvHeaderPreview?.warnings?.map((warning) => (
<p key={warning} className="text-xs text-muted-foreground">
{warning}
</p>
))}
{isUsingPreviewHeaders && (
<p className="text-xs text-muted-foreground">
Showing the local header preview while the backend-confirmed
headers load.
</p>
)}
</div>
<Separator />
<div className="flex flex-col gap-3">
<div className="w-max flex flex-col gap-3">
{!isLoading || resolvedHeaders.length > 0 ? (
resolvedHeaders.map((column, column_index) => (
<div
key={`${column}_input`}
className="flex w-full items-center gap-7"
>
<p className="w-[150px]">{column}</p>
<ToggleGroup
type="single"
value={
currentValues?.[column_index]?.type
? JSON.stringify({
columnIndex: column_index,
key: "type",
value: currentValues[column_index].type,
})
: ""
}
className="p-1 bg-muted w-max rounded-lg overflow-hidden"
onValueChange={(nextValue) =>
handleTypeChange(column_index, nextValue)
}
disabled={!canMutate}
>
<ToggleGroupItem
value={JSON.stringify({
columnIndex: column_index,
key: "type",
value: PropertyTypeEnum.InletProperty,
})}
aria-label={`input-${column}`}
>
Input
</ToggleGroupItem>
<ToggleGroupItem
value={JSON.stringify({
columnIndex: column_index,
key: "type",
value: PropertyTypeEnum.OutletProperty,
})}
aria-label={`output-${column}`}
>
Output
</ToggleGroupItem>
</ToggleGroup>
<Select
onValueChange={handleValueChange}
value={
currentValues?.[column_index]?.portIndex !== undefined
? JSON.stringify({
columnIndex: column_index,
key: "portIndex",
value: currentValues[column_index].portIndex,
})
: undefined
}
required
disabled={!canMutate}
>
<SelectTrigger
className="w-[180px] "
aria-label={`select-source-${column}`}
>
<SelectValue placeholder="Select source" />
</SelectTrigger>
<SelectContent>
<SelectGroup>
<SelectItem
value={JSON.stringify({
columnIndex: column_index,
key: "portIndex",
value: -1,
})}
ariaLabel={`custom-property-${column}`}
disabled={!canMutate}
>
Make custom property
</SelectItem>
<SelectSeparator />
{currentValues?.[column_index]?.type ===
PropertyTypeEnum.InletProperty
? inletStreams.map((item) => {
const portIndex = inletPorts?.find(
(port) => port.stream === item.id,
)?.index;
return (
<SelectItem
key={item.id}
value={JSON.stringify({
columnIndex: column_index,
key: "portIndex",
value: portIndex,
})}
ariaLabel={`${item.componentName}-${column}`}
>
{item.componentName}
</SelectItem>
);
})
: outletStreams.map((item) => {
const portIndex = outletPorts?.find(
(port) => port.stream === item.id,
)?.index;
return (
<SelectItem
key={item.id}
value={JSON.stringify({
columnIndex: column_index,
key: "portIndex",
value: portIndex,
})}
ariaLabel={`${item.componentName}-${column}`}
>
{item.componentName}
</SelectItem>
);
})}
</SelectGroup>
</SelectContent>
</Select>
{currentValues?.[column_index]?.portIndex !== -1 && (
<Select
onValueChange={handleValueChange}
value={
currentValues?.[column_index]?.propertyKey
? JSON.stringify({
columnIndex: column_index,
key: "propertyKey",
value: currentValues[column_index].propertyKey,
})
: undefined
}
required
disabled={!canMutate}
>
<SelectTrigger
className="w-[150px]"
aria-label={`select-property-${column}`}
>
<SelectValue placeholder="Select property" />
</SelectTrigger>
<SelectContent>
<SelectGroup>
{properties.map(([key, value], index) => (
<SelectItem
key={key + index}
value={JSON.stringify({
columnIndex: column_index,
key: "propertyKey",
value: key,
})}
ariaLabel={`${value.displayName}-${column}`}
>
{value.displayName}
</SelectItem>
))}
</SelectGroup>
</SelectContent>
</Select>
)}
</div>
))
) : (
<Spinner className="icon-large mt-5" />
)}
</div>
</div>
<div className="flex justify-end mt-10 gap-3">
<Button
className="w-max p-6 gap-3 rounded-lg"
onClick={handleSave}
disabled={!canMutate}
>
{isUpdateMode ? "Update Mappings" : "Next"}
<MoveRight />
</Button>
</div>
</div>
</ScrollArea>
);
}
|