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import { useRef, useState } from "react";
import { toast } from "sonner";
import { AccessControlledButton as Button } from "@/ahuora-design-system/ui/accessControlled";
import {
DropdownMenu,
DropdownMenuContent,
DropdownMenuItem,
DropdownMenuTrigger,
} from "@/ahuora-design-system/ui/dropdown-menu";
import { Progress } from "@/ahuora-design-system/ui/progress";
import { ScrollArea } from "@/ahuora-design-system/ui/scroll-area";
import {
MlModelRead,
ModelTypeEnum,
TransitionEnum,
useCoreMlPartialUpdateMutation,
useCoreMlTransitionWizardCreateMutation,
useCoreMlUploadMlModelCreateMutation,
useLazyUploadsCsvInspectRetrieveQuery,
} from "@/api/apiStore.gen";
import { useMLTrainRefresh } from "@/hooks/cache/useMLTrainRefresh";
import { useFlowsheetAccess } from "@/hooks/flowsheetAccess";
import { useFlowsheetId } from "@/hooks/project";
import { scanCsvHeadersLocal } from "@/lib/uploads/csvHeader";
import { formatUploadProgress } from "@/lib/uploads/formatUploadProgress";
import { NUMERIC_COLUMNS_TOOLTIP } from "@/lib/uploads/importNotes";
import { isSameUploadedFileSelection } from "@/lib/uploads/isSameUploadedFileSelection";
import { resolveUploadActivityStatus } from "@/lib/uploads/resolveUploadActivityStatus";
import {
ML_INPUT_CSV_EXPIRY_NOTE,
PARTIAL_UPLOAD_EXPIRY_NOTE,
} from "@/lib/uploads/retention";
import { UploadActivityStatus } from "@/lib/uploads/UploadActivityStatus";
import { UploadWarningNotice } from "@/lib/uploads/UploadWarningNotice";
import { useResumableMultipartUpload } from "@/lib/uploads/useResumableMultipartUpload.ts";
import CSVUploader from "@/pages/flowsheet-page/multi-steady-state/CSVUploader";
export type CsvHeaderPreviewState = {
headers: string[];
delimiter: string | null;
warnings: string[];
source: "local" | "backend";
};
interface UploadCSVProps {
model: MlModelRead;
simulationObject: number;
onUpdateModelType: (modelType: ModelTypeEnum) => void;
onCsvHeaderPreviewChange: (preview: CsvHeaderPreviewState | null) => void;
}
function isCsvFile(file: File): boolean {
return file.name.toLowerCase().endsWith(".csv");
}
export default function UploadCSV({
model,
simulationObject,
onUpdateModelType,
onCsvHeaderPreviewChange,
}: UploadCSVProps) {
const fileInputRef = useRef<HTMLInputElement | null>(null);
const access = useFlowsheetAccess();
const canMutate = access?.can_edit ?? true;
const flowsheetId = Number(useFlowsheetId());
const { refreshMLTrainDependencies } = useMLTrainRefresh();
const [isFinalizingUpload, setIsFinalizingUpload] = useState(false);
const [isUploadComplete, setIsUploadComplete] = useState(false);
const [updateMLModel] = useCoreMlPartialUpdateMutation();
const [transitionWizard] = useCoreMlTransitionWizardCreateMutation();
const [uploadModel] = useCoreMlUploadMlModelCreateMutation();
const [inspectUploadedCsv] = useLazyUploadsCsvInspectRetrieveQuery();
const uploadContext = {
purpose: "ml_training_csv" as const,
flowsheet_id: flowsheetId,
simulationObject_id: simulationObject,
};
const { state, startUpload, abortUpload, clearUploadState } =
useResumableMultipartUpload({
storageKey: `csv-upload:ml:${model.id}`,
context: uploadContext,
});
/** Submit a completed object-storage upload session to the ML model and refresh headers. */
async function finalizeUploadedCsv(uploadSessionId: string): Promise<void> {
setIsFinalizingUpload(true);
try {
await updateMLModel({
id: model.id,
patchedPatchMlModel: {
csv_upload_session: Number(uploadSessionId),
},
}).unwrap();
refreshMLTrainDependencies();
try {
const confirmedHeaders = await inspectUploadedCsv(
{ uploadSessionId: Number(uploadSessionId) },
true,
).unwrap();
onCsvHeaderPreviewChange({
headers: confirmedHeaders.headers,
delimiter: confirmedHeaders.detected_delimiter,
warnings: confirmedHeaders.warnings ?? [],
source: "backend",
});
} catch {
// The backend header endpoint remains the source of truth in the next wizard step.
}
clearUploadState();
setIsUploadComplete(true);
toast.success("CSV upload complete.");
} catch (error) {
toast.error("Upload finalization failed", {
description:
error instanceof Error
? error.message
: "The uploaded CSV could not be attached to the ML model.",
});
} finally {
setIsFinalizingUpload(false);
}
}
/** Upload a CSV to object storage, attach it to the ML model, and refresh headers. */
async function handleUpload(file: File): Promise<void> {
if (!isCsvFile(file)) {
toast.error("Unsupported file", {
description: "Please upload a CSV file.",
});
return;
}
try {
const localHeaders = await scanCsvHeadersLocal(file);
if (
localHeaders.guessedDelimiter == null ||
localHeaders.headers.length === 0
) {
toast.error("Unsupported CSV format", {
description:
localHeaders.warnings[0] ??
"Only UTF-8 CSV files with comma or semicolon delimiters are supported.",
});
return;
}
onCsvHeaderPreviewChange({
headers: localHeaders.headers,
delimiter: localHeaders.guessedDelimiter,
warnings: localHeaders.warnings,
source: "local",
});
if (isSameUploadedFileSelection(state, file)) {
toast.warning("CSV already uploaded", {
description:
"This file has already completed uploading. Use Finish upload if you still need to attach it.",
});
return;
}
const completedUpload = await startUpload(file);
await finalizeUploadedCsv(completedUpload.upload_session_id);
} catch (error) {
if (error instanceof DOMException && error.name === "AbortError") {
return;
}
toast.error("Upload failed", {
description:
error instanceof Error
? error.message
: "The CSV file could not be uploaded.",
});
}
}
const handleImportClick = () => {
fileInputRef.current?.click();
};
const importModel = (event: React.ChangeEvent<HTMLInputElement>) => {
const file = event.target.files?.[0];
if (file) {
const reader = new FileReader();
reader.onload = async (e) => {
try {
const raw = e.target?.result;
const parsedJson = typeof raw === "string" ? JSON.parse(raw) : raw;
await uploadModel({
uploadModel: {
model: model.id,
json_data: parsedJson,
},
}).unwrap();
onCsvHeaderPreviewChange(null);
refreshMLTrainDependencies();
} catch (error) {
toast.error("Model import failed", {
description: "Choose a valid exported ML model file.",
});
}
};
reader.readAsText(file);
}
};
const handlePrepareData = async () => {
if (isUploadComplete) {
try {
await transitionWizard({
mlWizardTransition: {
model: model.id,
transition: TransitionEnum.AdvanceToMappings,
},
}).unwrap();
refreshMLTrainDependencies();
} catch {
toast.error("Unable to set mappings", {
description: "Attach a completed CSV before mapping its columns.",
});
}
}
};
const showMultipartStatus = state.status !== "idle";
const uploadActivityStatus = resolveUploadActivityStatus({
uploadStatus: state.status,
progressPercentage: state.progress.percentage,
uploadingLabel: "Uploading the CSV to object storage.",
finalizingUploadLabel:
"Finishing the CSV upload before attaching it to the ML model.",
processingLabel: isFinalizingUpload
? "Finalizing the upload and attaching the CSV to the ML model."
: null,
isProcessing: isFinalizingUpload,
});
return (
<ScrollArea>
<div className="flex min-h-full flex-col justify-between gap-10">
<div className="flex flex-col gap-10">
<div className="flex flex-col gap-4">
<div className="flex flex-row items-center justify-between align-middle w-full my-2">
<div className="flex flex-col gap-1">
<h1>File Upload</h1>
<p className="font-light">{ML_INPUT_CSV_EXPIRY_NOTE}</p>
</div>
<div>
<input
type="file"
accept=".json"
onChange={importModel}
disabled={!canMutate}
ref={fileInputRef}
className="hidden"
/>
<Button
variant="outline"
disabled={!canMutate}
onClick={handleImportClick}
>
<FolderOpen />
Import Model
</Button>
</div>
</div>
<CSVUploader
onUpload={handleUpload}
disabled={!canMutate}
accept=".csv,text/csv"
inputAriaLabel="Upload CSV file"
tooltipContent={NUMERIC_COLUMNS_TOOLTIP}
promptText={
state.status === "resume_available"
? "Resume upload by selecting the same CSV file again"
: "Drag a CSV file here, or click to upload"
}
/>
{model && (
<p className="text-sm font-light mt-2">
Uploaded File: {model?.csv_file_name}
</p>
)}
{showMultipartStatus && (
<div className="rounded-lg border bg-muted/40 p-3 flex flex-col gap-3">
<div className="flex items-center justify-between gap-3">
<div className="flex flex-col gap-1">
<p className="text-sm font-medium">
{state.status === "uploading"
? "Uploading CSV to object storage"
: state.status === "resume_available"
? "A resumable upload is waiting"
: state.status === "uploaded"
? "CSV uploaded"
: state.status === "failed"
? "Upload failed"
: "Upload cancelled"}
</p>
{state.fileName && (
<p className="text-xs text-muted-foreground">
{state.fileName}
</p>
)}
</div>
<div className="flex items-center gap-2">
{state.status === "uploading" && (
<Button
variant="outline"
size="sm"
onClick={() => void abortUpload()}
>
<X className="w-4 h-4" />
Cancel
</Button>
)}
{(state.status === "resume_available" ||
state.status === "failed") && (
<Button
variant="outline"
size="sm"
onClick={clearUploadState}
>
<RotateCcw className="w-4 h-4" />
Start over
</Button>
)}
{state.status === "uploaded" && state.uploadSessionId && (
<Button
variant="outline"
size="sm"
disabled={isFinalizingUpload}
onClick={() =>
void finalizeUploadedCsv(state.uploadSessionId!)
}
>
Finish upload
</Button>
)}
</div>
</div>
<Progress
value={state.progress.percentage}
aria-label="ml-upload-progress"
/>
<div className="flex items-center justify-between text-xs text-muted-foreground">
<span>{state.progress.percentage}%</span>
<span>
{formatUploadProgress(
state.progress.uploadedBytes,
state.progress.totalBytes,
)}
</span>
</div>
{state.error && <UploadWarningNotice message={state.error} />}
{state.status === "uploading" && (
<p className="text-xs text-muted-foreground">
{PARTIAL_UPLOAD_EXPIRY_NOTE}
</p>
)}
<UploadActivityStatus {...uploadActivityStatus} />
</div>
)}
</div>
<div className="flex flex-col gap-5">
<div className="flex flex-col gap-1">
<h1>Model Type</h1>
<p className="font-light">
Select the type of machine learning model you want to use.
</p>
</div>
<DropdownMenu>
<DropdownMenuTrigger asChild>
<Button
variant="outline"
className="flex flex-row items-center justify-between w-1/2"
disabled={!canMutate}
>
<p>{model.model_type}</p>
<ChevronDown />
</Button>
</DropdownMenuTrigger>
<DropdownMenuContent>
<DropdownMenuItem
onClick={() => onUpdateModelType(ModelTypeEnum.RbfRegression)}
>
RBF
</DropdownMenuItem>
<DropdownMenuItem
onClick={() =>
onUpdateModelType(ModelTypeEnum.PolynomialRegression)
}
>
Polynomial
</DropdownMenuItem>
</DropdownMenuContent>
</DropdownMenu>
</div>
</div>
<div className="flex justify-end pt-4">
<Button
disabled={!canMutate || !isUploadComplete}
className="w-max p-6 gap-3 rounded-lg disabled:opacity-50 disabled:cursor-not-allowed"
aria-label="set-mappings"
onClick={() => void handlePrepareData()}
>
Set Mappings
<MoveRight />
</Button>
</div>
</div>
</ScrollArea>
);
}
|