Files
zeavis-edu/apps/api/src/routes/dashboard.ts
T
Asep Haryana Saputra 15c6be9e84 feat: implement backend image classification with TensorFlow.js model
- Extend shared types for image classification, including PredictionProbability, UploaderMetadata, and ImageClassificationRecord.
- Create image_classifications table in the database with necessary fields and foreign key constraints.
- Implement disease mappers to convert database rows to shared disease records.
- Develop uploader client to handle image uploads to external service.
- Create image model service to load and classify images using TensorFlow.js.
- Add API routes for image classification, including GET for history and POST for new classifications.
- Implement frontend components for image classification form and display results.
- Update dashboard to integrate image classification functionality and display results.
- Document implementation plan for backend image classification.
2026-05-22 15:13:22 +00:00

89 lines
3.5 KiB
TypeScript

import { Elysia } from 'elysia';
import type { DashboardSummary, RiskLevel } from '@zeavis/shared';
import { createDbClient } from '../db/client';
import { diseaseCatalog, imageClassifications, manualClassifications } from '../db/schema';
import { serviceUnavailable } from '../lib/http-errors';
import { desc, eq } from 'drizzle-orm';
export const dashboardRoutes = new Elysia({ prefix: '/api/v1' }).get('/dashboard/summary', async () => {
try {
const db = createDbClient();
const diseaseCount = await db.select().from(diseaseCatalog);
const manualClassificationCount = await db.select().from(manualClassifications);
const imageClassificationCount = await db.select().from(imageClassifications);
const latestClassificationRow = await db
.select({
id: manualClassifications.id,
diseaseSlug: manualClassifications.diseaseSlug,
observation: manualClassifications.observation,
location: manualClassifications.location,
createdAt: manualClassifications.createdAt,
disease: {
slug: diseaseCatalog.slug,
label: diseaseCatalog.label,
commonName: diseaseCatalog.commonName,
summary: diseaseCatalog.summary,
description: diseaseCatalog.description,
symptoms: diseaseCatalog.symptoms,
recommendations: diseaseCatalog.recommendations,
riskLevel: diseaseCatalog.riskLevel,
accentColor: diseaseCatalog.accentColor,
displayOrder: diseaseCatalog.displayOrder,
},
})
.from(manualClassifications)
.innerJoin(diseaseCatalog, eq(manualClassifications.diseaseSlug, diseaseCatalog.slug))
.orderBy(desc(manualClassifications.createdAt))
.limit(1);
const latestClassification = latestClassificationRow[0]
? {
id: latestClassificationRow[0].id,
diseaseSlug: latestClassificationRow[0].diseaseSlug as any,
observation: latestClassificationRow[0].observation,
location: latestClassificationRow[0].location,
createdAt: latestClassificationRow[0].createdAt.toISOString(),
disease: {
slug: latestClassificationRow[0].disease.slug as any,
label: latestClassificationRow[0].disease.label as any,
commonName: latestClassificationRow[0].disease.commonName,
summary: latestClassificationRow[0].disease.summary,
description: latestClassificationRow[0].disease.description,
symptoms: latestClassificationRow[0].disease.symptoms,
recommendations: latestClassificationRow[0].disease.recommendations,
riskLevel: latestClassificationRow[0].disease.riskLevel as any,
accentColor: latestClassificationRow[0].disease.accentColor,
displayOrder: latestClassificationRow[0].disease.displayOrder,
},
}
: null;
const riskDistributionRows = await db.select().from(diseaseCatalog);
const riskDistribution: Record<RiskLevel, number> = {
low: 0,
medium: 0,
high: 0,
};
for (const row of riskDistributionRows) {
const risk = row.riskLevel as RiskLevel;
if (risk in riskDistribution) {
riskDistribution[risk]++;
}
}
const summary: DashboardSummary = {
diseaseCount: diseaseCount.length,
classificationCount: manualClassificationCount.length + imageClassificationCount.length,
latestClassification,
riskDistribution,
};
return summary;
} catch (error) {
return serviceUnavailable('Database unavailable');
}
});