feat: call ML service for image classification

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-05-22 19:53:10 +00:00
parent 9a642a8581
commit 1689f3f44e
2 changed files with 164 additions and 108 deletions
@@ -0,0 +1,81 @@
+import { afterEach, describe, expect, test } from 'bun:test';
+import { classifyImage } from './image-model';
+
+const originalFetch = globalThis.fetch;
+
+afterEach(() => {
+  globalThis.fetch = originalFetch;
+});
+
+function makeImageFile(type = 'image/jpeg') {
+  return new File([new Uint8Array([1, 2, 3])], 'leaf.jpg', { type });
+}
+
+function mockFetch(handler: (input: Parameters<typeof fetch>[0], init?: Parameters<typeof fetch>[1]) => Promise<Response>) {
+  globalThis.fetch = Object.assign(handler, { preconnect: originalFetch.preconnect });
+}
+
+describe('classifyImage', () => {
+  test('maps ML service prediction response to API classification result', async () => {
+    mockFetch(async (input, init) => {
+      expect(String(input)).toBe('http://127.0.0.1:8001/predict');
+      expect(init?.method).toBe('POST');
+      expect(init?.body).toBeInstanceOf(FormData);
+
+      return new Response(
+        JSON.stringify({
+          label: 'Daun Sehat',
+          confidence: 0.92,
+          probabilities: {
+            'Bercak Daun': 0.02,
+            'Daun Sehat': 0.92,
+            'Karat Daun': 0.03,
+            'Hawar Daun': 0.03,
+          },
+        }),
+        { status: 200, headers: { 'content-type': 'application/json' } },
+      );
+    });
+
+    const result = await classifyImage(makeImageFile());
+
+    expect(result.predictedDiseaseSlug).toBe('daun-sehat');
+    expect(result.confidence).toBe(0.92);
+    expect(result.probabilities).toEqual([
+      { diseaseSlug: 'daun-sehat', label: 'Daun Sehat', confidence: 0.92 },
+      { diseaseSlug: 'karat-daun', label: 'Karat Daun', confidence: 0.03 },
+      { diseaseSlug: 'hawar-daun', label: 'Hawar Daun', confidence: 0.03 },
+      { diseaseSlug: 'bercak-daun', label: 'Bercak Daun', confidence: 0.02 },
+    ]);
+  });
+
+  test('rejects unsupported file types before calling ML service', async () => {
+    let called = false;
+    mockFetch(async () => {
+      called = true;
+      return new Response('{}');
+    });
+
+    await expect(classifyImage(makeImageFile('image/webp'))).rejects.toThrow('File must be JPEG or PNG');
+    expect(called).toBe(false);
+  });
+
+  test('throws when ML service returns a non-success response', async () => {
+    mockFetch(async () => new Response(JSON.stringify({ detail: 'Model is not loaded' }), { status: 503 }));
+
+    await expect(classifyImage(makeImageFile())).rejects.toThrow('ML service returned 503: Model is not loaded');
+  });
+
+  test('throws when ML service returns an unknown label', async () => {
+    mockFetch(async () => new Response(
+      JSON.stringify({
+        label: 'Unknown Disease',
+        confidence: 0.7,
+        probabilities: { 'Unknown Disease': 0.7 },
+      }),
+      { status: 200, headers: { 'content-type': 'application/json' } },
+    ));
+
+    await expect(classifyImage(makeImageFile())).rejects.toThrow('Unknown ML service label: Unknown Disease');
+  });
+});