wip

packages/testing-support/src/media/DemoFaceValidationAdapter.ts

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+import type { FaceValidationPort, FaceValidationResult } from '@gridpilot/media';
+
+/**
+ * Demo implementation of FaceValidationPort.
+ *
+ * In production, this would use a real face detection API like:
+ * - AWS Rekognition
+ * - Google Cloud Vision
+ * - Azure Face API
+ * - OpenCV / face-api.js
+ *
+ * For demo purposes, this always returns a valid face if the image data is provided.
+ */
+export class DemoFaceValidationAdapter implements FaceValidationPort {
+  async validateFacePhoto(imageData: string | Buffer): Promise<FaceValidationResult> {
+    // Simulate some processing time
+    await this.delay(500);
+
+    // Check if we have any image data
+    const dataString = typeof imageData === 'string' ? imageData : imageData.toString();
+
+    if (!dataString || dataString.length < 100) {
+      return {
+        isValid: false,
+        hasFace: false,
+        faceCount: 0,
+        confidence: 0,
+        errorMessage: 'Invalid or empty image data',
+      };
+    }
+
+    // Check for valid base64 image data or data URL
+    const isValidImage =
+      dataString.startsWith('data:image/') ||
+      dataString.startsWith('/9j/') || // JPEG magic bytes in base64
+      dataString.startsWith('iVBOR') || // PNG magic bytes in base64
+      dataString.length > 1000; // Assume long strings are valid image data
+
+    if (!isValidImage) {
+      return {
+        isValid: false,
+        hasFace: false,
+        faceCount: 0,
+        confidence: 0,
+        errorMessage: 'Please upload a valid image file (JPEG or PNG)',
+      };
+    }
+
+    // For demo: always return success with high confidence
+    // In production, this would actually analyze the image
+    return {
+      isValid: true,
+      hasFace: true,
+      faceCount: 1,
+      confidence: 0.95,
+    };
+  }
+
+  private delay(ms: number): Promise<void> {
+    return new Promise((resolve) => setTimeout(resolve, ms));
+  }
+}