scripting

apps/web/src/lib/ml/model-loader.ts

@@ -93,7 +93,10 @@ export async function getModel(): Promise<PlantDiseaseModel> {
     const model = await Promise.race([
       loadingPromise,
       new Promise<never>((_, reject) =>
-        setTimeout(() => reject(new Error(`Model load timed out after ${MODEL_LOAD_TIMEOUT}ms`)), MODEL_LOAD_TIMEOUT),
+        setTimeout(
+          () => reject(new Error(`Model load timed out after ${MODEL_LOAD_TIMEOUT}ms`)),
+          MODEL_LOAD_TIMEOUT,
+        ),
       ),
     ]);
 
@@ -172,6 +175,18 @@ async function tryLoadTFJS(): Promise<PlantDiseaseModel | null> {
   // eslint-disable-next-line @typescript-eslint/no-explicit-any
   let tf: any;
 
+  // Monkey-patch: add util.isNullOrUndefined for Node.js 26 compatibility.
+  // @tensorflow/tfjs-node references this function which was removed in Node 15+.
+  // eslint-disable-next-line @typescript-eslint/no-require-imports
+  const nodeUtil = require("util");
+  // eslint-disable-next-line @typescript-eslint/no-explicit-any
+  if (typeof (nodeUtil as any).isNullOrUndefined !== "function") {
+    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    (nodeUtil as any).isNullOrUndefined = function (x: unknown): boolean {
+      return x === null || x === undefined;
+    };
+  }
+
   // Try tfjs-node first (server-side, uses native bindings).
   // Use dynamic strings so bundlers (Turbopack/webpack) don't trace these
   // as required dependencies — they are truly optional.
@@ -197,7 +212,9 @@ async function tryLoadTFJS(): Promise<PlantDiseaseModel | null> {
       const startTime = performance.now();
 
       // Reshape to [1, 3, 160, 160] NCHW → [1, 160, 160, 3] NHWC for TF.js
-      const inputTensor = tf.tensor4d(Array.from(tensor), [3, 160, 160])
+      // Reshape NCHW flat array [3*160*160] → [3, 160, 160] → NHWC [1, 160, 160, 3]
+      const inputTensor = tf
+        .tensor3d(Array.from(tensor), [3, 160, 160])
         .transpose([1, 2, 0])
         .expandDims(0);
 
@@ -352,7 +369,7 @@ function generateMockLogits(tensor: Float32Array): Float32Array {
   logits[topIndex] = 3.5;
 
   // Second highest
-  const secondIndex = (topIndex + Math.abs(hash % 10) + 1) % (numClasses - 1) + 1;
+  const secondIndex = ((topIndex + Math.abs(hash % 10) + 1) % (numClasses - 1)) + 1;
   logits[secondIndex] = 2.5;
 
   logits[numClasses - 1] = -2; // "unknown" gets low score