[RNE Rewrite] chore!: miscellaneous jsdoc, export improvements and small fixes

.agents/skills/add-task-pipeline/SKILL.md

@@ -100,7 +100,7 @@ import { loadModel } from '../../../core/model';
 import { validateSpec, method, f32 } from '../../../core/schema';
 import { wrapAsync } from '../../../core/runtime';
 import { type ImageBuffer } from '../image';
-import { createImagePreprocessor, type ImagePreprocessorOptions } from './preprocessing';
+import { createImagePreprocessor, type ImagePreprocessorOptions } from '../utils/imagePreprocessor';
 
 export type MyTaskOptions = ImagePreprocessorOptions & {
   readonly defaultThreshold: number;
@@ -190,28 +190,21 @@ Wrap the task pipeline in a custom React Hook using the core hooks `useResourceD
 
 ```typescript
 import { useModel } from './useModel';
-import { useResourceDownload } from './useResourceDownload';
+import { useResourceDownload, type ResourceOptions } from './useResourceDownload';
 import { createMyTask, type MyTaskModel } from '../extensions/<domain>/tasks/<task>';
 
-export function useMyTask(config: MyTaskModel, options?: { preventLoad?: boolean }) {
+export function useMyTask(config: MyTaskModel, options?: ResourceOptions) {
   // 1. Resolve remote or local asset model path and download progress
-  const { localPath, downloadProgress, downloadError } = useResourceDownload(
-    config.modelPath,
-    options?.preventLoad
-  );
+  const { resource, downloadProgress, downloadError } = useResourceDownload(config, options);
 
   // 2. Instantiate and compile the task pipeline (with automatic lifecycle cleanup)
-  const { model, error } = useModel(
-    createMyTask,
-    localPath ? { ...config, modelPath: localPath } : null,
-    [localPath]
-  );
+  const { model, error } = useModel(createMyTask, resource);
 
   return {
     isReady: !!model,
     error: downloadError || error,
     downloadProgress,
-    localPath,
+    resource,
     runTask: model?.runTask,
     runTaskWorklet: model?.runTaskWorklet,
   };

.agents/skills/model-schema-validation/SKILL.md

@@ -30,7 +30,7 @@ import {
   i64,
   i32,
   DynamicDim as Dyn,
-  constr,
+  constraint,
 } from '../../../core/schema';
 
 const { variant, dims } = validateSpec(model.schema, {
@@ -39,7 +39,7 @@ const { variant, dims } = validateSpec(model.schema, {
     [i64(1, Dyn('L')), i64(1, Dyn('L'))],
     [f32(1, 'D')],
     [
-      constr.eq(
+      constraint.equality(
         { paramSide: 'input', tensorIdx: 0, dimIdx: 1 },
         { paramSide: 'input', tensorIdx: 1, dimIdx: 1 }
       ),
@@ -50,7 +50,7 @@ const { variant, dims } = validateSpec(model.schema, {
     [i64(Dyn('L')), i64(Dyn('L'))],
     [f32('D')],
     [
-      constr.eq(
+      constraint.equality(
         { paramSide: 'input', tensorIdx: 0, dimIdx: 0 },
         { paramSide: 'input', tensorIdx: 1, dimIdx: 0 }
       ),
@@ -68,10 +68,10 @@ const L = dims.range('L');
 - **`f32(...)` / `i64(...)` / `i32(...)` / `ui8(...)`**: Shorthand helpers for tensor parameter specs.
 - **`StaticDim('symbol')` / String Literals**: Strings passed to shape helpers (e.g. `'H'`, `'W'`) automatically map to `StaticDim`, acting as **static dimension wildcards**. They bind strictly to `constant` positive integer dimensions in the exported spec.
 - **`DynamicDim('symbol')` (or `Dyn('symbol')`)**: Creates a dynamic dimension symbol. Must be used when a dimension genuinely varies at runtime and binds to a `range` or `enum` domain in the exported spec.
-- **Constraint Helpers (`constr`)**:
+- **Constraint Helpers (`constraint`)**:
   - **`DimRef` Object Literal (`{ paramSide: 'input' | 'output', tensorIdx, dimIdx }`)**: Explicit reference to a tensor's dimension.
-  - **`constr.eq(...dims)`**: Creates an equality constraint requiring the referenced dimensions to take the exact same value at runtime.
-  - **`constr.linear(lhs, rhs, a, b)`**: Creates a linear constraint `lhs = a * rhs + b`.
+  - **`constraint.equality(...dims)`**: Creates an equality constraint requiring the referenced dimensions to take the exact same value at runtime.
+  - **`constraint.linear(lhs, rhs, a, b?)`**: Creates a linear constraint `lhs = a * rhs + b`.
 - **`validateSpec(exportedSchema, allowedVariants)`**: Compares the model's exported schema against named variants and returns `{ variant, dim, dims }`.
 - **Symbol Accessors (`dims` & `dim`)**:
   - `dims.constant('N', 'H')`: Extracts constant values for symbols as numbers.
@@ -118,24 +118,24 @@ Understanding the distinction between a dimension's **domain** and its **runtime
   - Dynamic symbols (`DynamicDim('S')`) bind to exported dimension domains. Reusing a symbol (`'S'`) across tensor inputs or outputs requires every occurrence to bind to the **exact same domain**.
   - ⚠️ **Key Rule**: Binding to the same domain does **NOT** mean runtime values coincide! Two dimensions bound to the same domain (e.g., both having range `1..512`) may take _different_ runtime values in a single execution (e.g. length 10 and length 25).
 
-### 2. Runtime Constraints (`constr.eq` & `constr.linear`)
+### 2. Runtime Constraints (`constraint.equality` & `constraint.linear`)
 
 - **Runtime Constraints**: Declarations about the **runtime values** of tensor dimensions during execution:
-  - **Equality Constraint (`constr.eq(...)`)**: Requires all referenced dimensions to take the exact same runtime value in any execution call.
+  - **Equality Constraint (`constraint.equality(...)`)**: Requires all referenced dimensions to take the exact same runtime value in any execution call.
     ```typescript
     method(
       'forward',
       [f32('B', Dyn('S1')), f32('B', Dyn('S2'))],
       [f32('B', Dyn('S1'))],
       [
-        constr.eq(
+        constraint.equality(
           { paramSide: 'input', tensorIdx: 0, dimIdx: 0 },
           { paramSide: 'input', tensorIdx: 1, dimIdx: 0 }
         ),
       ]
     );
     ```
-  - **Linear Constraint (`constr.linear(...)`)**: Requires two dimensions to satisfy `dimLhs = a * dimRhs + b` at runtime.
+  - **Linear Constraint (`constraint.linear(...)`)**: Requires two dimensions to satisfy `dimLhs = a * dimRhs + b` at runtime.
 - **Validation & Enforcement**:
   - `validateSpec` verifies that the exported model spec declares the exact same runtime constraints (1-to-1 declaration match).
   - Native C++ validates input runtime constraints before invoking `model.execute()`.

.eslintrc.js

@@ -1,14 +1,7 @@
 const path = require('path');
+const typedocConfig = require('./docs/typedoc.json');
 
-const VALID_CATEGORIES = [
-  'Constants',
-  'Errors',
-  'Hooks',
-  'Types',
-  'Typescript API',
-  'Utils',
-  'Utilities - General',
-];
+const VALID_CATEGORIES = typedocConfig.categoryOrder.filter((cat) => cat !== '*');
 
 const CATEGORY_TAG_MATCH = `^(${VALID_CATEGORIES.join('|')})$`;
 

apps/computer-vision/app/detection/index.tsx

@@ -16,11 +16,11 @@ import { BoundingBox } from '../../components/BoundingBox';
 const MODEL_OPTIONS: ModelOption[] = [
   {
     label: 'SSDLite 320 MobileNet V3 Large (XNNPACK FP32)',
-    value: models.objectDetection.SSDLITE320_MOBILENET_V3_LARGE,
+    value: models.objectDetection.SSDLITE320_MOBILENET_V3_LARGE.DEFAULT,
   },
   {
     label: 'RF-DETR Nano (XNNPACK FP32)',
-    value: models.objectDetection.RFDETR_NANO,
+    value: models.objectDetection.RFDETR_NANO.DEFAULT,
   },
   {
     label: 'RF-DETR Nano (CoreML FP16)',

apps/computer-vision/app/imageEmbeddings/index.tsx

@@ -71,7 +71,7 @@ function ImageEmbeddingsContent() {
   // Zero-shot classification pairs a CLIP image encoder with the CLIP text
   // encoder and scores the image against each text label by embedding similarity.
   const imageModel = useImageEmbedder(selectedImageModel);
-  const textModel = useTextEmbedder(models.textEmbeddings.CLIP_VIT_BASE_PATCH32_TEXT);
+  const textModel = useTextEmbedder(models.textEmbeddings.CLIP_VIT_BASE_PATCH32_TEXT.DEFAULT);
 
   const ready = imageModel.isReady && textModel.isReady;
 

apps/computer-vision/app/inspect/index.tsx

@@ -10,13 +10,13 @@ import {
   Alert,
 } from 'react-native';
 import { useSafeAreaInsets } from 'react-native-safe-area-context';
-import { inspectModel, type ConcreteDim, type ParamSpec } from 'react-native-executorch';
+import { inspectModel, type schema } from 'react-native-executorch';
 import ScreenWrapper from '../../components/ScreenWrapper';
 import { ColorPalette } from '../../theme';
 
 type InspectionResult = Awaited<ReturnType<typeof inspectModel>>;
 
-const formatDim = (dim: ConcreteDim): string => {
+const formatDim = (dim: schema.ConcreteDim): string => {
   switch (dim.kind) {
     case 'constant':
       return `${dim.value}`;
@@ -55,7 +55,7 @@ function InspectContent() {
   };
 
   const renderParamList = (
-    params: readonly ParamSpec<ConcreteDim>[] | undefined,
+    params: readonly schema.ParamSpec<schema.ConcreteDim>[] | undefined,
     title: string
   ) => {
     if (!params || params.length === 0) return null;

apps/computer-vision/app/keypoint/index.tsx

@@ -16,7 +16,7 @@ import { BoundingBox } from '../../components/BoundingBox';
 const MODEL_OPTIONS: ModelOption[] = [
   {
     label: 'BlazeFace (XNNPACK FP32)',
-    value: models.keypointDetection.BLAZEFACE,
+    value: models.keypointDetection.BLAZEFACE.DEFAULT,
   },
   {
     label: 'YOLO26 Pose (XNNPACK FP32)',

apps/computer-vision/tsconfig.json

@@ -9,7 +9,17 @@
     "customConditions": ["react-native"],
     "noEmit": true,
     "paths": {
-      "react-native-executorch": ["../../packages/react-native-executorch/src"]
+      "react-native-executorch": ["../../packages/react-native-executorch/src"],
+      "react-native-executorch/cv": ["../../packages/react-native-executorch/src/extensions/cv"],
+      "react-native-executorch/llm": ["../../packages/react-native-executorch/src/extensions/llm"],
+      "react-native-executorch/nlp": ["../../packages/react-native-executorch/src/extensions/nlp"],
+      "react-native-executorch/speech": [
+        "../../packages/react-native-executorch/src/extensions/speech"
+      ],
+      "react-native-executorch/math": [
+        "../../packages/react-native-executorch/src/extensions/math"
+      ],
+      "react-native-executorch/schema": ["../../packages/react-native-executorch/src/core/schema"]
     }
   }
 }

apps/nlp/app/llm/index.tsx

@@ -15,14 +15,7 @@ import {
 import { Skia } from '@shopify/react-native-skia';
 import RNBlobUtil from 'react-native-blob-util';
 import { useSafeAreaInsets } from 'react-native-safe-area-context';
-import {
-  useLLMChatSession,
-  type LLMGenerationStats,
-  type LLMKVCacheState,
-  type ToolCall,
-  type ChatMessage,
-  type cv,
-} from 'react-native-executorch';
+import { useLLMChatSession, type llm, type cv } from 'react-native-executorch';
 import ScreenWrapper from '../../components/ScreenWrapper';
 import { ModelPicker, type ModelOption } from '../../components/ModelPicker';
 import { Button } from '../../components/Button';
@@ -33,11 +26,11 @@ type Turn = {
   role: 'user' | 'assistant' | 'tool';
   content: string;
   imageUri?: string;
-  stats?: LLMGenerationStats;
-  toolCalls?: readonly ToolCall[];
+  stats?: llm.LLMGenerationStats;
+  toolCalls?: readonly llm.ToolCall[];
 };
 
-function formatStats(stats: LLMGenerationStats): string {
+function formatStats(stats: llm.LLMGenerationStats): string {
   const decodeMs = stats.inferenceEndMs - stats.firstTokenMs;
   const tokensPerSec = decodeMs > 0 ? (stats.numGeneratedTokens / decodeMs) * 1000 : 0;
   const decodeTtftMs = stats.firstTokenMs - stats.inferenceStartMs;
@@ -70,7 +63,7 @@ function LLMContent() {
     []
   );
 
-  const initialMessages: ChatMessage[] = useMemo(
+  const initialMessages: llm.ChatMessage[] = useMemo(
     () => (activeModel.systemPrompt ? [{ role: 'system', content: activeModel.systemPrompt }] : []),
     [activeModel]
   );
@@ -88,7 +81,7 @@ function LLMContent() {
   const [turns, setTurns] = useState<Turn[]>([]);
   const [streamingResponse, setStreamingResponse] = useState<string | null>(null);
 
-  let kvCacheState: LLMKVCacheState | null = null;
+  let kvCacheState: llm.LLMKVCacheState | null = null;
   if (isReady && getKVCacheState) {
     try {
       kvCacheState = getKVCacheState();

apps/nlp/app/privacy-filter/index.tsx

@@ -9,14 +9,7 @@ import {
   KeyboardAvoidingView,
   Platform,
 } from 'react-native';
-import {
-  usePrivacyFilter,
-  models,
-  piiSegments,
-  type PiiEntity,
-  type PiiSegment,
-  type PrivacyFilterModel,
-} from 'react-native-executorch';
+import { usePrivacyFilter, models, nlp, type PrivacyFilterModel } from 'react-native-executorch';
 import ScreenWrapper from '../../components/ScreenWrapper';
 import { ModelStatus } from '../../components/ModelStatus';
 import { Button } from '../../components/Button';
@@ -33,14 +26,18 @@ Reach her at maria.lopez@example.com or +1 (415) 555-0142. Address: 84 Cedar Hil
 /* cspell:enable */
 
 const MODELS: { label: string; value: PrivacyFilterModel; sample: string; iosOnly?: boolean }[] = [
-  { label: 'OpenAI (8 types)', value: models.privacyFilter.OPENAI, sample: OPENAI_SAMPLE },
+  { label: 'OpenAI (8 types)', value: models.privacyFilter.OPENAI.DEFAULT, sample: OPENAI_SAMPLE },
   {
     label: 'OpenAI MLX',
     value: models.privacyFilter.OPENAI.MLX_INT4,
     sample: OPENAI_SAMPLE,
     iosOnly: true,
   },
-  { label: 'Nemotron (55 types)', value: models.privacyFilter.NEMOTRON, sample: NEMOTRON_SAMPLE },
+  {
+    label: 'Nemotron (55 types)',
+    value: models.privacyFilter.NEMOTRON.DEFAULT,
+    sample: NEMOTRON_SAMPLE,
+  },
   {
     label: 'Nemotron MLX',
     value: models.privacyFilter.NEMOTRON.MLX_INT8,
@@ -64,14 +61,14 @@ function PrivacyFilterContent() {
   const { isReady, downloadProgress, error, detectPii } = usePrivacyFilter(active.value);
 
   const [text, setText] = useState(active.sample);
-  const [entities, setEntities] = useState<PiiEntity[] | null>(null);
+  const [entities, setEntities] = useState<nlp.PiiEntity[] | null>(null);
   const [busy, setBusy] = useState(false);
   const [runError, setRunError] = useState<string | null>(null);
   const [inferenceMs, setInferenceMs] = useState<number | null>(null);
 
   const ready = isReady && !!detectPii;
-  const segments: PiiSegment[] | null = useMemo(
-    () => (entities ? piiSegments(text, entities) : null),
+  const segments: nlp.PiiSegment[] | null = useMemo(
+    () => (entities ? nlp.piiSegments(text, entities) : null),
     [text, entities]
   );
 

apps/nlp/app/text-embeddings/index.tsx

@@ -24,16 +24,22 @@ const MODELS: {
   docPrompt?: string;
   iosOnly?: boolean;
 }[] = [
-  { label: 'MiniLM L6', value: models.textEmbeddings.ALL_MINILM_L6_V2 },
-  { label: 'MPNet Base', value: models.textEmbeddings.ALL_MPNET_BASE_V2 },
-  { label: 'MultiQA MiniLM', value: models.textEmbeddings.MULTI_QA_MINILM_L6_COS_V1 },
-  { label: 'MultiQA MPNet', value: models.textEmbeddings.MULTI_QA_MPNET_BASE_DOT_V1 },
-  { label: 'Paraphrase ML', value: models.textEmbeddings.PARAPHRASE_MULTILINGUAL_MINILM_L12_V2 },
-  { label: 'DistilUSE ML', value: models.textEmbeddings.DISTILUSE_BASE_MULTILINGUAL_CASED_V2 },
-  { label: 'CLIP Text', value: models.textEmbeddings.CLIP_VIT_BASE_PATCH32_TEXT },
+  { label: 'MiniLM L6', value: models.textEmbeddings.ALL_MINILM_L6_V2.DEFAULT },
+  { label: 'MPNet Base', value: models.textEmbeddings.ALL_MPNET_BASE_V2.DEFAULT },
+  { label: 'MultiQA MiniLM', value: models.textEmbeddings.MULTI_QA_MINILM_L6_COS_V1.DEFAULT },
+  { label: 'MultiQA MPNet', value: models.textEmbeddings.MULTI_QA_MPNET_BASE_DOT_V1.DEFAULT },
+  {
+    label: 'Paraphrase ML',
+    value: models.textEmbeddings.PARAPHRASE_MULTILINGUAL_MINILM_L12_V2.DEFAULT,
+  },
+  {
+    label: 'DistilUSE ML',
+    value: models.textEmbeddings.DISTILUSE_BASE_MULTILINGUAL_CASED_V2.DEFAULT,
+  },
+  { label: 'CLIP Text', value: models.textEmbeddings.CLIP_VIT_BASE_PATCH32_TEXT.DEFAULT },
   {
     label: 'LFM2.5',
-    value: models.textEmbeddings.LFM2_5_EMBEDDING_350M,
+    value: models.textEmbeddings.LFM2_5_EMBEDDING_350M.DEFAULT,
     docPrompt: 'document: ',
   },
   {