feat: Hookless API

docs/docs/computer-vision/useClassification.mdx

@@ -31,20 +31,6 @@ try {
 }
 ```
 
-<details>
-<summary>Type definitions</summary>
-
-```typescript
-interface ClassificationModule {
-  error: string | null;
-  isReady: boolean;
-  isGenerating: boolean;
-  forward: (input: string) => Promise<{ [category: string]: number }>;
-}
-```
-
-</details>
-
 ### Arguments
 
 **`modelSource`**

docs/docs/computer-vision/useObjectDetection.mdx

@@ -11,6 +11,7 @@ It is recommended to use models provided by us, which are available at our [Hugg
 :::
 
 ## Reference
+
 ```jsx
 import { useObjectDetection, SSDLITE_320_MOBILENET_V3_LARGE } from 'react-native-executorch';
 
@@ -45,42 +46,36 @@ interface Detection {
   label: keyof typeof CocoLabel;
   score: number;
 }
-
-interface ObjectDetectionModule {
-  error: string | null;
-  isReady: boolean;
-  isGenerating: boolean;
-  forward: (input: string) => Promise<Detection[]>;
-}
 ```
+
 </details>
 
 ### Arguments
 
 `modelSource`
 
-A string that specifies the path to the model file. You can download the model from our [HuggingFace repository](https://huggingface.co/software-mansion/react-native-executorch-ssdlite320-mobilenet-v3-large/tree/main). 
+A string that specifies the path to the model file. You can download the model from our [HuggingFace repository](https://huggingface.co/software-mansion/react-native-executorch-ssdlite320-mobilenet-v3-large/tree/main).
 For more information on that topic, you can check out the [Loading models](https://docs.swmansion.com/react-native-executorch/fundamentals/loading-models) page.
 
 ### Returns
 
 The hook returns an object with the following properties:
 
-
-| **Field**            | **Type**                              | **Description**                                                                                                  |
-|-----------------------|---------------------------------------|------------------------------------------------------------------------------------------------------------------|
-| `forward`            | `(input: string) => Promise<Detection[]>` | A function that accepts an image (url, b64) and returns an array of `Detection` objects.                                   |
-| `error`              | <code>string &#124; null</code>       | Contains the error message if the model loading failed.    |
-| `isGenerating`  | `boolean`                            | Indicates whether the model is currently processing an inference.                                               |
-| `isReady`       | `boolean`                            | Indicates whether the model has successfully loaded and is ready for inference.                                 |
-
+| Field          | Type                                      | Description                                                                              |
+| -------------- | ----------------------------------------- | ---------------------------------------------------------------------------------------- |
+| `forward`      | `(input: string) => Promise<Detection[]>` | A function that accepts an image (url, b64) and returns an array of `Detection` objects. |
+| `error`        | <code>string &#124; null</code>           | Contains the error message if the model loading failed.                                  |
+| `isGenerating` | `boolean`                                 | Indicates whether the model is currently processing an inference.                        |
+| `isReady`      | `boolean`                                 | Indicates whether the model has successfully loaded and is ready for inference.          |
 
 ## Running the model
 
 To run the model, you can use the `forward` method. It accepts one argument, which is the image. The image can be a remote URL, a local file URI, or a base64-encoded image. The function returns an array of `Detection` objects. Each object contains coordinates of the bounding box, the label of the detected object, and the confidence score. For more information, please refer to the reference or type definitions.
 
 ## Detection object
+
 The detection object is specified as follows:
+
 ```typescript
 interface Bbox {
   x1: number;
@@ -95,33 +90,37 @@ interface Detection {
   score: number;
 }
 ```
+
 The `bbox` property contains information about the bounding box of detected objects. It is represented as two points: one at the bottom-left corner of the bounding box (`x1`, `y1`) and the other at the top-right corner (`x2`, `y2`).
 The `label` property contains the name of the detected object, which corresponds to one of the `CocoLabels`. The `score` represents the confidence score of the detected object.
 
-
-
 ## Example
+
 ```tsx
-import { useObjectDetection, SSDLITE_320_MOBILENET_V3_LARGE } from 'react-native-executorch';
+import {
+  useObjectDetection,
+  SSDLITE_320_MOBILENET_V3_LARGE,
+} from 'react-native-executorch';
 
 function App() {
   const ssdlite = useObjectDetection({
     modelSource: SSDLITE_320_MOBILENET_V3_LARGE,
   });
 
   const runModel = async () => {
-    const detections = await ssdlite.forward("https://url-to-image.jpg");
+    const detections = await ssdlite.forward('https://url-to-image.jpg');
+
     for (const detection of detections) {
-      console.log("Bounding box: ", detection.bbox);
-      console.log("Bounding label: ", detection.label);
-      console.log("Bounding score: ", detection.score);
+      console.log('Bounding box: ', detection.bbox);
+      console.log('Bounding label: ', detection.label);
+      console.log('Bounding score: ', detection.score);
     }
-  }
+  };
 }
 ```
 
 ## Supported models
 
-| Model                                                                                                           | Number of classes | Class list                                                                                                                                                                 |
-| --------------------------------------------------------------------------------------------------------------- | ----------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| [SSDLite320 MobileNetV3 Large](https://pytorch.org/vision/main/models/generated/torchvision.models.detection.ssdlite320_mobilenet_v3_large.html#torchvision.models.detection.SSDLite320_MobileNet_V3_Large_Weights) | 91              | [COCO](https://github.com/software-mansion/react-native-executorch/blob/69802ee1ca161d9df00def1dabe014d36341cfa9/src/types/object_detection.ts#L14) |
+| Model                                                                                                                                                                                                               | Number of classes | Class list                                                                                                                                          |
+| ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------- | --------------------------------------------------------------------------------------------------------------------------------------------------- |
+| [SSDLite320 MobileNetV3 Large](https://pytorch.org/vision/main/models/generated/torchvision.models.detection.ssdlite320_mobilenet_v3_large.html#torchvision.models.detection.SSDLite320_MobileNet_V3_Large_Weights) | 91                | [COCO](https://github.com/software-mansion/react-native-executorch/blob/69802ee1ca161d9df00def1dabe014d36341cfa9/src/types/object_detection.ts#L14) |

docs/docs/computer-vision/useStyleTransfer.mdx

@@ -30,20 +30,6 @@ try {
 }
 ```
 
-<details>
-<summary>Type definitions</summary>
-
-```typescript
-interface StyleTransferModule {
-  error: string | null;
-  isReady: boolean;
-  isGenerating: boolean;
-  forward: (input: string) => Promise<string>;
-}
-```
-
-</details>
-
 ### Arguments
 
 **`modelSource`**

examples/computer-vision/components/ImageWithBboxes.tsx

@@ -68,13 +68,7 @@ export default function ImageWithBboxes({
         const height = (y2 - y1) * scaleY;
 
         return (
-          <View
-            key={index}
-            style={[
-              styles.bbox,
-              { left, top, width, height, borderColor: 'red' },
-            ]}
-          >
+          <View key={index} style={[styles.bbox, { left, top, width, height }]}>
             <Text style={styles.label}>
               {detection.label} ({(detection.score * 100).toFixed(1)}%)
             </Text>
@@ -98,6 +92,7 @@ const styles = StyleSheet.create({
   bbox: {
     position: 'absolute',
     borderWidth: 2,
+    borderColor: 'red',
   },
   label: {
     position: 'absolute',

examples/computer-vision/screens/ObjectDetectionScreen.tsx

@@ -76,7 +76,7 @@ export const ObjectDetectionScreen = ({
             />
           ) : (
             <Image
-              style={{ width: '100%', height: '100%' }}
+              style={styles.fullSizeImage}
               resizeMode="contain"
               source={require('../assets/icons/executorch_logo.png')}
             />
@@ -127,4 +127,8 @@ const styles = StyleSheet.create({
     flex: 1,
     marginRight: 4,
   },
+  fullSizeImage: {
+    width: '100%',
+    height: '100%',
+  },
 });

examples/llama/screens/ChatScreen.tsx

@@ -63,7 +63,7 @@ export default function ChatScreen() {
     <SafeAreaView style={styles.container}>
       <TouchableWithoutFeedback onPress={Keyboard.dismiss}>
         <KeyboardAvoidingView
-          style={{ flex: 1 }}
+          style={styles.keyboardAvoidingView}
           behavior={Platform.OS === 'ios' ? 'padding' : 'height'}
           keyboardVerticalOffset={Platform.OS === 'android' ? 30 : 0}
         >
@@ -133,6 +133,9 @@ const styles = StyleSheet.create({
   container: {
     flex: 1,
   },
+  keyboardAvoidingView: {
+    flex: 1,
+  },
   topContainer: {
     height: 68,
     width: '100%',

src/models/Classification.ts → src/hooks/computer_vision/useClassification.ts

@@ -1,21 +1,19 @@
 import { useState } from 'react';
-import { _ClassificationModule } from '../native/RnExecutorchModules';
-import { useModule } from '../useModule';
+import { _ClassificationModule } from '../../native/RnExecutorchModules';
+import { useModule } from '../../useModule';
 
 interface Props {
   modelSource: string | number;
 }
 
-interface ClassificationModule {
+export const useClassification = ({
+  modelSource,
+}: Props): {
   error: string | null;
   isReady: boolean;
   isGenerating: boolean;
   forward: (input: string) => Promise<{ [category: string]: number }>;
-}
-
-export const useClassification = ({
-  modelSource,
-}: Props): ClassificationModule => {
+} => {
   const [module, _] = useState(() => new _ClassificationModule());
   const {
     error,

src/models/ObjectDetection.ts → src/hooks/computer_vision/useObjectDetection.ts

@@ -1,22 +1,20 @@
 import { useState } from 'react';
-import { _ObjectDetectionModule } from '../native/RnExecutorchModules';
-import { useModule } from '../useModule';
-import { Detection } from '../types/object_detection';
+import { _ObjectDetectionModule } from '../../native/RnExecutorchModules';
+import { useModule } from '../../useModule';
+import { Detection } from '../../types/object_detection';
 
 interface Props {
   modelSource: string | number;
 }
 
-interface ObjectDetectionModule {
+export const useObjectDetection = ({
+  modelSource,
+}: Props): {
   error: string | null;
   isReady: boolean;
   isGenerating: boolean;
   forward: (input: string) => Promise<Detection[]>;
-}
-
-export const useObjectDetection = ({
-  modelSource,
-}: Props): ObjectDetectionModule => {
+} => {
   const [module, _] = useState(() => new _ObjectDetectionModule());
   const {
     error,

src/models/StyleTransfer.ts → src/hooks/computer_vision/useStyleTransfer.ts

@@ -1,21 +1,19 @@
 import { useState } from 'react';
-import { _StyleTransferModule } from '../native/RnExecutorchModules';
-import { useModule } from '../useModule';
+import { _StyleTransferModule } from '../../native/RnExecutorchModules';
+import { useModule } from '../../useModule';
 
 interface Props {
   modelSource: string | number;
 }
 
-interface StyleTransferModule {
+export const useStyleTransfer = ({
+  modelSource,
+}: Props): {
   error: string | null;
   isReady: boolean;
   isGenerating: boolean;
   forward: (input: string) => Promise<string>;
-}
-
-export const useStyleTransfer = ({
-  modelSource,
-}: Props): StyleTransferModule => {
+} => {
   const [module, _] = useState(() => new _StyleTransferModule());
   const {
     error,

src/ETModule.ts → src/hooks/general/useExecutorchModule.ts

@@ -1,16 +1,23 @@
 import { useState } from 'react';
-import { _ETModule } from './native/RnExecutorchModules';
-import { getError } from './Error';
-import { ExecutorchModule } from './types/common';
-import { useModule } from './useModule';
+import { _ETModule } from '../../native/RnExecutorchModules';
+import { useModule } from '../../useModule';
+import { ETInput } from '../../types/common';
+import { getError } from '../../Error';
 
 interface Props {
   modelSource: string | number;
 }
 
 export const useExecutorchModule = ({
   modelSource,
-}: Props): ExecutorchModule => {
+}: Props): {
+  error: string | null;
+  isReady: boolean;
+  isGenerating: boolean;
+  forward: (input: ETInput, shape: number[]) => Promise<number[][]>;
+  loadMethod: (methodName: string) => Promise<void>;
+  loadForward: () => Promise<void>;
+} => {
   const [module] = useState(() => new _ETModule());
   const {
     error,

src/LLM.ts → src/hooks/natural_language_processing/useLLM.ts

@@ -1,12 +1,12 @@
 import { useCallback, useEffect, useRef, useState } from 'react';
 import { EventSubscription, Image } from 'react-native';
-import { ResourceSource, Model } from './types/common';
+import { ResourceSource, Model } from '../../types/common';
 import {
   DEFAULT_CONTEXT_WINDOW_LENGTH,
   DEFAULT_SYSTEM_PROMPT,
   EOT_TOKEN,
-} from './constants/llamaDefaults';
-import { LLM } from './native/RnExecutorchModules';
+} from '../../constants/llamaDefaults';
+import { LLM } from '../../native/RnExecutorchModules';
 
 const interrupt = () => {
   LLM.interrupt();

src/index.tsx

@@ -1,7 +1,23 @@
-export * from './ETModule';
-export * from './LLM';
-export * from './constants/modelUrls';
-export * from './models/Classification';
-export * from './models/ObjectDetection';
-export * from './models/StyleTransfer';
+// hooks
+export * from './hooks/computer_vision/useClassification';
+export * from './hooks/computer_vision/useObjectDetection';
+export * from './hooks/computer_vision/useStyleTransfer';
+
+export * from './hooks/natural_language_processing/useLLM';
+
+export * from './hooks/general/useExecutorchModule';
+
+// modules
+export * from './modules/computer_vision/ClassificationModule';
+export * from './modules/computer_vision/ObjectDetectionModule';
+export * from './modules/computer_vision/StyleTransferModule';
+
+export * from './modules/natural_language_processing/LLMModule';
+
+export * from './modules/general/ExecutorchModule';
+
+// types
 export * from './types/object_detection';
+
+// constants
+export * from './constants/modelUrls';