refactor!: add static factories for remaining models

.cspell-wordlist.txt

@@ -128,4 +128,15 @@ detr
 metaprogramming
 ktlint
 lefthook
-espeak
+espeak
+NCHW
+həlˈO
+wˈɜɹld
+mˈæn
+dˈʌzᵊnt
+tɹˈʌst
+hɪmsˈɛlf
+nˈɛvəɹ
+ɹˈiᵊli
+ˈɛniwˌʌn
+ˈɛls

docs/docs/04-typescript-api/01-natural-language-processing/LLMModule.md

@@ -15,14 +15,13 @@ TypeScript API implementation of the [useLLM](../../03-hooks/01-natural-language
 ```typescript
 import { LLMModule, LLAMA3_2_1B_QLORA } from 'react-native-executorch';
 
-// Creating an instance
-const llm = new LLMModule({
-  tokenCallback: (token) => console.log(token),
-  messageHistoryCallback: (messages) => console.log(messages),
-});
-
-// Loading the model
-await llm.load(LLAMA3_2_1B_QLORA, (progress) => console.log(progress));
+// Creating an instance and loading the model
+const llm = await LLMModule.fromModelName(
+  LLAMA3_2_1B_QLORA,
+  (progress) => console.log(progress),
+  (token) => console.log(token),
+  (messages) => console.log(messages),
+);
 
 // Running the model - returns the generated response
 const response = await llm.sendMessage('Hello, World!');
@@ -41,30 +40,26 @@ All methods of `LLMModule` are explained in details here: [LLMModule API Referen
 
 ## Loading the model
 
-To create a new instance of `LLMModule`, use the [constructor](../../06-api-reference/classes/LLMModule.md#constructor) with optional callbacks:
-
-- [`tokenCallback`](../../06-api-reference/classes/LLMModule.md#tokencallback) - Function called on every generated token.
-
-- [`messageHistoryCallback`](../../06-api-reference/classes/LLMModule.md#messagehistorycallback) - Function called on every finished message.
-
-Then, to load the model, use the [`load`](../../06-api-reference/classes/LLMModule.md#load) method. It accepts an object with the following fields:
+Use the static [`fromModelName`](../../06-api-reference/classes/LLMModule.md#frommodelname) factory method:
 
-- [`model`](../../06-api-reference/classes/LLMModule.md#model) - Object containing:
-  - [`modelSource`](../../06-api-reference/classes/LLMModule.md#modelsource) - The location of the used model.
-
-  - [`tokenizerSource`](../../06-api-reference/classes/LLMModule.md#tokenizersource) - The location of the used tokenizer.
-
-  - [`tokenizerConfigSource`](../../06-api-reference/classes/LLMModule.md#tokenizerconfigsource) - The location of the used tokenizer config.
+```typescript
+const llm = await LLMModule.fromModelName(
+  LLAMA3_2_3B, // model config constant
+  onDownloadProgress, // optional, progress 0–1
+  tokenCallback, // optional, called on every token
+  messageHistoryCallback // optional, called when generation finishes
+);
+```
 
-- [`onDownloadProgressCallback`](../../06-api-reference/classes/LLMModule.md#ondownloadprogresscallback) - Callback to track download progress.
+The model config object contains `modelSource`, `tokenizerSource`, `tokenizerConfigSource`, and optional `capabilities`. Pass one of the built-in constants (e.g. `LLAMA3_2_3B`) or construct it manually.
 
-This method returns a promise, which can resolve to an error or void.
+This method returns a promise resolving to an `LLMModule` instance.
 
 For more information on loading resources, take a look at [loading models](../../01-fundamentals/02-loading-models.md) page.
 
 ## Listening for download progress
 
-To subscribe to the download progress event, you can pass the [`onDownloadProgressCallback`](../../06-api-reference/classes/LLMModule.md#ondownloadprogresscallback) function to the [`load`](../../06-api-reference/classes/LLMModule.md#load) method. This function is called whenever the download progress changes.
+To subscribe to the download progress event, you can pass the `onDownloadProgress` callback as the second argument to [`fromModelName`](../../06-api-reference/classes/LLMModule.md#frommodelname). This function is called whenever the download progress changes.
 
 ## Running the model
 
@@ -116,25 +111,26 @@ To configure model (i.e. change system prompt, load initial conversation history
 
 ## Vision-Language Models (VLM)
 
-Some models support multimodal input — text and images together. To use them, pass `capabilities` in the model object when calling [`load`](../../06-api-reference/classes/LLMModule.md#load):
+Some models support multimodal input — text and images together. To use them, pass `capabilities` in the model object when calling [`fromModelName`](../../06-api-reference/classes/LLMModule.md#frommodelname):
 
 ```typescript
 import { LLMModule, LFM2_VL_1_6B_QUANTIZED } from 'react-native-executorch';
 
-const llm = new LLMModule({
-  tokenCallback: (token) => console.log(token),
-});
-
-await llm.load(LFM2_VL_1_6B_QUANTIZED);
+const llm = await LLMModule.fromModelName(
+  LFM2_VL_1_6B_QUANTIZED,
+  undefined,
+  (token) => console.log(token)
+);
 ```
 
 The `capabilities` field is already set on the model constant. You can also construct the model object explicitly:
 
 ```typescript
-await llm.load({
-  modelSource: '...',
-  tokenizerSource: '...',
-  tokenizerConfigSource: '...',
+const llm = await LLMModule.fromModelName({
+  modelName: 'lfm2.5-vl-1.6b-quantized',
+  modelSource: require('./path/to/model.pte'),
+  tokenizerSource: require('./path/to/tokenizer.json'),
+  tokenizerConfigSource: require('./path/to/tokenizer_config.json'),
   capabilities: ['vision'],
 });
 ```
@@ -161,6 +157,27 @@ const chat: Message[] = [
 const response = await llm.generate(chat);
 ```
 
+## Using a custom model
+
+Use [`fromCustomModel`](../../06-api-reference/classes/LLMModule.md#fromcustommodel) to load your own exported LLM instead of a built-in preset:
+
+```typescript
+import { LLMModule } from 'react-native-executorch';
+
+const llm = await LLMModule.fromCustomModel(
+  'https://example.com/model.pte',
+  'https://example.com/tokenizer.json',
+  'https://example.com/tokenizer_config.json',
+  (progress) => console.log(progress),
+  (token) => console.log(token),
+  (messages) => console.log(messages)
+);
+```
+
+### Required model contract
+
+The `.pte` model binary must be exported following the [ExecuTorch LLM export process](https://docs.pytorch.org/executorch/1.1/llm/export-llm.html). The native runner expects the standard ExecuTorch text-generation interface — KV-cache management, prefill/decode phases, and logit sampling are all handled by the runtime.
+
 ## Deleting the model from memory
 
 To delete the model from memory, you can use the [`delete`](../../06-api-reference/classes/LLMModule.md#delete) method.

docs/docs/04-typescript-api/01-natural-language-processing/SpeechToTextModule.md

@@ -14,10 +14,12 @@ TypeScript API implementation of the [useSpeechToText](../../03-hooks/01-natural
 ```typescript
 import { SpeechToTextModule, WHISPER_TINY_EN } from 'react-native-executorch';
 
-const model = new SpeechToTextModule();
-await model.load(WHISPER_TINY_EN, (progress) => {
-  console.log(progress);
-});
+const model = await SpeechToTextModule.fromModelName(
+  WHISPER_TINY_EN,
+  (progress) => {
+    console.log(progress);
+  }
+);
 
 // Standard transcription (returns string)
 const text = await model.transcribe(waveform);
@@ -40,18 +42,17 @@ All methods of `SpeechToTextModule` are explained in details here: [`SpeechToTex
 
 ## Loading the model
 
-Create an instance of [`SpeechToTextModule`](../../06-api-reference/classes/SpeechToTextModule.md) and use the [`load`](../../06-api-reference/classes/SpeechToTextModule.md#load) method. It accepts an object with the following fields:
-
-- [`model`](../../06-api-reference/classes/SpeechToTextModule.md#model) - Object containing:
-  - [`isMultilingual`](../../06-api-reference/interfaces/SpeechToTextModelConfig.md#ismultilingual) - Flag indicating if model is multilingual.
+Use the static [`fromModelName`](../../06-api-reference/classes/SpeechToTextModule.md#frommodelname) factory method. It accepts an object with the following fields:
 
-  - [`modelSource`](../../06-api-reference/interfaces/SpeechToTextModelConfig.md#modelsource) - The location of the used model (bundled encoder + decoder functionality).
+- [`isMultilingual`](../../06-api-reference/interfaces/SpeechToTextModelConfig.md#ismultilingual) - Flag indicating if model is multilingual.
+- [`modelSource`](../../06-api-reference/interfaces/SpeechToTextModelConfig.md#modelsource) - The location of the used model (bundled encoder + decoder functionality).
+- [`tokenizerSource`](../../06-api-reference/interfaces/SpeechToTextModelConfig.md#tokenizersource) - The location of the used tokenizer.
 
-  - [`tokenizerSource`](../../06-api-reference/interfaces/SpeechToTextModelConfig.md#tokenizersource) - The location of the used tokenizer.
+And an optional second argument:
 
-- [`onDownloadProgressCallback`](../../06-api-reference/classes/SpeechToTextModule.md#ondownloadprogresscallback) - Callback to track download progress.
+- `onDownloadProgress` - Callback to track download progress.
 
-This method returns a promise, which can resolve to an error or void.
+This method returns a promise resolving to a `SpeechToTextModule` instance.
 
 For more information on loading resources, take a look at [loading models](../../01-fundamentals/02-loading-models.md) page.
 
@@ -66,10 +67,12 @@ If you aim to obtain a transcription in other languages than English, use the mu
 ```typescript
 import { SpeechToTextModule, WHISPER_TINY } from 'react-native-executorch';
 
-const model = new SpeechToTextModule();
-await model.load(WHISPER_TINY, (progress) => {
-  console.log(progress);
-});
+const model = await SpeechToTextModule.fromModelName(
+  WHISPER_TINY,
+  (progress) => {
+    console.log(progress);
+  }
+);
 
 const transcription = await model.transcribe(spanishAudio, { language: 'es' });
 ```
@@ -121,10 +124,12 @@ import * as FileSystem from 'expo-file-system';
 
 const transcribeAudio = async () => {
   // Initialize with the model config
-  const model = new SpeechToTextModule();
-  await model.load(WHISPER_TINY_EN, (progress) => {
-    console.log(progress);
-  });
+  const model = await SpeechToTextModule.fromModelName(
+    WHISPER_TINY_EN,
+    (progress) => {
+      console.log(progress);
+    }
+  );
 
   // Download the audio file
   const { uri } = await FileSystem.downloadAsync(
@@ -163,10 +168,12 @@ import { SpeechToTextModule, WHISPER_TINY_EN } from 'react-native-executorch';
 import { AudioManager, AudioRecorder } from 'react-native-audio-api';
 
 // Load the model
-const model = new SpeechToTextModule();
-await model.load(WHISPER_TINY_EN, (progress) => {
-  console.log(progress);
-});
+const model = await SpeechToTextModule.fromModelName(
+  WHISPER_TINY_EN,
+  (progress) => {
+    console.log(progress);
+  }
+);
 
 // Configure audio session
 AudioManager.setAudioSessionOptions({

docs/docs/04-typescript-api/01-natural-language-processing/TextEmbeddingsModule.md

@@ -17,11 +17,9 @@ import {
   ALL_MINILM_L6_V2,
 } from 'react-native-executorch';
 
-// Creating an instance
-const textEmbeddingsModule = new TextEmbeddingsModule();
-
-// Loading the model
-await textEmbeddingsModule.load(ALL_MINILM_L6_V2);
+// Creating an instance and loading the model
+const textEmbeddingsModule =
+  await TextEmbeddingsModule.fromModelName(ALL_MINILM_L6_V2);
 
 // Running the model
 const embedding = await textEmbeddingsModule.forward('Hello World!');
@@ -33,15 +31,12 @@ All methods of `TextEmbeddingsModule` are explained in details here: [`TextEmbed
 
 ## Loading the model
 
-To load the model, use the [`load`](../../06-api-reference/classes/TextEmbeddingsModule.md#load) method. It accepts an object:
-
-- [`model`](../../06-api-reference/classes/TextEmbeddingsModule.md#model) - Object containing:
-  - [`modelSource`](../../06-api-reference/classes/TextEmbeddingsModule.md#modelsource) - Location of the used model.
-  - [`tokenizerSource`](../../06-api-reference/classes/TextEmbeddingsModule.md#tokenizersource) - Location of the used tokenizer.
+Use the static [`fromModelName`](../../06-api-reference/classes/TextEmbeddingsModule.md#frommodelname) factory method. It accepts a model config object (e.g. `ALL_MINILM_L6_V2`) containing:
 
-- [`onDownloadProgressCallback`](../../06-api-reference/classes/TextEmbeddingsModule.md#ondownloadprogresscallback) - Callback to track download progress.
+- [`modelSource`](../../06-api-reference/classes/TextEmbeddingsModule.md#modelsource) - Location of the used model.
+- [`tokenizerSource`](../../06-api-reference/classes/TextEmbeddingsModule.md#tokenizersource) - Location of the used tokenizer.
 
-This method returns a promise, which can resolve to an error or void.
+And an optional `onDownloadProgress` callback. It returns a promise resolving to a `TextEmbeddingsModule` instance.
 
 For more information on loading resources, take a look at [loading models](../../01-fundamentals/02-loading-models.md) page.
 

docs/docs/04-typescript-api/01-natural-language-processing/TextToSpeechModule.md

@@ -19,15 +19,9 @@ import {
   KOKORO_VOICE_AF_HEART,
 } from 'react-native-executorch';
 
-const model = new TextToSpeechModule();
-await model.load(
-  {
-    model: KOKORO_MEDIUM,
-    voice: KOKORO_VOICE_AF_HEART,
-  },
-  (progress) => {
-    console.log(progress);
-  }
+const model = await TextToSpeechModule.fromModelName(
+  { model: KOKORO_MEDIUM, voice: KOKORO_VOICE_AF_HEART },
+  (progress) => console.log(progress)
 );
 
 await model.forward(text, 1.0);
@@ -39,15 +33,15 @@ All methods of `TextToSpeechModule` are explained in details here: [`TextToSpeec
 
 ## Loading the model
 
-To initialize the module, create an instance and call the [`load`](../../06-api-reference/classes/TextToSpeechModule.md#load) method with the following parameters:
+Use the static [`fromModelName`](../../06-api-reference/classes/TextToSpeechModule.md#frommodelname) factory method with the following parameters:
 
-- [`config`](../../06-api-reference/classes/TextToSpeechModule.md#config) - Object containing:
-  - [`model`](../../06-api-reference/interfaces/TextToSpeechConfig.md#model) - Model configuration.
-  - [`voice`](../../06-api-reference/interfaces/TextToSpeechConfig.md#voice) - Voice configuration.
+- [`config`](../../06-api-reference/interfaces/TextToSpeechConfig.md) - Object containing:
+  - [`model`](../../06-api-reference/interfaces/TextToSpeechConfig.md#model) - Model configuration (e.g. `KOKORO_MEDIUM`).
+  - [`voice`](../../06-api-reference/interfaces/TextToSpeechConfig.md#voice) - Voice configuration (e.g. `KOKORO_VOICE_AF_HEART`).
 
-- [`onDownloadProgressCallback`](../../06-api-reference/classes/TextToSpeechModule.md#ondownloadprogresscallback) - Callback to track download progress.
+- [`onDownloadProgress`](../../06-api-reference/classes/TextToSpeechModule.md#frommodelname) - Optional callback to track download progress (value between 0 and 1).
 
-This method returns a promise that resolves once the assets are downloaded and loaded into memory.
+This method returns a promise that resolves to a `TextToSpeechModule` instance once the assets are downloaded and loaded into memory.
 
 For more information on resource sources, see [loading models](../../01-fundamentals/02-loading-models.md).
 
@@ -83,15 +77,13 @@ import {
 } from 'react-native-executorch';
 import { AudioContext } from 'react-native-audio-api';
 
-const tts = new TextToSpeechModule();
+const tts = await TextToSpeechModule.fromModelName({
+  model: KOKORO_MEDIUM,
+  voice: KOKORO_VOICE_AF_HEART,
+});
 const audioContext = new AudioContext({ sampleRate: 24000 });
 
 try {
-  await tts.load({
-    model: KOKORO_MEDIUM,
-    voice: KOKORO_VOICE_AF_HEART,
-  });
-
   const waveform = await tts.forward('Hello from ExecuTorch!', 1.0);
 
   // Create audio buffer and play
@@ -117,11 +109,12 @@ import {
 } from 'react-native-executorch';
 import { AudioContext } from 'react-native-audio-api';
 
-const tts = new TextToSpeechModule();
+const tts = await TextToSpeechModule.fromModelName({
+  model: KOKORO_MEDIUM,
+  voice: KOKORO_VOICE_AF_HEART,
+});
 const audioContext = new AudioContext({ sampleRate: 24000 });
 
-await tts.load({ model: KOKORO_MEDIUM, voice: KOKORO_VOICE_AF_HEART });
-
 try {
   for await (const chunk of tts.stream({
     text: 'This is a streaming test, with a sample input.',
@@ -155,9 +148,7 @@ import {
   KOKORO_VOICE_AF_HEART,
 } from 'react-native-executorch';
 
-const tts = new TextToSpeechModule();
-
-await tts.load({
+const tts = await TextToSpeechModule.fromModelName({
   model: KOKORO_MEDIUM,
   voice: KOKORO_VOICE_AF_HEART,
 });

docs/docs/04-typescript-api/01-natural-language-processing/VADModule.md

@@ -14,10 +14,9 @@ TypeScript API implementation of the [useVAD](../../03-hooks/01-natural-language
 ```typescript
 import { VADModule, FSMN_VAD } from 'react-native-executorch';
 
-const model = new VADModule();
-await model.load(FSMN_VAD, (progress) => {
-  console.log(progress);
-});
+const model = await VADModule.fromModelName(FSMN_VAD, (progress) =>
+  console.log(progress)
+);
 
 await model.forward(waveform);
 ```
@@ -28,14 +27,15 @@ All methods of `VADModule` are explained in details here: [`VADModule` API Refer
 
 ## Loading the model
 
-To initialize the module, create an instance and call the [`load`](../../06-api-reference/classes/VADModule.md#load) method with the following parameters:
+To create a ready-to-use instance, call the static [`fromModelName`](../../06-api-reference/classes/VADModule.md#frommodelname) factory with the following parameters:
 
-- [`model`](../../06-api-reference/classes/VADModule.md#model) - Object containing:
-  - [`modelSource`](../../06-api-reference/classes/VADModule.md#modelsource) - Location of the used model.
+- `namedSources` - Object containing:
+  - `modelName` - Model name identifier.
+  - `modelSource` - Location of the model binary.
 
-- [`onDownloadProgressCallback`](../../06-api-reference/classes/VADModule.md#ondownloadprogresscallback) - Callback to track download progress.
+- `onDownloadProgress` - Optional callback to track download progress (value between 0 and 1).
 
-This method returns a promise, which can resolve to an error or void.
+The factory returns a promise that resolves to a loaded `VADModule` instance.
 
 For more information on loading resources, take a look at [loading models](../../01-fundamentals/02-loading-models.md) page.