Add a complete bare React Native example app demonstrating LLM integration with react-native-executorch.

## App: llm_bare

### Features
- Simple chat UI for LLM interactions
- Model loading with progress indicator
- Real-time streaming responses
- Send/stop generation controls
- Auto-scrolling message history

### Stack
- **Framework**: React Native 0.81.5 (bare/CLI)
- **LLM**: Uses LLAMA3_2_1B_SPINQUANT model
- **Adapter**: @rn-executorch/bare-adapter
- **Dependencies**: Minimal deps, only essential packages

### Platform Configuration

#### iOS
- Bridging header for RNBackgroundDownloader
- Background URL session handling in AppDelegate
- Background modes (fetch, processing)
- Xcode project configuration

#### Android
- Required permissions for background downloads
- Foreground service configuration
- Network state access
- Proper manifest configuration

### Infrastructure
- Babel configuration for export namespace transform

This serves as a reference implementation for using react-native-executorch in bare React Native environments (non-Expo).

…r better control

…oads

…er-adapters

…tion

…ions

…r for better error handling

Add explicit resetAdapter() method to ResourceFetcher class for cleaner API.
- Add resetAdapter() static method that sets adapter to null
- Update cleanupExecutorch() to use resetAdapter() instead of type assertion hack
- Update error message to reference new package names (@react-native-executorch/*)

This provides a cleaner, type-safe way to reset the adapter without
requiring "null as unknown as ResourceFetcherAdapter" type assertion.

…ecking and cleaning

…er-adapters

…el (software-mansion#734)

## Description

Currently, there is no other way to set configuration in `LLMModule`
other than load model first, and then call `configure` method. This PR
make it possible to configure parameters before loading the actual
model.

### Introduces a breaking change?

- [ ] Yes
- [X] No

### Type of change

- [ ] Bug fix (change which fixes an issue)
- [ ] New feature (change which adds functionality)
- [ ] Documentation update (improves or adds clarity to existing
documentation)
- [X] Other (chores, tests, code style improvements etc.)

### Tested on

- [x] iOS
- [ ] Android

### Testing instructions

Try to run configure on hook returned by `useLLM` and check that
everything works.

For simplicity, I present the example way how to test it inside our
library:
* Create the following file in `apps/llm/app/my_test/index.tsx`:

```typescript
import { useIsFocused } from '@react-navigation/native';
import React, { useEffect, useState, useRef } from 'react';
import {
  View,
  Text,
  TextInput,
  TouchableOpacity,
  FlatList,
  StyleSheet,
  ActivityIndicator,
  KeyboardAvoidingView,
  Platform,
  SafeAreaView,
} from 'react-native';
import { LLMModule, LLAMA3_2_1B_QLORA } from 'react-native-executorch';

// Define message type for UI
type Message = {
  role: 'user' | 'assistant' | 'system';
  content: string;
};

export default function VoiceChatScreenWrapper() {
  const isFocused = useIsFocused();

  return isFocused ? <LlamaChat /> : null;
}


const LlamaChat = () => {
  const [messages, setMessages] = useState<Message[]>([]);
  const [input, setInput] = useState('');
  const [isModelReady, setIsModelReady] = useState(false);
  const [loadingProgress, setLoadingProgress] = useState(0);
  const [isGenerating, setIsGenerating] = useState(false);

  // Use a ref to keep the LLM instance stable across renders
  const llmRef = useRef<LLMModule | null>(null);

  useEffect(() => {
    // 1. Initialize the LLM Module
    llmRef.current = new LLMModule({
      // Update state whenever history changes (covers both user and bot messages)
      messageHistoryCallback: (updatedMessages) => {
        // We cast this to our Message type (assuming the library returns compatible format)
        setMessages(updatedMessages as Message[]);
      },
      // Optional: Use tokenCallback if you want to trigger haptics or very fine-grained updates
      tokenCallback: (token) => {
        // console.log('New token:', token);
      },
    });

    // 2. Load the model
    const loadModel = async () => {
      try {
        await llmRef.current?.load(LLAMA3_2_1B_QLORA, (progress) => {
          setLoadingProgress(progress);
        });
        setIsModelReady(true);
      } catch (error) {
        console.error('Failed to load model:', error);
      }
    };

    loadModel();

    llmRef.current?.configure({chatConfig: {systemPrompt: "You are extremely enthusiastic chat assistant that is ecstatic about chatting with me."}});

    // 3. Cleanup: Delete model from memory when component unmounts
    return () => {
      console.log('Cleaning up LLM...');
      llmRef.current?.delete();
    };
  }, []);

  const handleSend = async () => {
    if (!input.trim() || !isModelReady || isGenerating) return;

    const userText = input;
    setInput(''); // Clear input immediately
    setIsGenerating(true);

    try {
      // sendMessage automatically updates the history via the callback defined in useEffect
      await llmRef.current?.sendMessage(userText);
    } catch (error) {
      console.error('Error generating response:', error);
    } finally {
      setIsGenerating(false);
    }
  };

  const handleStop = () => {
    llmRef.current?.interrupt();
    setIsGenerating(false);
  };

  // --- Render Helpers ---

  if (!isModelReady) {
    return (
      <View style={styles.centerContainer}>
        <ActivityIndicator size="large" color="#007AFF" />
        <Text style={styles.loadingText}>
          Loading Model... {(loadingProgress * 100).toFixed(0)}%
        </Text>
      </View>
    );
  }

  return (
    <SafeAreaView style={styles.container}>
      <KeyboardAvoidingView
        behavior={Platform.OS === 'ios' ? 'padding' : undefined}
        style={styles.keyboardContainer}
      >
        <FlatList
          data={messages}
          keyExtractor={(_, index) => index.toString()}
          contentContainerStyle={styles.listContent}
          renderItem={({ item }) => (
            <View
              style={[
                styles.bubble,
                item.role === 'user' ? styles.userBubble : styles.botBubble,
              ]}
            >
              <Text style={item.role === 'user' ? styles.userText : styles.botText}>
                {item.content}
              </Text>
            </View>
          )}
        />

        <View style={styles.inputContainer}>
          <TextInput
            style={styles.input}
            placeholder="Ask Llama..."
            value={input}
            onChangeText={setInput}
            editable={!isGenerating}
          />
          
          {isGenerating ? (
            <TouchableOpacity onPress={handleStop} style={styles.stopButton}>
              <Text style={styles.buttonText}>Stop</Text>
            </TouchableOpacity>
          ) : (
            <TouchableOpacity onPress={handleSend} style={styles.sendButton}>
              <Text style={styles.buttonText}>Send</Text>
            </TouchableOpacity>
          )}
        </View>
      </KeyboardAvoidingView>
    </SafeAreaView>
  );
};

const styles = StyleSheet.create({
  container: { flex: 1, backgroundColor: '#F5F5F5' },
  centerContainer: { flex: 1, justifyContent: 'center', alignItems: 'center' },
  loadingText: { marginTop: 10, fontSize: 16, color: 'software-mansion#333' },
  keyboardContainer: { flex: 1 },
  listContent: { padding: 16 },
  bubble: {
    maxWidth: '80%',
    padding: 12,
    borderRadius: 16,
    marginBottom: 10,
  },
  userBubble: {
    alignSelf: 'flex-end',
    backgroundColor: '#007AFF',
    borderBottomRightRadius: 2,
  },
  botBubble: {
    alignSelf: 'flex-start',
    backgroundColor: '#E5E5EA',
    borderBottomLeftRadius: 2,
  },
  userText: { color: '#FFF', fontSize: 16 },
  botText: { color: '#000', fontSize: 16 },
  inputContainer: {
    flexDirection: 'row',
    padding: 10,
    borderTopWidth: 1,
    borderColor: '#DDD',
    backgroundColor: '#FFF',
  },
  input: {
    flex: 1,
    backgroundColor: '#F0F0F0',
    borderRadius: 20,
    paddingHorizontal: 16,
    paddingVertical: 10,
    fontSize: 16,
    marginRight: 10,
  },
  sendButton: {
    backgroundColor: '#007AFF',
    justifyContent: 'center',
    alignItems: 'center',
    paddingHorizontal: 20,
    borderRadius: 20,
  },
  stopButton: {
    backgroundColor: '#FF3B30',
    justifyContent: 'center',
    alignItems: 'center',
    paddingHorizontal: 20,
    borderRadius: 20,
  },
  buttonText: { color: '#FFF', fontWeight: '600' },
});
```
* Add the following in `apps/llm/app/_layout.txs`:
```
+        <Drawer.Screen
+          name="my_test/index"
+          options={{
+            drawerLabel: 'Llama Chat',
+            title: 'Llama Chat',
+            headerTitleStyle: { color: ColorPalette.primary },
+          }}
+        />
```

* Add the following in `apps/llm/app/index.tsx`:

```
+
+          <TouchableOpacity
+          style={styles.button}
+          onPress={() => router.navigate('my_test/')}
+        >
+          <Text style={styles.buttonText}>LLama chat</Text>
+        </TouchableOpacity>
```

Run llm app and ask about anything. Generation config should work
correctly, and now responses of the LLM should be super ecstatic. Now,
move this part:

```typescript
    llmRef.current?.configure({chatConfig: {systemPrompt: "You are extremely enthusiastic chat assistant that is ecstatic about chatting with me."}});
```

before loading the model and check if everything works correct.

### Screenshots

<!-- Add screenshots here, if applicable -->

### Related issues

<!-- Link related issues here using #issue-number -->

### Checklist

- [x] I have performed a self-review of my code
- [x] I have commented my code, particularly in hard-to-understand areas
- [ ] I have updated the documentation accordingly
- [x] My changes generate no new warnings

### Additional notes

<!-- Include any additional information, assumptions, or context that
reviewers might need to understand this PR. -->

… param name (software-mansion#801)

## Description

This PR changes the param name of from `resize` to `resizeToInput` in
image segmentation APIs. It also defaults to true now, as the
performance impact is acceptable.

### Introduces a breaking change?

- [x] Yes
- [ ] No

### Type of change

- [ ] Bug fix (change which fixes an issue)
- [ ] New feature (change which adds functionality)
- [ ] Documentation update (improves or adds clarity to existing
documentation)
- [x] Other (chores, tests, code style improvements etc.)

### Tested on

- [ ] iOS
- [ ] Android

### Testing instructions

<!-- Provide step-by-step instructions on how to test your changes.
Include setup details if necessary. -->

### Screenshots

<!-- Add screenshots here, if applicable -->

### Related issues

<!-- Link related issues here using #issue-number -->

### Checklist

- [ ] I have performed a self-review of my code
- [ ] I have commented my code, particularly in hard-to-understand areas
- [ ] I have updated the documentation accordingly
- [ ] My changes generate no new warnings

### Additional notes

<!-- Include any additional information, assumptions, or context that
reviewers might need to understand this PR. -->

---------

Co-authored-by: Mateusz Sluszniak <56299341+msluszniak@users.noreply.github.com>

## Description

This PR changes binaries to include new tokenizer functionalities.

Added: 
- Wordpiece model and decoder
- Bert and Roberta tokenization is supported 
- Padding and truncation from tokenizer.json is now respected 



### Introduces a breaking change?

- [ ] Yes
- [x] No

### Type of change

- [x] Bug fix (change which fixes an issue)
- [ ] New feature (change which adds functionality)
- [ ] Documentation update (improves or adds clarity to existing
documentation)
- [ ] Other (chores, tests, code style improvements etc.)

### Tested on

- [x] iOS
- [x] Android

### Testing instructions
Run the test suites. 
Run all apps that use tokenizers and verify they load and produce proper
output (LLM, S2T, T2I, Embeddings etc.)

### Checklist

- [x] I have performed a self-review of my code

### Additional notes
Running the tests can yield some issues. Couldn't get to why they happen.
Calling failing functions in example apps yields proper results.
Probably some issue with test environment. We decided to not hold this
PR due to failing TC's and investigate them later on.

<!-- Provide a concise and descriptive summary of the changes
implemented in this PR. -->

- [x] Yes
- [ ] No
This PR introduces breaking change as now the return type from
`transcribe` and `stream` methods are based on `TranscriptionResult`
type. Also now there is no commited / nonCommited properties of hook.
`stream` now is async generator.

- [ ] Bug fix (change which fixes an issue)
- [x] New feature (change which adds functionality)
- [ ] Documentation update (improves or adds clarity to existing
documentation)
- [ ] Other (chores, tests, code style improvements etc.)

- [x] iOS
- [x] Android

* Run demo app in `apps/speech` and run transcription for both time
stamping and regular mode (both from url and from real time audio to
test both `transcribe` and `stream` methods).
* Run voice chat in `apps/llm` to check if transcription appears. *NOTE*
This example seems to be a bit buggy.
* You need to run this on **android device** since this PR also fixes
`Speech to Text` demo app in case of using physical android device.
Earlier, required permissions for microphone weren't granted and the
example effectively didn't work.
* Check that documentation for modified sections is updated and that api
reference is correct as well.
* Run tests and check that they compile and work as previously.

<!-- Add screenshots here, if applicable -->

<!-- Link related issues here using #issue-number -->

- [x] I have performed a self-review of my code
- [x] I have commented my code, particularly in hard-to-understand areas
- [x] I have updated the documentation accordingly
- [x] My changes generate no new warnings

<!-- Include any additional information, assumptions, or context that
reviewers might need to understand this PR. -->