docs: add note about new architecture in readme and docs (#127)

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

### Type of change
- [ ] Bug fix (non-breaking change which fixes an issue)
- [ ] New feature (non-breaking change which adds functionality)
- [ ] Breaking change (fix or feature that would cause existing
functionality to not work as expected)
- [x] Documentation update (improves or adds clarity to existing
documentation)

### Tested on
- [ ] iOS
- [ ] Android

### Testing instructions
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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. -->

Author: NorbertKlockiewicz

README.md

@@ -6,6 +6,12 @@
 
 **ExecuTorch** is a novel framework created by Meta that enables running AI models on devices such as mobile phones or microcontrollers. React Native ExecuTorch bridges the gap between React Native and native platform capabilities, allowing developers to run AI models locally on mobile devices with state-of-the-art performance, without requiring deep knowledge of native code or machine learning internals.
 
+## Compatibility
+
+React Native Executorch supports only the [New React Native architecture](https://reactnative.dev/architecture/landing-page).
+
+If your app still runs on the old architecture, please consider upgrading to the New Architecture.
+
 ## Readymade models 🤖
 
 To run any AI model in ExecuTorch, you need to export it to a `.pte` format. If you're interested in experimenting with your own models, we highly encourage you to check out the [Python API](https://pypi.org/project/executorch/). If you prefer focusing on developing your React Native app, we will cover several common use cases. For more details, please refer to the documentation.
@@ -15,12 +21,12 @@ To run any AI model in ExecuTorch, you need to export it to a `.pte` format. If
 Take a look at how our library can help build you your React Native AI features in our docs:  
 https://docs.swmansion.com/react-native-executorch
 
+# 🦙 **Quickstart - Running Llama**
 
-# 🦙 **Quickstart - Running Llama**  
+**Get started with AI-powered text generation in 3 easy steps!**
 
-**Get started with AI-powered text generation in 3 easy steps!**  
+### 1️⃣ **Installation**
 
-### 1️⃣ **Installation**  
 ```bash
 # Install the package
 yarn add react-native-executorch
@@ -29,46 +35,51 @@ cd ios && pod install && cd ..
 
 ---
 
-### 2️⃣ **Setup & Initialization**  
-Add this to your component file:  
+### 2️⃣ **Setup & Initialization**
+
+Add this to your component file:
+
 ```tsx
-import { 
-  LLAMA3_2_3B_QLORA, 
+import {
+  LLAMA3_2_3B_QLORA,
   LLAMA3_2_3B_TOKENIZER,
-  useLLM 
+  useLLM,
 } from 'react-native-executorch';
 
 function MyComponent() {
   // Initialize the model 🚀
   const llama = useLLM({
     modelSource: LLAMA3_2_3B_QLORA,
-    tokenizerSource: LLAMA3_2_3B_TOKENIZER
+    tokenizerSource: LLAMA3_2_3B_TOKENIZER,
   });
   // ... rest of your component
 }
 ```
 
 ---
 
-### 3️⃣ **Run the model!**  
+### 3️⃣ **Run the model!**
+
 ```tsx
 const handleGenerate = async () => {
-  const prompt = "The meaning of life is";
-  
+  const prompt = 'The meaning of life is';
+
   // Generate text based on your desired prompt
   const response = await llama.generate(prompt);
-  console.log("Llama says:", response);
+  console.log('Llama says:', response);
 };
 ```
 
 ## Minimal supported versions
+
 The minimal supported version is 17.0 for iOS and Android 13.
 
 ## Examples 📲
 
 https://github.com/user-attachments/assets/27ab3406-c7f1-4618-a981-6c86b53547ee
 
 We currently host two example apps demonstrating use cases of our library:
+
 - examples/speech-to-text - Whisper and Moonshine models ready for transcription tasks
 - examples/computer-vision - computer vision related tasks
 - examples/llama - chat applications showcasing use of LLMs
@@ -100,10 +111,10 @@ yarn expo run:ios
 ```
 
 ### Warning
-Running LLMs requires a significant amount of RAM. If you are encountering unexpected app crashes, try to increase the amount of RAM allocated to the emulator.
 
+Running LLMs requires a significant amount of RAM. If you are encountering unexpected app crashes, try to increase the amount of RAM allocated to the emulator.
 
-## License  
+## License
 
 This library is licensed under [The MIT License](./LICENSE).
 

docs/docs/fundamentals/getting-started.md

@@ -14,6 +14,12 @@ ExecuTorch is a novel AI framework developed by Meta, designed to streamline dep
 
 React Native ExecuTorch is our way of bringing ExecuTorch into the React Native world. Our API is built to be simple, declarative, and efficient. Plus, we’ll provide a set of pre-exported models for common use cases, so you won’t have to worry about handling exports yourself. With just a few lines of JavaScript, you’ll be able to run AI models (even LLMs 👀) right on your device—keeping user data private and saving on cloud costs.
 
+## Compatibility
+
+React Native Executorch supports only the [New React Native architecture](https://reactnative.dev/architecture/landing-page).
+
+If your app still runs on the old architecture, please consider upgrading to the New Architecture.
+
 ## Installation
 
 Installation is pretty straightforward, just use your favorite package manager.