feat: pre-commit code formatting

.github/ISSUE_TEMPLATE/bug-report.yml

@@ -163,4 +163,4 @@ body:
       options:
         - 'Yes'
     validations:
-      required: true
+      required: true

.github/ISSUE_TEMPLATE/feature-request.yml

@@ -47,4 +47,4 @@ body:
       description: >
         Add any other relevant context, code examples, or screenshots that should be considered.
     validations:
-      required: false
+      required: false

.github/pull_request_template.md

@@ -1,30 +1,38 @@
 ## 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)
 - [ ] Documentation update (improves or adds clarity to existing documentation)
 
 ### 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. -->
+
+<!-- Include any additional information, assumptions, or context that reviewers might need to understand this PR. -->

.github/workflows/build-ios-llama-example.yml

@@ -17,12 +17,12 @@ on:
 jobs:
   build:
     if: github.repository == 'software-mansion/react-native-executorch'
-    name: "Example app iOS build check"
+    name: 'Example app iOS build check'
     runs-on: macos-latest
     steps:
       - name: Check out Git repository
         uses: actions/checkout@v4
-        
+
       - name: Install node dependencies
         working-directory: examples/llama
         run: yarn
@@ -42,4 +42,3 @@ jobs:
             -destination 'platform=iOS Simulator,name=iPhone 16 Pro' \
             build \
             CODE_SIGNING_ALLOWED=NO | xcbeautify
-

.github/workflows/docs-build-check.yml

@@ -31,4 +31,4 @@ jobs:
         run: mkdir -p .yarn/cache && yarn
       - name: Generate docs
         working-directory: ${{ env.WORKING_DIRECTORY }}
-        run: yarn build
+        run: yarn build

.watchmanconfig

@@ -1 +1 @@
-{}
+{}

.yarnrc.yml

@@ -3,8 +3,8 @@ nmHoistingLimits: workspaces
 
 plugins:
   - path: .yarn/plugins/@yarnpkg/plugin-interactive-tools.cjs
-    spec: "@yarnpkg/plugin-interactive-tools"
+    spec: '@yarnpkg/plugin-interactive-tools'
   - path: .yarn/plugins/@yarnpkg/plugin-workspace-tools.cjs
-    spec: "@yarnpkg/plugin-workspace-tools"
+    spec: '@yarnpkg/plugin-workspace-tools'
 
 yarnPath: .yarn/releases/yarn-3.6.1.cjs

android/src/main/java/com/swmansion/rnexecutorch/Classification.kt

@@ -1,32 +1,36 @@
 package com.swmansion.rnexecutorch
 
 import android.util.Log
+import com.facebook.react.bridge.Arguments
 import com.facebook.react.bridge.Promise
 import com.facebook.react.bridge.ReactApplicationContext
+import com.facebook.react.bridge.WritableMap
 import com.swmansion.rnexecutorch.models.classification.ClassificationModel
 import com.swmansion.rnexecutorch.utils.ETError
 import com.swmansion.rnexecutorch.utils.ImageProcessor
 import org.opencv.android.OpenCVLoader
-import com.facebook.react.bridge.Arguments
-import com.facebook.react.bridge.WritableMap
-
-class Classification(reactContext: ReactApplicationContext) :
-  NativeClassificationSpec(reactContext) {
 
+class Classification(
+  reactContext: ReactApplicationContext,
+) : NativeClassificationSpec(reactContext) {
   private lateinit var classificationModel: ClassificationModel
 
   companion object {
     const val NAME = "Classification"
+
     init {
-      if(!OpenCVLoader.initLocal()){
+      if (!OpenCVLoader.initLocal()) {
         Log.d("rn_executorch", "OpenCV not loaded")
       } else {
         Log.d("rn_executorch", "OpenCV loaded")
       }
     }
   }
 
-  override fun loadModule(modelSource: String, promise: Promise) {
+  override fun loadModule(
+    modelSource: String,
+    promise: Promise,
+  ) {
     try {
       classificationModel = ClassificationModel(reactApplicationContext)
       classificationModel.loadModel(modelSource)
@@ -36,24 +40,25 @@ class Classification(reactContext: ReactApplicationContext) :
     }
   }
 
-  override fun forward(input: String, promise: Promise) {
+  override fun forward(
+    input: String,
+    promise: Promise,
+  ) {
     try {
       val image = ImageProcessor.readImage(input)
       val output = classificationModel.runModel(image)
 
       val writableMap: WritableMap = Arguments.createMap()
-      
+
       for ((key, value) in output) {
         writableMap.putDouble(key, value.toDouble())
       }
 
       promise.resolve(writableMap)
-    }catch(e: Exception){
+    } catch (e: Exception) {
       promise.reject(e.message!!, e.message)
     }
   }
 
-  override fun getName(): String {
-    return NAME
-  }
+  override fun getName(): String = NAME
 }

android/src/main/java/com/swmansion/rnexecutorch/ETModule.kt

@@ -11,19 +11,26 @@ import org.pytorch.executorch.EValue
 import org.pytorch.executorch.Module
 import java.net.URL
 
-class ETModule(reactContext: ReactApplicationContext) : NativeETModuleSpec(reactContext) {
+class ETModule(
+  reactContext: ReactApplicationContext,
+) : NativeETModuleSpec(reactContext) {
   private lateinit var module: Module
-  private var reactApplicationContext = reactContext;
-  override fun getName(): String {
-    return NAME
-  }
+  private var reactApplicationContext = reactContext
+
+  override fun getName(): String = NAME
 
-  override fun loadModule(modelSource: String, promise: Promise) {
+  override fun loadModule(
+    modelSource: String,
+    promise: Promise,
+  ) {
     module = Module.load(URL(modelSource).path)
     promise.resolve(0)
   }
 
-  override fun loadMethod(methodName: String, promise: Promise) {
+  override fun loadMethod(
+    methodName: String,
+    promise: Promise,
+  ) {
     val result = module.loadMethod(methodName)
     if (result != 0) {
       promise.reject("Method loading failed", result.toString())
@@ -37,35 +44,37 @@ class ETModule(reactContext: ReactApplicationContext) : NativeETModuleSpec(react
     inputs: ReadableArray,
     shapes: ReadableArray,
     inputTypes: ReadableArray,
-    promise: Promise
+    promise: Promise,
   ) {
     val inputEValues = ArrayList<EValue>()
     try {
       for (i in 0 until inputs.size()) {
-        val currentInput = inputs.getArray(i)
-          ?: throw Exception(ETError.InvalidArgument.code.toString())
-        val currentShape = shapes.getArray(i)
-          ?: throw Exception(ETError.InvalidArgument.code.toString())
+        val currentInput =
+          inputs.getArray(i)
+            ?: throw Exception(ETError.InvalidArgument.code.toString())
+        val currentShape =
+          shapes.getArray(i)
+            ?: throw Exception(ETError.InvalidArgument.code.toString())
         val currentInputType = inputTypes.getInt(i)
 
-        val currentEValue = TensorUtils.getExecutorchInput(
-          currentInput,
-          ArrayUtils.createLongArray(currentShape),
-          currentInputType
-        )
+        val currentEValue =
+          TensorUtils.getExecutorchInput(
+            currentInput,
+            ArrayUtils.createLongArray(currentShape),
+            currentInputType,
+          )
 
         inputEValues.add(currentEValue)
       }
 
-      val forwardOutputs = module.forward(*inputEValues.toTypedArray());
+      val forwardOutputs = module.forward(*inputEValues.toTypedArray())
       val outputArray = Arguments.createArray()
 
       for (output in forwardOutputs) {
         val arr = ArrayUtils.createReadableArrayFromTensor(output.toTensor())
         outputArray.pushArray(arr)
       }
       promise.resolve(outputArray)
-
     } catch (e: IllegalArgumentException) {
       // The error is thrown when transformation to Tensor fails
       promise.reject("Forward Failed Execution", ETError.InvalidArgument.code.toString())

android/src/main/java/com/swmansion/rnexecutorch/LLM.kt

@@ -4,23 +4,23 @@ import android.util.Log
 import com.facebook.react.bridge.Promise
 import com.facebook.react.bridge.ReactApplicationContext
 import com.facebook.react.bridge.ReadableArray
+import com.swmansion.rnexecutorch.utils.ArrayUtils
 import com.swmansion.rnexecutorch.utils.llms.ChatRole
 import com.swmansion.rnexecutorch.utils.llms.ConversationManager
 import com.swmansion.rnexecutorch.utils.llms.END_OF_TEXT_TOKEN
 import org.pytorch.executorch.LlamaCallback
 import org.pytorch.executorch.LlamaModule
-import com.swmansion.rnexecutorch.utils.ArrayUtils
 import java.net.URL
 
-class LLM(reactContext: ReactApplicationContext) : NativeLLMSpec(reactContext), LlamaCallback {
-
+class LLM(
+  reactContext: ReactApplicationContext,
+) : NativeLLMSpec(reactContext),
+  LlamaCallback {
   private var llamaModule: LlamaModule? = null
   private var tempLlamaResponse = StringBuilder()
   private lateinit var conversationManager: ConversationManager
 
-  override fun getName(): String {
-    return NAME
-  }
+  override fun getName(): String = NAME
 
   override fun initialize() {
     super.initialize()
@@ -41,12 +41,15 @@ class LLM(reactContext: ReactApplicationContext) : NativeLLMSpec(reactContext),
     systemPrompt: String,
     messageHistory: ReadableArray,
     contextWindowLength: Double,
-    promise: Promise
+    promise: Promise,
   ) {
     try {
-      this.conversationManager = ConversationManager(
-        contextWindowLength.toInt(), systemPrompt, ArrayUtils.createMapArray<String>(messageHistory)
-      )
+      this.conversationManager =
+        ConversationManager(
+          contextWindowLength.toInt(),
+          systemPrompt,
+          ArrayUtils.createMapArray<String>(messageHistory),
+        )
       llamaModule = LlamaModule(1, URL(modelSource).path, URL(tokenizerSource).path, 0.7f)
       this.tempLlamaResponse.clear()
       promise.resolve("Model loaded successfully")
@@ -55,7 +58,10 @@ class LLM(reactContext: ReactApplicationContext) : NativeLLMSpec(reactContext),
     }
   }
 
-  override fun runInference(input: String, promise: Promise) {
+  override fun runInference(
+    input: String,
+    promise: Promise,
+  ) {
     this.conversationManager.addResponse(input, ChatRole.USER)
     val conversation = this.conversationManager.getConversation()
 
@@ -66,7 +72,7 @@ class LLM(reactContext: ReactApplicationContext) : NativeLLMSpec(reactContext),
       // generated sequence length is larger than specified in the JNI callback, hence we check if EOT
       // is there and if not, we append it to the output and emit the EOT token to the JS side.
       if (!this.tempLlamaResponse.endsWith(END_OF_TEXT_TOKEN)) {
-        this.onResult(END_OF_TEXT_TOKEN);
+        this.onResult(END_OF_TEXT_TOKEN)
       }
 
       // We want to add the LLM response to the conversation once all the tokens are generated.