#fixups

devtools_options.yaml

@@ -0,0 +1 @@
+extensions:

ios/Podfile

@@ -1,5 +1,6 @@
 # Uncomment this line to define a global platform for your project
-platform :ios, '12.0'
+platform :ios, '13.0'
+$iOSVersion = '13.0'
 
 # CocoaPods analytics sends network stats synchronously affecting flutter build latency.
 ENV['COCOAPODS_DISABLE_STATS'] = 'true'
@@ -30,12 +31,23 @@ flutter_ios_podfile_setup
 target 'Runner' do
   use_frameworks!
   use_modular_headers!
-
+  # https://pub.dev/packages/edge_detection
+  pod 'WeScan', :path => '.symlinks/plugins/edge_detection/ios/WeScan-3.0.0'
   flutter_install_all_ios_pods File.dirname(File.realpath(__FILE__))
 end
 
 post_install do |installer|
+  # https://pub.dev/packages/google_mlkit_face_detection
+  installer.pods_project.build_configurations.each do |config|
+    config.build_settings["EXCLUDED_ARCHS[sdk=*]"] = "armv7"
+    config.build_settings['IPHONEOS_DEPLOYMENT_TARGET'] = $iOSVersion
+  end
   installer.pods_project.targets.each do |target|
     flutter_additional_ios_build_settings(target)
+    target.build_configurations.each do |config|
+      if Gem::Version.new($iOSVersion) > Gem::Version.new(config.build_settings['IPHONEOS_DEPLOYMENT_TARGET'])
+        config.build_settings['IPHONEOS_DEPLOYMENT_TARGET'] = $iOSVersion
+      end
+    end
   end
 end

lib/routes/monetization_inline_banner_ad_ex.dart

@@ -66,7 +66,7 @@ class _MyBannerAdWidgetState extends State<MyBannerAdWidget> {
   }
 
   Future<void> _loadAd() async {
-    if (kIsOnMobile) return;
+    if (!kIsOnMobile) return;
     //! Get an AnchoredAdaptiveBannerAdSize before loading the ad.
     final AnchoredAdaptiveBannerAdSize? size =
         await AdSize.getCurrentOrientationAnchoredAdaptiveBannerAdSize(

lib/routes/networking_chatgpt_ex.dart

@@ -30,7 +30,7 @@ class _ChatGptExampleState extends ConsumerState<ChatGptExample> {
   Future<String> _askChatGpt(String prompt) async {
     final request = ChatCompleteText(
       messages: [
-        Map.of({'role': Role.user, 'content': prompt})
+        Map.of({'role': 'user', 'content': prompt})
       ],
       model: GptTurboChatModel(),
       maxToken: 500,