genai: Created Package & implemented LLM Config, Manager & Request

packages/genai/.gitignore

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+# Miscellaneous
+*.class
+*.log
+*.pyc
+*.swp
+.DS_Store
+.atom/
+.buildlog/
+.history
+.svn/
+migrate_working_dir/
+
+# IntelliJ related
+*.iml
+*.ipr
+*.iws
+.idea/
+
+# The .vscode folder contains launch configuration and tasks you configure in
+# VS Code which you may wish to be included in version control, so this line
+# is commented out by default.
+#.vscode/
+
+# Flutter/Dart/Pub related
+# Libraries should not include pubspec.lock, per https://dart.dev/guides/libraries/private-files#pubspeclock.
+/pubspec.lock
+**/doc/api/
+.dart_tool/
+.packages
+build/

packages/genai/CHANGELOG.md

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+## 0.0.1
+
+* TODO: Describe initial release.

packages/genai/LICENSE

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+TODO: Add your license here.

packages/genai/README.md

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+# genai package
+This Package contains all the code related to generative AI capabilities and is a foundational package that can be used in various projects

packages/genai/analysis_options.yaml

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+include: package:flutter_lints/flutter.yaml
+
+# Additional information about this file can be found at
+# https://dart.dev/guides/language/analysis-options

packages/genai/lib/genai.dart

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+library genai;
+
+/// A Calculator.
+class Calculator {
+  /// Returns [value] plus 1.
+  int addOne(int value) => value + 1;
+}

packages/genai/lib/llm_config.dart

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+import 'dart:convert';
+
+typedef LLMOutputFormatter = String? Function(Map);
+
+class LLMModelConfiguration {
+  final String configId;
+  final String configName;
+  final String configDescription;
+  final LLMModelConfigurationType configType;
+  final LLMModelConfigValue configValue;
+
+  LLMModelConfiguration updateValue(LLMModelConfigValue value) {
+    return LLMModelConfiguration(
+      configId: configId,
+      configName: configName,
+      configDescription: configDescription,
+      configType: configType,
+      configValue: value,
+    );
+  }
+
+  LLMModelConfiguration({
+    required this.configId,
+    required this.configName,
+    required this.configDescription,
+    required this.configType,
+    required this.configValue,
+  }) {
+    // Assert that the configuration type and value matches
+    switch (configType) {
+      case LLMModelConfigurationType.boolean:
+        assert(configValue is LLMConfigBooleanValue);
+      case LLMModelConfigurationType.slider:
+        assert(configValue is LLMConfigSliderValue);
+      case LLMModelConfigurationType.numeric:
+        assert(configValue is LLMConfigNumericValue);
+      case LLMModelConfigurationType.text:
+        assert(configValue is LLMConfigTextValue);
+    }
+  }
+
+  factory LLMModelConfiguration.fromJson(Map x) {
+    LLMModelConfigurationType cT;
+    LLMModelConfigValue cV;
+    switch (x['configType']) {
+      case 'boolean':
+        cT = LLMModelConfigurationType.boolean;
+        cV = LLMConfigBooleanValue.deserialize(x['configValue']);
+        break;
+      case 'slider':
+        cT = LLMModelConfigurationType.slider;
+        cV = LLMConfigSliderValue.deserialize(x['configValue']);
+        break;
+      case 'numeric':
+        cT = LLMModelConfigurationType.numeric;
+        cV = LLMConfigNumericValue.deserialize(x['configValue']);
+        break;
+      case 'text':
+        cT = LLMModelConfigurationType.text;
+        cV = LLMConfigTextValue.deserialize(x['configValue']);
+        break;
+      default:
+        cT = LLMModelConfigurationType.text;
+        cV = LLMConfigTextValue.deserialize(x['configValue']);
+    }
+    return LLMModelConfiguration(
+      configId: x['configId'],
+      configName: x['configName'],
+      configDescription: x['configDescription'],
+      configType: cT,
+      configValue: cV,
+    );
+  }
+
+  Map toJson() {
+    return {
+      'configId': configId,
+      'configName': configName,
+      'configDescription': configDescription,
+      'configType': configType.name.toString(),
+      'configValue': configValue.serialize(),
+    };
+  }
+
+  LLMModelConfiguration clone() {
+    return LLMModelConfiguration.fromJson(toJson());
+  }
+}
+
+enum LLMModelConfigurationType { boolean, slider, numeric, text }
+
+//----------------LLMConfigValues ------------
+
+abstract class LLMModelConfigValue {
+  dynamic _value;
+
+  // ignore: unnecessary_getters_setters
+  dynamic get value => _value;
+
+  set value(dynamic newValue) => _value = newValue;
+
+  String serialize();
+
+  LLMModelConfigValue(this._value);
+}
+
+class LLMConfigBooleanValue extends LLMModelConfigValue {
+  LLMConfigBooleanValue({required bool value}) : super(value);
+
+  @override
+  String serialize() {
+    return value.toString();
+  }
+
+  static LLMConfigBooleanValue deserialize(String x) {
+    return LLMConfigBooleanValue(value: x == 'true');
+  }
+}
+
+class LLMConfigNumericValue extends LLMModelConfigValue {
+  LLMConfigNumericValue({required num value}) : super(value);
+
+  @override
+  String serialize() {
+    return value.toString();
+  }
+
+  static LLMConfigNumericValue deserialize(String x) {
+    return LLMConfigNumericValue(value: num.parse(x));
+  }
+}
+
+class LLMConfigSliderValue extends LLMModelConfigValue {
+  LLMConfigSliderValue({required (double, double, double) value})
+    : super(value);
+
+  @override
+  String serialize() {
+    final v = value as (double, double, double);
+    return jsonEncode([v.$1, v.$2, v.$3]);
+  }
+
+  static LLMConfigSliderValue deserialize(String x) {
+    final z = jsonDecode(x) as List;
+    final val = (
+      double.parse(z[0].toString()),
+      double.parse(z[1].toString()),
+      double.parse(z[2].toString()),
+    );
+    return LLMConfigSliderValue(value: val);
+  }
+}
+
+class LLMConfigTextValue extends LLMModelConfigValue {
+  LLMConfigTextValue({required String value}) : super(value);
+
+  @override
+  String serialize() {
+    return value.toString();
+  }
+
+  static LLMConfigTextValue deserialize(String x) {
+    return LLMConfigTextValue(value: x);
+  }
+}
+
+enum LLMConfigName { temperature, top_p, max_tokens, endpoint }
+
+Map<LLMConfigName, LLMModelConfiguration> defaultLLMConfigurations = {
+  LLMConfigName.temperature: LLMModelConfiguration(
+    configId: 'temperature',
+    configName: 'Temperature',
+    configDescription: 'The Temperature of the Model',
+    configType: LLMModelConfigurationType.slider,
+    configValue: LLMConfigSliderValue(value: (0, 0.5, 1)),
+  ),
+  LLMConfigName.top_p: LLMModelConfiguration(
+    configId: 'top_p',
+    configName: 'Top P',
+    configDescription: 'The Top P of the Model',
+    configType: LLMModelConfigurationType.slider,
+    configValue: LLMConfigSliderValue(value: (0, 0.95, 1)),
+  ),
+  LLMConfigName.max_tokens: LLMModelConfiguration(
+    configId: 'max_tokens',
+    configName: 'Maximum Tokens',
+    configDescription: 'The maximum number of tokens allowed in the output',
+    configType: LLMModelConfigurationType.numeric,
+    configValue: LLMConfigNumericValue(value: -1),
+  ),
+};

packages/genai/lib/llm_request.dart

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+class LLMRequestDetails {
+  String endpoint;
+  Map<String, String> headers;
+  String method;
+  Map<String, dynamic> body;
+
+  LLMRequestDetails({
+    required this.endpoint,
+    required this.headers,
+    required this.method,
+    required this.body,
+  });
+}

packages/genai/pubspec.yaml

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+name: genai
+description: "Generative AI capabilities for flutter applications"
+version: 0.0.1
+homepage:
+publish_to: none
+
+environment:
+  sdk: ^3.8.0
+  flutter: ">=1.17.0"
+
+dependencies:
+  flutter:
+    sdk: flutter
+  shared_preferences: ^2.5.2
+  better_networking:
+    path: ../better_networking
+
+dev_dependencies:
+  flutter_test:
+    sdk: flutter
+  build_runner: ^2.4.12
+  flutter_lints: ^4.0.0
+  freezed: ^2.5.7
+  json_serializable: ^6.7.1
+
+flutter:

packages/genai/test/genai_test.dart

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+import 'package:flutter_test/flutter_test.dart';
+import 'package:genai/genai.dart';
+
+void main() {
+}