Refactor genai package to new modular interface

Reorganized the genai package by removing legacy LLM-related files and introducing a new modular interface under the 'interface' directory. Added provider-specific model classes, centralized constants, and updated the example to use the new API and data structures. Updated exports in genai.dart and improved dependency management.

packages/genai/lib/interface/consts.dart

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+import '../consts.dart';
+import '../models/models.dart';
+import 'model_providers/model_providers.dart';
+
+enum ModelAPIProvider { openai, anthropic, gemini, azureopenai, ollama }
+
+final kModelProvidersMap = {
+  ModelAPIProvider.openai: OpenAIModel.instance,
+  ModelAPIProvider.anthropic: AnthropicModel.instance,
+  ModelAPIProvider.gemini: GeminiModel.instance,
+  ModelAPIProvider.azureopenai: AzureOpenAIModel.instance,
+  ModelAPIProvider.ollama: OllamaModel.instance,
+};
+
+const kAnthropicUrl = 'https://api.anthropic.com/v1/messages';
+const kGeminiUrl = 'https://generativelanguage.googleapis.com/v1beta/models';
+const kOpenAIUrl = 'https://api.openai.com/v1/chat/completions';
+const kOllamaUrl = '$kBaseOllamaUrl/v1/chat/completions';
+
+final kDefaultModelRequestData = ModelRequestData(
+  url: '',
+  model: '',
+  apiKey: '',
+  systemPrompt: '',
+  userPrompt: '',
+  modelConfigs: [
+    kDefaultModelConfigTemperature,
+    kDefaultModelConfigTopP,
+    kDefaultModelConfigMaxTokens,
+  ],
+  stream: false,
+);
+
+final kDefaultModelConfigTemperature = ModelConfig(
+  id: 'temperature',
+  name: 'Temperature',
+  description: 'The Temperature of the Model',
+  type: ConfigType.slider,
+  value: ConfigSliderValue(value: (0, 0.5, 1)),
+);
+
+final kDefaultModelConfigTopP = ModelConfig(
+  id: 'top_p',
+  name: 'Top P',
+  description: 'The Top P of the Model',
+  type: ConfigType.slider,
+  value: ConfigSliderValue(value: (0, 0.95, 1)),
+);
+
+final kDefaultModelConfigMaxTokens = ModelConfig(
+  id: 'max_tokens',
+  name: 'Maximum Tokens',
+  description: 'The maximum number of tokens allowed in the output',
+  type: ConfigType.numeric,
+  value: ConfigNumericValue(value: 1024),
+);
+
+final kDefaultModelConfigStream = ModelConfig(
+  id: 'stream',
+  name: 'Enable Streaming Mode',
+  description: 'The LLM output will be sent in a stream instead of all at once',
+  type: ConfigType.boolean,
+  value: ConfigBooleanValue(value: false),
+);
+
+final kDefaultGeminiModelConfigTopP = kDefaultModelConfigTopP.copyWith(
+  id: 'topP',
+);
+
+final kDefaultGeminiModelConfigMaxTokens = kDefaultModelConfigMaxTokens
+    .copyWith(id: 'maxOutputTokens');

packages/genai/lib/interface/interface.dart

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+export 'model_providers/model_providers.dart';
+export 'consts.dart';

packages/genai/lib/interface/model_providers/anthropic.dart

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+import 'package:better_networking/better_networking.dart';
+import '../../models/models.dart';
+import '../consts.dart';
+
+class AnthropicModel extends ModelProvider {
+  static final instance = AnthropicModel();
+
+  @override
+  ModelRequestData get defaultRequestData =>
+      kDefaultModelRequestData.copyWith(url: kAnthropicUrl);
+
+  @override
+  HttpRequestModel? createRequest(ModelRequestData? requestData) {
+    if (requestData == null) {
+      return null;
+    }
+    return HttpRequestModel(
+      method: HTTPVerb.post,
+      url: requestData.url,
+      headers: const [
+        NameValueModel(name: "anthropic-version", value: "2023-06-01"),
+      ],
+      authModel: AuthModel(
+        type: APIAuthType.apiKey,
+        apikey: AuthApiKeyModel(key: requestData.apiKey),
+      ),
+      body: kJsonEncoder.convert({
+        "model": requestData.model,
+        "messages": [
+          {"role": "system", "content": requestData.systemPrompt},
+          {"role": "user", "content": requestData.userPrompt},
+        ],
+        ...requestData.getModelConfigMap(),
+        if (requestData.stream ?? false) ...{'stream': true},
+      }),
+    );
+  }
+
+  @override
+  String? outputFormatter(Map x) {
+    return x['content']?[0]['text'];
+  }
+
+  @override
+  String? streamOutputFormatter(Map x) {
+    return x['text'];
+  }
+}

packages/genai/lib/interface/model_providers/azureopenai.dart

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+import 'package:better_networking/better_networking.dart';
+import '../../models/models.dart';
+import '../consts.dart';
+
+class AzureOpenAIModel extends ModelProvider {
+  static final instance = AzureOpenAIModel();
+  @override
+  ModelRequestData get defaultRequestData => kDefaultModelRequestData;
+
+  @override
+  HttpRequestModel? createRequest(ModelRequestData? requestData) {
+    if (requestData == null) {
+      return null;
+    }
+    if (requestData.url.isEmpty) {
+      throw Exception('MODEL ENDPOINT IS EMPTY');
+    }
+    return HttpRequestModel(
+      method: HTTPVerb.post,
+      url: requestData.url,
+      authModel: AuthModel(
+        type: APIAuthType.apiKey,
+        apikey: AuthApiKeyModel(key: requestData.apiKey, name: 'api-key'),
+      ),
+      body: kJsonEncoder.convert({
+        "model": requestData.model,
+        "messages": [
+          {"role": "system", "content": requestData.systemPrompt},
+          if (requestData.userPrompt.isNotEmpty) ...{
+            {"role": "user", "content": requestData.userPrompt},
+          } else ...{
+            {"role": "user", "content": "Generate"},
+          },
+        ],
+        ...requestData.getModelConfigMap(),
+        if (requestData.stream ?? false) ...{'stream': true},
+      }),
+    );
+  }
+
+  @override
+  String? outputFormatter(Map x) {
+    return x["choices"]?[0]["message"]?["content"]?.trim();
+  }
+
+  @override
+  String? streamOutputFormatter(Map x) {
+    return x["choices"]?[0]["delta"]?["content"];
+  }
+}

packages/genai/lib/interface/model_providers/gemini.dart

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+import 'package:better_networking/better_networking.dart';
+import '../../models/models.dart';
+import '../consts.dart';
+
+class GeminiModel extends ModelProvider {
+  static final instance = GeminiModel();
+
+  @override
+  ModelRequestData get defaultRequestData => kDefaultModelRequestData.copyWith(
+    url: kGeminiUrl,
+    modelConfigs: [
+      kDefaultModelConfigTemperature,
+      kDefaultGeminiModelConfigTopP,
+      kDefaultGeminiModelConfigMaxTokens,
+    ],
+  );
+
+  @override
+  HttpRequestModel? createRequest(ModelRequestData? requestData) {
+    if (requestData == null) {
+      return null;
+    }
+    List<NameValueModel> params = [];
+    String endpoint = "${requestData.url}/${requestData.model}:";
+    if (requestData.stream ?? false) {
+      endpoint += 'streamGenerateContent';
+      params.add(const NameValueModel(name: "alt", value: "sse"));
+    } else {
+      endpoint += 'generateContent';
+    }
+
+    return HttpRequestModel(
+      method: HTTPVerb.post,
+      url: endpoint,
+      authModel: AuthModel(
+        type: APIAuthType.apiKey,
+        apikey: AuthApiKeyModel(
+          key: requestData.apiKey,
+          location: 'query',
+          name: 'key',
+        ),
+      ),
+      body: kJsonEncoder.convert({
+        "contents": [
+          {
+            "role": "user",
+            "parts": [
+              {"text": requestData.userPrompt},
+            ],
+          },
+        ],
+        "systemInstruction": {
+          "role": "system",
+          "parts": [
+            {"text": requestData.systemPrompt},
+          ],
+        },
+        "generationConfig": requestData.getModelConfigMap(),
+      }),
+    );
+  }
+
+  @override
+  String? outputFormatter(Map x) {
+    return x['candidates']?[0]?['content']?['parts']?[0]?['text'];
+  }
+
+  @override
+  String? streamOutputFormatter(Map x) {
+    return x['candidates']?[0]?['content']?['parts']?[0]?['text'];
+  }
+}

packages/genai/lib/interface/model_providers/model_providers.dart

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+export 'anthropic.dart';
+export 'gemini.dart';
+export 'azureopenai.dart';
+export 'openai.dart';
+export 'ollama.dart';

packages/genai/lib/interface/model_providers/ollama.dart

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+import '../../models/models.dart';
+import '../consts.dart';
+import 'openai.dart';
+
+class OllamaModel extends OpenAIModel {
+  static final instance = OllamaModel();
+
+  @override
+  ModelRequestData get defaultRequestData => kDefaultModelRequestData.copyWith(
+    url: kOllamaUrl,
+    modelConfigs: [kDefaultModelConfigTemperature, kDefaultModelConfigTopP],
+  );
+}

packages/genai/lib/interface/model_providers/openai.dart

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+import 'package:better_networking/better_networking.dart';
+import '../../models/models.dart';
+import '../consts.dart';
+
+class OpenAIModel extends ModelProvider {
+  static final instance = OpenAIModel();
+
+  @override
+  ModelRequestData get defaultRequestData =>
+      kDefaultModelRequestData.copyWith(url: kOpenAIUrl);
+
+  @override
+  HttpRequestModel? createRequest(ModelRequestData? requestData) {
+    if (requestData == null) {
+      return null;
+    }
+    return HttpRequestModel(
+      method: HTTPVerb.post,
+      url: requestData.url,
+      authModel: AuthModel(
+        type: APIAuthType.bearer,
+        bearer: AuthBearerModel(token: requestData.apiKey),
+      ),
+      body: kJsonEncoder.convert({
+        "model": requestData.model,
+        "messages": [
+          {"role": "system", "content": requestData.systemPrompt},
+          if (requestData.userPrompt.isNotEmpty) ...{
+            {"role": "user", "content": requestData.userPrompt},
+          } else ...{
+            {"role": "user", "content": "Generate"},
+          },
+        ],
+        ...requestData.getModelConfigMap(),
+        if (requestData.stream ?? false) ...{'stream': true},
+      }),
+    );
+  }
+
+  @override
+  String? outputFormatter(Map x) {
+    return x["choices"]?[0]["message"]?["content"]?.trim();
+  }
+
+  @override
+  String? streamOutputFormatter(Map x) {
+    return x["choices"]?[0]["delta"]?["content"];
+  }
+}