Providers: Implemented anthropic, gemini, openai & azureopenai

packages/genai/lib/llm_manager.dart

@@ -0,0 +1,86 @@
+import 'dart:convert';
+import 'package:better_networking/better_networking.dart';
+import 'package:shared_preferences/shared_preferences.dart';
+
+class LLMManager {
+  static Map avaiableModels = {
+    "gemini": [
+      ["gemini-2.0-flash", "Gemini 2.0 Flash"],
+    ],
+  };
+
+  static get models => avaiableModels;
+
+  static const String modelRemoteURL =
+      'https://raw.githubusercontent.com/synapsecode/apidash/llm_model_rearch/packages/genai/models.json';
+  static const String baseOllamaURL = 'http://localhost:11434';
+
+  static addLLM(String providerID, String modelID, String modelName) async {
+    avaiableModels[providerID] = [
+      ...avaiableModels[providerID],
+      [modelID, modelName],
+    ];
+    await saveAvailableLLMs(avaiableModels);
+  }
+
+  static removeLLM(String providerID, String modelID, String modelName) async {
+    List z = avaiableModels[providerID] as List;
+    z = z.where((x) => x[0] != modelID && x[1] != modelName).toList();
+    avaiableModels[providerID] = z;
+    await saveAvailableLLMs(avaiableModels);
+  }
+
+  static fetchAvailableLLMs([String? remoteURL, String? ollamaURL]) async {
+    //get LLMs from remove
+    final (resp, _, __) = await sendHttpRequest(
+      'FETCH_MODELS',
+      APIType.rest,
+      HttpRequestModel(url: remoteURL ?? modelRemoteURL, method: HTTPVerb.get),
+    );
+    if (resp == null) {
+      throw Exception('UNABLE TO FETCH MODELS');
+    }
+    Map remoteModels = jsonDecode(resp.body);
+    final oM = await fetchInstalledOllamaModels(ollamaURL);
+    remoteModels['ollama'] = oM;
+    saveAvailableLLMs(remoteModels);
+    loadAvailableLLMs();
+  }
+
+  static saveAvailableLLMs(Map updatedLLMs) async {
+    SharedPreferences prefs = await SharedPreferences.getInstance();
+    await prefs.setString('genai_available_llms', jsonEncode(updatedLLMs));
+  }
+
+  static loadAvailableLLMs() async {
+    SharedPreferences prefs = await SharedPreferences.getInstance();
+    final avl = prefs.getString('genai_available_llms');
+    if (avl != null) {
+      avaiableModels = (jsonDecode(avl));
+    }
+  }
+
+  static clearAvailableLLMs() async {
+    SharedPreferences prefs = await SharedPreferences.getInstance();
+    prefs.remove('genai_available_llms');
+  }
+
+  static Future<List?> fetchInstalledOllamaModels([String? ollamaURL]) async {
+    final url = "${ollamaURL ?? baseOllamaURL}/api/tags";
+    final (resp, _, __) = await sendHttpRequest(
+      'OLLAMA_FETCH',
+      APIType.rest,
+      HttpRequestModel(url: url, method: HTTPVerb.get),
+      noSSL: true,
+    );
+    if (resp == null) return [];
+    final output = jsonDecode(resp.body);
+    final models = output['models'];
+    if (models == null) return [];
+    List ollamaModels = [];
+    for (final m in models) {
+      ollamaModels.add([m['model'], m['name']]);
+    }
+    return ollamaModels;
+  }
+}

packages/genai/lib/providers/anthropic.dart

@@ -0,0 +1,74 @@
+import '../llm_config.dart';
+import '../llm_input_payload.dart';
+import '../llm_request.dart';
+import 'common.dart';
+
+class AnthropicModelController extends ModelController {
+  static final instance = AnthropicModelController();
+  @override
+  LLMInputPayload get inputPayload => LLMInputPayload(
+    endpoint: 'https://api.anthropic.com/v1/messages',
+    credential: '',
+    systemPrompt: '',
+    userPrompt: '',
+    configMap: {
+      LLMConfigName.temperature.name:
+          defaultLLMConfigurations[LLMConfigName.temperature]!,
+      LLMConfigName.top_p.name: defaultLLMConfigurations[LLMConfigName.top_p]!,
+    },
+  ).clone();
+
+  @override
+  LLMRequestDetails createRequest(
+    LLMModel model,
+    LLMInputPayload inputPayload, {
+    bool stream = false,
+  }) {
+    return LLMRequestDetails(
+      endpoint: inputPayload.endpoint,
+      headers: {
+        'anthropic-version': '2023-06-01',
+        'Authorization': 'Bearer ${inputPayload.credential}',
+      },
+      method: 'POST',
+      body: {
+        "model": model.identifier,
+        if (stream) ...{'stream': true},
+        "messages": [
+          {"role": "system", "content": inputPayload.systemPrompt},
+          {"role": "user", "content": inputPayload.userPrompt},
+        ],
+        "temperature":
+            inputPayload
+                .configMap[LLMConfigName.temperature.name]
+                ?.configValue
+                .value
+                ?.$2 ??
+            0.5,
+        "top_p":
+            inputPayload
+                .configMap[LLMConfigName.top_p.name]
+                ?.configValue
+                .value
+                ?.$2 ??
+            0.95,
+        if (inputPayload.configMap[LLMConfigName.max_tokens.name] != null) ...{
+          "max_tokens": inputPayload
+              .configMap[LLMConfigName.max_tokens.name]!
+              .configValue
+              .value,
+        },
+      },
+    );
+  }
+
+  @override
+  String? outputFormatter(Map x) {
+    return x['content']?[0]['text'];
+  }
+
+  @override
+  String? streamOutputFormatter(Map x) {
+    return x['text'];
+  }
+}

packages/genai/lib/providers/azureopenai.dart

@@ -0,0 +1,77 @@
+import '../llm_config.dart';
+import '../llm_input_payload.dart';
+import '../llm_request.dart';
+import 'common.dart';
+
+class AzureOpenAIModelController extends ModelController {
+  static final instance = AzureOpenAIModelController();
+  @override
+  LLMInputPayload get inputPayload => LLMInputPayload(
+    endpoint: '', //TO BE FILLED BY USER
+    credential: '',
+    systemPrompt: '',
+    userPrompt: '',
+    configMap: {
+      LLMConfigName.temperature.name:
+          defaultLLMConfigurations[LLMConfigName.temperature]!,
+      LLMConfigName.top_p.name: defaultLLMConfigurations[LLMConfigName.top_p]!,
+    },
+  ).clone();
+
+  @override
+  LLMRequestDetails createRequest(
+    LLMModel model,
+    LLMInputPayload inputPayload, {
+    bool stream = false,
+  }) {
+    if (inputPayload.endpoint.isEmpty) {
+      throw Exception('MODEL ENDPOINT IS EMPTY');
+    }
+    return LLMRequestDetails(
+      endpoint: inputPayload.endpoint,
+      headers: {'api-key': inputPayload.credential},
+      method: 'POST',
+      body: {
+        if (stream) ...{'stream': true},
+        "messages": [
+          {"role": "system", "content": inputPayload.systemPrompt},
+          if (inputPayload.userPrompt.isNotEmpty) ...{
+            {"role": "user", "content": inputPayload.userPrompt},
+          } else ...{
+            {"role": "user", "content": "Generate"},
+          },
+        ],
+        "temperature":
+            inputPayload
+                .configMap[LLMConfigName.temperature.name]
+                ?.configValue
+                .value
+                ?.$2 ??
+            0.5,
+        "top_p":
+            inputPayload
+                .configMap[LLMConfigName.top_p.name]
+                ?.configValue
+                .value
+                ?.$2 ??
+            0.95,
+        if (inputPayload.configMap[LLMConfigName.max_tokens.name] != null) ...{
+          "max_tokens": inputPayload
+              .configMap[LLMConfigName.max_tokens.name]!
+              .configValue
+              .value,
+        },
+      },
+    );
+  }
+
+  @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/providers/gemini.dart

@@ -0,0 +1,92 @@
+import '../llm_config.dart';
+import '../llm_input_payload.dart';
+import '../llm_request.dart';
+import 'common.dart';
+
+class GeminiModelController extends ModelController {
+  static final instance = GeminiModelController();
+  @override
+  LLMInputPayload get inputPayload => LLMInputPayload(
+    endpoint: 'https://generativelanguage.googleapis.com/v1beta/models',
+    credential: '',
+    systemPrompt: '',
+    userPrompt: '',
+    configMap: {
+      LLMConfigName.temperature.name:
+          defaultLLMConfigurations[LLMConfigName.temperature]!,
+      LLMConfigName.top_p.name: defaultLLMConfigurations[LLMConfigName.top_p]!,
+    },
+  ).clone();
+
+  @override
+  LLMRequestDetails createRequest(
+    LLMModel model,
+    LLMInputPayload inputPayload, {
+    bool stream = false,
+  }) {
+    String endpoint = inputPayload.endpoint;
+    endpoint =
+        "$endpoint/${model.identifier}:generateContent?key=${inputPayload.credential}";
+    if (stream) {
+      endpoint = endpoint.replaceAll(
+        'generateContent?',
+        'streamGenerateContent?alt=sse&',
+      );
+    }
+    return LLMRequestDetails(
+      endpoint: endpoint,
+      headers: {},
+      method: 'POST',
+      body: {
+        "model": model.identifier,
+        "contents": [
+          {
+            "role": "user",
+            "parts": [
+              {"text": inputPayload.userPrompt},
+            ],
+          },
+        ],
+        "systemInstruction": {
+          "role": "system",
+          "parts": [
+            {"text": inputPayload.systemPrompt},
+          ],
+        },
+        "generationConfig": {
+          "temperature":
+              inputPayload
+                  .configMap[LLMConfigName.temperature.name]
+                  ?.configValue
+                  .value
+                  ?.$2 ??
+              0.5,
+          "topP":
+              inputPayload
+                  .configMap[LLMConfigName.top_p.name]
+                  ?.configValue
+                  .value
+                  ?.$2 ??
+              0.95,
+          if (inputPayload.configMap[LLMConfigName.max_tokens.name] !=
+              null) ...{
+            "maxOutputTokens": inputPayload
+                .configMap[LLMConfigName.max_tokens.name]!
+                .configValue
+                .value,
+          },
+        },
+      },
+    );
+  }
+
+  @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/providers/openai.dart

@@ -0,0 +1,76 @@
+import '../llm_config.dart';
+import '../llm_input_payload.dart';
+import '../llm_request.dart';
+import 'common.dart';
+
+class OpenAIModelController extends ModelController {
+  static final instance = OpenAIModelController();
+
+  @override
+  LLMInputPayload get inputPayload => LLMInputPayload(
+    endpoint: 'https://api.openai.com/v1/chat/completions',
+    credential: '',
+    systemPrompt: '',
+    userPrompt: '',
+    configMap: {
+      LLMConfigName.temperature.name:
+          defaultLLMConfigurations[LLMConfigName.temperature]!,
+      LLMConfigName.top_p.name: defaultLLMConfigurations[LLMConfigName.top_p]!,
+    },
+  ).clone();
+
+  @override
+  LLMRequestDetails createRequest(
+    LLMModel model,
+    LLMInputPayload inputPayload, {
+    bool stream = false,
+  }) {
+    return LLMRequestDetails(
+      endpoint: inputPayload.endpoint,
+      headers: {'Authorization': "Bearer ${inputPayload.credential}"},
+      method: 'POST',
+      body: {
+        'model': model.identifier,
+        if (stream) ...{'stream': true},
+        "messages": [
+          {"role": "system", "content": inputPayload.systemPrompt},
+          if (inputPayload.userPrompt.isNotEmpty) ...{
+            {"role": "user", "content": inputPayload.userPrompt},
+          } else ...{
+            {"role": "user", "content": "Generate"},
+          },
+        ],
+        "temperature":
+            inputPayload
+                .configMap[LLMConfigName.temperature.name]
+                ?.configValue
+                .value
+                ?.$2 ??
+            0.5,
+        "top_p":
+            inputPayload
+                .configMap[LLMConfigName.top_p.name]
+                ?.configValue
+                .value
+                ?.$2 ??
+            0.95,
+        if (inputPayload.configMap[LLMConfigName.max_tokens.name] != null) ...{
+          "max_tokens": inputPayload
+              .configMap[LLMConfigName.max_tokens.name]!
+              .configValue
+              .value,
+        },
+      },
+    );
+  }
+
+  @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/providers/providers.dart

@@ -1,6 +1,10 @@
 import '../llm_manager.dart';
+import 'anthropic.dart';
+import 'azureopenai.dart';
 import 'common.dart';
+import 'gemini.dart';
 import 'ollama.dart';
+import 'openai.dart';
 
 enum LLMProvider {
   gemini('Gemini'),
@@ -27,8 +31,14 @@ enum LLMProvider {
     switch (this) {
       case LLMProvider.ollama:
         return OllamaModelController.instance;
-      case _:
-        return OllamaModelController.instance;
+      case LLMProvider.gemini:
+        return GeminiModelController.instance;
+      case LLMProvider.azureopenai:
+        return AzureOpenAIModelController.instance;
+      case LLMProvider.openai:
+        return OpenAIModelController.instance;
+      case LLMProvider.anthropic:
+        return AnthropicModelController.instance;
     }
   }