feat(providers): separate each provider

src/lib/providers.ts

@@ -1,187 +0,0 @@
-import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai';
-import { ChatOllama } from '@langchain/community/chat_models/ollama';
-import { OllamaEmbeddings } from '@langchain/community/embeddings/ollama';
-import { HuggingFaceTransformersEmbeddings } from './huggingfaceTransformer';
-import {
-  getGroqApiKey,
-  getOllamaApiEndpoint,
-  getOpenaiApiKey,
-} from '../config';
-import logger from '../utils/logger';
-
-export const getAvailableChatModelProviders = async () => {
-  const openAIApiKey = getOpenaiApiKey();
-  const groqApiKey = getGroqApiKey();
-  const ollamaEndpoint = getOllamaApiEndpoint();
-
-  const models = {};
-
-  if (openAIApiKey) {
-    try {
-      models['openai'] = {
-        'GPT-3.5 turbo': new ChatOpenAI({
-          openAIApiKey,
-          modelName: 'gpt-3.5-turbo',
-          temperature: 0.7,
-        }),
-        'GPT-4': new ChatOpenAI({
-          openAIApiKey,
-          modelName: 'gpt-4',
-          temperature: 0.7,
-        }),
-        'GPT-4 turbo': new ChatOpenAI({
-          openAIApiKey,
-          modelName: 'gpt-4-turbo',
-          temperature: 0.7,
-        }),
-        'GPT-4 omni': new ChatOpenAI({
-          openAIApiKey,
-          modelName: 'gpt-4o',
-          temperature: 0.7,
-        }),
-      };
-    } catch (err) {
-      logger.error(`Error loading OpenAI models: ${err}`);
-    }
-  }
-
-  if (groqApiKey) {
-    try {
-      models['groq'] = {
-        'LLaMA3 8b': new ChatOpenAI(
-          {
-            openAIApiKey: groqApiKey,
-            modelName: 'llama3-8b-8192',
-            temperature: 0.7,
-          },
-          {
-            baseURL: 'https://api.groq.com/openai/v1',
-          },
-        ),
-        'LLaMA3 70b': new ChatOpenAI(
-          {
-            openAIApiKey: groqApiKey,
-            modelName: 'llama3-70b-8192',
-            temperature: 0.7,
-          },
-          {
-            baseURL: 'https://api.groq.com/openai/v1',
-          },
-        ),
-        'Mixtral 8x7b': new ChatOpenAI(
-          {
-            openAIApiKey: groqApiKey,
-            modelName: 'mixtral-8x7b-32768',
-            temperature: 0.7,
-          },
-          {
-            baseURL: 'https://api.groq.com/openai/v1',
-          },
-        ),
-        'Gemma 7b': new ChatOpenAI(
-          {
-            openAIApiKey: groqApiKey,
-            modelName: 'gemma-7b-it',
-            temperature: 0.7,
-          },
-          {
-            baseURL: 'https://api.groq.com/openai/v1',
-          },
-        ),
-      };
-    } catch (err) {
-      logger.error(`Error loading Groq models: ${err}`);
-    }
-  }
-
-  if (ollamaEndpoint) {
-    try {
-      const response = await fetch(`${ollamaEndpoint}/api/tags`, {
-        headers: {
-          'Content-Type': 'application/json',
-        },
-      });
-
-      const { models: ollamaModels } = (await response.json()) as any;
-
-      models['ollama'] = ollamaModels.reduce((acc, model) => {
-        acc[model.model] = new ChatOllama({
-          baseUrl: ollamaEndpoint,
-          model: model.model,
-          temperature: 0.7,
-        });
-        return acc;
-      }, {});
-    } catch (err) {
-      logger.error(`Error loading Ollama models: ${err}`);
-    }
-  }
-
-  models['custom_openai'] = {};
-
-  return models;
-};
-
-export const getAvailableEmbeddingModelProviders = async () => {
-  const openAIApiKey = getOpenaiApiKey();
-  const ollamaEndpoint = getOllamaApiEndpoint();
-
-  const models = {};
-
-  if (openAIApiKey) {
-    try {
-      models['openai'] = {
-        'Text embedding 3 small': new OpenAIEmbeddings({
-          openAIApiKey,
-          modelName: 'text-embedding-3-small',
-        }),
-        'Text embedding 3 large': new OpenAIEmbeddings({
-          openAIApiKey,
-          modelName: 'text-embedding-3-large',
-        }),
-      };
-    } catch (err) {
-      logger.error(`Error loading OpenAI embeddings: ${err}`);
-    }
-  }
-
-  if (ollamaEndpoint) {
-    try {
-      const response = await fetch(`${ollamaEndpoint}/api/tags`, {
-        headers: {
-          'Content-Type': 'application/json',
-        },
-      });
-
-      const { models: ollamaModels } = (await response.json()) as any;
-
-      models['ollama'] = ollamaModels.reduce((acc, model) => {
-        acc[model.model] = new OllamaEmbeddings({
-          baseUrl: ollamaEndpoint,
-          model: model.model,
-        });
-        return acc;
-      }, {});
-    } catch (err) {
-      logger.error(`Error loading Ollama embeddings: ${err}`);
-    }
-  }
-
-  try {
-    models['local'] = {
-      'BGE Small': new HuggingFaceTransformersEmbeddings({
-        modelName: 'Xenova/bge-small-en-v1.5',
-      }),
-      'GTE Small': new HuggingFaceTransformersEmbeddings({
-        modelName: 'Xenova/gte-small',
-      }),
-      'Bert Multilingual': new HuggingFaceTransformersEmbeddings({
-        modelName: 'Xenova/bert-base-multilingual-uncased',
-      }),
-    };
-  } catch (err) {
-    logger.error(`Error loading local embeddings: ${err}`);
-  }
-
-  return models;
-};

src/lib/providers/groq.ts

@@ -0,0 +1,57 @@
+import { ChatOpenAI } from '@langchain/openai';
+import { getGroqApiKey } from '../../config';
+import logger from '../../utils/logger';
+
+export const loadGroqChatModels = async () => {
+  const groqApiKey = getGroqApiKey();
+
+  try {
+    const chatModels = {
+      'LLaMA3 8b': new ChatOpenAI(
+        {
+          openAIApiKey: groqApiKey,
+          modelName: 'llama3-8b-8192',
+          temperature: 0.7,
+        },
+        {
+          baseURL: 'https://api.groq.com/openai/v1',
+        },
+      ),
+      'LLaMA3 70b': new ChatOpenAI(
+        {
+          openAIApiKey: groqApiKey,
+          modelName: 'llama3-70b-8192',
+          temperature: 0.7,
+        },
+        {
+          baseURL: 'https://api.groq.com/openai/v1',
+        },
+      ),
+      'Mixtral 8x7b': new ChatOpenAI(
+        {
+          openAIApiKey: groqApiKey,
+          modelName: 'mixtral-8x7b-32768',
+          temperature: 0.7,
+        },
+        {
+          baseURL: 'https://api.groq.com/openai/v1',
+        },
+      ),
+      'Gemma 7b': new ChatOpenAI(
+        {
+          openAIApiKey: groqApiKey,
+          modelName: 'gemma-7b-it',
+          temperature: 0.7,
+        },
+        {
+          baseURL: 'https://api.groq.com/openai/v1',
+        },
+      ),
+    };
+
+    return chatModels;
+  } catch (err) {
+    logger.error(`Error loading Groq models: ${err}`);
+    return {};
+  }
+};

src/lib/providers/index.ts

@@ -0,0 +1,36 @@
+import { loadGroqChatModels } from './groq';
+import { loadOllamaChatModels } from './ollama';
+import { loadOpenAIChatModels, loadOpenAIEmbeddingsModel } from './openai';
+import { loadTransformersEmbeddingsModel } from './transformers';
+
+const chatModelProviders = {
+  openai: loadOpenAIChatModels,
+  groq: loadGroqChatModels,
+  ollama: loadOllamaChatModels,
+};
+
+const embeddingModelProviders = {
+  openai: loadOpenAIEmbeddingsModel,
+  local: loadTransformersEmbeddingsModel,
+  ollama: loadOllamaChatModels,
+};
+
+export const getAvailableChatModelProviders = async () => {
+  const models = {};
+
+  for (const provider in chatModelProviders) {
+    models[provider] = await chatModelProviders[provider]();
+  }
+
+  return models;
+};
+
+export const getAvailableEmbeddingModelProviders = async () => {
+  const models = {};
+
+  for (const provider in embeddingModelProviders) {
+    models[provider] = await embeddingModelProviders[provider]();
+  }
+
+  return models;
+};

src/lib/providers/ollama.ts

@@ -0,0 +1,59 @@
+import { OllamaEmbeddings } from '@langchain/community/embeddings/ollama';
+import { getOllamaApiEndpoint } from '../../config';
+import logger from '../../utils/logger';
+import { ChatOllama } from '@langchain/community/chat_models/ollama';
+
+export const loadOllamaChatModels = async () => {
+  const ollamaEndpoint = getOllamaApiEndpoint();
+
+  try {
+    const response = await fetch(`${ollamaEndpoint}/api/tags`, {
+      headers: {
+        'Content-Type': 'application/json',
+      },
+    });
+
+    const { models: ollamaModels } = (await response.json()) as any;
+
+    const chatModels = ollamaModels.reduce((acc, model) => {
+      acc[model.model] = new ChatOllama({
+        baseUrl: ollamaEndpoint,
+        model: model.model,
+        temperature: 0.7,
+      });
+      return acc;
+    }, {});
+
+    return chatModels;
+  } catch (err) {
+    logger.error(`Error loading Ollama models: ${err}`);
+    return {};
+  }
+};
+
+export const loadOpenAIEmbeddingsModel = async () => {
+  const ollamaEndpoint = getOllamaApiEndpoint();
+
+  try {
+    const response = await fetch(`${ollamaEndpoint}/api/tags`, {
+      headers: {
+        'Content-Type': 'application/json',
+      },
+    });
+
+    const { models: ollamaModels } = (await response.json()) as any;
+
+    const embeddingsModels = ollamaModels.reduce((acc, model) => {
+      acc[model.model] = new OllamaEmbeddings({
+        baseUrl: ollamaEndpoint,
+        model: model.model,
+      });
+      return acc;
+    }, {});
+
+    return embeddingsModels;
+  } catch (err) {
+    logger.error(`Error loading Ollama embeddings model: ${err}`);
+    return {};
+  }
+};

src/lib/providers/openai.ts

@@ -0,0 +1,59 @@
+import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai';
+import { getOpenaiApiKey } from '../../config';
+import logger from '../../utils/logger';
+
+export const loadOpenAIChatModels = async () => {
+  const openAIApiKey = getOpenaiApiKey();
+
+  try {
+    const chatModels = {
+      'GPT-3.5 turbo': new ChatOpenAI({
+        openAIApiKey,
+        modelName: 'gpt-3.5-turbo',
+        temperature: 0.7,
+      }),
+      'GPT-4': new ChatOpenAI({
+        openAIApiKey,
+        modelName: 'gpt-4',
+        temperature: 0.7,
+      }),
+      'GPT-4 turbo': new ChatOpenAI({
+        openAIApiKey,
+        modelName: 'gpt-4-turbo',
+        temperature: 0.7,
+      }),
+      'GPT-4 omni': new ChatOpenAI({
+        openAIApiKey,
+        modelName: 'gpt-4o',
+        temperature: 0.7,
+      }),
+    };
+
+    return chatModels;
+  } catch (err) {
+    logger.error(`Error loading OpenAI models: ${err}`);
+    return {};
+  }
+};
+
+export const loadOpenAIEmbeddingsModel = async () => {
+  const openAIApiKey = getOpenaiApiKey();
+
+  try {
+    const embeddingModels = {
+      'Text embedding 3 small': new OpenAIEmbeddings({
+        openAIApiKey,
+        modelName: 'text-embedding-3-small',
+      }),
+      'Text embedding 3 large': new OpenAIEmbeddings({
+        openAIApiKey,
+        modelName: 'text-embedding-3-large',
+      }),
+    };
+
+    return embeddingModels;
+  } catch (err) {
+    logger.error(`Error loading OpenAI embeddings model: ${err}`);
+    return {};
+  }
+};

src/lib/providers/transformers.ts

@@ -0,0 +1,23 @@
+import logger from '../../utils/logger';
+import { HuggingFaceTransformersEmbeddings } from '../huggingfaceTransformer';
+
+export const loadTransformersEmbeddingsModel = async () => {
+  try {
+    const embeddingModels = {
+      'BGE Small': new HuggingFaceTransformersEmbeddings({
+        modelName: 'Xenova/bge-small-en-v1.5',
+      }),
+      'GTE Small': new HuggingFaceTransformersEmbeddings({
+        modelName: 'Xenova/gte-small',
+      }),
+      'Bert Multilingual': new HuggingFaceTransformersEmbeddings({
+        modelName: 'Xenova/bert-base-multilingual-uncased',
+      }),
+    };
+
+    return embeddingModels;
+  } catch (err) {
+    logger.error(`Error loading Transformers embeddings model: ${err}`);
+    return {};
+  }
+};