feat(providers): separate embedding providers, add custom-openai provider

src/lib/providers.ts

@@ -8,7 +8,7 @@ import {
 } from '../config';
 import logger from '../utils/logger';
 
-export const getAvailableProviders = async () => {
+export const getAvailableChatModelProviders = async () => {
   const openAIApiKey = getOpenaiApiKey();
   const groqApiKey = getGroqApiKey();
   const ollamaEndpoint = getOllamaApiEndpoint();
@@ -33,10 +33,6 @@ export const getAvailableProviders = async () => {
           modelName: 'gpt-4-turbo',
           temperature: 0.7,
         }),
-        embeddings: new OpenAIEmbeddings({
-          openAIApiKey,
-          modelName: 'text-embedding-3-large',
-        }),
       };
     } catch (err) {
       logger.error(`Error loading OpenAI models: ${err}`);
@@ -86,10 +82,6 @@ export const getAvailableProviders = async () => {
             baseURL: 'https://api.groq.com/openai/v1',
           },
         ),
-        embeddings: new OpenAIEmbeddings({
-          openAIApiKey: openAIApiKey,
-          modelName: 'text-embedding-3-large',
-        }),
       };
     } catch (err) {
       logger.error(`Error loading Groq models: ${err}`);
@@ -110,17 +102,56 @@ export const getAvailableProviders = async () => {
         });
         return acc;
       }, {});
-
-      if (Object.keys(models['ollama']).length > 0) {
-        models['ollama']['embeddings'] = new OllamaEmbeddings({
-          baseUrl: ollamaEndpoint,
-          model: models['ollama'][Object.keys(models['ollama'])[0]].model,
-        });
-      }
     } 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`);
+
+      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}`);
+    }
+  }
+
   return models;
 };

src/routes/config.ts

@@ -1,5 +1,8 @@
 import express from 'express';
-import { getAvailableProviders } from '../lib/providers';
+import {
+  getAvailableChatModelProviders,
+  getAvailableEmbeddingModelProviders,
+} from '../lib/providers';
 import {
   getGroqApiKey,
   getOllamaApiEndpoint,
@@ -12,16 +15,24 @@ const router = express.Router();
 router.get('/', async (_, res) => {
   const config = {};
 
-  const providers = await getAvailableProviders();
+  const [chatModelProviders, embeddingModelProviders] = await Promise.all([
+    getAvailableChatModelProviders(),
+    getAvailableEmbeddingModelProviders(),
+  ]);
 
-  for (const provider in providers) {
-    delete providers[provider]['embeddings'];
+  config['chatModelProviders'] = {};
+  config['embeddingModelProviders'] = {};
+
+  for (const provider in chatModelProviders) {
+    config['chatModelProviders'][provider] = Object.keys(
+      chatModelProviders[provider],
+    );
   }
 
-  config['providers'] = {};
-
-  for (const provider in providers) {
-    config['providers'][provider] = Object.keys(providers[provider]);
+  for (const provider in embeddingModelProviders) {
+    config['embeddingModelProviders'][provider] = Object.keys(
+      embeddingModelProviders[provider],
+    );
   }
 
   config['openaiApiKey'] = getOpenaiApiKey();

src/routes/images.ts

@@ -1,7 +1,7 @@
 import express from 'express';
 import handleImageSearch from '../agents/imageSearchAgent';
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import { getAvailableProviders } from '../lib/providers';
+import { getAvailableChatModelProviders } from '../lib/providers';
 import { HumanMessage, AIMessage } from '@langchain/core/messages';
 import logger from '../utils/logger';
 
@@ -19,7 +19,7 @@ router.post('/', async (req, res) => {
       }
     });
 
-    const chatModels = await getAvailableProviders();
+    const chatModels = await getAvailableChatModelProviders();
     const provider = chat_model_provider || Object.keys(chatModels)[0];
     const chatModel = chat_model || Object.keys(chatModels[provider])[0];
 

src/routes/models.ts

@@ -1,14 +1,20 @@
 import express from 'express';
 import logger from '../utils/logger';
-import { getAvailableProviders } from '../lib/providers';
+import {
+  getAvailableChatModelProviders,
+  getAvailableEmbeddingModelProviders,
+} from '../lib/providers';
 
 const router = express.Router();
 
 router.get('/', async (req, res) => {
   try {
-    const providers = await getAvailableProviders();
+    const [chatModelProviders, embeddingModelProviders] = await Promise.all([
+      getAvailableChatModelProviders(),
+      getAvailableEmbeddingModelProviders(),
+    ]);
 
-    res.status(200).json({ providers });
+    res.status(200).json({ chatModelProviders, embeddingModelProviders });
   } catch (err) {
     res.status(500).json({ message: 'An error has occurred.' });
     logger.error(err.message);

src/routes/videos.ts

@@ -1,6 +1,6 @@
 import express from 'express';
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import { getAvailableProviders } from '../lib/providers';
+import { getAvailableChatModelProviders } from '../lib/providers';
 import { HumanMessage, AIMessage } from '@langchain/core/messages';
 import logger from '../utils/logger';
 import handleVideoSearch from '../agents/videoSearchAgent';
@@ -19,7 +19,7 @@ router.post('/', async (req, res) => {
       }
     });
 
-    const chatModels = await getAvailableProviders();
+    const chatModels = await getAvailableChatModelProviders();
     const provider = chat_model_provider || Object.keys(chatModels)[0];
     const chatModel = chat_model || Object.keys(chatModels[provider])[0];
 

src/websocket/connectionManager.ts

@@ -1,10 +1,14 @@
 import { WebSocket } from 'ws';
 import { handleMessage } from './messageHandler';
-import { getAvailableProviders } from '../lib/providers';
+import {
+  getAvailableEmbeddingModelProviders,
+  getAvailableChatModelProviders,
+} from '../lib/providers';
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
 import type { Embeddings } from '@langchain/core/embeddings';
 import type { IncomingMessage } from 'http';
 import logger from '../utils/logger';
+import { ChatOpenAI } from '@langchain/openai';
 
 export const handleConnection = async (
   ws: WebSocket,
@@ -13,18 +17,53 @@ export const handleConnection = async (
   const searchParams = new URL(request.url, `http://${request.headers.host}`)
     .searchParams;
 
-  const models = await getAvailableProviders();
-  const provider =
-    searchParams.get('chatModelProvider') || Object.keys(models)[0];
+  const [chatModelProviders, embeddingModelProviders] = await Promise.all([
+    getAvailableChatModelProviders(),
+    getAvailableEmbeddingModelProviders(),
+  ]);
+
+  const chatModelProvider =
+    searchParams.get('chatModelProvider') || Object.keys(chatModelProviders)[0];
   const chatModel =
-    searchParams.get('chatModel') || Object.keys(models[provider])[0];
+    searchParams.get('chatModel') ||
+    Object.keys(chatModelProviders[chatModelProvider])[0];
+
+  const embeddingModelProvider =
+    searchParams.get('embeddingModelProvider') ||
+    Object.keys(embeddingModelProviders)[0];
+  const embeddingModel =
+    searchParams.get('embeddingModel') ||
+    Object.keys(embeddingModelProviders[embeddingModelProvider])[0];
 
   let llm: BaseChatModel | undefined;
   let embeddings: Embeddings | undefined;
 
-  if (models[provider] && models[provider][chatModel]) {
-    llm = models[provider][chatModel] as BaseChatModel | undefined;
-    embeddings = models[provider].embeddings as Embeddings | undefined;
+  if (
+    chatModelProviders[chatModelProvider] &&
+    chatModelProviders[chatModelProvider][chatModel] &&
+    chatModelProvider != 'custom_openai'
+  ) {
+    llm = chatModelProviders[chatModelProvider][chatModel] as
+      | BaseChatModel
+      | undefined;
+  } else if (chatModelProvider == 'custom_openai') {
+    llm = new ChatOpenAI({
+      modelName: chatModel,
+      openAIApiKey: searchParams.get('openAIApiKey'),
+      temperature: 0.7,
+      configuration: {
+        baseURL: searchParams.get('openAIBaseURL'),
+      },
+    });
+  }
+
+  if (
+    embeddingModelProviders[embeddingModelProvider] &&
+    embeddingModelProviders[embeddingModelProvider][embeddingModel]
+  ) {
+    embeddings = embeddingModelProviders[embeddingModelProvider][
+      embeddingModel
+    ] as Embeddings | undefined;
   }
 
   if (!llm || !embeddings) {