Merge 6edac6938c into f37686189e

src/config.ts

@@ -16,9 +16,10 @@ interface Config {
     ANTHROPIC: string;
     GEMINI: string;
   };
-  API_ENDPOINTS: {
-    SEARXNG: string;
+  API_ENDPOINTS: {  
     OLLAMA: string;
+    LMSTUDIO: string;
+    SEARXNG: string;
   };
 }
 
@@ -51,6 +52,8 @@ export const getSearxngApiEndpoint = () =>
 
 export const getOllamaApiEndpoint = () => loadConfig().API_ENDPOINTS.OLLAMA;
 
+export const getLMStudioApiEndpoint = () => loadConfig().API_ENDPOINTS.LMSTUDIO;
+
 export const updateConfig = (config: RecursivePartial<Config>) => {
   const currentConfig = loadConfig();
 
@@ -72,6 +75,27 @@ export const updateConfig = (config: RecursivePartial<Config>) => {
     }
   }
 
+  /*
+export const updateConfig = (config: RecursivePartial<Config>) => {
+  const currentConfig = loadConfig();
+
+  // Merge existing config with new values
+  const mergedConfig: RecursivePartial<Config> = {
+    GENERAL: {
+      ...currentConfig.GENERAL,
+      ...config.GENERAL,
+    },
+    API_KEYS: {
+      ...currentConfig.API_KEYS,
+      ...config.API_KEYS,
+    },
+    API_ENDPOINTS: {
+      ...currentConfig.API_ENDPOINTS,
+      ...config.API_ENDPOINTS,
+    },
+  };
+*/
+
   fs.writeFileSync(
     path.join(__dirname, `../${configFileName}`),
     toml.stringify(config),

src/lib/providers/index.ts

@@ -4,6 +4,7 @@ import { loadOpenAIChatModels, loadOpenAIEmbeddingsModels } from './openai';
 import { loadAnthropicChatModels } from './anthropic';
 import { loadTransformersEmbeddingsModels } from './transformers';
 import { loadGeminiChatModels, loadGeminiEmbeddingsModels } from './gemini';
+import { loadLMStudioChatModels, loadLMStudioEmbeddingsModels } from './lmstudio';
 
 const chatModelProviders = {
   openai: loadOpenAIChatModels,
@@ -11,6 +12,7 @@ const chatModelProviders = {
   ollama: loadOllamaChatModels,
   anthropic: loadAnthropicChatModels,
   gemini: loadGeminiChatModels,
+  lm_studio: loadLMStudioChatModels,
 };
 
 const embeddingModelProviders = {
@@ -18,6 +20,7 @@ const embeddingModelProviders = {
   local: loadTransformersEmbeddingsModels,
   ollama: loadOllamaEmbeddingsModels,
   gemini: loadGeminiEmbeddingsModels,
+  lm_studio: loadLMStudioEmbeddingsModels,
 };
 
 export const getAvailableChatModelProviders = async () => {

src/lib/providers/lmstudio.ts

@@ -0,0 +1,89 @@
+import { OpenAIEmbeddings } from '@langchain/openai';
+import { ChatOpenAI } from '@langchain/openai';
+import { getKeepAlive, getLMStudioApiEndpoint } from '../../config';
+import logger from '../../utils/logger';
+import axios from 'axios';
+
+interface LMStudioModel {
+  id: string;
+  // add other properties if LM Studio API provides them
+}
+
+interface ChatModelConfig {
+  displayName: string;
+  model: ChatOpenAI;
+}
+
+export const loadLMStudioChatModels = async (): Promise<Record<string, ChatModelConfig>> => {
+  const lmStudioEndpoint = getLMStudioApiEndpoint();
+
+  if (!lmStudioEndpoint) {
+    logger.debug('LM Studio endpoint not configured, skipping');
+    return {};
+  }
+
+  try {
+    const response = await axios.get<{ data: LMStudioModel[] }>(`${lmStudioEndpoint}/models`, {
+      headers: {
+        'Content-Type': 'application/json',
+      },
+    });
+
+    const lmStudioModels = response.data.data;
+
+    const chatModels = lmStudioModels.reduce<Record<string, ChatModelConfig>>((acc, model) => {
+      acc[model.id] = {
+        displayName: model.id,
+        model: new ChatOpenAI({
+          openAIApiKey: 'lm-studio',
+          configuration: {
+            baseURL: lmStudioEndpoint,
+          },
+          modelName: model.id,
+          temperature: 0.7,
+        }),
+      };
+      return acc;
+    }, {});
+
+    return chatModels;
+  } catch (err) {
+    logger.error(`Error loading LM Studio models: ${err}`);
+    return {};
+  }
+};
+
+export const loadLMStudioEmbeddingsModels = async () => {
+  const lmStudioEndpoint = getLMStudioApiEndpoint();
+
+  if (!lmStudioEndpoint) return {};
+
+  try {
+    const response = await axios.get(`${lmStudioEndpoint}/models`, {
+      headers: {
+        'Content-Type': 'application/json',
+      },
+    });
+
+    const lmStudioModels = response.data.data;
+
+    const embeddingsModels = lmStudioModels.reduce((acc, model) => {
+      acc[model.id] = {
+        displayName: model.id,
+        model: new OpenAIEmbeddings({
+          openAIApiKey: 'lm-studio', // Dummy key required by LangChain
+          configuration: {
+            baseURL: lmStudioEndpoint,
+          },
+          modelName: model.id,
+        }),
+      };
+      return acc;
+    }, {});
+
+    return embeddingsModels;
+  } catch (err) {
+    logger.error(`Error loading LM Studio embeddings model: ${err}`);
+    return {};
+  }
+};

src/routes/config.ts

@@ -6,6 +6,7 @@ import {
 import {
   getGroqApiKey,
   getOllamaApiEndpoint,
+  getLMStudioApiEndpoint,
   getAnthropicApiKey,
   getGeminiApiKey,
   getOpenaiApiKey,
@@ -51,6 +52,7 @@ router.get('/', async (_, res) => {
 
     config['openaiApiKey'] = getOpenaiApiKey();
     config['ollamaApiUrl'] = getOllamaApiEndpoint();
+    config['lmStudioApiUrl'] = getLMStudioApiEndpoint();
     config['anthropicApiKey'] = getAnthropicApiKey();
     config['groqApiKey'] = getGroqApiKey();
     config['geminiApiKey'] = getGeminiApiKey();
@@ -74,6 +76,7 @@ router.post('/', async (req, res) => {
     },
     API_ENDPOINTS: {
       OLLAMA: config.ollamaApiUrl,
+      LMSTUDIO: config.lmStudioApiUrl,
     },
   };