Patch bad models endpoint path in LM Studio embedding engine (#2628)

* patch bad models endpoint path in lm studio embedding engine

* convert to OpenAI wrapper compatibility

* add URL force parser/validation for LMStudio connections

* remove comment

---------

Co-authored-by: timothycarambat <rambat1010@gmail.com>

server/utils/AiProviders/lmStudio/index.js

@@ -11,7 +11,7 @@ class LMStudioLLM {
 
     const { OpenAI: OpenAIApi } = require("openai");
     this.lmstudio = new OpenAIApi({
-      baseURL: process.env.LMSTUDIO_BASE_PATH?.replace(/\/+$/, ""), // here is the URL to your LMStudio instance
+      baseURL: parseLMStudioBasePath(process.env.LMSTUDIO_BASE_PATH), // here is the URL to your LMStudio instance
       apiKey: null,
     });
 
@@ -173,6 +173,23 @@ class LMStudioLLM {
   }
 }
 
+/**
+ * Parse the base path for the LMStudio API. Since the base path must end in /v1 and cannot have a trailing slash,
+ * and the user can possibly set it to anything and likely incorrectly due to pasting behaviors, we need to ensure it is in the correct format.
+ * @param {string} basePath
+ * @returns {string}
+ */
+function parseLMStudioBasePath(providedBasePath = "") {
+  try {
+    const baseURL = new URL(providedBasePath);
+    const basePath = `${baseURL.origin}/v1`;
+    return basePath;
+  } catch (e) {
+    return providedBasePath;
+  }
+}
+
 module.exports = {
   LMStudioLLM,
+  parseLMStudioBasePath,
 };

server/utils/EmbeddingEngines/lmstudio/index.js

@@ -1,3 +1,4 @@
+const { parseLMStudioBasePath } = require("../../AiProviders/lmStudio");
 const { maximumChunkLength } = require("../../helpers");
 
 class LMStudioEmbedder {
@@ -6,10 +7,14 @@ class LMStudioEmbedder {
       throw new Error("No embedding base path was set.");
     if (!process.env.EMBEDDING_MODEL_PREF)
       throw new Error("No embedding model was set.");
-    this.basePath = `${process.env.EMBEDDING_BASE_PATH}/embeddings`;
+
+    const { OpenAI: OpenAIApi } = require("openai");
+    this.lmstudio = new OpenAIApi({
+      baseURL: parseLMStudioBasePath(process.env.EMBEDDING_BASE_PATH),
+      apiKey: null,
+    });
     this.model = process.env.EMBEDDING_MODEL_PREF;
 
-    // Limit of how many strings we can process in a single pass to stay with resource or network limits
     // Limit of how many strings we can process in a single pass to stay with resource or network limits
     this.maxConcurrentChunks = 1;
     this.embeddingMaxChunkLength = maximumChunkLength();
@@ -20,10 +25,9 @@ class LMStudioEmbedder {
   }
 
   async #isAlive() {
-    return await fetch(`${this.basePath}/models`, {
-      method: "HEAD",
-    })
-      .then((res) => res.ok)
+    return await this.lmstudio.models
+      .list()
+      .then((res) => res?.data?.length > 0)
       .catch((e) => {
         this.log(e.message);
         return false;
@@ -55,29 +59,29 @@ class LMStudioEmbedder {
     for (const chunk of textChunks) {
       if (hasError) break; // If an error occurred don't continue and exit early.
       results.push(
-        await fetch(this.basePath, {
-          method: "POST",
-          headers: {
-            "Content-Type": "application/json",
-          },
-          body: JSON.stringify({
+        await this.lmstudio.embeddings
+          .create({
             model: this.model,
             input: chunk,
-          }),
           })
-          .then((res) => res.json())
-          .then((json) => {
-            const embedding = json.data[0].embedding;
+          .then((result) => {
+            const embedding = result.data?.[0]?.embedding;
             if (!Array.isArray(embedding) || !embedding.length)
               throw {
                 type: "EMPTY_ARR",
                 message: "The embedding was empty from LMStudio",
               };
+            console.log(`Embedding length: ${embedding.length}`);
             return { data: embedding, error: null };
           })
-          .catch((error) => {
+          .catch((e) => {
+            e.type =
+              e?.response?.data?.error?.code ||
+              e?.response?.status ||
+              "failed_to_embed";
+            e.message = e?.response?.data?.error?.message || e.message;
             hasError = true;
-            return { data: [], error };
+            return { data: [], error: e };
           })
       );
     }

server/utils/agents/aibitat/providers/ai-provider.js

@@ -16,6 +16,7 @@ const { ChatBedrockConverse } = require("@langchain/aws");
 const { ChatOllama } = require("@langchain/community/chat_models/ollama");
 const { toValidNumber } = require("../../../http");
 const { getLLMProviderClass } = require("../../../helpers");
+const { parseLMStudioBasePath } = require("../../../AiProviders/lmStudio");
 
 const DEFAULT_WORKSPACE_PROMPT =
   "You are a helpful ai assistant who can assist the user and use tools available to help answer the users prompts and questions.";
@@ -169,7 +170,7 @@ class Provider {
       case "lmstudio":
         return new ChatOpenAI({
           configuration: {
-            baseURL: process.env.LMSTUDIO_BASE_PATH?.replace(/\/+$/, ""),
+            baseURL: parseLMStudioBasePath(process.env.LMSTUDIO_BASE_PATH),
           },
           apiKey: "not-used", // Needs to be specified or else will assume OpenAI
           ...config,

server/utils/agents/aibitat/providers/lmstudio.js

@@ -2,6 +2,9 @@ const OpenAI = require("openai");
 const Provider = require("./ai-provider.js");
 const InheritMultiple = require("./helpers/classes.js");
 const UnTooled = require("./helpers/untooled.js");
+const {
+  parseLMStudioBasePath,
+} = require("../../../AiProviders/lmStudio/index.js");
 
 /**
  * The agent provider for the LMStudio.
@@ -18,7 +21,7 @@ class LMStudioProvider extends InheritMultiple([Provider, UnTooled]) {
     const model =
       config?.model || process.env.LMSTUDIO_MODEL_PREF || "Loaded from Chat UI";
     const client = new OpenAI({
-      baseURL: process.env.LMSTUDIO_BASE_PATH?.replace(/\/+$/, ""), // here is the URL to your LMStudio instance
+      baseURL: parseLMStudioBasePath(process.env.LMSTUDIO_BASE_PATH),
       apiKey: null,
       maxRetries: 3,
     });

server/utils/helpers/customModels.js

@@ -5,6 +5,7 @@ const { togetherAiModels } = require("../AiProviders/togetherAi");
 const { fireworksAiModels } = require("../AiProviders/fireworksAi");
 const { ElevenLabsTTS } = require("../TextToSpeech/elevenLabs");
 const { fetchNovitaModels } = require("../AiProviders/novita");
+const { parseLMStudioBasePath } = require("../AiProviders/lmStudio");
 const SUPPORT_CUSTOM_MODELS = [
   "openai",
   "localai",
@@ -235,7 +236,9 @@ async function getLMStudioModels(basePath = null) {
   try {
     const { OpenAI: OpenAIApi } = require("openai");
     const openai = new OpenAIApi({
-      baseURL: basePath || process.env.LMSTUDIO_BASE_PATH,
+      baseURL: parseLMStudioBasePath(
+        basePath || process.env.LMSTUDIO_BASE_PATH
+      ),
       apiKey: null,
     });
     const models = await openai.models