fixed hardcoded embeddingDims (#3537)

mem0-ts/src/oss/src/embeddings/azure.ts

@@ -5,6 +5,7 @@ import { EmbeddingConfig } from "../types";
 export class AzureOpenAIEmbedder implements Embedder {
   private client: AzureOpenAI;
   private model: string;
+  private embeddingDims?: number;
 
   constructor(config: EmbeddingConfig) {
     if (!config.apiKey || !config.modelProperties?.endpoint) {
@@ -19,6 +20,7 @@ export class AzureOpenAIEmbedder implements Embedder {
       ...rest,
     });
     this.model = config.model || "text-embedding-3-small";
+    this.embeddingDims = config.embeddingDims || 1536;
   }
 
   async embed(text: string): Promise<number[]> {

mem0-ts/src/oss/src/embeddings/google.ts

@@ -5,17 +5,21 @@ import { EmbeddingConfig } from "../types";
 export class GoogleEmbedder implements Embedder {
   private google: GoogleGenAI;
   private model: string;
+  private embeddingDims?: number;
 
   constructor(config: EmbeddingConfig) {
-    this.google = new GoogleGenAI({ apiKey: config.apiKey });
-    this.model = config.model || "text-embedding-004";
+    this.google = new GoogleGenAI({
+      apiKey: config.apiKey || process.env.GOOGLE_API_KEY,
+    });
+    this.model = config.model || "gemini-embedding-001";
+    this.embeddingDims = config.embeddingDims || 1536;
   }
 
   async embed(text: string): Promise<number[]> {
     const response = await this.google.models.embedContent({
       model: this.model,
       contents: text,
-      config: { outputDimensionality: 768 },
+      config: { outputDimensionality: this.embeddingDims },
     });
     return response.embeddings![0].values!;
   }

mem0-ts/src/oss/src/embeddings/ollama.ts

@@ -6,6 +6,7 @@ import { logger } from "../utils/logger";
 export class OllamaEmbedder implements Embedder {
   private ollama: Ollama;
   private model: string;
+  private embeddingDims?: number;
   // Using this variable to avoid calling the Ollama server multiple times
   private initialized: boolean = false;
 
@@ -14,6 +15,7 @@ export class OllamaEmbedder implements Embedder {
       host: config.url || "http://localhost:11434",
     });
     this.model = config.model || "nomic-embed-text:latest";
+    this.embeddingDims = config.embeddingDims || 768;
     this.ensureModelExists().catch((err) => {
       logger.error(`Error ensuring model exists: ${err}`);
     });

mem0-ts/src/oss/src/embeddings/openai.ts

@@ -5,10 +5,12 @@ import { EmbeddingConfig } from "../types";
 export class OpenAIEmbedder implements Embedder {
   private openai: OpenAI;
   private model: string;
+  private embeddingDims?: number;
 
   constructor(config: EmbeddingConfig) {
     this.openai = new OpenAI({ apiKey: config.apiKey });
     this.model = config.model || "text-embedding-3-small";
+    this.embeddingDims = config.embeddingDims || 1536;
   }
 
   async embed(text: string): Promise<number[]> {

mem0-ts/src/oss/src/types/index.ts

@@ -16,6 +16,7 @@ export interface EmbeddingConfig {
   apiKey?: string;
   model?: string | any;
   url?: string;
+  embeddingDims?: number;
   modelProperties?: Record<string, any>;
 }