fixed hardcoded embeddingDims (#3537)

docs/components/embedders/models/azure_openai.mdx

@@ -117,9 +117,20 @@ Refer to [Azure Identity troubleshooting tips](https://github.com/Azure/azure-sd
 ### Config
 
 Here are the parameters available for configuring Azure OpenAI embedder:
-
+<Tabs>
+<Tab title="Python">
 | Parameter | Description | Default Value |
 | --- | --- | --- |
 | `model` | The name of the embedding model to use | `text-embedding-3-small` |
 | `embedding_dims` | Dimensions of the embedding model | `1536` |
 | `azure_kwargs` | The Azure OpenAI configs | `config_keys` |
+</Tab>
+<Tab title="TypeScript">
+| Parameter         | Description                                   | Default Value              |
+| ----------------- | --------------------------------------------- | -------------------------- |
+| `model`           | The name of the embedding model to use        | `text-embedding-3-small`   |
+| `embeddingDims`   | Dimensions of the embedding model             | `1536`                     |
+| `apiKey`          | Azure OpenAI API key                          | `None`                     |
+| `modelProperties` | Object containing endpoint and other settings | `{ endpoint: "",...rest   }`|
+</Tab>
+</Tabs>

docs/components/embedders/models/google_AI.mdx

@@ -38,13 +38,13 @@ import { Memory } from 'mem0ai/oss';
 
 const config = {
   embedder: {
-    provider: 'google',
-    config: {
-      apiKey: process.env.GOOGLE_API_KEY || '',
-      model: 'text-embedding-004',
-      // The output dimensionality is fixed at 768 for Google AI embeddings
+      provider: "google",
+      config: {
+        apiKey: process.env["GOOGLE_API_KEY"],
+        model: "gemini-embedding-001",
+        embeddingDims: 1536,
+      },
     },
-  },
 };
 
 const memory = new Memory(config);
@@ -61,9 +61,19 @@ await memory.add(messages, { userId: "john" });
 ### Config
 
 Here are the parameters available for configuring Gemini embedder:
-
-| Parameter | Description | Default Value |
-| --- | --- | --- |
-| `model` | The name of the embedding model to use | `models/text-embedding-004` |
-| `embedding_dims` | Dimensions of the embedding model (output_dimensionality will be considered as embedding_dims, so please set embedding_dims accordingly) | `768` |
-| `api_key` | The Google API key | `None` |
+<Tabs>
+<Tab title="Python">
+| Parameter        | Description                          | Default Value           |
+| ---------------- | ------------------------------------ | ----------------------- |
+| `model`          | The name of the embedding model to use| `models/text-embedding-004` |
+| `embedding_dims` | Dimensions of the embedding model     | `1536`                  |
+| `api_key`        | The Google API key                   | `None`                  |
+</Tab>
+<Tab title="TypeScript">
+| Parameter         | Description                                   | Default Value              |
+| ----------------- | --------------------------------------------- | -------------------------- |
+| `model`           | The name of the embedding model to use        | `gemini-embedding-001`     |
+| `embeddingDims`   | Dimensions of the embedding model             | `1536`                     |
+| `apiKey`          | Google API key                                | `None`                     |
+</Tab>
+</Tabs>

docs/components/embedders/models/ollama.mdx

@@ -69,5 +69,6 @@ Here are the parameters available for configuring Ollama embedder:
 | --- | --- | --- |
 | `model` | The name of the Ollama model to use | `nomic-embed-text:latest` |
 | `url` | Base URL for Ollama server | `http://localhost:11434` |
+| `embeddingDims` | Dimensions of the embedding model | 768
 </Tab>
 </Tabs>

docs/v0x/components/embedders/models/azure_openai.mdx

@@ -23,7 +23,7 @@ config = {
     "embedder": {
         "provider": "azure_openai",
         "config": {
-            "model": "text-embedding-3-large"
+            "model": "text-embedding-3-large",
             "azure_kwargs": {
                   "api_version": "",
                   "azure_deployment": "",
@@ -117,9 +117,20 @@ Refer to [Azure Identity troubleshooting tips](https://github.com/Azure/azure-sd
 ### Config
 
 Here are the parameters available for configuring Azure OpenAI embedder:
-
+<Tabs>
+<Tab title="Python">
 | Parameter | Description | Default Value |
 | --- | --- | --- |
 | `model` | The name of the embedding model to use | `text-embedding-3-small` |
 | `embedding_dims` | Dimensions of the embedding model | `1536` |
 | `azure_kwargs` | The Azure OpenAI configs | `config_keys` |
+</Tab>
+<Tab title="TypeScript">
+| Parameter         | Description                                   | Default Value              |
+| ----------------- | --------------------------------------------- | -------------------------- |
+| `model`           | The name of the embedding model to use        | `text-embedding-3-small`   |
+| `embeddingDims`   | Dimensions of the embedding model             | `1536`                     |
+| `apiKey`          | Azure OpenAI API key                          | `None`                     |
+| `modelProperties` | Object containing endpoint and other settings | `{ endpoint: "",...rest   }`|
+</Tab>
+</Tabs>

docs/v0x/components/embedders/models/google_AI.mdx

@@ -38,13 +38,13 @@ import { Memory } from 'mem0ai/oss';
 
 const config = {
   embedder: {
-    provider: 'google',
-    config: {
-      apiKey: process.env.GOOGLE_API_KEY || '',
-      model: 'text-embedding-004',
-      // The output dimensionality is fixed at 768 for Google AI embeddings
+      provider: "google",
+      config: {
+        apiKey: process.env["GOOGLE_API_KEY"],
+        model: "gemini-embedding-001",
+        embeddingDims: 1536,
+      },
     },
-  },
 };
 
 const memory = new Memory(config);
@@ -62,8 +62,19 @@ await memory.add(messages, { userId: "john" });
 
 Here are the parameters available for configuring Gemini embedder:
 
-| Parameter | Description | Default Value |
-| --- | --- | --- |
-| `model` | The name of the embedding model to use | `models/text-embedding-004` |
-| `embedding_dims` | Dimensions of the embedding model (output_dimensionality will be considered as embedding_dims, so please set embedding_dims accordingly) | `768` |
-| `api_key` | The Google API key | `None` |
+<Tabs>
+<Tab title="Python">
+| Parameter        | Description                          | Default Value           |
+| ---------------- | ------------------------------------ | ----------------------- |
+| `model`          | The name of the embedding model to use| `models/text-embedding-004` |
+| `embedding_dims` | Dimensions of the embedding model     | `1536`                  |
+| `api_key`        | The Google API key                   | `None`                  |
+</Tab>
+<Tab title="TypeScript">
+| Parameter         | Description                                   | Default Value              |
+| ----------------- | --------------------------------------------- | -------------------------- |
+| `model`           | The name of the embedding model to use        | `gemini-embedding-001`     |
+| `embeddingDims`   | Dimensions of the embedding model             | `1536`                     |
+| `apiKey`          | Google API key                                | `None`                     |
+</Tab>
+</Tabs>

docs/v0x/components/embedders/models/ollama.mdx

@@ -69,5 +69,6 @@ Here are the parameters available for configuring Ollama embedder:
 | --- | --- | --- |
 | `model` | The name of the Ollama model to use | `nomic-embed-text:latest` |
 | `url` | Base URL for Ollama server | `http://localhost:11434` |
+| `embeddingDims` | Dimensions of the embedding model | 768 |
 </Tab>
 </Tabs>

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>;
 }