Merge branch 'main' of https://github.com/llm-tools/embedJs

package.json

@@ -1,6 +1,6 @@
 {
     "name": "@llm-tools/embedjs",
-    "version": "0.0.89",
+    "version": "0.0.90",
     "description": "A NodeJS RAG framework to easily work with LLMs and custom datasets",
     "main": "dist/index.js",
     "types": "dist/index.d.ts",
@@ -59,7 +59,7 @@
         "@huggingface/inference": "^2.7.0",
         "@langchain/anthropic": "^0.2.3",
         "@langchain/cohere": "^0.1.0",
-        "@langchain/community": "^0.2.16",
+        "@langchain/community": "^0.2.17",
         "@langchain/core": "^0.2.12",
         "@langchain/google-vertexai": "^0.0.19",
         "@langchain/mistralai": "^0.0.25",

src/embeddings/ada-embeddings.ts

@@ -1,11 +1,16 @@
-import { OpenAIEmbeddings } from '@langchain/openai';
+import { ClientOptions, OpenAIEmbeddings } from '@langchain/openai';
 import { BaseEmbeddings } from '../interfaces/base-embeddings.js';
 
 export class AdaEmbeddings implements BaseEmbeddings {
     private model: OpenAIEmbeddings;
 
-    constructor() {
-        this.model = new OpenAIEmbeddings({ modelName: 'text-embedding-ada-002', maxConcurrency: 3, maxRetries: 5 });
+    constructor(options?: { configuration?: ClientOptions; maxConcurrency: number; maxRetries: number }) {
+        this.model = new OpenAIEmbeddings({
+            modelName: 'text-embedding-ada-002',
+            configuration: options?.configuration,
+            maxConcurrency: options?.maxConcurrency ?? 3,
+            maxRetries: options?.maxRetries ?? 5,
+        });
     }
 
     getDimensions(): number {

src/embeddings/openai-3large-embeddings.ts

@@ -1,18 +1,23 @@
-import { OpenAIEmbeddings } from '@langchain/openai';
+import { ClientOptions, OpenAIEmbeddings } from '@langchain/openai';
 import { BaseEmbeddings } from '../interfaces/base-embeddings.js';
 
 export class OpenAi3LargeEmbeddings implements BaseEmbeddings {
     private model: OpenAIEmbeddings;
     private readonly dynamicDimension: number;
 
-    constructor(params?: { dynamicDimension?: number }) {
-        this.dynamicDimension = params?.dynamicDimension ?? 3072;
+    constructor(options?: {
+        configuration?: ClientOptions;
+        dynamicDimension?: number;
+        maxConcurrency: number;
+        maxRetries: number;
+    }) {
+        this.dynamicDimension = options?.dynamicDimension ?? 3072;
 
         this.model = new OpenAIEmbeddings({
             modelName: 'text-embedding-3-large',
-            maxConcurrency: 3,
-            maxRetries: 5,
-            dimensions: this.dynamicDimension,
+            configuration: options?.configuration,
+            maxConcurrency: options?.maxConcurrency ?? 3,
+            maxRetries: options?.maxRetries ?? 5,
         });
     }
 

src/embeddings/openai-3small-embeddings.ts

@@ -1,11 +1,16 @@
-import { OpenAIEmbeddings } from '@langchain/openai';
+import { ClientOptions, OpenAIEmbeddings } from '@langchain/openai';
 import { BaseEmbeddings } from '../interfaces/base-embeddings.js';
 
 export class OpenAi3SmallEmbeddings implements BaseEmbeddings {
     private model: OpenAIEmbeddings;
 
-    constructor() {
-        this.model = new OpenAIEmbeddings({ modelName: 'text-embedding-3-small', maxConcurrency: 3, maxRetries: 5 });
+    constructor(options?: { configuration?: ClientOptions; maxConcurrency: number; maxRetries: number }) {
+        this.model = new OpenAIEmbeddings({
+            modelName: 'text-embedding-3-small',
+            configuration: options?.configuration,
+            maxConcurrency: options?.maxConcurrency ?? 3,
+            maxRetries: options?.maxRetries ?? 5,
+        });
     }
 
     getDimensions(): number {