diff --git a/src/components/Sidepanel/Settings/body.tsx b/src/components/Sidepanel/Settings/body.tsx
index 89410bc..dc36baa 100644
--- a/src/components/Sidepanel/Settings/body.tsx
+++ b/src/components/Sidepanel/Settings/body.tsx
@@ -11,7 +11,8 @@ import {
   defaultEmbeddingChunkOverlap,
   defaultEmbeddingChunkSize,
   defaultEmbeddingModelForRag,
-  saveForRag
+  saveForRag,
+  getEmbeddingModels
 } from "~/services/ollama"
 
 import {
@@ -77,7 +78,7 @@ export const SettingsBody = () => {
         getOllamaURL(),
         systemPromptForNonRag(),
         promptForRag(),
-        getAllModels({ returnEmpty: true }),
+        getEmbeddingModels({ returnEmpty: true }),
         defaultEmbeddingChunkOverlap(),
         defaultEmbeddingChunkSize(),
         defaultEmbeddingModelForRag(),
diff --git a/src/hooks/useMessage.tsx b/src/hooks/useMessage.tsx
index 18cceb5..c85324a 100644
--- a/src/hooks/useMessage.tsx
+++ b/src/hooks/useMessage.tsx
@@ -539,7 +539,7 @@ export const useMessage = () => {
       if (selectedPrompt) {
         applicationChatHistory.unshift(
           new SystemMessage({
-            content:  selectedPrompt.content
+            content: selectedPrompt.content
           })
         )
       }
diff --git a/src/models/OAIEmbedding.ts b/src/models/OAIEmbedding.ts
index 7617021..c7b8a25 100644
--- a/src/models/OAIEmbedding.ts
+++ b/src/models/OAIEmbedding.ts
@@ -1,52 +1,21 @@
 import { type ClientOptions, OpenAI as OpenAIClient } from "openai"
-import { Embeddings, type EmbeddingsParams } from "@langchain/core/embeddings"
+import { Embeddings, EmbeddingsParams } from "@langchain/core/embeddings"
 import { chunkArray } from "@langchain/core/utils/chunk_array"
 import { OpenAICoreRequestOptions, LegacyOpenAIInput } from "./types"
 import { wrapOpenAIClientError } from "./utils/openai"
 
-/**
- * Interface for OpenAIEmbeddings parameters. Extends EmbeddingsParams and
- * defines additional parameters specific to the OpenAIEmbeddings class.
- */
 export interface OpenAIEmbeddingsParams extends EmbeddingsParams {
-    /**
-     * Model name to use
-     * Alias for `model`
-     */
     modelName: string
-    /** Model name to use */
     model: string
-
-    /**
-     * The number of dimensions the resulting output embeddings should have.
-     * Only supported in `text-embedding-3` and later models.
-     */
     dimensions?: number
-
-    /**
-     * Timeout to use when making requests to OpenAI.
-     */
     timeout?: number
-
-    /**
-     * The maximum number of documents to embed in a single request. This is
-     * limited by the OpenAI API to a maximum of 2048.
-     */
     batchSize?: number
-
-    /**
-     * Whether to strip new lines from the input text. This is recommended by
-     * OpenAI for older models, but may not be suitable for all use cases.
-     * See: https://github.com/openai/openai-python/issues/418#issuecomment-1525939500
-     */
     stripNewLines?: boolean
-
     signal?: AbortSignal
 }
 
 export class OAIEmbedding
-    extends Embeddings
-    implements OpenAIEmbeddingsParams {
+    extends Embeddings {
     modelName = "text-embedding-ada-002"
 
     model = "text-embedding-ada-002"
@@ -81,7 +50,7 @@ export class OAIEmbedding
     protected client: OpenAIClient
 
     protected clientConfig: ClientOptions
-    
+
     signal?: AbortSignal
 
     constructor(
@@ -107,7 +76,7 @@ export class OAIEmbedding
         this.modelName =
             fieldsWithDefaults?.model ?? fieldsWithDefaults?.modelName ?? this.model
         this.model = this.modelName
-        this.batchSize = fieldsWithDefaults?.batchSize
+        this.batchSize = fieldsWithDefaults?.batchSize || this.batchSize
         this.stripNewLines = fieldsWithDefaults?.stripNewLines ?? this.stripNewLines
         this.timeout = fieldsWithDefaults?.timeout
         this.dimensions = fieldsWithDefaults?.dimensions
@@ -127,15 +96,12 @@ export class OAIEmbedding
             ...configuration,
             ...fields?.configuration
         }
+
+
+        // initialize the client
+        this.client = new OpenAIClient(this.clientConfig)
     }
 
-    /**
-     * Method to generate embeddings for an array of documents. Splits the
-     * documents into batches and makes requests to the OpenAI API to generate
-     * embeddings.
-     * @param texts Array of documents to generate embeddings for.
-     * @returns Promise that resolves to a 2D array of embeddings for each document.
-     */
     async embedDocuments(texts: string[]): Promise<number[][]> {
         const batches = chunkArray(
             this.stripNewLines ? texts.map((t) => t.replace(/\n/g, " ")) : texts,
@@ -165,12 +131,6 @@ export class OAIEmbedding
         return embeddings
     }
 
-    /**
-     * Method to generate an embedding for a single document. Calls the
-     * embeddingWithRetry method with the document as the input.
-     * @param text Document to generate an embedding for.
-     * @returns Promise that resolves to an embedding for the document.
-     */
     async embedQuery(text: string): Promise<number[]> {
         const params: OpenAIClient.EmbeddingCreateParams = {
             model: this.model,
@@ -183,16 +143,19 @@ export class OAIEmbedding
         return data[0].embedding
     }
 
-    /**
-     * Private method to make a request to the OpenAI API to generate
-     * embeddings. Handles the retry logic and returns the response from the
-     * API.
-     * @param request Request to send to the OpenAI API.
-     * @returns Promise that resolves to the response from the API.
-     */
+    async _embed(texts: string[]): Promise<number[][]> {
+        const embeddings: number[][] = await Promise.all(
+            texts.map((text) => this.caller.call(() => this.embedQuery(text)))
+        )
+
+        return embeddings
+    }
+
+
     protected async embeddingWithRetry(
         request: OpenAIClient.EmbeddingCreateParams
     ) {
+
         const requestOptions: OpenAICoreRequestOptions = {}
         if (this.azureOpenAIApiKey) {
             requestOptions.headers = {
diff --git a/src/utils/memory-embeddings.ts b/src/utils/memory-embeddings.ts
index 8d0decc..99d2be4 100644
--- a/src/utils/memory-embeddings.ts
+++ b/src/utils/memory-embeddings.ts
@@ -47,12 +47,11 @@ export const memoryEmbedding = async ({
   type: string
   pdf: { content: string; page: number }[]
   keepTrackOfEmbedding: Record<string, MemoryVectorStore>
-  ollamaEmbedding: OllamaEmbeddings
+  ollamaEmbedding: any
   setIsEmbedding: (value: boolean) => void
   setKeepTrackOfEmbedding: (value: Record<string, MemoryVectorStore>) => void
 }) => {
   setIsEmbedding(true)
-
   const loader = getLoader({ html, pdf, type, url })
   const docs = await loader.load()
   const chunkSize = await defaultEmbeddingChunkSize()