diff --git a/libs/langchain-openai/src/azure/azureDallEAPIWrapper.ts b/libs/langchain-openai/src/azure/azureDallEAPIWrapper.ts
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+++ b/libs/langchain-openai/src/azure/azureDallEAPIWrapper.ts
@@ -0,0 +1,258 @@
+import { Tool, ToolParams } from "@langchain/core/tools";
+import {
+  MessageContentComplex,
+  MessageContentImageUrl,
+} from "@langchain/core/messages";
+import { AzureOpenAI } from "openai";
+import type { OpenAI } from "openai";
+
+/**
+ * @see https://platform.openai.com/docs/api-reference/images/create
+ */
+export type OpenAIImageModelId = "dall-e-2" | "dall-e-3";
+
+/**
+ * An interface for the Azure Dall-E API Wrapper.
+ */
+export interface AzureDallEAPIWrapperParams extends ToolParams {
+  /**
+   * The Azure OpenAI API key
+   */
+  apiKey: string;
+
+  /**
+   * The Azure OpenAI api version
+   */
+  apiVersion: string;
+
+  /**
+   * The model to use.
+   * Alias for `model`
+   * @params "dall-e-2" | "dall-e-3"
+   * @default "dall-e-3"
+   * @deprecated Use `model` instead.
+   */
+  modelName?: OpenAIImageModelId;
+  /**
+   * The model to use.
+   * @params "dall-e-2" | "dall-e-3"
+   * @default "dall-e-3"
+   */
+  model?: OpenAIImageModelId;
+  /**
+   * The style of the generated images. Must be one of vivid or natural.
+   * Vivid causes the model to lean towards generating hyper-real and dramatic images.
+   * Natural causes the model to produce more natural, less hyper-real looking images.
+   * @default "vivid"
+   */
+  style?: "natural" | "vivid";
+  /**
+   * The quality of the image that will be generated. ‘hd’ creates images with finer
+   * details and greater consistency across the image.
+   * @default "standard"
+   */
+  quality?: "standard" | "hd";
+  /**
+   * The number of images to generate.
+   * Must be between 1 and 10.
+   * For dall-e-3, only `n: 1` is supported.
+   * @default 1
+   */
+  n?: number;
+  /**
+   * The size of the generated images.
+   * Must be one of 256x256, 512x512, or 1024x1024 for DALL·E-2 models.
+   * Must be one of 1024x1024, 1792x1024, or 1024x1792 for DALL·E-3 models.
+   * @default "1024x1024"
+   */
+  size?: "256x256" | "512x512" | "1024x1024" | "1792x1024" | "1024x1792";
+  /**
+   * The format in which the generated images are returned.
+   * Must be one of "url" or "b64_json".
+   * @default "url"
+   */
+  dallEResponseFormat?: "url" | "b64_json";
+  /**
+   * @deprecated Use dallEResponseFormat instead for the Dall-E response type.
+   */
+  // eslint-disable-next-line @typescript-eslint/no-explicit-any
+  responseFormat?: any;
+  /**
+   * A unique identifier representing your end-user, which will help
+   * OpenAI to monitor and detect abuse.
+   */
+  user?: string;
+  /**
+   * The organization to use
+   */
+  organization?: string;
+  /**
+   * The base URL of the OpenAI API.
+   */
+  baseUrl?: string;
+}
+
+/**
+ * A tool for generating images with Open AIs Dall-E 2 or 3 API.
+ */
+export class AzureDallEAPIWrapper extends Tool {
+  static lc_name() {
+    return "DallEAPIWrapper";
+  }
+
+  name = "dalle_api_wrapper";
+
+  description =
+    "A wrapper around OpenAI DALL-E API. Useful for when you need to generate images from a text description. Input should be an image description.";
+
+  protected client: AzureOpenAI;
+
+  static readonly toolName = "dalle_api_wrapper";
+
+  private model = "dall-e-3";
+
+  private style: "natural" | "vivid" = "vivid";
+
+  private quality: "standard" | "hd" = "standard";
+
+  private n = 1;
+
+  private size:
+    | "256x256"
+    | "512x512"
+    | "1024x1024"
+    | "1792x1024"
+    | "1024x1792" = "1024x1024";
+
+  private dallEResponseFormat: "url" | "b64_json" = "url";
+
+  private user?: string;
+
+  constructor(params: AzureDallEAPIWrapperParams) {
+    // Shim for new base tool param name
+    if (
+      params.responseFormat !== undefined &&
+      ["url", "b64_json"].includes(params.responseFormat)
+    ) {
+      // eslint-disable-next-line @typescript-eslint/no-explicit-any
+      params.dallEResponseFormat = params.responseFormat as any;
+      params.responseFormat = "content";
+    }
+    super(params);
+
+    this.client = new AzureOpenAI({
+      apiKey: params.apiKey,
+      apiVersion: params.apiVersion,
+      deployment: this.model,
+    });
+    this.model = params.model ?? this.model;
+    this.style = params.style ?? this.style;
+    this.quality = params.quality ?? this.quality;
+    this.n = params.n ?? this.n;
+    this.size = params.size ?? this.size;
+    this.dallEResponseFormat =
+      params.dallEResponseFormat ?? this.dallEResponseFormat;
+    this.user = params.user;
+  }
+
+  /**
+   * Processes the API response if multiple images are generated.
+   * Returns a list of MessageContentImageUrl objects. If the response
+   * format is `url`, then the `image_url` field will contain the URL.
+   * If it is `b64_json`, then the `image_url` field will contain an object
+   * with a `url` field with the base64 encoded image.
+   *
+   * @param {OpenAIClient.Images.ImagesResponse[]} response The API response
+   * @returns {MessageContentImageUrl[]}
+   */
+  private processMultipleGeneratedUrls(
+    response: OpenAI.Images.ImagesResponse[]
+  ): MessageContentImageUrl[] {
+    if (this.dallEResponseFormat === "url") {
+      return response.flatMap((res) => {
+        const imageUrlContent =
+          res.data
+            ?.flatMap((item) => {
+              if (!item.url) return [];
+              return {
+                type: "image_url" as const,
+                image_url: item.url,
+              };
+            })
+            .filter(
+              (item) =>
+                item !== undefined &&
+                item.type === "image_url" &&
+                typeof item.image_url === "string" &&
+                item.image_url !== undefined
+            ) ?? [];
+        return imageUrlContent;
+      });
+    } else {
+      return response.flatMap((res) => {
+        const b64Content =
+          res.data
+            ?.flatMap((item) => {
+              if (!item.b64_json) return [];
+              return {
+                type: "image_url" as const,
+                image_url: {
+                  url: item.b64_json,
+                },
+              };
+            })
+            .filter(
+              (item) =>
+                item !== undefined &&
+                item.type === "image_url" &&
+                typeof item.image_url === "object" &&
+                "url" in item.image_url &&
+                typeof item.image_url.url === "string" &&
+                item.image_url.url !== undefined
+            ) ?? [];
+        return b64Content;
+      });
+    }
+  }
+
+  /** @ignore */
+  async _call(input: string): Promise<string | MessageContentComplex[]> {
+    const generateImageFields = {
+      model: this.model,
+      prompt: input,
+      n: 1,
+      size: this.size,
+      response_format: this.dallEResponseFormat,
+      style: this.style,
+      quality: this.quality,
+      user: this.user,
+    };
+
+    if (this.n > 1) {
+      const results = await Promise.all(
+        Array.from({ length: this.n }).map(() =>
+          this.client.images.generate(generateImageFields)
+        )
+      );
+
+      return this.processMultipleGeneratedUrls(results);
+    }
+
+    const response = await this.client.images.generate(generateImageFields);
+
+    let data = "";
+    if (this.dallEResponseFormat === "url") {
+      [data] =
+        response.data
+          ?.map((item) => item.url)
+          .filter((url): url is string => url !== "undefined") ?? [];
+    } else {
+      [data] =
+        response.data
+          ?.map((item) => item.b64_json)
+          .filter((b64_json): b64_json is string => b64_json !== "undefined") ??
+        [];
+    }
+    return data;
+  }
+}