Merge pull request #2894 from aahill/foundry-docs-3

updating docker page

Author: JillGrant615

articles/ai-services/containers/docker-compose-recipe.md

@@ -7,21 +7,20 @@ author: aahill
 manager: nitinme
 ms.service: azure-ai-services
 ms.topic: how-to
-ms.date: 11/06/2024
+ms.date: 02/12/2025
 ms.author: aahi
 
 # SME: Brendan Walsh
 #Customer intent: As a potential customer, I want to know how to configure containers so I can reuse them.
 ---
 
-# Use Docker Compose to deploy multiple containers
+# Use Docker Compose to deploy multiple Azure AI containers
 
-This article shows you how to deploy multiple Azure AI containers. Specifically, you'll learn how to use Docker Compose to orchestrate multiple Docker container images.
+This article shows you how to deploy multiple Azure AI containers. Specifically, you'll learn how to use Docker Compose to orchestrate multiple Docker container images on a single host computer. The example in this article is deploying a [Document Intelligence](../document-intelligence/overview.md) container and a [AI Vision read](../computer-vision/how-to/call-read-api.md) container together.
 
+> [!NOTE] 
 > [Docker Compose](https://docs.docker.com/compose/) is a tool for defining and running multi-container Docker applications. In Compose, you use a YAML file to configure your application's services. Then, you create and start all the services from your configuration by running a single command.
 
-It can be useful to orchestrate multiple container images on a single host computer. In this article, we'll pull together the Read and Document Intelligence containers.
-
 ## Prerequisites
 
 This procedure requires several tools that must be installed and run locally:
@@ -36,13 +35,16 @@ This procedure requires several tools that must be installed and run locally:
 
 ## Docker Compose file
 
-The YAML file defines all the services to be deployed. These services rely on either a `DockerFile` or an existing container image. In this case, we'll use two preview images. Copy and paste the following YAML file, and save it as *docker-compose.yaml*. Provide the appropriate **apikey**, **billing**, and **EndpointUri** values in the file.
+The YAML file defines all the Azure AI services containers to be deployed. These services rely on either a `DockerFile` or an existing container image. In this case, we'll use two images. Copy and paste the following YAML file, and save it as *docker-compose.yaml*. Provide the appropriate **apikey**, **billing**, and **EndpointUri** values in the file.
+
+> [!IMPORTANT]
+> Be sure to create the directories on the host machine that are specified under the `volumes` node, or provide ones that exist on your machine. These directories must exist before you try to mount an image by using volume bindings.
 
 ```yaml
 version: '3.7'
 services:
   forms:
-    image: "mcr.microsoft.com/azure-cognitive-services/form-recognizer/layout"
+    image: "mcr.microsoft.com/azure-cognitive-services/form-recognizer/layout-3.1:latest"
     environment:
        eula: accept
        billing: # < Your Document Intelligence billing URL >
@@ -51,16 +53,16 @@ services:
        FormRecognizer__ComputerVisionEndpointUri: # < Your Document Intelligence URI >
     volumes:
        - type: bind
-         source: E:\publicpreview\output
+         source: E:\mydirectory\output
          target: /output
        - type: bind
-         source: E:\publicpreview\input
+         source: E:\mydirectory\input
          target: /input
     ports:
       - "5010:5000"
 
   ocr:
-    image: "mcr.microsoft.com/azure-cognitive-services/vision/read:3.1-preview"
+    image: "mcr.microsoft.com/azure-cognitive-services/vision/read:latest"
     environment:
       eula: accept
       apikey: # < Your Azure AI Vision API key >
@@ -69,16 +71,10 @@ services:
       - "5021:5000"
 ```
 
-> [!IMPORTANT]
-> Create the directories on the host machine that are specified under the **volumes** node. This approach is required because the directories must exist before you try to mount an image by using volume bindings.
-
 ## Start the configured Docker Compose services
 
 A Docker Compose file enables the management of all the stages in a defined service's life cycle: starting, stopping, and rebuilding services; viewing the service status; and log streaming. Open a command-line interface from the project directory (where the docker-compose.yaml file is located).
 
-> [!NOTE]
-> To avoid errors, make sure that the host machine correctly shares drives with Docker Engine. For example, if *E:\publicpreview* is used as a directory in the *docker-compose.yaml* file, share drive **E** with Docker.
-
 From the command-line interface, execute the following command to start (or restart) all the services defined in the *docker-compose.yaml* file:
 
 ```console
@@ -152,19 +148,19 @@ ocr_1    | Application started. Press Ctrl+C to shut down.
 
 [!INCLUDE [Tip for using docker list](../includes/cognitive-services-containers-docker-list-tip.md)]
 
-Here's some example output:
+Here's some example outputs:
 
 ```
 IMAGE ID            REPOSITORY                                                                 TAG
-2ce533f88e80        mcr.microsoft.com/azure-cognitive-services/form-recognizer/layout          latest
+2ce533f88e80        mcr.microsoft.com/azure-cognitive-services/form-recognizer/layout-3.1      latest
 4be104c126c5        mcr.microsoft.com/azure-cognitive-services/vision/read:3.1-preview         latest
 ```
 
 ### Test containers
 
-Open a browser on the host machine and go to **localhost** by using the specified port from the *docker-compose.yaml* file, such as http://localhost:5021/swagger/index.html. For example, you could use the **Try It** feature in the API to test the Document Intelligence endpoint. Both containers swagger pages should be available and testable.
+Open a browser on the host machine and go to **localhost** by using the specified port from the *docker-compose.yaml* file, such as `http://localhost:5021`. Both containers' landing pages should be available.
 
-![Document Intelligence Container](media/form-recognizer-swagger-page.png)
+:::image type="content" source="../media/container-webpage.png" alt-text="A screenshot of the container landing page.":::
 
 ## Next steps