In this article, we will learn how to run Cognitive Service Text Analytics for Health in a Web App for Containers. We can deploy Azure Cognitive Services to Docker containers. This enables us to increase performance by running cognitive services close to our data, controlling where data gets processed, and using cognitive services in a portable solution. 

Implementation:

Follow the below steps to run cognitive service text analytics in a web app for containers:

Step 1: First, we need to create a Text Analytics service resource. The cognitive service in the container image will use this to report billing data too.

Step 2: Select a resource group, and now we’ll fill in a name. Pick a pricing tier. We also need to agree to the responsible AI notice. Let’s create it.

Step 3: In the Text Analytics service. To enable the container to send billing data to it, we need a couple of things. We need the API key from here and also the service endpoint.

Step 4: Let’s create a container. We’ll do that using a Power Shell script in the Azure Cloud Shell. We can also use the Azure CLI for this. The scripts will create a new Azure App Service web app for containers, and it will create a container in there with this image. This is a cognitive service image for the Text Analytics health feature. We’ve also filled in the key and endpoint for the service in Azure. 

There it goes and we can find its URL in the web app for containers.

Step 5: Let’s take a look. The health feature of the Text Analytics Service has a demo feature. Just add /demo to access it. Now, this feature analyzes text for health-related phrases like illness, treatment, and medication. Let’s try with a  sentence.  It identified these phrases with their meanings. It used the Cognitive Service that runs in a container, in the Web App for Containers.

 Hence, this is how we can run cognitive service text analytics in a web app for containers.

Advantages of Azure Web:

1. Scalability: Azure Web App Containers can scale up or down based on demand, which means you can easily handle large volumes of text data without worrying about infrastructure or capacity constraints.
2. Cost-Effective: Azure Cognitive Services Text Analytics is a cost-effective way to add natural language processing capabilities to your applications. You only pay for what you use, and you don’t need to invest in expensive hardware or software licenses.
3. Improved User Experience: By extracting key information from unstructured text data, you can provide a better user experience to your customers. For example, you can analyze customer feedback to identify common issues and improve your products or services accordingly.
4. Advanced Natural Language Processing: Text Analytics provides advanced natural language processing capabilities to extract key information from unstructured text data. This can help you gain insights into customer feedback, social media sentiment, and other unstructured data sources that would be difficult to analyze manually.
5. Easy Integration: Text Analytics can be easily integrated into Azure Web App Containers using pre-built SDKs, which can save time and effort compared to building natural language processing capabilities from scratch.