Using Azure Cognitive Search for portal content

Azure Cognitive Search is a fully managed search-as-a-service solution that enables you to add powerful search capabilities to your applications. It is particularly useful for large-scale applications where you want to provide advanced search features like full-text search, filters, faceted navigation, and relevance ranking. When integrated with a portal, it enhances the user experience by allowing them to quickly and accurately find content.

Here’s a step-by-step guide to integrating Azure Cognitive Search with your portal content:

Step 1: Set Up Azure Cognitive Search

Before integrating with your portal, you need to create and configure an Azure Cognitive Search service.

1.1. Create an Azure Cognitive Search Resource:

Go to the Azure Portal.
Search for Azure Cognitive Search and click on Create.
Fill in the required details such as:
- Subscription
- Resource Group
- Region
- Name (this will be your search service name)
After creating the service, go to the newly created search resource.

1.2. Create an Index:

An index defines the structure of your searchable data. For example, if your portal contains knowledge articles, you might create an index that includes fields like Title, Description, Tags, and Content.

In the Azure Cognitive Search service, go to Indexes and create a new index.
Define fields for the index:
- Title: Searchable (String)
- Description: Searchable (String)
- Tags: Searchable (String)
- Content: Searchable (Text)
You can also define facets, filters, and sorting parameters here.

1.3. Add Data to the Index:

Once the index is created, you’ll need to populate it with data. You can do this via:

Indexing API: Directly upload your data via REST API.
Azure Data Import: Use Azure Blob Storage or SQL databases to import data into the index.

Step 2: Connect Your Portal to Azure Cognitive Search

To allow your portal users to search content, you will need to integrate Azure Cognitive Search into the portal. This can be done using either Azure Search SDK or REST API.

2.1. Integrating Azure Cognitive Search via REST API

You can directly make REST API calls from the portal to fetch search results from Azure Cognitive Search.

Generate API Key: In the Azure Portal, go to your Cognitive Search service, navigate to Keys, and copy one of the API keys.
Make API Calls: Use JavaScript (or any backend technology) to make REST API calls to Azure Cognitive Search.
const endpoint = "https://<YourSearchServiceName>.search.windows.net"; const indexName = "<YourIndexName>"; const apiKey = "<YourApiKey>"; const query = "search query"; // The query from the user input fetch(`${endpoint}/indexes/${indexName}/docs/search?api-version=2021-04-30-Preview`, { method: "POST", headers: { "Content-Type": "application/json", "api-key": apiKey }, body: JSON.stringify({ "search": query, "top": 10, // Number of results per page "select": "title, description, tags", // Fields to return "filter": "", // Optional filtering conditions "orderby": "title" // Optional sorting }) }) .then(response => response.json()) .then(data => { console.log(data); // Render results to the portal }) .catch(error => console.error("Error:", error)); This script will search the data in the indexName and return results based on the search query.

2.2. Displaying Search Results in the Portal

Once the search results are fetched, you will need to render them dynamically in the portal’s user interface. Here’s an example of how you can render the results:

<div id="searchResults"></div>

<script>
  function renderSearchResults(results) {
    const resultsContainer = document.getElementById('searchResults');
    resultsContainer.innerHTML = ''; // Clear previous results

    results.value.forEach(item => {
      const resultItem = document.createElement('div');
      resultItem.className = 'search-result-item';
      resultItem.innerHTML = `
        <h3>${item.title}</h3>
        <p>${item.description}</p>
        <p>Tags: ${item.tags.join(", ")}</p>
      `;
      resultsContainer.appendChild(resultItem);
    });
  }

  // Example results data from the search API
  const exampleResults = {
    "value": [
      {
        "title": "How to Use Azure Search",
        "description": "Learn the basics of Azure Cognitive Search.",
        "tags": ["Azure", "Search", "Cloud"]
      },
      {
        "title": "Building a Searchable Knowledge Base",
        "description": "Step-by-step guide to creating a searchable knowledge base.",
        "tags": ["Knowledge", "Search", "Portal"]
      }
    ]
  };

  renderSearchResults(exampleResults);
</script>

Step 3: Enhance Search Functionality with Filters and Facets

One of the powerful features of Azure Cognitive Search is the ability to add facets and filters to refine the search results based on categories, tags, or other metadata.

3.1. Implement Facets

Facets allow users to filter search results based on specific fields. For instance, you can allow users to filter search results based on tags or categories.

fetch(`${endpoint}/indexes/${indexName}/docs/search?api-version=2021-04-30-Preview`, {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    "api-key": apiKey
  },
  body: JSON.stringify({
    "search": query,
    "top": 10,
    "facets": ["tags"]
  })
})
.then(response => response.json())
.then(data => {
  console.log(data);
  // Display the facets (categories/tags) to the user
})

3.2. Apply Filters

Filters can be added to restrict the results. For example, you can filter results by date or specific tag.

fetch(`${endpoint}/indexes/${indexName}/docs/search?api-version=2021-04-30-Preview`, {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    "api-key": apiKey
  },
  body: JSON.stringify({
    "search": query,
    "filter": "tags eq 'Azure'",
    "top": 10
  })
})
.then(response => response.json())
.then(data => {
  console.log(data);
  // Render filtered results to the portal
})

Step 4: Improve Relevance with Custom Scoring

Azure Cognitive Search allows you to boost the relevance of certain fields or documents based on certain criteria. This can help you prioritize more relevant results for the users.

4.1. Boosting Fields

You can adjust the weight or boost specific fields like title or tags to make them more relevant.

{
  "search": query,
  "scoringProfile": "boostTitle",
  "top": 10
}

In the scoring profile, you can define custom weightings to boost the score of certain fields.

Step 5: Monitor and Optimize Search

Azure Cognitive Search offers monitoring capabilities through Azure Monitor and Application Insights. Track query performance, failures, and usage patterns to continually optimize your search experience.