return config.searchFieldSet != null && config.searchFieldSet.contains(field);
    }

    /**
     * Gets the query languages from the current request.
     * @return An optional containing the query languages array, or empty if not available.
     */
    protected OptionalThing<String[]> getQueryLanguages() {
        return LaRequestUtil.getOptionalRequest()

 * to the specific provider interface being implemented.
 * <p>
 * Example implementation for a custom language provider:
 * <pre>
 * public class CustomLanguageProvider implements LanguageProvider {
 *     public Collection&lt;Language&gt; provides() {
 *         return Arrays.asList(
 *             language("kotlin"),
 *             language("scala")
 *         );
 *     }
 * }
 * </pre>
 *

     * @param normalizer the normalizer to use for normalizing the search words
     * @param analyzer the analyzer to use for analyzing the search words
     * @param langs the array of languages associated with the search words
     * @return a SuggestItem created from the given search words and associated data
     */

            } else {
                searchLog.setAccessType(Constants.SEARCH_LOG_ACCESS_TYPE_WEB);
            }
            final Object languages = req.getAttribute(Constants.REQUEST_LANGUAGES);
            if (languages != null) {
                searchLog.setLanguages(StringUtils.join((String[]) languages, ","));
            } else {
                searchLog.setLanguages(StringUtil.EMPTY);
            }

This makes it easy to generate up-to-date **documentation**, client libraries (<abbr title="Software Development Kits">**SDKs**</abbr>) in multiple languages, and **testing** or **automation workflows** that stay in sync with your code.

In this guide, you'll learn how to generate a **TypeScript SDK** for your FastAPI backend.

        val applicationStructureChoice = if (descriptor.language === Language.CPP || descriptor.language === Language.SWIFT) "" else """
Select application structure:
  1: Single application project
  2: Application and library project
Enter selection (default: Single application project) [1..2] 1
"""
        val toolChain = when {
            descriptor.language === Language.SWIFT -> {

namespace tensorflow {
namespace checkpoint {

class TensorSliceReader;

// A wrapper around BundleReader (for V2 checkpoints) and
// checkpoint::TensorSliceReader (for V1), that is more easily SWIG wrapped for
// other languages.
//
// The class currently only interacts with single-slice (i.e., non-partitioned)
// variables.
class CheckpointReader {
 public:
  CheckpointReader(const string& filename, TF_Status* status);

      matrix:
        # Override automatic language detection by changing the below list
        # Supported options are ['csharp', 'cpp', 'go', 'java', 'javascript', 'python']
        language: ['java', 'javascript']
        # Learn more...
        # https://docs.github.com/en/github/finding-security-vulnerabilities-and-errors-in-your-code/configuring-code-scanning#overriding-automatic-language-detection

    steps:

* **Harder for non-native speakers**: Contributors and users for whom English is a second language benefit from a single, consistent convention

While both American and British English are valid, establishing a single standard improves consistency, readability, and maintainability of the codebase.

## Decision

        }
        return converter.convert(text, field);
    }

    /**
     * Language-specific analyzer converter.
     */
    protected class LangAnalyzerConverter implements ReadingConverter {
        /** Language. */
        protected final String lang;

        /**
         * Constructor.
         * @param lang Language
         */
        protected LangAnalyzerConverter(final String lang) {