* @param langs Languages
     * @param analyzer Analyzer
     * @return True if the search word is excluded
     */
    protected boolean isExcludeSearchword(final String searchWord, final String field, final String[] langs,
            final SuggestAnalyzer analyzer) {
        if (langs == null || langs.length == 0) {
            final List<AnalyzeToken> tokens = analyzer.analyze(searchWord, "", null);

        protected final String contentsAnalyzer;
        /** Contents reading analyzer name. */
        protected final String contentsReadingAnalyzer;

        /**
         * Constructor.
         * @param readingAnalyzer Reading analyzer name
         * @param readingTermAnalyzer Reading term analyzer name
         * @param normalizeAnalyzer Normalize analyzer name
         * @param contentsAnalyzer Contents analyzer name

    abstract val textReportFile: RegularFileProperty

    @get:Inject
    abstract val workerExecutor: WorkerExecutor

    @get:Inject
    abstract val layout: ProjectLayout

    @TaskAction
    fun analyze() = workerExecutor.processIsolation { classpath.from(additionalClasspath) }.submit(IncubatingApiReportWorkAction::class) {
        repositoryRoot = layout.settingsDirectory
        srcDirs.from(******@****.***s)

### Examples

Use American English spelling, for example:

* `color` (not `colour`)
* `initialize` (not `initialise`)
* `behavior` (not `behaviour`)
* `analyze` (not `analyse`)
* `organization` (not `organisation`)
* `center` (not `centre`)
* `canceled` (not `cancelled`)
* `labeled` (not `labelled`)

### Rationale for American English

What FastAPI actually checks is that it is a "callable" (function, class or anything else) and the parameters defined.

If you pass a "callable" as a dependency in **FastAPI**, it will analyze the parameters for that "callable", and process them in the same way as the parameters for a *path operation function*. Including sub-dependencies.

Later you will see how **powerful** it can be.

/// tip

The fact that this is **standard Python** means that you will still get the **best possible developer experience** in your editor, with the tools you use to analyze and refactor your code, etc. ✨

And also that your code will be very compatible with many other Python tools and libraries. 🚀

///

## Type hints in **FastAPI** { #type-hints-in-fastapi }

        assertTrue(analyzerNames.contains(settings.analyzer().getNormalizeAnalyzerName("", "")));

        for (final String lang : settings.analyzer().SUPPORTED_LANGUAGES) {
            assertTrue(analyzerNames.contains(settings.analyzer().getContentsAnalyzerName("", lang)));
            assertTrue(analyzerNames.contains(settings.analyzer().getContentsReadingAnalyzerName("", lang)));

labels.chat_messages_area=Chat messages
labels.chat_welcome_title=Ask and Discover.
labels.chat_welcome_description=Ask questions and I'll search through documents to find the answers you need.
labels.chat_step_intent=Analyze
labels.chat_step_search=Search
labels.chat_step_evaluate=Evaluate
labels.chat_step_fetch=Retrieve
labels.chat_step_answer=Answer
labels.chat_input_hint=Press Enter to send, Shift+Enter for new line

        SuggestAnalyzer analyzer = suggester.settings().analyzer().new DefaultContentsAnalyzer();
        String text = "これはテストです。検索エンジン。";

        List<AnalyzeToken> tokens = defaultContentsParser.analyzeTextByReading(analyzer, "content", text, null);

        assertNotNull(tokens);
        // analyzeAndReading may return null for some analyzers
        // Just verify it doesn't throw an exception
    }

labels.chat_messages_area=Chat messages
labels.chat_welcome_title=Ask and Discover.
labels.chat_welcome_description=Ask questions and I'll search through documents to find the answers you need.
labels.chat_step_intent=Analyze
labels.chat_step_search=Search
labels.chat_step_evaluate=Evaluate
labels.chat_step_fetch=Retrieve
labels.chat_step_answer=Answer
labels.chat_input_hint=Press Enter to send, Shift+Enter for new line