* the standard Fess file transformation process with support for various content types.
 *
 * <p>It extends AbstractFessFileTransformer to provide file-specific transformation
 * capabilities while using the appropriate extractor for each document type.</p>
 */
public class FessStandardTransformer extends AbstractFessFileTransformer {
    /**
     * Default constructor.
     */
    public FessStandardTransformer() {
        super();
    }

        return super.createAccessResult(responseData, ingest(responseData, resultData));
    }

    /**
     * Processes the result data through all available ingesters.
     * Each ingester can transform and enrich the data before it is indexed.
     *
     * @param responseData the response data from the crawled resource
     * @param resultData the result data to be processed

## Structure

Each platform and module has its own source directory under [platforms/](../platforms).
In these source directories, you will find the Gradle projects that make up the platform or module.

The platforms and modules are defined using a DSL in [settings.gradle.kts](../settings.gradle.kts)

 *
 * This interface defines the contract for SSO authentication providers that can be
 * integrated with Fess. Implementations handle specific SSO protocols like SAML,
 * OAuth, SPNEGO, or other authentication mechanisms. Each authenticator is responsible
 * for obtaining login credentials, resolving user information, and managing SSO
 * lifecycle operations like logout and metadata exchange.
 */
public interface SsoAuthenticator {

    /**

 */
package org.codelibs.fess.llm;

/**
 * Callback interface for receiving streaming chat responses from LLM.
 */
@FunctionalInterface
public interface LlmStreamCallback {

    /**
     * Called for each chunk of the streaming response.
     *
     * @param chunk the text chunk from the LLM response
     * @param done true if this is the final chunk
     */
    void onChunk(String chunk, boolean done);

    /**

 * Implementations provide integration with different LLM providers
 * such as Ollama, OpenAI, and Google Gemini.
 *
 * In addition to low-level chat operations, this interface defines
 * high-level RAG workflow methods that allow each provider to optimize
 * prompt construction, parameter tuning, and response parsing.
 */
public interface LlmClient {

    /**
     * Performs a chat completion request.
     *

      if ($submitButton.size() > 0) {
        $submitButton[0].submit();
      }
      // ignore enter key down
      return false;
    }
  });

  $(".table tr[data-href]").each(function() {
    $(this)
      .css("cursor", "pointer")
      .hover(
        function() {
          $(this).addClass("active");
        },
        function() {
          $(this).removeClass("active");

        item1.id = 100L;
        item2.id = 200L;

        assertEquals(100L, item1.getId());
        assertEquals(200L, item2.getId());

        // Verify they don't affect each other
        item1.id = 300L;
        assertEquals(300L, item1.getId());
        assertEquals(200L, item2.getId());
    }

    @Test
    public void test_constructor() {

* The [Gradle Tooling API client](https://docs.gradle.org/8.8/userguide/third_party_integration.html#embedding)
  * This requires a Java application, and thus runtime, to run the tooling API client

As indicated, each of those components require a Java runtime to run.

The recommended way of invoking Gradle is to use the Gradle Wrapper.

        Map<String, CtClass> result = [:]
        collect(result, c)
        return result
    }

    private void collect(Map<String, CtClass> result, CtClass c) {
        c.interfaces.each { result.put(it.name, it) }

        if (c.superclass != null) {
            collect(result, c.superclass)
        }
    }

    private List<String> filterChangesToReport(CtClass c, Map<String, CtClass> interfaces) {