"ihm", "es", "etwas", "euer", "eure", "eurem", "euren", "eurer", "eures", "für", "gegen", "gewesen", "hab", "habe", "haben", "hat", "hatte", "hatten", "hier", "hin", "hinter", "ich", "mich", "mir", "ihr", "ihre", "ihrem", "ihren", "ihrer", "ihres", "euch", "im", "in", "indem", "ins", "ist", "jede", "jedem", "jeden", "jeder", "jedes", "jene", "jenem", "jenen", "jener", "jenes", "jetzt", "kann", "kein", "keine", "keinem", "keinen", "keiner", "keines", "können", "könnte", "machen", "man", "manche", "manchem",...

"ihm", "es", "etwas", "euer", "eure", "eurem", "euren", "eurer", "eures", "für", "gegen", "gewesen", "hab", "habe", "haben", "hat", "hatte", "hatten", "hier", "hin", "hinter", "ich", "mich", "mir", "ihr", "ihre", "ihrem", "ihren", "ihrer", "ihres", "euch", "im", "in", "indem", "ins", "ist", "jede", "jedem", "jeden", "jeder", "jedes", "jene", "jenem", "jenen", "jener", "jenes", "jetzt", "kann", "kein", "keine", "keinem", "keinen", "keiner", "keines", "können", "könnte", "machen", "man", "manche", "manchem",...

/**
 * Interface for LLM (Large Language Model) clients.
 * 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 {

    /**

Fess enthält auch einen Crawler, der Dokumente auf einem [Webserver](https://fess.codelibs.org/15.3/admin/webconfig-guide.html), [Dateisystem](https://fess.codelibs.org/15.3/admin/fileconfig-guide.html) oder [Datenspeicher](https://fess.codelibs.org/15.3/admin/dataconfig-guide.html)...

 * This class manages highlighting parameters such as fragment size, number of fragments,
 * and highlighting type for displaying search query matches in result snippets.
 */
public class HighlightInfo {
    /** The highlighting type (e.g., plain, html). */
    private String type;
    /** The size of each highlighted fragment in characters. */
    private int fragmentSize;

/**
 * A thread that reads from an input stream line by line and maintains a buffer of recent lines.
 * This class provides functionality to read input stream data asynchronously,
 * optionally process each line with a callback function, and maintain a circular buffer
 * of recent lines for retrieval.
 */
public class InputStreamThread extends Thread {
    /** Logger instance for this class */

    }

    /**
     * Scrolls through all documents in the specified index and applies the callback function to each hit.
     *
     * @param index the name of the index to scroll through
     * @param callback the function to apply to each search hit, returning true to continue or false to stop
     * @return the number of documents processed
     */

        assertTrue(result);
        assertEquals("4 indices × 2 creates each (backup + rebuild)", 8, testClient.createdIndices.size());
        assertEquals("4 indices × 2 reindexes each (to backup + from backup)", 8, testClient.reindexPairs.size());
        assertEquals("4 indices × 2 deletes each (old + backup)", 8, testClient.deletedIndices.size());
    }

    @Test

 * and DI container integration.
 *
 * <p>Thread Safety: This class is thread-safe. Each cached entry holds its own
 * GroovyClassLoader. The cache uses Guava Cache with segment-based locking for
 * lock-free concurrent reads. Each evaluate() call creates a new Script instance
 * to ensure thread isolation of bindings.</p>
 *

      if ($submitButton.length > 0) {
        $submitButton.closest("form").trigger("submit");
      }
      return false;
    }
  });

  $(".table tr[data-href]").each(function() {
    var $row = $(this);
    $row.css("cursor", "pointer")
      .on("mouseenter", function() {
        $(this).addClass("active");
      })
      .on("mouseleave", function() {