}

    @Inject
    protected ExecOperations getExecOperations() {
        throw new UnsupportedOperationException();
    }

    public void execute(Action<VagrantExecSpec> action) {
        VagrantExecSpec vagrantSpec = new VagrantExecSpec();
        action.execute(vagrantSpec);

        Objects.requireNonNull(vagrantSpec.command);

        LoggedExec.exec(getExecOperations(), execSpec -> {

        String result = thumbnailJob.execute();

        assertNotNull(result);
        // The result should contain Session Id with the generated session ID
        assertNotNull(thumbnailJob.sessionId);
        assertTrue(result.contains("Session Id:"));

        // The test cannot actually start the process since it requires many dependencies
        // The execute method catches the exception and returns the session ID

        if (timeoutMillis < 0) {
            throw new IllegalArgumentException("Timeout must be non-negative");
        }
    }

    /**
     * Execute a callable through the circuit breaker
     *
     * @param <T> return type
     * @param callable the callable to execute
     * @return the result
     * @throws Exception if execution fails or circuit is open
     */

    //                                                                      Search Execute
    //                                                                      ==============
    /**
     * Displays the general error page.
     *
     * @param form the error form containing error information
     * @return HTML response for the error page
     */
    @Execute
    public HtmlResponse index(final ErrorForm form) {

import org.codelibs.fess.helper.SearchHelper;
import org.codelibs.fess.opensearch.client.SearchEngineClient;
import org.codelibs.fess.util.ComponentUtil;
import org.lastaflute.web.Execute;
import org.lastaflute.web.response.JsonResponse;
import org.opensearch.index.query.QueryBuilder;
import org.opensearch.index.query.QueryBuilders;

import jakarta.annotation.Resource;

/**

programs that TensorFlow executes. TensorFlow programs are encoded as
computation
[**graphs**](https://developers.google.com/machine-learning/glossary/#graph).
Since models are practically programs that TensorFlow executes, using untrusted
models or graphs is equivalent to running untrusted code.

If you need to run untrusted models, execute them inside a

 *      </td>
 *   </tr>
 *   <tr>
 *      <td>execute</td>
 *      <td>@Execute
 *       ( phase=LifecyclePhase.&lt;phase&gt;, goal= "&lt;goal-name&gt;", lifecycle="&lt;lifecycle-id&gt;" )</td>
 *      <td>No</td>
 *      <td>When this goal is invoked, it will first invoke a parallel lifecycle, ending at the given phase.
 *          If a goal is provided instead of a phase, that goal will be executed in isolation.

    //                                                                      Search Execute
    //                                                                      ==============
    /**
     * Displays the system error page.
     *
     * @param form the error form containing error information
     * @return HTML response for the system error page
     */
    @Execute
    public HtmlResponse index(final ErrorForm form) {

import org.codelibs.fess.sso.SsoManager;
import org.codelibs.fess.sso.SsoResponseType;
import org.codelibs.fess.util.ComponentUtil;
import org.dbflute.optional.OptionalThing;
import org.lastaflute.web.Execute;
import org.lastaflute.web.UrlChain;
import org.lastaflute.web.login.credential.LoginCredential;
import org.lastaflute.web.login.exception.LoginFailureException;
import org.lastaflute.web.response.ActionResponse;

    //                                                                      Search Execute
    //                                                                      ==============

    /**
     * Retrieves the list of available log files.
     *
     * @return JSON response containing log file list
     */
    // GET /api/admin/log/files
    @Execute
    public JsonResponse<ApiResult> files() {