public ChatClient() {
        // Default constructor
    }

    /**
     * Checks if RAG chat is available.
     *
     * @return true if RAG chat is available
     */
    public boolean isAvailable() {
        final boolean available = llmClientManager.available();
        if (logger.isTraceEnabled()) {
            logger.trace("[RAG] ChatClient availability check. available={}", available);
        }
        return available;

            logger.warn("[RAG] Failed to process chat request. message={}", e.getMessage(), e);
            writeJsonResponse(response, HttpServletResponse.SC_INTERNAL_SERVER_ERROR, createErrorResponse("Internal server error"));
        }
    }

    /**
     * Processes a streaming chat request using Server-Sent Events (SSE).
     * Uses the enhanced multi-phase RAG flow with intent detection and result evaluation.

import org.codelibs.fess.util.RenderDataUtil;
import org.lastaflute.web.Execute;
import org.lastaflute.web.response.HtmlResponse;

import jakarta.annotation.Resource;

/**
 * Action class for the RAG chat page.
 *
 * @author FessProject
 */
public class ChatAction extends FessSearchAction {

    private static final Logger logger = LogManager.getLogger(ChatAction.class);

    /**
     * Default constructor.

 * 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.
     *

            httpClient = null;
        }
    }

    /**
     * Starts periodic availability checking if RAG chat is enabled.
     */
    protected void startAvailabilityCheck() {
        if (!isRagChatEnabled()) {
            if (logger.isDebugEnabled()) {
                logger.debug("RAG chat is disabled. Skipping availability check.");
            }
            return;
        }

     * Path to the service account credentials JSON file.
     */
    @Size(max = 1000)
    public String storageCredentialsPath;

    /**
     * RAG LLM provider name.
     * Selects which LLM client to use for RAG operations.
     */
    @Size(max = 100)
    public String ragLlmName;

    /**
     * LLM log level.
     * Controls the logging level for LLM-related packages.
     */

     */
    protected String getLlmType() {
        return ComponentUtil.getFessConfig().getSystemProperty("rag.llm.name", "ollama");
    }

    /**
     * Checks if RAG chat feature is enabled.
     *
     * @return true if RAG chat is enabled, false otherwise
     */
    protected boolean isRagChatEnabled() {
        return ComponentUtil.getFessConfig().isRagChatEnabled();

import org.codelibs.fess.util.ComponentUtil;
import org.junit.jupiter.api.Test;
import org.junit.jupiter.api.TestInfo;

/**
 * Unit tests for {@link ChatApiManager}.
 * Tests the RAG chat API endpoints including SSE streaming.
 */
public class ChatApiManagerTest extends UnitFessTestCase {

    private ChatApiManager chatApiManager;

    @Override

#                                                  RAG Chat
#                                                     ------

# Whether RAG chat feature is enabled.
rag.chat.enabled=false


# Chat generation settings.
rag.chat.context.max.documents=5

# Session settings.
rag.chat.session.timeout.minutes=30
rag.chat.session.max.size=10000
rag.chat.history.max.messages=30

    @Resource
    protected OsddHelper osddHelper;

    /** Helper for managing popular search words and suggestions. */
    @Resource
    protected PopularWordHelper popularWordHelper;

    /** Client for RAG chat functionality. */
    @Resource
    protected ChatClient chatClient;

    /** The HTTP servlet request object for the current request. */
    @Resource
    protected HttpServletRequest request;