package org.codelibs.fess.llm;

import java.util.List;
import java.util.Map;

/**
 * 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

        assertEquals("ollama", request.getAttribute(Constants.SEARCH_LOG_ACCESS_TYPE));
    }

    @Test
    public void test_mockRequest_attributeOverwrite() {
        final MockHttpServletRequest request = new MockHttpServletRequest();

        request.setAttribute(Constants.SEARCH_LOG_ACCESS_TYPE, "ollama");

    }

    @Test
    public void test_addSearchLog_accessType_ollama() {
        final SearchLog searchLog = callCreateSearchLogAndGetResult("ollama");
        assertEquals("ollama", searchLog.getAccessType());
    }

    @Test
    public void test_addSearchLog_accessType_openai() {
        final SearchLog searchLog = callCreateSearchLogAndGetResult("openai");

            // Set LLM type name as Access Type for search log
            request.setAttribute(Constants.SEARCH_LOG_ACCESS_TYPE,
                    ComponentUtil.getFessConfig().getSystemProperty("rag.llm.name", "ollama"));

            final Map<String, String[]> fields = parseFieldFilters(request);
            final String[] extraQueries = parseExtraQueries(request);
            final ChatResult result;

    /**
     * Gets the configured LLM type from the system configuration.
     *
     * @return The LLM type string from configuration (e.g., "ollama", "openai", "gemini")
     */
    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

    default void setRagLlmName(final String value) {
        setSystemProperty(Constants.RAG_LLM_NAME, value);
    }

    default String getRagLlmName() {
        return getSystemProperty(Constants.RAG_LLM_NAME, "ollama");
    }

    Integer getLdapMaxUsernameLengthAsInteger();

    default String getLdapSecurityPrincipal(final String username) {
        final String value;

                .addAssistantMessage("Hi there!")
                .addUserMessage("How are you?")
                .setModel("llama3")
                .setMaxTokens(500)
                .setTemperature(0.5)
                .setStream(false);

        assertEquals(4, request.getMessages().size());
        assertEquals("llama3", request.getModel());
        assertEquals(Integer.valueOf(500), request.getMaxTokens());

    }

    @Test
    public void test_setModel() {
        final LlmChatResponse response = new LlmChatResponse();

        response.setModel("llama3");
        assertEquals("llama3", response.getModel());

        response.setModel("gpt-3.5-turbo");
        assertEquals("gpt-3.5-turbo", response.getModel());
    }

    @Test
    public void test_nullValues() {

labels.popular_word_word_enabled=Respons Kata Populer
labels.supported_search_web=Web
labels.supported_search_none=Tidak Tersedia
labels.purge_search_log_day=Hapus log pencarian lama
labels.purge_job_log_day=Hapus log job lama
labels.purge_user_info_day=Hapus log pengguna lama
labels.purge_by_bots=Nama bot untuk menghapus log
labels.log_level=Level Log
labels.csv_file_encoding=Encoding Berkas CSV
labels.notification_to=Email Notifikasi

"kepada", "kepadanya", "ketika", "seketika", "khususnya", "kini", "kinilah", "kiranya", "sekiranya", "kita", "kitalah", "kok", "lagi", "lagian", "selagi", "lah", "lain", "lainnya", "melainkan", "selaku", "lalu", "melalui", "terlalu", "lama", "lamanya", "selama", "selama", "selamanya", "lebih", "terlebih", "bermacam", "macam", "semacam", "maka", "makanya", "makin", "malah", "malahan", "mampu", "mampukah", "mana", "manakala", "manalagi", "masih", "masihkah", "semasih", "masing", "mau", "maupun", "semaunya",...