String stdout,
        String stderr
    ) {
        @Override
        public String toString() {
            return "exitCode=" + exitCode + ", stdout=" + summarize(stdout) + ", stderr=" + summarize(stderr);
        }

        private static String summarize(String s) {
            if (s == null) return "null";
            String t = s.replace("\n", "\\n");

        int returnCode
    ) {
        @Override
        public String toString() {
            return "ExecResult{returnCode=" + returnCode + ", stdout=" + summarize(stdout) + ", stderr=" + summarize(stderr) + "}";
        }

        private static String summarize(String s) {
            if (s == null) return "null";
            String t = s.replace("\n", "\\n");
            if (t.length() > 500) {

            this.stderr = stderr;
        }

        @Override
        public String toString() {
            return "exitCode=" + exitCode + ", stdout=" + summarize(stdout) + ", stderr=" + summarize(stderr);
        }

        private static String summarize(String s) {
            if (s == null) return "null";
            String t = s.replace("\n", "\\n");

        return new IntentDetectionResult(ChatIntent.SEARCH, query, null, reasoning);
    }

    /**
     * Creates a summary intent result for a specific document.
     *
     * @param documentUrl the document URL to summarize
     * @param reasoning the detection reasoning
     * @return the summary intent result
     */
    public static IntentDetectionResult summary(final String documentUrl, final String reasoning) {

    /**
     * Generates a summary of the specified documents.
     *
     * @param userMessage the user's message
     * @param documents the documents to summarize
     * @param history the conversation history
     * @param callback the streaming callback
     */
    void generateSummaryResponse(String userMessage, List<Map<String, Object>> documents, List<LlmMessage> history,

    return methods_.summarize != nullptr;
  }

  absl::Status SummarizeValue(std::string& summary) const override {
    if (methods_.summarize == nullptr) {
      return tensorflow::CustomDeviceTensorHandle::SummarizeValue(summary);
    }
    TF_Status c_status;
    std::unique_ptr<TF_Buffer, decltype(&TF_DeleteBuffer)> summary_buffer(
        methods_.summarize(data_, &c_status), TF_DeleteBuffer);

                    captured.append(msg.getContent());
                }
            }
            callback.onChunk("response", true);
        });

        client.generateSummaryResponse("summarize", documents, history, (chunk, done) -> {});

        final String systemMsg = captured.toString();
        assertTrue(systemMsg.contains("HTML content"));
        assertFalse(systemMsg.contains("<p>"));

    }

    /**
     * Generates a summary of the specified documents.
     *
     * @param userMessage the user's message
     * @param documents the documents to summarize
     * @param history the conversation history
     * @param callback the streaming callback
     * @throws LlmException if LLM is not available
     */

 * forms of variance -- that were computed from a single set of zero or more floating-point values.
 *
 * <p>There are two ways to obtain a {@code Stats} instance:
 *
 * <ul>
 *   <li>If all the values you want to summarize are already known, use the appropriate {@code
 *       Stats.of} factory method below. Primitive arrays, iterables and iterators of any kind of
 *       {@code Number}, and primitive varargs are supported.

        chatClient.setTestSummaryMaxChars(20);
        final ChatSession session = new ChatSession();
        session.addUserMessage("Q1");
        session.addAssistantMessage("This is a fairly long response that should be summarized using smart summary mode.");

        final List<LlmMessage> history = chatClient.testExtractHistory(session);
        assertEquals(2, history.size());
        assertEquals("assistant", history.get(1).getRole());