package com.zy.ai.service.impl;
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import com.alibaba.fastjson.JSON;
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import com.alibaba.fastjson.JSONObject;
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import com.zy.ai.entity.AiPromptTemplate;
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import com.zy.ai.entity.ChatCompletionRequest;
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import com.zy.ai.entity.ChatCompletionResponse;
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import com.zy.ai.enums.AiPromptScene;
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import com.zy.ai.mcp.service.SpringAiMcpToolManager;
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import com.zy.ai.service.AiPromptTemplateService;
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import com.zy.ai.service.AutoTuneAgentService;
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import com.zy.ai.service.LlmChatService;
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import lombok.RequiredArgsConstructor;
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import lombok.extern.slf4j.Slf4j;
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import org.springframework.stereotype.Service;
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import java.util.ArrayList;
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import java.util.LinkedHashMap;
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import java.util.List;
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@Slf4j
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@Service
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@RequiredArgsConstructor
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public class AutoTuneAgentServiceImpl implements AutoTuneAgentService {
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private static final int MAX_TOOL_ROUNDS = 10;
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private static final double TEMPERATURE = 0.2D;
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private static final int MAX_TOKENS = 2048;
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private final LlmChatService llmChatService;
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private final SpringAiMcpToolManager mcpToolManager;
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private final AiPromptTemplateService aiPromptTemplateService;
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@Override
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public AutoTuneAgentResult runAutoTune(String triggerType) {
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String normalizedTriggerType = normalizeTriggerType(triggerType);
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UsageCounter usageCounter = new UsageCounter();
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int toolCallCount = 0;
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boolean maxRoundsReached = false;
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StringBuilder summaryBuffer = new StringBuilder();
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try {
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List<Object> tools = mcpToolManager.buildOpenAiTools();
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if (tools == null || tools.isEmpty()) {
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throw new IllegalStateException("No MCP tools registered");
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}
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AiPromptTemplate promptTemplate = aiPromptTemplateService.resolvePublished(AiPromptScene.AUTO_TUNE_DISPATCH.getCode());
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List<ChatCompletionRequest.Message> messages = buildMessages(promptTemplate, normalizedTriggerType);
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for (int round = 0; round < MAX_TOOL_ROUNDS; round++) {
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ChatCompletionResponse response = llmChatService.chatCompletion(messages, TEMPERATURE, MAX_TOKENS, tools);
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ChatCompletionRequest.Message assistantMessage = extractAssistantMessage(response);
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usageCounter.add(response.getUsage());
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messages.add(assistantMessage);
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appendSummary(summaryBuffer, assistantMessage.getContent());
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List<ChatCompletionRequest.ToolCall> toolCalls = assistantMessage.getTool_calls();
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if (toolCalls == null || toolCalls.isEmpty()) {
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return buildResult(true, normalizedTriggerType, summaryBuffer, toolCallCount, usageCounter, false);
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}
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for (ChatCompletionRequest.ToolCall toolCall : toolCalls) {
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Object toolOutput = callMountedTool(toolCall);
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toolCallCount++;
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messages.add(buildToolMessage(toolCall, toolOutput));
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}
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}
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maxRoundsReached = true;
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return buildResult(true, normalizedTriggerType, summaryBuffer, toolCallCount, usageCounter, maxRoundsReached);
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} catch (Exception exception) {
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log.error("Auto tune agent stopped with error", exception);
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appendSummary(summaryBuffer, "自动调参 Agent 执行异常: " + exception.getMessage());
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return buildResult(false, normalizedTriggerType, summaryBuffer, toolCallCount, usageCounter, maxRoundsReached);
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}
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}
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private List<ChatCompletionRequest.Message> buildMessages(AiPromptTemplate promptTemplate, String triggerType) {
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List<ChatCompletionRequest.Message> messages = new ArrayList<>();
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ChatCompletionRequest.Message systemMessage = new ChatCompletionRequest.Message();
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systemMessage.setRole("system");
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systemMessage.setContent(promptTemplate == null ? "" : promptTemplate.getContent());
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messages.add(systemMessage);
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ChatCompletionRequest.Message userMessage = new ChatCompletionRequest.Message();
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userMessage.setRole("user");
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userMessage.setContent("请执行一次后台 WCS 自动调参。triggerType=" + triggerType
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+ "。必须先调用 wcs_local_dispatch_get_auto_tune_snapshot 获取事实；如需提交变更，"
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+ "必须先 dry-run，再根据 dry-run 结果决定是否实际应用。不要输出自由格式 JSON 供外层解析。");
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messages.add(userMessage);
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return messages;
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}
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private ChatCompletionRequest.Message extractAssistantMessage(ChatCompletionResponse response) {
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if (response == null || response.getChoices() == null || response.getChoices().isEmpty()) {
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throw new IllegalStateException("LLM returned empty response");
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}
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ChatCompletionRequest.Message message = response.getChoices().get(0).getMessage();
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if (message == null) {
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throw new IllegalStateException("LLM returned empty message");
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}
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return message;
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}
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private Object callMountedTool(ChatCompletionRequest.ToolCall toolCall) {
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String toolName = resolveToolName(toolCall);
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JSONObject arguments = parseArguments(toolCall);
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try {
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return mcpToolManager.callTool(toolName, arguments);
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} catch (Exception exception) {
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LinkedHashMap<String, Object> error = new LinkedHashMap<>();
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error.put("tool", toolName);
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error.put("error", exception.getMessage());
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return error;
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}
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}
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private ChatCompletionRequest.Message buildToolMessage(ChatCompletionRequest.ToolCall toolCall, Object toolOutput) {
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ChatCompletionRequest.Message toolMessage = new ChatCompletionRequest.Message();
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toolMessage.setRole("tool");
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toolMessage.setTool_call_id(toolCall == null ? null : toolCall.getId());
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toolMessage.setContent(JSON.toJSONString(toolOutput));
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return toolMessage;
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}
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private String resolveToolName(ChatCompletionRequest.ToolCall toolCall) {
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if (toolCall == null || toolCall.getFunction() == null || isBlank(toolCall.getFunction().getName())) {
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throw new IllegalArgumentException("missing tool name");
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}
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return toolCall.getFunction().getName();
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}
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private JSONObject parseArguments(ChatCompletionRequest.ToolCall toolCall) {
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String rawArguments = toolCall == null || toolCall.getFunction() == null
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? null
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: toolCall.getFunction().getArguments();
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if (isBlank(rawArguments)) {
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return new JSONObject();
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}
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try {
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return JSON.parseObject(rawArguments);
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} catch (Exception exception) {
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JSONObject arguments = new JSONObject();
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arguments.put("_raw", rawArguments);
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return arguments;
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}
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}
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private AutoTuneAgentResult buildResult(boolean success,
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String triggerType,
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StringBuilder summaryBuffer,
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int toolCallCount,
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UsageCounter usageCounter,
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boolean maxRoundsReached) {
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AutoTuneAgentResult result = new AutoTuneAgentResult();
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result.setSuccess(success);
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result.setTriggerType(triggerType);
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result.setToolCallCount(toolCallCount);
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result.setLlmCallCount(usageCounter.getLlmCallCount());
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result.setPromptTokens(usageCounter.getPromptTokens());
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result.setCompletionTokens(usageCounter.getCompletionTokens());
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result.setTotalTokens(usageCounter.getTotalTokens());
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result.setMaxRoundsReached(maxRoundsReached);
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String summary = summaryBuffer == null ? "" : summaryBuffer.toString().trim();
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if (toolCallCount <= 0 && success) {
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summary = "自动调参 Agent 未调用任何 MCP 工具，未执行调参。" + (summary.isEmpty() ? "" : "\n" + summary);
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}
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if (maxRoundsReached) {
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summary = summary + "\n自动调参 Agent 达到最大工具调用轮次，已停止。";
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}
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result.setSummary(summary);
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return result;
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}
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private void appendSummary(StringBuilder summaryBuffer, String content) {
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if (summaryBuffer == null || isBlank(content)) {
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return;
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}
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if (summaryBuffer.length() > 0) {
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summaryBuffer.append('\n');
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}
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summaryBuffer.append(content.trim());
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}
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private String normalizeTriggerType(String triggerType) {
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return isBlank(triggerType) ? "agent" : triggerType.trim();
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}
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private boolean isBlank(String value) {
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return value == null || value.trim().isEmpty();
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}
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private static class UsageCounter {
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private long promptTokens;
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private long completionTokens;
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private long totalTokens;
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private int llmCallCount;
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void add(ChatCompletionResponse.Usage usage) {
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llmCallCount++;
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if (usage == null) {
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return;
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}
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promptTokens += usage.getPromptTokens() == null ? 0L : usage.getPromptTokens();
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completionTokens += usage.getCompletionTokens() == null ? 0L : usage.getCompletionTokens();
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totalTokens += usage.getTotalTokens() == null ? 0L : usage.getTotalTokens();
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}
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long getPromptTokens() {
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return promptTokens;
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}
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long getCompletionTokens() {
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return completionTokens;
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}
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long getTotalTokens() {
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return totalTokens;
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}
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int getLlmCallCount() {
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return llmCallCount;
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}
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}
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}
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