use supervisor agent for complex chat
This commit is contained in:
@@ -397,11 +397,25 @@ public class ChatService {
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.subAgents(List.of(planner, executor, verifier))
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.build();
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String plannerPlan = callAgent(planner, buildPlannerInput(question, retryContext), config);
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answer = callAgent(executor, buildExecutorInput(question, plannerPlan, retryContext), config);
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String supervisorInput = buildSupervisorInput(question, retryContext);
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Optional<OverAllState> stateOptional = supervisor.invoke(supervisorInput, config);
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if (stateOptional.isEmpty()) {
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finalDecision = buildVerifierFallbackDecision(round, "supervisor 未返回有效状态");
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answer = buildLowConfidenceOutput(answer, finalDecision);
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persistVerifierEvaluation(session, finalDecision, round);
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break;
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}
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String plannerPlan = extractStateText(stateOptional, "planner_plan");
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answer = extractStateText(stateOptional, "executor_feedback");
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VerifierContextHolder.setExecutorFinalAnswer(answer);
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String verifierOutput = callAgent(verifier, "VERIFY", config);
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String verifierOutput = extractStateText(stateOptional, "verifier_output");
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finalDecision = parseVerifierDecision(verifierOutput, round);
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logger.debug("Supervisor round {} finished: plannerPlanLength={}, answerLength={}, verifierOutputLength={}",
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round,
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plannerPlan != null ? plannerPlan.length() : 0,
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answer != null ? answer.length() : 0,
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verifierOutput != null ? verifierOutput.length() : 0);
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if (finalDecision == null) {
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finalDecision = buildVerifierFallbackDecision(round, "verifier_output 缺失或无法解析");
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@@ -530,10 +544,6 @@ public class ChatService {
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.build();
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}
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private String callAgent(ReactAgent agent, String input, RunnableConfig config) throws GraphRunnerException {
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return agent.call(input, config).getText();
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}
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private String resolveSessionId(String requestedSessionId) {
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if (requestedSessionId != null && !requestedSessionId.isBlank()) {
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return requestedSessionId;
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@@ -558,21 +568,14 @@ public class ChatService {
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return session;
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}
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private String buildPlannerInput(String question, String retryContext) {
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if (retryContext == null || retryContext.isBlank()) {
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return question;
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}
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return question + "\n\n--- 补充约束 ---\n" + retryContext;
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}
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private String buildExecutorInput(String question, String plannerPlan, String retryContext) {
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StringBuilder input = new StringBuilder(question);
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if (plannerPlan != null && !plannerPlan.isBlank()) {
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input.append("\n\n--- planner_plan ---\n").append(plannerPlan);
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}
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private String buildSupervisorInput(String question, String retryContext) {
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StringBuilder input = new StringBuilder();
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input.append("请按 supervisor 系统提示完成本轮 Planner -> Executor -> Verifier 编排。\n\n");
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input.append("--- 用户问题 ---\n").append(question);
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if (retryContext != null && !retryContext.isBlank()) {
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input.append("\n\n--- retry_context ---\n").append(retryContext);
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}
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input.append("\n\n完成 verifier 后立即 FINISH,不要额外生成最终答案。");
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return input.toString();
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}
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@@ -674,55 +677,20 @@ public class ChatService {
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""".formatted(round);
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}
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private String buildRoundInput(String question, String retryContext) {
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if (retryContext == null || retryContext.isBlank()) {
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return question;
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}
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return question + "\n\n--- 补充约束 ---\n" + retryContext;
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}
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private String extractExecutorAnswer(Optional<OverAllState> stateOptional) {
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private String extractStateText(Optional<OverAllState> stateOptional, String key) {
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if (stateOptional.isEmpty()) {
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return null;
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}
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return stateOptional.get().value("executor_feedback")
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.filter(AssistantMessage.class::isInstance)
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.map(AssistantMessage.class::cast)
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.map(AssistantMessage::getText)
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return stateOptional.get().value(key)
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.map(value -> {
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if (value instanceof AssistantMessage assistantMessage) {
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return assistantMessage.getText();
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}
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return String.valueOf(value);
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})
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.orElse(null);
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}
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private VerifierDecision parseVerifierDecision(Optional<OverAllState> stateOptional, int round) {
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if (stateOptional.isEmpty()) {
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return null;
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}
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Optional<AssistantMessage> verifierOutput = stateOptional.get().value("verifier_output")
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.filter(AssistantMessage.class::isInstance)
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.map(AssistantMessage.class::cast);
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if (verifierOutput.isEmpty() || verifierOutput.get().getText() == null || verifierOutput.get().getText().isBlank()) {
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return null;
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}
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try {
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JsonNode root = objectMapper.readTree(verifierOutput.get().getText());
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List<Map<String, Object>> factsChecked = parseFactsChecked(root.path("facts_checked"));
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return new VerifierDecision(
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root.path("verdict").asText("LOW_CONFID"),
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root.path("groundedness_score").asDouble(0.0),
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root.path("critical_fact_count").asInt(0),
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factsChecked,
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root.path("rationale").asText(""),
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round
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);
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} catch (Exception e) {
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logger.error("解析 verifier_output 失败: {}", verifierOutput.get().getText(), e);
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return null;
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}
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}
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private void persistVerifierEvaluation(DiagnosisSession session, VerifierDecision decision, int round) {
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if (decision == null) {
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return;
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@@ -0,0 +1,136 @@
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package com.superbiz.agent.service;
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import com.superbiz.agent.agent.tool.DateTimeTools;
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import com.superbiz.agent.agent.tool.QueryLogsTools;
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import com.superbiz.agent.domain.entity.AgentStep;
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import com.superbiz.agent.domain.entity.DiagnosisSession;
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import com.superbiz.agent.repository.AgentStepRepository;
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import com.superbiz.agent.repository.DiagnosisSessionRepository;
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import com.superbiz.agent.tool.LookupKnowledgeTool;
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import com.superbiz.agent.tool.RetrievedDocTracker;
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import org.junit.jupiter.api.Test;
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import org.springframework.ai.chat.messages.AssistantMessage;
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import org.springframework.ai.chat.model.ChatModel;
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import org.springframework.ai.chat.model.ChatResponse;
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import org.springframework.ai.chat.model.Generation;
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import org.springframework.ai.chat.prompt.Prompt;
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import org.springframework.ai.tool.ToolCallback;
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import org.springframework.test.util.ReflectionTestUtils;
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import java.util.List;
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import java.util.Map;
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import java.util.Optional;
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import java.util.concurrent.atomic.AtomicInteger;
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import static org.junit.jupiter.api.Assertions.assertEquals;
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import static org.junit.jupiter.api.Assertions.assertTrue;
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import static org.mockito.ArgumentMatchers.any;
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import static org.mockito.ArgumentMatchers.anyString;
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import static org.mockito.Mockito.mock;
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import static org.mockito.Mockito.when;
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class ChatServiceSupervisorAgentTest {
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@Test
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void executeChatComplexInvokesSupervisorFlow() throws Exception {
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ChatService chatService = new ChatService();
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ScriptedChatModel chatModel = new ScriptedChatModel();
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DiagnosisSessionRepository diagnosisSessionRepository = mock(DiagnosisSessionRepository.class);
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when(diagnosisSessionRepository.findBySessionId(anyString())).thenReturn(Optional.empty());
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when(diagnosisSessionRepository.save(any(DiagnosisSession.class))).thenAnswer(invocation -> invocation.getArgument(0));
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AtomicInteger stepId = new AtomicInteger(1);
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AgentStepRepository agentStepRepository = mock(AgentStepRepository.class);
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when(agentStepRepository.save(any(AgentStep.class))).thenAnswer(invocation -> {
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AgentStep step = invocation.getArgument(0);
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if (step.getId() == null) {
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step.setId((long) stepId.getAndIncrement());
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}
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return step;
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});
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when(agentStepRepository.findById(any())).thenReturn(Optional.of(new AgentStep()));
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when(agentStepRepository.findBySessionIdOrderByStepIndex(anyString())).thenReturn(List.of());
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EvaluationService evaluationService = mock(EvaluationService.class);
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RetrievedDocTracker retrievedDocTracker = mock(RetrievedDocTracker.class);
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KnowledgeDomainService knowledgeDomainService = mock(KnowledgeDomainService.class);
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when(knowledgeDomainService.buildKnowledgeMap()).thenReturn("");
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ToolTraceSummaryService toolTraceSummaryService = mock(ToolTraceSummaryService.class);
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when(toolTraceSummaryService.buildVerifierTraceSummary(anyString(), anyString())).thenReturn(List.of());
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SelfEvaluationMergeService selfEvaluationMergeService = mock(SelfEvaluationMergeService.class);
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when(selfEvaluationMergeService.mergeVerifierEvaluation(any(), any())).thenReturn("{}");
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ReflectionTestUtils.setField(chatService, "dateTimeTools", new DateTimeTools());
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ReflectionTestUtils.setField(chatService, "lookupKnowledgeTool", new LookupKnowledgeTool());
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ReflectionTestUtils.setField(chatService, "queryLogsTools", new QueryLogsTools(mock(ToolInvocationRecorder.class)));
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ReflectionTestUtils.setField(chatService, "diagnosisSessionRepository", diagnosisSessionRepository);
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ReflectionTestUtils.setField(chatService, "agentStepRepository", agentStepRepository);
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ReflectionTestUtils.setField(chatService, "evaluationService", evaluationService);
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ReflectionTestUtils.setField(chatService, "retrievedDocTracker", retrievedDocTracker);
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ReflectionTestUtils.setField(chatService, "knowledgeDomainService", knowledgeDomainService);
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ReflectionTestUtils.setField(chatService, "toolTraceSummaryService", toolTraceSummaryService);
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ReflectionTestUtils.setField(chatService, "selfEvaluationMergeService", selfEvaluationMergeService);
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ReflectionTestUtils.setField(chatService, "verifierLowConfidenceThreshold", 0.5d);
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ReflectionTestUtils.setField(chatService, "chatPlannerPrompt", "PLANNER_TEST_PROMPT");
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ReflectionTestUtils.setField(chatService, "chatExecutorPrompt", "EXECUTOR_TEST_PROMPT");
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ReflectionTestUtils.setField(chatService, "chatVerifierPrompt", "VERIFIER_TEST_PROMPT");
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ChatService.ChatResult result = chatService.executeChatComplex(
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chatModel,
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new ToolCallback[0],
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"请分析订单支付超时的原因,并给出修复建议",
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List.of(),
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"supervisor-test-session"
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);
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assertEquals("EXECUTOR_FINAL_ANSWER", result.answer());
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assertEquals("supervisor-test-session", result.sessionId());
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assertEquals(List.of("chat_planner", "chat_executor", "chat_verifier", "FINISH"), chatModel.decisions);
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assertTrue(chatModel.sawVerifierPrompt);
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}
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private static final class ScriptedChatModel implements ChatModel {
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private final List<String> decisionScript = List.of("chat_planner", "chat_executor", "chat_verifier", "FINISH");
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private final java.util.ArrayList<String> decisions = new java.util.ArrayList<>();
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private int decisionIndex;
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private String promptText = "";
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private boolean sawVerifierPrompt;
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@Override
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public ChatResponse call(Prompt prompt) {
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promptText = prompt.getContents();
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String text;
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if (promptText.contains("Available options:")) {
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text = "{\"agent\":\"" + decisionScript.get(decisionIndex++) + "\"}";
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decisions.add(text.substring(10, text.length() - 2));
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} else if (promptText.contains("PLANNER_TEST_PROMPT")) {
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text = "PLANNER_PLAN";
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} else if (promptText.contains("EXECUTOR_TEST_PROMPT")) {
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text = "EXECUTOR_FINAL_ANSWER";
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} else if (promptText.contains("VERIFIER_TEST_PROMPT")) {
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sawVerifierPrompt = true;
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text = """
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{
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"verdict": "PASS",
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"groundedness_score": 1.0,
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"critical_fact_count": 1,
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"facts_checked": [
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{
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"fact": "executor answer generated",
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"is_critical": true,
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"verification": "direct_evidence",
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"detail": "covered by scripted verifier",
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"evidence_refs": []
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}
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],
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"rationale": "scripted pass"
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}
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""";
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} else {
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text = "UNEXPECTED_PROMPT";
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}
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return new ChatResponse(List.of(new Generation(new AssistantMessage(text))));
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}
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}
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}
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