feat(aihr): wire practice turn/finish to real LLM with seed fallback

/turn 客户回复按人设走 LLM 生成(seed 台词作剧情锚点),/finish 单次
temperature=0 结构化评分(4维+导师改写+点评,档位锚点60/75/90),维度
缺失回落 total、文本截断防落库溢出;模型未配置或调用失败逐级回退
seed,前后端契约不变。会话列表读写同锁,评分只在 finish 跑一次。

backend/ruoyi-modules/ruoyi-aihr/src/main/java/org/dromara/aihr/service/AihrModelSeedService.java

@@ -69,7 +69,9 @@ public class AihrModelSeedService {
             new ConfigResponse(-1L, "chat", DEFAULT_MODEL, DEFAULT_PROVIDER, "Demo 对话与 RAG 生成模型", null, "Y", null, true, false, false),
             new ConfigResponse(-2L, "vector", "embedding-3", "zhipu", "后续用于知识片段向量化", 2048, "N", null, false, false, false),
             new ConfigResponse(-3L, "rerank", "rerank", "zhipu", "后续用于召回片段重排序", null, "N", null, false, false, false),
-            new ConfigResponse(-4L, "vector", "BAAI/bge-m3", "siliconflow", "硅基流动 bge-m3，用于知识片段向量化", 1024, "N", null, false, false, false)
+            new ConfigResponse(-4L, "vector", "BAAI/bge-m3", "siliconflow", "硅基流动 bge-m3，用于知识片段向量化", 1024, "N", null, false, false, false),
+            new ConfigResponse(-5L, "asr", "FunAudioLLM/SenseVoiceSmall", "siliconflow", "语音识别，用于对练语音输入", null, "N", null, false, false, false),
+            new ConfigResponse(-6L, "tts", "FunAudioLLM/CosyVoice2-0.5B", "siliconflow", "语音合成，用于 AI 客户语音播报（支持粤语/川话）", null, "N", null, false, false, false)
         );
     }
 
@@ -194,7 +196,7 @@ public class AihrModelSeedService {
         }
 
         try {
-            String content = callOpenAiCompatible(runtime, modelName, prompt, request == null ? null : request.systemPrompt());
+            String content = callOpenAiCompatible(runtime, modelName, prompt, request == null ? null : request.systemPrompt(), 0.2);
             return new ChatResponse(true, runtime.providerCode(), modelName, content, "openai-compatible", null, List.of());
         } catch (Exception e) {
             return new ChatResponse(
@@ -209,6 +211,55 @@ public class AihrModelSeedService {
         }
     }
 
+    /**
+     * 按类目(asr/tts)查已启用且配置齐全的语音模型运行参数，供 AihrSpeechService 使用。
+     */
+    public Optional<SpeechModel> speechModel(String category) {
+        try {
+            List<SpeechModel> rows = jdbcTemplate.query("""
+                select c.model_name, c.provider_code,
+                       coalesce(nullif(c.api_host, ''), nullif(p.api_host, '')) as resolved_api_host,
+                       coalesce(nullif(c.api_key, ''), nullif(p.api_key, '')) as resolved_api_key
+                  from aihr_model_config c
+                  left join aihr_model_provider p
+                    on p.tenant_id = c.tenant_id and p.provider_code = c.provider_code
+                 where c.tenant_id = ? and c.category = ? and c.enabled = 1
+                   and (p.status is null or p.status = '0')
+                 order by case when c.model_show = 'Y' then 0 else 1 end, c.id asc
+                """, (rs, rowNum) -> new SpeechModel(
+                rs.getString("provider_code"),
+                rs.getString("model_name"),
+                rs.getString("resolved_api_host"),
+                rs.getString("resolved_api_key")
+            ), TENANT_ID, category);
+            return rows.stream()
+                .filter(model -> configured(model.baseUrl(), model.modelName(), model.apiKey()))
+                .findFirst();
+        } catch (DataAccessException e) {
+            log.debug("aihr speech model db fallback: {}", e.getMessage());
+            return Optional.empty();
+        }
+    }
+
+    public record SpeechModel(String providerCode, String modelName, String baseUrl, String apiKey) {
+    }
+
+    /**
+     * 供其他模块(如三角色对练)复用的 chat 调用：模型未配置或调用失败返回 empty，由调用方决定兜底。
+     */
+    public Optional<String> tryChat(String systemPrompt, String userPrompt, double temperature) {
+        RuntimeConfig runtime = runtimeConfig(null);
+        if (!runtime.configured()) {
+            return Optional.empty();
+        }
+        try {
+            return Optional.of(callOpenAiCompatible(runtime, runtime.modelName(), userPrompt, systemPrompt, temperature));
+        } catch (Exception e) {
+            log.warn("aihr llm tryChat failed, caller falls back to seed: {}", e.getMessage());
+            return Optional.empty();
+        }
+    }
+
     private List<ProviderResponse> dbProviders() {
         try {
             return jdbcTemplate.query("""
@@ -286,10 +337,10 @@ public class AihrModelSeedService {
         }
     }
 
-    private String callOpenAiCompatible(RuntimeConfig runtime, String modelName, String prompt, String systemPrompt) throws Exception {
+    private String callOpenAiCompatible(RuntimeConfig runtime, String modelName, String prompt, String systemPrompt, double temperature) throws Exception {
         ObjectNode body = objectMapper.createObjectNode();
         body.put("model", modelName);
-        body.put("temperature", 0.2);
+        body.put("temperature", temperature);
         body.put("stream", false);
 
         ArrayNode messages = body.putArray("messages");
@@ -417,8 +468,8 @@ public class AihrModelSeedService {
 
     private static String category(String value) {
         String category = required(value, "模型类型不能为空");
-        if (!List.of("chat", "vector", "rerank").contains(category)) {
-            throw new IllegalArgumentException("模型类型只支持 chat/vector/rerank");
+        if (!List.of("chat", "vector", "rerank", "asr", "tts").contains(category)) {
+            throw new IllegalArgumentException("模型类型只支持 chat/vector/rerank/asr/tts");
         }
         return category;
     }

backend/ruoyi-modules/ruoyi-aihr/src/main/java/org/dromara/aihr/service/AihrPracticeLlmService.java

@@ -0,0 +1,172 @@
+package org.dromara.aihr.service;
+
+import com.fasterxml.jackson.databind.JsonNode;
+import com.fasterxml.jackson.databind.ObjectMapper;
+import lombok.RequiredArgsConstructor;
+import lombok.extern.slf4j.Slf4j;
+import org.dromara.aihr.domain.AihrPracticeDto.DialogueResponse;
+import org.springframework.stereotype.Service;
+
+import java.util.List;
+import java.util.Optional;
+
+/**
+ * 三角色对练的 LLM 编排：AI 客户回复生成 + /finish 单次结构化评分（TechSpec 第 6 章 P0）。
+ * 所有方法失败返回 empty，由 AihrPracticeSeedService 用 seed 数据兜底，前后端契约不变。
+ */
+@Service
+@RequiredArgsConstructor
+@Slf4j
+public class AihrPracticeLlmService {
+
+    private static final String PROMPT_VERSION = "practice-p0-v1";
+    private static final double CUSTOMER_TEMPERATURE = 0.7;
+    private static final double SCORE_TEMPERATURE = 0.0;
+    private static final int MAX_CUSTOMER_CHARS = 80;
+
+    private final AihrModelSeedService modelService;
+    private final ObjectMapper objectMapper;
+
+    public record PracticeScore(
+        int total,
+        int compliance,
+        int communication,
+        int emotion,
+        int marketing,
+        String rewrite,
+        String summary
+    ) {
+    }
+
+    /**
+     * 生成 AI 客户(业主)的下一句回应。nextBeat 为 seed 剧本中下一轮台词，作为剧情推进锚点。
+     */
+    public Optional<String> customerReply(
+        String personaTraits, String project, String goal,
+        List<DialogueResponse> dialogue, String traineeText, String nextBeat
+    ) {
+        String system = """
+            你只扮演一位物业小区的业主本人，正在和物业员工对话。
+            人设特征：%s
+            场景：%s
+            你的隐性诉求：%s
+            规则：
+            1. 只输出业主的下一句话，一句以内，不超过%d个字，口语化。
+            2. 禁止提及：系统、人设、评分、SOP、AI、训练。
+            3. 禁止替员工给出解决方案，禁止主动自曝隐性诉求（除非员工直接问到或你已明显被安抚）。
+            4. 剧情推进方向（不要照抄原句，按此方向自然回应）：%s
+            """.formatted(personaTraits, project, goal, MAX_CUSTOMER_CHARS, nextBeat);
+        String user = "对话记录：\n" + renderDialogue(dialogue)
+            + "\n员工刚才说：" + traineeText
+            + "\n请输出业主的下一句话。";
+        return modelService.tryChat(system, user, CUSTOMER_TEMPERATURE)
+            .map(AihrPracticeLlmService::cleanCustomerLine)
+            .filter(text -> !text.isBlank());
+    }
+
+    /**
+     * /finish 单 LLM 结构化评分：temperature=0 + 固定 prompt 版本 + 档位锚点 60/75/90。
+     */
+    public Optional<PracticeScore> score(String scenarioName, String goal, String strategy, List<DialogueResponse> dialogue) {
+        if (dialogue.stream().noneMatch(turn -> "trainee".equals(turn.role()) && !turn.text().isBlank())) {
+            return Optional.empty();
+        }
+        String system = """
+            你是物业行业培训考官（prompt版本 %s）。根据对练记录给员工话术评分。
+            评分锚点：60=及格线（有明显缺失）；75=合格（覆盖主要要点）；90=优秀（完整且超预期）。
+            约束：只根据"员工"实际说过的话评分，未提及的内容不得臆造加分。
+            只输出一个 JSON 对象，不要输出任何其他文字、解释或代码块标记，字段如下：
+            {"total":0-100,"compliance":0-100,"communication":0-100,"emotion":0-100,"marketing":0-100,"rewrite":"给员工的示范话术改写，80字内","summary":"一句话点评，60字内"}
+            """.formatted(PROMPT_VERSION);
+        String user = """
+            训练场景：%s
+            训练目标：%s
+            教练策略：%s
+            对练记录：
+            %s
+            """.formatted(scenarioName, goal, strategy, renderDialogue(dialogue));
+        return modelService.tryChat(system, user, SCORE_TEMPERATURE).flatMap(this::parseScore);
+    }
+
+    private Optional<PracticeScore> parseScore(String content) {
+        try {
+            JsonNode root = objectMapper.readTree(extractJson(content));
+            JsonNode totalNode = root.path("total");
+            if (!totalNode.isNumber() && !totalNode.isTextual()) {
+                return Optional.empty();
+            }
+            int total = clampScore(totalNode.asInt());
+            return Optional.of(new PracticeScore(
+                total,
+                dimension(root, "compliance", total),
+                dimension(root, "communication", total),
+                dimension(root, "emotion", total),
+                dimension(root, "marketing", total),
+                truncateText(root.path("rewrite").asText(""), 400),
+                truncateText(root.path("summary").asText(""), 300)
+            ));
+        } catch (Exception e) {
+            log.warn("practice score parse failed, falls back to seed: {}", e.getMessage());
+            return Optional.empty();
+        }
+    }
+
+    /** 维度字段缺失时回落到 total，避免 asInt() 把缺失当 0 分落库。 */
+    private static int dimension(JsonNode root, String field, int fallback) {
+        JsonNode node = root.path(field);
+        if (!node.isNumber() && !node.isTextual()) {
+            return fallback;
+        }
+        return clampScore(node.asInt(fallback));
+    }
+
+    /** 落库列为 varchar(1000)，模型输出截断兜底。 */
+    private static String truncateText(String value, int maxChars) {
+        if (value == null || value.length() <= maxChars) {
+            return value;
+        }
+        return value.substring(0, maxChars);
+    }
+
+    private static String extractJson(String content) {
+        String text = content == null ? "" : content.trim();
+        int start = text.indexOf('{');
+        int end = text.lastIndexOf('}');
+        if (start >= 0 && end > start) {
+            return text.substring(start, end + 1);
+        }
+        return text;
+    }
+
+    private static int clampScore(int value) {
+        return Math.max(0, Math.min(100, value));
+    }
+
+    private static String cleanCustomerLine(String content) {
+        String text = content == null ? "" : content.trim();
+        text = text.replaceAll("^[\"“」』\\s]+", "").replaceAll("[\"”「『\\s]+$", "");
+        if (text.startsWith("业主：") || text.startsWith("业主:")) {
+            text = text.substring(3);
+        }
+        if (text.length() > MAX_CUSTOMER_CHARS * 2) {
+            text = text.substring(0, MAX_CUSTOMER_CHARS * 2);
+        }
+        return text.trim();
+    }
+
+    private static String renderDialogue(List<DialogueResponse> dialogue) {
+        StringBuilder builder = new StringBuilder();
+        for (DialogueResponse turn : dialogue) {
+            String speaker = switch (turn.role()) {
+                case "customer" -> "业主";
+                case "trainee" -> "员工";
+                default -> null;
+            };
+            if (speaker == null || turn.text() == null || turn.text().isBlank()) {
+                continue;
+            }
+            builder.append(speaker).append("：").append(turn.text().trim()).append('\n');
+        }
+        return builder.toString();
+    }
+}

backend/ruoyi-modules/ruoyi-aihr/src/main/java/org/dromara/aihr/service/AihrPracticeSeedService.java

@@ -31,7 +31,8 @@ import java.util.concurrent.ConcurrentHashMap;
 import java.util.concurrent.ConcurrentMap;
 
 /**
- * 三角色对练 seed 编排器。P0 先稳定前后端契约，后续再替换为会话表、ASR 和 LLM 评分。
+ * 三角色对练编排器。seed 剧本承担剧情锚点与兜底；配置了 chat 模型时，
+ * 客户回复与 /finish 评分走真 LLM（AihrPracticeLlmService），失败自动回退 seed。
  */
 @Service
 public class AihrPracticeSeedService {
@@ -43,11 +44,13 @@ public class AihrPracticeSeedService {
     private final ConcurrentMap<String, ActiveSession> activeSessions = new ConcurrentHashMap<>();
     private final ObjectMapper objectMapper;
     private final JdbcTemplate jdbcTemplate;
+    private final AihrPracticeLlmService practiceLlmService;
     private volatile boolean practiceTableReady;
 
-    public AihrPracticeSeedService(ObjectMapper objectMapper, JdbcTemplate jdbcTemplate) {
+    public AihrPracticeSeedService(ObjectMapper objectMapper, JdbcTemplate jdbcTemplate, AihrPracticeLlmService practiceLlmService) {
         this.objectMapper = objectMapper;
         this.jdbcTemplate = jdbcTemplate;
+        this.practiceLlmService = practiceLlmService;
     }
 
     public StartResponse start(StartRequest request) {
@@ -55,7 +58,9 @@ public class AihrPracticeSeedService {
         RoundSeed firstRound = scenario.rounds().get(0);
         String sessionId = "seed-" + scenario.id() + "-" + System.currentTimeMillis();
         String trainee = resolveTrainee(request, scenario);
-        activeSessions.put(sessionId, new ActiveSession(scenario.id(), trainee, resolveExtPartyId(request, trainee), isMobile(request), LocalDateTime.now(), new ArrayList<>()));
+        List<String> customerLines = new ArrayList<>();
+        customerLines.add(firstRound.customer());
+        activeSessions.put(sessionId, new ActiveSession(scenario.id(), trainee, resolveExtPartyId(request, trainee), isMobile(request), LocalDateTime.now(), new ArrayList<>(), customerLines));
         return new StartResponse(
             sessionId,
             scenario.id(),
@@ -73,13 +78,15 @@ public class AihrPracticeSeedService {
         ScenarioSeed scenario = resolveScenario(null, request == null ? null : request.sessionId());
         int roundIndex = normalizeRoundIndex(request == null ? null : request.roundIndex(), scenario.rounds().size());
         rememberTraineeReply(request, roundIndex);
+        ActiveSession session = request == null || isBlank(request.sessionId()) ? null : activeSessions.get(request.sessionId());
         RoundSeed currentRound = scenario.rounds().get(roundIndex);
         int nextRoundIndex = roundIndex + 1;
         boolean finished = nextRoundIndex >= scenario.rounds().size();
         RoundSeed nextRound = finished ? currentRound : scenario.rounds().get(nextRoundIndex);
         int trust = finished ? scenario.trustEnd() : nextRound.trust();
+        String customerText = finished ? "" : resolveCustomerReply(scenario, session, request, nextRound, nextRoundIndex);
         return new TurnResponse(
-            finished ? "" : nextRound.customer(),
+            customerText,
             "",
             nextRound.emotion(),
             trust,
@@ -89,23 +96,67 @@ public class AihrPracticeSeedService {
         );
     }
 
+    /**
+     * 优先用 LLM 按人设生成客户回应（seed 下一轮台词作为剧情锚点），失败回退 seed 台词。
+     */
+    private String resolveCustomerReply(ScenarioSeed scenario, ActiveSession session, TurnRequest request, RoundSeed nextRound, int nextRoundIndex) {
+        String traineeText = request == null || isBlank(request.traineeText()) ? "" : request.traineeText().trim();
+        String customerText = nextRound.customer();
+        if (session != null && !traineeText.isEmpty()) {
+            customerText = practiceLlmService.customerReply(
+                scenario.customer(),
+                scenario.project(),
+                scenario.goal(),
+                dialogueTurns(session, scenario),
+                traineeText,
+                nextRound.customer()
+            ).orElse(customerText);
+        }
+        rememberCustomerLine(session, nextRoundIndex, customerText);
+        return customerText;
+    }
+
     public FinishResponse finish(FinishRequest request) {
         String sessionId = request == null ? null : request.sessionId();
         ActiveSession activeSession = sessionId == null ? null : activeSessions.remove(sessionId);
         ScenarioSeed scenario = resolveScenario(activeSession == null ? null : activeSession.scenarioId(), sessionId);
         String trainee = activeSession == null ? scenario.trainee() : activeSession.trainee();
-        RecordResponse record = new RecordResponse(null, sessionId, formatNow(), trainee, scenario.name(), scenario.total(), "待复盘", scenario.summary());
-        savePracticeRecord(sessionId, activeSession, scenario, record);
+        PracticeResult result = evaluate(activeSession, scenario);
+        RecordResponse record = new RecordResponse(null, sessionId, formatNow(), trainee, scenario.name(), result.total(), "待复盘", result.summary());
+        savePracticeRecord(sessionId, activeSession, scenario, record, result);
         return new FinishResponse(
-            scenario.total(),
-            scenario.scores(),
-            scenario.rewrite(),
-            scenario.summary(),
+            result.total(),
+            result.scores(),
+            result.rewrite(),
+            result.summary(),
             List.of(scenario.trustStart(), scenario.rounds().get(0).trust(), scenario.trustEnd()),
             List.of(record)
         );
     }
 
+    /**
+     * /finish 单次评分：配置了 chat 模型且学员有真实回复时走 LLM 结构化评分，否则用 seed 分。
+     */
+    private PracticeResult evaluate(ActiveSession activeSession, ScenarioSeed scenario) {
+        PracticeResult seedResult = new PracticeResult(scenario.total(), scenario.scores(), scenario.rewrite(), scenario.summary());
+        if (activeSession == null) {
+            return seedResult;
+        }
+        return practiceLlmService.score(scenario.name(), scenario.goal(), scenario.strategy(), dialogueTurns(activeSession, scenario))
+            .map(score -> new PracticeResult(
+                score.total(),
+                List.of(
+                    new DimensionResponse("合规", score.compliance(), "SOP关键点覆盖"),
+                    new DimensionResponse("沟通", score.communication(), "承诺与表达清晰度"),
+                    new DimensionResponse("情绪", score.emotion(), "安抚与承接能力"),
+                    new DimensionResponse("营销", score.marketing(), "增值转化意识")
+                ),
+                isBlank(score.rewrite()) ? scenario.rewrite() : score.rewrite(),
+                isBlank(score.summary()) ? scenario.summary() : score.summary()
+            ))
+            .orElse(seedResult);
+    }
+
     public int mobileCompletedCount() {
         return countMobileRecords("");
     }
@@ -232,7 +283,7 @@ public class AihrPracticeSeedService {
         return LocalDateTime.now().format(TIME_FORMATTER);
     }
 
-    private void savePracticeRecord(String sessionId, ActiveSession activeSession, ScenarioSeed scenario, RecordResponse record) {
+    private void savePracticeRecord(String sessionId, ActiveSession activeSession, ScenarioSeed scenario, RecordResponse record, PracticeResult result) {
         ensurePracticeTable();
         LocalDateTime now = LocalDateTime.now();
         LocalDateTime started = activeSession == null ? now : activeSession.startedAt();
@@ -266,13 +317,13 @@ public class AihrPracticeSeedService {
             scenario.id(),
             scenario.name(),
             mobile ? "mobile" : "text",
-            scenario.total(),
-            scoreValue(scenario, "合规"),
-            scoreValue(scenario, "情绪"),
-            scoreValue(scenario, "沟通"),
-            scoreValue(scenario, "营销"),
-            scenario.rewrite(),
-            scenario.summary(),
+            result.total(),
+            scoreValue(result.scores(), "合规"),
+            scoreValue(result.scores(), "情绪"),
+            scoreValue(result.scores(), "沟通"),
+            scoreValue(result.scores(), "营销"),
+            result.rewrite(),
+            result.summary(),
             record.summary(),
             dialogueJson(activeSession, scenario),
             scenario.trustStart() + "," + scenario.rounds().get(0).trust() + "," + scenario.trustEnd(),
@@ -388,6 +439,19 @@ public class AihrPracticeSeedService {
         }
     }
 
+    private void rememberCustomerLine(ActiveSession session, int roundIndex, String customerText) {
+        if (session == null || isBlank(customerText)) {
+            return;
+        }
+        List<String> lines = session.customerLines();
+        synchronized (lines) {
+            while (lines.size() <= roundIndex) {
+                lines.add("");
+            }
+            lines.set(roundIndex, customerText.trim());
+        }
+    }
+
     private String dialogueJson(ActiveSession activeSession, ScenarioSeed scenario) {
         try {
             return objectMapper.writeValueAsString(dialogueTurns(activeSession, scenario));
@@ -422,10 +486,12 @@ public class AihrPracticeSeedService {
 
     private List<DialogueResponse> dialogueTurns(ActiveSession activeSession, ScenarioSeed scenario) {
         List<DialogueResponse> turns = new ArrayList<>();
-        List<String> replies = activeSession == null ? List.of() : activeSession.traineeReplies();
+        List<String> replies = snapshot(activeSession == null ? null : activeSession.traineeReplies());
+        List<String> customerLines = snapshot(activeSession == null ? null : activeSession.customerLines());
         for (int i = 0; i < scenario.rounds().size(); i++) {
             RoundSeed round = scenario.rounds().get(i);
-            turns.add(new DialogueResponse("customer", "AI业主", round.customer()));
+            String customerLine = i < customerLines.size() && !isBlank(customerLines.get(i)) ? customerLines.get(i) : round.customer();
+            turns.add(new DialogueResponse("customer", "AI业主", customerLine));
             if (i < replies.size() && !isBlank(replies.get(i))) {
                 turns.add(new DialogueResponse("trainee", "员工话术", replies.get(i)));
             }
@@ -434,8 +500,18 @@ public class AihrPracticeSeedService {
         return turns;
     }
 
-    private Integer scoreValue(ScenarioSeed scenario, String label) {
-        for (DimensionResponse score : scenario.scores()) {
+    /** 会话内列表写入均持有各自 monitor，读取同样加锁拷贝，避免并发 /turn、/finish 读到中间态。 */
+    private static List<String> snapshot(List<String> source) {
+        if (source == null) {
+            return List.of();
+        }
+        synchronized (source) {
+            return new ArrayList<>(source);
+        }
+    }
+
+    private Integer scoreValue(List<DimensionResponse> scores, String label) {
+        for (DimensionResponse score : scores) {
             if (label.equals(score.label()) && score.value() instanceof Number) {
                 return ((Number) score.value()).intValue();
             }
@@ -628,6 +704,10 @@ public class AihrPracticeSeedService {
     private record CompetencySnapshot(Integer completed, Integer score, Integer pendingReview, Integer compliance, Integer communication, Integer emotion) {
     }
 
-    private record ActiveSession(String scenarioId, String trainee, String extPartyId, boolean mobile, LocalDateTime startedAt, List<String> traineeReplies) {
+    private record ActiveSession(String scenarioId, String trainee, String extPartyId, boolean mobile, LocalDateTime startedAt,
+                                 List<String> traineeReplies, List<String> customerLines) {
+    }
+
+    private record PracticeResult(Integer total, List<DimensionResponse> scores, String rewrite, String summary) {
     }
 }