fix(复习)：AI 对比结果由 Java 端标注标准树，不再依赖 LLM 输出树结构

根因：LLM 无法可靠输出 CompareResult 所需的完整嵌套树 JSON，
实际返回格式（coverage/matched/missed）与预期不符。

修复：
- AiServiceClient.compareRecall() 返回 Optional<JsonNode>（原始 JSON），
  不再尝试直接反序列化为 CompareResult
- StandardMindMapServiceImpl 新增 buildCompareResultFromAI()：
  解析 AI 返回的平铺 matches/missedTitles/extraNodes 列表，
  将 MATCHED|/MISSED| 标注写入标准树，确定性构建 CompareResult
- AI 只负责语义匹配判断，树结构操作由 Java 端保证可靠性

src/main/java/com/guo/learningprogresstracker/service/impl/AiServiceClient.java

@@ -2,7 +2,6 @@ package com.guo.learningprogresstracker.service.impl;
 
 import com.fasterxml.jackson.databind.JsonNode;
 import com.fasterxml.jackson.databind.ObjectMapper;
-import com.guo.learningprogresstracker.utils.CompareResult;
 import jakarta.annotation.PostConstruct;
 import lombok.Setter;
 import lombok.extern.slf4j.Slf4j;
@@ -133,10 +132,12 @@ public class AiServiceClient {
 
     /**
      * 调用 lpt-ai 进行语义化回忆对比。
+     * 注意：AI 返回平铺的匹配列表，不返回完整树结构。
+     * 树标注（MATCHED/MISSED）由 StandardMindMapServiceImpl 基于本方法返回的 JSON 完成。
      *
-     * @return 带 MATCHED/MISSED 标注和评价文本的对比结果；服务未配置或调用失败时返回 empty
+     * @return AI 返回的原始 JSON；服务未配置或调用失败时返回 empty
      */
-    public Optional<CompareResult> compareRecall(String taskName, String standardOutline, String recallOutline) {
+    public Optional<JsonNode> compareRecall(String taskName, String standardOutline, String recallOutline) {
         if (!isConfigured()) {
             return Optional.empty();
         }
@@ -160,7 +161,7 @@ public class AiServiceClient {
                         response.body() != null ? response.body().substring(0, Math.min(200, response.body().length())) : "");
                 return Optional.empty();
             }
-            return Optional.of(objectMapper.readValue(response.body(), CompareResult.class));
+            return Optional.of(objectMapper.readTree(response.body()));
         } catch (Exception e) {
             log.warn("lpt-ai 回忆对比调用异常，将降级为内置算法: {}", e.getMessage());
             return Optional.empty();

src/main/java/com/guo/learningprogresstracker/service/impl/StandardMindMapServiceImpl.java

@@ -1,6 +1,7 @@
 package com.guo.learningprogresstracker.service.impl;
 
 import com.baomidou.mybatisplus.core.toolkit.Wrappers;
+import com.fasterxml.jackson.databind.JsonNode;
 import com.fasterxml.jackson.databind.ObjectMapper;
 import com.guo.learningprogresstracker.entity.*;
 import com.guo.learningprogresstracker.exception.NotFindEntitiesException;
@@ -112,13 +113,13 @@ public class StandardMindMapServiceImpl implements StandardMindMapService {
             String taskName = tasksMapper.selectOne(
                     Wrappers.<TaskEntity>lambdaQuery().eq(TaskEntity::getTaskNum, taskNum).last("LIMIT 1"))
                     .getTaskName();
-            var optResult = aiServiceClient.compareRecall(
+            var optJson = aiServiceClient.compareRecall(
                     taskName,
                     MindMapTreeTool.toFullOutline(standardRoot),
                     recallOutline
             );
-            if (optResult.isPresent()) {
+            if (optJson.isPresent()) {
-                result = optResult.get();
+                result = buildCompareResultFromAI(optJson.get(), standardRoot);
                 log.info("AI 回忆对比: taskNum={}, recallRatio={}, evaluation={}",
                         taskNum, result.getRecallRatio(),
                         result.getEvaluation() != null ? result.getEvaluation().substring(0, Math.min(50, result.getEvaluation().length())) : "");
@@ -225,6 +226,74 @@ public class StandardMindMapServiceImpl implements StandardMindMapService {
         return result;
     }
 
+    /**
+     * 从 AI 返回的平铺匹配列表构建 CompareResult，并将 MATCHED/MISSED 标注回标准树。
+     * <p>AI 只输出哪些节点匹配/遗漏，树结构标注由本方法确定性完成，避免 LLM 输出不可靠的嵌套 JSON。</p>
+     */
+    private CompareResult buildCompareResultFromAI(JsonNode aiJson, MindMapNode standardRoot) {
+        CompareResult result = new CompareResult();
+
+        // 1. 读取 AI 返回的匹配对 → 构建 standardNorm → matchFlag
+        Set<String> matchedStandardTitles = new HashSet<>();
+        JsonNode matchesArr = aiJson.path("matches");
+        if (matchesArr.isArray()) {
+            for (JsonNode m : matchesArr) {
+                String stdTitle = m.path("standardTitle").asText(null);
+                if (stdTitle != null) {
+                    matchedStandardTitles.add(normalize(stdTitle));
+                }
+            }
+        }
+
+        // 2. 读取遗漏列表
+        Set<String> missedTitles = new HashSet<>();
+        JsonNode missedArr = aiJson.path("missedTitles");
+        if (missedArr.isArray()) {
+            for (JsonNode t : missedArr) {
+                String title = t.asText(null);
+                if (title != null) missedTitles.add(normalize(title));
+            }
+        }
+
+        // 3. 标注标准树的每个非根节点
+        List<MindMapNode> standardFlat = MindMapTreeTool.flatten(standardRoot);
+        int matched = 0, missed = 0;
+        for (MindMapNode node : standardFlat) {
+            if (node == standardRoot) continue;
+            String key = normalize(node.getTitle());
+            if (matchedStandardTitles.contains(key)) {
+                node.setNotes(MATCH_STATUS_MATCHED + "|" + (node.getNotes() != null ? node.getNotes() : ""));
+                matched++;
+            } else {
+                node.setNotes(MATCH_STATUS_MISSED + "|" + (node.getNotes() != null ? node.getNotes() : ""));
+                missed++;
+            }
+        }
+
+        // 4. 读取 extraNodes
+        List<CompareResult.FlatNode> extras = new ArrayList<>();
+        JsonNode extrasArr = aiJson.path("extraNodes");
+        if (extrasArr.isArray()) {
+            for (JsonNode e : extrasArr) {
+                CompareResult.FlatNode fn = new CompareResult.FlatNode();
+                fn.setTitle(e.path("title").asText(""));
+                fn.setPath(e.path("path").asText(""));
+                extras.add(fn);
+            }
+        }
+
+        // 5. 组装结果
+        result.setMatchedTree(standardRoot);
+        result.setExtraNodes(extras);
+        result.setMatchedCount(matched);
+        result.setMissedCount(missed);
+        result.setExtraCount(extras.size());
+        int total = matched + missed;
+        result.setRecallRatio(total > 0 ? (double) matched / total : 0);
+        result.setEvaluation(aiJson.path("evaluation").asText(null));
+        return result;
+    }
+
     // ============ 回忆记录查询 ============
 
     @Override