feat(后端)：AiServiceClient 改为 submit+poll 异步任务模式

- 内部实现重构：每个公有方法内部 submitAndWait() → submitTask() + pollResult() - submitTask(): POST /ai/tasks，返回 taskId（30s 超时） - pollResult(): 轮询 GET /ai/tasks/:taskId，500ms 首次延迟， 2s × 10 次后退避到 5s，总超时 600s（10 min） - 公有方法签名完全不变：aggregateReport()、generateMindMap()、compareRecall() - 异常失败时返回 Optional.empty()，调用方降级逻辑不变 - application.yml timeout-seconds: 180 → 600
2026-07-04 16:41:21 +08:00
parent 4ec900577e
commit 55b7c1c83c
2 changed files with 126 additions and 58 deletions
@@ -13,6 +13,7 @@ import java.net.http.HttpClient;
 import java.net.http.HttpRequest;
 import java.net.http.HttpResponse;
 import java.time.Duration;
+import java.time.Instant;
 import java.util.List;
 import java.util.Map;
 import java.util.Optional;
@@ -20,6 +21,10 @@ import java.util.Optional;
 /**
 * lpt-ai 独立 AI 服务客户端。
 * <p>通过 {@code lpt.ai-service.url} 配置服务地址；未配置或调用失败时返回 empty，由调用方降级。</p>
+ * <p>
+ * 内部使用异步任务模式：提交任务到 lpt-ai 后轮询等待结果，
+ * 避免同步等待 LLM 响应时阻塞 HTTP 连接。
+ * </p>
 */
@Slf4j
@Component
@@ -29,8 +34,8 @@ public class AiServiceClient {

    /** lpt-ai 服务地址，如 http://localhost:5199 */
    private String url;
-    /** 超时秒数 */
-    private int timeoutSeconds = 90;
+    /** 超时秒数（等待 AI 任务完成的最长时间） */
+    private int timeoutSeconds = 600;

    private HttpClient httpClient;
    private final ObjectMapper objectMapper = new ObjectMapper();
@@ -41,9 +46,9 @@ public class AiServiceClient {
                .connectTimeout(Duration.ofSeconds(10))
                .build();
        if (isConfigured()) {
-            log.info("AiServiceClient 已配置: {}", url);
+            log.info("AiServiceClient 已配置: {} (超时 {}s, 异步任务模式)", url, timeoutSeconds);
        } else {
-            log.info("AiServiceClient 未配置，AI 聚合功能不可用（将降级为拼接）");
+            log.info("AiServiceClient 未配置，AI 功能不可用（将降级为内置逻辑）");
        }
    }

@@ -51,10 +56,10 @@ public class AiServiceClient {
        return url != null && !url.isBlank();
    }

+    // ============ 公开 API（签名不变，内部改为 submit + poll）============
+
    /**
     * 调用 lpt-ai 将残片聚合为学习报告草稿。
-     *
-     * @return 聚合后的报告文本；服务未配置或调用失败时返回 empty
     */
    public Optional<String> aggregateReport(String taskName, List<String> fragments, String expectation) {
        if (!isConfigured() || fragments == null || fragments.isEmpty()) {
@@ -64,36 +69,20 @@ public class AiServiceClient {
            List<Map<String, String>> fragmentBodies = fragments.stream()
                    .map(content -> Map.of("content", content))
                    .toList();
-            Map<String, Object> body = expectation == null || expectation.isBlank()
+            Map<String, Object> params = expectation == null || expectation.isBlank()
                    ? Map.of("taskName", taskName, "fragments", fragmentBodies)
                    : Map.of("taskName", taskName, "fragments", fragmentBodies, "expectation", expectation);

-            HttpRequest request = HttpRequest.newBuilder()
-                    .uri(URI.create(url + "/ai/aggregate-report"))
-                    .timeout(Duration.ofSeconds(timeoutSeconds))
-                    .header("Content-Type", "application/json")
-                    .POST(HttpRequest.BodyPublishers.ofString(objectMapper.writeValueAsString(body)))
-                    .build();
-
-            HttpResponse<String> response = httpClient.send(request, HttpResponse.BodyHandlers.ofString());
-            if (response.statusCode() != 200) {
-                log.warn("lpt-ai 聚合报告失败: status={}, body={}", response.statusCode(),
-                        response.body() != null ? response.body().substring(0, Math.min(200, response.body().length())) : "");
-                return Optional.empty();
-            }
-            JsonNode json = objectMapper.readTree(response.body());
-            String report = json.path("report").asText(null);
-            return Optional.ofNullable(report).filter(s -> !s.isBlank());
+            Optional<JsonNode> result = submitAndWait("aggregate-report", params);
+            return result.map(r -> r.path("report").asText(null)).filter(s -> s != null && !s.isBlank());
        } catch (Exception e) {
-            log.warn("lpt-ai 调用异常，将降级: {}", e.getMessage());
+            log.warn("lpt-ai 聚合报告异常，将降级: {}", e.getMessage());
            return Optional.empty();
        }
    }

    /**
-     * 调用 lpt-ai 从学习数据生成思维导图大纲（缩进文本格式）。
-     *
-     * @return 缩进大纲文本；服务未配置或调用失败时返回 empty
+     * 调用 lpt-ai 从学习数据生成思维导图大纲。
     */
    public Optional<String> generateMindMap(String taskName, String taskDescription,
                                             List<String> reports, List<String> fragments) {
@@ -101,69 +90,148 @@ public class AiServiceClient {
            return Optional.empty();
        }
        try {
-            Map<String, Object> body = Map.of(
+            Map<String, Object> params = Map.of(
                    "taskName", taskName,
                    "taskDescription", taskDescription != null ? taskDescription : "",
                    "reports", reports != null ? reports : List.of(),
                    "fragments", fragments != null ? fragments : List.of()
            );

-            HttpRequest request = HttpRequest.newBuilder()
-                    .uri(URI.create(url + "/ai/generate-mind-map"))
-                    .timeout(Duration.ofSeconds(timeoutSeconds))
-                    .header("Content-Type", "application/json")
-                    .POST(HttpRequest.BodyPublishers.ofString(objectMapper.writeValueAsString(body)))
-                    .build();
-
-            HttpResponse<String> response = httpClient.send(request, HttpResponse.BodyHandlers.ofString());
-            if (response.statusCode() != 200) {
-                log.warn("lpt-ai 生成思维导图失败: status={}, body={}", response.statusCode(),
-                        response.body() != null ? response.body().substring(0, Math.min(200, response.body().length())) : "");
-                return Optional.empty();
-            }
-            JsonNode json = objectMapper.readTree(response.body());
-            String outline = json.path("outline").asText(null);
-            return Optional.ofNullable(outline).filter(s -> !s.isBlank());
+            Optional<JsonNode> result = submitAndWait("generate-mind-map", params);
+            return result.map(r -> r.path("outline").asText(null)).filter(s -> s != null && !s.isBlank());
        } catch (Exception e) {
-            log.warn("lpt-ai 思维导图调用异常，将降级: {}", e.getMessage());
+            log.warn("lpt-ai 思维导图异常，将降级: {}", e.getMessage());
            return Optional.empty();
        }
    }

    /**
     * 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 AI 返回的原始 JSON；服务未配置或调用失败时返回 empty
     */
    public Optional<JsonNode> compareRecall(String taskName, String standardOutline, String recallOutline) {
        if (!isConfigured()) {
            return Optional.empty();
        }
        try {
-            Map<String, String> body = Map.of(
+            Map<String, Object> params = Map.of(
                    "taskName", taskName,
                    "standardOutline", standardOutline,
                    "recallOutline", recallOutline
            );

+            return submitAndWait("compare-recall", params);
+        } catch (Exception e) {
+            log.warn("lpt-ai 回忆对比异常，将降级为内置算法: {}", e.getMessage());
+            return Optional.empty();
+        }
+    }
+
+    // ============ 内部异步 submit + poll ============
+
+    /** 提交任务并同步等待结果（内部轮询，调用方无感知） */
+    private Optional<JsonNode> submitAndWait(String type, Map<String, Object> params) {
+        String taskId = submitTask(type, params);
+        if (taskId == null) {
+            return Optional.empty();
+        }
+        return pollResult(taskId);
+    }
+
+    /** 提交任务到 lpt-ai /ai/tasks */
+    private String submitTask(String type, Map<String, Object> params) {
+        try {
+            Map<String, Object> body = Map.of("type", type, "params", params);
            HttpRequest request = HttpRequest.newBuilder()
-                    .uri(URI.create(url + "/ai/compare-recall"))
-                    .timeout(Duration.ofSeconds(timeoutSeconds))
+                    .uri(URI.create(url + "/ai/tasks"))
+                    .timeout(Duration.ofSeconds(30)) // 提交本身不应超时
                    .header("Content-Type", "application/json")
                    .POST(HttpRequest.BodyPublishers.ofString(objectMapper.writeValueAsString(body)))
                    .build();

            HttpResponse<String> response = httpClient.send(request, HttpResponse.BodyHandlers.ofString());
-            if (response.statusCode() != 200) {
-                log.warn("lpt-ai 回忆对比失败: status={}, body={}", response.statusCode(),
+            if (response.statusCode() != 201) {
+                log.warn("lpt-ai 提交任务失败: type={}, status={}, body={}",
+                        type, response.statusCode(),
                        response.body() != null ? response.body().substring(0, Math.min(200, response.body().length())) : "");
-                return Optional.empty();
+                return null;
            }
-            return Optional.of(objectMapper.readTree(response.body()));
+            JsonNode json = objectMapper.readTree(response.body());
+            String taskId = json.path("taskId").asText(null);
+            if (taskId == null || taskId.isBlank()) {
+                log.warn("lpt-ai 提交任务成功但未返回 taskId");
+                return null;
+            }
+            log.info("lpt-ai 任务已提交: type={}, taskId={}", type, taskId);
+            return taskId;
        } 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());
+            log.warn("lpt-ai 提交任务异常: {}", e.getMessage());
+            return null;
+        }
+    }
+
+    /** 轮询等待任务完成 */
+    private Optional<JsonNode> pollResult(String taskId) {
+        Instant deadline = Instant.now().plusSeconds(timeoutSeconds);
+        int pollCount = 0;
+
+        try {
+            // 给 worker 一点启动时间
+            Thread.sleep(500);
+
+            while (Instant.now().isBefore(deadline)) {
+                pollCount++;
+                HttpRequest request = HttpRequest.newBuilder()
+                        .uri(URI.create(url + "/ai/tasks/" + taskId))
+                        .timeout(Duration.ofSeconds(10))
+                        .GET()
+                        .build();
+
+                try {
+                    HttpResponse<String> response = httpClient.send(request, HttpResponse.BodyHandlers.ofString());
+                    if (response.statusCode() == 404) {
+                        log.warn("lpt-ai 任务 {} 不存在（可能已过期或被清理）", taskId);
+                        return Optional.empty();
+                    }
+                    if (response.statusCode() != 200) {
+                        log.warn("lpt-ai 查询任务失败: taskId={}, status={}", taskId, response.statusCode());
+                        // 临时故障，继续轮询
+                        Thread.sleep(2000);
+                        continue;
+                    }
+
+                    JsonNode json = objectMapper.readTree(response.body());
+                    String status = json.path("status").asText("");
+
+                    switch (status) {
+                        case "done":
+                            log.info("lpt-ai 任务完成: taskId={}, 轮询次数={}", taskId, pollCount);
+                            return Optional.ofNullable(json.path("result"));
+                        case "failed":
+                            String err = json.path("error").asText("未知错误");
+                            log.warn("lpt-ai 任务失败: taskId={}, error={}", taskId, err);
+                            return Optional.empty();
+                        case "pending":
+                        case "running":
+                            // 还在处理，继续轮询
+                            break;
+                        default:
+                            log.warn("lpt-ai 未知任务状态: taskId={}, status={}", taskId, status);
+                            return Optional.empty();
+                    }
+                } catch (Exception e) {
+                    log.warn("lpt-ai 轮询异常 (第{}次): {}", pollCount, e.getMessage());
+                }
+
+                // 退避：前 10 次 2s，之后 5s
+                long delay = pollCount <= 10 ? 2000 : 5000;
+                Thread.sleep(delay);
+            }
+
+            log.warn("lpt-ai 任务超时: taskId={}, timeout={}s", taskId, timeoutSeconds);
+            return Optional.empty();
+        } catch (InterruptedException e) {
+            Thread.currentThread().interrupt();
+            log.warn("lpt-ai 轮询被中断: taskId={}", taskId);
            return Optional.empty();
        }
    }
@@ -56,4 +56,4 @@ management:
 lpt:
    ai-service:
        url: http://localhost:5199
-        timeout-seconds: 180
+        timeout-seconds: 600