feat: review training attempt details

docs/AI_ICT_Training_Case_Engine_开发方案_v1.md

@@ -661,6 +661,21 @@ Invalidation：20
 3. started attempt 显示 status。
 4. history 仅按 `user_id` 读取，不影响其他用户进度。
 
+### M19：Attempt 复盘详情
+
+完成：
+
+1. `GET /training/attempts/{id}` 返回 attempt、隐藏答案的 case、annotations、scores、replay。
+2. graded/submitted attempt 的 replay 可 reveal answer，started attempt 继续隐藏答案。
+3. Training Lab 点击 Recent attempts 后进入 attempt review。
+4. Score 面板展示历史分项得分。
+
+验收：
+
+1. attempt detail 的 `case.answer_key` 始终隐藏。
+2. 只有复盘 replay 在已提交/已评分后显示答案。
+3. 历史记录点击后能恢复当时 frame index。
+
 ## 10. 第一版验收标准
 
 第一版完成时必须满足：
@@ -683,6 +698,7 @@ Invalidation：20
 16. 高阶 MSS 答案能在图表上直观看到结构打破价位。
 17. 每次提交后能明确展示阶段是否推进、掌握或解锁。
 18. 读者能回看最近训练记录与分数。
+19. 读者能打开历史 attempt 复盘当时的标注、得分与答案图层。
 
 ## 11. 推荐立即开始的第一步
 

src/api/training.py

@@ -108,7 +108,23 @@ class TrainingAPI:
         attempt = self.repository.fetch_attempt(attempt_id)
         if not attempt:
             raise ValueError(f"training_attempt_not_found:{attempt_id}")
-        payload = {"attempt": attempt}
+        case = self.repository.fetch_case(attempt["case_id"])
+        if not case:
+            raise ValueError(f"training_case_not_found:{attempt['case_id']}")
+        case_payload = _hide_answer_key(case)
+        case_payload["tasks"] = self.repository.list_tasks(attempt["case_id"])
+        reveal_answer = attempt.get("status") in {"submitted", "graded"}
+        replay = self.replay_service.build_case_replay(
+            case_id=attempt["case_id"],
+            frame_index=attempt.get("current_frame_index"),
+            reveal_answer=reveal_answer,
+        )
+        payload = {
+            "attempt": attempt,
+            "case": case_payload,
+            "scores": self.repository.list_scores(attempt_id),
+            "replay": replay.__dict__,
+        }
         if include_annotations:
             payload["annotations"] = self.repository.list_annotations(attempt_id)
         return payload

src/web/training/training.js

@@ -177,7 +177,7 @@ function renderProgress(payload, recommendations = { items: [] }, history = { it
   (history.items || []).forEach((item) => {
     const button = document.createElement('button');
     button.className = 'attempt-history-item';
-    button.addEventListener('click', () => selectCase(item.case_id));
+    button.addEventListener('click', () => loadAttempt(item.attempt_id));
 
     const kind = document.createElement('span');
     kind.textContent = `#${item.attempt_id} ${item.case_type}`;
@@ -275,6 +275,18 @@ async function selectCase(caseId) {
   renderCase();
 }
 
+async function loadAttempt(attemptId) {
+  const payload = await fetchJson(`/training/attempts/${attemptId}`);
+  state.selectedCase = payload.case;
+  state.attempt = payload.attempt;
+  state.replay = payload.replay;
+  state.selectedCandleIndex = null;
+  renderCaseList();
+  renderCase();
+  renderAttemptReview(payload);
+  setStatus(`Review attempt #${attemptId}`);
+}
+
 function renderCase() {
   const current = state.selectedCase;
   if (!current) {
@@ -490,6 +502,17 @@ function renderScores(payload) {
   });
 }
 
+function renderAttemptReview(payload) {
+  const scores = payload.scores || [];
+  const maxScore = scores.reduce((sum, item) => sum + Number(item.max_score || 0), 0);
+  const totalScore = payload.attempt?.total_score ?? scores.reduce((sum, item) => sum + Number(item.score || 0), 0);
+  renderScores({
+    total_score: totalScore,
+    max_score: maxScore,
+    scores,
+  });
+}
+
 function updateButtons() {
   const hasCase = Boolean(state.selectedCase);
   const hasAttempt = Boolean(state.attempt);

tests/unit/test_api_static_server.py

@@ -66,6 +66,7 @@ class ApiStaticServerTests(unittest.TestCase):
         app_js = app_file.read_text(encoding="utf-8")
 
         self.assertIn("/training/attempts/history", app_js)
+        self.assertIn("/training/attempts/${attemptId}", app_js)
         self.assertIn("Recent attempts", app_js)
         self.assertIn("attempt-history-item", app_js)
 

tests/unit/test_training_module.py

@@ -648,6 +648,18 @@ class TrainingApiAnswerHidingTests(unittest.TestCase):
         self.assertEqual(payload["items"][0]["score_pct"], 80.0)
         self.assertNotIn("answer_key", payload["items"][0])
 
+    def test_attempt_detail_includes_review_payload_without_case_answer(self) -> None:
+        api = TrainingAPI(repository=StubAttemptDetailRepository())
+
+        payload = api.get_attempt(91)
+
+        self.assertEqual(payload["attempt"]["id"], 91)
+        self.assertEqual(payload["case"]["answer_key"], None)
+        self.assertEqual(payload["case"]["tasks"][0]["task_type"], "mark_dealing_range")
+        self.assertEqual(payload["scores"][0]["category"], "dealing_range")
+        self.assertTrue(payload["replay"]["answer_visible"])
+        self.assertIsNotNone(payload["replay"]["case"]["answer_key"])
+
     def test_recommendations_balance_case_types_when_no_weakness_exists(self) -> None:
         repo = StubBalancedRecommendationRepository()
         api = TrainingAPI(repository=repo)
@@ -1024,6 +1036,47 @@ class StubAttemptHistoryRepository:
         ][:limit]
 
 
+class StubAttemptDetailRepository:
+    def __init__(self) -> None:
+        self.ts = datetime(2026, 4, 29, 8, 0, tzinfo=timezone.utc)
+
+    def fetch_attempt(self, attempt_id):
+        return {
+            "id": attempt_id,
+            "case_id": 31,
+            "user_id": "local",
+            "status": "graded",
+            "current_frame_index": 1,
+            "total_score": 60,
+            "meta": {},
+        }
+
+    def fetch_case(self, case_id):
+        return {
+            "id": case_id,
+            "instrument_id": 1,
+            "timeframe": "1m",
+            "case_type": "range",
+            "decision_ts": self.ts.replace(minute=1),
+            "answer_key": {"low": 90.0, "high": 110.0, "equilibrium": 100.0},
+        }
+
+    def list_tasks(self, case_id):
+        return [{"id": 1, "case_id": case_id, "task_type": "mark_dealing_range"}]
+
+    def list_scores(self, attempt_id):
+        return [{"category": "dealing_range", "score": 20, "max_score": 20, "feedback": {"reason": "matched"}}]
+
+    def list_annotations(self, attempt_id):
+        return [{"annotation_type": "dealing_range", "payload": {"price_low": 90, "price_high": 110}}]
+
+    def fetch_case_candles(self, case_id):
+        return [
+            {"ts_open": self.ts, "open": 100, "high": 101, "low": 99, "close": 100},
+            {"ts_open": self.ts.replace(minute=1), "open": 100, "high": 102, "low": 98, "close": 101},
+        ]
+
+
 class StubBalancedRecommendationRepository:
     def __init__(self) -> None:
         self.case_type_queries = []