feat: 消费停录汇总与查结果同口径，并更新分类与 TSV

- 停录时由 details 经 build_consumption_summary 写 TSV/终端汇总，移除 consumption_log_totals 与时间窗累加
- 更新 consumable_classifier 权重、YAML 标签与 consumable_vision_algorithm
- 扩展 consumption TSV 相关测试与配置注释

Made-with: Cursor

app/services/consumable_vision_algorithm.py

@@ -5,8 +5,9 @@
 
 from __future__ import annotations
 
-from typing import Any
+import functools
 import os
+from typing import Any
 import sys
 from collections import Counter
 from dataclasses import dataclass
@@ -126,6 +127,38 @@ def load_name_to_label_id_from_yaml(path: Path) -> dict[str, str]:
     return out
 
 
+def load_index_to_label_id_from_yaml(path: Path) -> dict[int, str]:
+    """与 ``label_id`` 段：类索引 -> 业务 id 字符串；类名与 YAML 略有不一致时仍可落盘到正确 id。"""
+    try:
+        raw = path.read_text(encoding="utf-8")
+    except OSError:
+        return {}
+    try:
+        data: Any = yaml.safe_load(raw)
+    except yaml.YAMLError:
+        return {}
+    if not isinstance(data, dict):
+        return {}
+    label_raw = data.get("label_id")
+    if not isinstance(label_raw, dict):
+        return {}
+    out: dict[int, str] = {}
+    for k, v in label_raw.items():
+        try:
+            i = int(k)
+        except (TypeError, ValueError):
+            continue
+        if v is None or (isinstance(v, str) and not str(v).strip()):
+            continue
+        out[i] = str(v).strip()
+    return out
+
+
+@functools.lru_cache(maxsize=8)
+def _cached_index_to_label_id(path_resolved: str, mtime_ns: int) -> dict[int, str]:
+    return load_index_to_label_id_from_yaml(Path(path_resolved))
+
+
 def list_sorted_class_names_from_yaml(path: Path) -> list[str]:
     """自 ``names`` 段按类索引升序取类名字符串（与训练/权重一致）。"""
     try:
@@ -218,7 +251,11 @@ def _probs_data_to_numpy1d(raw) -> np.ndarray:
 
 
 def cls_top3_from_result(
-    cls: YOLO, r, name_to_code: dict[str, str]
+    cls: YOLO,
+    r,
+    name_to_code: dict[str, str],
+    *,
+    index_to_label_id: dict[int, str] | None = None,
 ) -> ClsTop3 | None:
     pr = r[0].probs
     if pr is None:
@@ -244,6 +281,7 @@ def cls_top3_from_result(
 
     n2 = n3 = ""
     c2 = c3 = 0.0
+    i2 = i3 = -1
     if len(t5i) > 1:
         i2 = int(t5i[1])
         n2 = str(cls.names.get(i2, "")).strip()
@@ -253,12 +291,19 @@ def cls_top3_from_result(
         n3 = str(cls.names.get(i3, "")).strip()
         c3 = _conf_for_idx(i3)
 
-    def _pid(label: str) -> str:
+    idx_extras = index_to_label_id or {}
+
+    def _pid(label: str, class_idx: int) -> str:
         lb = (label or "").strip()
         if not lb:
             return ""
         norm = _norm_product_name(lb)
-        return (name_to_code.get(norm) or name_to_code.get(lb) or "").strip()
+        c = (name_to_code.get(norm) or name_to_code.get(lb) or "").strip()
+        if c:
+            return c
+        if class_idx >= 0 and class_idx in idx_extras:
+            return idx_extras[class_idx]
+        return ""
 
     return ClsTop3(
         t1_name=n1,
@@ -267,9 +312,9 @@ def cls_top3_from_result(
         t2_conf=c2,
         t3_name=n3,
         t3_conf=c3,
-        t1_pid=_pid(n1),
-        t2_pid=_pid(n2),
-        t3_pid=_pid(n3),
+        t1_pid=_pid(n1, t1i),
+        t2_pid=_pid(n2, i2),
+        t3_pid=_pid(n3, i3),
     )
 
 
@@ -475,12 +520,31 @@ class ConsumableVisionAlgorithmService:
         except Exception as exc:
             raise PredictionError(f"耗材分类推理失败: {exc}") from exc
 
-        snap = cls_top3_from_result(cls_model, r, name_to_code)
+        yp = Path(self._s.consumable_classifier_labels_yaml_path).expanduser()
+        if yp.is_file():
+            st = yp.stat()
+            index_to_label_id = _cached_index_to_label_id(
+                str(yp.resolve()), st.st_mtime_ns
+            )
+        else:
+            index_to_label_id = {}
+
+        snap = cls_top3_from_result(
+            cls_model,
+            r,
+            name_to_code,
+            index_to_label_id=index_to_label_id,
+        )
         if snap is None:
             return None
         if snap.t1_conf < self._s.consumable_min_cls_confidence:
             return None
         pname = snap.t1_name
-        if not pname or pname not in whitelist:
+        if not pname:
             return None
-        return snap
+        pnorm = _norm_product_name(pname)
+        if pnorm in whitelist or pname in whitelist:
+            return snap
+        if (snap.t1_pid or "").strip():
+            return snap
+        return None