feat: demo CORS, demo client, openpyxl catalog load

- Load consumable catalog XLSX with openpyxl and drop the pandas dependency.
- Add optional demo CORS settings and FastAPI CORSMiddleware for browser clients.
- Add scripts/demo_client static page and local server for API smoke tests.

Made-with: Cursor

app/config.py

@@ -135,6 +135,20 @@ class Settings(BaseSettings):
     #: 上传医生语音 WAV 的最大字节数（默认 10MB）。
     voice_upload_max_bytes: int = Field(default=10 * 1024 * 1024, ge=64, le=50 * 1024 * 1024)
 
+    # --- Demo 客户端跨源（仅用于 scripts/demo_client 联调；生产置 false） ---
+    #: 为 true 时挂载 CORSMiddleware，便于浏览器 demo 从另一个端口访问本服务。
+    demo_cors_enabled: bool = True
+    #: 逗号分隔的允许来源；`*` 表示允许全部来源（demo/联调用，生产应显式指定）。
+    demo_cors_origins: str = "*"
+
+    def parsed_demo_cors_origins(self) -> list[str]:
+        raw = (self.demo_cors_origins or "").strip()
+        if not raw:
+            return []
+        if raw == "*":
+            return ["*"]
+        return [item.strip() for item in raw.split(",") if item.strip()]
+
     @field_validator("consumable_classifier_weights", mode="before")
     @classmethod
     def consumable_classifier_weights_default(cls, value: object) -> str:

app/services/consumable_vision_algorithm.py

@@ -5,6 +5,7 @@
 
 from __future__ import annotations
 
+import math
 import os
 import sys
 from collections import Counter
@@ -13,8 +14,8 @@ from pathlib import Path
 from threading import Lock
 
 import numpy as np
-import pandas as pd
 from loguru import logger
+from openpyxl import load_workbook
 from ultralytics import YOLO
 
 from app.config import Settings, settings
@@ -74,14 +75,22 @@ class ClsTop3:
     t3_pid: str
 
 
-def _find_col(df: pd.DataFrame, want: str) -> str | None:
+def _find_col_idx(headers: list[object], want: str) -> int | None:
     want = want.strip()
-    for c in df.columns:
-        if str(c).strip() == want:
-            return str(c)
+    for i, h in enumerate(headers):
+        if str(h).strip() == want:
+            return i
     return None
 
 
+def _cell_empty(value: object) -> bool:
+    if value is None:
+        return True
+    if isinstance(value, float) and math.isnan(value):
+        return True
+    return False
+
+
 def _norm_product_name(name: str) -> str:
     s = (name or "").strip()
     if s == "一次性医用垫单":
@@ -91,29 +100,41 @@ def _norm_product_name(name: str) -> str:
 
 def load_name_to_product_code(xlsx: Path) -> dict[str, str]:
     """商品名称 -> 产品编码（白名单键为归一化后的名称）。"""
-    df = pd.read_excel(xlsx, sheet_name=0)
-    c_code = _find_col(df, "产品编码")
-    c_name = _find_col(df, "商品名称")
-    if c_code is None or c_name is None:
-        raise ValueError("Excel 缺少「产品编码」或「商品名称」列")
-    m: dict[str, str] = {}
-    dups: set[str] = set()
-    for _, row in df.iterrows():
-        raw = row.get(c_name)
-        if raw is None or (isinstance(raw, float) and pd.isna(raw)):
-            continue
-        n = _norm_product_name(str(raw).strip())
-        if not n:
-            continue
-        code = row.get(c_code)
-        if code is None or (isinstance(code, float) and pd.isna(code)):
-            continue
-        sc = str(code).strip()
-        if n in m and m[n] != sc:
-            dups.add(n)
-            continue
-        if n not in m:
-            m[n] = sc
+    wb = load_workbook(filename=str(xlsx), read_only=True, data_only=True)
+    try:
+        ws = wb.worksheets[0]
+        rows = ws.iter_rows(values_only=True)
+        header = next(rows, None)
+        if header is None:
+            raise ValueError("Excel 为空")
+        headers = list(header)
+        i_code = _find_col_idx(headers, "产品编码")
+        i_name = _find_col_idx(headers, "商品名称")
+        if i_code is None or i_name is None:
+            raise ValueError("Excel 缺少「产品编码」或「商品名称」列")
+
+        m: dict[str, str] = {}
+        dups: set[str] = set()
+        for row in rows:
+            if not row:
+                continue
+            raw = row[i_name] if i_name < len(row) else None
+            if _cell_empty(raw):
+                continue
+            n = _norm_product_name(str(raw).strip())
+            if not n:
+                continue
+            code = row[i_code] if i_code < len(row) else None
+            if _cell_empty(code):
+                continue
+            sc = str(code).strip()
+            if n in m and m[n] != sc:
+                dups.add(n)
+                continue
+            if n not in m:
+                m[n] = sc
+    finally:
+        wb.close()
     if dups:
         logger.warning(
             "Excel 中以下商品名称对应多组产品编码，已保留首次映射: {}",