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app.py

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+import pandas as pd
+import openpyxl
+from openpyxl.styles import PatternFill, Font
+import re
+import gradio as gr
+import os
+import json
+import math
+
+DB_TK_FILE = "db_tk.xlsx"
+DB_DINH_FILE = "db_dinh.xlsx"
+DB_DVT_FILE = "db_dvt.xlsx"
+DB_LIEU_FILE = "db_lieu.xlsx"
+DB_NL_FILE = "db_nl.xlsx"
+EXCEPTION_FILE = "exceptions.json"
+
+def normalize(value):
+    if pd.isna(value):
+        return ""
+    return str(value).strip().replace(",", ".")
+
+def normalize_unit(unit):
+    if pd.isna(unit):
+        return ""
+    return str(unit).strip().lower()
+
+def normalize_drug_name(name):
+    return str(name).strip().lower() if pd.notna(name) else ""
+
+def trim_column(df_input):
+    if "LIEU_DUNG" in df_input.columns:
+        df_input["LIEU_DUNG"] = df_input["LIEU_DUNG"].astype(str).str.strip()
+    if "DON_VI_TINH" in df_input.columns:
+        df_input["DON_VI_TINH"] = df_input["DON_VI_TINH"].astype(str).str.strip()
+    return df_input
+
+def extract_units(lieu_dung_str):
+    text = str(lieu_dung_str).strip().lower()
+    m1 = re.match(r"^(\d+(?:[.,]\d+|\/\d+)?)[ ]*([^\s\/\[\]\*]+)", text)
+    unit1 = m1.group(2) if m1 else ""
+    m2 = re.search(r"\[\s*(\d+(?:[.,]\d+|\/\d+)?)\s*([^\s\/\[\]]+)", text)
+    unit2 = m2.group(2) if m2 else ""
+    return unit1.strip(), unit2.strip()
+
+def get_special_format_set_from_file(file_path):
+    """
+    Đọc file DB_DINH và trả về set các tuple (normalized_ten_thuoc, normalized_lieu_dung, normalized_so_luong).
+    """
+    if not os.path.exists(file_path):
+        return set()
+    try:
+        df = pd.read_excel(file_path, header=0)
+        if not all(col in df.columns for col in ["TEN_THUOC", "LIEU_DUNG", "SO_LUONG"]):
+            return set()
+        exceptions = set()
+        for _, row in df.iterrows():
+            ten = normalize_drug_name(row["TEN_THUOC"])
+            lieu = normalize(row["LIEU_DUNG"])
+            so_luong = normalize(row["SO_LUONG"])
+            if ten and lieu and so_luong:
+                exceptions.add((ten, lieu, so_luong))
+        return exceptions
+    except Exception:
+        return set()
+
+def get_special_qty_set_from_file(file_path):
+    """
+    Đọc file DB_TK và trả về set các tuple (normalized_ten_thuoc, normalized_lieu_dung, normalized_so_luong).
+    """
+    if not os.path.exists(file_path):
+        return set()
+    try:
+        df = pd.read_excel(file_path, header=0)
+        if not all(col in df.columns for col in ["TEN_THUOC", "LIEU_DUNG", "SO_LUONG"]):
+            return set()
+        exceptions = set()
+        for _, row in df.iterrows():
+            ten = normalize_drug_name(row["TEN_THUOC"])
+            lieu = normalize(row["LIEU_DUNG"])
+            so_luong = normalize(row["SO_LUONG"])
+            if ten and lieu and so_luong:
+                exceptions.add((ten, lieu, so_luong))
+        return exceptions
+    except Exception:
+        return set()
+
+def get_special_unit_set_from_file(file_path):
+    """
+    Đọc file DB_DVT và trả về set các tuple (normalized_ten_thuoc, normalized_lieu_dung, normalized_so_luong).
+    """
+    if not os.path.exists(file_path):
+        return set()
+    try:
+        df = pd.read_excel(file_path, header=0)
+        if not all(col in df.columns for col in ["TEN_THUOC", "LIEU_DUNG", "SO_LUONG"]):
+            return set()
+        exceptions = set()
+        for _, row in df.iterrows():
+            ten = normalize_drug_name(row["TEN_THUOC"])
+            lieu = normalize(row["LIEU_DUNG"])
+            so_luong = normalize(row["SO_LUONG"])
+            if ten and lieu and so_luong:
+                exceptions.add((ten, lieu, so_luong))
+        return exceptions
+    except Exception:
+        return set()
+
+def get_lieu_exceptions(file_path):
+    """
+    Đọc file DB_LIEU và trả về set các tuple (normalized_ten_thuoc, normalized_lieu_dung, normalized_so_luong).
+    """
+    if not os.path.exists(file_path):
+        return set()
+    try:
+        df = pd.read_excel(file_path, header=0)
+        if not all(col in df.columns for col in ["TEN_THUOC", "LIEU_DUNG", "SO_LUONG"]):
+            return set()
+        exceptions = set()
+        for _, row in df.iterrows():
+            ten = normalize_drug_name(row["TEN_THUOC"])
+            lieu = normalize(row["LIEU_DUNG"])
+            so_luong = normalize(row["SO_LUONG"])
+            if ten and lieu and so_luong:
+                exceptions.add((ten, lieu, so_luong))
+        return exceptions
+    except Exception:
+        return set()
+
+def get_allowed_exceptions_tuples(file_path):
+    """
+    Đọc file DB_NL và trả về set các tuple (normalized_ten_thuoc, normalized_lieu_dung, normalized_so_luong).
+    """
+    if not os.path.exists(file_path):
+        return set()
+    try:
+        df = pd.read_excel(file_path, header=0)
+        if not all(col in df.columns for col in ["TEN_THUOC", "LIEU_DUNG", "SO_LUONG"]):
+            return set()
+        exceptions = set()
+        for _, row in df.iterrows():
+            ten = normalize_drug_name(row["TEN_THUOC"])
+            lieu = normalize(row["LIEU_DUNG"])
+            so_luong = normalize(row["SO_LUONG"])
+            if ten and lieu and so_luong:
+                exceptions.add((ten, lieu, so_luong))
+        return exceptions
+    except Exception:
+        return set()
+
+def load_exceptions():
+    if not os.path.exists(EXCEPTION_FILE):
+        return {
+            "format": [],
+            "allowed": [],
+            "unitAllowed": []
+        }
+    with open(EXCEPTION_FILE, "r", encoding="utf-8") as f:
+        data = json.load(f)
+    return {
+        "format": [normalize(x) for x in data.get("formatErrors", [])],
+        "allowed": [normalize(x) for x in data.get("allowedExceptions", [])],
+        "unitAllowed": [normalize(x) for x in data.get("unitAllowed", [])]
+    }
+
+def save_exceptions_from_files(db_tk_file, db_dinh_file, db_dvt_file, db_lieu_file, db_nl_file):
+    file_map = [
+        (db_tk_file, DB_TK_FILE),
+        (db_dinh_file, DB_DINH_FILE),
+        (db_dvt_file, DB_DVT_FILE),
+        (db_lieu_file, DB_LIEU_FILE),
+        (db_nl_file, DB_NL_FILE)
+    ]
+    for fileobj, target in file_map:
+        if fileobj is not None:
+            try:
+                if hasattr(fileobj, "name"):
+                    with open(fileobj.name, "rb") as src, open(target, "wb") as dst:
+                        dst.write(src.read())
+                else:
+                    fileobj.seek(0)
+                    with open(target, "wb") as f:
+                        f.write(fileobj.read())
+            except Exception as e:
+                return f"Lỗi lưu {target}: {e}"
+
+    def read_col_a(fileobj):
+        if fileobj is None:
+            return []
+        try:
+            if hasattr(fileobj, "name"):
+                df = pd.read_excel(fileobj.name, sheet_name=0, header=0)
+            else:
+                fileobj.seek(0)
+                df = pd.read_excel(fileobj, sheet_name=0, header=0)
+            return [str(x).strip() for x in df.iloc[:,0] if pd.notna(x) and str(x).strip() != ""]
+        except Exception:
+            return []
+    format_list = read_col_a(db_dinh_file)
+    allowed_list = [] # không dùng allowed_list kiểu cũ nữa
+    unitallowed_list = read_col_a(db_dvt_file)
+    if os.path.exists(EXCEPTION_FILE):
+        with open(EXCEPTION_FILE, "r", encoding="utf-8") as f:
+            data = json.load(f)
+    else:
+        data = {
+            "formatErrors": [],
+            "allowedExceptions": [],
+            "unitAllowed": []
+        }
+    if format_list:
+        data["formatErrors"] = format_list
+    if unitallowed_list:
+        data["unitAllowed"] = unitallowed_list
+    with open(EXCEPTION_FILE, "w", encoding="utf-8") as f:
+        json.dump(data, f, indent=2, ensure_ascii=False)
+
+    return "✅ Đã cập nhật DB_TK, DB_DINH, DB_DVT, DB_LIEU, DB_NL!"
+
+def highlight_insulin_errors(df_input, insulin_file):
+    if insulin_file is None:
+        return [], []
+
+    try:
+        df_insulin = pd.read_excel(insulin_file.name if hasattr(insulin_file, "name") else insulin_file, header=0)
+    except Exception:
+        return [], []
+
+    insulin_map = {}
+    for idx, row in df_insulin.iterrows():
+        ten = normalize_drug_name(row.get("TEN_THUOC", ""))
+        try:
+            hamluong = float(str(row.get("HAM_LUONG", "")).replace(",", "."))
+            so_sanh = float(str(row.get("SO_LUONG_SO_SANH", "")).replace(",", "."))
+        except Exception:
+            continue
+        if ten and hamluong is not None and so_sanh is not None:
+            insulin_map[ten] = (hamluong, so_sanh)
+
+    error_rows_cam = []
+    error_rows_xanh = []
+    for idx, row in df_input.iterrows():
+        ten_thuoc = normalize_drug_name(row.get("TEN_THUOC", ""))
+        if ten_thuoc not in insulin_map:
+            continue
+        ham_luong, so_sanh = insulin_map[ten_thuoc]
+        lieu_goc = str(row.get("LIEU_DUNG", ""))
+        lieu = re.sub(r"\s+", "", lieu_goc)
+        matches = re.findall(r":(\d+)[iI][uU]\/lần", lieu)
+        tong_1_lan = sum(int(m) for m in matches) if matches else 0
+        match_ngay = re.search(r"\[(\d+)[iI][uU]\/ngày\]", lieu)
+        so_trong_ngay = int(match_ngay.group(1)) if match_ngay else 0
+
+        if tong_1_lan != so_trong_ngay or tong_1_lan == 0 or so_trong_ngay == 0:
+            error_rows_xanh.append(idx)
+        else:
+            match_son = re.search(r"\*(\d+)ngày", lieu)
+            so_ngay = int(match_son.group(1)) if match_son else 0
+            tong_chi_dinh = so_trong_ngay * so_ngay
+            so_luong_thuc_te = row.get("SO_LUONG", row.get("So_luong", row.get("so_luong", row.get("SỐ_LƯỢNG", row.get("M", None)))))
+            try:
+                so_luong_thuc_te = float(str(so_luong_thuc_te).replace(",", "."))
+            except Exception:
+                continue
+            tong_thuc_te = ham_luong * so_luong_thuc_te
+            hieu = tong_thuc_te - tong_chi_dinh
+            if hieu >= so_sanh:
+                error_rows_cam.append(idx)
+    return error_rows_cam, error_rows_xanh
+
+def highlight_invalid_rows(df_input, exceptions, special_format_tuples, lieu_exceptions, insulin_xanh_rows=None, allowed_exceptions=None):
+    pattern = re.compile(
+        r"^(\d+(?:[.,]\d+|\/\d+)?)\s+"
+        r"(ml|mg|viên|gói|chai|lọ|ống|túi|giọt|iu|ui)\/lần\s*\*\s*"
+        r"(\d+)\s*lần\/ngày\s*\*\s*"
+        r"(\d+(?:[.,]\d+|\/\d+)?)\s*ngày\s*\["
+        r"(\d+(?:[.,]\d+|\/\d+)?)\s+"
+        r"(ml|mg|viên|gói|chai|lọ|ống|túi|giọt|iu|ui)\/ngày\]\.$"
+    )
+    dose_error_rows, format_error_rows = [], []
+    insulin_xanh_rows = set(insulin_xanh_rows) if insulin_xanh_rows else set()
+    allowed_exceptions = allowed_exceptions if allowed_exceptions is not None else set()
+    if "LIEU_DUNG" in df_input.columns:
+        for index, row in df_input.iterrows():
+            if index in insulin_xanh_rows:
+                dose_error_rows.append(index)
+                continue
+            ten_thuoc = normalize_drug_name(row.get("TEN_THUOC", row.get("ten_thuoc", "")))
+            lieu_value = normalize(row.get("LIEU_DUNG", ""))
+            so_luong = normalize(row.get("SO_LUONG", row.get("So_luong", row.get("so_luong", row.get("SỐ_LƯỢNG", row.get("M", None))))))
+            if (ten_thuoc, lieu_value, so_luong) in allowed_exceptions:
+                continue
+            if (ten_thuoc, lieu_value, so_luong) in lieu_exceptions:
+                continue
+            if (ten_thuoc, lieu_value, so_luong) in special_format_tuples:
+                continue
+            if lieu_value in exceptions.get("format", []):
+                format_error_rows.append(index)
+                continue
+            match = pattern.match(lieu_value)
+            if match:
+                try:
+                    dose_per_time = float(match.group(1).replace(",", ".").replace("/", "/1.0"))
+                    times_per_day = int(match.group(3))
+                    actual_daily_dose = float(match.group(5).replace(",", ".").replace("/", "/1.0"))
+                    expected = dose_per_time * times_per_day
+                    if not math.isclose(expected, actual_daily_dose, rel_tol=1e-3):
+                        dose_error_rows.append(index)
+                except Exception:
+                    dose_error_rows.append(index)
+            else:
+                format_error_rows.append(index)
+    return dose_error_rows, format_error_rows
+
+def highlight_unit_errors(df_input, exceptions, special_unit_tuples, allowed_exceptions=None):
+    unit_error_rows = []
+    allowed_unit_lieudung = set([normalize(x) for x in exceptions.get("unitAllowed", [])])
+    allowed_exceptions = allowed_exceptions if allowed_exceptions is not None else set()
+    for idx, row in df_input.iterrows():
+        ten_thuoc = normalize_drug_name(row.get("TEN_THUOC", row.get("ten_thuoc", "")))
+        lieu_dung_raw = row.get("LIEU_DUNG", "")
+        don_vi_tinh_raw = row.get("DON_VI_TINH", "")
+        lieu_dung_norm = normalize(lieu_dung_raw)
+        don_vi_tinh_norm = normalize_unit(don_vi_tinh_raw)
+        so_luong = normalize(row.get("SO_LUONG", row.get("So_luong", row.get("so_luong", row.get("SỐ_LƯỢNG", row.get("M", None))))))
+        if (ten_thuoc, lieu_dung_norm, so_luong) in allowed_exceptions:
+            continue
+        if (ten_thuoc, lieu_dung_norm, so_luong) in special_unit_tuples:
+            continue
+        if lieu_dung_norm in allowed_unit_lieudung:
+            continue
+        unit1, unit2 = extract_units(lieu_dung_raw)
+        unit1_norm = normalize_unit(unit1)
+        unit2_norm = normalize_unit(unit2)
+        if not don_vi_tinh_norm or don_vi_tinh_norm == "nan":
+            unit_error_rows.append(idx)
+            continue
+        if not (unit1_norm == don_vi_tinh_norm and unit2_norm == don_vi_tinh_norm):
+            unit_error_rows.append(idx)
+    return unit_error_rows
+
+def highlight_wrong_quantity_rows(df_input, special_qty_tuples, allowed_exceptions=None):
+    wrong_qty_rows = []
+    allowed_exceptions = allowed_exceptions if allowed_exceptions is not None else set()
+    for idx, row in df_input.iterrows():
+        ten_thuoc = normalize_drug_name(row.get("TEN_THUOC", row.get("ten_thuoc", "")))
+        lieu_dung = str(row.get("LIEU_DUNG", ""))
+        lieu_dung_norm = normalize(lieu_dung)
+        so_luong = normalize(row.get("SO_LUONG", row.get("So_luong", row.get("so_luong", row.get("SỐ_LƯỢNG", row.get("M", None))))))
+        if (ten_thuoc, lieu_dung_norm, so_luong) in allowed_exceptions:
+            continue
+        if (ten_thuoc, lieu_dung_norm, so_luong) in special_qty_tuples:
+            continue
+        so_luong_thuc_te = row.get("SO_LUONG", row.get("So_luong", row.get("so_luong", row.get("SỐ_LƯỢNG", row.get("M", None)))))
+        if so_luong_thuc_te is None and isinstance(row, (pd.Series, dict)):
+            try:
+                so_luong_thuc_te = row.iloc[12]
+            except Exception:
+                continue
+        if pd.isna(so_luong_thuc_te):
+            continue
+        so_ngay_match = re.search(r"\*\s*(\d+(?:[.,]\d+|\/\d+)?)\s*ngày", lieu_dung)
+        so_luong_ngay_match = re.search(r"\[\s*(\d+(?:[.,]\d+|\/\d+)?)\s*[^\]]+\/ngày\]", lieu_dung)
+        if not so_ngay_match or not so_luong_ngay_match:
+            continue
+        try:
+            so_ngay = float(so_ngay_match.group(1).replace(",", "."))
+            so_luong_moi_ngay = float(so_luong_ngay_match.group(1).replace(",", "."))
+            so_luong_can_ke = so_ngay * so_luong_moi_ngay
+            try:
+                so_luong_thuc_te_val = float(str(so_luong_thuc_te).replace(",", "."))
+            except Exception:
+                continue
+            if not math.isclose(so_luong_can_ke, so_luong_thuc_te_val, rel_tol=1e-2):
+                wrong_qty_rows.append(idx)
+        except Exception:
+            continue
+    return wrong_qty_rows
+
+def update_excel_with_errors(wb, insulin_errors, dose_errors, format_errors, unit_errors, wrong_qty_errors, output_path):
+    ws = wb.active
+    orange_fill = PatternFill(start_color="FFA500", end_color="FFA500", fill_type="solid") # Cam
+    yellow_fill = PatternFill(start_color="FFFF00", end_color="FFFF00", fill_type="solid")
+    blue_fill = PatternFill(start_color="0088FF", end_color="0088FF", fill_type="solid")
+    red_fill = PatternFill(start_color="FF0000", end_color="FF0000", fill_type="solid")
+    purple_fill = PatternFill(start_color="845EC2", end_color="845EC2", fill_type="solid")
+    white_font = Font(color="FFFFFF")
+    insulin_set = set(insulin_errors)
+    wrong_qty_set = set(wrong_qty_errors)
+    unit_set = set(unit_errors)
+    dose_set = set(dose_errors)
+    format_set = set(format_errors)
+    for idx in range(2, ws.max_row + 1):
+        row_idx = idx - 2
+        if row_idx in insulin_set:
+            ws[f"I{idx}"].fill = orange_fill
+        elif row_idx in wrong_qty_set:
+            ws[f"I{idx}"].fill = yellow_fill
+        elif row_idx in unit_set:
+            ws[f"I{idx}"].fill = purple_fill
+            ws[f"I{idx}"].font = white_font
+        elif row_idx in format_set:
+            ws[f"I{idx}"].fill = red_fill
+        elif row_idx in dose_set:
+            ws[f"I{idx}"].fill = blue_fill
+    wb.save(output_path)
+    return output_path
+
+def process_excel(file, insulin_file=None):
+    input_path = file.name
+    try:
+        df = pd.read_excel(input_path)
+        wb = openpyxl.load_workbook(input_path)
+    except Exception as e:
+        return None, None, None, None, None, None, f"❌ Lỗi khi đọc file Excel: {e}"
+
+    df = trim_column(df)
+    exceptions = load_exceptions()
+    allowed_exceptions = get_allowed_exceptions_tuples(DB_NL_FILE)
+    special_qty_tuples = get_special_qty_set_from_file(DB_TK_FILE)
+    special_format_tuples = get_special_format_set_from_file(DB_DINH_FILE)
+    special_unit_tuples = get_special_unit_set_from_file(DB_DVT_FILE)
+    lieu_exceptions = get_lieu_exceptions(DB_LIEU_FILE)
+    insulin_errors_cam, insulin_errors_xanh = highlight_insulin_errors(df, insulin_file) if insulin_file else ([], [])
+
+    dose_errors, format_errors = highlight_invalid_rows(df, exceptions, special_format_tuples, lieu_exceptions, insulin_errors_xanh, allowed_exceptions)
+    unit_errors = highlight_unit_errors(df, exceptions, special_unit_tuples, allowed_exceptions)
+    wrong_qty_errors = highlight_wrong_quantity_rows(df, special_qty_tuples, allowed_exceptions)
+
+    used = set(insulin_errors_cam)
+    wrong_qty_errors = [i for i in wrong_qty_errors if i not in used]
+    used |= set(wrong_qty_errors)
+    unit_errors = [i for i in unit_errors if i not in used]
+    used |= set(unit_errors)
+    format_errors = [i for i in format_errors if i not in used]
+    used |= set(format_errors)
+    dose_errors = [i for i in dose_errors if i not in used]
+
+    output_path = "ketqua_" + os.path.basename(input_path)
+    update_excel_with_errors(wb, insulin_errors_cam, dose_errors, format_errors, unit_errors, wrong_qty_errors, output_path)
+
+    format_path = "sai_dinhdang_" + os.path.basename(input_path)
+    dose_path = "sai_lieu_" + os.path.basename(input_path)
+    unit_path = "sai_donvitinh_" + os.path.basename(input_path)
+    qty_path = "sai_soluong_" + os.path.basename(input_path)
+    insulin_path = "insulin_soluong_" + os.path.basename(input_path)
+    df.iloc[format_errors].to_excel(format_path, index=False)
+    df.iloc[dose_errors].to_excel(dose_path, index=False)
+    df.iloc[unit_errors].to_excel(unit_path, index=False)
+    df.iloc[wrong_qty_errors].to_excel(qty_path, index=False)
+    if insulin_errors_cam:
+        df.iloc[insulin_errors_cam].to_excel(insulin_path, index=False)
+    else:
+        insulin_path = None
+
+    msg = []
+    if insulin_errors_cam:
+        msg.append(f"🟧 Có {len(insulin_errors_cam)} dòng Insulin sai số lượng chỉ định (ưu tiên màu cam).")
+    if insulin_errors_xanh:
+        msg.append(f"🔵 Có {len(insulin_errors_xanh)} dòng Insulin sai liều (tô xanh, không đúng tổng IU/lần/ngày).")
+    if wrong_qty_errors:
+        msg.append(f"🟡 Có {len(wrong_qty_errors)} dòng sai số lượng th��c kê.")
+    if dose_errors:
+        msg.append(f"🔵 Có {len(dose_errors)} dòng sai liều.")
+    if format_errors:
+        msg.append(f"🔴 Có {len(format_errors)} dòng sai định dạng.")
+    if unit_errors:
+        msg.append(f"🟣 Có {len(unit_errors)} dòng sai đơn vị tính.")
+    if not msg:
+        msg.append("✅ Không phát hiện lỗi nào.")
+    notice = "\n".join(msg)
+    return (
+        output_path,
+        format_path,
+        dose_path,
+        unit_path,
+        qty_path,
+        insulin_path,
+        notice
+    )
+
+with gr.Blocks(title="Kiểm tra định dạng & liều dùng") as demo:
+    gr.Markdown("# 💊 Kiểm tra đơn thuốc ngoại trú")
+    gr.HTML("<span style='color:#0077b6;font-weight:bold'>Được tạo bởi DSCKI. Nguyễn Thành Trung - Bệnh viện Đa khoa khu vực Bảo Thắng.</span>")
+    with gr.Row():
+        with gr.Column():
+            file_input = gr.File(label="Tải lên file dinhdang 130")
+            insulin_input = gr.File(label="Tải lên file Insulin")
+            check_btn = gr.Button("✅ Kiểm tra",variant="primary")
+        with gr.Column():
+            notification = gr.Textbox(label="Thông báo", interactive=False,lines=4)
+            file_output = gr.File(label="File tổng kiểm tra (tô màu)")
+            file_format = gr.File(label="File lỗi định dạng")
+            file_dose = gr.File(label="File lỗi liều")
+            file_unit = gr.File(label="File lỗi đơn vị tính")
+            file_qty = gr.File(label="File lỗi số lượng thực kê")
+            file_insulin = gr.File(label="File lỗi Insulin (cam)")
+
+    check_btn.click(
+        fn=process_excel,
+        inputs=[file_input, insulin_input],
+        outputs=[file_output, file_format, file_dose, file_unit, file_qty, file_insulin, notification]
+    )
+
+    with gr.Tab("⚙️ Chỉnh sửa ngoại lệ"):
+        db_dinh_file = gr.File(label="DB_DINH")
+        db_dvt_file = gr.File(label="DB_DVT")
+        db_lieu_file = gr.File(label="DB_LIEU")
+        db_nl_file = gr.File(label="DB_NL")
+        db_tk_file = gr.File(label="DB_TK")
+        save_btn = gr.Button("💾 Cập nhật danh sách",variant="primary")
+        result_text = gr.Textbox(label="Trạng thái lưu", interactive=False)
+        save_btn.click(
+            fn=save_exceptions_from_files,
+            inputs=[db_tk_file, db_dinh_file, db_dvt_file, db_lieu_file, db_nl_file],
+            outputs=result_text
+        )
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

@@ -0,0 +1,3 @@
+gradio
+pandas
+openpyxl