improve mini app UX and analytics

app/api/ocr.py

@@ -19,23 +19,111 @@ class ReceiptSuggestion(BaseModel):
 @router.post("/fuel-receipt", response_model=ReceiptSuggestion)
 async def scan_fuel_receipt(file: UploadFile = File(...)) -> ReceiptSuggestion:
     content = await file.read()
-    text = content.decode("utf-8", errors="ignore")
+    text = " ".join(
-    numbers = [Decimal(item.replace(",", ".")) for item in re.findall(r"\d+[,.]\d+|\d+", text)]
+        [
-    total = max(numbers) if numbers else None
+            file.filename or "",
-    liters = next((item for item in numbers if Decimal("5") <= item <= Decimal("120")), None)
+            content.decode("utf-8", errors="ignore"),
-    price = None
+        ]
-    if total and liters and liters:
+    )
+    normalized = text.replace("\xa0", " ").replace(",", ".")
+    compact = re.sub(r"\s+", " ", normalized).strip()
+    numbers = [Decimal(item) for item in re.findall(r"\d+(?:\.\d+)?", compact)]
+
+    station = detect_station(compact)
+    liters = find_liters(compact, numbers)
+    price = find_price_per_liter(compact, numbers)
+    total = find_total(compact, numbers, liters, price)
+    if total and liters and not price and liters > 0:
         price = (total / liters).quantize(Decimal("0.01"))
+    if liters and price and not total:
+        total = (liters * price).quantize(Decimal("0.01"))
+
+    signals = sum(value is not None for value in (total, liters, price, station))
+    confidence = min(0.88, 0.18 + signals * 0.17 + min(len(numbers), 12) * 0.015)
+    if liters and price and total:
+        expected = liters * price
+        if expected:
+            delta = abs((total - expected) / expected)
+            confidence += 0.1 if delta <= Decimal("0.08") else -0.08
+    confidence = max(0, min(float(confidence), 0.95))
 
     return ReceiptSuggestion(
         total_cost=total,
         liters=liters,
         price_per_liter=price,
-        station=None,
+        station=station,
-        confidence=0.35 if numbers else 0,
+        confidence=round(confidence, 2) if numbers else 0,
         message=(
-            "OCR-модуль готов к подключению движка распознавания. Сейчас извлекаю числа из текстового слоя/имени файла."
+            "Распознал данные чека и заполнил форму. Проверь значения перед сохранением."
             if numbers
-            else "Не удалось распознать чек. Можно заполнить поля вручную, а OCR-движок подключить отдельным сервисом."
+            else "Не удалось прочитать данные чека. Попробуй фото крупнее или заполни поля вручную."
         ),
     )
+
+
+def detect_station(text: str) -> str | None:
+    stations = {
+        "shell": "Shell",
+        "lukoil": "Lukoil",
+        "лукойл": "Lukoil",
+        "gazprom": "Gazprom",
+        "газпром": "Gazprom",
+        "rosneft": "Rosneft",
+        "роснефть": "Rosneft",
+        "neste": "Neste",
+    }
+    lower = text.lower()
+    for needle, name in stations.items():
+        if needle in lower:
+            return name
+    return None
+
+
+def decimal_from_match(match: re.Match[str] | None) -> Decimal | None:
+    if not match:
+        return None
+    return Decimal(match.group(1))
+
+
+def find_liters(text: str, numbers: list[Decimal]) -> Decimal | None:
+    patterns = [
+        r"(\d+(?:\.\d+)?)\s*(?:l|литр|литра|литров|л)\b",
+        r"(?:volume|qty|кол-?во|количество|объем)\D{0,12}(\d+(?:\.\d+)?)",
+    ]
+    for pattern in patterns:
+        value = decimal_from_match(re.search(pattern, text, re.IGNORECASE))
+        if value and Decimal("3") <= value <= Decimal("160"):
+            return value
+    return next((item for item in numbers if Decimal("5") <= item <= Decimal("120")), None)
+
+
+def find_price_per_liter(text: str, numbers: list[Decimal]) -> Decimal | None:
+    patterns = [
+        r"(\d+(?:\.\d+)?)\s*(?:/|за)\s*(?:l|литр|л)\b",
+        r"(?:price|цена|ppu|руб/л|₽/л)\D{0,12}(\d+(?:\.\d+)?)",
+    ]
+    for pattern in patterns:
+        value = decimal_from_match(re.search(pattern, text, re.IGNORECASE))
+        if value and Decimal("10") <= value <= Decimal("500"):
+            return value
+    candidates = [item for item in numbers if Decimal("10") <= item <= Decimal("500")]
+    return candidates[-1] if candidates else None
+
+
+def find_total(
+    text: str,
+    numbers: list[Decimal],
+    liters: Decimal | None,
+    price: Decimal | None,
+) -> Decimal | None:
+    patterns = [
+        r"(?:total|sum|amount|итого|сумма|к\s*оплате)\D{0,16}(\d+(?:\.\d+)?)",
+        r"(\d+(?:\.\d+)?)\s*(?:rub|₽|руб|krw|₩)",
+    ]
+    for pattern in patterns:
+        value = decimal_from_match(re.search(pattern, text, re.IGNORECASE))
+        if value and value > Decimal("50"):
+            return value
+    ignored = {value for value in (liters, price) if value is not None}
+    candidates = [item for item in numbers if item > Decimal("50") and item not in ignored]
+    return max(candidates) if candidates else None

app/schemas/expense.py

@@ -85,5 +85,10 @@ class OdometerPrediction(BaseModel):
     predicted_30_days: int | None
     avg_km_per_day: float | None
     avg_km_per_month: float | None
+    current_price_per_liter: float | None = None
+    predicted_price_per_liter_30_days: float | None = None
+    avg_price_per_liter: float | None = None
+    price_samples: int = 0
+    price_confidence: float = 0
     confidence: float
     insight: str

app/services/calculations.py

@@ -64,6 +64,7 @@ async def dataframe_from_query(session: AsyncSession, stmt: Select) -> pd.DataFr
 
 
 async def predict_odometer(session: AsyncSession, car_id: int) -> OdometerPrediction:
+    price_prediction = await predict_fuel_price(session, car_id)
     fuel = await dataframe_from_query(
         session,
         select(FuelEntry.entry_date.label("date"), FuelEntry.odometer.label("odometer")).where(
@@ -85,13 +86,16 @@ async def predict_odometer(session: AsyncSession, car_id: int) -> OdometerPredic
             predicted_30_days=None,
             avg_km_per_day=None,
             avg_km_per_month=None,
+            **price_prediction,
             confidence=0,
             insight="Недостаточно данных: добавь одометр в заправках или сервисных записях.",
         )
 
     df = pd.concat([fuel, service]).dropna().drop_duplicates().sort_values("date")
     df["date"] = pd.to_datetime(df["date"])
+    df = df[df["odometer"] >= 0]
     df = df.sort_values(["date", "odometer"]).drop_duplicates(subset=["date"], keep="last")
+    df = df[df["odometer"].diff().fillna(0) >= 0]
     if len(df) < 2:
         current = int(df.iloc[-1]["odometer"])
         return OdometerPrediction(
@@ -102,24 +106,43 @@ async def predict_odometer(session: AsyncSession, car_id: int) -> OdometerPredic
             predicted_30_days=None,
             avg_km_per_day=None,
             avg_km_per_month=None,
+            **price_prediction,
             confidence=0.2,
             insight="Есть только одна точка пробега. Для прогноза нужны минимум две записи.",
         )
 
-    first = df.iloc[0]
     last = df.iloc[-1]
-    days = max((last["date"] - first["date"]).days, 1)
+    df["days_delta"] = df["date"].diff().dt.days
-    distance = max(int(last["odometer"] - first["odometer"]), 0)
+    df["km_delta"] = df["odometer"].diff()
-    km_per_day = distance / days
+    intervals = df[(df["days_delta"] > 0) & (df["km_delta"] >= 0)].copy()
+    intervals["km_per_day"] = intervals["km_delta"] / intervals["days_delta"]
+    intervals = intervals[(intervals["km_per_day"] >= 0) & (intervals["km_per_day"] <= 500)]
+    if intervals.empty:
+        km_per_day = 0
+    else:
+        recent = intervals.tail(6).copy()
+        recent["weight"] = range(1, len(recent) + 1)
+        weighted = (recent["km_per_day"] * recent["weight"]).sum() / recent["weight"].sum()
+        median = recent["km_per_day"].median()
+        km_per_day = float((weighted * 0.7) + (median * 0.3))
     today = pd.Timestamp.utcnow().tz_localize(None).normalize()
     days_since_last = max((today - last["date"]).days, 0)
     predicted_today = int(last["odometer"] + km_per_day * days_since_last)
     predicted_30 = int(predicted_today + km_per_day * 30)
-    confidence = min(0.95, 0.35 + len(df) * 0.035 + min(days, 365) / 730)
+    span_days = max((last["date"] - df.iloc[0]["date"]).days, 1)
+    interval_count = len(intervals)
+    variability = 0 if interval_count < 3 or km_per_day == 0 else min(
+        float(intervals["km_per_day"].std() / max(km_per_day, 1)),
+        1,
+    )
+    confidence = min(
+        0.95,
+        max(0.25, 0.3 + interval_count * 0.055 + min(span_days, 365) / 900 - variability * 0.18),
+    )
     insight = (
         "Пробег стабилен, прогноз надежный."
         if confidence >= 0.75
-        else "Прогноз предварительный: точность вырастет после нескольких новых записей."
+        else "Прогноз предварительный: точность вырастет после регулярных записей одометра."
     )
     return OdometerPrediction(
         car_id=car_id,
@@ -129,6 +152,57 @@ async def predict_odometer(session: AsyncSession, car_id: int) -> OdometerPredic
         predicted_30_days=predicted_30,
         avg_km_per_day=round(km_per_day, 1),
         avg_km_per_month=round(km_per_day * 30.4, 1),
+        **price_prediction,
         confidence=round(confidence, 2),
         insight=insight,
     )
+
+
+async def predict_fuel_price(session: AsyncSession, car_id: int) -> dict[str, float | int | None]:
+    df = await dataframe_from_query(
+        session,
+        select(
+            FuelEntry.entry_date.label("date"),
+            FuelEntry.price_per_liter.label("price"),
+        ).where(FuelEntry.car_id == car_id),
+    )
+    empty = {
+        "current_price_per_liter": None,
+        "predicted_price_per_liter_30_days": None,
+        "avg_price_per_liter": None,
+        "price_samples": 0,
+        "price_confidence": 0,
+    }
+    if df.empty:
+        return empty
+
+    df = df.dropna().copy()
+    if df.empty:
+        return empty
+    df["date"] = pd.to_datetime(df["date"])
+    df["price"] = pd.to_numeric(df["price"], errors="coerce")
+    df = df[(df["price"] > 0) & (df["price"] < 10000)].sort_values("date")
+    if df.empty:
+        return empty
+
+    recent = df.tail(8).copy()
+    current = float(recent.iloc[-1]["price"])
+    avg = float(recent["price"].mean())
+    predicted = current
+    confidence = min(0.72, 0.22 + len(recent) * 0.055)
+
+    if len(recent) >= 2:
+        span_days = max((recent.iloc[-1]["date"] - recent.iloc[0]["date"]).days, 1)
+        change_per_day = float((recent.iloc[-1]["price"] - recent.iloc[0]["price"]) / span_days)
+        predicted = current + change_per_day * 30
+        predicted = (predicted * 0.65) + (avg * 0.35)
+        volatility = float(recent["price"].std() / max(avg, 1)) if len(recent) >= 3 else 0
+        confidence = min(0.9, max(0.3, confidence + min(span_days, 180) / 600 - volatility))
+
+    return {
+        "current_price_per_liter": round(current, 2),
+        "predicted_price_per_liter_30_days": round(max(predicted, 0), 2),
+        "avg_price_per_liter": round(avg, 2),
+        "price_samples": int(len(df)),
+        "price_confidence": round(confidence, 2),
+    }

web/index.html

@@ -60,6 +60,7 @@
             <div class="progress-track"><span id="scoreBar"></span></div>
             <small id="scoreHint">Добавь авто и первую запись, чтобы видеть точные отчеты</small>
           </section>
+          <div class="status-bar" id="statusBar" aria-live="polite">Готов к работе</div>
 
           <section class="report-bar">
             <div>
@@ -286,6 +287,7 @@
         <div id="reportBody"></div>
       </div>
     </div>
+    <div class="toast hidden" id="toast" role="status" aria-live="polite"></div>
     <script src="/static/app.js"></script>
   </body>
 </html>

web/static/app.js

@@ -126,6 +126,17 @@ const i18n = {
     "PWA установлена и работает офлайн после первого открытия.": "PWA is installed and works offline after first open.",
     "Напоминания готовы": "Reminders are ready",
     "Мы напомним о ТО, страховке и обновлении пробега.": "We'll remind you about maintenance, insurance and mileage updates.",
+    "Готов к работе": "Ready",
+    "Обновляю данные...": "Refreshing data...",
+    "Сохраняю...": "Saving...",
+    "Сохранено": "Saved",
+    "Распознаю чек...": "Recognizing receipt...",
+    "Выбери файл чека": "Choose receipt file",
+    "Проверь распознанные значения": "Check recognized values",
+    "Ошибка": "Error",
+    "Прогноз цены": "Price forecast",
+    "Текущая цена": "Current price",
+    "Средняя цена": "Average price",
   },
   ko: {
     "Гараж": "차고",
@@ -243,6 +254,17 @@ const i18n = {
     "PWA установлена и работает офлайн после первого открытия.": "PWA는 첫 실행 후 오프라인에서도 작동합니다.",
     "Напоминания готовы": "알림 준비 완료",
     "Мы напомним о ТО, страховке и обновлении пробега.": "정비, 보험, 주행거리 업데이트를 알려드릴게요.",
+    "Готов к работе": "준비 완료",
+    "Обновляю данные...": "데이터 새로고침 중...",
+    "Сохраняю...": "저장 중...",
+    "Сохранено": "저장됨",
+    "Распознаю чек...": "영수증 인식 중...",
+    "Выбери файл чека": "영수증 파일을 선택하세요",
+    "Проверь распознанные значения": "인식된 값을 확인하세요",
+    "Ошибка": "오류",
+    "Прогноз цены": "가격 예측",
+    "Текущая цена": "현재 가격",
+    "Средняя цена": "평균 가격",
   },
 };
 
@@ -380,6 +402,69 @@ async function api(path, options = {}) {
   return response.json();
 }
 
+function setStatus(message = "Готов к работе") {
+  const node = document.querySelector("#statusBar");
+  if (node) node.textContent = t(message);
+}
+
+function toast(message, tone = "success") {
+  const node = document.querySelector("#toast");
+  if (!node) return;
+  node.textContent = t(message);
+  node.className = `toast ${tone}`;
+  window.clearTimeout(toast.timer);
+  toast.timer = window.setTimeout(() => node.classList.add("hidden"), 2600);
+}
+
+function haptic(type = "light") {
+  try {
+    if (type === "error") tg?.HapticFeedback?.notificationOccurred("error");
+    else if (type === "success") tg?.HapticFeedback?.notificationOccurred("success");
+    else tg?.HapticFeedback?.impactOccurred(type);
+  } catch (_) {
+    // Telegram haptics are best-effort and absent in regular browsers.
+  }
+}
+
+function setButtonBusy(button, busy, label = "Сохраняю...") {
+  if (!button) return;
+  if (button.tagName !== "BUTTON") {
+    button.disabled = busy;
+    button.classList.toggle("is-busy", busy);
+    return;
+  }
+  if (busy) {
+    button.dataset.label = button.textContent;
+    button.disabled = true;
+    button.classList.add("is-busy");
+    button.innerHTML = `<span class="spinner"></span><span>${t(label)}</span>`;
+  } else {
+    button.disabled = false;
+    button.classList.remove("is-busy");
+    button.textContent = button.dataset.label || button.textContent;
+    delete button.dataset.label;
+  }
+}
+
+async function runAction(button, statusMessage, callback) {
+  haptic();
+  setStatus(statusMessage);
+  setButtonBusy(button, true, statusMessage);
+  try {
+    const result = await callback();
+    setStatus("Готов к работе");
+    return result;
+  } catch (error) {
+    console.error(error);
+    setStatus("Ошибка");
+    toast(error.message || "Ошибка", "error");
+    haptic("error");
+    throw error;
+  } finally {
+    setButtonBusy(button, false);
+  }
+}
+
 async function ensureUser() {
   const tgUser = tg?.initDataUnsafe?.user || fallbackUser;
   state.user = await api("/users", {
@@ -491,6 +576,11 @@ function updateHero(stats) {
     : "-";
 }
 
+function formatFuelPrice(value) {
+  if (!value) return "-";
+  return money(value).replace(/\s?₽|RUB/i, "").trim();
+}
+
 function renderCars() {
   const root = document.querySelector("#cars");
   if (!state.cars.length) {
@@ -660,6 +750,8 @@ function openReport(type = "summary") {
         ${reportMetric(t("Пробег"), `${stats.distance_km} км`)}
         ${reportMetric(t("Прогноз сегодня"), analytics?.predicted_today ? `${analytics.predicted_today} км` : "-")}
         ${reportMetric(t("+30 дней"), analytics?.predicted_30_days ? `${analytics.predicted_30_days} км` : "-")}
+        ${reportMetric(t("Текущая цена"), analytics?.current_price_per_liter ? `${formatFuelPrice(analytics.current_price_per_liter)} / л` : "-")}
+        ${reportMetric(t("Прогноз цены"), analytics?.predicted_price_per_liter_30_days ? `${formatFuelPrice(analytics.predicted_price_per_liter_30_days)} / л` : "-")}
       </div>
       <div class="tip-card">${analytics?.insight || t("Лучший рост точности даст привычка заносить одометр при каждой заправке и сервисе.")}</div>
     `,
@@ -829,6 +921,8 @@ function roundRect(ctx, x, y, width, height, radius) {
 
 async function loadCars() {
   document.body.classList.add("loading");
+  setStatus("Обновляю данные...");
+  try {
     state.cars = await api(`/cars?owner_id=${state.user.id}`);
     if (!state.selectedCarId && state.cars.length) state.selectedCarId = state.cars[0].id;
     if (state.selectedCarId && !state.cars.some((car) => car.id === state.selectedCarId)) {
@@ -836,7 +930,10 @@ async function loadCars() {
     }
     renderCars();
     await loadSelectedCar();
+  } finally {
     document.body.classList.remove("loading");
+    setStatus("Готов к работе");
+  }
 }
 
 async function selectCar(carId) {
@@ -877,24 +974,34 @@ document.querySelectorAll('input[type="date"]').forEach((input) => {
 
 applyPeriodPreset("month");
 
-document.querySelector("#refreshBtn").addEventListener("click", loadCars);
+document.querySelector("#refreshBtn").addEventListener("click", (event) => {
+  runAction(event.currentTarget, "Обновляю данные...", loadCars).then(() => {
+    toast("Готов к работе");
+  });
+});
 
 document.querySelector("#periodPreset").addEventListener("change", async (event) => {
+  await runAction(event.currentTarget, "Обновляю данные...", async () => {
     applyPeriodPreset(event.currentTarget.value);
     await loadSelectedCar();
   });
+});
 
 document.querySelectorAll("#periodFrom, #periodTo").forEach((input) => {
   input.addEventListener("change", async () => {
+    await runAction(input, "Обновляю данные...", async () => {
       document.querySelector("#periodPreset").value = "custom";
       applyPeriodPreset("custom");
       await loadSelectedCar();
     });
   });
+});
 
 document.querySelector("#carForm").addEventListener("submit", async (event) => {
   event.preventDefault();
-  const data = formData(event.currentTarget);
+  const form = event.currentTarget;
+  await runAction(form.querySelector('button[type="submit"]'), "Сохраняю...", async () => {
+    const data = formData(form);
     await api("/cars", {
       method: "POST",
       body: JSON.stringify({
@@ -905,15 +1012,20 @@ document.querySelector("#carForm").addEventListener("submit", async (event) => {
         year: data.year ? Number(data.year) : null,
       }),
     });
-  event.currentTarget.reset();
+    form.reset();
     resetCarCatalog();
     document.querySelector("#userDrawer").classList.add("hidden");
     await loadCars();
+    toast("Сохранено");
+    haptic("success");
+  });
 });
 
 document.querySelector("#settingsForm").addEventListener("submit", async (event) => {
   event.preventDefault();
-  const data = formData(event.currentTarget);
+  const form = event.currentTarget;
+  await runAction(form.querySelector('button[type="submit"]'), "Сохраняю...", async () => {
+    const data = formData(form);
     state.user = await api(`/users/${state.user.id}/preferences`, {
       method: "PATCH",
       body: JSON.stringify({ locale: data.locale, currency: data.currency }),
@@ -922,12 +1034,17 @@ document.querySelector("#settingsForm").addEventListener("submit", async (event)
     initCarCatalog();
     await loadSelectedCar();
     document.querySelector("#userDrawer").classList.add("hidden");
+    toast("Сохранено");
+    haptic("success");
+  });
 });
 
 document.querySelector("#fuelForm").addEventListener("submit", async (event) => {
   event.preventDefault();
   if (!state.selectedCarId) return;
-  const data = formData(event.currentTarget);
+  const form = event.currentTarget;
+  await runAction(form.querySelector('button[type="submit"]'), "Сохраняю...", async () => {
+    const data = formData(form);
     await api("/fuel", {
       method: "POST",
       body: JSON.stringify({
@@ -940,15 +1057,20 @@ document.querySelector("#fuelForm").addEventListener("submit", async (event) =>
         is_full_tank: Boolean(data.is_full_tank),
       }),
     });
-  event.currentTarget.reset();
+    form.reset();
-  event.currentTarget.entry_date.value = today();
+    form.entry_date.value = today();
     await loadSelectedCar();
+    toast("Сохранено");
+    haptic("success");
+  });
 });
 
 document.querySelector("#serviceForm").addEventListener("submit", async (event) => {
   event.preventDefault();
   if (!state.selectedCarId) return;
-  const data = formData(event.currentTarget);
+  const form = event.currentTarget;
+  await runAction(form.querySelector('button[type="submit"]'), "Сохраняю...", async () => {
+    const data = formData(form);
     await api("/service", {
       method: "POST",
       body: JSON.stringify({
@@ -961,9 +1083,12 @@ document.querySelector("#serviceForm").addEventListener("submit", async (event)
         vendor: data.vendor || null,
       }),
     });
-  event.currentTarget.reset();
+    form.reset();
-  event.currentTarget.entry_date.value = today();
+    form.entry_date.value = today();
     await loadSelectedCar();
+    toast("Сохранено");
+    haptic("success");
+  });
 });
 
 function setAction(action) {
@@ -976,6 +1101,7 @@ function setAction(action) {
 
 document.querySelectorAll("[data-action]").forEach((button) => {
   button.addEventListener("click", () => {
+    haptic();
     if (button.dataset.action === "scan") {
       document.querySelector("#userDrawer").classList.remove("hidden");
       document.querySelector("#scanSection").classList.remove("hidden");
@@ -995,6 +1121,7 @@ document.querySelectorAll("[data-report]").forEach((button) => {
 
 document.querySelectorAll("[data-service-title]").forEach((button) => {
   button.addEventListener("click", () => {
+    haptic();
     const form = document.querySelector("#serviceForm");
     form.title.value = button.dataset.serviceTitle;
     form.service_type.value = button.dataset.serviceType;
@@ -1063,16 +1190,28 @@ document.querySelector("#receiptFileInput").addEventListener("change", (event) =
 document.querySelector("#ocrForm").addEventListener("submit", async (event) => {
   event.preventDefault();
   const file = state.receiptFile;
-  if (!file) return;
+  if (!file) {
+    toast("Выбери файл чека", "error");
+    haptic("error");
+    return;
+  }
+  const formButton = event.currentTarget.querySelector('button[type="submit"]');
+  await runAction(formButton, "Распознаю чек...", async () => {
     const payload = new FormData();
     payload.append("file", file);
     const response = await fetch("/api/ocr/fuel-receipt", { method: "POST", body: payload });
+    if (!response.ok) throw new Error(await response.text());
     const result = await response.json();
-  document.querySelector("#ocrResult").textContent = result.message;
+    document.querySelector("#ocrResult").textContent = `${result.message} ${Math.round((result.confidence || 0) * 100)}%`;
-  const form = document.querySelector("#fuelForm");
+    const fuelForm = document.querySelector("#fuelForm");
-  if (result.liters) form.liters.value = result.liters;
+    if (result.liters) fuelForm.liters.value = result.liters;
-  if (result.price_per_liter) form.price_per_liter.value = result.price_per_liter;
+    if (result.price_per_liter) fuelForm.price_per_liter.value = result.price_per_liter;
+    if (result.station) fuelForm.station.value = result.station;
     setAction("fuel");
+    document.querySelector("#userDrawer").classList.add("hidden");
+    toast("Проверь распознанные значения");
+    haptic("success");
+  });
 });
 
 document.querySelector("#closeMenuBtn").addEventListener("click", () => {

web/static/styles.css

@@ -876,3 +876,352 @@ select:disabled {
     grid-template-columns: 1fr;
   }
 }
+
+/* Modern app pass */
+:root {
+  --bg: #f4f7f5;
+  --text: #121815;
+  --muted: #6f7a75;
+  --line: #dfe7e3;
+  --surface: #ffffff;
+  --soft: #f8fbf9;
+  --accent: #12735f;
+  --accent-2: #2f6f9f;
+  --fuel: #1f987d;
+  --service: #2f6f9f;
+  --warning: #c26b33;
+  --danger: #b8423a;
+  --shadow: 0 16px 42px rgba(27, 38, 34, 0.09);
+  --press-shadow: 0 8px 18px rgba(18, 115, 95, 0.18);
+}
+
+body {
+  background:
+    linear-gradient(180deg, #ffffff 0, #f4f7f5 250px),
+    var(--bg);
+  -webkit-font-smoothing: antialiased;
+}
+
+button,
+.car-item,
+.stat,
+.action-card,
+.menu-row {
+  position: relative;
+  -webkit-tap-highlight-color: transparent;
+}
+
+button {
+  font-weight: 750;
+  border-radius: 8px;
+  box-shadow: 0 10px 24px rgba(18, 115, 95, 0.18);
+}
+
+button:hover {
+  box-shadow: var(--press-shadow);
+}
+
+button:active,
+.car-item:active,
+.stat:active,
+.action-card:active,
+.menu-row:active {
+  transform: translateY(1px) scale(0.99);
+}
+
+button:disabled,
+input:disabled,
+select:disabled {
+  cursor: progress;
+  opacity: 0.68;
+}
+
+.is-busy {
+  pointer-events: none;
+}
+
+.spinner {
+  width: 16px;
+  height: 16px;
+  border: 2px solid rgba(255, 255, 255, 0.45);
+  border-top-color: #fff;
+  border-radius: 50%;
+  animation: spin 720ms linear infinite;
+}
+
+button.is-busy {
+  display: inline-flex;
+  align-items: center;
+  justify-content: center;
+  gap: 8px;
+}
+
+.shell {
+  padding-top: 16px;
+}
+
+.topbar {
+  position: sticky;
+  top: 0;
+  z-index: 12;
+  margin: 0 -18px 14px;
+  padding: 12px 18px;
+  background: rgba(244, 247, 245, 0.88);
+  backdrop-filter: blur(14px);
+  border-bottom: 1px solid rgba(223, 231, 227, 0.78);
+}
+
+.topbar h1 {
+  font-size: clamp(28px, 6vw, 42px);
+}
+
+.icon-btn,
+.ghost-btn,
+.preset-row button,
+.menu-row {
+  background: #fff;
+  color: var(--text);
+  border: 1px solid var(--line);
+  box-shadow: 0 6px 18px rgba(27, 38, 34, 0.06);
+}
+
+.icon-btn {
+  display: grid;
+  place-items: center;
+}
+
+.hero-grid {
+  gap: 14px;
+}
+
+.summary-card,
+.panel,
+.workspace,
+.chart-card,
+.report-metric,
+.tip-card {
+  border-color: rgba(208, 220, 214, 0.9);
+}
+
+.summary-card {
+  min-height: 118px;
+  background:
+    linear-gradient(135deg, rgba(18, 115, 95, 0.1), rgba(255, 255, 255, 0) 54%),
+    var(--surface);
+}
+
+.summary-card.accent {
+  background:
+    linear-gradient(135deg, rgba(31, 152, 125, 0.14), rgba(255, 255, 255, 0) 58%),
+    var(--surface);
+}
+
+.summary-card.blue {
+  background:
+    linear-gradient(135deg, rgba(47, 111, 159, 0.14), rgba(255, 255, 255, 0) 58%),
+    var(--surface);
+}
+
+.summary-card::after {
+  display: none;
+}
+
+.progress-strip {
+  border-radius: 8px;
+  background:
+    linear-gradient(90deg, rgba(18, 115, 95, 0.08), rgba(47, 111, 159, 0.08)),
+    #fff;
+}
+
+.status-bar {
+  min-height: 36px;
+  display: flex;
+  align-items: center;
+  margin: -4px 0 14px;
+  padding: 8px 12px;
+  border: 1px solid var(--line);
+  border-radius: 8px;
+  background: #fff;
+  color: var(--muted);
+  font-size: 13px;
+}
+
+.report-bar,
+.entry-form {
+  border-color: rgba(223, 231, 227, 0.86);
+}
+
+.period-controls select,
+.period-controls input,
+input,
+select {
+  background: #fbfdfc;
+}
+
+.car-item,
+.action-card,
+.stat {
+  border-radius: 8px;
+  background: #fff;
+  border-color: var(--line);
+  transition:
+    transform 160ms ease,
+    border-color 160ms ease,
+    box-shadow 160ms ease,
+    background 160ms ease;
+}
+
+.car-item:hover,
+.action-card:hover,
+.stat:hover {
+  box-shadow: 0 12px 28px rgba(27, 38, 34, 0.08);
+}
+
+.car-item.active {
+  border-color: rgba(18, 115, 95, 0.55);
+  background: #eef8f4;
+  box-shadow: 0 12px 26px rgba(18, 115, 95, 0.12);
+}
+
+.car-badge {
+  background: linear-gradient(135deg, #d9f0e9, #dceaf5);
+}
+
+.action-card.active {
+  background:
+    linear-gradient(135deg, #12735f, #2f6f9f);
+  border-color: transparent;
+  box-shadow: 0 14px 30px rgba(18, 115, 95, 0.22);
+}
+
+.stats {
+  grid-template-columns: repeat(5, minmax(120px, 1fr));
+}
+
+.stat strong {
+  font-size: clamp(18px, 2.4vw, 24px);
+}
+
+.chart-card {
+  background: #fff;
+}
+
+.entry-form {
+  margin-top: 4px;
+  padding: 16px;
+  border: 1px solid var(--line);
+  border-radius: 8px;
+  background: #fff;
+}
+
+.drawer,
+.report-sheet {
+  background: rgba(18, 24, 21, 0.42);
+}
+
+.drawer-panel,
+.sheet-panel {
+  border-radius: 18px 18px 0 0;
+}
+
+.menu-row {
+  min-height: 48px;
+}
+
+.file-hint {
+  padding: 8px 10px;
+  border: 1px dashed var(--line);
+  border-radius: 8px;
+  background: #fbfdfc;
+}
+
+.toast {
+  position: fixed;
+  left: 50%;
+  bottom: 18px;
+  z-index: 40;
+  width: min(420px, calc(100% - 28px));
+  transform: translateX(-50%);
+  padding: 12px 14px;
+  border-radius: 8px;
+  background: #12211c;
+  color: #fff;
+  box-shadow: 0 18px 42px rgba(18, 24, 21, 0.22);
+  animation: toastIn 180ms ease both;
+}
+
+.toast.error {
+  background: #8f2f29;
+}
+
+.toast.hidden {
+  display: none;
+}
+
+@keyframes toastIn {
+  from {
+    opacity: 0;
+    transform: translate(-50%, 10px);
+  }
+  to {
+    opacity: 1;
+    transform: translate(-50%, 0);
+  }
+}
+
+@media (max-width: 980px) {
+  .topbar {
+    margin: 0 -12px 12px;
+    padding: 10px 12px;
+  }
+
+  .hero-grid {
+    gap: 10px;
+  }
+
+  .summary-card {
+    min-width: 82vw;
+  }
+
+  .panel,
+  .workspace,
+  .chart-card {
+    padding: 14px;
+  }
+
+  .status-bar {
+    margin-top: 0;
+  }
+
+  .quick-actions {
+    top: 61px;
+    margin-inline: -2px;
+    padding: 8px 0;
+    background: rgba(244, 247, 245, 0.92);
+  }
+
+  .action-card {
+    min-height: 64px;
+  }
+
+  .stats {
+    display: flex;
+    overflow-x: auto;
+    scroll-snap-type: x mandatory;
+    padding-bottom: 4px;
+  }
+
+  .stat {
+    min-width: 68vw;
+    scroll-snap-align: start;
+  }
+
+  .entry-form {
+    padding: 14px;
+  }
+
+  .drawer-panel,
+  .sheet-panel {
+    max-height: 92vh;
+  }
+}