Refactor: Make model packages true leaf nodes - remove app-layer dependencies

Models in app/models/ are now pure data classes with no cross-layer dependencies.
This ensures the models layer remains a true leaf node in the dependency graph.

Changes:
- Create app/models/_common.py with shared types (TimeRange, bucket_count, constants)
- Move TimeRange and time-range constants from ban.py to _common.py
- Update history.py, routers, and services to import from _common.py
- Remove imports from app.config and app.utils from config.py models
- Move field validators from models to router layer:
  - Add log_target validation in config_misc router
  - Add log_path validation in jail_config router
- Update test_models.py to reflect validators moved to router layer
- Update documentation (Architekture.md, Backend-Development.md) with model layering rules
- Fix import ordering and type annotations in affected files

Model layering rule: Models may only import from:
✓ Standard library and third-party packages (Pydantic, typing)
✓ Other models in app/models/ (sibling models)
✓ app.models.response (response envelopes)
✗ app.services, app.config, app.utils, or any application layer

Validation requiring app-level state (settings, allowed directories) now happens
at the router or service layer, not in model validators.

Fixes: Models were not true leaf nodes due to circular imports and app-layer dependencies

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

backend/app/models/ban.py

@@ -3,7 +3,6 @@
 Request, response, and domain models used by the ban router and service.
 """
 
-import math
 from typing import Literal
 
 from pydantic import Field
@@ -11,21 +10,6 @@ from pydantic import Field
 from app.models.response import BanGuiBaseModel, CollectionResponse, PaginatedListResponse
 
 
-# ---------------------------------------------------------------------------
-# Time-range selector
-# ---------------------------------------------------------------------------
-
-#: The four supported time-range presets for the dashboard views.
-TimeRange = Literal["24h", "7d", "30d", "365d"]
-
-#: Number of seconds represented by each preset.
-TIME_RANGE_SECONDS: dict[str, int] = {
-    "24h": 24 * 3600,
-    "7d": 7 * 24 * 3600,
-    "30d": 30 * 24 * 3600,
-    "365d": 365 * 24 * 3600,
-}
-
 class BanRequest(BanGuiBaseModel):
     """Payload for ``POST /api/bans`` (ban an IP)."""
 
@@ -204,36 +188,7 @@ class BansByCountryResponse(BanGuiBaseModel):
 
 # ---------------------------------------------------------------------------
 # Trend endpoint models
-# ---------------------------------------------------------------------------
 
-#: Bucket size in seconds for each time-range preset.
-BUCKET_SECONDS: dict[str, int] = {
-    "24h": 3_600,          # 1 hour  → 24 buckets
-    "7d": 6 * 3_600,       # 6 hours → 28 buckets
-    "30d": 86_400,         # 1 day   → 30 buckets
-    "365d": 7 * 86_400,    # 7 days  → ~53 buckets
-}
-
-#: Human-readable bucket size label for each time-range preset.
-BUCKET_SIZE_LABEL: dict[str, str] = {
-    "24h": "1h",
-    "7d": "6h",
-    "30d": "1d",
-    "365d": "7d",
-}
-
-def bucket_count(range_: TimeRange) -> int:
-    """Return the number of buckets needed to cover *range_* completely.
-
-    Args:
-        range_: One of the supported time-range presets.
-
-    Returns:
-        Ceiling division of the range duration by the bucket size so that
-        the last bucket is included even when the window is not an exact
-        multiple of the bucket size.
-    """
-    return math.ceil(TIME_RANGE_SECONDS[range_] / BUCKET_SECONDS[range_])
 
 class BanTrendBucket(BanGuiBaseModel):
     """A single time bucket in the ban trend series."""