Setmaster
e9e3ade3f0
- Add model usage tracking via PromptExecutor hook - Support 12+ loader node types (checkpoints, LoRAs, VAEs, etc.) - Pattern matching for custom node loaders - Cross-platform file locking (Windows/Unix) - JSON storage with schema migrations - REST API endpoints for usage data - Sidebar panel with timeframe filtering and sorting - Stale model highlighting (>30 days unused)
259 lines
7.7 KiB
Python
259 lines
7.7 KiB
Python
"""
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ModelPulse - Storage Layer
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JSON-based persistence for model usage data with cross-platform file locking.
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"""
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import json
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import sys
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import time
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from datetime import datetime
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from pathlib import Path
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from typing import Any
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# Cross-platform file locking
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if sys.platform == "win32":
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import msvcrt
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def _lock_file(f, exclusive: bool = False) -> None:
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"""Lock file on Windows using msvcrt."""
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msvcrt.locking(f.fileno(), msvcrt.LK_NBLCK if exclusive else msvcrt.LK_LOCK, 1)
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def _unlock_file(f) -> None:
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"""Unlock file on Windows using msvcrt."""
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try:
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f.seek(0)
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msvcrt.locking(f.fileno(), msvcrt.LK_UNLCK, 1)
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except OSError:
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pass # Already unlocked or file closed
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else:
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import fcntl
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def _lock_file(f, exclusive: bool = False) -> None:
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"""Lock file on Unix using fcntl."""
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fcntl.flock(f.fileno(), fcntl.LOCK_EX if exclusive else fcntl.LOCK_SH)
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def _unlock_file(f) -> None:
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"""Unlock file on Unix using fcntl."""
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fcntl.flock(f.fileno(), fcntl.LOCK_UN)
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class FileLock:
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"""Cross-platform file lock context manager using a .lock file."""
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def __init__(self, path: Path, timeout: float = 10.0):
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self.lock_path = path.with_suffix(path.suffix + ".lock")
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self.timeout = timeout
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self._lock_file = None
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def __enter__(self):
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start = time.time()
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while True:
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try:
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# Create lock file exclusively
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self._lock_file = open(self.lock_path, "x")
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return self
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except FileExistsError:
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# Check if lock is stale (older than timeout)
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try:
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lock_age = time.time() - self.lock_path.stat().st_mtime
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if lock_age > self.timeout:
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# Stale lock, remove it
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self.lock_path.unlink()
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continue
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except FileNotFoundError:
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continue # Lock was released, retry
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if time.time() - start > self.timeout:
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raise TimeoutError(f"Could not acquire lock on {self.lock_path}")
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time.sleep(0.1)
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def __exit__(self, exc_type, exc_val, exc_tb):
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if self._lock_file:
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self._lock_file.close()
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try:
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self.lock_path.unlink()
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except FileNotFoundError:
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pass
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SCHEMA_VERSION = 1
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def get_storage_path() -> Path:
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"""Get the path to the usage data file."""
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# ComfyUI stores user data in user/default/
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# We need to find the ComfyUI root directory
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# This file is in custom_nodes/ComfyUI-ModelPulse/py/
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current_file = Path(__file__).resolve()
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custom_nodes_dir = current_file.parent.parent.parent # Go up to custom_nodes
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comfyui_root = custom_nodes_dir.parent # Go up to ComfyUI root
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storage_dir = comfyui_root / "user" / "default" / "modelpulse"
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storage_dir.mkdir(parents=True, exist_ok=True)
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return storage_dir / "usage_data.json"
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def get_backup_path() -> Path:
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"""Get the path for backup files."""
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storage_path = get_storage_path()
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return storage_path.with_suffix(".backup.json")
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def create_empty_data() -> dict[str, Any]:
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"""Create an empty data structure."""
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now = datetime.utcnow().isoformat() + "Z"
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return {
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"version": SCHEMA_VERSION,
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"models": {},
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"metadata": {
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"tracking_started": now,
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"last_updated": now,
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},
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}
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def load_data() -> dict[str, Any]:
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"""
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Load usage data from JSON file.
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Creates the file with empty data if it doesn't exist.
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Handles schema migrations if needed.
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"""
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storage_path = get_storage_path()
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if not storage_path.exists():
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data = create_empty_data()
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save_data(data)
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return data
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try:
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with FileLock(storage_path):
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with open(storage_path, "r", encoding="utf-8") as f:
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data = json.load(f)
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# Handle schema migrations
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data = migrate_schema(data)
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return data
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except (json.JSONDecodeError, KeyError) as e:
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# Corrupted file - backup and create fresh
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print(f"[ModelPulse] Warning: Corrupted data file, creating backup. Error: {e}")
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backup_corrupted_file(storage_path)
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data = create_empty_data()
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save_data(data)
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return data
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def save_data(data: dict[str, Any]) -> None:
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"""
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Save usage data to JSON file with file locking.
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Uses exclusive lock to prevent concurrent writes.
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"""
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storage_path = get_storage_path()
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# Update last_updated timestamp
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data["metadata"]["last_updated"] = datetime.utcnow().isoformat() + "Z"
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# Write to temp file first, then rename (atomic operation)
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temp_path = storage_path.with_suffix(".tmp")
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try:
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with FileLock(storage_path):
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with open(temp_path, "w", encoding="utf-8") as f:
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json.dump(data, f, indent=2, ensure_ascii=False)
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# Atomic rename
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temp_path.replace(storage_path)
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except Exception as e:
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# Clean up temp file if it exists
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if temp_path.exists():
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temp_path.unlink()
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raise e
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def migrate_schema(data: dict[str, Any]) -> dict[str, Any]:
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"""
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Migrate data to the current schema version.
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Creates a backup before migration.
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"""
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current_version = data.get("version", 0)
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if current_version == SCHEMA_VERSION:
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return data
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# Backup before migration
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backup_path = get_backup_path()
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with open(backup_path, "w", encoding="utf-8") as f:
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json.dump(data, f, indent=2)
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print(f"[ModelPulse] Created backup at {backup_path} before schema migration")
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# Apply migrations sequentially
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if current_version < 1:
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data = migrate_to_v1(data)
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# Future migrations would go here:
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# if current_version < 2:
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# data = migrate_to_v2(data)
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data["version"] = SCHEMA_VERSION
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return data
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def migrate_to_v1(data: dict[str, Any]) -> dict[str, Any]:
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"""Migrate from pre-v1 (or no version) to v1 schema."""
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# Ensure required structure exists
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if "models" not in data:
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data["models"] = {}
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if "metadata" not in data:
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now = datetime.utcnow().isoformat() + "Z"
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data["metadata"] = {
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"tracking_started": now,
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"last_updated": now,
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}
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# Ensure all models have required fields
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for model_id, model_data in data.get("models", {}).items():
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if "usage_log" not in model_data:
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model_data["usage_log"] = []
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if "first_used" not in model_data:
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model_data["first_used"] = model_data.get(
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"last_used", datetime.utcnow().isoformat() + "Z"
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)
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return data
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def backup_corrupted_file(storage_path: Path) -> None:
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"""Backup a corrupted file for manual recovery."""
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if storage_path.exists():
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timestamp = datetime.utcnow().strftime("%Y%m%d_%H%M%S")
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backup_path = storage_path.with_suffix(f".corrupted_{timestamp}.json")
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storage_path.rename(backup_path)
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print(f"[ModelPulse] Backed up corrupted file to {backup_path}")
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def cleanup_old_usage_logs(data: dict[str, Any], max_days: int = 365) -> dict[str, Any]:
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"""
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Clean up old daily usage logs to prevent unbounded growth.
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Keeps the last `max_days` days of daily data.
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"""
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cutoff_date = datetime.utcnow().date()
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from datetime import timedelta
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cutoff_str = (cutoff_date - timedelta(days=max_days)).isoformat()
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for model_data in data.get("models", {}).values():
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usage_log = model_data.get("usage_log", [])
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model_data["usage_log"] = [
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entry for entry in usage_log if entry.get("date", "") >= cutoff_str
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]
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return data
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