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| import aiosqlite | |
| import os | |
| import time | |
| import asyncio | |
| from datetime import datetime | |
| from typing import List, Dict, Any | |
| from huggingface_hub import HfApi, hf_hub_download | |
| from config import settings | |
| DB_PATH = os.path.join(os.path.dirname(os.path.abspath(__file__)), settings.db_name) | |
| api = HfApi() | |
| last_sync = 0 | |
| sync_lock = asyncio.Lock() | |
| async def sync_from_hub(): | |
| global last_sync | |
| if not settings.hf_token: | |
| print("No HF_TOKEN found. Skipping sync.") | |
| return | |
| async with sync_lock: | |
| if time.time() - last_sync < 60: | |
| return | |
| try: | |
| try: | |
| api.create_repo(repo_id=settings.repo_id, repo_type="dataset", exist_ok=True, token=settings.hf_token) | |
| except Exception as e: | |
| print(f"Failed to create repo: {e}") | |
| print(f"Downloading {settings.db_name} from Hub...") | |
| def _download(): | |
| path = hf_hub_download( | |
| repo_id=settings.repo_id, | |
| filename=settings.db_name, | |
| repo_type="dataset", | |
| token=settings.hf_token, | |
| force_download=True | |
| ) | |
| import shutil | |
| shutil.copy(path, DB_PATH) | |
| await asyncio.to_thread(_download) | |
| last_sync = time.time() | |
| print("Sync from Hub complete.") | |
| except Exception as e: | |
| print(f"Sync from Hub failed: {e}") | |
| async def sync_to_hub(): | |
| if not settings.hf_token: | |
| return | |
| try: | |
| def _upload(): | |
| api.upload_file( | |
| path_or_fileobj=DB_PATH, | |
| path_in_repo=settings.db_name, | |
| repo_id=settings.repo_id, | |
| repo_type="dataset", | |
| token=settings.hf_token | |
| ) | |
| await asyncio.to_thread(_upload) | |
| except Exception as e: | |
| print(f"Sync to Hub failed: {e}") | |
| async def init_db() -> None: | |
| await sync_from_hub() | |
| async with aiosqlite.connect(DB_PATH) as db: | |
| await db.execute(''' | |
| CREATE TABLE IF NOT EXISTS predictions ( | |
| id INTEGER PRIMARY KEY AUTOINCREMENT, | |
| timestamp DATETIME, | |
| heart_rate REAL, | |
| spo2 REAL, | |
| sys_bp REAL, | |
| dia_bp REAL, | |
| temp REAL, | |
| fall_detection TEXT, | |
| prediction_label TEXT, | |
| confidence REAL | |
| ) | |
| ''') | |
| await db.commit() | |
| async def log_prediction(data: Any, prediction_label: str, confidence: float) -> None: | |
| async with aiosqlite.connect(DB_PATH) as db: | |
| from datetime import timezone, timedelta | |
| ist = timezone(timedelta(hours=5, minutes=30)) | |
| await db.execute(''' | |
| INSERT INTO predictions (timestamp, heart_rate, spo2, sys_bp, dia_bp, temp, fall_detection, prediction_label, confidence) | |
| VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?) | |
| ''', ( | |
| datetime.now(ist).strftime("%Y-%m-%d %H:%M:%S"), | |
| data.Heart_Rate, | |
| data.SpO2_Level, | |
| data.Systolic_BP, | |
| data.Diastolic_BP, | |
| data.Body_Temp, | |
| "N/A", | |
| prediction_label, | |
| confidence | |
| )) | |
| await db.commit() | |
| async def get_history() -> List[Dict[str, Any]]: | |
| if not os.path.exists(DB_PATH): | |
| return [] | |
| async with aiosqlite.connect(DB_PATH) as db: | |
| db.row_factory = aiosqlite.Row | |
| async with db.execute('SELECT * FROM predictions ORDER BY timestamp DESC LIMIT 100') as cursor: | |
| rows = await cursor.fetchall() | |
| return [dict(row) for row in rows] | |