import os, json, time, schedule, threading
from pathlib import Path
from datetime import datetime
# FIX #13: Added filelock to prevent race conditions when Node.js and this
#           script both try to read/write conversations.json simultaneously
from filelock import FileLock

HF_TOKEN    = os.environ.get("HF_TOKEN")
HF_DATASET  = os.environ.get("HF_BACKUP_DATASET", "your-username/llm-space-backup")
DATA_DIR    = Path("/app/data")
SYNC_EVERY  = int(os.environ.get("SYNC_INTERVAL_MINUTES", "3"))
LOCK_PATH   = str(DATA_DIR / "conversations.lock")

DATA_DIR.mkdir(parents=True, exist_ok=True)


def save_conversations(conversations: dict):
    """Save in-memory conversations to disk (with file lock)."""
    path = DATA_DIR / "conversations.json"
    # FIX #13: File lock prevents torn writes when Node.js is also writing
    with FileLock(LOCK_PATH, timeout=10):
        with open(path, "w") as f:
            json.dump(conversations, f, indent=2, default=str)


def load_conversations() -> dict:
    """Load conversations from disk on boot (with file lock)."""
    path = DATA_DIR / "conversations.json"
    if path.exists():
        with FileLock(LOCK_PATH, timeout=10):
            with open(path) as f:
                return json.load(f)
    return {}


def sync_to_hf_dataset():
    """Push backup data to HuggingFace private Dataset."""
    if not HF_TOKEN:
        print("⚠️  HF_TOKEN not set, skipping HF sync")
        return
    try:
        from huggingface_hub import HfApi
        api = HfApi(token=HF_TOKEN)

        # Ensure dataset exists
        try:
            api.create_repo(
                repo_id=HF_DATASET,
                repo_type="dataset",
                private=True,
                exist_ok=True
            )
        except Exception:
            pass

        # Upload all data files (skip lock file)
        for file in DATA_DIR.glob("*"):
            if file.suffix == ".lock":
                continue
            api.upload_file(
                path_or_fileobj=str(file),
                path_in_repo=file.name,
                repo_id=HF_DATASET,
                repo_type="dataset"
            )

        print(f"✅ [{datetime.now().isoformat()}] Synced to HF Dataset: {HF_DATASET}")

    except Exception as e:
        print(f"❌ Sync failed: {e}")


def restore_from_hf_dataset():
    """Restore backup from HF Dataset on boot."""
    if not HF_TOKEN:
        return
    try:
        # FIX #1 (CRITICAL): The original code called `api.hf_hub_download()`
        # which does NOT exist on the HfApi class. This caused a silent
        # AttributeError meaning conversations were NEVER restored on restart.
        # Correct approach: use the module-level `hf_hub_download` function.
        from huggingface_hub import HfApi, hf_hub_download, list_repo_files

        files = list_repo_files(repo_id=HF_DATASET, repo_type="dataset", token=HF_TOKEN)

        for fname in files:
            if fname.endswith(".lock"):
                continue
            hf_hub_download(           # ← was `api.hf_hub_download` (bug)
                repo_id=HF_DATASET,
                filename=fname,
                repo_type="dataset",
                local_dir=str(DATA_DIR),
                token=HF_TOKEN
            )
        print(f"✅ Restored backup from {HF_DATASET}")
    except Exception as e:
        print(f"⚠️  Could not restore backup (first run?): {e}")


if __name__ == "__main__":
    print("💾 Hermes Sync starting...")
    restore_from_hf_dataset()

    schedule.every(SYNC_EVERY).minutes.do(sync_to_hf_dataset)

    print(f"🔄 Syncing every {SYNC_EVERY} minutes to {HF_DATASET}")
    while True:
        schedule.run_pending()
        time.sleep(30)