import os
import json
import datetime
from typing import Optional
from huggingface_hub import HfApi, hf_hub_download
from huggingface_hub.utils import HfFolder, RepositoryNotFoundError

HF_TOKEN = os.environ.get("HF_TOKEN")
HF_REPO_ID = os.environ.get("HF_REPO_ID","broadfield-dev/chat-ai-db")
DB_FILENAME = "social_media_platform.db"
DATASET_FILENAME = "interactions.jsonl"

def _ensure_repo_exists():
    """Creates the Hugging Face repository if it does not already exist."""
    if not HF_TOKEN or not HF_REPO_ID:
        return
    try:
        api = HfApi()
        # This will create the repo if it doesn't exist and do nothing if it does.
        api.create_repo(
            repo_id=HF_REPO_ID,
            repo_type="dataset",
            token=HF_TOKEN,
            exist_ok=True,
        )
    except Exception as e:
        print(f"SYNC ERROR: Could not create or verify repository '{HF_REPO_ID}'. Please check your token and repo ID. Error: {e}")

def log_interaction_to_dataset(event_data: dict):
    if not HF_TOKEN or not HF_REPO_ID:
        return
    try:
        with open(DATASET_FILENAME, "a") as f:
            f.write(json.dumps(event_data) + "\n")
    except Exception as e:
        print(f"DATASET LOG ERROR: {e}")

def sync_files_to_hub():
    if not HF_TOKEN or not HF_REPO_ID:
        return
    
    _ensure_repo_exists() # Make sure the repo exists before uploading
    
    print("SYNC: Uploading database and dataset to Hugging Face Hub...")
    try:
        api = HfApi()
        api.upload_file(
            path_or_fileobj=DB_FILENAME, path_in_repo=DB_FILENAME,
            repo_id=HF_REPO_ID, repo_type="dataset", token=HF_TOKEN,
            commit_message="Sync latest simulation state"
        )
        if os.path.exists(DATASET_FILENAME):
            api.upload_file(
                path_or_fileobj=DATASET_FILENAME, path_in_repo=DATASET_FILENAME,
                repo_id=HF_REPO_ID, repo_type="dataset", token=HF_TOKEN,
                commit_message="Sync latest interactions"
            )
        print("SYNC: Upload successful.")
    except Exception as e:
        print(f"SYNC ERROR: Failed to upload files: {e}")

def download_files_from_hub():
    if not HF_TOKEN or not HF_REPO_ID:
        print("SYNC: Hub environment variables not set. Skipping download.")
        return
    print(f"SYNC: Attempting to download latest state from '{HF_REPO_ID}'...")
    try:
        hf_hub_download(
            repo_id=HF_REPO_ID, filename=DB_FILENAME,
            repo_type="dataset", token=HF_TOKEN, local_dir="."
        )
        print("SYNC: Database download successful.")
        hf_hub_download(
            repo_id=HF_REPO_ID, filename=DATASET_FILENAME,
            repo_type="dataset", token=HF_TOKEN, local_dir="."
        )
        print("SYNC: Dataset log download successful.")
    except RepositoryNotFoundError:
         print(f"SYNC INFO: Repository '{HF_REPO_ID}' not found on the Hub. A new one will be created on the first action.")
    except Exception as e:
        print(f"SYNC INFO: Could not download files (may not exist yet): {e}")

def upload_image_to_hub(image_file, agent_id: int) -> Optional[str]:
    if not HF_TOKEN or not HF_REPO_ID:
        return None
        
    _ensure_repo_exists() # Make sure the repo exists before uploading

    try:
        api = HfApi()
        timestamp = datetime.datetime.utcnow().strftime("%Y%m%d_%H%M%S")
        filename_ext = image_file.filename.split('.')[-1] if '.' in image_file.filename else 'jpg'
        filename = f"images/{agent_id}_{timestamp}.{filename_ext}"
        
        base_url = f"https://huggingface.co/datasets/{HF_REPO_ID}/resolve/main/{filename}"

        api.upload_file(
            path_or_fileobj=image_file.stream.read(),
            path_in_repo=filename,
            repo_id=HF_REPO_ID,
            repo_type="dataset",
            token=HF_TOKEN,
        )
        return base_url
    except Exception as e:
        print(f"IMAGE UPLOAD ERROR: {e}")
        return None