# logging.py

import os
import uuid
import time
from huggingface_hub import CommitScheduler, HfApi
from PIL import Image

APP_VERSION = "0_3"
HF_DATASET_REPO = "LPX55/upscaler_logs"  # Change to your dataset repo
HF_TOKEN = os.environ.get("HUGGINGFACE_TOKEN")   # Make sure this is set in your environment

LOG_DIR = "logs_" + APP_VERSION
IMAGE_DIR = os.path.join(LOG_DIR, "upscaler")

LOG_FILE = os.path.join(LOG_DIR, f"{int(time.time())}-logs.csv")
os.makedirs(IMAGE_DIR, exist_ok=True)


scheduler = CommitScheduler(
    repo_id=HF_DATASET_REPO,
    repo_type="dataset",
    folder_path=LOG_DIR,
    every=5,
    private=True,
    token=HF_TOKEN,
    allow_patterns=["*.csv", "images/*.png", "images/*.webp", "images/*.jpg", "images/*.jpeg"],
    path_in_repo="v" + APP_VERSION

)

def log_params(
    prompt, scale, steps, controlnet_conditioning_scale, guidance_scale, seed, guidance_end,
    before_image, after_image, user=None
):
    before_id = str(uuid.uuid4()) + "_before.png"
    after_id = str(uuid.uuid4()) + "_after.png"
    before_path = os.path.join(IMAGE_DIR, before_id)
    after_path = os.path.join(IMAGE_DIR, after_id)
    before_image.save(before_path)
    after_image.save(after_path)

    is_new = not os.path.exists(LOG_FILE)
    with open(LOG_FILE, "a", newline='') as f:
        import csv
        writer = csv.writer(f)
        if is_new:
            writer.writerow([
                "timestamp", "user", "prompt", "scale", "steps", "controlnet_conditioning_scale",
                "guidance_scale", "seed", "guidance_end", "before_image", "after_image"
            ])
        writer.writerow([
            time.strftime("%Y-%m-%dT%H:%M:%S"),
            user or "anonymous",
            prompt, scale, steps, controlnet_conditioning_scale,
            guidance_scale, seed, guidance_end, before_path, after_path
        ])