"""
Configuration and Constants Module

This module centralizes all configuration settings and constants used throughout
the application. Think of this as a "settings file" where you can adjust behavior
without touching the main code.

For Non-Technical Developers:
- DEVICE: Where the AI runs (GPU if available, CPU otherwise)
- TIMEOUTS: How long to wait before giving up on internet requests
- MODEL_CACHE_SIZE: How many things to remember to avoid re-downloading
- THREAD_WORKERS: How many tasks can run at the same time
"""

import os
import torch

# ==================== DEVICE CONFIGURATION ====================
# Determines where the AI models run:
# - 'cuda': Graphics card (NVIDIA GPU) - MUCH faster but requires NVIDIA GPU
# - 'cpu': Regular computer processor - slower but works everywhere
DEVICE = 'cuda' if torch.cuda.is_available() else 'cpu'

# ==================== FILE PATHS ====================
# Paths to downloaded AI models that we use for face swapping
INSWAPPER_MODEL_PATH = 'inswapper_128.onnx'  # The main face-swapping model
GFPGAN_MODEL_URL = 'https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/GFPGANv1.4.pth'  # Updated to v1.4

# ==================== HUGGING FACE API ====================
# Hugging Face is a platform where AI models are stored
# We need a token to download larger models
HF_TOKEN = os.getenv('HF_TOKEN')
INSWAPPER_HF_URL = 'https://huggingface.co/netrunner-exe/Insight-Swap-models-onnx/resolve/main/inswapper_128.onnx'

# ==================== MODEL PATHS ====================
# Where downloaded models are stored
# These can be customized via environment variables
MODELS_DIR = os.getenv('MODELS_DIR', os.path.join(os.path.dirname(__file__), '..', 'models'))
INSIGHTFACE_MODELS_DIR = os.getenv('INSIGHTFACE_MODELS_DIR', os.path.expanduser('~/.insightface/models'))
GFPGAN_MODELS_DIR = os.getenv('GFPGAN_MODELS_DIR', os.path.expanduser('~/.cache/gfpgan'))

# Create model directories if they don't exist
os.makedirs(MODELS_DIR, exist_ok=True)
os.makedirs(INSIGHTFACE_MODELS_DIR, exist_ok=True)
os.makedirs(GFPGAN_MODELS_DIR, exist_ok=True)

# ==================== HTTP/WEB SETTINGS ====================
# Standard browser headers - tells websites we're a normal browser, not a bot
DEFAULT_HEADERS = {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36',
    'Accept': 'image/avif,image/webp,image/apng,image/*,*/*;q=0.8',
}

# Optional Instagram session cookie to improve media extraction reliability
INSTAGRAM_SESSION_COOKIE = os.getenv('INSTAGRAM_SESSION_COOKIE') or os.getenv('INSTAGRAM_COOKIE')
INSTAGRAM_ACCEPT_LANGUAGE = os.getenv('INSTAGRAM_ACCEPT_LANGUAGE', 'en-US,en;q=0.9')
INSTAGRAM_APP_ID = os.getenv('INSTAGRAM_APP_ID', '936619743392459')

INSTAGRAM_HEADERS = dict(DEFAULT_HEADERS)
INSTAGRAM_HEADERS['Accept-Language'] = INSTAGRAM_ACCEPT_LANGUAGE
INSTAGRAM_HEADERS['X-IG-App-ID'] = INSTAGRAM_APP_ID
INSTAGRAM_HEADERS['X-Requested-With'] = 'XMLHttpRequest'
INSTAGRAM_HEADERS['Referer'] = 'https://www.instagram.com/'
if INSTAGRAM_SESSION_COOKIE:
    INSTAGRAM_HEADERS['Cookie'] = INSTAGRAM_SESSION_COOKIE

# How long to wait (in seconds) before timing out when downloading files from the internet
DOWNLOAD_TIMEOUT = 30

# ==================== SUPPORTED MEDIA FORMATS ====================
# File extensions we can process
SUPPORTED_IMAGE_FORMATS = {'.jpg', '.jpeg', '.png', '.webp', '.bmp', '.tiff'}
SUPPORTED_VIDEO_FORMATS = {'.mp4', '.mov', '.avi', '.mkv', '.flv', '.wmv'}
SUPPORTED_GIF_FORMATS = {'.gif'}
SUPPORTED_FORMATS = SUPPORTED_IMAGE_FORMATS | SUPPORTED_VIDEO_FORMATS | SUPPORTED_GIF_FORMATS

# Default processing limits to avoid deployment timeouts on long videos
DEFAULT_MAX_FRAMES = 60
MAX_ALLOWED_FRAMES = 120
PROCESSING_TIMEOUT_SECONDS = 240

# ==================== CACHING SETTINGS ====================
# Cache: A way to remember things we've already downloaded/processed
# This saves time and internet bandwidth
EMBEDDING_CACHE_SIZE = 10  # How many face embeddings to remember
FRAME_CACHE_SIZE = 5        # How many video/GIF frame sequences to remember

# ==================== FACE DETECTION SETTINGS ====================
# Constants for face detection thresholds
FACE_DETECTION_THRESHOLDS = [0.15, 0.10, 0.05]  # Try these confidence levels, in order
MIN_FACE_CONFIDENCE = 0.15  # Don't process faces with confidence lower than this
MIN_LANDMARK_CONFIDENCE = 0.2  # Minimum confidence for face landmarks (features like eyes, nose)

# How many consecutive frames can have NO face before we give up and stop trying
NO_FACE_LIMIT = 10

# Face size thresholds (in pixels)
MIN_FACE_AREA_RATIO = 0.01  # Minimum face area as a percentage of frame size
FACE_POSE_THRESHOLD = 60  # Maximum head rotation angle (degrees) to accept

# ==================== PREPROCESSING SETTINGS ====================
# Preprocessing: Preparing frames to make them easier for AI to detect faces
# Different strengths for different use cases

PREPROCESS_STRENGTHS = {
    'light': {
        'clahe_limit': 1.5,
        'sharpen_strength': 0.3,
        'apply_gamma': False,
    },
    'medium': {
        'clahe_limit': 2.5,
        'sharpen_strength': 0.5,
        'apply_gamma': False,
    },
    'heavy': {
        'clahe_limit': 4.0,
        'sharpen_strength': 1.0,
        'apply_gamma': True,
    },
}

# ==================== THREADING/PARALLELIZATION ====================
# Threading: Running multiple tasks at the same time to speed things up
MAX_WORKERS = 4  # Maximum number of tasks that can run simultaneously

# Multi-threading options for PyTorch (AI library)
TORCH_NUM_THREADS = 2  # Keep low to avoid bottlenecks
ONNX_INTRA_OP_THREADS = 2  # Threads for running individual AI operations

# ==================== OUTPUT SETTINGS ====================
# Settings for generating output GIFs
GIF_QUALITY = 80  # Quality level (1-100, higher = better quality but bigger file)
DEFAULT_GIF_DURATION = 67  # milliseconds - how long to show each frame

# ==================== INSTAGRAM SETTINGS ====================
# Instagram connection settings for extracting photos/videos from posts/reels
INSTAGRAM_API_TIMEOUT = 30  # How long to wait for Instagram responses
INSTAGRAM_MAX_RETRIES = 3  # How many times to try if Instagram connection fails
INSTAGRAM_REQUEST_DELAY = 1  # Seconds to wait between Instagram API requests (to be polite)

# ==================== LOGGING/DEBUGGING ====================
# Whether to print detailed information while processing
DEBUG_MODE = os.getenv('DEBUG_MODE', 'False').lower() == 'true'

# ==================== VIDEO SETTINGS ====================
# Settings for converting videos to frames
VIDEO_FRAME_EXTRACTION_METHOD = 'cv2'  # How to extract frames from video files
VIDEO_CODEC = 'mp4v'  # Codec for video encoding

# Default frames per second when extracting from video
# If unknown, we use this to estimate duration
DEFAULT_VIDEO_FPS = 30

# ==================== ERROR MESSAGES ====================
# User-friendly error messages

ERROR_MESSAGES = {
    'no_face_source': 'Could not detect a face in the source image. Please provide a clear photo with a visible face.',
    'no_face_target': 'Could not detect a face in the target image/video. Please use a target with visible faces.',
    'invalid_media_url': 'The provided URL does not point to a valid image or video.',
    'unsupported_format': 'The media format is not supported. Please use: GIF, MP4, WebP, PNG, or JPG.',
    'download_failed': 'Failed to download the media. Please check the URL and try again.',
    'instagram_extraction_failed': 'Could not extract media from Instagram. Please check the link and try again.',
    'processing_error': 'An error occurred during face swapping. Please try again.',
    'swap_failed': 'Face swap failed. The source or target images may not be suitable.',
}