config.py

"""
Configuration management for EceMotion Pictures.
Centralized settings for models, parameters, and deployment.
"""

import os
from typing import Dict, Any, Optional

# Model Configuration - with fallbacks for HuggingFace Spaces
MODEL_VIDEO = os.getenv("MODEL_VIDEO", "damo-vilab/text-to-video-ms-1.7b")  # Start with lighter model
MODEL_AUDIO = os.getenv("MODEL_AUDIO", "parler-tts/parler-tts-mini-v1")  # Start with working model
MODEL_LLM = os.getenv("MODEL_LLM", "microsoft/DialoGPT-medium")  # Start with lighter LLM

# Video Configuration
MAX_DURATION = int(os.getenv("MAX_DURATION", "15"))
MIN_DURATION = int(os.getenv("MIN_DURATION", "5"))
DEFAULT_FPS = int(os.getenv("DEFAULT_FPS", "8"))
DEFAULT_FRAMES = int(os.getenv("DEFAULT_FRAMES", "64"))  # 8 seconds at 8fps

# Audio Configuration
AUDIO_SAMPLE_RATE = int(os.getenv("AUDIO_SAMPLE_RATE", "22050"))  # Standard rate
AUDIO_BITRATE = os.getenv("AUDIO_BITRATE", "128k")  # Lower bitrate for stability
MUSIC_GAIN = float(os.getenv("MUSIC_GAIN", "0.3"))

# GPU Configuration
GPU_MEMORY_THRESHOLD = float(os.getenv("GPU_MEMORY_THRESHOLD", "0.8"))
USE_QUANTIZATION = os.getenv("USE_QUANTIZATION", "true").lower() == "true"
QUANTIZATION_BITS = int(os.getenv("QUANTIZATION_BITS", "8"))

# Sync Configuration
SYNC_TOLERANCE_MS = int(os.getenv("SYNC_TOLERANCE_MS", "200"))  # More lenient for stability
FORCE_SYNC = os.getenv("FORCE_SYNC", "false").lower() == "true"  # Disabled by default

# Retro Filter Configuration
VHS_INTENSITY = float(os.getenv("VHS_INTENSITY", "0.5"))
SCANLINE_OPACITY = float(os.getenv("SCANLINE_OPACITY", "0.2"))
CHROMATIC_ABERRATION = float(os.getenv("CHROMATIC_ABERRATION", "0.05"))
FILM_GRAIN = float(os.getenv("FILM_GRAIN", "0.1"))

# UI Configuration
UI_THEME = os.getenv("UI_THEME", "default")
SHOW_PROGRESS = os.getenv("SHOW_PROGRESS", "true").lower() == "true"
ENABLE_EXAMPLES = os.getenv("ENABLE_EXAMPLES", "true").lower() == "true"

# Logging Configuration
LOG_LEVEL = os.getenv("LOG_LEVEL", "INFO")
LOG_FORMAT = os.getenv("LOG_FORMAT", "text")  # text format for HuggingFace Spaces

# Model-specific configurations with conservative settings
MODEL_CONFIGS: Dict[str, Dict[str, Any]] = {
    "damo-vilab/text-to-video-ms-1.7b": {
        "max_frames": 64,
        "min_frames": 8,
        "default_frames": 32,
        "memory_usage_gb": 6,
        "supports_quantization": False,
        "stable": True,
    },
    "THUDM/CogVideoX-5b": {
        "max_frames": 48,  # Reduced for stability
        "min_frames": 16,
        "default_frames": 32,
        "memory_usage_gb": 16,  # Conservative estimate
        "supports_quantization": True,
        "stable": False,  # Mark as experimental
    },
    "parler-tts/parler-tts-mini-v1": {
        "max_text_length": 500,
        "min_text_length": 10,
        "default_voice": "Announcer '80s",
        "memory_usage_gb": 2,
        "stable": True,
    },
    "SWivid/F5-TTS": {
        "max_text_length": 300,
        "min_text_length": 10,
        "default_voice": "announcer",
        "memory_usage_gb": 4,
        "stable": False,  # Mark as experimental
    },
    "microsoft/DialoGPT-medium": {
        "max_tokens": 512,
        "temperature": 0.7,
        "top_p": 0.9,
        "memory_usage_gb": 2,
        "stable": True,
    },
    "Qwen/Qwen2.5-7B-Instruct": {
        "max_tokens": 1024,
        "temperature": 0.7,
        "top_p": 0.9,
        "memory_usage_gb": 8,
        "stable": False,  # Mark as experimental
    },
}

# Voice styles for TTS
VOICE_STYLES = {
    "Announcer '80s": "A confident, upbeat 1980s TV announcer with warm AM-radio tone.",
    "Mall PA": "Casual, slightly echoey mall public-address vibe.",
    "Late Night": "Low energy, sly late-night infomercial style.",
    "News Anchor": "Professional, authoritative news anchor delivery.",
    "Infomercial": "Enthusiastic, persuasive infomercial host style.",
    "Radio DJ": "Smooth, charismatic radio disc jockey voice.",
}

# Structure templates for script generation
STRUCTURE_TEMPLATES = [
    "Montage → Close-up → Logo stinger",
    "Before/After → Feature highlight → CTA",
    "Testimonial → B-roll → Price tag reveal",
    "Unboxing → Demo → Deal countdown",
    "Retro news bulletin → Product shot → Tagline",
    "Opening hook → Problem/Solution → Call to action",
    "Brand story → Product showcase → Final tagline",
]

# Taglines for commercial endings
TAGLINES = [
    "So retro, it's the future.",
    "Pixels you can trust.",
    "VHS vibes. Modern results.",
    "Old-school cool. New-school sales.",
    "Where nostalgia meets innovation.",
    "Rewind to the future.",
    "Classic style. Modern performance.",
    "The past perfected.",
    "EceMotion Pictures - Bringing the '80s back to life.",
    "Your story, our vision, timeless memories.",
]

def get_model_config(model_name: str) -> Dict[str, Any]:
    """Get configuration for a specific model."""
    return MODEL_CONFIGS.get(model_name, {
        "max_frames": 32,
        "min_frames": 8,
        "default_frames": 16,
        "memory_usage_gb": 4,
        "supports_quantization": False,
        "stable": True,
    })

def get_device() -> str:
    """Determine the best available device."""
    try:
        import torch
        if torch.cuda.is_available() and os.getenv("CUDA_VISIBLE_DEVICES", None) not in (None, ""):
            return "cuda"
    except ImportError:
        pass
    return "cpu"

def validate_config() -> bool:
    """Validate configuration settings."""
    try:
        assert MIN_DURATION < MAX_DURATION, "MIN_DURATION must be less than MAX_DURATION"
        assert DEFAULT_FPS > 0, "DEFAULT_FPS must be positive"
        assert AUDIO_SAMPLE_RATE > 0, "AUDIO_SAMPLE_RATE must be positive"
        assert 0 <= VHS_INTENSITY <= 1, "VHS_INTENSITY must be between 0 and 1"
        assert 0 <= SCANLINE_OPACITY <= 1, "SCANLINE_OPACITY must be between 0 and 1"
        return True
    except AssertionError as e:
        print(f"Configuration validation failed: {e}")
        return False

def get_safe_model_name(model_name: str, model_type: str) -> str:
    """Get a safe model name with fallback to stable models."""
    config = get_model_config(model_name)
    
    # If model is not stable, fallback to stable alternatives
    if not config.get("stable", False):
        if model_type == "video":
            return "damo-vilab/text-to-video-ms-1.7b"
        elif model_type == "audio":
            return "parler-tts/parler-tts-mini-v1"
        elif model_type == "llm":
            return "microsoft/DialoGPT-medium"
    
    return model_name

def log_config():
    """Log current configuration for debugging."""
    print(f"EceMotion Pictures Configuration:")
    print(f"  Video Model: {MODEL_VIDEO}")
    print(f"  Audio Model: {MODEL_AUDIO}")
    print(f"  LLM Model: {MODEL_LLM}")
    print(f"  Device: {get_device()}")
    print(f"  Duration Range: {MIN_DURATION}-{MAX_DURATION}s")
    print(f"  FPS: {DEFAULT_FPS}")
    print(f"  Sync Tolerance: {SYNC_TOLERANCE_MS}ms")