from video_gen import VideoGenerator

# Initialize with advanced model
generator = VideoGenerator(model="animatediff", quality="high")

# Generate video from text
video = generator.text_to_video(
    prompt="A serene lake at sunset with gentle ripples",
    duration=4.0,  # seconds
    fps=24,
    resolution=(1024, 576)
)

# Save output
video.save("outputs/lake_sunset.mp4")

# Initialize SVD model
generator = VideoGenerator(model="stable-video-diffusion")

# Generate from image
video = generator.image_to_video(
    image_path="inputs/landscape.jpg",
    motion_strength=0.7,
    duration=3.0
)

# Fast generation for prototyping
quick_gen = VideoGenerator(model="text2video-zero", mode="fast")

video = quick_gen.text_to_video(
    prompt="Flying through clouds",
    duration=2.0,
    quality="standard"
)

from video_gen.batch import BatchProcessor

processor = BatchProcessor()

# Process multiple prompts
prompts = [
    "Ocean waves crashing on rocks",
    "City skyline at night with moving traffic",
    "Forest with sunlight filtering through trees"
]

processor.batch_text_to_video(
    prompts=prompts,
    output_dir="outputs/batch/",
    model="animatediff"
)

# Add your own fine-tuned model
from video_gen.models import register_custom_model

register_custom_model(
    name="my_custom_model",
    path="models/custom/my_model",
    config="config/custom_model.yaml"
)

# Chain multiple operations
pipeline = VideoGenerator.create_pipeline([
    ("upscale", {"factor": 2}),
    ("stabilize", {"strength": 0.5}),
    ("enhance", {"sharpness": 1.2})
])

enhanced_video = pipeline.process(original_video)

# Automatic memory optimization
generator = VideoGenerator(
    model="stable-video-diffusion",
    memory_management="auto",
    enable_xformers=True,
    use_fp16=True
)

# Distribute across multiple GPUs
generator = VideoGenerator(
    model="animatediff",
    device_map="auto",
    gpu_ids=[0, 1, 2]
)

from video_gen.scheduler import VideoScheduler

scheduler = VideoScheduler()

# Schedule daily content generation
scheduler.add_daily_task(
    prompt_source="prompts/daily_prompts.txt",
    output_pattern="outputs/daily/{date}_{prompt_hash}.mp4",
    model="animatediff"
)

scheduler.start()

# Automatic error handling and retries
generator = VideoGenerator(
    auto_retry=True,
    max_retries=3,
    fallback_model="text2video-zero"
)

# Reduce batch size or use gradient checkpointing
generator = VideoGenerator(
    model="animatediff",
    gradient_checkpointing=True,
    batch_size=1
)