import os

# Set SLA attention backend BEFORE fastvideo imports
os.environ["FASTVIDEO_ATTENTION_BACKEND"] = "SLA_ATTN"

from fastvideo import VideoGenerator
from fastvideo.api import (
    EngineConfig, GenerationRequest, GeneratorConfig, OutputConfig, SamplingConfig,
)

OUTPUT_PATH = "video_samples_turbodiffusion"


def main() -> None:
    # TurboDiffusion: 1-4 step video generation using RCM scheduler + SLA attention
    # FastVideo will automatically use TurboDiffusionPipeline when specified
    generator = VideoGenerator.from_config(
        GeneratorConfig(
            model_path="loayrashid/TurboWan2.1-T2V-1.3B-Diffusers",
            # FastVideo will automatically handle distributed setup
            engine=EngineConfig(
                num_gpus=1,
                use_fsdp_inference=False,  # set to True if GPU is out of memory
            ),
            # set to false if using RTX 4090
            # pin_cpu_memory=False,
        )
    )

    # Generate videos with the same simple API, regardless of GPU count
    # TurboDiffusion defaults: guidance_scale=1.0 and num_inference_steps=4 (from config)
    prompt = (
        "A curious raccoon peers through a vibrant field of yellow sunflowers, its eyes "
        "wide with interest. The playful yet serene atmosphere is complemented by soft "
        "natural light filtering through the petals. Mid-shot, warm and cheerful tones."
    )
    video = generator.generate(
        GenerationRequest(
            prompt=prompt,
            output=OutputConfig(
                output_path=OUTPUT_PATH,
                save_video=True,
            ),
            sampling=SamplingConfig(
                seed=42,
            ),
        )
    )

    # Generate another video with a different prompt, without reloading the model!
    prompt2 = (
        "A majestic lion strides across the golden savanna, its powerful frame "
        "glistening under the warm afternoon sun. The tall grass ripples gently in "
        "the breeze, enhancing the lion's commanding presence. The tone is vibrant, "
        "embodying the raw energy of the wild. Low angle, steady tracking shot, "
        "cinematic."
    )
    video2 = generator.generate(
        GenerationRequest(
            prompt=prompt2,
            output=OutputConfig(
                output_path=OUTPUT_PATH,
                save_video=True,
            ),
            sampling=SamplingConfig(
                seed=42,
            ),
        )
    )


if __name__ == "__main__":
    main()