from fastvideo import VideoGenerator
import json
# from fastvideo.api.sampling_param import SamplingParam

OUTPUT_PATH = "video_samples_hy15"


def main():
    # FastVideo will automatically use the optimal default arguments for the
    # model.
    # If a local path is provided, FastVideo will make a best effort
    # attempt to identify the optimal arguments.
    generator = VideoGenerator.from_pretrained(
        "hunyuanvideo-community/HunyuanVideo-1.5-Diffusers-480p_t2v",
        # FastVideo will automatically handle distributed setup
        num_gpus=1,
        use_fsdp_inference=False,  # set to True if GPU is out of memory
        dit_cpu_offload=True,
        vae_cpu_offload=True,
        text_encoder_cpu_offload=True,
        pin_cpu_memory=True,  # set to false if low CPU RAM or hit obscure "CUDA error: Invalid argument"
        # image_encoder_cpu_offload=False,
    )

    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({
        "prompt": prompt,
        "negative_prompt": "",
        "sampling": {"num_frames": 81, "fps": 16},
        "output": {"output_path": OUTPUT_PATH, "save_video": True},
    })

    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({
        "prompt": prompt2,
        "negative_prompt": "",
        "sampling": {"num_frames": 81, "fps": 16},
        "output": {"output_path": OUTPUT_PATH, "save_video": True},
    })


if __name__ == "__main__":
    main()