"""
Wan2.2 distilled model image-to-video generation example.
This example demonstrates how to use LightX2V with Wan2.2 distilled model for I2V generation.
"""

from lightx2v import LightX2VPipeline

# Initialize pipeline for Wan2.2 distilled I2V task
# For wan2.1, use model_cls="wan2.1_distill"
pipe = LightX2VPipeline(
    model_path="/path/to/wan2.2/Wan2.2-I2V-A14B",
    model_cls="wan2.2_moe_distill",
    task="i2v",
    # Distilled weights: For wan2.1, only need to specify dit_original_ckpt="/path/to/wan2.1_i2v_720p_lightx2v_4step.safetensors"
    low_noise_original_ckpt="/path/to/wan2.2_i2v_A14b_low_noise_lightx2v_4step.safetensors",
    high_noise_original_ckpt="/path/to/wan2.2_i2v_A14b_high_noise_lightx2v_4step_1030.safetensors",
)

# Alternative: create generator from config JSON file
# pipe.create_generator(
#     config_json="../configs/wan22/wan_moe_i2v_distill.json"
# )

# Enable offloading to significantly reduce VRAM usage
# Suitable for RTX 30/40/50 consumer GPUs
pipe.enable_offload(
    cpu_offload=True,
    offload_granularity="block",
    text_encoder_offload=True,
    image_encoder_offload=False,
    vae_offload=False,
)

# Create generator manually with specified parameters
pipe.create_generator(
    attn_mode="sage_attn2",
    infer_steps=4,
    height=480,  # Can be set to 720 for higher resolution
    width=832,  # Can be set to 1280 for higher resolution
    num_frames=81,
    guidance_scale=1,
    sample_shift=5.0,
)

seed = 42
prompt = "Summer beach vacation style, a white cat wearing sunglasses sits on a surfboard. The fluffy-furred feline gazes directly at the camera with a relaxed expression. Blurred beach scenery forms the background featuring crystal-clear waters, distant green hills, and a blue sky dotted with white clouds. The cat assumes a naturally relaxed posture, as if savoring the sea breeze and warm sunlight. A close-up shot highlights the feline's intricate details and the refreshing atmosphere of the seaside."
negative_prompt = "镜头晃动，色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走"
save_result_path = "/path/to/save_results/output.mp4"
image_path = "/path/to/img_0.jpg"

pipe.generate(
    seed=seed,
    image_path=image_path,
    prompt=prompt,
    negative_prompt=negative_prompt,
    save_result_path=save_result_path,
)