#!/usr/bin/env python3
"""HunyuanVideo I2V - Lilo & Stitch Pool Adventure"""

import json
import urllib.request
import urllib.error
import uuid

COMFY_URL = "http://localhost:8188"
INPUT_IMAGE = "lilo_stitch_pool.jpg"

# Refined prompt for Lilo & Stitch magical poolside adventure
PROMPT = """A magical poolside adventure with Lilo and Stitch. Lilo and Stitch are playing happily by the edge of a sparkling blue swimming pool. Stitch is doing a funny dance while Lilo laughs and claps her hands. The water in the pool ripples gently. Tropical plants and colorful flowers surround the pool area. The sun is shining brightly, creating beautiful reflections on the water. Disney animation style, vibrant colors, high quality, smooth character movement. Static camera shot. The camera remains perfectly still."""

workflow = {
    "1": {"class_type": "LoadImage", "inputs": {"image": INPUT_IMAGE, "upload": "image"}},
    
    "2": {"class_type": "HyVideoModelLoader", "inputs": {
        "model": "hunyuan/hunyuan_video_I2V_720_fixed_fp8_e4m3fn.safetensors",
        "base_precision": "bf16",
        "quantization": "fp8_e4m3fn",
        "load_device": "offload_device"
    }},
    
    "3": {"class_type": "HyVideoVAELoader", "inputs": {
        "model_name": "hunyuan_video_vae_bf16.safetensors",
        "precision": "bf16"
    }},
    
    "4": {"class_type": "DownloadAndLoadHyVideoTextEncoder", "inputs": {
        "llm_model": "Kijai/llava-llama-3-8b-text-encoder-tokenizer",
        "clip_model": "openai/clip-vit-large-patch14",
        "precision": "bf16",
        "quantization": "fp8_e4m3fn",
        "load_device": "offload_device"
    }},
    
    "5": {"class_type": "HyVideoEncode", "inputs": {
        "vae": ["3", 0],
        "image": ["1", 0],
        "enable_vae_tiling": True,
        "temporal_tiling_sample_size": 64,
        "spatial_tile_sample_min_size": 256,
        "auto_tile_size": True
    }},
    
    "6": {"class_type": "HyVideoI2VEncode", "inputs": {
        "text_encoders": ["4", 0],
        "prompt": PROMPT,
        "force_offload": True,
        "image": ["1", 0],
        "image_embed_interleave": 4
    }},
    
    "7": {"class_type": "HyVideoSampler", "inputs": {
        "model": ["2", 0],
        "hyvid_embeds": ["6", 0],
        "width": 1280,
        "height": 720,
        "num_frames": 81,
        "steps": 30,
        "embedded_guidance_scale": 6.0,
        "flow_shift": 9.0,
        "seed": 42,
        "force_offload": True,
        "scheduler": "FlowMatchDiscreteScheduler",
        "image_cond_latents": ["5", 0]
    }},
    
    "8": {"class_type": "HyVideoDecode", "inputs": {
        "vae": ["3", 0],
        "samples": ["7", 0],
        "enable_vae_tiling": True,
        "auto_tile_size": True,
        "temporal_tiling_sample_size": 64,
        "spatial_tile_sample_min_size": 256
    }},
    
    "9": {"class_type": "VHS_VideoCombine", "inputs": {
        "images": ["8", 0],
        "frame_rate": 24,
        "loop_count": 0,
        "filename_prefix": "LiloStitch_Pool_Adventure",
        "format": "video/h264-mp4",
        "pix_fmt": "yuv420p",
        "crf": 16,
        "save_metadata": True,
        "pingpong": False,
        "save_output": True
    }}
}

def submit():
    prompt_id = str(uuid.uuid4())
    data = {"prompt": workflow, "client_id": "selena"}
    req = urllib.request.Request(
        f"{COMFY_URL}/prompt",
        data=json.dumps(data).encode('utf-8'),
        headers={'Content-Type': 'application/json'}
    )
    try:
        with urllib.request.urlopen(req) as response:
            result = json.load(response)
            print(f"✅ Submitted! ID: {result.get('prompt_id')}")
    except urllib.error.HTTPError as e:
        print(f"❌ Error: {e.read().decode('utf-8')[:1500]}")

if __name__ == "__main__":
    submit()