#!/usr/bin/env python3
"""HunyuanVideo I2V - Fixed with correct bucket node params"""

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

COMFY_URL = "http://localhost:8188"
INPUT_IMAGE = "pool_party.png"

PROMPT = """Two men stand beside a swimming pool at sunset. The larger man on the left slowly turns to face the smaller man. The smaller man turns around to face him. They embrace in a warm hug and share a tender romantic kiss. All movements are smooth, slow, and natural. High quality detailed hands with proper anatomy. Photorealistic video quality."""

workflow = {
    "1": {"class_type": "LoadImage", "inputs": {"image": INPUT_IMAGE, "upload": "image"}},
    
    "2": {"class_type": "HyVideoGetClosestBucketSize", "inputs": {
        "image": ["1", 0], "width": 848, "height": 480, "base_size": "540"
    }},
    
    "3": {"class_type": "HyVideoModelLoader", "inputs": {
        "model": "hunyuan/hunyuan_video_I2V_720_fixed_fp8_e4m3fn.safetensors",
        "base_precision": "bf16",
        "quantization": "fp8_e4m3fn",
        "load_device": "offload_device"
    }},
    
    "4": {"class_type": "HyVideoVAELoader", "inputs": {
        "model_name": "hunyuan_video_vae_bf16.safetensors",
        "precision": "bf16"
    }},
    
    "5": {"class_type": "DownloadAndLoadHyVideoTextEncoder", "inputs": {
        "llm_model": "Kijai/llava-llama-3-8b-text-encoder-tokenizer",
        "clip_model": "openai/clip-vit-large-patch14",
        "precision": "bf16"
    }},
    
    "6": {"class_type": "HyVideoEncode", "inputs": {
        "vae": ["4", 0],
        "image": ["1", 0],
        "enable_vae_tiling": True,
        "temporal_tiling_sample_size": 64,
        "spatial_tile_sample_min_size": 256,
        "auto_tile_size": True
    }},
    
    "7": {"class_type": "HyVideoI2VEncode", "inputs": {
        "text_encoders": ["5", 0],
        "prompt": PROMPT,
        "force_offload": True,
        "image": ["1", 0],
        "image_embed_interleave": 4
    }},
    
    "8": {"class_type": "HyVideoBlockSwap", "inputs": {"blocks_to_swap": 20, "offload_img_emb": False, "offload_txt_emb": False}},
    
    "9": {"class_type": "HyVideoSampler", "inputs": {
        "model": ["3", 0],
        "hyvid_embeds": ["7", 0],
        "width": ["2", 0],
        "height": ["2", 1],
        "num_frames": 61,
        "steps": 30,
        "embedded_guidance_scale": 6.0,
        "flow_shift": 9.0,
        "seed": 42,
        "force_offload": True,
        "scheduler": "FlowMatchDiscreteScheduler",
        "image_cond_latents": ["6", 0]
    }},
    
    "10": {"class_type": "HyVideoDecode", "inputs": {
        "vae": ["4", 0],
        "samples": ["9", 0],
        "enable_vae_tiling": True,
        "auto_tile_size": True,
        "temporal_tiling_sample_size": 64,
        "spatial_tile_sample_min_size": 256
    }},
    
    "11": {"class_type": "VHS_VideoCombine", "inputs": {
        "images": ["10", 0],
        "frame_rate": 24,
        "loop_count": 0,
        "filename_prefix": "Hunyuan_I2V_Final",
        "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()