#!/usr/bin/env python3
"""短剧《雨夜撞上陆总后》第十五集 - 场景图生成"""
import json, urllib.request, time
COMFYUI_URL = "http://127.0.0.1:8188"
BEST_MODEL = "SDXL 1.0\\9527DetailRealistic_v30.safetensors"
NEGATIVE_PROMPT = "(worst quality, low quality:1.4), deformed, distorted, disfigured, bad anatomy, bad proportions, ugly, noisy, blurry, low contrast, watermark, text, signature, cartoon, anime, 3d, painting, drawing, illustration, western features, blue eyes, blonde hair, extra fingers, malformed hands, missing limbs, floating limbs, disconnected limbs, nsfw, nude, naked"
SCENES = [
    {"id": "01", "name": "蜜月归来", "seed": 17001, "width": 1216, "height": 832, "prompt": "(masterpiece, best quality, ultra-detailed:1.3), couple returning home from honeymoon, airport arrival, luggage, happy expressions, home setting, photorealistic, 8k, wide shot", "output_prefix": "Drama_EP15_01_Return_Home_"},
    {"id": "02", "name": "身体不适", "seed": 17002, "width": 832, "height": 1216, "prompt": "(masterpiece, best quality, ultra-detailed:1.3), beautiful chinese woman feeling sick in bathroom, morning sickness, concerned expression, home interior, photorealistic, 8k, medium shot", "output_prefix": "Drama_EP15_02_Feeling_Sick_"},
    {"id": "03", "name": "验孕棒", "seed": 17003, "width": 832, "height": 1216, "prompt": "(masterpiece, best quality, ultra-detailed:1.3), close-up of positive pregnancy test with two lines, woman's hand holding, emotional moment, soft focus, photorealistic, 8k, close-up", "output_prefix": "Drama_EP15_03_Pregnancy_Test_"},
    {"id": "04", "name": "惊喜告白", "seed": 17004, "width": 1216, "height": 832, "prompt": "(masterpiece, best quality, ultra-detailed:1.3), woman showing pregnancy test to man, living room setting, man surprised, emotional moment, photorealistic, 8k, medium shot", "output_prefix": "Drama_EP15_04_Surprise_Reveal_"},
    {"id": "05", "name": "准爸爸反应", "seed": 17005, "width": 1216, "height": 832, "prompt": "(masterpiece, best quality, ultra-detailed:1.3), man hugging woman tightly after pregnancy reveal, tears of joy, emotional expression, living room, photorealistic, 8k, medium shot", "output_prefix": "Drama_EP15_05_Dad_Reaction_"},
    {"id": "06", "name": "医院检查", "seed": 17006, "width": 1216, "height": 832, "prompt": "(masterpiece, best quality, ultra-detailed:1.3), couple at doctor's office, ultrasound examination, doctor explaining, hospital setting, happy expressions, photorealistic, 8k, medium shot", "output_prefix": "Drama_EP15_06_Hospital_Visit_"},
    {"id": "07", "name": "家庭会议", "seed": 17007, "width": 1216, "height": 832, "prompt": "(masterpiece, best quality, ultra-detailed:1.3), family gathering to celebrate pregnancy, parents excited, couple smiling, living room, warm atmosphere, photorealistic, 8k, wide shot", "output_prefix": "Drama_EP15_07_Family_Meeting_"},
    {"id": "08", "name": "幸福期待", "seed": 17008, "width": 832, "height": 1216, "prompt": "(masterpiece, best quality, ultra-detailed:1.3), man gently touching woman's pregnant belly, bedroom setting, moonlight, intimate moment, emotional expression, photorealistic, 8k, medium shot", "output_prefix": "Drama_EP15_08_Happy_Expectation_"}
]
def submit_prompt(scene):
    prompt_data = {"prompt": {"3": {"class_type": "KSampler", "inputs": {"cfg": 7.0, "denoise": 1, "latent_image": ["5", 0], "model": ["4", 0], "negative": ["7", 0], "positive": ["6", 0], "sampler_name": "dpmpp_2m", "scheduler": "karras", "seed": scene["seed"], "steps": 30}}, "4": {"class_type": "CheckpointLoaderSimple", "inputs": {"ckpt_name": BEST_MODEL}}, "5": {"class_type": "EmptyLatentImage", "inputs": {"batch_size": 1, "height": scene["height"], "width": scene["width"]}}, "6": {"class_type": "CLIPTextEncode", "inputs": {"clip": ["4", 1], "text": scene["prompt"]}}, "7": {"class_type": "CLIPTextEncode", "inputs": {"clip": ["4", 1], "text": NEGATIVE_PROMPT}}, "8": {"class_type": "VAEDecode", "inputs": {"samples": ["3", 0], "vae": ["4", 2]}}, "9": {"class_type": "SaveImage", "inputs": {"filename_prefix": scene["output_prefix"], "images": ["8", 0]}}}}
    try:
        req = urllib.request.Request(f'{COMFYUI_URL}/prompt', data=json.dumps(prompt_data).encode('utf-8'), headers={'Content-Type': 'application/json'}, method='POST')
        with urllib.request.urlopen(req, timeout=10) as response:
            result = json.loads(response.read().decode('utf-8'))
            return True, result.get('prompt_id', 'unknown')
    except Exception as e:
        return False, str(e)
def main():
    print("=" * 70); print("🎬 短剧《雨夜撞上陆总后》第十五集 - 场景图生成"); print("=" * 70)
    print(f"\n📦 使用模型：{BEST_MODEL}"); print(f"📊 场景数量：{len(SCENES)} 个"); print("=" * 70)
    print("\n📡 检查 ComfyUI 连接...")
    try:
        req = urllib.request.Request(f'{COMFYUI_URL}/queue', method='GET')
        with urllib.request.urlopen(req, timeout=5) as response:
            queue = json.loads(response.read().decode('utf-8'))
            print(f"✅ ComfyUI 连接成功"); print(f"   当前队列：{len(queue.get('queue_running', []))} 运行中，{len(queue.get('queue_pending', []))} 等待中")
    except Exception as e:
        print(f"❌ 无法连接 ComfyUI: {e}"); return
    print("\n" + "=" * 70); print("🚀 开始提交生成任务..."); print("=" * 70)
    success_count = 0
    for i, scene in enumerate(SCENES, 1):
        print(f"\n[{i}/{len(SCENES)}] {scene['name']}"); success, result = submit_prompt(scene)
        if success: print(f"   ✅ 提交成功 (Prompt ID: {result})"); success_count += 1
        else: print(f"   ❌ 提交失败：{result}"); time.sleep(0.5)
    print("\n" + "=" * 70); print("📊 生成结果"); print("=" * 70); print(f"✅ 成功：{success_count}/{len(SCENES)}")
    if success_count > 0: print(f"\n💾 图片将保存到：ComfyUI/output/\n   文件名前缀：Drama_EP15_XX_场景名_\n\n🌐 查看进度：http://127.0.0.1:8188")
    print("\n" + "=" * 70); print("\n📋 场景清单:"); print("-" * 70)
    for scene in SCENES: print(f"  {scene['id']}. {scene['name']} - {scene['output_prefix']}")
    print("-" * 70)
if __name__ == "__main__":
    main()