ai_service/scripts/workflows/flux_redux.json

{
  "6": {
    "inputs": {
      "text": [
        "45",
        0
      ],
      "clip": [
        "11",
        0
      ]
    },
    "class_type": "CLIPTextEncode",
    "_meta": {
      "title": "CLIP Text Encode (Positive Prompt)"
    }
  },
  "8": {
    "inputs": {
      "samples": [
        "13",
        0
      ],
      "vae": [
        "10",
        0
      ]
    },
    "class_type": "VAEDecode",
    "_meta": {
      "title": "VAE解码"
    }
  },
  "9": {
    "inputs": {
      "filename_prefix": "ComfyUI",
      "images": [
        "8",
        0
      ]
    },
    "class_type": "SaveImage",
    "_meta": {
      "title": "保存图像"
    }
  },
  "10": {
    "inputs": {
      "vae_name": "ae.safetensors"
    },
    "class_type": "VAELoader",
    "_meta": {
      "title": "加载VAE"
    }
  },
  "11": {
    "inputs": {
      "clip_name1": "t5xxl_fp16.safetensors",
      "clip_name2": "clip_l.safetensors",
      "type": "flux",
      "device": "default"
    },
    "class_type": "DualCLIPLoader",
    "_meta": {
      "title": "双CLIP加载器"
    }
  },
  "12": {
    "inputs": {
      "unet_name": "flux1-dev.safetensors",
      "weight_dtype": "default"
    },
    "class_type": "UNETLoader",
    "_meta": {
      "title": "UNet加载器"
    }
  },
  "13": {
    "inputs": {
      "noise": [
        "25",
        0
      ],
      "guider": [
        "22",
        0
      ],
      "sampler": [
        "16",
        0
      ],
      "sigmas": [
        "17",
        0
      ],
      "latent_image": [
        "27",
        0
      ]
    },
    "class_type": "SamplerCustomAdvanced",
    "_meta": {
      "title": "自定义采样器（高级）"
    }
  },
  "16": {
    "inputs": {
      "sampler_name": "euler"
    },
    "class_type": "KSamplerSelect",
    "_meta": {
      "title": "K采样器选择"
    }
  },
  "17": {
    "inputs": {
      "scheduler": "simple",
      "steps": 20,
      "denoise": 1,
      "model": [
        "30",
        0
      ]
    },
    "class_type": "BasicScheduler",
    "_meta": {
      "title": "基本调度器"
    }
  },
  "22": {
    "inputs": {
      "model": [
        "30",
        0
      ],
      "conditioning": [
        "41",
        0
      ]
    },
    "class_type": "BasicGuider",
    "_meta": {
      "title": "基本引导器"
    }
  },
  "25": {
    "inputs": {
      "noise_seed": 214516345808749
    },
    "class_type": "RandomNoise",
    "_meta": {
      "title": "随机噪波"
    }
  },
  "26": {
    "inputs": {
      "guidance": 3.5,
      "conditioning": [
        "6",
        0
      ]
    },
    "class_type": "FluxGuidance",
    "_meta": {
      "title": "Flux引导"
    }
  },
  "27": {
    "inputs": {
      "width": 1024,
      "height": 1024,
      "batch_size": 4
    },
    "class_type": "EmptySD3LatentImage",
    "_meta": {
      "title": "空Latent图像（SD3）"
    }
  },
  "30": {
    "inputs": {
      "max_shift": 1.15,
      "base_shift": 0.5,
      "width": 1024,
      "height": 1024,
      "model": [
        "12",
        0
      ]
    },
    "class_type": "ModelSamplingFlux",
    "_meta": {
      "title": "采样算法（Flux）"
    }
  },
  "38": {
    "inputs": {
      "clip_name": "sigclip_vision_patch14_384.safetensors"
    },
    "class_type": "CLIPVisionLoader",
    "_meta": {
      "title": "加载CLIP视觉"
    }
  },
  "39": {
    "inputs": {
      "crop": "center",
      "clip_vision": [
        "38",
        0
      ],
      "image": [
        "40",
        0
      ]
    },
    "class_type": "CLIPVisionEncode",
    "_meta": {
      "title": "CLIP视觉编码"
    }
  },
  "40": {
    "inputs": {
      "image": "WechatIMG16695.jpeg"
    },
    "class_type": "LoadImage",
    "_meta": {
      "title": "加载图像"
    }
  },
  "41": {
    "inputs": {
      "strength": 1,
      "strength_type": "multiply",
      "conditioning": [
        "26",
        0
      ],
      "style_model": [
        "42",
        0
      ],
      "clip_vision_output": [
        "39",
        0
      ]
    },
    "class_type": "StyleModelApply",
    "_meta": {
      "title": "应用风格模型"
    }
  },
  "42": {
    "inputs": {
      "style_model_name": "flux1-redux-dev.safetensors"
    },
    "class_type": "StyleModelLoader",
    "_meta": {
      "title": "加载风格模型"
    }
  },
  "45": {
    "inputs": {
      "user_prompt": "作为一个AI提示词专家，请你仿照范例，根据我给出的主题，生成一条符合下列要求的提示词，来让CLIP模型可以更好地理解画面主体。注意：你的输出将提供给图生图（image-to-image）模型，所以你只需要对用户输入中的风格和细节部分作扩展。\n 要求共五条，请严格遵守：\n 1： 用自然语言简单句来描述画面，请避免出现过于长的，或者格式过于复杂的句子，句子中不要出现*等特殊符号。\n 2.用英语表达。 \n 3.直接给出prompt内容即可，不需要解释和说明。\n 4. 每条prompt至少50词，不超过200词。\n 5.避免模棱两可的说法。\n 例如：[Reference Image Weight: 0.7] Cartoonized Nankai University Main Building,  \nGothic-Revival architecture with rounded edges, crimson bricks and golden arched windows (ultra-high texture details), whimsical cloud-shaped eaves dripping liquid clock gears (steampunk elements), soft pastel gradients.  \nDynamic elements:  \nTranslucent 1919-era scholar phantoms floating with glowing books (semi-transparent mercury texture), oversized origami maple leaves spiraling around twin bell towers (visible musical notes in air).  \nEnvironment:  \nSurreal candy-pink to indigo gradient sky, emerald velvet lawns with squirrels wearing graduation caps (playful proportions:1.5x). Ground puddles reflecting calculus formula ripples (mathematical glow effect).  \nTechnical parameters:  \nStudio Ghibli style, watercolor rendering, 8K resolution, cinematic lighting, symmetry composition, ultra-detailed lineart",
      "system_prompt": "南开大学鸟瞰图，3D电影高级风格。",
      "enable_history": false,
      "max_history": 10,
      "history_json": "",
      "save_path": "./chat_history.json",
      "api_config": [
        "46",
        0
      ]
    },
    "class_type": "DeepSeekChat",
    "_meta": {
      "title": "LLM Model Input Box"
    }
  },
  "46": {
    "inputs": {
      "config_name": "DeepSeek官方Chat API",
      "temperature": 1,
      "max_tokens": 512,
      "stream": false,
      "api_key": ""
    },
    "class_type": "DeepSeekAPIConfig",
    "_meta": {
      "title": "LLM API Model Selector"
    }
  }
}