After the image is generated, the history/prompt_id operation obtains the response status but does not return the image

[DFires]

Your question

After the prompt API submits the task, the WS listens for the task status and calls the history/prompt_id operation to obtain the response status. However, no image is returned in the outputs node

Logs

history api response: {
    'prompt': [0, '630d9195-d483-4b79-8c70-73d503833957', {
            '22': {
                'class_type': 'PulidModelLoader',
                'inputs': {
                    'pulid_file': 'ip-adapter_pulid_sdxl_fp16.safetensors'
                },
                '_meta': {
                    'title': 'PuLID模型加载器'
                }
            },
            '44': {
                'class_type': 'InstantIDModelLoader',
                'inputs': {
                    'instantid_file': 'ip-adapter.bin'
                },
                '_meta': {
                    'title': 'InstnatID模型加载器'
                }
            },
            '88': {
                'class_type': 'UpscaleModelLoader',
                'inputs': {
                    'model_name': '4x_NMKD-Siax_200k.pth'
                },
                '_meta': {
                    'title': '放大模型加载器'
                }
            },
            '23': {
                'class_type': 'PulidEvaClipLoader',
                'inputs': {},
                '_meta': {
                    'title': 'PuLIDEVAClip加载器'
                }
            },
            '45': {
                'class_type': 'InstantIDFaceAnalysis',
                'inputs': {
                    'provider': 'CPU'
                },
                '_meta': {
                    'title': 'InstantID面部分析'
                }
            },
            '89': {
                'class_type': 'ImageScaleBy',
                'inputs': {
                    'image': ['87', 0],
                    'scale_by': 0.38,
                    'upscale_method': 'nearest-exact'
                },
                '_meta': {
                    'title': '图像按系数缩放'
                }
            },
            '46': {
                'class_type': 'ControlNetLoader',
                'inputs': {
                    'control_net_name': 'diffusion_pytorch_model.safetensors'
                },
                '_meta': {
                    'title': 'ControlNet加载器'
                }
            },
            '47': {
                'class_type': 'KSampler (Efficient)',
                'inputs': {
                    'vae_decode': 'true',
                    'latent_image': ['90', 0],
                    'seed': ['93', 0],
                    'cfg': 5.0,
                    'positive': ['43', 1],
                    'steps': 25,
                    'script': ['75', 0],
                    'scheduler': 'karras',
                    'negative': ['43', 2],
                    'denoise': 0.58,
                    'sampler_name': 'dpmpp_2m_sde',
                    'optional_vae': ['11', 4],
                    'preview_method': 'none',
                    'model': ['43', 0]
                },
                '_meta': {
                    'title': 'K采样器(效率)'
                }
            },
            '29': {
                'class_type': 'ApplyPulid',
                'inputs': {
                    'end_at': 1.0,
                    'image': ['86', 0],
                    'pulid': ['22', 0],
                    'method': 'fidelity',
                    'weight': 0.3,
                    'model': ['10', 0],
                    'eva_clip': ['23', 0],
                    'face_analysis': ['76', 0],
                    'start_at': 0.0
                },
                '_meta': {
                    'title': '应用PuLID'
                }
            },
            '90': {
                'class_type': 'VAEEncode',
                'inputs': {
                    'pixels': ['89', 0],
                    'vae': ['11', 4]
                },
                '_meta': {
                    'title': 'VAE编码'
                }
            },
            '92': {
                'class_type': 'String Literal',
                'inputs': {
                    'string': 'professional,4k,highly detailed,medium portrait soft light, beautiful model,vivid,photorealistic, vivid colors, ',
                    'speak_and_recognation': True
                },
                '_meta': {
                    'title': 'String Literal'
                }
            },
            '93': {
                'class_type': 'Seed Generator',
                'inputs': {
                    'seed': 1047523952660796
                },
                '_meta': {
                    'title': 'Seed Generator'
                }
            },
            '94': {
                'class_type': 'String Literal',
                'inputs': {
                    'string': '1man,indoors,business suit,necktie,,upper_body,portrait, ',
                    'speak_and_recognation': True
                },
                '_meta': {
                    'title': 'String Literal'
                }
            },
            '75': {
                'class_type': 'Noise Control Script',
                'inputs': {
                    'seed': 813662192183951,
                    'cfg_denoiser': False,
                    'add_seed_noise': False,
                    'weight': 0.015,
                    'rng_source': 'gpu'
                },
                '_meta': {
                    'title': '控制噪波'
                }
            },
            '10': {
                'class_type': 'Efficient Loader',
                'inputs': {
                    'lora_name': 'None',
                    'weight_interpretation': 'A1111',
                    'batch_size': 2,
                    'empty_latent_width': 832,
                    'empty_latent_height': 1216,
                    'speak_and_recognation': True,
                    'token_normalization': 'mean',
                    'lora_stack': ['103', 0],
                    'positive': ['99', 0],
                    'lora_clip_strength': 1.0,
                    'ckpt_name': 'leosamsHelloworldXL_helloworldXL70.safetensors',
                    'negative': '(worst quality, low quality, blurry, bad eye, wrong hand, bad anatomy, wrong anatomy, open mouth, deformed, distorted, disfigured, cgi, illustration, cartoon, poorly drawn, watermark),nsfw,nipples,flag,american_flag, ',
                    'lora_model_strength': 1.0,
                    'clip_skip': -1,
                    'vae_name': 'Baked VAE'
                },
                '_meta': {
                    'title': '效率加载器'
                }
            },
            '76': {
                'class_type': 'PulidInsightFaceLoader',
                'inputs': {
                    'provider': 'CPU'
                },
                '_meta': {
                    'title': 'PuLIDInsightFace加载器'
                }
            },
            '11': {
                'class_type': 'KSampler (Efficient)',
                'inputs': {
                    'vae_decode': 'true',
                    'latent_image': ['10', 3],
                    'seed': ['93', 0],
                    'cfg': 6.0,
                    'positive': ['10', 1],
                    'steps': 25,
                    'script': ['75', 0],
                    'scheduler': 'karras',
                    'negative': ['10', 2],
                    'denoise': 1.0,
                    'sampler_name': 'dpmpp_2m_sde',
                    'optional_vae': ['10', 4],
                    'preview_method': 'none',
                    'model': ['29', 0]
                },
                '_meta': {
                    'title': 'K采样器(效率)'
                }
            },
            '99': {
                'class_type': 'Text Concatenate',
                'inputs': {
                    'delimiter': ', ',
                    'text_a': ['94', 0],
                    'clean_whitespace': 'true',
                    'text_c': ['92', 0],
                    'text_b': ['100', 0]
                },
                '_meta': {
                    'title': '文本连锁'
                }
            },
            '16': {
                'class_type': 'LoadImage',
                'inputs': {
                    'image': '94a506e555b24c20969b19a401825986.png',
                    'upload': 'image'
                },
                '_meta': {
                    'title': '加载图像'
                }
            },
            '100': {
                'class_type': 'String Literal',
                'inputs': {
                    'string': '',
                    'speak_and_recognation': True
                },
                '_meta': {
                    'title': 'String Literal'
                }
            },
            '103': {
                'class_type': 'easy loraStack',
                'inputs': {
                    'lora_3_name': 'None',
                    'lora_6_name': 'None',
                    'lora_7_strength': 1.0,
                    'lora_9_clip_strength': 1.0,
                    'lora_1_strength': 0.6,
                    'lora_9_model_strength': 1.0,
                    'lora_5_model_strength': 1.0,
                    'lora_4_clip_strength': 1.0,
                    'lora_2_clip_strength': 1.0,
                    'lora_4_strength': 1.0,
                    'mode': 'simple',
                    'num_loras': 1,
                    'lora_6_clip_strength': 1.0,
                    'lora_8_name': 'None',
                    'lora_7_name': 'None',
                    'lora_8_model_strength': 1.0,
                    'lora_5_strength': 1.0,
                    'lora_4_name': 'None',
                    'lora_4_model_strength': 1.0,
                    'lora_1_name': 'None',
                    'lora_2_strength': 1.0,
                    'lora_2_model_strength': 1.0,
                    'lora_3_clip_strength': 1.0,
                    'lora_8_clip_strength': 1.0,
                    'lora_10_model_strength': 1.0,
                    'lora_7_model_strength': 1.0,
                    'lora_8_strength': 1.0,
                    'toggle': False,
                    'lora_1_clip_strength': 1.0,
                    'lora_2_name': 'None',
                    'lora_10_name': 'None',
                    'lora_10_clip_strength': 1.0,
                    'lora_10_strength': 1.0,
                    'lora_1_model_strength': 1.0,
                    'lora_5_name': 'None',
                    'lora_3_model_strength': 1.0,
                    'lora_9_strength': 1.0,
                    'lora_3_strength': 1.0,
                    'lora_5_clip_strength': 1.0,
                    'lora_6_model_strength': 1.0,
                    'lora_6_strength': 1.0,
                    'lora_7_clip_strength': 1.0,
                    'lora_9_name': 'None'
                },
                '_meta': {
                    'title': '简易Lora堆'
                }
            },
            '85': {
                'class_type': 'LayerUtility: SaveImagePlus',
                'inputs': {
                    'preview': False,
                    'filename_prefix': 'comfyui',
                    'images': ['47', 5],
                    'save_workflow_as_json': False,
                    'custom_path': '',
                    'format': 'png',
                    'meta_data': False,
                    'blind_watermark': '',
                    'timestamp': 'None',
                    'quality': 100
                },
                '_meta': {
                    'title': 'LayerUtility: SaveImage Plus'
                }
            },
            '86': {
                'class_type': 'CropFace',
                'inputs': {
                    'image': ['16', 0],
                    'facedetection': 'retinaface_resnet50'
                },
                '_meta': {
                    'title': '裁剪面部'
                }
            },
            '43': {
                'class_type': 'ApplyInstantID',
                'inputs': {
                    'instantid': ['44', 0],
                    'end_at': 1.0,
                    'image': ['86', 0],
                    'negative': ['11', 2],
                    'control_net': ['46', 0],
                    'insightface': ['45', 0],
                    'image_kps': ['89', 0],
                    'weight': 0.8,
                    'model': ['11', 0],
                    'positive': ['11', 1],
                    'start_at': 0.0
                },
                '_meta': {
                    'title': '应用InstantID'
                }
            },
            '87': {
                'class_type': 'ImageUpscaleWithModel',
                'inputs': {
                    'image': ['11', 5],
                    'upscale_model': ['88', 0]
                },
                '_meta': {
                    'title': '图像通过模型放大'
                }
            }
        }, {
            'client_id': 'f7fdb85f7b0f435498a348772b8e45b1'
        },
        ['85', '47', '11']
    ],
    'outputs': {
        '11': {
            'images': []
        },
        '85': {
            'images': []
        },
        '47': {
            'images': []
        }
    },
    'status': {
        'status_str': 'success',
        'completed': True,
        'messages': [
            ['execution_start', {
                'prompt_id': '630d9195-d483-4b79-8c70-73d503833957',
                'timestamp': 1727321498175
            }],
            ['execution_cached', {
                'nodes': [],
                'prompt_id': '630d9195-d483-4b79-8c70-73d503833957',
                'timestamp': 1727321498252
            }],
            ['execution_success', {
                'prompt_id': '630d9195-d483-4b79-8c70-73d503833957',
                'timestamp': 1727321574821
            }]
        ]
    },
    'meta': {
        '11': {
            'node_id': '11',
            'display_node': '11',
            'parent_node': None,
            'real_node_id': '11'
        },
        '85': {
            'node_id': '85',
            'display_node': '85',
            'parent_node': None,
            'real_node_id': '85'
        },
        '47': {
            'node_id': '47',
            'display_node': '47',
            'parent_node': None,
            'real_node_id': '47'
        }
    }
}
}

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