Add Flux2 Klein multi-reference edit workflow
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# Flux.2 Klein 9B multi-reference composite
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API workflow for combining two reference images with Flux.2 Klein:
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- `person_reference.png` supplies the primary subject identity and appearance.
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- `scene_reference.png` supplies the environment, lighting, perspective, and composition.
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The workflow chains both encoded images through `ReferenceLatent` for the positive and negative conditioning branches, then renders a 1920×1080 result. Update the prompt when the references have different roles (for example, product + room, character + landscape, or object + background).
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This is an API-format workflow. The tested example is stored under `fluxExperiments/multiImage/`.
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{
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"1": {"class_type":"LoadImage","inputs":{"image":"person_reference.png"}},
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"2": {"class_type":"LoadImage","inputs":{"image":"scene_reference.png"}},
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"70": {"class_type":"UNETLoader","inputs":{"unet_name":"flux-2-klein-9b-fp8mixed.safetensors","weight_dtype":"default"}},
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"71": {"class_type":"CLIPLoader","inputs":{"clip_name":"qwen_3_8b_fp8mixed.safetensors","type":"flux2","device":"default"}},
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"72": {"class_type":"VAELoader","inputs":{"vae_name":"full_encoder_small_decoder.safetensors"}},
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"80": {"class_type":"ImageScaleToTotalPixels","inputs":{"image":["1",0],"upscale_method":"nearest-exact","megapixels":1.0,"resolution_steps":1}},
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"81": {"class_type":"ImageScaleToTotalPixels","inputs":{"image":["2",0],"upscale_method":"nearest-exact","megapixels":1.0,"resolution_steps":1}},
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"124": {"class_type":"VAEEncode","inputs":{"pixels":["80",0],"vae":["72",0]}},
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"125": {"class_type":"VAEEncode","inputs":{"pixels":["81",0],"vae":["72",0]}},
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"74": {"class_type":"CLIPTextEncode","inputs":{"text":"Combine two reference images into one coherent photorealistic image. Image 1 is the authoritative identity and full-appearance reference for the primary subject; preserve that subject's face, hair, skin, clothing, accessories, proportions, anatomy, and important visible details. Image 2 is the authoritative environment and composition reference; preserve its setting, materials, lighting, perspective, and important scene details. Place the exact primary subject naturally into the environment, matching scale, contact shadows, perspective, and lighting. Replace the source background when appropriate. Keep one coherent primary subject, natural anatomy, natural hands and feet, no duplicate subjects, no extra limbs, no text, no logos, and no watermark.","clip":["71",0]}},
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"82": {"class_type":"ConditioningZeroOut","inputs":{"conditioning":["74",0]}},
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"126": {"class_type":"ReferenceLatent","inputs":{"conditioning":["74",0],"latent":["124",0]}},
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"127": {"class_type":"ReferenceLatent","inputs":{"conditioning":["126",0],"latent":["125",0]}},
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"128": {"class_type":"ReferenceLatent","inputs":{"conditioning":["82",0],"latent":["124",0]}},
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"129": {"class_type":"ReferenceLatent","inputs":{"conditioning":["128",0],"latent":["125",0]}},
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"63": {"class_type":"CFGGuider","inputs":{"cfg":1.0,"model":["70",0],"positive":["127",0],"negative":["129",0]}},
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"61": {"class_type":"KSamplerSelect","inputs":{"sampler_name":"euler"}},
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"62": {"class_type":"Flux2Scheduler","inputs":{"steps":6,"width":1920,"height":1080}},
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"66": {"class_type":"EmptyFlux2LatentImage","inputs":{"width":1920,"height":1080,"batch_size":1}},
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"73": {"class_type":"RandomNoise","inputs":{"noise_seed":20260953}},
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"64": {"class_type":"SamplerCustomAdvanced","inputs":{"noise":["73",0],"guider":["63",0],"sampler":["61",0],"sigmas":["62",0],"latent_image":["66",0]}},
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"65": {"class_type":"VAEDecode","inputs":{"samples":["64",0],"vae":["72",0]}},
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"9": {"class_type":"SaveImage","inputs":{"images":["65",0],"filename_prefix":"fluxExperiments/multiImage/combined_person_scene"}}
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}
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