Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Generate fashion model imagery, virtual try-on, runway videos, and campaign visuals using EachLabs AI. Use when the user needs fashion content, model photography, or virtual try-on.
Generate fashion model imagery, virtual try-on, runway videos, and campaign visuals using EachLabs AI. Use when the user needs fashion content, model photography, or virtual try-on.
This item's current download entry is known to bounce back to a listing or homepage instead of returning a package file.
Use the source page and any available docs to guide the install because the item currently does not return a direct package file.
I tried to install a skill package from Yavira, but the item currently does not return a direct package file. Inspect the source page and any extracted docs, then tell me what you can confirm and any manual steps still required.
I tried to upgrade a skill package from Yavira, but the item currently does not return a direct package file. Compare the source page and any extracted docs with my current installation, then summarize what changed and what manual follow-up I still need.
Generate AI fashion model imagery, virtual try-on experiences, runway content, and campaign visuals using EachLabs models.
Header: X-API-Key: <your-api-key> Set the EACHLABS_API_KEY environment variable. Get your key at eachlabs.ai.
TaskModelSlugFashion model generationGPT Image v1.5gpt-image-v1-5-text-to-imageVirtual try-on (best)Kolors Virtual Try-Onkling-v1-5-kolors-virtual-try-onVirtual try-on (alt)IDM VTONidm-vtonGarment on modelWan v2.6 Image-to-Imagewan-v2-6-image-to-imageModel photoshootProduct Photo to Modelshootproduct-photo-to-modelshootPhotoshoot stylingNano Banana Pro Photoshootnano-banana-pro-photoshootFace/look consistencyOmni Zeroomni-zeroCharacter consistencyIdeogram Characterideogram-characterPhotomakerPhotomakerphotomakerPhotomaker StylePhotomaker Stylephotomaker-styleAvatar generationInstant IDinstant-idSoul stylingHiggsfield AI Soulhiggsfield-ai-soulBecome imageBecome Imagebecome-image
TaskModelSlugBrand style trainingZ Image Trainerz-image-trainerPortrait LoRAFlux LoRA Portrait Trainerflux-lora-portrait-trainer
TaskModelSlugRunway videoPixverse v5.6 Image-to-Videopixverse-v5-6-image-to-videoCatwalk animationBytedance Omnihuman v1.5bytedance-omnihuman-v1-5Motion referenceKling v2.6 Pro Motionkling-v2-6-pro-motion-control
Check model GET https://api.eachlabs.ai/v1/model?slug=<slug> β validates the model exists and returns the request_schema with exact input parameters. Always do this before creating a prediction to ensure correct inputs. POST https://api.eachlabs.ai/v1/prediction with model slug, version "0.0.1", and input matching the schema Poll GET https://api.eachlabs.ai/v1/prediction/{id} until status is "success" or "failed" Extract output URL from response
curl -X POST https://api.eachlabs.ai/v1/prediction \ -H "Content-Type: application/json" \ -H "X-API-Key: $EACHLABS_API_KEY" \ -d '{ "model": "gpt-image-v1-5-text-to-image", "version": "0.0.1", "input": { "prompt": "Professional fashion model wearing a tailored navy blazer, editorial photography, studio lighting, full body shot, neutral background", "image_size": "1024x1536", "quality": "high" } }'
Combine a garment image with a model image: curl -X POST https://api.eachlabs.ai/v1/prediction \ -H "Content-Type: application/json" \ -H "X-API-Key: $EACHLABS_API_KEY" \ -d '{ "model": "wan-v2-6-image-to-image", "version": "0.0.1", "input": { "prompt": "The person in image 1 wearing the clothing from image 2, professional fashion photography, editorial style", "image_urls": ["https://example.com/model.jpg", "https://example.com/garment.jpg"], "image_size": "portrait_4_3" } }'
curl -X POST https://api.eachlabs.ai/v1/prediction \ -H "Content-Type: application/json" \ -H "X-API-Key: $EACHLABS_API_KEY" \ -d '{ "model": "pixverse-v5-6-image-to-video", "version": "0.0.1", "input": { "image_url": "https://example.com/fashion-model.jpg", "prompt": "Fashion model walking confidently on a runway, camera follows from front, professional fashion show lighting", "duration": "5", "resolution": "1080p" } }'
Use a real runway walk as motion reference: curl -X POST https://api.eachlabs.ai/v1/prediction \ -H "Content-Type: application/json" \ -H "X-API-Key: $EACHLABS_API_KEY" \ -d '{ "model": "kling-v2-6-pro-motion-control", "version": "0.0.1", "input": { "image_url": "https://example.com/fashion-model.jpg", "video_url": "https://example.com/runway-walk-reference.mp4", "character_orientation": "video" } }'
Train a LoRA on your brand's visual style for consistent campaign imagery: curl -X POST https://api.eachlabs.ai/v1/prediction \ -H "Content-Type: application/json" \ -H "X-API-Key: $EACHLABS_API_KEY" \ -d '{ "model": "z-image-trainer", "version": "0.0.1", "input": { "image_data_url": "https://example.com/brand-photos.zip", "default_caption": "brand editorial fashion photography style", "training_type": "style", "steps": 1500 } }'
Specify pose: "full body shot", "half body", "close-up on garment details" Include lighting: "editorial studio lighting", "natural light", "dramatic side lighting" Mention style: "editorial", "street style", "haute couture", "casual lookbook" For diversity: specify body types, skin tones, and ages in prompts For consistency: use the same style keywords across a campaign series
See the eachlabs-image-generation and eachlabs-video-generation references for complete model parameters.
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Largest current source with strong distribution and engagement signals.