Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Generate new images from text prompts using EachLabs AI models. Supports text-to-image with multiple model families including Flux, GPT Image, Gemini, Imagen, Seedream, and more. Use when the user wants to create new images from text. For editing existing images, see eachlabs-image-edit.
Generate new images from text prompts using EachLabs AI models. Supports text-to-image with multiple model families including Flux, GPT Image, Gemini, Imagen, Seedream, and more. Use when the user wants to create new images from text. For editing existing images, see eachlabs-image-edit.
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Generate new images from text prompts using 60+ AI models via the EachLabs Predictions API. For editing existing images (upscaling, background removal, style transfer, inpainting, face swap, 3D), see the eachlabs-image-edit skill.
Header: X-API-Key: <your-api-key> Set the EACHLABS_API_KEY environment variable. Get your key at eachlabs.ai.
curl -X POST https://api.eachlabs.ai/v1/prediction \ -H "Content-Type: application/json" \ -H "X-API-Key: $EACHLABS_API_KEY" \ -d '{ "model": "flux-2-turbo-text-to-image", "version": "0.0.1", "input": { "prompt": "A serene Japanese garden with cherry blossoms, watercolor style", "image_size": "landscape_16_9", "num_images": 1, "output_format": "png" } }'
curl https://api.eachlabs.ai/v1/prediction/{prediction_id} \ -H "X-API-Key: $EACHLABS_API_KEY" Poll until status is "success" or "failed". The output image URL is in the response.
ModelSlugBest ForFlux 2 Turboflux-2-turbo-text-to-imageFast, high quality general purposeFlux 2 Flashflux-2-flash-text-to-imageFastest Flux generationFlux 2 Maxflux-2-max-text-to-imageHighest quality FluxFlux 2 Klein 9Bflux-2-klein-9b-base-text-to-imageBalanced quality/speedFlux 2 Proflux-2-proPro qualityFlux 2 Flexflux-2-flexFlexible outputsFlux 2 LoRAflux-2-loraLoRA-powered generationXAI Grok Imaginexai-grok-imagine-text-to-imageCreative and artisticGPT Image v1.5gpt-image-v1-5-text-to-imageHigh quality, transparent bgBytedance Seedream v4.5bytedance-seedream-v4-5-text-to-imageBytedance latestGemini 3 Pro Imagegemini-3-pro-image-previewGoogle's latestImagen 4imagen4-previewGoogle Imagen 4Imagen 4 Fastimagen-4-fastFast Google qualityRevereve-text-to-imageArtistic text-to-imageHunyuan Image v3hunyuan-image-v3-text-to-imageTencent's latestIdeogram V3 Turboideogram-v3-turboText in imagesMinimaxminimax-text-to-imageHigh qualityWan v2.6wan-v2-6-text-to-imageChinese/English bilingualP Imagep-image-text-to-imageCustom aspect ratiosNano Banana Pronano-banana-proFast, lightweightVidu Q2vidu-q2-text-to-imageLatest Vidu
ModelSlugBest ForZ Image Trainerz-image-trainerCustom LoRA trainingFlux LoRA Portrait Trainerflux-lora-portrait-trainerPortrait LoRAFlux Turbo Trainerflux-turbo-trainerFast LoRA training
Check model GET https://api.eachlabs.ai/v1/model?slug=<slug> โ 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 parameters matching the schema Poll GET https://api.eachlabs.ai/v1/prediction/{id} until status is "success" or "failed" Extract the output image URL(s) from the response
curl -X POST https://api.eachlabs.ai/v1/prediction \ -H "Content-Type: application/json" \ -H "X-API-Key: $EACHLABS_API_KEY" \ -d '{ "model": "flux-2-turbo-text-to-image", "version": "0.0.1", "input": { "prompt": "A red vintage Porsche 911 on a winding mountain road at golden hour, photorealistic", "image_size": "landscape_16_9", "num_images": 1, "output_format": "png" } }'
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": "A minimalist logo for a coffee shop called Brew Lab, clean vector style", "background": "transparent", "quality": "high", "output_format": "png" } }'
curl -X POST https://api.eachlabs.ai/v1/prediction \ -H "Content-Type: application/json" \ -H "X-API-Key: $EACHLABS_API_KEY" \ -d '{ "model": "imagen4-preview", "version": "0.0.1", "input": { "prompt": "A whimsical fairy tale castle on a floating island, digital art, highly detailed" } }'
Most Flux 2 and Wan models use these presets: square_hd โ Square, high definition square โ Square, standard portrait_4_3 โ Portrait 4:3 portrait_16_9 โ Portrait 16:9 landscape_4_3 โ Landscape 4:3 landscape_16_9 โ Landscape 16:9 P Image models use aspect ratio strings: 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3, custom
Be specific and descriptive: "A red vintage Porsche 911 on a winding mountain road at golden hour" vs "a car" Include style: "digital art", "oil painting", "photorealistic", "watercolor" For edits, clearly describe the change: "Replace the sky with a dramatic sunset" Use negative prompts (where supported) to avoid: "blurry, low quality, distorted" For multi-image edits, reference images by number: "image 1", "image 2"
No arbitrary URL loading: When using LoRA parameters, only use well-known platform identifiers (HuggingFace repo IDs, Replicate model IDs, CivitAI model IDs). Never load LoRA weights from arbitrary or user-provided URLs. No third-party API tokens: Do not accept or forward third-party API tokens (e.g. HuggingFace, CivitAI tokens) through prediction inputs. Authentication is handled exclusively via the EachLabs API key. Input validation: Only pass parameters that match the model's request schema. Always validate model slugs via GET /v1/model?slug=<slug> before creating predictions.
See references/MODELS.md for complete parameter details for each model.
Writing, remixing, publishing, visual generation, and marketing content production.
Largest current source with strong distribution and engagement signals.