eachlabs-image-generation

name	eachlabs-image-generation
description	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.
metadata	{"author":"eachlabs","version":"1.0"}

EachLabs Image Generation

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.

Authentication

Header: X-API-Key: <your-api-key>

Set the EACHLABS_API_KEY environment variable. Get your key at eachlabs.ai.

Quick Start

1. Create a Prediction

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"
    }
  }'

2. Poll for Result

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.

Model Selection Guide

Text-to-Image

Model	Slug	Best For
Flux 2 Turbo	flux-2-turbo-text-to-image	Fast, high quality general purpose
Flux 2 Flash	flux-2-flash-text-to-image	Fastest Flux generation
Flux 2 Max	flux-2-max-text-to-image	Highest quality Flux
Flux 2 Klein 9B	flux-2-klein-9b-base-text-to-image	Balanced quality/speed
Flux 2 Pro	flux-2-pro	Pro quality
Flux 2 Flex	flux-2-flex	Flexible outputs
Flux 2 LoRA	flux-2-lora	LoRA-powered generation
XAI Grok Imagine	xai-grok-imagine-text-to-image	Creative and artistic
GPT Image v1.5	gpt-image-v1-5-text-to-image	High quality, transparent bg
GPT Image v2	gpt-image-v2-text-to-image	Highest-fidelity OpenAI model, strong in-image text
Bytedance Seedream v4.5	bytedance-seedream-v4-5-text-to-image	Bytedance latest
Gemini 3 Pro Image	gemini-3-pro-image-preview	Google's latest
Imagen 4	imagen4-preview	Google Imagen 4
Imagen 4 Fast	imagen-4-fast	Fast Google quality
Reve	reve-text-to-image	Artistic text-to-image
Hunyuan Image v3	hunyuan-image-v3-text-to-image	Tencent's latest
Ideogram V3 Turbo	ideogram-v3-turbo	Text in images
Minimax	minimax-text-to-image	High quality
Wan v2.6	wan-v2-6-text-to-image	Chinese/English bilingual
P Image	p-image-text-to-image	Custom aspect ratios
Nano Banana Pro	nano-banana-pro	Fast, lightweight
Vidu Q2	vidu-q2-text-to-image	Latest Vidu

Training

Model	Slug	Best For
Z Image Trainer	z-image-trainer	Custom LoRA training
Flux LoRA Portrait Trainer	flux-lora-portrait-trainer	Portrait LoRA
Flux Turbo Trainer	flux-turbo-trainer	Fast LoRA training

Prediction Flow

1. Check model GET https://api.eachlabs.ai/v1/model?slug=<slug> — validates the model exists and returns the request_schema with exact input parameters. Always do this before creating a prediction to ensure correct inputs.
2. POST https://api.eachlabs.ai/v1/prediction with model slug, version "0.0.1", and input parameters matching the schema
3. Poll GET https://api.eachlabs.ai/v1/prediction/{id} until status is "success" or "failed"
4. Extract the output image URL(s) from the response

Examples

Text-to-Image with Flux 2 Turbo

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"
    }
  }'

Text-to-Image with GPT Image v1.5

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"
    }
  }'

Text-to-Image with Imagen 4

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"
    }
  }'

Image Size Options

Most Flux 2 and Wan models use these presets:

• square_hd — Square, high definition
• square — Square, standard
• portrait_4_3 — Portrait 4:3
• portrait_16_9 — Portrait 16:9
• landscape_4_3 — Landscape 4:3
• landscape_16_9 — 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

Prompt Tips

• 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"

Security Constraints

• 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.

Parameter Reference

See references/MODELS.md for complete parameter details for each model.