AI Image Generation
Skill Verified ActiveGenerate AI images with GPT-Image-2, FLUX, Gemini, Grok, Seedream, Reve and 50+ models via inference.sh CLI. Models: GPT-Image-2, FLUX Dev LoRA, FLUX.2 Klein LoRA, Gemini 3 Pro Image, Grok Imagine, Seedream 4.5, Reve, ImagineArt. Capabilities: text-to-image, image-to-image, inpainting, LoRA, image editing, upscaling, text rendering. Use for: AI art, product mockups, concept art, social media graphics, marketing visuals, illustrations. Triggers: flux, image generation, ai image, text to image, stable diffusion, generate image, ai art, midjourney alternative, dall-e alternative, text2img, t2i, image generator, ai picture, create image with ai, generative ai, ai illustration, grok image, gemini image, gpt image, openai image, chatgpt image
Generate a wide variety of AI images for artistic, professional, or marketing purposes using a diverse set of advanced AI models through a single, convenient CLI interface.
Features
- Generate images with 50+ AI models
- Supports text-to-image, image-to-image, inpainting, LoRA, and editing
- Offers upscaling and text rendering capabilities
- Integrates with the inference.sh CLI (`belt`)
Use Cases
- Creating AI art and illustrations
- Generating product mockups and concept art
- Producing social media graphics and marketing visuals
- Experimenting with different AI image generation models
Non-Goals
- Directly embedding or managing AI models
- Providing a graphical user interface for image generation
- Replacing the inference.sh CLI itself
Workflow
- Login to the inference.sh CLI (`belt login`).
- Select an AI model and specify generation parameters (e.g., prompt, aspect ratio).
- Execute the image generation command using `belt app run`.
- Review the generated image output.
Prerequisites
- inference.sh CLI (`belt`) installed and logged in
Documentation
- info:Configuration & parameter referenceWhile the documentation lists models and examples, specific CLI parameters beyond the basic input structure are not explicitly documented with defaults, requiring users to refer to external inference.sh documentation.
Execution
- info:ValidationInput validation is handled by the `belt` CLI and the underlying inference.sh service, which is not explicitly detailed within the skill's markdown.
Code Execution
- info:Error HandlingError handling is primarily managed by the `belt` CLI and the inference.sh service. The skill's markdown does not detail specific error reporting or recovery steps.
Errors
- info:Actionable error messagesError messages would primarily come from the `belt` CLI or the inference.sh service. While the skill itself doesn't detail specific error paths, the underlying CLI is expected to provide them.
Practical Utility
- info:Edge casesWhile the skill lists many models and capabilities, specific edge cases, failure modes, or limitations of the inference.sh CLI within this skill's context are not explicitly documented.
Installation
npx skills add inferen-sh/skillsRuns the Vercel skills CLI (skills.sh) via npx — needs Node.js locally and at least one installed skills-compatible agent (Claude Code, Cursor, Codex, …). Assumes the repo follows the agentskills.io format.
Quality Score
VerifiedTrust Signals
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