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Image Generation

Text-to-image generation integrated directly into your pipelines.

Overview

PipeImgGen generates images from text prompts using state-of-the-art models. Generated images can be stored locally or in cloud storage with public or signed URLs. Image generation supports both text-to-image and image-to-image workflows.

Supported Models

Via Pipelex Gateway:

  • GPT-Image-1.5 — OpenAI's latest image generation model
  • GPT-Image-1 — OpenAI image generation
  • GPT-Image-1-mini — Smaller, faster variant for quick generations
  • FLUX-2-pro — Black Forest Labs' high-quality generation model
  • Nano Banana / Nano Banana Pro / Nano Banana 2 — Google Gemini-based image generation

Via direct provider SDKs:

  • OpenAI — Direct OpenAI API for GPT Image models
  • Google Gemini — Native Google image generation
  • fal — FLUX and other models via the fal platform
  • Hugging Face Inference — Open-source models like qwen-image
  • BlackboxAI — Via completions-based image generation
  • Azure REST — Azure-hosted image generation
  • OpenRouter — Multi-provider image generation access

Cloud Storage Integration

Generated images can be automatically uploaded to AWS S3 or Google Cloud Storage with configurable URL signing. See Cloud Storage for details.

Usage in Pipelines

Use PipeImgGen in your .mthds files to generate images as part of a pipeline. The operator accepts a text prompt (or an ImgGenPrompt concept) and outputs an Image concept. Model presets let you configure quality levels and default models in 2_img_gen_deck.toml.

See PipeImgGen reference.