image-generation-workflow-engine

license	Apache-2.0
name	image-generation-workflow-engine
description	Build image generation pipelines with Stable Diffusion, FLUX, ControlNet, LoRA, and ComfyUI workflows. Activate on: image generation pipeline, ComfyUI workflow, ControlNet, LoRA training, diffusion model. NOT for: video generation (ai-video-production-master), image classification (computer-vision-pipeline).
allowed-tools	Read,Write,Edit,Bash(python:*,pip:*,npm:*,npx:*)
category	AI & Machine Learning
tags	["image-generation","stable-diffusion","flux","comfyui","lora"]
pairs-with	[{"skill":"ai-video-production-master","reason":"Generated images serve as keyframes and style references for video pipelines"},{"skill":"computer-vision-pipeline","reason":"CV preprocessing (segmentation, depth) feeds ControlNet conditioning"},{"skill":"multimodal-embedding-generator","reason":"CLIP/SigLIP embeddings guide generation and enable style search"}]

Image Generation Workflow Engine

Build production image generation pipelines with FLUX, Stable Diffusion 3.5, ControlNet, LoRA, and ComfyUI for automated creative workflows.

Activation Triggers

Activate on: "image generation pipeline", "ComfyUI workflow", "ControlNet conditioning", "LoRA training", "FLUX generation", "Stable Diffusion pipeline", "batch image generation", "img2img workflow", "inpainting pipeline"

NOT for: Video generation from images (ai-video-production-master), image classification or object detection (computer-vision-pipeline), or multimodal search embeddings (multimodal-embedding-generator)

Quick Start

1. Choose model — FLUX.1-dev for quality, FLUX.1-schnell for speed, SD 3.5 for ControlNet ecosystem, SDXL for LoRA abundance.
2. Design workflow — Text-to-image (simplest), img2img (style transfer), ControlNet (structural guidance), inpainting (targeted edits).
3. Build pipeline — ComfyUI for visual node graphs, diffusers library for code-first, or API services (Replicate, fal.ai) for managed.
4. Add conditioning — ControlNet (canny, depth, pose), IP-Adapter (style transfer), LoRA (fine-tuned concepts).
5. Automate — Batch generation with parameter sweeps, quality filtering, and output organization.

Core Capabilities

Domain	Technologies	Notes
Models	FLUX.1-dev/schnell, SD 3.5, SDXL, Kandinsky 3	FLUX is 2025-2026 standard for quality
Conditioning	ControlNet (canny, depth, pose, segmentation), IP-Adapter	Structural and style guidance
Fine-Tuning	LoRA, DreamBooth, textual inversion	Custom concepts in 20 min on consumer GPU
Workflows	ComfyUI, diffusers (Python), A1111	ComfyUI for complex multi-step; diffusers for code
APIs	Replicate, fal.ai, Together AI, HF Inference	Managed GPU, pay-per-image
Local	qwen-image-mps (Apple Silicon), CUDA, ROCm	M4 Max: FLUX.1-schnell in 4-8 sec/image

Architecture Patterns

Pattern 1: ComfyUI Production Pipeline

[Load Checkpoint] ──→ [CLIP Text Encode] ──→ [KSampler] ──→ [VAE Decode] ──→ [Save Image]
       │                      │                    │
   FLUX.1-dev          positive + negative     steps: 20-30
   or SD 3.5           prompts with weights    cfg: 3.5-7.5
                                                scheduler: euler
                                                    │
                                    [ControlNet Apply] (optional)
                                           │
                                    canny/depth/pose
                                    from reference image