Simpler version of my "Combined Workflow" that removes Stage 3 and 4 steps (resamplers, detailers, 4->16MP upscalers) in favor of a multi-model workflow that generates 4MP results.

This is a very simplified version of https://civarchive.com/models/2149956/ where I have removed a lot of nodes just to keep the simple initial generation and the initial upscaler (similar to running the much larger workflow without Stage 3 and 4). A lot of the details on usage are in the larger workflow and were not copied here, and a few notes might contain content that is just copied from the larger workflow)

0. Use the various toggle ↘️ to quick select (the arrows at the end of the selection will bring you to the node/subgraph directly).

1. Select a Model to generate an image with, adapts its parameters to match your setup.

2. Decide if you want to perform txt2img (enter a prompt and get an image) or img2img (use a prompt and a base image to generate a new image based on both). When using img2img make sure to provide an image, set the expected base image resolution (in MP) and set a denoise.

3. Decide if you want to write your prompt or use use an image and have QwenVL write a prompt (you can still add to the prompt in the main prompting area). When using QwenVL, load an image and select the preset for the type of response you need.

4. Decide if you want to use Qwen to optimize the final prompt before the image generation occurs. When doing so, decide on the type of prompt you want generated: tags, narrative or both.

5. Click "Run", the image generation will start with your selected parameters. Depending on the batch_size you will have a set of image generated. The final prompt is viewable. After the initial generation, a simple HiResFix will upscale the image to 4MP.

The extras add some other features from the original workflow:

• detailer: Stage3's detailers made generic detailer with manual mask (and drawing for inpainting) selection.

• detailer_sam3: Stage 3's detailers with automatic detection (SAM3 based) to automatically detail the mask found with the provided prompt.

• resampler: Stage3's Initial and Detailer resamplers.

• Flux_resampler: Stage3's Flus resampler.