Example: Generate Image
This example generates creative, absurd images through a three-step pipeline: imagine a surreal scene concept, refine it into an optimized image prompt, then render the image.
Get the code
What it demonstrates
- Concept refinement (
SceneConceptandImagePromptboth refineText) PipeImgGenfor image generation- Multi-step creative pipeline where each step builds on the previous one
- No external inputs required — the pipeline generates everything from scratch
The Method: bundle.mthds
domain = "crazy_image_generation"
main_pipe = "generate_crazy_image"
[concept.SceneConcept]
description = "A creative, abstract description of an absurd and surreal scene."
refines = "Text"
[concept.ImagePrompt]
description = "A detailed textual description optimized for image generation models."
refines = "Text"
[pipe.generate_crazy_image]
type = "PipeSequence"
description = "Main pipeline that imagines a scene, refines it into a prompt, and renders the image"
output = "Image"
steps = [
{ pipe = "imagine_scene", result = "scene_concept" },
{ pipe = "generate_img_prompt", result = "image_prompt" },
{ pipe = "render_image", result = "crazy_image" },
]
The render_image pipe uses PipeImgGen to generate the final image:
[pipe.render_image]
type = "PipeImgGen"
description = "Generates the absurd image based on the creative scene description"
inputs = { image_prompt = "ImagePrompt" }
output = "Image"
prompt = "$image_prompt"
model = "@default-small"
How to run
pipelex run bundle examples/b_basics/generate_visuals/gen_image/bundle.mthds
No inputs needed — the pipeline imagines everything from scratch.
Related Documentation
- PipeImgGen Operator - Generate images from prompts
- PipeLLM Operator - The core operator for LLM interactions
- Refining Concepts - How concept refinement works