OpenMontage/skills/creative/image-provider-usage.md

Image Provider Usage for OpenMontage

How to choose between image generation and stock providers, and how to use each effectively. Supplements the existing image-gen-usage.md (which covers FLUX prompting in depth).

Provider Landscape

Generation Providers (AI creates the image)

Tool	Provider	Cost	Speed	Best For
flux_image	FLUX 2 Pro via fal.ai	~$0.03-0.05	~5-10s	Photorealism, general purpose, workhorse
grok_image	Grok Imagine Image (xAI)	$0.02/output + $0.002/input edit image	~5-15s	Image edits, style transfer, multi-image compositing
openai_image	GPT Image 2 (OpenAI)	~$0.01-0.21	~5-15s	Complex instructions, text in images, multi-element
recraft_image	Recraft V4 via fal.ai	~$0.04-0.25	~5-10s	Logos, SVG vectors, brand assets, text rendering (see caveat below)
local_diffusion	Stable Diffusion (local)	Free	~30s+	Offline, privacy, free
image_gen	Multi (legacy, deprecated)	Varies	Varies	Deprecated — use image_selector or per-provider tools

Stock Providers (search and download existing images)

Tool	Provider	Cost	Speed	Best For
pexels_image	Pexels	Free	~2-5s	High-quality photography, color filtering
pixabay_image	Pixabay	Free	~2-5s	Large library, category filtering, illustrations

Selector

Tool	Purpose
image_selector	Routes to the best available provider based on preference and availability

Provider Selection by Scene Type

Scene Type	Primary Provider	Why	Fallback
Real-world photo (city, nature, people)	pexels_image	Real photos > AI for realism	pixabay_image → flux_image
Technical diagram	diagram_gen	Structured, editable	flux_image with diagram prompt
Abstract/conceptual illustration	flux_image	AI excels at custom concepts	openai_image
Style transfer / repaint of an existing image	grok_image	Native edit flow, strong promptable transforms	openai_image
Multi-image merge / composite	grok_image	Can combine multiple source images into one scene	openai_image
Logo or brand asset	recraft_image	SVG support, text accuracy	openai_image
Image with text/labels	openai_image	Best text rendering (GPT Image 2)	recraft_image
Complex multi-element composition	openai_image	Best instruction following	flux_image
Hero image (key visual)	flux_image	Highest visual quality	openai_image
Thumbnail	flux_image or recraft_image	Needs to be eye-catching	—
Budget/free project	pexels_image or pixabay_image	Free, immediate	local_diffusion
Offline/air-gapped	local_diffusion	No network needed	—

Provider-Specific Caveats

Recraft V4 via fal.ai

• style parameter causes 422 errors (as of 2026-04). The style enum values (digital_illustration, realistic_image, etc.) are rejected by fal.ai's Recraft V4 endpoint. Workaround: encode style direction in the prompt text instead (e.g. "digital illustration of a tooth cross-section" rather than style="digital_illustration"). The image_size and colors parameters work fine.
• Text rendering is unreliable for exact business names. Recraft (like all AI image models) may hallucinate wrong text. For any scene where text must be verbatim (CTA screens, business names, phone numbers), use Remotion text_card instead of generating an image with text.

Cost-Quality Tradeoff

PRODUCTION PATH: Premium
├── Hero images: flux_image ($0.05/img)
├── Supporting visuals: flux_image ($0.03/img)
├── Text overlays: openai_image ($0.05/img medium)
├── B-roll stills: pexels_image ($0.00)
└── Total for 10 images: ~$0.35

PRODUCTION PATH: Standard
├── All generated: flux_image ($0.03/img)
├── B-roll stills: pexels_image ($0.00)
└── Total for 10 images: ~$0.25

PRODUCTION PATH: Budget
├── All stock: pexels_image + pixabay_image ($0.00)
├── Diagrams: diagram_gen ($0.00)
└── Total: $0.00

PRODUCTION PATH: Offline
├── All generated: local_diffusion ($0.00)
├── Diagrams: diagram_gen ($0.00)
└── Total: $0.00 (but slower, lower quality)

Use generation_mode="edit" when the task starts from an existing image and should route only to edit-capable providers.

Using the Image Selector

For most cases, use image_selector and let it route:

# The selector finds the best available provider
result = image_selector.execute({
    "prompt": "aerial view of a modern data center",
    "preferred_provider": "auto",  # or "flux", "pexels", etc.
    "output_path": "assets/images/scene-3.png"
})

Override with preferred_provider when you know which provider is best for the scene type. Use allowed_providers to restrict to free or local options:

# Budget mode: only free providers
result = image_selector.execute({
    "prompt": "server room interior",
    "allowed_providers": ["pexels", "pixabay", "local_diffusion"],
    "output_path": "assets/images/scene-3.jpg"
})

Consistency Across Mixed Sources

When mixing stock and generated images in the same video, visual consistency is the challenge.

Strategy: Color Grade Everything

Apply the playbook's color grading LUT to both stock and generated images in the compose stage. This unifies the look. The color_grade enhancement tool handles this.

Strategy: Match The Visual Identity, Not A Copied Prefix

When generating images, adapt the playbook's mood, palette, texture, and medium into a short scene-specific anchor. When searching stock, filter for the same emotional and visual qualities: color, lighting, environment, composition, era, and texture. Use the playbook as a consistency source, not a script to paste.

Strategy: Avoid Mixing Styles Within a Scene

Don't use a stock photo for one element and an AI illustration for another in the same scene. Keep each scene internally consistent — all stock or all generated.