Initial release — OpenMontage: the first open-source agentic video production system
11 production pipelines, 47 tools, 124 agent skills. Supports cloud APIs (fal.ai, OpenAI, ElevenLabs, Suno, HeyGen, Runway) and free local providers (diffusers, Piper TTS, WAN 2.1, Hunyuan, CogVideo). Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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# Image Provider Usage for OpenMontage
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> How to choose between image generation and stock providers, and how to use each effectively.
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> Supplements the existing `image-gen-usage.md` (which covers FLUX prompting in depth).
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## Provider Landscape
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### Generation Providers (AI creates the image)
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| Tool | Provider | Cost | Speed | Best For |
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|------|----------|------|-------|----------|
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| `flux_image` | FLUX 2 Pro via fal.ai | ~$0.03-0.05 | ~5-10s | Photorealism, general purpose, workhorse |
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| `openai_image` | GPT Image 1 (OpenAI) | ~$0.01-0.17 | ~5-15s | Complex instructions, text in images, multi-element |
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| `recraft_image` | Recraft V4 via fal.ai | ~$0.04-0.25 | ~5-10s | Logos, SVG vectors, brand assets, text rendering |
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| `local_diffusion` | Stable Diffusion (local) | Free | ~30s+ | Offline, privacy, free |
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| `image_gen` | Multi (legacy, deprecated) | Varies | Varies | **Deprecated** — use `image_selector` or per-provider tools |
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### Stock Providers (search and download existing images)
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| Tool | Provider | Cost | Speed | Best For |
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|------|----------|------|-------|----------|
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| `pexels_image` | Pexels | Free | ~2-5s | High-quality photography, color filtering |
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| `pixabay_image` | Pixabay | Free | ~2-5s | Large library, category filtering, illustrations |
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### Selector
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| Tool | Purpose |
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|------|---------|
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| `image_selector` | Routes to the best available provider based on preference and availability |
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## Provider Selection by Scene Type
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| Scene Type | Primary Provider | Why | Fallback |
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|-----------|-----------------|-----|----------|
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| **Real-world photo** (city, nature, people) | `pexels_image` | Real photos > AI for realism | `pixabay_image` → `flux_image` |
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| **Technical diagram** | `diagram_gen` | Structured, editable | `flux_image` with diagram prompt |
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| **Abstract/conceptual illustration** | `flux_image` | AI excels at custom concepts | `openai_image` |
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| **Logo or brand asset** | `recraft_image` | SVG support, text accuracy | `openai_image` |
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| **Image with text/labels** | `openai_image` | Best text rendering (GPT Image 1) | `recraft_image` |
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| **Complex multi-element composition** | `openai_image` | Best instruction following | `flux_image` |
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| **Hero image (key visual)** | `flux_image` | Highest visual quality | `openai_image` |
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| **Thumbnail** | `flux_image` or `recraft_image` | Needs to be eye-catching | — |
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| **Budget/free project** | `pexels_image` or `pixabay_image` | Free, immediate | `local_diffusion` |
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| **Offline/air-gapped** | `local_diffusion` | No network needed | — |
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## Cost-Quality Tradeoff
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```
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PRODUCTION PATH: Premium
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├── Hero images: flux_image ($0.05/img)
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├── Supporting visuals: flux_image ($0.03/img)
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├── Text overlays: openai_image ($0.04/img)
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├── B-roll stills: pexels_image ($0.00)
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└── Total for 10 images: ~$0.35
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PRODUCTION PATH: Standard
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├── All generated: flux_image ($0.03/img)
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├── B-roll stills: pexels_image ($0.00)
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└── Total for 10 images: ~$0.25
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PRODUCTION PATH: Budget
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├── All stock: pexels_image + pixabay_image ($0.00)
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├── Diagrams: diagram_gen ($0.00)
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└── Total: $0.00
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PRODUCTION PATH: Offline
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├── All generated: local_diffusion ($0.00)
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├── Diagrams: diagram_gen ($0.00)
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└── Total: $0.00 (but slower, lower quality)
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```
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## Using the Image Selector
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For most cases, use `image_selector` and let it route:
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```python
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# The selector finds the best available provider
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result = image_selector.execute({
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"prompt": "aerial view of a modern data center",
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"preferred_provider": "auto", # or "flux", "pexels", etc.
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"output_path": "assets/images/scene-3.png"
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})
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```
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Override with `preferred_provider` when you know which provider is best for the scene type.
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Use `allowed_providers` to restrict to free or local options:
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```python
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# Budget mode: only free providers
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result = image_selector.execute({
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"prompt": "server room interior",
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"allowed_providers": ["pexels", "pixabay", "local_diffusion"],
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"output_path": "assets/images/scene-3.jpg"
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})
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```
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## Consistency Across Mixed Sources
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When mixing stock and generated images in the same video, visual consistency is the challenge.
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### Strategy: Color Grade Everything
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Apply the playbook's color grading LUT to both stock and generated images in the compose stage.
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This unifies the look. The `color_grade` enhancement tool handles this.
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### Strategy: Match Playbook Style in Prompts
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When generating images, always prepend the playbook's `image_prompt_prefix`. When searching stock,
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use the playbook's color names in search filters (Pexels supports color filtering).
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### Strategy: Avoid Mixing Styles Within a Scene
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Don't use a stock photo for one element and an AI illustration for another in the same scene.
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Keep each scene internally consistent — all stock or all generated.
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