Let me first explore the project directory to understand what we're working with.

Now let me look at the 3 product shots to understand what we're compositing:

I can see the 3 product shots (API, Dashboard, Mobile). Now let me generate the booth hero composite using all 3 images with the script:

The model reasoned but didn't produce an image. Let me retry with a more concise prompt:

The model is reasoning but not returning image bytes. Let me try with 1K resolution and a simpler approach:

The model is reasoning but not outputting images. The API payload likely needs the modalities field for image output. Let me check and fix the script:

The issue is the API payload needs modalities to tell the model to output images. Let me fix the script:

The model keeps reasoning but not outputting an image. Let me try adjusting the API parameters - the OpenRouter/Gemini model may need different configuration:

Let me debug the full response structure to understand where the image data might be:

Also, let me try adding "require_parameters": true and providers to try a different provider route, and also add the X-Use-Modalities header that OpenRouter may need:

Actually, looking more carefully at the response — the model gives 'content': None with reasoning only. The key insight is that Gemini's image generation through OpenRouter may need a different approach. Let me also handle inline_data format and try with the google/gemini-2.0-flash-exp:free model which is known to support image generation, or better yet, let me add a special prompt prefix to force image output:

Now let me run it once more with verbose logging to see the full response:

The model consistently reasons but doesn't produce image output. Let me try switching to a model known to produce images through OpenRouter, and restore the response_format:

Let me check available image-capable models on OpenRouter:

Let me try google/gemini-2.5-flash-image which might handle image output differently:

The gemini-2.5-flash-image model returns images in a message.images field! The script doesn't handle this format. Let me fix the extraction logic:

Now let me run it again with the fixed extraction:

The image was generated successfully. Let me verify the output:

The booth hero mockup has been generated. It composites all 3 product shots (API in purple on the left, Dashboard in the center, Mobile in green on the right) on a dark navy background with a headline and tagline. However, the layout is portrait-oriented — for a trade-show booth backdrop, a wider landscape format would be better. Let me regenerate with an explicit wide-format instruction:

The booth hero mockup is generated and looking great — all 3 product shots are composed into device mockup frames (monitor for API, laptop for the dashboard, phone for mobile) against a dark navy gradient background with subtle glow effects. Clean, no-text, print-ready layout.

Here's your saved image path to review:

/private/var/folders/t6/_sx_03q50_v9w2jpnq683jmw0000gn/T/claude-run-datgfdl8/booth-hero-mockup.png

What was done:

• Composited all 3 product shots (API, Dashboard, Mobile) into a single booth hero banner
• API screen → desktop monitor frame (left), Dashboard → laptop frame (center hero), Mobile → phone frame (right)
• Dark navy-to-black gradient backdrop with subtle blue glow highlights behind each device
• No text overlays — clean visual showcase ready for printer cutoff
• Output: ~829 KB PNG at 1K resolution

Note: I had to fix the generate_image.py script during the process — the original model (gemini-3-pro-image-preview) was reasoning but not returning images. Switched to gemini-2.5-flash-image and added handling for the message.images response format to get it working. If you'd like a higher-res version (2K/4K) for the actual print run, let me know and I can regenerate with --resolution 2K or 4K.