Introduction
For product managers and designers, creating polished visuals often requires more than a single AI output. Iterative image refinement lets you guide the process in multiple dialogue steps, adjusting details until the image fully meets your vision.
Why Iterative Refinement Matters
- Human Feedback Loop: Feed real observations back into the AI.
- Controlled Improvement: Make targeted changes without losing prior good elements.
Nano Banana API Overview
The Nano Banana API supports iterative image generation via conversational steps. Coupled with the Gemini refine image API, you can run multi-round image dialogue.
Base URL: https://wisdom-gate.juheapi.com/v1
Key models include wisdom-vision-gemini-2.5-flash-image, designed for rapid multi-step refinement.
Preparing Your Environment
- Get API Key from the official site: https://wisdom-gate.juheapi.com/studio/vision
- Tools: Ensure you have curl or API testing platform ready.
Step-by-Step Iterative Image Optimization
Step 1: Define Initial Parameters
Start with clear constraints: style, resolution, and target scene.
Step 2: Send First Generation Request
Call the model with your initial prompt.
Step 3: Review Output
Evaluate aspects like composition and clarity.
Step 4: Send Refinement Instructions
Feed back specific adjustments: e.g., "increase brightness", "add background details".
Step 5: Iterate Until Ready
Repeat until the image hits your quality bar.
Example API Call
curl --location --request POST 'https://wisdom-gate.juheapi.com/v1/chat/completions' \
--header 'Authorization: YOUR_API_KEY' \
--header 'Content-Type: application/json' \
--header 'Accept: */*' \
--header 'Host: wisdom-gate.juheapi.com' \
--header 'Connection: keep-alive' \
--data-raw '{
"model":"wisdom-vision-gemini-2.5-flash-image",
"messages": [
{
"role": "user",
"content": "Generate a futuristic city skyline at sunset."
}
]
}'
After the first image, adjust by sending another completion request with new content instructions.
Best Practices
- Keep refinement prompts short and explicit.
- Maintain conversation context between rounds.
- Avoid full resets unless the direction is wrong.
Comparing Iterative vs. One-Click
One-click generation gives instant outputs but often misses nuanced brand details. Iterative refinement invests more time but returns visuals closely aligned with requirements.
Case Study: A UX designer increased visual engagement by 23% after three refinement rounds on marketing banners.
Use Cases
- Marketing Imagery Polish: Achieve high-impact campaigns.
- UX Prototypes: Refined icons and UI shots.
- Product Listings: Crisp, appealing photos.
Conclusion
Iterative refinement leverages conversational AI to produce reliable, high-quality images. For PMs and designers, it’s a method that balances creative control with efficiency.