Image Generator
Convert text descriptions into images with AI agents
Build a text-to-image system where an agent bridges the gap between what users say and what image models need. The agent interprets natural language descriptions, enriches them with visual detail, and iterates on generation until the output matches the user's intent.
Stack
Implementation
- 1
Build the prompt interpreter
Create an agent that takes conversational input like 'a cozy coffee shop at sunset' and translates it into a detailed image generation prompt with specific style, lighting, and composition directives.
- 2
Add iterative refinement
Use a vision model to evaluate generated images against the original description. The agent automatically regenerates with adjusted prompts when results don't match intent.
- 3
Implement style transfer
Allow users to specify style references — 'in the style of watercolor', 'like a vintage postcard'. The agent maps these to appropriate model parameters.
- 4
Add negative prompt generation
The agent automatically generates negative prompts to avoid common artifacts, quality issues, and unwanted elements based on the desired output.
- 5
Build the feedback loop
Let users provide natural language feedback on results — 'make it warmer', 'less busy background'. The agent adjusts prompts and regenerates.
What You Get
- Natural language to high-quality images without prompt engineering
- Iterative refinement produces results that match user intent
- Style control through conversational descriptions
- Continuous improvement through user feedback loop
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