Vision-Language Model Integration — Image & Text Understanding

I will integrate a vision-language model (GPT-4o, Claude 3.5 Sonnet with vision, or Gemini 1.5) into your application — enabling your system to understand and reason about images alongside text inputs, covering API integration, image encoding, prompt design for vision tasks, and a structured output extraction layer for image analysis results. Vision-language models accessed without proper image encoding optimisation (unnecessarily large images costing excessive tokens), prompt design for visual reasoning (structuring the text prompt to guide the model's visual attention), and output parsing (extracting structured data from the model's free-text analysis) consistently underperform their theoretical capability.

The integration covers image preprocessing and token-optimal encoding, prompt design for your visual task, API integration with vision inputs, structured output extraction, error handling, and a demonstration of the integration on your sample images.