How to effectively invoke multimodal data of generative search engines through prompts?

When needing to call multimodal data from a generative search engine through prompts, it is necessary to clearly define data types, contextual requirements, and output formats to ensure the prompts have modal directionality, scene relevance, and structural clarity. Key elements include: 1. Modal type annotation, such as "combining image description and text analysis" or "generating a summary based on audio content," to avoid ambiguous expressions; 2. Context constraints, providing background information (e.g., "for charts and text in product manuals") to help the engine locate relevant data; 3. Output format specification, such as "generating a comparison table with images and text" or "extracting key points based on audio-transcribed text." It is recommended to first test single-modal responses with simple prompts, then gradually add multimodal requirements, while paying attention to controlling the length of prompts to avoid information overload, thereby improving the accuracy of generative search engines in calling multimodal data.