Design Document Generation from Text Prompts
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Solution Overview
Problem
Conventional methods for design generation are inefficient and often fail to fully embody the creator's intent due to manual editing processes and constraints of pre-selected templates.
Innovation Solution
A system and method for generating design documents from a text prompt, which includes encoding the prompt to produce an intent embedding, retrieving design templates based on similarity, and curating text and image assets using multiple generation models to create a cohesive design document.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual editing processes are used to create design documents, then creators can adjust and modify templates to match their intent, but the process is time-consuming and inefficient
Solution Approach 1:
The system enables self-service design document creation by automatically generating documents from text prompts using AI models. The design document generation apparatus autonomously encodes prompts, retrieves templates, generates images and text, and composes final documents without requiring manual editing, thus resolving the contradiction between alignment with intent and time consumption
Solution Approach 2:
The patent replaces the mechanical manual editing process with automated AI-based generation. The image generation model, text generation model, and document composer automatically perform tasks that previously required manual intervention, substituting human mechanical operations with automated computational processes to reduce time while maintaining quality
2Ease of manufacture
If pre-selected templates are used for design documents, then the creation process is simplified, but the documents may not fully embody the creator's intent
Solution Approach 1:
The system dynamically adapts templates based on the encoded prompt intent rather than using static pre-selected templates. The filtering component dynamically retrieves and selects templates that best match the specific creator intent, and the document composer dynamically assembles elements according to the generated content, enabling both ease of use and intent alignment
Solution Approach 2:
The system changes the parameters of template selection and document assembly based on the encoded prompt. By encoding the text prompt into an intent embedding and using it to filter and select templates, the system adapts the template parameters to match the creator's specific intent, resolving the contradiction between ease of manufacture and reliability
3Manufacturing precision
If multiple generation models are used to curate text and image assets, then the design document quality improves, but the system complexity increases
Solution Approach 1:
The patent segments the design document generation process into distinct functional components: an image generation model for creating images, a text generation model for generating text, a filtering component for selecting templates, and a document composer for assembling the final document. This segmentation allows each model to specialize in its specific task, improving overall quality while managing complexity through modular architecture
Solution Approach 2:
The design document generation apparatus integrates multiple generation models into a single unified system that handles both image and text generation, template filtering, and document composition. This multi-functional system resolves the contradiction by providing high-quality output through specialized models while presenting a simplified interface to users
4Productivity
If automatic design document generation is implemented, then efficiency improves, but the ability to fully capture creator intent becomes challenging
Solution Approach 1:
The patent introduces an intent embedding as an intermediary representation between the text prompt and the generation models. The encoding component transforms the text prompt into an intent embedding that captures the creator's intent, which then guides the template filtering and content generation processes, preserving intent information while enabling automatic generation
Solution Approach 2:
The filtering component uses the intent embedding to evaluate and filter templates, providing feedback on how well each template matches the creator's intent. This feedback mechanism ensures that the automatic generation process remains aligned with the creator's original intent while maintaining high efficiency through automated selection
Data Source
AI summary
A method, apparatus, non-transitory computer readable medium, and system for generating a design document from a text prompt include obtaining a design prompt that describes a document type and selecting a design template for the document type based on the design prompt. An image generation model generates an image for the design template based on the design prompt and a design document is generated based on the design template. The design document has the document type and includes the image at a location indicated by the design template.