Website Generation Using Language Models

A method for generating a website, comprising:

• selecting website sections from a predefined section database based on a determined website type;
• generating, using a language model, keywords for image search by analyzing a website description;
• converting the keywords into vector embeddings;
• performing, based on the vector embeddings, a vector search in an image database to identify relevant images;
• ranking the relevant images based on similarity scoring between vector embeddings of the website description and embeddings of image textual descriptions;
• assembling the selected website sections and one or more of the ranked images into a hierarchical data structure;
• and
• rendering the hierarchical data structure in a web browser.

A system for generating a website, comprising:

• a memory subsystem;
• and
• processing circuitry, the processing circuitry configured to execute instructions stored in the memory subsystem to:
• select website sections from a predefined section database based on a determined website type;
• generate, using a language model, keywords for image search by analyzing a website description;
• convert the keywords into vector embeddings;
• perform, based on the vector embeddings, a vector search in an image database to identify relevant images;
• rank the relevant images based on similarity scoring between vector embeddings of the website description and embeddings of image textual descriptions;
• assemble the selected website sections and one or more of the ranked images into a hierarchical data structure;
• and
• render the hierarchical data structure in a web browser.

One or more non-transitory computer readable media storing instructions operable to cause one or more processors to perform operations for generating a website, the operations comprising:

• selecting website sections from a predefined section database based on a determined website type;
• generating, using a language model, keywords for image search by analyzing a website description;
• converting the keywords into vector embeddings;
• performing, based on the vector embeddings, a vector search in an image database to identify relevant images;
• ranking the relevant images based on similarity scoring between vector embeddings of the website description and embeddings of image textual descriptions;
• assembling the selected website sections and one or more of the ranked images into a hierarchical data structure;
• and
• rendering the hierarchical data structure in a web browser.