Website Generation Using Language Models

1 - 20 . (canceled)

21 . 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.

22 . The method of claim 21 , further comprising:

generating an image using an image generation model in response to the vector search not identifying any relevant image having a similarity score above a predefined threshold.

23 . The method of claim 21 , wherein the image database comprises image embeddings that each include:

a first embedding representing a textual description of the image; and

a second embedding representing visual features of the image.

24 . The method of claim 21 , wherein selecting website sections comprises:

determining, using the language model, a website type based on the website description; and

selecting sections from the section database based on the determined website type.

25 . The method of claim 21 , further comprising:

generating, using the language model, search engine optimization metadata for at least one page based on the website description and user preferences.

26 . The method of claim 21 , wherein ranking the relevant images comprises:

computing a similarity score for each image based on both:

semantic similarity between the website description and the image textual description; and

visual coherence with the selected website sections.

27 . The method of claim 21 , further comprising:

analyzing the website description using the language model to extract explicit preferences for at least one of colors, fonts, or layout style.

28 . 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.

29 . The system of claim 28 , the processing circuitry further configured to execute instructions stored in the memory subsystem to:

apply a color palette and typography to the website, wherein the color palette is selected based on user preferences or industry standards, and wherein the typography is mapped to a font style consistent with the website type.

30 . The system of claim 28 , wherein, to assemble the selected website sections and ranked images, the processing circuitry configured to execute instructions stored in the memory subsystem to:

insert the images into sections based on contextual relevance; and

adjust element layout parameters to maintain compatibility with responsive design characteristics.

31 . The system of claim 28 , the processing circuitry further configured to execute instructions stored in the memory subsystem to:

present a preview of the rendered website via a web interface as the hierarchical data structure is updated.

32 . The system of claim 28 , wherein, to render the hierarchical data structure, the processing circuitry configured to execute instructions stored in the memory subsystem to:

generate a Document Object Model (DOM) based on the hierarchical data structure; and

display the DOM in a browser-compatible format.

33 . The system of claim 28 , wherein the hierarchical data structure comprises page objects representing pages of the website, section objects associated with the page objects, and element objects within each section object, each element object including styling and positioning metadata.

34 . The system of claim 28 , wherein, to perform the vector search, the processing circuitry configured to execute instructions stored in the memory subsystem to:

compute a vector similarity between the vector embeddings of the keywords and the image embeddings using a vector similarity search retrieval algorithm.

35 . The system of claim 28 , the processing circuitry further configured to execute instructions stored in the memory subsystem to:

filter the identified images based on one or more design constraints selected from image shape or dimensional characteristics.

36 . 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.

37 . The one or more non-transitory computer readable media of claim 36 , wherein generating the keywords comprises:

analyzing the website description to isolate descriptive phrases; and

mapping the descriptive phrases to keywords using few-shot prompt examples.

38 . The one or more non-transitory computer readable media of claim 36 , the operations further comprising:

updating the hierarchical data structure in response to a user modification to an image or section, wherein the website is rendered in real-time based on the updated data structure.

39 . The one or more non-transitory computer readable media of claim 36 , the operations further comprising:

generating an image using an image generation model in response to the vector search not identifying any relevant image having a similarity score above a predefined threshold.

40 . The one or more non-transitory computer readable media of claim 36 , wherein the image database comprises image embeddings that each include:

a first embedding representing a textual description of the image; and

a second embedding representing visual features of the image.