# US 12,332,965 B1 · Website personalization and interactive assistant > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,332,965 B1 - Document ID: US12332965B1 - Status: Granted - Kind: B1 - Application number: 18/783,421 - Filed: 2024-07-25 - Published: 2025-06-19 - Granted: 2025-06-17 - Earliest claimed: 2023-12-15 - Assignees: Typeface Inc. - Applicants: Typeface Inc. - Inventors: Abhay Parasnis; Vishal Sood; Hari Krishna; Kishore Battula - Web page: https://patentgrep.com/patent/US12332965B1 ## CPC - G06T 11/60: Creating or editing images; Combining images with text - G06F 16/9577: {Optimising the visualization of content, e.g. distillation of HTML documents} - G06Q 30/0242: Determining effectiveness of advertisements - G06Q 30/0271: {Personalized advertisement} - G06Q 30/0276: {Advertisement creation} - G06T 2200/24: involving graphical user interfaces [GUIs] - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR ## Abstract Methods, systems, and computer programs are presented to provide a personalized view of webpages and an interactive assistant for exploring website content. One method includes operations for accessing website data of a website, and detecting a request entered by a user in a user interface (UI). One or more blocks for a webpage are generated in response to the request, where generating each block includes constructing a prompt by entering website data, user information, and block information on a prompt template; providing the prompt as input to a Generative Artificial Intelligence (GAI) tool; and utilizing the response from the GAI tool to build the block for the webpage. The method further includes causing presentation on the UI of the webpage including the generated one or more blocks. ## Claims ### Claim 1 A computer-implemented method comprising: accessing website data of a website; detecting a request entered by a user in a user interface (UI) for a webpage in the website; generating one or more blocks for the webpage in response to the request, wherein generating each block comprises: constructing a prompt based on the website data, user information, block information, and a prompt template, the prompt comprising descriptive text for desired results, the prompt template including fillable fields, wherein constructing the prompt comprises filling the fillable fields with information based on the website data and the user information; providing the prompt, comprising website data, user information, and block information, as input to a Generative Artificial Intelligence (GAI) tool; utilizing the response from the GAI tool to build the block for the webpage; and adding the block built by the GAI tool to the webpage; and causing presentation on the UI of the webpage including the generated one or more blocks. ### Claim 2 (depends on 1) The method as recited in claim 1, wherein accessing the website data further comprises: obtaining product information from the website; identifying blocks of pages in the website; and retrieving one or more entity tags for each block, wherein the website data comprises the product information, the identified blocks of pages in the website, and the one or more entity tags for each block. ### Claim 3 (depends on 1) The method as recited in claim 1, wherein accessing the website data further comprises: generating semantic embeddings for blocks in the webpages of the website. ### Claim 4 (depends on 3) The method as recited in claim 3, wherein the block is an image block for an image, wherein generating the semantic embeddings for the image block comprises: extracting captions from the image; extracting a description of the image; obtaining alt-text for the image; obtaining one or more bounding boxes for the image; and generating the semantic embedding for the image block based on the captions, the description, the alt-text, and the one or more bounding boxes. ### Claim 5 (depends on 3) The method as recited in claim 3, wherein generating the one or more blocks further comprises: generating a request embedding for the request; and selecting the one or more blocks with the semantic embeddings closest to the request embedding. ### Claim 6 (depends on 1) The method as recited in claim 1, further comprising: providing an interactive assistant on the webpage in the UI, wherein the request is entered in the interactive assistant. ### Claim 7 (depends on 6) The method as recited in claim 6, further comprising: creating a prompt based on the request and the user information; providing the prompt as input to a Large Language Model (LLM); and presenting the response from the LLM in the interactive assistant. ### Claim 8 (depends on 1) The method as recited in claim 1, wherein the one or more blocks comprise an image block, wherein the GAI tool is an image-generation tool. ### Claim 9 (depends on 1) The method as recited in claim 1, wherein the one or more blocks comprise at least one image block and at least one text block. ### Claim 10 (depends on 1) The method as recited in claim 1, further comprising: after accessing the website data, performing incremental training for a Large Language Model (LLM) with text data from the website data. ### Claim 11 A system comprising: a memory comprising instructions; and one or more computer processors, wherein the instructions, when executed by the one or more computer processors, cause the system to perform operations comprising: accessing website data of a website; detecting a request entered by a user in a user interface (UI) for a webpage in the website; generating one or more blocks for the webpage in response to the request, wherein generating each block comprises: constructing a prompt based on the website data, user information, block information, and a prompt template, the prompt comprising descriptive text for desired results, the prompt template including fillable fields, wherein constructing the prompt comprises filling the fillable fields with information based on the website data and the user information; providing the prompt, comprising website data, user information, and block information, as input to a Generative Artificial Intelligence (GAI) tool; utilizing the response from the GAI tool to build the block for the webpage; and adding the block built by the GAI tool to the webpage; and causing presentation on the UI of the webpage including the generated one or more blocks. ### Claim 12 (depends on 11) The system as recited in claim 11, wherein accessing the website data further comprises: obtaining product information from the website; identifying blocks of pages in the website; and retrieving one or more entity tags for each block, wherein the website data comprises the product information, the identified blocks of pages in the website, and the one or more entity tags for each block. ### Claim 13 (depends on 11) The system as recited in claim 11, wherein accessing the website data further comprises: generating semantic embeddings for blocks in the webpages of the website. ### Claim 14 (depends on 13) The system as recited in claim 13, wherein the block is an image block for an image, wherein generating the semantic embeddings for the image block comprises: extracting captions from the image; extracting a description of the image; obtaining alt-text for the image; obtaining one or more bounding boxes for the image; and generating the semantic embedding for the image block based on the captions, the description, the alt-text, and the one or more bounding boxes. ### Claim 15 (depends on 13) The system as recited in claim 13, wherein generating the one or more blocks further comprises: generating a request embedding for the request; and selecting the one or more blocks with the semantic embeddings closest to the request embedding. ### Claim 16 A non-transitory machine-readable storage medium including instructions that, when executed by a machine, cause the machine to perform operations comprising: accessing website data of a website; detecting a request entered by a user in a user interface (UI) for a webpage in the website; generating one or more blocks for the webpage in response to the request, wherein generating each block comprises: constructing a prompt based on the website data, user information, block information, and a prompt template, the prompt comprising descriptive text for desired results, the prompt template including fillable fields, wherein constructing the prompt comprises filling the fillable fields with information based on the website data and the user information; providing the prompt, comprising website data, user information, and block information, as input to a Generative Artificial Intelligence (GAI) tool; utilizing the response from the GAI tool to build the block for the webpage; and adding the block built by the GAI tool to the webpage; and causing presentation on the UI of the webpage including the generated one or more blocks. ### Claim 17 (depends on 16) The non-transitory machine-readable storage medium as recited in claim 16, wherein accessing the website data further comprises: obtaining product information from the website; identifying blocks of pages in the website; and retrieving one or more entity tags for each block, wherein the website data comprises the product information, the identified blocks of pages in the website, and the one or more entity tags for each block. ### Claim 18 (depends on 16) The non-transitory machine-readable storage medium as recited in claim 16, wherein accessing the website data further comprises: generating semantic embeddings for blocks in the webpages of the website. ### Claim 19 (depends on 18) The non-transitory machine-readable storage medium as recited in claim 18, wherein the block is an image block for an image, wherein generating the semantic embeddings for the image block comprises: extracting captions from the image; extracting a description of the image; obtaining alt-text for the image; obtaining one or more bounding boxes for the image; and generating the semantic embedding for the image block based on the captions, the description, the alt-text, and the one or more bounding boxes. ### Claim 20 (depends on 18) The non-transitory machine-readable storage medium as recited in claim 18, wherein generating the one or more blocks further comprises: generating a request embedding for the request, and selecting the one or more blocks with the semantic embeddings closest to the request embedding.