Granted Patent B2

US 12,602,412 · App. 19/306,379 · Granted Apr 14, 2026

Inventors: Vijay Madisetti (Alpharetta, GA); Arshdeep Bahga (Chandigarh, IN)

Assignee: Vijay Madisetti

G06F16/3329G06F40/284

Abstract

Claims (99)

1 . A method of processing domain-specific content in a generative artificial intelligence system, comprising:

receiving a prompt from a user;

generating a tokenized prompt by performing an initial tokenization of the prompt;

identifying an identified domain comprised by a plurality of supported domains that is associated with the tokenized prompt by analyzing the tokenized prompt;

identifying one or more domain-specific functions within the identified domain by performing a domain-specific analysis on the tokenized prompt;

generating a plurality of domain-specific sub-functions from the one or more domain-specific functions according to a hierarchical mapping of the identified domain;

generating a plurality of hierarchical tokens (H-Tokens), each H-Token of the plurality of H-Tokens being configured to encapsulate one of a domain-specific function of the one or more domain-specific functions or a domain-specific sub-function of the plurality of domain-specific sub-functions, and relationships between the one or more domain-specific functions and the plurality of domain-specific sub-functions;

implementing the plurality of H-Tokens, resulting in an implemented plurality of H-Tokens, by mapping each H-Token of the plurality of H-Tokens to each of a corresponding function, event, and implementation method within the identified domain;

assembling a response using the implemented plurality of H-Tokens; and

transmitting the response to the user.

2 . The method of claim 1 , wherein implementing the plurality H-Tokens comprises:

identifying a plurality of functions as one of domain-specific tasks that lead to events or domain-specific processes that lead to events;

identifying a plurality of events as results of the plurality of functions; and

identifying a plurality of implementation methods to accomplish the plurality of functions.

3 . The method of claim 2 wherein each implementation method of the plurality of implementation methods is represented as an H-Token.

4 . The method of claim 1 , further comprising:

assembling a context using the implemented plurality of H-Tokens;

selecting a processing path from one of:

expanding the plurality H-Tokens into regular tokens for processing; or

generating processed content by directly processing the plurality of H-Tokens without expansion;

generating a processed context by processing the context consistent with the processing path; and

integrating the processed context into the response.

5 . The method of claim 1 , further comprising integrating the implemented plurality of H-Tokens with a retrieval-augmented generation (RAG) system by:

assembling an H-Token context comprising at least one of a location context, a duration context, and a preference context;

generating a processed context by processing the H-Token context through one of:

a token expansion path operable to expand the plurality of H-Tokens to regular tokens for traditional RAG processing; or

a direct H-Token processing path for H-Token-aware response generation; and

producing the response based on the processed context.

6 . The method of claim 1 wherein assembling the response using the implemented plurality of H-Tokens comprises:

assembling the implemented plurality of H-Tokens;

forming a preliminary response responsive to assembling the implemented plurality of H-Tokens; and

generating the response by performing a quality verification on the preliminary response.

7 . A system for processing domain-specific content in a generative artificial intelligence system, comprising:

a processor;

a network communication device operably coupled to the processor and configured to transmit and receive digital transmissions across a network to removed computerized devices; and

a non-transitory computer-readable storage medium having stored thereon software that, when executed by the processor, is configured to:

receive a prompt from a user;

generate a tokenized prompt by performing an initial tokenization of the prompt;

identify an identified domain comprised by a plurality of supported domains that is associated with the tokenized prompt by analyzing the tokenized prompt;

identify one or more domain-specific functions within the identified domain by performing a domain-specific analysis on the tokenized prompt;

generate a plurality of domain-specific sub-functions from the one or more domain-specific functions according to a hierarchical mapping of the identified domain;

generate a plurality of hierarchical tokens (H-Tokens), each H-Token of the plurality of H-Tokens being configured to encapsulate one of a domain-specific function of the one or more domain-specific functions or a domain-specific sub-function of the plurality of domain-specific sub-functions, and relationships between the one or more domain-specific functions and the plurality of domain-specific sub-functions;

implement the plurality of H-Tokens, resulting in an implemented plurality of H-Tokens, by mapping each H-Token of the plurality of H-Tokens to each of a corresponding function, event, and implementation method within the identified domain;

assemble a response using the implemented plurality of H-Tokens; and

transmit the response to the user.

8 . The system of claim 7 , wherein the software, when executed by the processor, is operable to implement the plurality H-Tokens by:

identifying a plurality of functions as one of domain-specific tasks that lead to events or domain-specific processes that lead to events;

identifying a plurality of events as results of the plurality of functions; and

identifying a plurality of implementation methods to accomplish the plurality of functions.

9 . The system of claim 8 wherein each implementation method of the plurality of implementation methods is represented as an H-Token.

10 . The system of claim 7 , wherein the software, when executed by the processor, is further operable to:

assemble a context using the implemented plurality of H-Tokens;

select a processing path from one of:

expand the plurality H-Tokens into regular tokens for processing; or

generate processed content by directly processing the plurality of H-Tokens without expansion;

generate a processed context by processing the context consistent with the processing path; and

integrate the processed context into the response.

11 . The system of claim 7 wherein the software, when executed by the processor, is further operable to integrate the implemented plurality of H-Tokens with a retrieval-augmented generation (RAG) system by:

assembling an H-Token context comprising at least one of a location context, a duration context, and a preference context;

generating a processed context by processing the H-Token context through one of:

a token expansion path operable to expand the plurality of H-Tokens to regular tokens for traditional RAG processing; or

a direct H-token processing path for H-Token-aware response generation; and

producing the response based on the processed context.

12 . The system of claim 7 wherein the software, when executed by the processor, is operable to assemble the response using the implemented plurality of H-Tokens by:

assembling the implemented plurality of H-Tokens;

forming a preliminary response responsive to assembling the implemented plurality of H-Tokens; and

generating the response by performing a quality verification on the preliminary response.

13 . A system for processing domain-specific content in a generative artificial intelligence system, comprising:

means for receiving a prompt from a user;

means for generating a tokenized prompt by performing an initial tokenization of the prompt;

means for identifying an identified domain comprised by a plurality of supported domains that is associated with the tokenized prompt by analyzing the tokenized prompt;

means for identifying one or more domain-specific functions within the identified domain by performing a domain-specific analysis on the tokenized prompt;

means for generating a plurality of domain-specific sub-functions from the one or more domain-specific functions according to a hierarchical mapping of the identified domain;

means for generating a plurality of hierarchical tokens (H-Tokens), each H-Token of the plurality of H-Tokens being configured to encapsulate one of a domain-specific function of the one or more domain-specific functions or a domain-specific sub-function of the plurality of domain-specific sub-functions, and relationships between the one or more domain-specific functions and the plurality of domain-specific sub-functions;

means for implementing the plurality of H-Tokens, resulting in an implemented plurality of H-Tokens, by mapping each H-Token of the plurality of H-Tokens to each of a corresponding function, event, and implementation method within the identified domain;

means for assembling a response using the implemented plurality of H-Tokens; and

means for transmitting the response to the user.

14 . The system of claim 13 , wherein the means for implementing the plurality H-Tokens is operable to:

identify a plurality of functions as one of domain-specific tasks that lead to events or domain-specific processes that lead to events;

identify a plurality of events as results of the plurality of functions; and

identify a plurality of implementation methods to accomplish the plurality of functions.

15 . The system of claim 14 wherein each implementation method of the plurality of implementation methods is represented as an H-Token.

16 . The system of claim 13 , further comprising:

means for assembling a context using the implemented plurality of H-Tokens;

means for selecting a processing path from one of:

expanding the plurality H-Tokens into regular tokens for processing; or

generating processed content by directly processing the plurality of H-Tokens without expansion;

means for generating a processed context by processing the context consistent with the processing path; and

means for integrating the processed context into the response.

17 . The system of claim 13 , further comprising means for integrating the implemented plurality of H-Tokens with a retrieval-augmented generation (RAG) system by:

assembling an H-Token context comprising at least one of a location context, a duration context, and a preference context;

generating a processed context by processing the H-Token context through one of:

a token expansion path operable to expand the plurality of H-Tokens to regular tokens for traditional RAG processing; or

a direct H-token processing path for H-Token-aware response generation; and

producing the response based on the processed context.

18 . The system of claim 13 wherein the means for assembling the response using the implemented plurality of H-Tokens is operable to:

assemble the implemented plurality of H-Tokens;

form a preliminary response responsive to assembling the implemented plurality of H-Tokens; and

generate the response by performing a quality verification on the preliminary response.

Assignments (1)

Continuity (18)

References Cited (17)