DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This Office Action is in response to the claim amendment filed on June 4, 2026 and wherein claims 1, 16, 20 amended.
In virtue of this communication, claims 1-20 are currently pending in this Office Action.
With respect to the Examiner Comment to claim 20, the claim amendment and argument, see paragraph 5 of page 6 in Remarks filed on June 4, 2026, have been fully considered and the argument found persuasive. Therefore, the Examiner Amendment as to claim 20 has been withdrawn.
The Office appreciates the explanation of the amendment and analyses of the prior arts, and however, although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993) and MPEP 2145.
Specification
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action
About the claimed “transmitting … novel text formatting information to the client machine via the communication interface”, “novel text passage”, etc., applicant presented application figures 21, 22 and figures 9 through 10B, etc., see paragraph 3 of page 6 in Remarks filed on June 4, 2026 and further amendment claims as such “(transmitting the novel text passage …) such that the client machine is provided with … formatting information identifying a presentation configuration native to the communication channel of the client machine”.
In response to the argument above, the Office respectfully disagrees because figure 22 as referred by applicant in Remarks above, merely disclosed “transmit the formatted text via the communication channel (2216)” after “determine a formatted response portion based on the text portion and the configuration information (2212)” in fig. 22 (para 247-249, USPGPub 20250272501 A1 hereinafter), and “store the presentation configuration information (2112)” in fig. 21 (para 254-256) and other findings, according to figs. 9-10B as indicated by applicant, read “a natural language response requesting additional user input may be transmitted at 616 (para 116)”, “the response is transmitted via the communication channel at 514 (para 90)”, “Alternatively, or additionally, updating the database system may involve transmitting a response to a client machine (para 137)”, “An instruction to update the conversational chat interface to include the action recommendation is transmitted to the client machine at 1812. In some embodiments, the instruction may identify the action to present in the conversational chat interface. For instance, the action may be presented as a button, a drop-down menu, or another user interface affordance. The nature of the instruction may depend in significant part on the conversation channel in which the conversational chat interface is being presented (para 225)”, “FIG. 22 illustrates a method 2200 for transmitting a natural language response generated by a conversational chat assistant, performed in accordance with one or more embodiments (para 248)”, “A communication channel for transmitting the text is identified at 2208 (para 253)”, “Upon determining not to identify an additional response portion, the formatted text is transmitted at 2216 via the communication channel (para 256)”, “The presentation configuration information is stored at 2112. The stored presentation configuration information may then be used to format the presentation of information output via a conversational chat interface. Examples of such formatting are shown throughout the application, for instance in FIG. 23A and FIG. 23B”, but none of them would be considered as the support(s) to the claimed limitations above. Therefore, the specification objection maintained.
Drawing
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action
For at least similar reasons as described in the specification objection in the previous office and above, the drawing objection maintained and see the drawings figure 21-22 as referred by applicant.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Qadrud-Din et al. (US 11860914 B1, hereinafter Qadrud) and in view of reference Addala et al. (US 20210382909 A1, IDS, hereinafter Addala).
Claim 1: Qadrud teaches a computing services environment (title and abstract, ln 1-11, a services environment in fig. 2, multiple client machines 202, 204 with text generation modeling system 270 in fig. 2, and with multiple text generation modeling systems for more sophisticated than simple back-and-forth interactions in fig. 11, col 27, ln 26-30) comprising:
a database system (dataset system 214 in fig. 2) storing a plurality of database records for a plurality of client organizations (represented by different client machines 202, 204, etc., in fig. 2) accessing computing services via the computing services environment (chat service in figs. 8, requesting for summary service in fig. 9, time-line related service such as drafting a contract, legal research, etc., col 5, ln 31-43), the computing services including a conversational chat assistant accessible via a plurality of communication channels (including text editor plugin, dedicated application, a web browser, or combinations thereof, col 6, ln 59-64 to accomplish chat assistance in fig. 8, and through communication interface 212 to connected to the client machines 202, 203, 204, col 8, ln 43-46);
a communication interface (communication interface 212 in fig. 2) configured to receive an input message from a client machine via a communication channel of the plurality of communication channels (facilitating communications with the client machines, including receiving from and transmitting to the client machines, col 8, ln 43-50);
a generative language model interface providing access to one or more generative language models (including scheduler 242 for scheduling requests for transmission to the text generation modeling system 270, col 8, ln 46-50, chat interface 258 for text-based chat communication between the user at a client machine and the text generation model 276 in fig. 2, col 8, ln 29-32); and
an orchestration and planning service (portions of orchestrator 230 in fig. 2) configured to:
analyze the input message (via parsing in fig. 3, and implemented by the orchestrator 230 when a document is identified for analysis, col 9, ln 6-23, e.g., determining segment of the document, performing optical character recognition on the individual pages, etc., in fig. 3, e.g., identify domain-specific text chunking constraints, etc., in step 510 in fig. 5, col 12, ln 46-51 and for generating request-related prompt to the generative language model, e.g., prompt for summarization request for a lawyer for a legal AI organization, col 21, ln 19-25, extracting task prompt, col 21, ln 35-40, etc.) to determine a novel text passage via a generative language model of the one or more generative language models (based on received prompts from the orchestrator 230 at step 414 to generate novel text portions by the remote text generation model, col 11, ln 46-54, and e.g., a response to the extractive task questions, col 22, ln 20-42),
determine novel text formatting information (via parsing chat response message 818, formatting the novel text in a letter format, col 19, ln 19-24) based on designated text formatting configuration information specifying one or more parameters (based on instructions in the chat output message to generate one or more user interface elements buttons or lists to allowing the user to select the recommended skills, col 18, ln 7-11, further including revised correspondence letter by which the formatting the novel text in a letter format, col 19, ln 35-42 or additional instructions included in prompt template and used for format the text generated by the text generation model as structured text such as JavaScript Object Notation JSON list format, col 31, ln 8-12) for formatting text generated for transmission via the communication channel (e.g., formatting to JSON list specified in prompt template of requesting summarization, “passages a JSON array of the verbatim passages, … Format each item as a JSON object with keys of … page, score, passage, answer, id, etc., col 22, ln 24-42 specified with prompt template for a request of summarizing a text, col 21, ln 19-20, and wherein “page”, “score”, “passage”, “answer”, “id”, etc., are parameters for formatting above, and another example, response is in JSON L format, “description”, “page”, “notability”, “year”, “month”, .., “second option”, etc., for timeline object such as scheduling, col 24, 60-67, col 25, ln 1-37 and in deduplication request, the response is required in format specified in the prompt, including “id”, “description”, “reference”, etc., as parameters, col 26, ln 64-67, col 27, ln 1), and
transmitting the novel text passage (e.g., parsed summary responses 920 concatenated and transmitted to the client machine at 924 in fig. 9, col 22, ln 44-53 or consolidated summary to the client machine at 936, col 23, ln 14-24 and other example of finding relevant information from the given contract and the given response in a format specified in the prompt, col 31, ln 57-67, col 32, ln 1-5).
However, Qadrud does not explicitly teach wherein the novel text formatting information is also transmitted to the client machine via the communication interface and does not explicitly teach wherein the novel text formatting information comprising presentation configuration information determined based on designated text formatting specifying one or more parameters for formatting text generated for transmission via the communication channel and such that the client machine is provided with the novel text passage as well as formatting information identifying a presentation configuration native to the communication channel of the client machine.
Suh teaches an analogous field of endeavor by disclosing a computing services environment (title and abstract, ln 1-10 and a system in fig. 9) and wherein Suh teaches wherein the computing services environment comprising:
a database system storing a plurality of database records for a plurality of client organizations disclosed (storage resources 902 on server side in fig. 9 and storing program instructions and functions, para 101 and storing chat history 710 in fig. 7B, para 63; e.g., for network administrator, para 90, restaurant selection, para 93, etc., as the organizations);
a communication interface (including part of constraint manager 211, for receiving user’s text, para 41-48, and communications 221 for sending response to the user display in fig. 2, para 37) configured to receive an input message from a client machine via a communication channel of the plurality of communication channels (constraint manager 211 to receive chat from a user 202 and including calendar user interface 700, etc., para 63);
a generative language model interface providing access to one or more generative language models (generative language model 100 in fig. 2, included in generative language models for interactive constraint satisfaction for a wide range of applications, e.g., scheduling example, para 36);
an orchestration and planning service (including service by adding, deleting, changing, generating, etc., included in interactive constraint satisfaction agent 210 in fig. 2) configured to:
analyze the input message to determine a novel text passage via a generative language model of the one or more generative language models (translating the request into an action, generating prompt with selected actions related to the request and constraints, etc., para 41-48, and for generating suggested meeting schedule, session 302 of the generated prompt in fig. 3A and response format is specified in session 308 of the generated prompt in fig. 3D),
determine novel text formatting information based on designated text formatting configuration information specifying one or more parameters for formatting text generated for transmission via the communication channel (the generated meeting scheduling prompt including the response format in session 308, including “User:”, “Action:”, “Action Input”, “Observation”, etc. as parameter in fig. 3D and/or “response”, “rationale” etc., as parameter specified in response format 402 in fig. 4A for meeting scheduling, and/or “organizer”, “attendees” specified in session 502 in fig. 5A for meeting scheduling, and formatting information carried by the parameters above), and
transmitting the novel text passage and the novel text formatting information to the client machine via the communication interface (novel text passage is transmitted and displayed on the user’s display in figs. 7B-7C, including suggested attendees, time, date, and day and constraints “everyone”, some of “You, Stu, and Carol”, etc., as the novel text and including User’s part “I’D Rather meet in the afternoon” in session 715 as specified by “User”, suggesting with the constraint “HERE IS SUGGESTION …” as specified by “action”, and “FRI 9/15 4:30PM-4:50PM, …” as suggested result and specified by “Observation”, para 63-64 and repeated with different contents in fig. 7C, para 65) for benefits of improving application performance of generative language model (by accepting a natural language request and structuring the data including tasks and constraints without programming language background, para 1, performing diversity in candidate solutions by evaluating the possible solutions according to diversity criteria, para 122, sharing the results with different users, para 121, and by not only generating constraints with the request, but also generating check code of whether the constraints is satisfied or not to increase successful percentage of the response, para 119 and effectively using previously-generated constraints for the current constraints, para 117-118).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have applied transmitting the novel text passage and the novel text formatting information to the client machine via the communication interface, as taught by Suh, to transmitting the novel text passage to the client machine via the communication interface in the computing services environment, as taught by Qadrud, for the benefits discussed above.
However, the combination of Qadrud and Suh does not explicitly teach wherein the novel text formatting information comprising presentation configuration information determined based on designated text formatting specifying one or more parameters for formatting text generated for transmission via the communication channel and such that the client machine is provided with the novel text passage as well as formatting information identifying a presentation configuration native to the communication channel of the client machine.
Addala teaches an analogous field of endeavor by disclosing a computing services environment (title and abstract, ln 1-11 and an environment comprising computer environments services, para 4, in fig. 2) and wherein novel text formatting information is disclosed (including generated markup language code such as JavaScript, HTML, etc., para 95, having text portion for presenting a desired interactive database object representation with metadata when published to desktop or laptop screen of clients, para 70-71) to comprise presentation configuration information (configuration information at step 102 in fig. 1, para 23 and including description of the interactive database object representation, para 23) determined based on designated text formatting specifying one or more parameters (determined based on user input request message, para 48, and included in a presentation configuration message including instructions to configure an interactive database object representation, para 46, and the configuration parameters specified at 1708 of a client user interface in fig. 17, para 59) for formatting text generated (through an interactive user interface presented in a particular context, para 77, e.g., items and sections coexist with legacy record details presented, para 78, such as presenting a form having “description” etc., in fields, and marketing information, opportunity information, partner information, etc., in form sections in fig. 8) for transmission via the communication channel (published to the client laptop or mobile phone at step 418, para 70) and such that the client machine is provided with the novel text passage as well as formatting information identifying a presentation configuration native to the communication channel of the client machine (published through the network interface 220 to the user system 212 for presenting the interactive database object representation including designed forms and sessions and pages to the laptop and mobile phone of the user system 212, para 70 and specified by display section header and layout, and tap orders, etc., in fig. 9) for benefits of improve user experiences through the user interface (by providing user’s desired page layout, drag/drop positioning of fields, revealing information about instance of dbase objects, and component visibility is controlled by the user, para 75) in an easier and costless manner (by reducing response times and overhead, para 85, and by utilizing the existing functionality of the system when constructing dynamic page layouts, para 76).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have applied the novel text formatting information and wherein the novel text formatting information comprising presentation configuration information determined based on designated text formatting specifying one or more parameters for formatting text generated for transmission via the communication channel and such that the client machine is provided with the novel text passage as well as formatting information identifying a presentation configuration native to the communication channel of the client machine, as taught by Addala, to the novel text formatting information in the computer services environment, as taught by the combination of Qadrud and Suh, for the benefits discussed above.
Claim 16 recited a method implemented in the computing services environment as disclosed by the combination of Qadrud, Suh, and Addla, as discussed in claim 1 above and thus, has been analyzed and rejected according to claim 1 above.
Claim 20 has been analyzed and rejected according to claims 1, 16 above and the combination of Qadrud, Suh, and Addala further teaches One or more non-transitory computer readable media having instructions stored thereon (Qadrud, one or more non-transitory media 703 with processor 701, and Suh, storage with instructions, para 79 and Addala, non-transitory computer readable media or some other storage device 604, para 94) for performing the method of claim 16 at the computing services environment (Qadrud, with software, col 39, ln 50-58 and Suh, the functions implemented by CPUs and SOC, para 101, and the method discussed in claims 1, 16 above and Addala, the non-transitory computer readable media for storing instructions and executed by a processor 602, para 94).
Claim 2: the combination of Qadrud, Suh, and Addala further teaches, according to claim 1 above, wherein the novel text formatting information is specific to the communication channel (Qadrud, including editor plugin, dedicated application, a web browser, other types of interactions, col 6, ln 59-64 and also supporting JavaScript Object Notation JSON format, col 5, ln 59-60, and the discussion in claim 1 above, and client machine must have facility or browser to support link, col 20, ln 32-35 and Suh, the output image, audio, other modalities as output the client machine would inherently support, para 27, i.e., channel related output format to be supported and Addala, selecting the published page by access a database object and particular version for presentation).
Claim 3: the combination of Qadrud, Suh, and Addala further teaches, according to claim 1 above, wherein the conversational chat assistant is one of a plurality of conversational chat assistants accessible via the computing services environment (Qadrud, including chat request for summarization of the document, extracting relevance portion from the document, deduplication of the document, as discussed in claim 1 above, and Suh, dialog chat service for scheduling service 204 in fig. 2, figs. 3A-3D, and the discussion in claim 1 above), and wherein the novel text formatting information is specific to the conversational chat assistant (Qadrud, e.g., the formatting information includes “page”, “score”, etc., for summarization assistant, including “date”, “year”, in specific format specified in the prompt to the response for scheduling assistance service, and “id”, “description”, “reference” formatting information for deduplication assistant, and discussed in claim 1 above, and Suh, different formatting information for different meeting scheduling assistance from the generative language model included in the computing services environment and discussed in claim 1 above).
Claim 4: the combination of Qadrud, Suh, and Addala further teaches, according to claim 3 above, wherein the conversational chat assistant and the novel text formatting information are specific to a client organization of the plurality of client organizations (Qadrud, skill selection request for an employee in a legal AI created by a company Casetext, col 18, ln 35-38, and no link URL or phone number to Casetext’s website in the response, i.e., the formatting is specific to the specific company, in the specific skill selection chat assistance, col 18, ln 30-33, and another formatting information for the transmission is a document corresponding to a client machine via a link and returned, having a link, col 20, ln 32-39, and Suh, scheduling tasks for a dedicated organizer and attendees specified in an access specific for checking chat specified in the prompt in fig. 4A, and the format including “rationale” comprising company employee’s name “Billy” in session 404 in fig. 4B, i.e., the formatting information is dedicated to the company and the conversational chat assistant about meeting scheduling, and another example, meeting scheduling in a single response or with repeat format for a wide recommendations of non-single responses, and meeting scheduling assistance at specific time zone with specific employees’ names of the organization in figs. 7B/7C ).
Claim 5: the combination of Qadrud, Suh, and Addala further teaches, according to claim 1 above, wherein the novel text passage (Qadrud, generated novel text portions by the remote text generation model, col 11, ln 46-54, and Suh, generating suggested meeting schedule, session 302 based on the prompt in fig. 3A and response format is specified in session 308 of the generated prompt in fig. 3D) includes a novel text portion characterizing a data object (Qadrud, e.g., “page” data type by filling digital number, a JSON array for a data type “passages”, string for “passage”, and answer for “string”, col 22, ln 20-42, and Suh, discussed in claim 1 above) corresponding to a data type of a plurality of data types (Qadrud, and Suh, id with digital number in session 306 in fig. 3C), and wherein the novel text formatting information is specific to the data type (Qadrud, discussed above, e.g., integer number format specific for “page”, “score”, and JSON array for “passages”, etc., above and Suh, the response must contain “action” with string data type or verb, and results by the “observation” is limited to likely Boolean value “successful” or “yes” or “no” in figs. 4A-4B).
Claim 6: the combination of Qadrud, Suh, and Addala further teaches, according to claim 1 above, further comprising a conversational chat studio configured to customize the conversational chat assistant based on graphical user input provided via a graphical user interface (Qadrud, suitable display for providing any of the results to the user, col 16, ln 42-45, e.g., consolidated timeline response is presented on a display to the user in the user interface, col 27, ln 20-23, and Suh, customized to display a single response in fig. 7B or an option with three choices in figs.7C based on the MeetMate app in fig. 7A), and wherein configuring the conversational chat assistant comprises specifying the novel text formatting information (Qadrud, consolidated timeline response is presented on a display to the user in the user interface, col 27, ln 20-23 and Suh, the discussed above, e.g., configured to the novel text to be displayed in a single response window or repeated same-format with three or more response windown above, figs. 7B, 7C respectively).
Claim 7: the combination of Qadrud, Suh, and Addala further teaches, according to claim 1 above, wherein the communication channel is a messaging service (Qadrud, message without instructions and/or input text, col 11, ln 60-63, and Suh, generating suggestion in form of message to user through the constraint solver, para 37 and chat is message chat, para 41).
Claim 8: the combination of Qadrud, Suh, and Addala further teaches, according to claim 1 above, wherein the communication channel is a conversational chat interface included in a web application providing access to the computing services environment (Qadrud, two-communication chat through a chat interface 258 in fig. 2, col 8, ln 24-32 and Suh, interactive chat for capitalizing constraint satisfaction algorithms for refining suggestions, i.e., conversational chat interface, para 39-40).
Claim 9: the combination of Qadrud, Suh, and Addala further teaches, according to claim 1 above, wherein the communication channel is a conversational chat interface included in a native mobile application providing access to the computing services environment (Qadrud, mobile computing device as client machine, col 6, ln 52-56 and Suh, the client device can be mobile, smartphones, tablets, device with applications, para 77 and performing interactive chat, para 39 and discussion in claim 8 above).
Claim 10: the combination of Qadrud and Suh further teaches, according to claim 1 above, wherein determining the novel text passage comprises determining one or more actions of a plurality of actions by analyzing natural language user input included in the input message (Qadrud, optical character recognition on individual pages of the input document at step 308, combining at step 310, identifying and correcting inappropriate text splits at step 312, etc., as actions in fig. 3 , determining a text generation flow 404 in fig. 4, etc., and Suh, constraints are defined based on the user request and generating constraints prompt to the generative language model, actions are determined by generating and using prompt template, discussed in claim 1 above, and add constraint, delete constraint, changing priority, etc., within the interactive constraint satisfaction agent 210 in fig. 2, para 41, returning time suggestions, para 40, providing context with chat history, para 48).
Claim 11: the combination of Qadrud, Suh, and Addala further teaches, according to claim 10 above, wherein an action of the one or more actions comprises generating a summary of one or more database records of the plurality of database records via a generative language model (Qadrud, based on a “summarize documents” request, col 10, ln 27-32 and summarizing and further summarizing as actions to generate summarization report, col 11, ln 7-15, the requested document is retrieved from database system, abstract, and Suh, based on summarization prompt to the generative language model, summarizing large documents, para 19 and e.g., generating summarizing prompt to scheduled list as document, and response as summary with day and answer in figs. 6A/6B), and wherein the novel text passage includes the summary (Qadrud, the resulting summaries is generated and outputted through col 12, ln 1-2, and provide summary message corresponding to the summary request and presented to client machine 202 in fig. 9 and Suh, the summary in figs. 6A/6B).
Claim 12: the combination of Qadrud, Suh, and Addala further teaches, according to claim 10 above, wherein an action of the one or more actions comprises storing information to the database system (Qadrud, updating a database system based on request in fig. 13, col 32, ln 64-67, col 33, ln 1-6 and col 34, ln 22-28, e.g., one or more entries added as action to identify the field values, col 32, ln 64-65, and storing metadata information about documents based on information extracted from those docuemnts, col 8, ln 51-61 and including storing the summary in a file in the response, col 22, ln 52-53 and Suh, constraints are stored, i.e., “Hen is a vegan” is stored, para 93 and including updating the data sources at step 10).
Claim 13: the combination of Qadrud, Suh, and Addala further teaches, according to claim 10 above, wherein an action of the one or more actions comprises verifying an identity of a user associated with the input message (Qadrud, for searching service, the actions includes identifying document and identifying clauses, col 30, ln 12-24, identifying data corresponding to fields of the text, col 6, ln 55-58, and field of the text including user’s name “CoCounsel”, col 18, ln 35-38, and Suh, removing out user’s personally identifiable private data PII to generate universal calendar, i.e., the private data PII is identified for being masked, para 66-67).
Claim 14: the combination of Qadrud, Suh, and Addala further teaches, according to claim 1 above, further comprising a metadata framework for specifying information related to the conversational chat assistant (Qadrud, metadata such as instructions and included in the prompt and the response, col 12, ln 64-67, col 13, 1-6, and Suh, constraint data structure generated by the generative language model, para 3, and representing user’s preferences in the chat, para 4 and used to identify candidate solutions that matches user preferences in the chat communication, para 20) and the one or more actions (Qadrud, e.g., in the input metadata extraction prompt based on clauses col 30, ln 65-67, col 31, ln 1-5, and Suh, actions including adding 212, delete 213, change priority of constraints 314 , generating suggestions 215, generating message to user 216), an action of the one or more actions being defined via a definition that includes one or more inputs (Qadrud, e.g., in extracting relevant from a contract, including action of providing ID of the clause if relevance found, and definition of relevance, col 31, ln 18-23 and Suh, including constraint management prompts and code generation prompts as actions, for the generative language model with preference lists such as “id”, “priority”, value”, “preference”, “ACTIOIN”, etc., in fig. 3A-3C, and code generation prompt such as “organization” (string), “attendees”, “calendar”, “candidate_time”, etc., in figs. 5A-5B), one or more outputs (Qadrud, e.g., “question_comprehension”, “what_to_look_for” in if-else, col 32, ln 6-15, and Suh, “observation” for each of attendees in fig. 3A-3C and python function called meeting_constraint, returned candidate_time.start.hour, candidate_time.start.weekday, etc., in figs. 5A/5B), a description (Qadrud, description of task and definition of relevance, col 31, ln 18-47, and Suh, description for each of inputs and actions in figs. 3A-3C and 5A/5B), and one or more operations performed via the computing services environment (Qadrud, if-else operation discussed above, and Suh, e.g., filling in data and contents in “id”, “priority”, and “preference”, etc., in “preference list” in figs. 3A-3C and <START_CODE>, <END_CODE> in figs. 5A/5B), wherein the inputs and outputs are defined based on respective metadata entries consistent with the metadata framework (Qadrud, entries of the input and output and discussed above, and Suh, “INPUT”, “Observation” with contents in figs. 3A-3C, “START_CODE”, “END_CODE”, “def”, and returned values from input of “organizer” in “candidate_time.avaialbe”, etc., in figs. 5A/5B).
Claim 15: the combination of Qadrud, Suh, and Addala further teaches, according to claim 1 above, further comprising a trust layer (Qadrud, via test repository 224 for evaluating whether a prompt constructed be tested and whether test success or test failure, col 29, ln 7-14 and Suh, user study stage, para 67), wherein determining the novel text passage comprises transmitting an input prompt to the generative language model for completion (Qadrud, through prompt template 238 in fig. 2, different prompt templates selected from the prompt library based on the text generation flow col 11, ln 16-21, and Suh, the constraint management prompt inputted to the generative language model through the template in figs. 3A-3C, para 49), and wherein the trust layer is configured to mask sensitive data included in an input prompt (Qadrud, name of a chat bot is removed during parsing by pattern match, col 17, ln 27-30, and Suh, removing shared personally identifiable information PII, and attendees, project title, removed and replaced with placeholders, para 67) before the input prompt is transmitted to the generative language model (Qadrud, removing during the parsing, col 17, ln 26-30, and it is before the consolidation prompt message inputted to the generative language model in 918-930 in fig. 9 and Suh, the removement by user study, para 67, and inherently it is before generating constraint management prompt to the generative language mode), and wherein masking the sensitive data includes replacing a text portion with a unique identifier (Qadrud, name of a chat bot is removed during parsing by pattern match, col 17, in 27-30, and Suh, removed and replaced with a placeholders, para 67), and wherein the trust layer is further configured to demask a prompt completion received from the generative language model by replacing the unique identifier with the text portion (Suh, these placeholders were later in-filled by relevant meeting characteristic such as name of the organizer for the meeting, para 67).
Claim 17 has been analyzed and rejected according to claims 16, 2 above.
Claim 18 has been analyzed and rejected according to claims 16, 3 above.
Claim 19 has been analyzed and rejected according to claims 18, 4 above.
Response to Arguments
Applicant's arguments filed on June 4, 2026 have been fully considered and but are moot in view of the new ground(s) of rejection necessitated by the applicant amendment. Although a new ground of rejection has been used to address additional limitations that have been added to claims 1, 16, 20, a response is considered necessary for several of applicant’s arguments since references Qadrud and Suh will continue to be used to meet several claimed limitations.
With respect to the prior art rejection of independent claim 1, similar to claims 16, 20, under 35 USC §103(a), as set forth in the Office Action, applicant argued about “Qadrud … does not disclose generating formatting text for specific communications channels, and transmitting text along with such formatting information for use by a client machine”, and “Qadrud does not disclose determining novel text formatting information …”, etc., as asserted in paragraph 2 of page 7 in Remarks filed on June 4, 2026, and about prior art Suh, applicant further argued Suh “also does not disclose generating formatting information and text for specific communication channels, and transmitting such text along with such formatting information for use by a client machine”, etc., as asserted in paragraph 3 of page 7 and paragraph 1 of page 8 in Remarks filed on June 4, 2026.
In response to the argument above, the Office respectfully disagrees because, Qadrud does not only disclosed “describes natural language generation in the context of database query responses”, etc., but also, as discussed in the office action above, teaches “determine novel text formatting information …” by “parsing” and “formatting the novel text …” (col 19, ln 19-24) based on “instruction in the chat output message”, etc., (col 18, ln 7-11), and transmitting the novel text passage by transmitting the concatenated parsed summary to the client machine (fig. 9, col 22, ln 44-53, col 23, ln 14-24, etc.), which would anticipate the broadly recited limitation of “determine” and “transmit” above (office action above, page 6-7), but applicant is in silence and thus, the argument above is moot.
Similarly, Suh does not only teach “leveraging a generative language model for interactive constraint solving …”, but also disclosed determination of novel text formatting information based on designed text formatting configuration information …, (by disclosing response format information in session 308, and the response format 402/502 with parameters, figs. 4A, 5A,) and both the novel text passage and the novel text formatting information are transmitted to the client machine via the communication interface (for displaying on the user’s display in figs. 7B-7C, etc., para 63-65). Applicant is also in silence and thus, the argument about the prior art Suh is also moot.
Therefore, prior art rejection of claims 1, similar to claims 16, 20, under 35 U.S.C. 103(a) maintained.
In the response to this office action, the Office respectfully requests that support be shown for language added to any original claims on amendment and any new claims. That is, indicate support for newly added claim language by specifically pointing to page(s) and line numbers in the specification and/or drawing figure(s). This will assist the Office in prosecuting this application.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/LESHUI ZHANG/
Primary Examiner,
Art Unit 2695
Prosecution Insights