Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
The office action sent in response to Applicant’s communication received on 6/21/2024 for the application number 18750469. The office hereby acknowledges receipt of the following placed of record in the file: Specification, Abstract, Oath/Declaration and claims.
Priority
This application claims the benefit under 35 U.S.C. § 119 (e) of U.S. Provisional Patent Application 63/558,557 (Attorney Docket No. SFDCP224P) by Padmanabhan, titled “GENERATIVE LANGUAGE MODEL DATABASE SYSTEM INTEGRATION ARCHITECTURE”, filed on Feb. 27, 2024, and to U.S. Provisional Patent Application 63/558,580 (Attorney Docket No. SFDCP225P) by Padmanabhan, titled “GENERATIVE LANGUAGE MODEL DATABASE SYSTEM INTEGRATION INTERFACE CONFIGURATION”, filed on Feb. 27, 2024, and to U.S. Provisional Patent Application 63/558,641 (Attorney Docket No. SFDCP226P) by Padmanabhan, titled “GENERATIVE LANGUAGE MODEL DATABASE SYSTEM ACTION CONFIGURATION AND EXECUTION”, filed on Feb. 27, 2024, and to U.S. Provisional Patent Application 63/558,653 (Attorney Docket No. SFDCP227P) by Padmanabhan, titled “GENERATIVE LANGUAGE MODEL DATABASE SYSTEM ACTION CUSTOMIZATION AND EXECUTION”, filed on Feb. 28, 2024,
Status of the claims
Claims 1-20 are presented for examination.
Information Disclosure Statement
The information disclosure submitted on 6/21/2024 were before the mailing data of the first office action. The /submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
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Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of Co-pending U.S. Application No. 18/817,976 . Although the claims at issue are not identical, they are not patentably distinct from each other.
Regarding claim 1, claim 1 of Co-pending U.S. Application No. 18/817979 claims all the limitations set forth in the application claim 1. Although the claims are not exactly same the co-pending application reads on the current application and has additional limitations. ( italicized portions)
US Application No. 18750469 Claim 1
Co-pending U.S. Application No. 18817976 Claim 1
1. A computing services environment comprising: a database system storing a plurality of database records for a plurality of client organizations accessing computing services via the computing services environment, the computing services including a conversational chat assistant; an application server receiving natural language user input for the conversational chat assistant via the Internet; a generative language model interface providing access to one or more generative language models; an orchestration and planning service configured to analyze the natural language user input via a generative language model of the one or more generative language models to identify a plurality of actions to execute via the computing services environment to fulfill an intent expressed in the natural language user input, wherein the computing services environment is configured to execute the plurality of actions to determine a natural language response message; and a communication interface configured to transmit the natural language response message to a client machine via the application server.
1. A computing services environment comprising: a database system storing a plurality of database records for a plurality of client organizations accessing computing services via the computing services environment, the computing services including a conversational chat interface; an application server providing access to the conversational chat interface to a plurality of client machines associated with one or more of the plurality of client organizations; a metadata repository storing a plurality of metadata entries for a plurality of agents, a metadata entry of the plurality of metadata entries including a description of a designated agent of the plurality of agents, the metadata entry defining interaction data for interacting with the designated agent; and an orchestration service configured to execute an orchestration process based on a natural language request message received via the conversational chat interface, wherein executing the orchestration process includes: determining an input prompt including (1) the natural language request message and (2) a plurality of agent descriptions selected from some or all of the plurality of metadata entries, transmitting the input prompt to a generative language model via a generative language model interface, receiving from the generative language model interface a prompt completion including a selection of the designated agent based on the plurality of agent descriptions, and generating novel text responsive to the natural language request message by transmitting a request to the designated agent based on the natural language request message and the interaction data.
Regarding claim 14 and 19 , claim 17 and 20 of copending application claims all the limitations set forth in the application claims 14 and 18 respectively.
Regarding claims 2-13, 15-18 and 20, claims 1-20 of the copending application claims all the limitations set forth in the application claims 2-13, 15-18 and 20 respectively.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of Co-pending U.S. Application No. 18/817,996 . Although the claims at issue are not identical, they are not patentably distinct from each other.
Regarding claim 1, claim 1 of Co-pending U.S. Application No. 18/817996 claims all the limitations set forth in the application claim 1. Although the claims are not exactly same the co-pending application reads on the current application and has additional limitations. ( italicized portions)
US Application No. 18/750469Claim 1
Co-pending U.S. Application No. 18/817996 Claim 1
1. A computing services environment comprising: a database system storing a plurality of database records for a plurality of client organizations accessing computing services via the computing services environment, the computing services including a conversational chat assistant; an application server receiving natural language user input for the conversational chat assistant via the Internet; a generative language model interface providing access to one or more generative language models; an orchestration and planning service configured to analyze the natural language user input via a generative language model of the one or more generative language models to identify a plurality of actions to execute via the computing services environment to fulfill an intent expressed in the natural language user input, wherein the computing services environment is configured to execute the plurality of actions to determine a natural language response message; and a communication interface configured to transmit the natural language response message to a client machine via the application server
1. A computing services environment comprising: a database system storing a plurality of database records for a plurality of client organizations accessing computing services via the computing services environment, the computing services including a conversational chat interface; an application server providing access to the conversational chat interface to a plurality of client machines associated with one or more of the plurality of client organizations; a metadata repository storing metadata entries characterizing a plurality of actions capable of being performed via the computing services environment; an orchestration service configured to execute an orchestration process based on a natural language request message received via the conversational chat interface, wherein executing the orchestration process includes: determining an input prompt including (1) the natural language request message and (2) descriptions of actions selected from the metadata entries, transmitting the input prompt to a generative language model of a plurality of generative language models via a generative language model interface, receiving from the generative language model interface a prompt completion including: (1) a plan that includes a subset of the actions, and (2) a natural language description of the plan, transmitting the natural language description to the client machine via the conversational chat interface, receiving user input regarding the plan via the conversational chat interface, generating novel text responsive to the natural language request message by executing one or more actions of the plurality of actions, the one or more actions being determined based on the plan and the user input, and transmitting the novel text to the client machine via the conversational chat interface.
Regarding claims 14 and 19 , claim 13 and 17 of copending application 18/817996 claims all the limitations set forth in the application claims 13 and 19 respectively.
Regarding dependent claims 2-13, 15-18 and 20, claims 1-20 of co-pending application 18/817996 reads on claims 2-13, 15-18 and 20 of instant application.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
Claims 1-13 include one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitations use a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are: a database system, an application server, an orchestration and planning service, computing service environment, communication interface in claim 1, trust layer in claim 10-11 and conversational chat studio in claim 8.
Because these claim limitations are being interpreted under 35 U.S.C. 112(f), they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof (environment include …processor ( fig 9, 11, Para 0141, 171; FIG. 11 illustrates one example of a computing device. According to various embodiments, a system 1100 suitable for implementing embodiments described herein includes a processor 1101, a memory module 1103, a storage device 1105, an interface 1111, and a bus 1115 (e.g., a PCI bus or other interconnection fabric.) System 1100 may operate as variety of devices such as an application server, a database server, or any other device or service described herein, Para 0141; layer is a part of computing environments and processor performs the function, Fig 1)
If applicant does not intend to have these limitation(s) interpreted under 35 U.S.C. 112(f), applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f).
Examiner’s Note regarding 101
analysis in Step 2A Prong Two considers the claim as a whole. The way in which the additional elements use or interact with the exception may integrate the judicial exception into a practical application. Accordingly, the additional limitations should not be evaluated in a vacuum, completely separate from the recited judicial exception. Instead, the analysis should take into consideration all the claim limitations and how these limitations interact and impact each other when evaluating whether the exception is integrated into a practical application.12 While an additional limitation (or combination) that merely applies the judicial exception on a generic computer may not render a claim eligible on its own, an additional limitation (or combination) that meaningfully limits the judicial exception can render it eligible.
In the present claims the combination of additional element integrates the judicial exception to provide improvement to a technical field ( computing service environment ). Reminders on evaluating subject matter eligibility of claims under 35 U.S.C. 101
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-3, 5-6, 8, 12-16 and 18-19 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Fan ( US 20250078823)
Regarding claim 1, Fan teaches a computing services environment (LLM orchestrator, Fig 1) comprising:
a database system storing a plurality of database records for a plurality of client organizations accessing computing services via the computing services environment (personalized context data, Para 0041-0042; storage can be repository, database etc.. Para 0112) , the computing services including a conversational chat assistant (AI agent, Table 1-3, 10-11) ;
an application server receiving natural language user input for the conversational chat assistant via the Internet ( receive user input, Para 0034; network connected, Fig 1) ; a generative language model interface providing access to one or more generative language models ( LLM, Fig 1 and Fig 4) ; an orchestration and planning service configured to analyze the natural language user input ( analyse bodies of text, Para 0027) via a generative language model of the one or more generative language models ( LLM orchestrator component 130, Para 0034) to identify a plurality of actions to execute via the computing services environment ( The user input data 127 may be received at the LLM orchestrator component 130 of the system component(s) 120, which may be configured to generate a list (e.g., one or more) of tasks (e.g., steps/actions) that are to be completed in order to perform an action responsive to the user input and select a task of the list of the tasks that is to be completed first (e.g., in a current iteration of processing by the system 100), as described in detail herein below with respect to FIG. 4. In instances where the plan generation component 135 generates more than one task to be completed in order to perform the action responsive to the user input, the plan generation component 135 may further maintain and prioritize the list of tasks as the processing of the system 100 with respect to the user input is performed. In other words, as the system 100 processes to complete the list of tasks, the plan generation component 135 may (1) incorporate the potential responses associated with completed tasks into data provided to other components of the system 100; (2) update the list of tasks to indicate completed (or attempted, in-progress, etc.) tasks; (3) generate an updated prioritization of the tasks remaining to be completed (or tasks to be attempted again); and/or (4) determine an updated current task to be completed, Para 0035) to fulfill an intent expressed in the natural language user input ( fulfil the user input, Para 0145; task is determined intent, Table 4 and Table 7) , wherein the computing services environment is configured to execute the plurality of actions to determine a natural language response message ( The LLM shortlister component 140 receives and processes the action response data 158a-n and generates potential response data 143a-n representing the potential response(s), Para 0036; action plan execution component perform the actions, Para 0107) ; and a communication interface configured to transmit the natural language response message to a client machine via the application server (respond as tts/skill etc., Fig 5, Para 0107-0111)
Regarding claim 2, Fan as above in claim 1, teaches wherein identifying the plurality of actions comprises: determining an intent identification input prompt that includes the natural language user input and one or more natural language instructions executable by the generative language model to identify the plurality of actions ( user input ( representation of intent, Para 0066, 0171) ; transmitting the intent identification input prompt to the generative language model for completion (the personalized context component 165 (or the system 100) may include a personalized context prompt generation component (not illustrated), which may be configured to generate a prompt including the user input data 127 (or a representation of an intent of the user input) to be input to the LLM), Para 0066) ; receiving an intent identification prompt completion from the generative language model( LLM receives the prompt, Para 0066; wherein the input is related to the determined intent to perform a task { Select the top prioritized task given the ultimate goal of [user input data 127 (or a representation of a determined intent included in the user input data 127]; Table 7; action plan execution, Fig 4, Para 0125) ; and identifying the plurality of actions by parsing the intent identification prompt completion (the plan generation component 135 may include another component that parses the model output data 425 to determine the one or more tasks and may send a representation of the one or more tasks to the task selection prompt generation component 430., Para 0092, Fig 4)
Regarding claim 3, Fan as above in claim 2, teaches wherein the intent identification input prompt identifies a plurality of predetermined actions executable by the computing services environment ( action plan, Para 0081-0082) , wherein the plurality of actions are a subset of the plurality of predetermined actions, and wherein the plurality of actions are identified in the intent identification prompt completion ( the plan generation component 135 may include another component that parses the model output data 425 to determine the one or more tasks and may send a representation of the one or more tasks to the task selection prompt generation component 430., Para 0092, Fig 4)
Regarding claim 5, Fan as above in claim 2, teaches wherein identifying the plurality of actions comprises: determining a topic identification input prompt that includes the natural language user input and a second one or more natural language instructions executable by the generative language model to identify a topic based on the natural language user input ( domain of the user input, Para 0070, for e.g. topic – food or booking etc.) ; transmitting the topic identification input prompt to the generative language model for completion; receiving a topic identification input prompt completion from the generative language model ( the LLM agent component 152d may be configured to handle user inputs/tasks related to ordering food from a particular restaurant (e.g., a particular pizza restaurant), the LLM agent component 152e may be configured to handle user inputs/tasks related to booking a hotel, the LLM agent component 152f may be configured to handle user inputs/tasks related to booking a flight, etc., Para 0070); and identifying a topic of a plurality of topics by parsing the intent identification prompt completion, wherein each of the plurality of topics corresponds with a respective topic-based subset of the plurality of actions ( skill based on the particular domain, Para 0111, 0171)
Regarding claim 6, Fan as above in claim 5, teaches wherein the intent identification input prompt identifies a plurality of predetermined actions executable by the computing services environment, wherein the plurality of actions are a subset of the plurality of predetermined actions, wherein the plurality of actions are identified in the intent identification prompt completion, and wherein the plurality of predetermined actions are those corresponding with the identified topic ( particular topic, Para 0111, 0141)
Regarding claim 8, Fan as above in claim 1, teaches further comprising a conversational chat studio configured to customize the conversational chat assistant based on graphical user input provided via a graphical user interface ( skill component can be customized, Para 0069-0070)
Regarding claim 12, Fan as above on claim 1, teaches wherein the one or more generative language models includes a first generative language model hosted outside the computing services environment, wherein the one or more generative language models includes a second generative language model hosted outside of the computing services environment ( language model 420 and 440 for e.g.., Fig 4; LLM can be gpt ( hosted outside ), Para 0029)
Regarding claim 13, Fan as above in claim 1, teaches wherein an action of the plurality of actions comprises retrieving one or more database records from the database system, the one or more database records being associated with a client organization of the plurality of client organizations ( action can be based on personalized context, Fig 1, Fig 4)
Regarding claim 14, arguments analogous to claim 1, are applicable. In addition, Fan teaches steps ( method) to perform the functions of claim 1 ( Abstract)
Regarding claim 15, arguments analogous to claim 2, are applicable.
Regarding claim 16, arguments analogous to claim 3, are applicable.
Regarding claim 18, arguments analogous to claim 5,are applicable.
Regarding claim 19, arguments analogous to claim 1, are applicable. In addition, Fan teaches non transitory computer readable medium ( Para 0179-0180)
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, 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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
And
KSR, 550 U.S. at 418, 82 USPQ2d at 1396. Exemplary rationales that may support a conclusion of obviousness include:
(A) Combining prior art elements according to known methods to yield predictable results;
(B) Simple substitution of one known element for another to obtain predictable results;
(C) Use of known technique to improve similar devices (methods, or products) in the same way;
(D) Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results;
(E) "Obvious to try" – choosing from a finite number of identified, predictable solutions, with a reasonable expectation of success;
(F) Known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations are predictable to one of ordinary skill in the art;
(G) Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention.
See MPEP § 2143 for a discussion of the rationales listed above along with examples illustrating how the cited rationales may be used to support a finding of obviousness. See also MPEP § 2144 - § 2144.09 for additional guidance regarding support for obviousness determination.
Claims 4, 10-11, 17 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Fan ( US 20250078823) and further in view of Bazzo (US 20250138986)
Regarding claim 4, Fan as above in claim 3, teaches identified ( Para 0116) but does not explicitly teach wherein the plurality of predetermined actions are each associated with a respective unique identifier and a respective action description in the intent identification input prompt, and wherein the plurality of actions are identified in the intent identification prompt completion via the respective unique identifiers
However, Bazzo teaches wherein the plurality of predetermined actions are each associated with a respective unique identifier and a respective action description in the intent identification input prompt ( (] De-identification may be performed by the change data preprocessing component 208 by replacing PII with alternative data items or placeholders, such as unique identifiers (e.g., USER_NAME_1, ADDRESS_2, or CLIENT_NAME_3), or replacing PII with mask characters,, Para 0078), and wherein the plurality of actions are identified in the intent identification prompt completion via the respective unique identifiers ( The response generation component 216 may postprocess “raw” responses from the LLM 118 to transform the responses into final output that can be presented to a user (e.g., at the user device 106 via the web client 112). For example, where original data items where replaced with alternative or placeholder data items in order to de-identify or shorten the input prompt, and one or more of the alternative or placeholder data items appear in the response from the LLM 118, the response generation component 216 may automatically replace them with the corresponding original data items (e.g., to re-identify the information in the response to make the output understandable or relevant to the user)., Para 0088)
It would have been obvious having the teachings of Fan to further include the concept of Bazzo before effective filing date to protect privacy and reduce token size ( Para 0028, 0035, Bazzo)
Regarding claim 10, Fan as above in claim 1, does not teach trust layer, wherein the trust layer is configured to mask sensitive data included in an input prompt before the input prompt is transmitted to a generative language model for completion
However, Basso teaches wherein the trust layer is configured to mask sensitive data included in an input prompt before the input prompt is transmitted to a generative language model for completion ( replacing PII with mask characters, thereby de-identifying or redacting the PII before it is sent to the LLM 118, Para 0078, 0035, 0111)
It would have been obvious having the teachings of Fan to further include the concept of Bazzo before effective filing date to protect privacy ( Para 0035, Bazzo)
Regarding claim 11, Bazzo as above in claim 10, teaches wherein masking the sensitive data includes replacing a text portion with a unique identifier ( unique identifier, Para 0078) , 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 ( The response generation component 216 may postprocess “raw” responses from the LLM 118 to transform the responses into final output that can be presented to a user (e.g., at the user device 106 via the web client 112). For example, where original data items where replaced with alternative or placeholder data items in order to de-identify or shorten the input prompt, and one or more of the alternative or placeholder data items appear in the response from the LLM 118, the response generation component 216 may automatically replace them with the corresponding original data items (e.g., to re-identify the information in the response to make the output understandable or relevant to the user)., Para 0088)
Regarding claim 17, arguments analogous to claim 4, are applicable.
Regarding claim 20, arguments analogous to claim 4, are applicable.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Fan ( US 20250078823) and further in view of Mohammad ( US 20250117411 )
Regarding claim 7, Fan as above in claim 1, teaches wherein the conversational chat assistant is one of a plurality of conversational chat assistants accessible via the computing services environment, and wherein the conversational chat assistant is specific to a client organization of the plurality of client organizations
However, Mohammad teaches wherein the conversational chat assistant is one of a plurality of conversational chat assistants accessible via the computing services environment, and wherein the conversational chat assistant is specific to a client organization of the plurality of client organizations (To provide further interaction with users, those businesses, entities, and/or organizations can register particular end points with the generic or non-domain-specific chatbot, which can allow links or connections to the domain-specific conversational interfaces specific to those businesses, entities, and/or organizations to be identified, suggested, and accessed by the generic chatbot users, Para 0020)
It would have been obvious having the concept of Fan to further include the teachings of Mohammad before effective filing date to have the bot more tailored to the organization domain specific needs ( Para 0053, Mohammad)
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Fan ( US 20250078823) and further in view of Earley (US 20230016460 )
Regarding claim 9, Fan as above in claim 1, teaches metadata framework and the plurality of actions, an action of the plurality of actions being defined via a definition that includes one or more inputs, one or more outputs, a description, and one or more operations performed via the computing services environment, wherein the inputs and outputs are defined based on respective metadata entries consistent with the metadata framework ( metadata associated with global index which determines whether to send the user input data, Para 0141, 0143)
Fan does not teach metadata framework for specifying information related to the conversational chat assistant and the plurality of actions
Earley teaches metadata framework for specifying information related to the conversational chat assistant ( a metadata field 16i identifying a chat bot, Para 0183-0184) and the plurality of actions ( scripts are retrieved to drive the conversation in an order determined by the sequence indicator contained in the metadata field 16h of the main facet 16c with which that dialog facet and those sub-facets are associated, Para 0203)
It would have been obvious having the teachings of Fan to further include the concept of Earley before effective filing date to identify the tags of categories and domain where there are many domain employed ( Para 0125-0127, Earley)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Azire How To: Text PII Anonymization for Chatbot Systems with Presidio
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/Richa Sonifrank/Primary Examiner, Art Unit 2654