DETAILED ACTION
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 .
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, 7 – 12, and 16 – 20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Kuppusamy et al. (US PAP 2026/0017325).
As per claims 1, 10, and 19, Kuppusamy et al. teach a computer-implemented method, comprising:
receiving a user instruction to generate a report (“receiving a query to generate a report”; Abstract);
generating an information prompt configured to instruct a large language model (LLM) to derive a plurality of vectors from the user instruction, wherein a first vector of the plurality of vectors identifies reference information that is to be used to generate the report (“large language model architecture including at least one vector database including vectorized data corresponding to one or more documents from one or more document storage locations and a large language model. The method also includes receiving a query to generate a report associated with a current project using the large language model. The method also includes returning, in response to the query, a relevant context generated using the at least one vector database. The method also includes generating and outputting, using the large language model and based on the relevant context, one or more portions of the report.”; paragraphs 5 – 11);
identifying a first question from a plurality of questions based on comparing the first vector to the plurality of questions, wherein the first question is associated with a first query template (“creating a question-answer chain such that one or more relevant queries 106 can be used for obtaining relevant information from the first vector database 102… a function provides a prompt template”; paragraphs 42, 55);
receiving a query result from a collection database based on executing a query corresponding to the first query template against the collection database, the query result comprising a data that corresponds to the reference information; generating an answer prompt configured to instruct the LLM to generate an answer comprising a natural language interpretation of the query result in view of the first question (“the retrieved information/contexts from both the first and second vector database 102, 114 are used along with the LLM 112 to generate responses for sections of the report; paragraphs 49 – 55);
generating a report prompt configured to instruct the LLM to generate the report comprising a natural language interpretation of the answer in view of the user instruction; and providing the generated report responsive to receiving the user instruction (“the generated responses from the LLM 112 are used to complete the report 126 according to a report schema 128. The report schema 128 can be a template created based on various report formatting and structure requirements, and can be created manually or automatically. In some embodiments, the report schema 128 can be a CSV file or other similar file type. To populate the report 126, a prompt template can be defined in-line with the report schema 128 so that outputs from the LLM 112 based on user queries to the RAG systems to generate the relevant context are used to populate specific portions of the report 126.”: paragraphs 40 – 51).
As per claims 2, 11, and 20, Kuppusamy et al. further disclose identifying a placeholder in the first query template, wherein the first query template is not executable with the placeholder (“creating a question-answer chain such that one or more relevant queries 106 can be used for obtaining relevant information from the first vector database 102… a function provides a prompt template”; paragraphs 42, 55).
As per claims 3, 12, Kuppusamy et al. further disclose generating the query by replacing the placeholder in the first query template with a parameter, wherein the parameter comprises a portion of the reference information from the first vector, and wherein the query is executable (“a function provides a prompt template (“def prompt_template”), a function to call an embedding model to create the vector embeddings for the vector databases (“def Embedding_model”)”; paragraphs 51 – 55).
As per claims 7, 16, Kuppusamy et al. further disclose the report comprises a chart (“the final report 126 can also include tables and figures which can be inserted automatically using programming (PYTHON) scripts and/or using multimodal LLMs, such as the LLM 112.”; paragraph 51).
As per claims 8, 17, Kuppusamy et al. further disclose generating a reusable template comprising the plurality of vectors, the first question, and the first query template; and receiving a request for the reusable template to generate a subsequent report (“large language model architecture including at least one vector database including vectorized data corresponding to one or more documents from one or more document storage locations and a large language model… a function provides a prompt template (“def prompt_template”), a function to call an embedding model to create the vector embeddings for the vector databases (“def Embedding_model”)”; paragraphs 5 – 11, 49 - 55).
As per claims 9, 18, Kuppusamy et al. further disclose the plurality of questions are stored in a vector database (“large language model architecture including at least one vector database including vectorized data corresponding to one or more documents from one or more document storage locations and a large language model.”; paragraphs 5 – 11, 55).
Allowable Subject Matter
Claims 4 – 6, 13 – 15 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. The following is a statement of reasons for the indication of allowable subject matter:
As to claims 4 – 6, 13 – 15, the prior art of record does not teach or suggest that the identifying the first question comprises: identifying multiple questions, of the plurality of questions, that are associated with the reference information of the first vector, and wherein each of the multiple questions is paired with its own unique query template.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Vick et al. teach configuring generative artificial intelligence to produce the output report in response to a prompt. Singh et al. teach generating text summary and data visualizations for executive summaries of annual product quality reports based on an input query from a user. Agrawal et al. teach using the in-database LLMs to help generate or summarize content based on unstructured documents.
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/LEONARD SAINT-CYR/Primary Examiner, Art Unit 2658
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