DETAILED ACTION
This action is responsive to Remarks and Claim amendments filed on January 12, 2026.
Claims 1-5, 8-13 and 16-17 have been amended. Claims 18-20 have been newly added.
Claims 1-20 are pending and are presented to examination.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Examiner Notes
Examiner cites particular columns, paragraphs, figures and line numbers in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner.
Response to amendments
The objection of claims 2-3 and 10-11 is withdrawn in view of applicant’s amendments.
Response to Arguments
Applicant has argued that Mathis along with the remaining prior arts of record, does not teach the newly added limitation of independent claims 1, 9 and 17 (Remarks, pages 8-13). Applicant’s arguments have been fully considered and are persuasive. Therefore, the rejection is withdrawn. However, upon further consideration, a new ground of rejection is made as set forth in details below. See Friddle (US Pub. No. 2024/0403005), art being made of record as applied herein.
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, 6-7, 9, 14-15 and 17-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Friddle (US Pub. No. 2024/0403005).
With respect to claim 1 (currently amended), Friddle teaches a method for program code generation for data processing programs, the method comprising: for receipt of a user prompt: referencing a prompt database that associates historical prompts, program code generated from the historical prompts, and information indicative of whether execution results of the program code were expected or not expected to generate a combined prompt from the user prompt and a historical prompt from the historical prompts determined to be related to the combined prompt from the referencing; using historical prompts associated with program code that did not produce expected results to avoid generating similar unsuccessful program code (See figure 1 (and related text), process database 106, existing/generated code/prompt 109 and paragraph [0055] “database 106 is used to store code/prompt processes. In some examples, stored code/prompt processes may be stored as embeddings in order to facilitate search operations. In some examples, metadata regarding the code/prompt processes is also stored in the database and is used in connection with applicable searches that may be performed. The metadata can include, for example, runtime information associated with the code/prompt processes including, 1) a number of times the code/prompt processes has been run/executed; 2) A number of prompts needed for successful execution 3) the author or authors of the code/prompt processes; 4) and additional data as needed.”. See paragraph [0089], “As users develop code/prompt processes, interactions with the interpreter enable analysis, debug/testing, and the like to be performed. Further, querying of a knowledgeable database of historical prompt sequences that greatly accelerate their development.”. See paragraph [0305], “a smart interpreter can analyze a code/prompt process and dynamically retrieve/apply existing code/prompt processes to eliminate parts of a code/prompt process that are determined to have a low probability of success. In some instances, the smart interpreter allows for replacing certain elements where there is a more efficient configuration. This results in efficiency gains by saving a developer time and enables developers to construct more efficient code/prompt processes that may have decreased level of interaction with one or more models (e.g., LLMs or the like).”. Furthermore, see paragraphs [0117], [0321]-[0322]). referencing a program template database that associates combinations of the historical prompts and historical program code that was verified to work as expected to generate program code with the combined prompt (See figures 1-4 and 11-12 (and related text), interpreter 101 and paragraph [0066], “From the analyze process 102, an analysis file is produced (at 202) which contains estimates on runtime (e.g., how many prompts were needed to execute the provided code/prompt processes (202)), and what is the likelihood that the code/prompt processes will successfully complete. Once the analysis step concludes, the input data, the code/prompt processes, and the generated analysis file are sent to the query process (103) for processing.”. Furthermore, see paragraphs [0117]-[0122], [0133], [0305], “In certain example embodiments, a smart interpreter can analyze a code/prompt process and dynamically retrieve/apply existing code/prompt processes to eliminate parts of a code/prompt process that are determined to have a low probability of success. In some instances, the smart interpreter allows for replacing certain elements where there is a more efficient configuration. This results in efficiency gains by saving a developer time and enables developers to construct more efficient code/prompt processes that may have decreased level of interaction with one or more models (e.g., LLMs or the like).”) and executing the generated program code and the combined prompt for the data processing programs (See abstract and figures 1-4 and 11-12 (and related text), “The system includes an interpreter for managing the execution of code/prompt processes and corresponding interactions with external models, system processes, a process database (e.g., of existing code/prompt processes), and other sources.”. See paragraph [0076], “Once the interpreter 101 loads the indicated code/prompt processes and the configuration of that code/prompt processes is completed, a message may be communicated back to the user at 223 indicating the status of the interpreter. At 224, the user can then trigger execution of the code/prompt processes.”). With respect to claim 6 (original), Friddle teaches wherein the data processing programs are part of a data analytics system (See figures 1-3 (and related text)).
With respect to claim 7 (original), Friddle teaches wherein the executing the generated program code and the combined prompt for the data processing programs is conducted by a generative artificial intelligence process configured to intake the combined prompt and the generated code and execute a process based on the combined prompt and the generated code (See figures 1-3 (and related text), LLM).
With respect to claims 9 and 14-15, the claims are directed to a non-transitory computer readable medium that corresponds to the method recited in claims 1 and 6-7, respectively (see the rejection of claims 1 and 6-7 above; wherein Friddle also teaches such medium in paragraph [0329] and figure 20).
With respect to claim 17, the claim is directed to an apparatus that corresponds to the method recited in claim 1, respectively (see the rejection of claim 1 above; wherein Friddle also teaches such apparatus in figures 1-3 and 20). With respect to claim 18 (new), Friddle teaches wherein the prompt database stores user evaluations of generated program code indicating whether execution results were appropriate, and wherein the user evaluations are used to determine whether to record the generated program code in the program template database (See rejection of claim 1 which apply in the same manner over this claim. Friddle performs evaluation of code/prompts to generate code and store them in database 106. See paragraphs [0058], [0140], “In some examples, when the user has created/submitted a code/prompt processes, the system 50 facilitates an upload/evaluation mechanism and if the code/prompt processes passes validation it's updated to the database for future re-use.”). With respect to claim 19 (new), Friddle teaches wherein when a program template related to the combined prompt is found in the program template database, the program code is generated by replacing parameters in the program template without using a large language model (See paragraphs [0109]-[0110], “218 If the execute process is running in Automatic mode a query is communicated to the microservices with information about the analysis and the execution so far in order to generate a query for the database to retrieve existing applicable code/prompt process (e). 220 If in Automatic mode and an externally applicable code/prompt processes is found (and public) it will be returned and inserted (or replace the relevant sections) in the user's code/prompt processes.”). With respect to claim 20 (new), Friddle teaches further comprising a parameterization unit that divides the user prompt into a stationary portion and a parameter portion, and stores both portions together with verified program code in the program template database (See figure 1-3 (and related text) and paragraph [0175], “The embeddings 517 of each logical block can be stored to a database or other storage, combined, and/or used to identify applicable or similar code/prompt processes in the database(s). This process is automatic as well. 517, 516 facilitate a recommendation function involving the query sub process. Effectively these operations make it possible to author code/prompt processes with minimal input and natural language, the microservices can then search for similar concepts in the database. If the retrieved code/prompt process(es) needs to be adapted by the microservices in order to work with the user's data object a system code/prompt process will be executed that performs the adaptation. This is similarly effective for code segments, individual prompts and relevant data. (e.g., adapt_process.pf will be retrieved from the database and run on the client's interpreter if public, if private adaptation is run on the remote interpreter).”).
Allowable Subject Matter
Claims 2-5, 8, 10-13 and 16 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.
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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/ANIBAL RIVERACRUZ/Primary Examiner, Art Unit 2192