Natural language-based management of computing resources executing radio access network workloads
The techniques disclosed herein manage computing environments associated with radio access networks using a natural language interface. This is achieved through utilizing natural language processing to analyze user generated inputs and generate robust large language model queries. In various examples, the queries can include radio access network documentation, diagnostic data, and past interactions to provide custom context to the large language model. Accordingly, the query can cause the large language model to generate an operation sequence comprising a plurality of commands to interface with a resource management tool and control computing resources and supporting components. In this way, the present techniques can alleviate the technical burden on end users and minimize the risk of errors.
1 . A method for translating a natural language input into an automated computing resource management task for a radio access network providing a telecommunications service, the method performed by a computing environment associated with the radio access network, the method comprising:
receiving the natural language input defining a desired outcome for the computing environment associated with the radio access network;
analyzing the natural language input utilizing a natural language processing function to detect the desired outcome for the computing environment associated with the radio access network;
retrieving, based on the desired outcome, an auxiliary information set pertaining to the radio access network;
generating, by the natural language processing function, a custom contextual query based on the desired outcome defined by the natural language input and the auxiliary information set;
providing the custom contextual query to a large language model of the natural language processing function, wherein the custom contextual query causes the large language model to generate an operation sequence containing a plurality of commands defining the automated computing resource management task; and
configuring the computing environment associated with the radio access network with the operation sequence generated by the large language model based on the desired outcome defined by the natural language input and the auxiliary information set, wherein the operation sequence causes the computing environment associated with the radio access network to perform the automated computing resource management task.
2 . The method of claim 1 , wherein the desired outcome defined by the natural language input comprises an implementation of networking functionality within the radio access network.
3 . The method of claim 2 , wherein the operation sequence causes the computing environment associated with the radio access network to retrieve and install a component facilitating the network functionality.
4 . The method of claim 1 , wherein the auxiliary information set comprises documentation that is specific to the computing environment associated with the radio access network.
5 . The method of claim 1 , wherein the auxiliary information set comprises diagnostic information that is retrieved in response to an event within the radio access network.
6 . The method of claim 1 , wherein the custom contextual query includes an intrinsic instruction for constraining a behavior of the large language model.
7 . The method of claim 1 , wherein the natural language input is a predetermined natural language input that is selected from a set of predetermined natural language inputs.
8 . A system for translating a natural language input into an automated computing resource management task for a radio access network providing a telecommunications service, the system comprising:
a processing system; and
a computer readable medium having encoded thereon computer readable instructions that when executed by the processing system cause the system to perform operations comprising:
receiving the natural language input defining a desired outcome for the radio access network;
analyzing the natural language input utilizing a natural language processing function;
detecting, based on the analyzing, the desired outcome for the radio access network;
retrieving, based on the desired outcome, an auxiliary information set pertaining to the radio access network;
generating, by the natural language processing function, a custom contextual query based on the desired outcome defined by the natural language input and the auxiliary information set;
providing the custom contextual query to a large language model of the natural language processing function, wherein the custom contextual query causes the large language model to generate an operation sequence containing a plurality of commands defining the automated computing resource management task; and
executing the operation sequence generated by the large language model based on the desired outcome defined by the natural language input and the auxiliary information set, wherein execution of the operation sequence causes the radio access network to perform the automated computing resource management task.
9 . The system of claim 8 , wherein the desired outcome defined by the natural language input comprises an implementation of networking functionality within the radio access network.
10 . The system of claim 9 , wherein the operation sequence causes the system to retrieve and install a component facilitating the network functionality.
11 . The system of claim 8 , wherein the auxiliary information set comprises documentation that is specific to the radio access network.
12 . The system of claim 8 , wherein the auxiliary information set comprises diagnostic information that is retrieved in response to an event within the radio access network.
13 . The system of claim 8 , wherein the custom contextual query includes an intrinsic instruction for constraining a behavior of the large language model.
14 . The system of claim 8 , wherein the natural language input is a predetermined natural language input that is selected from a set of predetermined natural language inputs.
15 . A computer readable storage medium having encoded thereon computer readable instructions that, when executed by a system, cause the system to perform operations comprising:
receiving a natural language input defining a desired outcome for a radio access network;
analyzing the natural language input utilizing a natural language processing function;
detecting, based on the analyzing, the desired outcome for the radio access network;
retrieving, based on the desired outcome, an auxiliary information set pertaining to the radio access network;
generating, by the natural language processing function, a custom contextual query based on the desired outcome defined by the natural language input and the auxiliary information set;
providing the custom contextual query to a large language model of the natural language processing function, wherein the custom contextual query causes the large language model to generate an operation sequence containing a plurality of commands defining an automated computing resource management task; and
executing the operation sequence generated by the large language model based on the desired outcome defined by the natural language input and the auxiliary information set, wherein execution of the operation sequence causes the radio access network to perform the automated computing resource management task.
16 . The computer readable storage medium of claim 15 , wherein the desired outcome defined by the natural language input comprises an implementation of networking functionality within the radio access network.
17 . The computer readable storage medium of claim 16 , wherein the operation sequence causes the system to retrieve and install a component facilitating the network functionality.
18 . The computer readable storage medium of claim 15 , wherein the auxiliary information set comprises documentation that is specific to the radio access network.
19 . The computer readable storage medium of claim 15 , wherein the auxiliary information set comprises diagnostic information that is retrieved in response to an event within the radio access network.
20 . The computer readable storage medium of claim 15 , wherein the custom contextual query includes an intrinsic instruction for constraining a behavior of the large language model.