Method and apparatus for generating blocks of code using artificial intelligence

A non-transitory machine-readable medium, comprising executable instructions that, when executed by a processing system including a processor, facilitate performance of operations, the operations comprising:

• obtaining code data from a plurality of repositories, wherein each of the plurality of repositories includes a particular domain-related code;
• generating a Natural Language Processing (NLP) model based on the code data;
• receiving input via an Application Programming Interface (API), the input including a natural language statement from equipment of a programmer, the natural language statement indicating an intent of the programmer to generate a particular domain-specific code compatible with the particular domain-related code;
• generating according to the intent of the programmer, a code block by applying the NLP model to the natural language statement, wherein the generating the code block comprises generating multiple versions of the code block, and wherein the multiple versions of the code block are at least one of applicable to different vendor equipment, in different programming languages, applicable to different service providers, or a combination thereof;
• and
• providing the multiple versions of the code block for presentation at the equipment of the programmer.

A device, comprising:

• a processing system including a processor;
• and
• a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations, the operations comprising:
• providing input to a server, the input including a natural language statement, the natural language statement indicating an intent by a programmer to generate network domain-specific code;
• receiving, from the server, code block, wherein the code block is generated based on applying an NLP model to the natural language statement, wherein the NLP model is generated from training based on code data, wherein the code data is scanned from a plurality of repositories that include network domain-related code;
• and
• providing, to the server, at least one of feedback data, additional code data, or a combination thereof, wherein the feedback data is associated with an analysis of the code block, wherein the additional code data includes the code block, and wherein the NLP model is adjusted based on at least one of the feedback data, the additional code data, or a combination thereof resulting in an adjusted NLP model.