Multi-agent code review comment generation

A computer-implemented method for generating a code review comment, comprising:

• obtaining a code change to a file of a repository;
• causing, by a first agent, a neural encoder model to determine if the code change represents a risk to the repository if merged into the file, wherein the neural encoder model is given the code change and a context of the code change;
• causing, by a second agent, a first language model to generate a code review comment for the code change when the neural encoder model determines that the code change represents a risk to the repository if merged into the file, wherein the first language model is given original source code of the code change, the code change and a context of the code change, wherein the code review comment for the code change comprises an issue with the code change and a suggestion for remedying the issue with the code change;
• causing, by the second agent, the first language model to generate a severity score of the issue with the code change;
• causing, by a third agent, a second language model to determine if the code review comment generated by the first language model having a high severity score of the issue with the code change includes a wrong suggestion, wherein the first language model and the second language model differ;
• and
• outputting, by the third agent, the code review comment upon the second language model determining that the code review comment does not include the wrong suggestion,
• wherein the first agent, the second agent, and the third agent are separate executable components invoked by a distinct Application Programming Interface (API).

A hardware storage device having stored thereon computer executable instructions that are structured to be executable by a processor of a computing device to thereby cause the computing device to generate a code review comment by performing actions that:

• obtain a code change to a file of a repository;
• cause, by a first agent, a neural encoder model to determine if the code change represents a risk to the repository if merged into the file, wherein the neural encoder model is given the code change and a context of the code change;
• cause, by a second agent, a first language model to generate a code review comment for the code change when the neural encoder model determines that the code change represents a risk to the repository if merged into the file, wherein the first language model is given original source code of the code change, the code change and a context of the code change, wherein the code review comment for the code change comprises an issue with the code change and a suggestion for remedying the issue with the code change;
• cause, by the second agent, the first language model to generate a severity score of the issue with the code change;
• cause, by a third agent, a second language model to determine if the code review comment generated by the first language model having a high severity score of the issue with the code change includes a wrong suggestion, wherein the first language model and the second language model differ;
• and
• output, by the third agent, the code review comment upon the second language model determining that the code review comment does not include the wrong suggestion,
• wherein the first agent, the second agent, and the third agent are separate executable software components invoked by a distinct Application Programming Interface (API).