Vector Graph-Based Repository Understanding for Issue-Driven File Retrieval

A big part of the high - level programming repositories used by software developers over the world every day have more than 2000 files; the largest files from those repositories could have 5,000 or more lines of code -- those scales exceed LLM context window size by magnitude of 1,000 - 10,000 times. Based on such limitations, application of highly productive and smart LLM to large code bases becomes a challenge which stays at the front door of automatization of the software development process [8, 3]. Keeping this in mind, we developed a solution that allows us to apply a certain level of automatization and simplification of the development of large code bases for software developers. The most complete and main task that our system is capable of is automatic bug - fix and feature addition / enhancement using only a short user description. The given task can be split into two smaller tasks: (1) retrieval of relevant source code repository files to a Natural Language (NL) user query / issue description; (2) applying changes to a set of files selected in Step #1.