The invention discloses an AI-based localized environment application offline deployment method and device and a medium. The method comprises the steps that a localized environment is pre-detected based on probe service, a
system layer configuration
list is generated, heterogeneous features are extracted through a dual-channel
deep learning model based on the
system layer configuration
list, and adaptive priority labels of the heterogeneous features are generated; the method comprises the following steps: analyzing an application program through
static analysis and dynamic scanning technologies, constructing a dependency
list, and constructing a version compatibility atlas based on
metadata of a domestic
operating system warehouse; generating a minimum-cost replacement path by using a graph
attention network, performing hash check on each dependency packet, and generating an incremental update packet through a differential packaging
algorithm; the resource occupation condition of the
system is monitored in real time through a
reinforcement learning model so as to dynamically optimize a deployment sequence and a
resource allocation strategy, a deployment log is analyzed based on a
natural language processing model, an error type is recognized, a repair operation is triggered, and application offline deployment is achieved.