This paper focuses on near-optimal controls for a class of fully-coupled, two-time-scale stochastic functional differential equations (SFDEs). The coefficients of the system involve infinite integral-type delays in both the slow and fast components, which induces a loss of the Markov property. To overcome this challenge, the original system is first transformed into a higher-dimensional system without delay via state augmentation. The core of the analysis is an averaging principle. To ensure its successful application, the ergodicity of the resulting high-dimensional fixed-X equation and its continuous dependence on parameters are established. A key result is the convergence of the value function of the original system to that of a simplified, limiting system, whose coefficients are averages with respect to the invariant measure of the fixed-X equation. Finally, a two-time-scale optimal control problem for an advertising model is presented as an illustrative example.