A wide variety of control schemes for Grid-Forming Inverters (GFMIs) have been developed to enable inverter-based resources (IBRs) to comply with evolving grid-code requirements and deliver essential support services such as frequency and voltage regulation. However, the diversity in these control structures presents substantial challenges for consistent modeling, analysis, and systematic comparison. Conventional approaches to modeling Grid-Forming Inverters typically focus on individual control strategies or isolated configurations, limiting their flexibility and scalability for broader applications. To overcome these limitations, this paper introduces a unified, modular framework utilizing state-space representation (SSR) and the Component Connection Method (CCM) for small-signal modeling of GFMIs. The proposed framework systematically accommodates four prevalent Active Power Control (APC) strategies—Droop control, Droop with Low-Pass Filter (LPF), Virtual Synchronous Generator (VSG), and Compensated Generalized Virtual Synchronous Generator (CGVSG). By establishing a comprehensive and modular modeling methodology, this paper facilitates efficient stability analysis, parameter sensitivity assessment, and performance optimization of diverse GFMI configurations under varying grid conditions. The effectiveness and accuracy of the proposed approach are demonstrated through detailed eigenvalue analyses and validated via time-domain simulations, illustrating significant implications for practical engineering design, grid code compliance, and operational stability in inverter-dominated power systems. The computational implementation of the proposed methodology is available online in a public repository.