ADFWI is an open-source framework for high-resolution subsurface parameter estimation by minimizing discrepancies between observed and simulated waveform. Utilizing automatic differentiation (AD), ADFWI simplifies the derivation and implementation of full waveform inversion (FWI), enhancing the design and evaluation of methodologies. It supports wave propagation in various media, including isotropic acoustic, isotropic elastic, and both vertical transverse isotropy (VTI) and horizontal transverse isotropy (HTI) medias. In addition, ADFWI provides a comprehensive collection of Objective functions, regularization techniques, optimization algorithms, and deep neural networks. This rich set of tools facilitates researchers in conducting experiments and comparisons, enabling them to explore innovative approaches and refine their methodologies effectively. more details can be found at: https://github.com/liufeng2317/ADFWI