Our goal is to build a declarative framework for approximate graph matching where various constraints can be stated upon the pattern graph, enabling approximate constrained subgraph matching, extending models and constraints proposed by Rudolf [1] and Valiente et al. [2]. In the present work, we propose a CSP approach for approximate subgraph matching where the potential approximation is declaratively stated in the pattern graph as mandatory/optional nodes/edges. Forbidden edges, that is edges that may not be included in the matching, can be declared on the pattern graph. We also want to declare properties between pairs of nodes in the pattern graph, such as distance properties, that can be either stated by the user, or automatically inferred by the system. In the former case, such properties can define new approximate patterns. In the latter case, these redundant constraints enhance the pruning.