DA-CLIP is a degradation-aware visual language model that can serve as a general framework for image recovery. It trains an additional controller to enable a fixed CLIP image encoder to predict high-quality feature embeddings, which are then integrated into the image recovery network, leading to high-fidelity image reconstruction. The controller also outputs degradation features that match the true corruption of the input, providing a natural classifier for different degradation types. DA-CLIP is further trained on mixed degradation datasets, improving performance on specific degradation and unified image recovery tasks.