GraphNovo implements a three-stage procedure. Initially, the observed spectrum is converted into a spectrum graph representation, where nodes correspond to peaks and edges represent mass relationships between pairs of peaks. This spectrum graph is then processed successively by two networks: GraphNovo-PathSearcher produces the optimal node sequence corresponding to a partial peptide prediction and unresolved mass tags based on the mass difference encoded in the edges, and then GraphNovo-SeqFiller outputs the full amino acid sequence. Both networks adopt a six-layer Graphormer encoder architecture, which combines transformers and graph neural networks by introducing centrality encoding, spatial encoding, and edge encoding in the attention mechanism. These embeddings are input into a 12-layer transformer decoder in both PathSearcher and SeqFiller to predict the optimal node sequence and full amino acid sequence, respectively.