Based on symptom-herb mapping patterns learned by the model, this tool infers recommended herb combinations from input symptom patterns, or inversely infers the primary symptom patterns from herb combinations. It quantifies the correspondence between formulas and syndromes in traditional pattern differentiation and TCM learning, supporting clinical decision-making, TCM research, and interpretation of formula principles. Symptom inputs support semantic encoding, allowing terms not present in the dataset.