Phonon anharmonicity can provide solutions to many aspects of fundamental problems such as the thermal properties, mechanical properties, and phase transition behavior in crystals. The emerging hybrid machine learning and DFT-based tools like the HiPhive package make highorder force constants extraction accessible with acceptable computational costs. However, any model with abundant parameters faces the dilemma of prediction accuracy and the consumed time of determining and benchmarking parameters for specific systems. Here, we incorporate all necessary steps into a smooth pipeline with pre-tested parameters from evaluations in diverse materials and demonstrated accuracy against experimental measurements. The ultimate goal of this work is to produce the same level of accurate results as direct calculations from Phonopy (harmonic phonons) and Phono3py (anharmonic properties) but with much less computational expense and at a large scale.