import time import json import gradio as gr from gradio_molecule3d import Molecule3D def predict (input_seq_1, input_msa_1, input_protein_1, input_seq_2,input_msa_2, input_protein_2): start_time = time.time() # Do inference here # return an output pdb file with the protein and two chains A and B. # also return a JSON with any metrics you want to report metrics = {"mean_plddt": 80, "binding_affinity": 2} end_time = time.time() run_time = end_time - start_time return "test_out.pdb",json.dumps(metrics), run_time with gr.Blocks() as app: gr.Markdown("# Template for inference") gr.Markdown("Title, description, and other information about the model") with gr.Row(): with gr.Column(): input_seq_1 = gr.Textbox(lines=3, label="Input Protein 1 sequence (FASTA)") input_msa_1 = gr.File(label="Input MSA Protein 1 (A3M)") input_protein_1 = gr.File(label="Input Protein 2 monomer (PDB)") with gr.Column(): input_seq_2 = gr.Textbox(lines=3, label="Input Protein 2 sequence (FASTA)") input_msa_2 = gr.File(label="Input MSA Protein 2 (A3M)") input_protein_2 = gr.File(label="Input Protein 2 structure (PDB)") # define any options here # for automated inference the default options are used # slider_option = gr.Slider(0,10, label="Slider Option") # checkbox_option = gr.Checkbox(label="Checkbox Option") # dropdown_option = gr.Dropdown(["Option 1", "Option 2", "Option 3"], label="Radio Option") btn = gr.Button("Run Inference") gr.Examples( [ [ "GSGSPLAQQIKNIHSFIHQAKAAGRMDEVRTLQENLHQLMHEYFQQSD", "3v1c_A.pdb", "GSGSPLAQQIKNIHSFIHQAKAAGRMDEVRTLQENLHQLMHEYFQQSD", "3v1c_B.pdb", ], ], [input_seq_1, input_protein_1, input_seq_2, input_protein_2], ) reps = [ { "model": 0, "style": "cartoon", "chain": "A", "color": "whiteCarbon", }, { "model": 0, "style": "cartoon", "chain": "B", "color": "greenCarbon", }, { "model": 0, "chain": "A", "style": "stick", "sidechain": True, "color": "whiteCarbon", }, { "model": 0, "chain": "B", "style": "stick", "sidechain": True, "color": "greenCarbon" } ] # outputs out = Molecule3D(reps=reps) metrics = gr.JSON(label="Metrics") run_time = gr.Textbox(label="Runtime") btn.click(predict, inputs=[input_seq_1, input_msa_1, input_protein_1, input_seq_2, input_msa_2, input_protein_2], outputs=[out, metrics, run_time]) app.launch()