Add .csv download, add inputs info

app.py

@@ -7,6 +7,7 @@ from functools import partial
 import gradio as gr
 import torch
 import numpy as np
+import pandas as pd
 from Bio.PDB.Polypeptide import protein_letters_3to1
 from biopandas.pdb import PandasPdb
 from colour import Color
@@ -229,10 +230,14 @@ def predict(models, temp_dir, *inputs):
     ddg = np.round(ddg, 3)
     df = list(zip(muts, ddg))
 
+    # Create dataframe file
+    path = 'ppiformer_ddg_predictions.csv'
+    pd.DataFrame(df).rename(columns={0: "Mutation", 1: "ddG [kcal/mol]"}).to_csv(path, index=False)
+
     # Create 3DMol plot
     plot = plot_3dmol(pdb_path, ppi_path, muts, attn)
 
-    return df, plot
+    return df, path, plot
 
 
 app = gr.Blocks(theme=gr.themes.Default(primary_hue="green", secondary_hue="pink"))
@@ -261,13 +266,13 @@ with app:
         with gr.Column():
             gr.Markdown("## PPI structure")
             with gr.Row():
-                pdb_code = gr.Textbox(placeholder="1BUI", label="PDB code")
-                partners = gr.Textbox(placeholder="A,B,C", label="Partners")
+                pdb_code = gr.Textbox(placeholder="1BUI", label="PDB code", info="Protein Data Bank code (https://www.rcsb.org/)")
+                partners = gr.Textbox(placeholder="A,B,C", label="Partners", info="Protein chains in the PDB file forming the PPI interface")
             pdb_path = gr.File(file_count="single", label="Or PDB file instead of PDB code")
 
         with gr.Column():
             gr.Markdown("## Mutations")
-            muts = gr.Textbox(placeholder="SC16A,FC47A", label="List of (multi-point) mutations")
+            muts = gr.Textbox(placeholder="SC16A;FC47A;SC16A,FC47A", label="List of (multi-point) mutations", info="SC16A,FC47A;SC16A;FC47A for three mutations: serine to alanine at position 16 in chain C, phenylalanine to alanine at position 47 in chain C, and their double-point combination")
             muts_path = gr.File(file_count="single", label="Or file with mutations")
 
     examples = gr.Examples(
@@ -285,6 +290,7 @@ with app:
 
     # Output GUI
     gr.Markdown("## Predictions")
+    df_file = gr.File(label="Download predictions as .csv", interactive=False, visible=True)
     df = gr.Dataframe(
         headers=["Mutation", "ddG [kcal/mol]"],
         datatype=["str", "number"],
@@ -310,7 +316,7 @@ with app:
 
     # Main logic
     inputs = [pdb_code, pdb_path, partners, muts, muts_path]
-    outputs = [df, plot]
+    outputs = [df, df_file, plot]
     predict = partial(predict, models, temp_dir)
     predict_button.click(predict, inputs=inputs, outputs=outputs)