Update app.py

app.py

@@ -12,6 +12,7 @@ from pathlib import Path
 import sys
 
 import numpy as np
+from Bio import SeqIO
 from Bio.Align import PairwiseAligner
 # from email_validator import validate_email
 import gradio as gr
@@ -1178,11 +1179,25 @@ QALAHAYFAQYHDPDDEPVADPYDQSFESRDLLIDEWKSLTYDEVISFVPPPLDQEEMES
                 if library in TARGET_LIBRARY_MAP.keys():
                     identify_df = pd.read_csv(Path('data/target_libraries', TARGET_LIBRARY_MAP[library]))
                 else:
-                    identify_df = pd.read_csv(library_upload)
+                    if library_upload.endswith('.csv'):
+                        identify_df = pd.read_csv(library_upload)
+                    elif library_upload.endswith('.fasta'):
+                        records = list(SeqIO.parse(library_upload, "fasta"))
+                        id2 = [record.id for record in records]
+                        seq = [str(record.seq) for record in records]
+                        identify_df = pd.DataFrame({'ID2': id2, 'X2': seq})
+                    else:
+                        raise 'Currently only csv and fasta files are supported.'
                     validate_columns(identify_df, ['X2'])
 
                 identify_df['X1'] = smiles
-
+                if not np.isin('ID1', identify_df.columns):
+                    identify_df['ID1'] = 'Input'
+                if not np.isin('ID2', identify_df.columns):
+                    identify_df['ID2'] = list(range(identify_df.shape[0]))
+                identify_df = identify_df.loc[:, ['ID1', 'X1', 'ID2', 'X2']]
+                identify_df['Y'] = 0
+                
                 job_id = uuid4()
                 temp_file = Path(f'{job_id}_input.csv').resolve()
                 identify_df.to_csv(temp_file, index=False)