finish main

app.py

@@ -1,7 +1,25 @@
 import gradio as gr
+import pandas as pd
+from rdkit import Chem
+from rdkit.Chem import AllChem
+import joblib
 
-def greet(name):
-    return "Hello " + name + "!!"
+model = joblib.load('CHO.pkl')
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
+def predict(smiles):
+    if smiles.strip() == "":
+        raise gr.Error("SMILES input error")
+
+    mol = Chem.MolFromSmiles(smiles)
+    if mol == None:
+        raise gr.Error("SMILES input error")
+    mol_ECFP4 = list(AllChem.GetMorganFingerprintAsBitVect(mol, 2, nBits=1024).ToBitString())
+    preprocess_data = pd.DataFrame([mol_ECFP4])
+    result = model.predict(preprocess_data)
+    postprocess_data = '{:.2e}'.format(pow(10, result[0]))
+    return postprocess_data
+
+iface = gr.Interface(fn=predict, inputs=gr.Textbox(lines=2, label="Chemical substance SMILES"), 
+                     outputs=gr.Textbox(lines=1, label="Cytotoxicity of disinfection byproducts in CHO cells",info="Unit of measurement: molar concentration"),
+                     examples=[["O=C(O)CBr"],["O=CC(Br)(Br)Br"],["IC(Br)Br"]],allow_flagging="never")
 iface.launch()

requirements.txt

@@ -0,0 +1,5 @@
+gradio==3.36.1
+joblib==1.3.1
+pandas==2.0.3
+rdkit==2023.3.2
+sklearn==0.0.post5