Duplicate from arcosx/CHO-cytotoxicity

.gitattributes

@@ -0,0 +1,35 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,14 @@
+---
+title: CHO Cytotoxicity
+emoji: 🐠
+colorFrom: blue
+colorTo: gray
+sdk: gradio
+sdk_version: 3.36.1
+app_file: app.py
+pinned: false
+license: apache-2.0
+duplicated_from: arcosx/CHO-cytotoxicity
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,42 @@
+import gradio as gr
+import pandas as pd
+from rdkit import Chem
+from rdkit.Chem import AllChem
+import joblib
+
+model = joblib.load('CHO.pkl')
+
+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
+
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        with gr.Column():
+            inputs=gr.Textbox(lines=2, label="Please enter SMILES for the compound")
+            with gr.Row():
+                btn = gr.Button(variant="primary",value="submit")
+                clear_btn = gr.ClearButton(value="clear")
+        with gr.Column():
+            outputs=gr.Textbox(lines=1, label="Predicted CHO cytotoxicity of the chemical is:",info="Unit: Molar Concentration")
+
+    btn.click(predict, inputs=[inputs], outputs=[outputs])
+    clear_btn.add([inputs,outputs])
+
+    gr.Examples(
+        [["O=C(O)CBr"],["O=CC(Br)(Br)Br"],["IC(Br)Br"]],
+        [inputs],
+    )
+
+
+demo.launch()

requirements.txt

@@ -0,0 +1,6 @@
+gradio==3.36.1
+joblib==1.3.1
+pandas==2.0.3
+rdkit==2023.3.2
+scikit-learn==1.3.0
+gradio_client==0.2.7