Update app.py

app.py

@@ -22,6 +22,7 @@ import gradio as gr
 import pandas as pd
 from matplotlib.backends.backend_agg import FigureCanvasAgg
 import PIL.Image as Image
+import matplotlib.pyplot as plt
 warnings.filterwarnings("ignore")
 
 Eluent_smiles=['CCCCCC','CC(OCC)=O','C(Cl)Cl','CO','CCOCC']
@@ -461,7 +462,7 @@ if __name__=='__main__':
     Citation1: H. Xu, J. Lin, Q. Liu, Y. Chen, J. Zhang, Y. Yang, M.C. Young, Y. Xu, D. Zhang, F. Mo
     High-throughput discovery of chemical structure-polarity relationships combining automation and machine-learning techniques
     Chem (2022), 3202–3214, 10.1016/j.chempr.2022.08.008\n
-    Citation2: https://huggingface.co/spaces/woshixuhao/Rf_compare
+    Citation2: https://huggingface.co/spaces/woshixuhao/Rf_prediction
     ## Function\n
     Single predict: predict a compound under a given eluent system\n
     Batch predict: Upload a .csv file with multiple conditions to conduct batch prediction\n
@@ -482,7 +483,7 @@ if __name__=='__main__':
             gr.Interface(fn=predict_xlsx,description='please upload a .csv file formatted in the form of the example', inputs="file", outputs="file",examples=[os.path.join(os.path.dirname(__file__),"TLC_1.csv")],cache_examples=True)
         with gr.Tab("Rf compare"):
             gr.Interface(fn=predict_compare, inputs=["text", "text"], outputs=["image","image","image"],
-                         description='input: smiles of two compounds, such as CC(OCC)=O and CC(C)CCC(NC(C)C)=O\n output: three images that show the Rf curve with different eluent ratios under PE/EA, DCM/MeOH, PE/Et2O system.\n\n')
+                         description='input: smiles of two compounds, such as CC(OCC)=O and CCOCC\n output: three images that show the Rf curve with different eluent ratios under PE/EA, DCM/MeOH, PE/Et2O system.\n\n')
     demo.launch()
     # smile='O=C(OC1C(OC(C)=O)C(OC(C)=O)C(OC(C)=O)C(COC(C)=O)O1)C'
     # eluent=[0,0.9,0,0,0]