Yin Fang commited on
Commit
8d62ec9
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1 Parent(s): 1def893

Update app.py

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Files changed (1) hide show
  1. app.py +6 -14
app.py CHANGED
@@ -139,7 +139,10 @@ def opt_process(opt_input):
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  results = data[(data['improvement']> 0) & (data['sim']>0.4)]
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  opt_output = results["candidates"].tolist()
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  opt_output_imp = results["improvement"].tolist()
 
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  opt_output_sim = results["sim"].tolist()
 
 
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  smis = [sf.decoder(i) for i in opt_output]
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  mols = []
@@ -153,18 +156,7 @@ def opt_process(opt_input):
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  subImgSize=(200,200),
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  legends=['' for x in mols]
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  )
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-
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- return opt_input_img, "\n".join(opt_output), opt_output_imp, opt_output_sim, opt_output_img
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- # examples = [
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-
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- # ['[C][C][=Branch1][C][=O][N][C][C][O][C][C][O][C][C][O][C][C][Ring1][N]'],['[C][C][S][C][C][S][C][C][C][S][C][C][S][C][Ring1][=C]']
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-
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- # ]
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-
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-
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-
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- # iface = gr.Interface(fn=greet, inputs="text", outputs="numpy", title="Molecular Language Model as Multi-task Generator",examples=examples)
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- # iface.launch()
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  with gr.Blocks() as demo:
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  gr.Markdown("# MolGen: Molecular Language Model as Multi-task Generator")
@@ -178,7 +170,7 @@ with gr.Blocks() as demo:
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  with gr.Column():
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  gen_output = gr.Textbox(label="Generation Results", lines=5, placeholder="")
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- gen_output_image = gr.Image(type='pil', label="Visualization")
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  gr.Examples(
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  examples=[["[C][=C][C][=C][C][=C][Ring1][=Branch1]"],
@@ -202,7 +194,7 @@ with gr.Blocks() as demo:
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  opt_output_imp = gr.Textbox(label="Optimization Property Improvements", lines=3, placeholder="")
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  opt_output_sim = gr.Textbox(label="Similarity", lines=3, placeholder="")
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  opt_output_img = gr.Textbox(label="Output Visualization", lines=3, placeholder="")
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- opt_output_img = gr.Image(type='pil', label="Output Visualization")
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  gr.Examples(
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  examples=[
 
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  results = data[(data['improvement']> 0) & (data['sim']>0.4)]
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  opt_output = results["candidates"].tolist()
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  opt_output_imp = results["improvement"].tolist()
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+ opt_output_imp = [str(i) for i in opt_output_imp]
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  opt_output_sim = results["sim"].tolist()
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+ opt_output_sim = [str(i) for i in opt_output_sim]
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+
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  smis = [sf.decoder(i) for i in opt_output]
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  mols = []
 
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  subImgSize=(200,200),
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  legends=['' for x in mols]
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  )
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+ return opt_input_img, "\n".join(opt_output), "\n".join(opt_output_imp), "\n".join(opt_output_sim), opt_output_img
 
 
 
 
 
 
 
 
 
 
 
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  with gr.Blocks() as demo:
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  gr.Markdown("# MolGen: Molecular Language Model as Multi-task Generator")
 
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  with gr.Column():
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  gen_output = gr.Textbox(label="Generation Results", lines=5, placeholder="")
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+ gen_output_image = gr.Image(label="Visualization")
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  gr.Examples(
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  examples=[["[C][=C][C][=C][C][=C][Ring1][=Branch1]"],
 
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  opt_output_imp = gr.Textbox(label="Optimization Property Improvements", lines=3, placeholder="")
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  opt_output_sim = gr.Textbox(label="Similarity", lines=3, placeholder="")
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  opt_output_img = gr.Textbox(label="Output Visualization", lines=3, placeholder="")
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+ opt_output_img = gr.Image(label="Output Visualization")
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  gr.Examples(
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  examples=[