willwim commited on
Commit
22b54b9
·
verified ·
1 Parent(s): f780603

Update app.py

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Files changed (1) hide show
  1. app.py +12 -8
app.py CHANGED
@@ -72,6 +72,7 @@ def adr_predict(x):
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  htext = "<p style='color: black;'>NER processing error.</p>"
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  label_output = {"Severe Reaction": float(scores[1]), "Non-severe Reaction": float(scores[0])}
 
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  return label_output, local_plot, htext
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  # FIX: Added !important tags to ensure Gradio's dark mode doesn't override the white background and black text
@@ -86,7 +87,7 @@ with gr.Blocks(title="ADR Detector") as demo:
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  with gr.Column(elem_classes="main-header"):
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  gr.Markdown("# Adverse Drug Reaction (ADR) Detector")
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  gr.Markdown("Analyze clinical text for potential medication-related severity and key medical entities.")
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-
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  with gr.Row():
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  with gr.Column(scale=1):
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  gr.Markdown("### Input")
@@ -106,20 +107,23 @@ with gr.Blocks(title="ADR Detector") as demo:
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  ],
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  inputs=[prob1]
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  )
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-
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  with gr.Column(scale=1):
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  gr.Markdown("### Classification")
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  label = gr.Label(label="Severity Probability")
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- with gr.Tabs():
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- with gr.TabItem("Medical Entities"):
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- htext = gr.HTML(label="NER Mapping", elem_classes="output-box")
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- with gr.TabItem("Model Logic (SHAP)"):
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- local_plot = gr.HTML(label='Feature Importance', elem_classes="output-box")
 
 
 
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  gr.Markdown("---")
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  gr.Markdown("Disclaimer: This tool is for research purposes only and does not constitute medical advice.")
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-
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  submit_btn.click(
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  fn=adr_predict,
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  inputs=[prob1],
 
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  htext = "<p style='color: black;'>NER processing error.</p>"
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  label_output = {"Severe Reaction": float(scores[1]), "Non-severe Reaction": float(scores[0])}
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+
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  return label_output, local_plot, htext
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  # FIX: Added !important tags to ensure Gradio's dark mode doesn't override the white background and black text
 
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  with gr.Column(elem_classes="main-header"):
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  gr.Markdown("# Adverse Drug Reaction (ADR) Detector")
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  gr.Markdown("Analyze clinical text for potential medication-related severity and key medical entities.")
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+
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  with gr.Row():
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  with gr.Column(scale=1):
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  gr.Markdown("### Input")
 
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  ],
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  inputs=[prob1]
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  )
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+
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  with gr.Column(scale=1):
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  gr.Markdown("### Classification")
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  label = gr.Label(label="Severity Probability")
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+ # --- TABS REMOVED HERE ---
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+ # Both components are now stacked sequentially in the column
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+
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+ gr.Markdown("### Medical Entities")
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+ htext = gr.HTML(label="NER Mapping", elem_classes="output-box")
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+
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+ gr.Markdown("### Model Logic (SHAP)")
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+ local_plot = gr.HTML(label='Feature Importance', elem_classes="output-box")
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  gr.Markdown("---")
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  gr.Markdown("Disclaimer: This tool is for research purposes only and does not constitute medical advice.")
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+
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  submit_btn.click(
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  fn=adr_predict,
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  inputs=[prob1],