Update app.py

app.py

@@ -669,18 +669,18 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
 # =============================================================================
 # === START: S1-D · R1a · LNP Corona =========================================
 # =============================================================================
-        with gr.TabItem("S1-D · R1a · LNP Corona"):
-            gr.HTML(proj_badge("S1-D · R1a", "LNP Protein Corona (Serum)", "AUC = 0.791"))
-            with gr.Row():
-                sz = gr.Slider(50,300,value=100,step=1,label="Size (nm)")
-                zt = gr.Slider(-40,10,value=-5,step=1,label="Zeta (mV)")
-            with gr.Row():
-                pg = gr.Slider(0,5,value=1.5,step=0.1,label="PEG mol%")
-                lp = gr.Dropdown(["Ionizable","Cationic","Anionic","Neutral"],value="Ionizable",label="Lipid type")
-            b6 = gr.Button("Predict", variant="primary")
-            o6 = gr.Markdown()
-            gr.Examples([[100,-5,1.5,"Ionizable"],[80,5,0.5,"Cationic"]], inputs=[sz,zt,pg,lp])
-            b6.click(predict_corona, [sz,zt,pg,lp], o6)
+        # with gr.TabItem("S1-D · R1a · LNP Corona"):
+        #     gr.HTML(proj_badge("S1-D · R1a", "LNP Protein Corona (Serum)", "AUC = 0.791"))
+        #     with gr.Row():
+        #         sz = gr.Slider(50,300,value=100,step=1,label="Size (nm)")
+        #         zt = gr.Slider(-40,10,value=-5,step=1,label="Zeta (mV)")
+        #     with gr.Row():
+        #         pg = gr.Slider(0,5,value=1.5,step=0.1,label="PEG mol%")
+        #         lp = gr.Dropdown(["Ionizable","Cationic","Anionic","Neutral"],value="Ionizable",label="Lipid type")
+        #     b6 = gr.Button("Predict", variant="primary")
+        #     o6 = gr.Markdown()
+        #     gr.Examples([[100,-5,1.5,"Ionizable"],[80,5,0.5,"Cationic"]], inputs=[sz,zt,pg,lp])
+        #     b6.click(predict_corona, [sz,zt,pg,lp], o6)
 # =============================================================================
 # === END: S1-D · R1a =========================================================
 # =============================================================================
@@ -726,18 +726,18 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
 # =============================================================================
 # === START: S1-D · R4a · AutoCorona NLP =====================================
 # =============================================================================
-        with gr.TabItem("S1-D · R4a · AutoCorona NLP"):
-            gr.HTML(proj_badge("S1-D · R4a", "AutoCorona NLP — from abstracts", "F1 = 0.71"))
-            txt  = gr.Textbox(lines=5,label="Paper abstract",placeholder="Paste abstract here...")
-            b10  = gr.Button("Extract Data", variant="primary")
-            o10j = gr.Code(label="Extracted JSON", language="json")
-            o10f = gr.Textbox(label="Validation flags")
-            gr.Examples([[
-                "LNPs composed of MC3, DSPC, Cholesterol (50:10:40 mol%) with 1.5% PEG-DMG. "
-                "Hydrodynamic diameter was 98 nm, zeta potential -3.2 mV, PDI 0.12. "
-                "Incubated in human plasma. Corona: albumin, apolipoprotein E, fibrinogen."
-            ]], inputs=[txt])
-            b10.click(extract_corona, txt, [o10j, o10f])
+        # with gr.TabItem("S1-D · R4a · AutoCorona NLP"):
+        #     gr.HTML(proj_badge("S1-D · R4a", "AutoCorona NLP — from abstracts", "F1 = 0.71"))
+        #     txt  = gr.Textbox(lines=5,label="Paper abstract",placeholder="Paste abstract here...")
+        #     b10  = gr.Button("Extract Data", variant="primary")
+        #     o10j = gr.Code(label="Extracted JSON", language="json")
+        #     o10f = gr.Textbox(label="Validation flags")
+        #     gr.Examples([[
+        #         "LNPs composed of MC3, DSPC, Cholesterol (50:10:40 mol%) with 1.5% PEG-DMG. "
+        #         "Hydrodynamic diameter was 98 nm, zeta potential -3.2 mV, PDI 0.12. "
+        #         "Incubated in human plasma. Corona: albumin, apolipoprotein E, fibrinogen."
+        #     ]], inputs=[txt])
+        #     b10.click(extract_corona, txt, [o10j, o10f])
 # =============================================================================
 # === END: S1-D · R4a =========================================================
 # =============================================================================