Update app.py

app.py

@@ -466,18 +466,18 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
     with gr.Tabs(elem_classes="outer-tabs"):
 
         # ── 🗺️ MAP ─────────────────────────────────────────
-        with gr.TabItem("🗺️ Lab Map"):
+        with gr.Tab("🗺️ Lab Map"):
             gr.HTML(MAP_HTML)
 
         # ── 🧬 S1-A · PHYLO-GENOMICS ───────────────────────
-        with gr.TabItem("🧬 S1-A PHYLO-GENOMICS"):
+        with gr.Tab("🧬 S1-A PHYLO-GENOMICS"):
             gr.HTML(section_header(
                 "S1-A", "PHYLO-GENOMICS", "— What breaks in DNA",
                 "S1-R1 OpenVariant ✅  ·  S1-R1b Somatic classifier 🔶  ·  S1-R12a Rare variants 🔴"
             ))
             with gr.Tabs(elem_classes="inner-tabs"):
 
-                with gr.TabItem("S1-R1 · OpenVariant"):
+                with gr.Tab("S1-R1 · OpenVariant"):
                     gr.HTML(proj_badge("S1-A · PHYLO-GENOMICS · S1-R1",
                                        "OpenVariant — SNV Pathogenicity Classifier", "AUC = 0.939"))
                     hgvs = gr.Textbox(label="HGVS notation", placeholder="BRCA1:p.R1699Q")
@@ -493,20 +493,20 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                                  ["BRCA2:p.D2723A",0.01,0.98,0.0]], inputs=[hgvs,sift,pp,gn])
                     b_v.click(predict_variant, [hgvs,sift,pp,gn], o_v)
 
-                with gr.TabItem("S1-R1b · Somatic 🔶"):
+                with gr.Tab("S1-R1b · Somatic 🔶"):
                     gr.HTML(proj_badge("S1-A · PHYLO-GENOMICS · S1-R1b",
                                        "Somatic Mutation Classifier — BRCA · LUAD panels", "🔶 In progress"))
                     gr.Markdown("> This module is in active development. Coming in the next release.")
 
         # ── 🔬 S1-B · PHYLO-RNA ────────────────────────────
-        with gr.TabItem("🔬 S1-B PHYLO-RNA"):
+        with gr.Tab("🔬 S1-B PHYLO-RNA"):
             gr.HTML(section_header(
                 "S1-B", "PHYLO-RNA", "— How to silence it via RNA",
                 "S1-R2 miRNA ✅  ·  S1-R3 siRNA ✅  ·  S1-R4 lncRNA ✅  ·  S1-R4b ASO ✅"
             ))
             with gr.Tabs(elem_classes="inner-tabs"):
 
-                with gr.TabItem("S1-R2 · miRNA"):
+                with gr.Tab("S1-R2 · miRNA"):
                     gr.HTML(proj_badge("S1-B · PHYLO-RNA · S1-R2",
                                        "miRNA Silencing — BRCA1/2 · TP53 tumor suppressors"))
                     g1 = gr.Dropdown(["BRCA2","BRCA1","TP53"], value="BRCA2", label="Gene")
@@ -515,7 +515,7 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                     gr.Examples([["BRCA2"],["BRCA1"],["TP53"]], inputs=[g1])
                     b1.click(predict_mirna, g1, o1)
 
-                with gr.TabItem("S1-R3 · siRNA"):
+                with gr.Tab("S1-R3 · siRNA"):
                     gr.HTML(proj_badge("S1-B · PHYLO-RNA · S1-R3",
                                        "siRNA Synthetic Lethal — TP53-null · LUAD · BRCA · COAD"))
                     g2 = gr.Dropdown(["LUAD","BRCA","COAD"], value="LUAD", label="Cancer type")
@@ -524,7 +524,7 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                     gr.Examples([["LUAD"],["BRCA"],["COAD"]], inputs=[g2])
                     b2.click(predict_sirna, g2, o2)
 
-                with gr.TabItem("S1-R4 · lncRNA + ASO"):
+                with gr.Tab("S1-R4 · lncRNA + ASO"):
                     gr.HTML(proj_badge("S1-B · PHYLO-RNA · S1-R4 + S1-R4b",
                                        "lncRNA-TREM2 ceRNA Network + ASO Candidates · Alzheimer neuroinflammation"))
                     b3 = gr.Button("Load Results", variant="primary")
@@ -533,14 +533,14 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                     b3.click(get_lncrna, [], [o3a, o3b])
 
         # ── 💊 S1-C · PHYLO-DRUG ───────────────────────────
-        with gr.TabItem("💊 S1-C PHYLO-DRUG"):
+        with gr.Tab("💊 S1-C PHYLO-DRUG"):
             gr.HTML(section_header(
                 "S1-C", "PHYLO-DRUG", "— Which molecule treats it",
                 "S1-R5 FGFR3 ✅  ·  S1-R5b SL drug mapping 🔶  ·  S1-R13 m6A×Ferroptosis×Circadian 🔴⭐"
             ))
             with gr.Tabs(elem_classes="inner-tabs"):
 
-                with gr.TabItem("S1-R5 · FGFR3"):
+                with gr.Tab("S1-R5 · FGFR3"):
                     gr.HTML(proj_badge("S1-C · PHYLO-DRUG · S1-R5",
                                        "FGFR3 RNA-Directed Drug Discovery · ChEMBL screen",
                                        "top score 0.793"))
@@ -552,7 +552,7 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                     gr.Examples([["P1 (hairpin loop)"],["P10 (G-quadruplex)"]], inputs=[g4])
                     b4.click(predict_drug, g4, [o4t, o4p])
 
-                with gr.TabItem("S1-R13 · Frontier 🔴⭐"):
+                with gr.Tab("S1-R13 · Frontier 🔴⭐"):
                     gr.HTML(proj_badge("S1-C · PHYLO-DRUG · S1-R13",
                                        "m6A × Ferroptosis × Circadian — Pan-cancer triad", "🔴 Frontier"))
                     gr.Markdown(
@@ -562,14 +562,14 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                     )
 
         # ── 🧪 S1-D · PHYLO-LNP ────────────────────────────
-        with gr.TabItem("🧪 S1-D PHYLO-LNP"):
+        with gr.Tab("🧪 S1-D PHYLO-LNP"):
             gr.HTML(section_header(
                 "S1-D", "PHYLO-LNP", "— How to deliver the drug to the cell",
                 "S1-R6 Corona ✅ · S1-R7 Flow ✅ · S1-R8 Brain ✅ · S1-R10 NLP ✅ · S1-R11 CSF/BM 🔴⭐"
             ))
             with gr.Tabs(elem_classes="inner-tabs"):
 
-                with gr.TabItem("S1-R6 · Corona"):
+                with gr.Tab("S1-R6 · Corona"):
                     gr.HTML(proj_badge("S1-D · PHYLO-LNP · S1-R6",
                                        "LNP Protein Corona (Serum)", "AUC = 0.791"))
                     with gr.Row():
@@ -582,7 +582,7 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                     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-R7 · Flow"):
+                with gr.Tab("S1-R7 · Flow"):
                     gr.HTML(proj_badge("S1-D · PHYLO-LNP · S1-R7",
                                        "Flow Corona — Vroman Effect · albumin→ApoE kinetics"))
                     with gr.Row():
@@ -597,7 +597,7 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                     gr.Examples([[100,-5,1.5,"Ionizable",40],[150,5,0.5,"Cationic",10]], inputs=[s8,z8,pg8,ch8,fl8])
                     b8.click(predict_flow, [s8,z8,pg8,ch8,fl8], [o8t,o8p])
 
-                with gr.TabItem("S1-R8 · Brain"):
+                with gr.Tab("S1-R8 · Brain"):
                     gr.HTML(proj_badge("S1-D · PHYLO-LNP · S1-R8",
                                        "LNP Brain Delivery — ApoE% + BBB probability"))
                     smi = gr.Textbox(label="Ionizable lipid SMILES",
@@ -610,7 +610,7 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                     gr.Examples([["CC(C)CC(=O)OCC(COC(=O)CC(C)C)OC(=O)CC(C)C",6.5,-3]], inputs=[smi,pk,zt9])
                     b9.click(predict_bbb, [smi,pk,zt9], [o9t,o9p])
 
-                with gr.TabItem("S1-R10 · NLP"):
+                with gr.Tab("S1-R10 · NLP"):
                     gr.HTML(proj_badge("S1-D · PHYLO-LNP · S1-R10",
                                        "AutoCorona NLP — structured data from PMC abstracts", "F1 = 0.71"))
                     txt  = gr.Textbox(lines=5,label="Paper abstract",placeholder="Paste abstract here...")
@@ -624,7 +624,7 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                     ]], inputs=[txt])
                     b10.click(extract_corona, txt, [o10j, o10f])
 
-                with gr.TabItem("S1-R11 · CSF/BM 🔴⭐"):
+                with gr.Tab("S1-R11 · CSF/BM 🔴⭐"):
                     gr.HTML(proj_badge("S1-D · PHYLO-LNP · S1-R11",
                                        "LNP Corona in CSF · Vitreous · Bone Marrow", "🔴 0 prior studies"))
                     gr.Markdown(
@@ -635,14 +635,14 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                     )
 
         # ── 🩸 S1-E · PHYLO-BIOMARKERS ─────────────────────
-        with gr.TabItem("🩸 S1-E PHYLO-BIOMARKERS"):
+        with gr.Tab("🩸 S1-E PHYLO-BIOMARKERS"):
             gr.HTML(section_header(
                 "S1-E", "PHYLO-BIOMARKERS", "— Detect cancer without tissue biopsy",
                 "S1-R9 Liquid Biopsy ✅  ·  S1-R9b Panel validator 🔶  ·  S1-R9c ctDNA gap 🔴"
             ))
             with gr.Tabs(elem_classes="inner-tabs"):
 
-                with gr.TabItem("S1-R9 · Liquid Biopsy"):
+                with gr.Tab("S1-R9 · Liquid Biopsy"):
                     gr.HTML(proj_badge("S1-E · PHYLO-BIOMARKERS · S1-R9",
                                        "Liquid Biopsy Classifier — CTHRC1 · FHL2 · LDHA panel",
                                        "AUC = 0.992*"))
@@ -664,13 +664,13 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                                 inputs=[p1,p2,p3,p4,p5,p6,p7,p8,p9,p10])
                     b7.click(predict_cancer, [p1,p2,p3,p4,p5,p6,p7,p8,p9,p10], [o7t,o7p])
 
-                with gr.TabItem("S1-R9b · Validator 🔶"):
+                with gr.Tab("S1-R9b · Validator 🔶"):
                     gr.HTML(proj_badge("S1-E · PHYLO-BIOMARKERS · S1-R9b",
                                        "Protein Panel Validator — multi-cancer plasma validation", "🔶 In progress"))
                     gr.Markdown("> Coming next — validates S1-R9 results against GEO plasma proteomics datasets.")
 
         # ── 📓 JOURNAL ──────────────────────────────────────
-        with gr.TabItem("📓 Journal"):
+        with gr.Tab("📓 Journal"):
             gr.Markdown("### Lab Journal\nEvery tool call auto-logged with project code.")
             with gr.Row():
                 note_text = gr.Textbox(label="📝 Observation", placeholder="What did you discover?", lines=3)
@@ -684,7 +684,7 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
             save_btn.click(save_note, [note_text,note_tab,note_last], [save_msg,journal_df])
 
         # ── 📚 LEARNING ─────────────────────────────────────
-        with gr.TabItem("📚 Learning"):
+        with gr.Tab("📚 Learning"):
             gr.Markdown("""
 ## 🧪 Guided Investigations — S1 Biomedical
 > 🟢 Beginner → 🟡 Intermediate → 🔴 Advanced