Update app.py

app.py

@@ -11,6 +11,7 @@ from datetime import datetime
 from pathlib import Path
 import plotly.graph_objects as go
 import plotly.express as px
+import tabulate  # для коректної роботи to_markdown()
 
 # ========== Діагностичний друк ==========
 print("Gradio version:", gr.__version__)
@@ -39,21 +40,24 @@ def log_entry(tab, inputs, result, note=""):
             w.writerow({"timestamp": datetime.now().strftime("%Y-%m-%d %H:%M"),
                         "tab": tab, "inputs": str(inputs),
                         "result": str(result)[:200], "note": note})
-    except Exception: pass
+    except Exception as e:
+        print(f"Log error: {e}")
 
 def load_journal():
     try:
-        if not LOG_PATH.exists():
+        if not LOG_PATH.exists() or LOG_PATH.stat().st_size == 0:
             return "No entries yet."
         df = pd.read_csv(LOG_PATH)
         if df.empty:
             return "No entries yet."
         return df.tail(20).to_markdown(index=False)
-    except Exception:
+    except Exception as e:
+        print(f"Journal load error: {e}")
         return "Error loading journal."
 
 def save_note(note, tab):
-    log_entry(tab, "manual note", note, note)
+    if note.strip():
+        log_entry(tab, "manual note", note, note)
     return load_journal()
 
 def clear_journal():
@@ -608,7 +612,7 @@ body, .gradio-container {{ background: {BG} !important; color: {TXT} !important;
     background: {BG} !important;
 }}
 
-/* Контейнер вкладок всередині основної колонки */
+/* Контейнер вкладок всередині основної колонки (R1, R2, ...) */
 .main-tabs .tab-nav button {{
     color: {DIM} !important;
     background: {BG} !important;
@@ -633,6 +637,19 @@ body, .gradio-container {{ background: {BG} !important; color: {TXT} !important;
     padding: 14px !important;
 }}
 
+/* Третій рівень вкладок (a, b) */
+.sub-tabs .tab-nav button {{
+    color: {DIM} !important;
+    background: {CARD} !important;
+    font-size: 11px !important;
+    padding: 3px 8px !important;
+    border-radius: 3px 3px 0 0 !important;
+}}
+.sub-tabs .tab-nav button.selected {{
+    color: {ACC} !important;
+    background: {BG} !important;
+}}
+
 /* Стиль для badges */
 .proj-badge {{
     background: {CARD};
@@ -741,7 +758,7 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                     with gr.Tabs(elem_classes="main-tabs"):
                         # R1 · Variant classification
                         with gr.TabItem("R1 · Variant classification"):
-                            with gr.Tabs():
+                            with gr.Tabs(elem_classes="sub-tabs"):
                                 # R1a · OpenVariant
                                 with gr.TabItem("R1a · OpenVariant"):
                                     gr.HTML(proj_badge("S1-A · R1a", "OpenVariant — SNV Pathogenicity Classifier", "AUC=0.939"))
@@ -771,7 +788,7 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                     with gr.Tabs(elem_classes="main-tabs"):
                         # R1 · miRNA silencing
                         with gr.TabItem("R1 · miRNA silencing"):
-                            with gr.Tabs():
+                            with gr.Tabs(elem_classes="sub-tabs"):
                                 with gr.TabItem("R1a · BRCA2 miRNA"):
                                     gr.HTML(proj_badge("S1-B · R1a", "miRNA Silencing — BRCA1/2 · TP53"))
                                     g1 = gr.Dropdown(["BRCA2","BRCA1","TP53"], value="BRCA2", label="Gene")
@@ -781,7 +798,7 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                                     b1.click(predict_mirna, [g1], o1)
                         # R2 · siRNA SL
                         with gr.TabItem("R2 · siRNA SL"):
-                            with gr.Tabs():
+                            with gr.Tabs(elem_classes="sub-tabs"):
                                 with gr.TabItem("R2a · TP53 siRNA"):
                                     gr.HTML(proj_badge("S1-B · R2a", "siRNA Synthetic Lethal — TP53-null"))
                                     g2 = gr.Dropdown(["LUAD","BRCA","COAD"], value="LUAD", label="Cancer type")
@@ -791,7 +808,7 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                                     b2.click(predict_sirna, [g2], o2)
                         # R3 · lncRNA + ASO
                         with gr.TabItem("R3 · lncRNA + ASO"):
-                            with gr.Tabs():
+                            with gr.Tabs(elem_classes="sub-tabs"):
                                 with gr.TabItem("R3a · lncRNA-TREM2"):
                                     gr.HTML(proj_badge("S1-B · R3a", "lncRNA-TREM2 ceRNA Network"))
                                     b3a = gr.Button("Load ceRNA", variant="primary")
@@ -812,7 +829,7 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                     with gr.Tabs(elem_classes="main-tabs"):
                         # R1 · RNA-directed drug
                         with gr.TabItem("R1 · RNA-directed drug"):
-                            with gr.Tabs():
+                            with gr.Tabs(elem_classes="sub-tabs"):
                                 with gr.TabItem("R1a · FGFR3 RNA Drug"):
                                     gr.HTML(proj_badge("S1-C · R1a", "FGFR3 RNA-Directed Drug Discovery", "top score 0.793"))
                                     g4 = gr.Radio(["P1 (hairpin loop)","P10 (G-quadruplex)"],
@@ -827,7 +844,7 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                                     gr.Markdown("> In development. Coming soon.")
                         # R2 · Frontier
                         with gr.TabItem("R2 · Frontier"):
-                            with gr.Tabs():
+                            with gr.Tabs(elem_classes="sub-tabs"):
                                 with gr.TabItem("R2a · m6A×Ferroptosis×Circadian 🔴⭐"):
                                     gr.HTML(proj_badge("S1-C · R2a", "m6A × Ferroptosis × Circadian", "🔴 Frontier"))
                                     gr.Markdown(
@@ -845,7 +862,7 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                     with gr.Tabs(elem_classes="main-tabs"):
                         # R1 · Serum corona
                         with gr.TabItem("R1 · Serum corona"):
-                            with gr.Tabs():
+                            with gr.Tabs(elem_classes="sub-tabs"):
                                 with gr.TabItem("R1a · LNP Corona ML"):
                                     gr.HTML(proj_badge("S1-D · R1a", "LNP Protein Corona (Serum)", "AUC=0.791"))
                                     with gr.Row():
@@ -860,7 +877,7 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                                     b6.click(predict_corona, [sz,zt,pg,lp], o6)
                         # R2 · Flow corona
                         with gr.TabItem("R2 · Flow corona"):
-                            with gr.Tabs():
+                            with gr.Tabs(elem_classes="sub-tabs"):
                                 with gr.TabItem("R2a · Flow Corona"):
                                     gr.HTML(proj_badge("S1-D · R2a", "Flow Corona — Vroman Effect"))
                                     with gr.Row():
@@ -877,7 +894,7 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                                     b8.click(predict_flow, [s8,z8,pg8,ch8,fl8], [o8t,o8p])
                         # R3 · Brain BBB
                         with gr.TabItem("R3 · Brain BBB"):
-                            with gr.Tabs():
+                            with gr.Tabs(elem_classes="sub-tabs"):
                                 with gr.TabItem("R3a · LNP Brain"):
                                     gr.HTML(proj_badge("S1-D · R3a", "LNP Brain Delivery"))
                                     smi = gr.Textbox(label="Ionizable lipid SMILES",
@@ -892,7 +909,7 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                                     b9.click(predict_bbb, [smi,pk,zt9], [o9t,o9p])
                         # R4 · NLP
                         with gr.TabItem("R4 · NLP"):
-                            with gr.Tabs():
+                            with gr.Tabs(elem_classes="sub-tabs"):
                                 with gr.TabItem("R4a · AutoCorona NLP"):
                                     gr.HTML(proj_badge("S1-D · R4a", "AutoCorona NLP", "F1=0.71"))
                                     txt  = gr.Textbox(lines=5,label="Paper abstract",placeholder="Paste abstract here...")
@@ -907,7 +924,7 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                                     b10.click(extract_corona, txt, [o10j, o10f])
                         # R5 · Exotic fluids
                         with gr.TabItem("R5 · Exotic fluids 🔴⭐"):
-                            with gr.Tabs():
+                            with gr.Tabs(elem_classes="sub-tabs"):
                                 with gr.TabItem("R5a · CSF/Vitreous/BM"):
                                     gr.HTML(proj_badge("S1-D · R5a", "LNP Corona in CSF · Vitreous · Bone Marrow", "🔴 0 prior studies"))
                                     gr.Markdown(
@@ -925,7 +942,7 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                     ))
                     with gr.Tabs(elem_classes="main-tabs"):
                         with gr.TabItem("R1 · Liquid biopsy"):
-                            with gr.Tabs():
+                            with gr.Tabs(elem_classes="sub-tabs"):
                                 with gr.TabItem("R1a · Liquid Biopsy"):
                                     gr.HTML(proj_badge("S1-E · R1a", "Liquid Biopsy Classifier", "AUC=0.992*"))
                                     with gr.Row():
@@ -960,7 +977,7 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                     with gr.Tabs(elem_classes="main-tabs"):
                         # R1 · DIPG
                         with gr.TabItem("R1 · DIPG"):
-                            with gr.Tabs():
+                            with gr.Tabs(elem_classes="sub-tabs"):
                                 with gr.TabItem("R1a · DIPG Toolkit"):
                                     gr.HTML(proj_badge("S1-F · R1a", "DIPG Toolkit", "PBTA · GSE126319"))
                                     gr.Markdown(
@@ -994,7 +1011,7 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                                             )
                         # R2 · UVM
                         with gr.TabItem("R2 · UVM"):
-                            with gr.Tabs():
+                            with gr.Tabs(elem_classes="sub-tabs"):
                                 with gr.TabItem("R2a · UVM Toolkit"):
                                     gr.HTML(proj_badge("S1-F · R2a", "UVM Toolkit", "TCGA-UVM n=80"))
                                     gr.Markdown(
@@ -1024,7 +1041,7 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                                             )
                         # R3 · pAML
                         with gr.TabItem("R3 · pAML"):
-                            with gr.Tabs():
+                            with gr.Tabs(elem_classes="sub-tabs"):
                                 with gr.TabItem("R3a · pAML Toolkit"):
                                     gr.HTML(proj_badge("S1-F · R3a", "pAML Toolkit", "TARGET-AML n≈197"))
                                     gr.Markdown(