Update app.py

app.py

@@ -1,10 +1,6 @@
 # -*- coding: utf-8 -*-
 """
 Verbatify — Analyse sémantique NPS (Paste-only, NPS inféré)
-- Entrée : verbatims collés (1 par ligne, score NPS optionnel après |)
-- Sorties : émotion, thématiques, occurrences, synthèse, graphiques Plotly + exports
-- IA (facultatif) : OpenAI (robuste), fallback CamemBERT si installé, puis règles
-- Branding : thème Plotly + CSS Manrope intégrés, logo inline (aucun fichier externe)
 """
 
 import os, re, json, collections, tempfile, zipfile
@@ -15,194 +11,172 @@ import plotly.express as px
 import plotly.graph_objects as go
 import plotly.io as pio
 
-# ---------------- Branding Verbatify (CSS + Plotly) ----------------
+# ====================== BRANDING (CSS + PLOTLY) ======================
+
 VB_CSS = r"""
 @import url('https://fonts.googleapis.com/css2?family=Manrope:wght@400;600;700;800&display=swap');
 
-/* ---------- Palette Verbatify ---------- */
 :root{
-  --vb-bg:#F7FAFF;
-  --vb-card:#FFFFFF;
-  --vb-text:#0F172A;
-  --vb-muted:#475569;
-  --vb-primary:#7C3AED;     /* violet */
-  --vb-primary-2:#06B6D4;   /* cyan */
-  --vb-border:#E7EEF7;      /* bordures douces */
-  --vb-radius:14px;
-  --vb-shadow:0 10px 26px rgba(2,6,23,.06);
+  --body-background-fill:#F8FAFC;
+  --panel-background-fill:#FFFFFF;
+  --block-background-fill:#FFFFFF;
+  --block-border-color:#E2E8F0;
+  --text-color:#0F172A;
+  --muted-text-color:#475569;
+  --radius-lg:14px;
+
+  --vb-primary:#7C3AED;
+  --vb-primary-2:#06B6D4;
+  --vb-border:#E2E8F0;
+  --vb-shadow:0 10px 26px rgba(2,6,23,.08);
+
+  /* force gradio accent (anti-orange) */
+  --color-accent:#7C3AED;
 }
 
-/* Forcer un look clair partout */
-*{color-scheme:light !important}
+* { color-scheme: light !important; }
 html,body,.gradio-container{
-  background:var(--vb-bg) !important;
-  color:var(--vb-text);
-  font-family:Manrope,system-ui,-apple-system,'Segoe UI',Roboto,Arial,sans-serif;
+  background:#F8FAFC !important;
+  color:var(--text-color) !important;
+  font-family:Manrope,system-ui,-apple-system,'Segoe UI',Roboto,Arial,sans-serif !important;
 }
 .gradio-container{max-width:1120px !important;margin:0 auto !important}
 
 /* ---------- Hero ---------- */
 .vb-hero{
-  display:flex;align-items:center;gap:14px;padding:16px 18px;margin:8px 0 16px;
-  background:linear-gradient(90deg, rgba(124,58,237,.12), rgba(6,182,212,.12));
-  border:1px solid var(--vb-border);border-radius:var(--vb-radius);box-shadow:var(--vb-shadow);
+  display:flex;align-items:center;gap:16px;
+  padding:20px 22px;margin:10px 0 20px;
+  background:linear-gradient(90deg, rgba(124,58,237,.18), rgba(6,182,212,.18));
+  border-radius:14px;box-shadow:var(--vb-shadow);
+  border:none;
 }
-.vb-title{font-size:20px;font-weight:800;letter-spacing:.2px;color:var(--vb-text)}
-.vb-sub{color:var(--vb-muted);font-size:13px;margin-top:-2px}
+.vb-hero .vb-title{font-size:22px;font-weight:800;color:#0F172A}
+.vb-hero .vb-sub{color:var(--muted-text-color);font-size:13px;margin-top:-2px}
 
-/* ---------- Sections (encarts titres) ---------- */
-.vb-section{
-  display:inline-block;margin:10px 0 8px;padding:8px 12px;
-  border-radius:999px;color:#fff;font-weight:800;font-size:13px;letter-spacing:.2px;
-  background:linear-gradient(90deg,var(--vb-primary),var(--vb-primary-2));
-  box-shadow:0 6px 18px rgba(124,58,237,.18);
+/* ---------- Cartes / blocs généraux ---------- */
+.gradio-container .block,.gradio-container .gr-box,.gradio-container .gr-block,
+.gradio-container .panel,.gradio-container .row,.gradio-container .column{
+  background:#fff !important;border:1px solid var(--vb-border) !important;
+  border-radius:14px !important; box-shadow:var(--vb-shadow);
 }
 
-/* ---------- Cartes / panneaux : plus de bordures noires ---------- */
-.gradio-container .gr-box,
-.gradio-container .gr-panel,
-.gradio-container .gr-accordion,
-.gradio-container .gr-group,
-.gradio-container .gr-form,
-.gradio-container .gr-article{
-  background:var(--vb-card) !important;
-  border:1px solid var(--vb-border) !important; /* jamais noir */
-  border-radius:var(--vb-radius) !important;
-  box-shadow:var(--vb-shadow);
+/* ---------- Labels & titres (NOIR, sans fond/bordure) ---------- */
+/* 1) labels de champs générés par Gradio */
+.gradio-container [data-testid="block-label"],
+.gradio-container .component .label,
+.gradio-container .wrap > .label{
+  background:transparent !important;
+  color:#0F172A !important;
+  padding:0 0 6px 0 !important;
+  border:none !important;
+  box-shadow:none !important;
+  font-weight:700 !important;
 }
 
-/* En-têtes internes générés par Gradio/Svelte : neutraliser les bordures sombres */
-.gradio-container [class*="block-title"],
-.gradio-container .header,
-.gradio-container .header-button,
-.gradio-container span[class*="block"],
-.gradio-container .container.show_textbox_border,
-.gradio-container .container.show_textbox_border *{
-  border-color:var(--vb-border) !important;
-  color:var(--vb-text) !important;
+/* 2) le "block-info" (span qui contient le texte du label) */
+.gradio-container [data-testid="block-info"]{
+  color:#0F172A !important;
+  background:transparent !important;
+  border:none !important;
+  box-shadow:none !important;
+  font-weight:700 !important;
 }
 
-/* ---------- Labels & textes : tous en noir lisible ---------- */
-.gradio-container label,
-.gradio-container .label,
-.gradio-container .gr-text,
-.gradio-container .wrap .label,
-.gradio-container .form .label,
-.gradio-container .input-label,
-.gradio-container .input-label *{
-  color:var(--vb-text) !important;
+/* 3) conteneur label qui ajoute une bordure par défaut chez Gradio */
+.gradio-container label.container.show_textbox_border{
+  border:none !important;
+  background:transparent !important;
+  box-shadow:none !important;
 }
 
-/* Titres explicitement demandés en noir */
-.gradio-container label:has(+ input),
-.gradio-container span[dir="ltr"] { color:var(--vb-text) !important; }
-
-/* Checkbox — texte noir + case dégradée bouton */
-.gradio-container label:has(> input[type="checkbox"]){ color:var(--vb-text) !important; border:none !important; box-shadow:none !important; background:transparent !important; }
-.gradio-container label:has(> input[type="checkbox"]) > span{ color:var(--vb-text) !important; }
-/* Fallback si :has n'est pas supporté */
-.gradio-container input[type="checkbox"] + span,
-.gradio-container input[type="checkbox"] ~ span{ color:var(--vb-text) !important; }
-
-/* Cases à cocher : */
-.gradio-container input[type="checkbox"]{
-  -webkit-appearance:none; appearance:none;
-  width:18px;height:18px;border-radius:4px;border:1px solid var(--vb-border);
-  background:#fff; display:inline-grid; place-content:center; margin-right:8px;
-}
-.gradio-container input[type="checkbox"]:checked{
-  background:linear-gradient(135deg,var(--vb-primary),var(--vb-primary-2));
-  border-color:transparent;
-}
-.gradio-container input[type="checkbox"]:checked::after{
-  content:""; width:10px;height:10px;border-radius:2px;background:#fff;
+/* ---------- ENCARTS DE SECTION (bandeau) ---------- */
+.vb-section{
+  display:block; width:100%;
+  background:linear-gradient(90deg, var(--vb-primary), var(--vb-primary-2));
+  color:#fff; padding:12px 16px; border-radius:12px;
+  font-weight:800; letter-spacing:.2px; box-shadow:0 10px 26px rgba(124,58,237,.22);
+  margin:20px 0 10px 0;
+  border:none;
 }
 
 /* ---------- Inputs ---------- */
-.gradio-container input[type="text"],
-.gradio-container input[type="number"],
-.gradio-container textarea,
-.gradio-container select,
-.gradio-container .gr-textbox,
+.gradio-container input[type="text"], .gradio-container input[type="number"],
+.gradio-container textarea, .gradio-container select, .gradio-container .gr-textbox,
 .gradio-container .gr-textbox textarea{
-  background:#fff !important;border:1px solid var(--vb-border) !important;
-  border-radius:calc(var(--vb-radius) - 4px) !important; box-shadow:none !important; color:var(--vb-text);
+  background:#fff !important; color:var(--text-color) !important;
+  border:1px solid var(--vb-border) !important; border-radius:10px !important;
 }
-.gradio-container input::placeholder,
-.gradio-container textarea::placeholder{color:#9AA4B2}
-
-/* ---------- Sliders (barres de jauge) — dégradé, plus d'orange ---------- */
-.gradio-container input[type="range"]{
-  width:100%; background:transparent; outline:none; height:20px;
+.gradio-container input::placeholder, .gradio-container textarea::placeholder{color:#6B7280}
+.gradio-container input:focus, .gradio-container textarea:focus{
+  border-color:transparent !important;
+  box-shadow:0 0 0 2px rgba(124,58,237,.35), 0 0 0 4px rgba(6,182,212,.25) !important;
 }
-.gradio-container input[type="range"]::-webkit-slider-runnable-track{
-  height:6px; border-radius:999px;
-  background:linear-gradient(90deg, var(--vb-primary) 0 calc(var(--range_progress, 0%)),
-                                  var(--vb-primary-2) calc(var(--range_progress, 0%)),
-                                  #E5EAF3 calc(var(--range_progress, 0%)));
+
+/* ---------- Checkboxes (pas d’orange) ---------- */
+.gradio-container input[type="checkbox"]{
+  accent-color:var(--vb-primary) !important;
 }
-.gradio-container input[type="range"]::-webkit-slider-thumb{
-  -webkit-appearance:none; width:18px;height:18px;border-radius:50%;
-  background:linear-gradient(135deg,var(--vb-primary),var(--vb-primary-2));
-  border:0; box-shadow:0 2px 8px rgba(124,58,237,.35); margin-top:-6px;
+.gradio-container input[type="checkbox"]:focus-visible{
+  outline:none; box-shadow:0 0 0 2px rgba(124,58,237,.35), 0 0 0 4px rgba(6,182,212,.25) !important;
 }
-/* Firefox */
-.gradio-container input[type="range"]::-moz-range-track{
-  height:6px;border-radius:999px;background:#E5EAF3;
+
+/* ---------- Sliders (barre de jauge non orange) ---------- */
+.gradio-container input[type="range"]{
+  height:8px !important; border-radius:999px !important;
+  background:
+    linear-gradient(90deg, var(--vb-primary), var(--vb-primary-2)) 0/ var(--range_progress, 0%) 100% no-repeat,
+    #EEF2FF !important;
 }
-.gradio-container input[type="range"]::-moz-range-progress{
-  height:6px;border-radius:999px;background:linear-gradient(90deg,var(--vb-primary),var(--vb-primary-2));
+.gradio-container input[type="range"]::-webkit-slider-runnable-track{height:8px;background:transparent;border-radius:999px}
+.gradio-container input[type="range"]::-moz-range-track{height:8px;background:transparent;border-radius:999px}
+.gradio-container input[type="range"]::-webkit-slider-thumb{
+  -webkit-appearance:none;width:18px;height:18px;border-radius:50%;
+  background:#fff;border:2px solid var(--vb-primary);box-shadow:0 2px 10px rgba(124,58,237,.3);margin-top:-5px
 }
 .gradio-container input[type="range"]::-moz-range-thumb{
   width:18px;height:18px;border-radius:50%;
-  background:linear-gradient(135deg,var(--vb-primary),var(--vb-primary-2));
-  border:0; box-shadow:0 2px 8px rgba(124,58,237,.35);
+  background:#fff;border:2px solid var(--vb-primary);box-shadow:0 2px 10px rgba(124,58,237,.3);
 }
 
-/* ---------- Boutons ---------- */
-button,.gr-button{
-  border-radius:var(--vb-radius) !important;border:0 !important;font-weight:800 !important;
-  box-shadow:var(--vb-shadow);
-}
-.gr-button-primary{
-  background:linear-gradient(90deg,var(--vb-primary),var(--vb-primary-2)) !important;
-  color:#fff !important; padding:14px 22px !important; font-size:16px !important;
+/* ---------- Bouton principal ---------- */
+.gradio-container .vb-cta{
+  background:linear-gradient(90deg, var(--vb-primary), var(--vb-primary-2)) !important;
+  color:#fff !important; border:0 !important; font-weight:800 !important;
+  padding:16px 32px !important; font-size:17px !important; min-height:52px !important;
+  border-radius:14px !important; box-shadow:0 12px 28px rgba(124,58,237,.28);
 }
-.gr-button-primary:hover{filter:brightness(1.06); transform:translateY(-1px)}
+.gradio-container .vb-cta:hover{transform:translateY(-2px);filter:brightness(1.05)}
 
-/* ---------- DataFrames / Tables ---------- */
-.gradio-container table{border-collapse:separate;border-spacing:0;width:100%}
-.gradio-container thead th{
-  background:linear-gradient(90deg,rgba(124,58,237,.06),rgba(6,182,212,.06)) !important;
-  color:#0F172A !important;font-weight:800 !important;border-bottom:1px solid var(--vb-border) !important;
+/* ---------- DataFrames / Tables : pas de bandeaux sombres ---------- */
+.gradio-container .table, .gradio-container .svelte-virtual-table-viewport,
+.gradio-container .table-wrap, .gradio-container .table *{
+  background:#fff !important; color:#0F172A !important; border-color:#E2E8F0 !important;
 }
-.gradio-container td, .gradio-container th{
-  padding:10px;border-bottom:1px solid #EEF3FA;
-  background:#fff !important; color:#0F172A !important;
+.gradio-container .table thead, .gradio-container .table thead tr, .gradio-container .table thead th{
+  background:linear-gradient(90deg, rgba(124,58,237,.12), rgba(6,182,212,.12)) !important;
+  color:#0F172A !important; border-bottom:1px solid #E2E8F0 !important;
 }
+.gradio-container .header-button{background:transparent !important;color:#0F172A !important;border:none !important;box-shadow:none !important}
 
-/* ---------- Graphiques (Plotly) ---------- */
+/* ---------- Files / Placeholders : on cache les icônes (non pro) ---------- */
+.gradio-container .empty, .gradio-container .icon{ display:none !important; }
+.gradio-container [class*="unbounded"], .gradio-container [class*="unbounded_box"]{ display:none !important; }
+
+/* ---------- Plotly ---------- */
 .js-plotly-plot .plotly .bg{fill:#fff !important}
 .js-plotly-plot .plotly .xgrid,.js-plotly-plot .plotly .ygrid{stroke:#E2E8F0 !important;opacity:1}
-.js-plotly-plot .plotly .legend text{font-weight:600}
-
-/* ---------- Nettoyage des icônes/grilles sombres Gradio ---------- */
-.gradio-container .icon, 
-.gradio-container .empty,
-.gradio-container .icon.svelte-1oiin9d,
-.gradio-container .empty.svelte-1oiin9d,
-.gradio-container .unpadded_box{ display:none !important }
 
-/* Footer */
-.vb-footer{color:var(--vb-muted);font-size:12px;text-align:center;margin:18px 0}
+/* ---------- Footer ---------- */
+.vb-footer{color:#475569;font-size:12px;text-align:center;margin:16px 0}
 """
 
 def apply_plotly_theme():
     pio.templates["verbatify"] = go.layout.Template(
         layout=go.Layout(
-            font=dict(family="Manrope, system-ui, -apple-system, Segoe UI, Roboto, Arial, sans-serif", size=13, color="#0F172A"),
+            font=dict(family="Manrope, system-ui, -apple-system, Segoe UI, Roboto, Arial, sans-serif",
+                      size=13, color="#0F172A"),
             paper_bgcolor="white", plot_bgcolor="white",
-            colorway=["#7C3AED","#06B6D4","#2563EB","#10B981","#EF4444","#14B8A6","#F59E0B","#F43F5E"],
+            colorway=["#7C3AED","#06B6D4","#2563EB","#10B981","#A855F7","#22D3EE","#1D4ED8","#0EA5E9"],
             xaxis=dict(gridcolor="#E2E8F0", zerolinecolor="#E2E8F0"),
             yaxis=dict(gridcolor="#E2E8F0", zerolinecolor="#E2E8F0"),
             legend=dict(borderwidth=0, bgcolor="rgba(255,255,255,0)")
@@ -219,7 +193,7 @@ LOGO_SVG = """<svg xmlns='http://www.w3.org/2000/svg' width='224' height='38' vi
   </g>
 </svg>"""
 
-# ---------------- unidecode (fallback si paquet absent) ----------------
+# ====================== UNIDECODE (fallback) ======================
 try:
     from unidecode import unidecode
 except Exception:
@@ -230,7 +204,7 @@ except Exception:
         except Exception:
             return str(x)
 
-# ---------------- Thésaurus ASSURANCE ----------------
+# ====================== THÉSAURUS, SENTIMENT, OpenAI (identiques) ======================
 THEMES = {
     "Remboursements santé":[r"\bremboursement[s]?\b", r"\bt[eé]l[eé]transmission\b", r"\bno[eé]mie\b",
         r"\bprise\s*en\s*charge[s]?\b", r"\btaux\s+de\s+remboursement[s]?\b", r"\b(ameli|cpam)\b",
@@ -261,7 +235,6 @@ THEMES = {
     "Agence / Accueil":[r"\bagence[s]?\b", r"\bboutique[s]?\b", r"\baccueil\b", r"\bconseil[s]?\b", r"\battente\b", r"\bcaisse[s]?\b"],
 }
 
-# ---------------- Sentiment (règles) ----------------
 POS_WORDS = {"bien":1.0,"super":1.2,"parfait":1.4,"excellent":1.5,"ravi":1.2,"satisfait":1.0,
              "rapide":0.8,"efficace":1.0,"fiable":1.0,"simple":0.8,"facile":0.8,"clair":0.8,"conforme":0.8,
              "sympa":0.8,"professionnel":1.0,"réactif":1.0,"reactif":1.0,"compétent":1.0,"competent":1.0,
@@ -275,17 +248,14 @@ INTENSIFIERS = [r"\btr[eè]s\b", r"\bvraiment\b", r"\bextr[eê]mement\b", r"\bhy
 DIMINISHERS  = [r"\bun[e]?\s+peu\b", r"\bassez\b", r"\bplut[oô]t\b", r"\bl[eé]g[eè]rement\b"]
 INTENSIFIER_W, DIMINISHER_W = 1.5, 0.7
 
-# ---------------- OpenAI (optionnel, robuste) ----------------
 OPENAI_AVAILABLE = False
 try:
-    from openai import OpenAI
-    if os.getenv("OPENAI_API_KEY"):
-        _client = OpenAI()
-        OPENAI_AVAILABLE = True
+  from openai import OpenAI
+  if os.getenv("OPENAI_API_KEY"):
+    _client = OpenAI(); OPENAI_AVAILABLE = True
 except Exception:
-    OPENAI_AVAILABLE = False
+  OPENAI_AVAILABLE = False
 
-# ---------------- Utils ----------------
 def normalize(t:str)->str:
     if not isinstance(t,str): return ""
     return re.sub(r"\s+"," ",t.strip())
@@ -345,7 +315,6 @@ def anonymize(t:str)->str:
     t=re.sub(r"\b(?:\+?\d[\s.-]?){7,}\b","[tel]",t)
     return t
 
-# --------- Coller du texte → DataFrame ----------
 def df_from_pasted(text:str, sep="|", has_score=False) -> pd.DataFrame:
     lines = [l.strip() for l in (text or "").splitlines() if l.strip()]
     rows = []
@@ -357,7 +326,6 @@ def df_from_pasted(text:str, sep="|", has_score=False) -> pd.DataFrame:
             rows.append({"id": i, "comment": line.strip(), "nps_score": None})
     return pd.DataFrame(rows)
 
-# --------- OpenAI helpers (optionnels) ----------
 def openai_json(model:str, system:str, user:str, temperature:float=0.0) -> Optional[dict]:
     if not OPENAI_AVAILABLE: return None
     try:
@@ -390,7 +358,6 @@ def oa_summary(nps:Optional[float], dist:Dict[str,int], themes_df:pd.DataFrame,
     if isinstance(j, dict): return ' '.join(str(v) for v in j.values())
     return None
 
-# --------- HF sentiment (optionnel)
 def make_hf_pipe():
     try:
         from transformers import pipeline
@@ -400,22 +367,22 @@ def make_hf_pipe():
     except Exception:
         return None
 
-# --------- Inférence de note NPS depuis le sentiment ----------
 def infer_nps_from_sentiment(label: str, score: float) -> int:
-    scaled = int(round((float(score) + 4.0) * 1.25))  # -4 -> 0, 0 -> 5, +4 -> 10
+    scaled = int(round((float(score) + 4.0) * 1.25))
     scaled = max(0, min(10, scaled))
-    if label == "positive":
-        return max(9, scaled)
-    if label == "negatif":
-        return min(6, scaled)
+    if label == "positive": return max(9, scaled)
+    if label == "negatif":  return min(6, scaled)
     return 8 if score >= 0 else 7
 
 # --------- Graphiques ----------
 def fig_nps_gauge(nps: Optional[float]) -> go.Figure:
     v = 0.0 if nps is None else float(nps)
-    return go.Figure(go.Indicator(mode="gauge+number", value=v,
-                                  gauge={"axis":{"range":[-100,100]}, "bar":{"thickness":0.3}},
-                                  title={"text":"NPS (−100 à +100)"}))
+    return go.Figure(go.Indicator(
+        mode="gauge+number", value=v,
+        gauge={"axis":{"range":[-100,100]},
+               "bar":{"thickness":0.3, "color":"#7C3AED"}},  # violet
+        title={"text":"NPS (−100 à +100)"}
+    ))
 
 def fig_sentiment_bar(dist: Dict[str,int]) -> go.Figure:
     order = ["negatif","neutre","positive"]
@@ -435,7 +402,7 @@ def fig_theme_balance(themes_df: pd.DataFrame, k: int) -> go.Figure:
     fig = px.bar(d2, x="theme", y="count", color="type", barmode="stack", title=f"Top {k} thèmes — balance Pos/Neg")
     fig.update_layout(xaxis_tickangle=-30); return fig
 
-# --------- Analyse principale ----------
+# ====================== ANALYSE ======================
 def analyze_text(pasted_txt, has_sc, sep_chr,
                  do_anonymize, use_oa_sent, use_oa_themes, use_oa_summary,
                  oa_model, oa_temp, top_k):
@@ -447,7 +414,6 @@ def analyze_text(pasted_txt, has_sc, sep_chr,
     if do_anonymize:
         df["comment"]=df["comment"].apply(anonymize)
 
-    # OpenAI indisponible → on bascule silencieusement
     if (use_oa_sent or use_oa_themes or use_oa_summary) and not OPENAI_AVAILABLE:
         use_oa_sent = use_oa_themes = use_oa_summary = False
 
@@ -468,7 +434,6 @@ def analyze_text(pasted_txt, has_sc, sep_chr,
     for idx, r in df.iterrows():
         cid=r.get("id", idx+1); comment=normalize(str(r["comment"]))
 
-        # Sentiment: OpenAI -> HF -> règles
         sent=None
         if use_oa_sent:
             sent=oa_sentiment(comment, oa_model, float(oa_temp or 0.0)); used_oa = used_oa or bool(sent)
@@ -479,7 +444,6 @@ def analyze_text(pasted_txt, has_sc, sep_chr,
             s=float(lexical_sentiment_score(comment))
             sent={"label":lexical_sentiment_label(s),"score":s}
 
-        # Thèmes: regex (+ fusion OpenAI)
         themes, counts = detect_themes_regex(comment)
         if use_oa_themes:
             tjson=oa_themes(comment, oa_model, float(oa_temp or 0.0))
@@ -490,7 +454,6 @@ def analyze_text(pasted_txt, has_sc, sep_chr,
                         counts[th] = max(counts.get(th, 0), int(c))
                 themes = [th for th, c in counts.items() if c > 0]
 
-        # Note NPS : donnée ou inférée
         given = r.get("nps_score", None)
         try:
             given = int(given) if given is not None and str(given).strip() != "" else None
@@ -523,7 +486,6 @@ def analyze_text(pasted_txt, has_sc, sep_chr,
     nps=compute_nps(out_df["nps_score_final"])
     dist=out_df["sentiment_label"].value_counts().to_dict()
 
-    # Stats par thème
     trs=[]
     for th, d in theme_agg.items():
         trs.append({"theme":th,"total_mentions":int(d["mentions"]),
@@ -531,7 +493,6 @@ def analyze_text(pasted_txt, has_sc, sep_chr,
                     "net_sentiment":int(d["pos"]-d["neg"])})
     themes_df=pd.DataFrame(trs).sort_values(["total_mentions","net_sentiment"],ascending=[False,False])
 
-    # Synthèse
     method = "OpenAI + HF + règles" if (use_oa_sent and used_hf) else ("OpenAI + règles" if use_oa_sent else ("HF + règles" if used_hf else "Règles"))
     nps_label = "NPS global (inféré)" if any_inferred else "NPS global"
     lines=[ "# Synthèse NPS & ressentis clients",
@@ -598,21 +559,27 @@ def analyze_text(pasted_txt, has_sc, sep_chr,
     return (summary_md, themes_df.head(100), out_df.head(200), [enriched, themes, summ, zip_path],
             ench_md, irr_md, reco_md, fig_gauge, fig_emots, fig_top, fig_bal)
 
-# ---------------- UI ----------------
-apply_plotly_theme()
+# ====================== UI ======================
+
+def apply_plotly_theme_wrapper(): apply_plotly_theme()
+apply_plotly_theme_wrapper()
 
 with gr.Blocks(title="Verbatify — Analyse NPS", css=VB_CSS) as demo:
-    # Header
     gr.HTML(
         "<div class='vb-hero'>"
-        f"{LOGO_SVG}"
+        """<svg xmlns='http://www.w3.org/2000/svg' width='224' height='38' viewBox='0 0 224 38'>
+            <defs><linearGradient id='g' x1='0%' y1='0%' x2='100%'><stop offset='0%' stop-color='#7C3AED'/><stop offset='100%' stop-color='#06B6D4'/></linearGradient></defs>
+            <g fill='none' fill-rule='evenodd'>
+              <rect x='0' y='7' width='38' height='24' rx='12' fill='url(#g)'/>
+              <circle cx='13' cy='19' r='5' fill='#fff' opacity='0.95'/><circle cx='25' cy='19' r='5' fill='#fff' opacity='0.72'/>
+              <text x='46' y='25' font-family='Manrope, system-ui, -apple-system, Segoe UI, Roboto, Arial, sans-serif' font-size='20' font-weight='800' fill='#0F172A' letter-spacing='0.2'>Verbatify</text>
+            </g></svg>"""
         "<div><div class='vb-title'>Verbatify — Analyse NPS</div>"
         "<div class='vb-sub'>Émotions • Thématiques • Occurrences • Synthèse</div></div>"
         "</div>"
     )
 
-    # Inputs
-    gr.HTML("<div class='vb-section'>Entrées</div>")
+    # ---------- Inputs ----------
     with gr.Column():
         pasted = gr.Textbox(
             label="Verbatims (un par ligne)", lines=10,
@@ -632,24 +599,24 @@ with gr.Blocks(title="Verbatify — Analyse NPS", css=VB_CSS) as demo:
         oa_model=gr.Textbox(label="Modèle OpenAI", value="gpt-4o-mini")
         oa_temp=gr.Slider(label="Température", minimum=0.0, maximum=1.0, value=0.1, step=0.1)
         top_k=gr.Slider(label="Top thèmes (K) pour les graphes", minimum=5, maximum=20, value=10, step=1)
-        run=gr.Button("Lancer l'analyse", variant="primary")
+        run=gr.Button("Lancer l'analyse", elem_classes=["vb-cta"])
 
-    gr.HTML("<div class='vb-section'>Cartes synthétiques</div>")
+    # ---------- Panneaux courts ----------
     with gr.Row():
         ench_panel=gr.Markdown()
         irr_panel=gr.Markdown()
         reco_panel=gr.Markdown()
 
-    gr.HTML("<div class='vb-section'>Synthèse NPS & ressentis clients</div>")
-    summary=gr.Markdown()
-
+    # ---------- Encarts + tableaux ----------
     gr.HTML("<div class='vb-section'>Thèmes — statistiques</div>")
-    themes_table=gr.Dataframe()
+    themes_table=gr.Dataframe(label="")  # label vide, encart fait office de titre
 
     gr.HTML("<div class='vb-section'>Verbatims enrichis (aperçu)</div>")
-    enriched_table=gr.Dataframe()
+    enriched_table=gr.Dataframe(label="")
+
     files_out=gr.Files(label="Téléchargements (CSV & ZIP)")
 
+    # ---------- Graphes ----------
     gr.HTML("<div class='vb-section'>Graphiques</div>")
     with gr.Row():
         plot_nps = gr.Plot(label="NPS — Jauge")
@@ -658,7 +625,11 @@ with gr.Blocks(title="Verbatify — Analyse NPS", css=VB_CSS) as demo:
         plot_top  = gr.Plot(label="Top thèmes — occurrences")
         plot_bal  = gr.Plot(label="Top thèmes — balance Pos/Neg")
 
-    # Lancer
+    # ---------- Synthèse ----------
+    gr.HTML("<div class='vb-section'>Synthèse NPS & ressentis clients</div>")
+    summary=gr.Markdown()
+
+    # ---------- Action ----------
     run.click(
         analyze_text,
         inputs=[pasted, has_score, sep, anon, use_oa_sent, use_oa_themes, use_oa_summary, oa_model, oa_temp, top_k],
@@ -667,7 +638,6 @@ with gr.Blocks(title="Verbatify — Analyse NPS", css=VB_CSS) as demo:
                  plot_nps, plot_sent, plot_top, plot_bal]
     )
 
-    # Footer
     gr.HTML(
         '<div class="vb-footer">© Verbatify.com — Construit par '
         '<a href="https://jeremy-lagache.fr/" target="_blank" rel="noopener">Jérémy Lagache</a></div>'