**Add token gate to public Gradio app and update UI title**

Implemented a simple token‑based access gate for the public app.
- Added `_check_token` helper that validates a token from environment variables (`APP_ACCESS_TOKEN` or `KESHERAT_TOKEN`) and returns visibility updates.
- Introduced a gate UI group with a password textbox, status message, and “Entrar” button.
- Updated the app title and header text to “KESHERAT AI”.
- Connected the gate button to the `_check_token` function, hiding the main app until a valid token is entered.
- Adjusted imports and placeholders for the gated app components.

app.py

@@ -248,6 +248,17 @@ def _extract_path_update(d):
     v = (d.get("path") if isinstance(d, dict) else d)
     return gr.update(value=v, visible=True)
 
+def _check_token(token: str):
+    """Token gate for public app. Expected token via env APP_ACCESS_TOKEN or KESHERAT_TOKEN.
+    Defaults to 'KESHERAT' if none provided.
+    Returns visibility updates for [gate_group, app_group, gate_status]."""
+    expected = os.getenv("APP_ACCESS_TOKEN") or os.getenv("KESHERAT_TOKEN") or "KESHERAT"
+    ok = str(token or "").strip() == str(expected).strip()
+    if ok:
+        return gr.update(visible=False), gr.update(visible=True), gr.update(visible=False, value="")
+    else:
+        return gr.update(visible=True), gr.update(visible=False), gr.update(visible=True, value="Token inválido. Intenta nuevamente.")
+
 def compute_visual_features(image_path, detections=None):
     """Compute simple visual features and return a short description plus numeric metrics.
 
@@ -774,17 +785,25 @@ def generar_analisis_fuerte(media_path):
     except Exception as e:
         return {"status": f"error: {e}", "report_pdf": None, "report_md": None, "report_json": None}
 
-# ────────────────────────────
-# Interfaz Gradio (extendida)
 # ────────────────────────────
 with gr.Blocks(
-    title="Kesherat · AI Blade Inspection",
+    title="KESHERAT AI",
     theme=gr.themes.Soft(),
 ) as demo:
     gr.HTML("""
     <link rel=\"stylesheet\" href=\"/file=assets/kesheret.css\" />
-    <div class=\"kesheret-header\"><h1>🔍 AI Blade Inspection</h1><p>Detección de defectos en palas eólicas con YOLOv8</p></div>
+    <div class=\"kesheret-header\"><h1>KESHERAT AI</h1><p>KESHERAT AI</p></div>
     """)
+    # Access gate (token) — app is public but gated by token
+    with gr.Group(visible=True) as gate_group:
+        gr.Markdown("### Acceso — Introduce tu token de seguridad")
+        gate_token = gr.Textbox(label="Token", type="password", placeholder="Introduce tu token")
+        gate_status = gr.Markdown(visible=False)
+        btn_enter = gr.Button("Entrar")
+
+    with gr.Group(visible=False) as app_group:
+        pass  # placeholder; actual app components below
+
 
     with gr.Row():
         with gr.Tabs() as media_tabs:
@@ -830,6 +849,8 @@ with gr.Blocks(
     json_video = gr.JSON(visible=False)
     json_image = gr.JSON(visible=False)
 
+    btn_enter.click(fn=_check_token, inputs=[gate_token], outputs=[gate_group, app_group, gate_status])
+
     btn_detect = gr.Button("Detectar defectos")
 
     # Endpoint API para vídeo: devuelve dict {video, classes}. UI: muestra resultado solo tras análisis