Merge branch 'development' of gitea.centx.de:lelo/bethaus-app into development

static/app.css

@@ -347,3 +347,24 @@ footer {
 @keyframes spin {
   to { transform: rotate(360deg); }
 }
+
+.card-body.collapsable {
+  display: none;
+  transition: max-height 0.3s ease;
+  overflow: hidden;
+
+}
+
+.card-body.collapsable.show {
+  display: block;
+  max-height: 1000px; 
+}
+
+.toggle-icon {
+  font-size: 1.25rem;
+  user-select: none;
+}
+
+.toggle-icon:hover {
+  color: #007bff;
+}

static/app.js

@@ -499,3 +499,55 @@ function syncThemeColor() {
 }
 
 document.addEventListener('DOMContentLoaded', syncThemeColor);
+
+
+// toggle card visibility
+document.addEventListener('DOMContentLoaded', function() {
+    // 1. Select all plus/minus icons
+    var icons = document.querySelectorAll('.card .toggle-icon');
+
+    icons.forEach(function(icon) {
+      // 2. For each icon, find its corresponding collapsable body
+      var card = icon.closest('.card');
+      if (!card) return;
+
+      var body = card.querySelector('.card-body.collapsable');
+      if (!body) return;
+
+      // 3. Initialize aria‐expanded & icon text based on whether .show is present
+      if (body.classList.contains('show')) {
+        icon.textContent = '–';
+        icon.setAttribute('aria-expanded', 'true');
+      } else {
+        icon.textContent = '+';
+        icon.setAttribute('aria-expanded', 'false');
+      }
+
+      function toggleSection() {
+        // Toggle the 'show' class
+        if (body.classList.contains('show')) {
+          body.classList.remove('show');
+          icon.textContent = '+';
+          icon.setAttribute('aria-expanded', 'false');
+        } else {
+          body.classList.add('show');
+          icon.textContent = '–';
+          icon.setAttribute('aria-expanded', 'true');
+        }
+      }
+
+      // 4. Click listener
+      icon.addEventListener('click', function(e) {
+        e.stopPropagation();
+        toggleSection();
+      });
+
+      // 5. Keydown listener (Enter/Space for accessibility)
+      icon.addEventListener('keydown', function(e) {
+        if (e.key === 'Enter' || e.key === ' ') {
+          e.preventDefault();
+          toggleSection();
+        }
+      });
+    });
+  });

templates/connections.html

@@ -26,7 +26,7 @@
 
 {% block content %}
   <div class="container-fluid">
-    <h2>Übersicht deiner gültigen Links</h2>
+    <h2>Verbindungen der letzten 10 Minuten</h2>
     <span class="ms-3">
       Anzahl Verbindungen: <strong id="totalConnections">0</strong>
     </span>

templates/file_access.html

@@ -62,10 +62,11 @@
       <!-- Detailed Table of Top File Accesses -->
       {% for top20_item in top20 %}
       <div class="card mb-4">
-        <div class="card-header">
+        <div class="card-header d-flex justify-content-between align-items-center">
-          Top 20 Dateizugriffe ({{ top20_item['category'] }})
+          <span>Top 20 Dateizugriffe ({{ top20_item['category'] }})</span>
+          <span class="toggle-icon" aria-label="collapse" role="button" tabindex="0">+</span>
         </div>
-        <div class="card-body">
+        <div class="card-body collapsable">
           <div class="table-responsive">
             <table class="table table-striped">
               <thead>

transcribe_all.py

@@ -1,6 +1,7 @@
 import os
 import sys
 import time
+import torch
 import whisper
 import concurrent.futures
 import json
@@ -18,7 +19,6 @@ with open("transcription_config.yml", "r", encoding="utf-8") as file:
     settings = yaml.safe_load(file)
     folder_list = settings.get("folder_list")
     model_name = settings.get("model_name")
-    device = settings.get("device")
 
 def load_audio_librosa(path: str, sr: int = 16_000) -> np.ndarray:
     audio, orig_sr = librosa.load(path, sr=sr)      # load + resample to 16 kHz
@@ -222,7 +222,10 @@ def process_folder(root_folder):
     else:
         print(f"Checked {checked_files} files. Start to transcribe {len(valid_files)} files.")
     
-    print("Loading Whisper model...")
+    # Choose “cuda” if available, otherwise “cpu”
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+    print(f"Loading Whisper model on {device}…")
+
     model = whisper.load_model(model_name, device=device)
     
     # Use a thread pool to pre-load files concurrently.