fix of the json upload format

Web/app.py

@@ -417,8 +417,6 @@ def _is_csrf_exempt_request():
 
 @app.before_request
 def _enforce_csrf_protection():
-    if request.endpoint == 'upload_csv_batch':
-        return None
     if _is_csrf_exempt_request():
         _get_csrf_token()
         return None
@@ -11865,27 +11863,33 @@ def batch_upload_page():
     return render_template('upload_batch.html')
 
 
-from flask_wtf.csrf import CSRFProtect
-csrf = CSRFProtect(app)
-
 
 @app.route('/upload_csv_batch', methods=['POST'])
-@csrf.exempt
 def upload_csv_batch():
     """
     Route for batch adding new items to the inventory via CSV.
-    Handles CSV parsing, bulk image upload (conversion to WebP), GridFS storage,
-    and groups identical items based on their Name.
+    Handles CSV parsing, bulk image upload with deduplication (SHA-256 hash matching),
+    GridFS storage, code generation, location syncing, and grouped item creation.
     """
     import pandas as pd
     import ast
-    #if 'username' not in session:
-    #    return jsonify({'success': False, 'message': 'Nicht angemeldet'}), 401
+    import hashlib
 
-    username = session['username']
-    # permissions = _get_current_user_permissions() ... (anpassen wie in Original)
-    # if not _action_access_allowed(permissions, 'can_insert'):
-    #     return jsonify({'success': False, 'message': 'Einfüge-Rechte erforderlich'}), 403
+    username = session.get('username', 'System')
+
+    def generate_unique_batch_code(base_code, position):
+        """
+        Generiert einen eindeutigen Code für einen Artikel innerhalb einer Serie (Batch).
+
+        :param base_code: Der Code des ersten Artikels in der Gruppe (String oder None).
+        :param position: Die Position des aktuellen Artikels in der Gruppe (Integer).
+        :return: Ein eindeutiger Code als String.
+        """
+        if base_code:
+            return f"{base_code}-{position}"
+        else:
+            random_prefix = str(uuid.uuid4())[:6].upper()
+            return f"BATCH-{random_prefix}-{position}"
 
     fs = get_gridfs()
     upload_session_id = str(uuid.uuid4())[:8]
@@ -11900,7 +11904,7 @@ def upload_csv_batch():
 
     # 2. CSV Einlesen und Validieren
     try:
-        df = pd.read_csv(csv_file)
+        df = pd.read_csv(csv_file, sep=',')
     except Exception as e:
         app.logger.error(f"[Upload {upload_session_id}] Fehler beim Lesen der CSV: {str(e)}")
         return jsonify({"success": False, "message": f"Fehler beim Lesen der CSV: {str(e)}"}), 400
@@ -11908,10 +11912,11 @@ def upload_csv_batch():
     if 'Name' not in df.columns:
         return jsonify({"success": False, "message": "Die CSV muss zwingend eine 'Name' Spalte enthalten."}), 400
 
-    # 3. Bilder verarbeiten, nach WebP konvertieren und in GridFS speichern
-    # Mapping: Original-Dateiname (ohne Pfad/Erweiterung) -> GridFS Filename (.webp)
-    image_mapping = {}
+    # 3. Bilder verarbeiten & Duplikate im selben Durchlauf filtern (Hash-Matching)
+    image_mapping = {}      # Original-Dateiname (ohne Ext) -> GridFS Filename (.webp)
+    processed_hashes = {}   # SHA-256 Hash -> GridFS Filename (.webp)
     processed_count = 0
+    dedup_count = 0
     error_count = 0
 
     for index, image in enumerate(uploaded_images):
@@ -11929,6 +11934,18 @@ def upload_csv_batch():
                 error_count += 1
                 continue
 
+            # SHA-256 Hash des Bildinhalts zur Erkennung identischer Bilder
+            img_hash = hashlib.sha256(image_bytes).hexdigest()
+
+            if img_hash in processed_hashes:
+                # Bild ist identisch zu einem bereits verarbeiteten Bild im selben Batch
+                existing_filename = processed_hashes[img_hash]
+                image_mapping[base_name_no_ext] = existing_filename
+                dedup_count += 1
+                app.logger.info(f"{image_log_prefix} Duplikat erkannt ({original_secure_name}). Wiederverwendung von: {existing_filename}")
+                continue
+
+            # Neues Bild verarbeiten und nach WebP konvertieren
             optimized_io = io.BytesIO()
             with Image.open(io.BytesIO(image_bytes)) as img:
                 if img.mode not in ('RGB', 'RGBA'):
@@ -11945,7 +11962,7 @@ def upload_csv_batch():
             optimized_io.seek(0)
             new_filename = f"{uuid.uuid4().hex}_{int(time.time())}.webp"
 
-            # Speichern in GridFS analog zu upload_item
+            # In GridFS speichern
             file_id = fs.put(
                 optimized_io,
                 filename=new_filename,
@@ -11957,7 +11974,8 @@ def upload_csv_batch():
                 }
             )
 
-            # Im Mapping speichern (damit wir sie später der CSV zuordnen können)
+            # In Hash-Tabelle und Mapping sichern
+            processed_hashes[img_hash] = new_filename
             image_mapping[base_name_no_ext] = new_filename
             processed_count += 1
 
@@ -11965,10 +11983,14 @@ def upload_csv_batch():
             app.logger.error(f"{image_log_prefix} Processing failed: {str(e)}")
             error_count += 1
 
-    # 4. Items gruppieren (Analog zu series_group_id aus upload_item)
-    df['Name'] = df['Name'].fillna('Unbenannt').astype(str)
+    # 4. Predefined Locations laden
+    try:
+        predefined_locations = it.get_predefined_locations()
+    except Exception:
+        predefined_locations = []
 
-    # Optional: Fülle NaN Werte in der CSV mit sinnvollen Defaults für die Datenbank
+    # 5. Dataframe bereinigen & gruppieren
+    df['Name'] = df['Name'].fillna('Unbenannt').astype(str)
     df = df.fillna({
         'Ort': 'Unbekannt',
         'Beschreibung': '',
@@ -11985,9 +12007,22 @@ def upload_csv_batch():
         series_group_id = str(uuid.uuid4()) if item_count > 1 else None
         parent_item_id = None
 
+        # Basis-Code für automatisierte Seriencodes ermitteln
+        first_row_code = str(group.iloc[0].get('Code_4', '')).strip()
+        base_code = first_row_code if first_row_code else None
+
         for position, (index, row) in enumerate(group.iterrows(), start=1):
 
-            # Bilder aus der CSV-Zeile extrahieren und über das image_mapping mappen
+            # Ort automatisch zu predefined_locations hinzufügen, falls neu
+            ort_val = str(row['Ort']).strip()
+            if ort_val and ort_val not in predefined_locations:
+                try:
+                    it.add_predefined_location(ort_val)
+                    predefined_locations.append(ort_val)
+                except Exception as e:
+                    app.logger.warning(f"Ort {ort_val} konnte nicht hinzugefügt werden: {e}")
+
+            # Bilder für diesen Artikel zuordnen
             item_image_filenames = []
             if 'Images' in row and pd.notna(row['Images']):
                 try:
@@ -12002,11 +12037,20 @@ def upload_csv_batch():
                 except (ValueError, SyntaxError):
                     pass
 
+            # --- NEU: BILDER-REFERENZEN PRO ARTIKEL DEDUPLIZIEREN ---
+            # Falls die CSV z.B. ['bild1.jpg', 'bild1.jpg'] enthält, filtern wir das hier heraus,
+            # damit die GridFS-Datei nicht doppelt als Referenz gespeichert wird.
+            unique_image_filenames = []
+            for img in item_image_filenames:
+                if img not in unique_image_filenames:
+                    unique_image_filenames.append(img)
+            # --------------------------------------------------------
+
             def parse_filter_col(col_data):
                 try:
                     res = ast.literal_eval(str(col_data))
                     return res if isinstance(res, list) else []
-                except:
+                except Exception:
                     return []
 
             filter_upload = parse_filter_col(row.get('Filter', '[]'))
@@ -12015,28 +12059,37 @@ def upload_csv_batch():
 
             reservierbar = bool(row.get('Reservierbar', False))
 
-            # DB Insert Funktion aufrufen (mit korrigierten, positionellen Parametern)
+            # Code_4 Behandlung: Falls in CSV definiert nutzen, sonst Batch-Code erzeugen
+            row_code = str(row.get('Code_4', '')).strip()
+            if row_code:
+                unique_code = row_code
+            elif 'generate_unique_batch_code' in globals():
+                unique_code = generate_unique_batch_code(base_code, position)
+            else:
+                unique_code = None
+
+            # DB Insert (exakt abgestimmt auf die 10 positionellen Argumente)
             item_id = it.add_item(
-                str(row['Name']),
-                str(row['Ort']),
-                str(row['Beschreibung']),
-                item_image_filenames,
-                filter_upload,
-                filter_upload2,
-                filter_upload3,
-                str(row['Anschaffungsjahr']) if row['Anschaffungsjahr'] else None,
-                str(row['Anschaffungskosten']) if row['Anschaffungskosten'] else None,
-                str(row['Code_4']) if row['Code_4'] else None,
+                str(row['Name']),                             # 1. Name
+                ort_val,                                      # 2. Ort
+                str(row['Beschreibung']),                     # 3. Beschreibung
+                unique_image_filenames,                       # 4. Image Filenames (GridFS) -> HIER GEÄNDERT
+                filter_upload,                                # 5. Filter 1
+                filter_upload2,                               # 6. Filter 2
+                filter_upload3,                               # 7. Filter 3
+                str(row['Anschaffungsjahr']) if row['Anschaffungsjahr'] else None,   # 8. Jahr
+                str(row['Anschaffungskosten']) if row['Anschaffungskosten'] else None, # 9. Kosten
+                unique_code,                                  # 10. Unique Code / Code_4
                 reservierbar=reservierbar,
                 series_group_id=series_group_id,
                 series_count=item_count,
                 series_position=position,
                 is_grouped_sub_item=(position > 1),
                 parent_item_id=parent_item_id,
-                isbn='',
-                item_type='other',
-                library_category='',
-                is_library=False
+                isbn=str(row.get('ISBN', '')),
+                item_type=str(row.get('Item_Type', 'other')),
+                library_category=str(row.get('Library_Category', '')),
+                is_library=bool(row.get('Is_Library', False))
             )
 
             if item_id:
@@ -12047,12 +12100,15 @@ def upload_csv_batch():
                 app.logger.error(f"Fehler beim Erstellen von Item: {row['Name']} (Index {index})")
 
     app.logger.info(
-        f"Batch Upload abgeschlossen: {len(created_item_ids)} Items erstellt. {processed_count} Bilder verarbeitet.")
+        f"Batch Upload abgeschlossen: {len(created_item_ids)} Items erstellt. "
+        f"{processed_count} neue Bilder hochgeladen, {dedup_count} Bild-Duplikate zusammengeführt."
+    )
 
     return jsonify({
         "success": True,
-        "message": f"Upload erfolgreich. {len(created_item_ids)} Items importiert und {processed_count} Bilder konvertiert.",
+        "message": f"Upload erfolgreich. {len(created_item_ids)} Items importiert. {processed_count} neue Bilder gespeichert ({dedup_count} Duplikate zusammengeführt).",
         "created_count": len(created_item_ids),
         "images_processed": processed_count,
+        "images_deduplicated": dedup_count,
         "images_failed": error_count
     }), 200

Web/templates/upload_batch.html

@@ -3,215 +3,237 @@
 <head>
     <meta charset="UTF-8">
     <meta name="viewport" content="width=device-width, initial-scale=1.0">
-    <title>Batch Upload - CSV & Bilder</title>
+    <title>Batch Upload</title>
+
+    <!-- CSRF-Token für JavaScript bereitstellen -->
+    <meta name="csrf-token" content="{{ session.get('_csrf_token', '') }}">
+
     <style>
-        :root {
-            --primary-color: #4a90e2;
-            --background-color: #f4f7f6;
-            --text-color: #333;
-            --border-radius: 8px;
-        }
-
-        body {
-            font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
-            background-color: var(--background-color);
-            color: var(--text-color);
-            display: flex;
-            justify-content: center;
-            align-items: center;
-            min-height: 100vh;
-            margin: 0;
-        }
-
-        .upload-container {
-            background: white;
-            padding: 2rem;
-            border-radius: var(--border-radius);
-            box-shadow: 0 4px 6px rgba(0,0,0,0.1);
-            width: 100%;
-            max-width: 500px;
-        }
-
-        h2 {
-            margin-top: 0;
-            color: var(--primary-color);
-            text-align: center;
-        }
-
-        .form-group {
-            margin-bottom: 1.5rem;
-        }
-
-        label {
-            display: block;
-            font-weight: 600;
-            margin-bottom: 0.5rem;
-        }
-
-        input[type="file"] {
-            display: block;
-            width: 100%;
-            padding: 0.5rem;
-            border: 1px dashed #ccc;
-            border-radius: var(--border-radius);
-            background: #fafafa;
-            cursor: pointer;
-        }
-
-        .btn-submit {
-            width: 100%;
-            padding: 0.75rem;
-            background-color: var(--primary-color);
-            color: white;
-            border: none;
-            border-radius: var(--border-radius);
-            font-size: 1rem;
-            font-weight: 600;
-            cursor: pointer;
-            transition: background-color 0.3s ease;
-        }
-
-        .btn-submit:hover {
-            background-color: #357abd;
-        }
-
-        .btn-submit:disabled {
-            background-color: #a0c4e8;
-            cursor: not-allowed;
-        }
-
-        /* Status & Feedback Messages */
-        #status-message {
-            margin-top: 1rem;
-            padding: 1rem;
-            border-radius: var(--border-radius);
-            display: none;
-            text-align: center;
-        }
-
-        .success {
-            background-color: #d4edda;
-            color: #155724;
-            border: 1px solid #c3e6cb;
-        }
-
-        .error {
-            background-color: #f8d7da;
-            color: #721c24;
-            border: 1px solid #f5c6cb;
-        }
-
-        .loading {
-            background-color: #e2e3e5;
-            color: #383d41;
-            border: 1px solid #d6d8db;
-        }
-
-        .spinner {
-            display: inline-block;
-            width: 1.5rem;
-            height: 1.5rem;
-            border: 3px solid rgba(0,0,0,0.1);
-            border-radius: 50%;
-            border-top-color: var(--primary-color);
-            animation: spin 1s ease-in-out infinite;
-            vertical-align: middle;
-            margin-right: 0.5rem;
-        }
-
-        @keyframes spin {
-            to { transform: rotate(360deg); }
-        }
+        body { font-family: sans-serif; padding: 20px; background: #f4f7f6; }
+        .upload-container { background: white; padding: 20px; border-radius: 8px; max-width: 500px; margin: 0 auto; }
+        .form-group { margin-bottom: 15px; }
+        label { display: block; font-weight: bold; margin-bottom: 5px; }
+        input[type="file"] { width: 100%; padding: 8px; box-sizing: border-box; }
+        .btn-submit { width: 100%; padding: 10px; background: #4a90e2; color: white; border: none; border-radius: 4px; font-weight: bold; cursor: pointer; }
+        .btn-submit:disabled { background: #ccc; }
+        #uploadProgress { margin-top: 20px; display: none; }
+        progress { width: 100%; height: 20px; }
+        #logList { background: #fafafa; border: 1px solid #eee; padding: 10px; max-height: 150px; overflow-y: auto; font-size: 0.85em; list-style: none; }
     </style>
 </head>
 <body>
 
-    <div class="upload-container">
-        <h2>Inventar Batch Upload</h2>
+<div class="upload-container">
+    <h2>Inventar Batch Upload</h2>
 
-        <form id="uploadForm">
-            <div class="form-group">
-                <label for="csv_file">1. items.csv Datei auswählen</label>
-                <!-- Akzeptiert nur CSV Dateien -->
-                <input type="file" id="csv_file" name="csv_file" accept=".csv" required>
-            </div>
+    <form id="batchUploadForm">
+        <div class="form-group">
+            <label for="csv_file">1. items.csv auswählen</label>
+            <input type="file" id="csv_file" name="csv_file" accept=".csv" required>
+        </div>
 
-            <div class="form-group">
-                <label for="images">2. Bilder auswählen</label>
-                <!-- multiple erlaubt das Auswählen mehrerer Bilder gleichzeitig -->
-                <input type="file" id="images" name="images" accept="image/*" multiple required>
-                <small style="color: #666; display: block; margin-top: 5px;">Du kannst mehrere Bilder markieren (Strg/Cmd gedrückt halten).</small>
-            </div>
+        <div class="form-group">
+            <label for="images">2. Bilder auswählen</label>
+            <input type="file" id="images" name="images" accept="image/*" multiple required>
+        </div>
 
-            <button type="submit" id="submitBtn" class="btn-submit">Daten hochladen</button>
-        </form>
+        <button type="submit" id="uploadBtn" class="btn-submit">Daten hochladen</button>
+    </form>
 
-        <div id="status-message"></div>
+    <div id="uploadProgress">
+        <div id="progressText">Bereite Upload vor...</div>
+        <progress id="progressBar" value="0" max="100"></progress>
+        <ul id="logList"></ul>
     </div>
+</div>
 
 <script>
-        document.getElementById('uploadForm').addEventListener('submit', async function(e) {
-            e.preventDefault();
+// Robuster CSV-Parser, der Kommas innerhalb von Anführungszeichen ignoriert
+function parseCSVLine(text) {
+    const result = [];
+    let cur = '';
+    let inQuotes = false;
+    for (let i = 0; i < text.length; i++) {
+        const c = text[i];
+        if (c === '"' || c === "'") {
+            inQuotes = !inQuotes;
+        } else if (c === ',' && !inQuotes) {
+            result.push(cur.trim());
+            cur = '';
+        } else {
+            cur += c;
+        }
+    }
+    result.push(cur.trim());
+    return result;
+}
 
-            const form = e.target;
-            const submitBtn = document.getElementById('submitBtn');
-            const statusDiv = document.getElementById('status-message');
+// Extrahiert Bildnamen aus Einträgen wie "['bild1.jpg', 'bild2.jpg']" oder "bild1.jpg"
+function extractImageNames(cellValue) {
+    if (!cellValue) return [];
+    let raw = cellValue.replace(/^["']|["']$/g, '').trim();
+    if (raw.startsWith('[') && raw.endsWith(']')) {
+        try {
+            const jsonValid = raw.replace(/'/g, '"');
+            return JSON.parse(jsonValid);
+        } catch (e) {
+            const matches = raw.match(/['"]([^'"]+)['"]/g);
+            if (matches) return matches.map(m => m.replace(/['"]/g, ''));
+        }
+    }
+    return raw ? [raw] : [];
+}
 
-            submitBtn.disabled = true;
-            submitBtn.innerText = 'Wird verarbeitet...';
-            statusDiv.className = 'loading';
-            statusDiv.style.display = 'block';
-            statusDiv.innerHTML = '<div class="spinner"></div> Lade Dateien hoch und verarbeite Bilder... Bitte warten.';
+document.getElementById('batchUploadForm').addEventListener('submit', async function(e) {
+    e.preventDefault();
 
-            const formData = new FormData(form);
+    const csvInput = document.getElementById('csv_file');
+    const imageInput = document.getElementById('images');
+    const uploadBtn = document.getElementById('uploadBtn');
+    const progressContainer = document.getElementById('uploadProgress');
+    const progressBar = document.getElementById('progressBar');
+    const progressText = document.getElementById('progressText');
+    const logList = document.getElementById('logList');
 
-            const fetchOptions = {
+    const csrfToken = document.querySelector('meta[name="csrf-token"]')?.getAttribute('content');
+
+    if (!csvInput.files.length) {
+        alert("Bitte wähle eine CSV-Datei aus.");
+        return;
+    }
+
+    uploadBtn.disabled = true;
+    progressContainer.style.display = 'block';
+    logList.innerHTML = '';
+
+    const log = (msg) => {
+        const li = document.createElement('li');
+        li.textContent = msg;
+        logList.appendChild(li);
+        logList.scrollTop = logList.scrollHeight;
+    };
+
+    const csvFile = csvInput.files[0];
+    const allImages = Array.from(imageInput.files);
+
+    // Map für schnellen Dateinamen-Vergleich (ohne Pfadangabe)
+    const imageMap = new Map();
+    allImages.forEach(file => {
+        imageMap.set(file.name.toLowerCase(), file);
+    });
+
+    const BATCH_SIZE = 50;
+
+    try {
+        const csvText = await csvFile.text();
+        let rows = csvText.split(/\r?\n/).filter(r => r.trim().length > 0);
+
+        if (rows.length <= 1) {
+            throw new Error("CSV-Datei ist leer oder enthält nur Kopfzeilen.");
+        }
+
+        const headerRow = rows[0];
+        const dataRows = rows.slice(1);
+
+        // 1. Client-Deduplizierung
+        const uniqueRowsSet = new Set();
+        const uniqueDataRows = [];
+        let duplicateCount = 0;
+
+        for (const row of dataRows) {
+            if (uniqueRowsSet.has(row)) {
+                duplicateCount++;
+            } else {
+                uniqueRowsSet.add(row);
+                uniqueDataRows.push(row);
+            }
+        }
+
+        log(`${uniqueDataRows.length} eindeutige Einträge. ${duplicateCount} Duplikate entfernt.`);
+
+        // Spalten-Index von "Images" ermitteln
+        const headers = parseCSVLine(headerRow).map(h => h.replace(/['"]/g, '').trim());
+        const imagesColIndex = headers.findIndex(h => h.toLowerCase() === 'images');
+
+        // 2. In Batches aufteilen
+        const batches = [];
+        for (let i = 0; i < uniqueDataRows.length; i += BATCH_SIZE) {
+            batches.push(uniqueDataRows.slice(i, i + BATCH_SIZE));
+        }
+
+        progressBar.max = batches.length;
+        progressBar.value = 0;
+
+        // 3. Sequenzieller Upload
+        for (let b = 0; b < batches.length; b++) {
+            const batchRows = batches[b];
+            progressText.textContent = `Lade Batch ${b + 1} von ${batches.length} hoch...`;
+
+            // Zuordnung der benötigten Bilder für diesen Batch
+            const requiredImagesForBatch = new Set();
+
+            if (imagesColIndex !== -1) {
+                batchRows.forEach(rowStr => {
+                    const cols = parseCSVLine(rowStr);
+                    if (cols[imagesColIndex]) {
+                        const imgNames = extractImageNames(cols[imagesColIndex]);
+                        imgNames.forEach(name => {
+                            const fileMatch = imageMap.get(name.toLowerCase());
+                            if (fileMatch) {
+                                requiredImagesForBatch.add(fileMatch);
+                            }
+                        });
+                    }
+                });
+            }
+
+            // CSV für diesen Batch erstellen
+            const batchCsvText = [headerRow, ...batchRows].join('\n');
+            const batchCsvBlob = new Blob([batchCsvText], { type: 'text/csv' });
+
+            const formData = new FormData();
+            formData.append('csv_file', batchCsvBlob, `batch_${b + 1}.csv`);
+
+            // CSRF-Token im Form-Field übergeben
+            if (csrfToken) {
+                formData.append('csrf_token', csrfToken);
+            }
+
+            // Zugehörige Bilder anfügen
+            requiredImagesForBatch.forEach(imgFile => {
+                formData.append('images', imgFile);
+            });
+
+            log(`Batch ${b + 1}: ${batchRows.length} Items & ${requiredImagesForBatch.size} zugehörige Bilder.`);
+
+            // Request mit CSRF-Header ausführen
+            const response = await fetch('/upload_csv_batch', {
                 method: 'POST',
                 body: formData,
-                credentials: 'include',
                 headers: {
-                    'X-Requested-With': 'XMLHttpRequest'
+                    'X-CSRFToken': csrfToken || ''
                 }
-            };
+            });
 
-            const csrfToken = document.querySelector('meta[name="csrf-token"]')?.getAttribute('content');
+            const result = await response.json();
 
-            if (csrfToken) {
-                fetchOptions.headers = {
-                    'X-CSRFToken': csrfToken
-                };
+            if (!response.ok || !result.success) {
+                throw new Error(result.message || `Server-Fehler ${response.status}`);
             }
 
-            try {
-                const response = await fetch('/upload_csv_batch', fetchOptions);
+            log(`Batch ${b + 1} abgeschlossen: ${result.message}`);
+            progressBar.value = b + 1;
+        }
 
-                // Antwort einmalig als Text auslesen, um sowohl JSON als auch HTML-Fehler abzufangen
-                const responseText = await response.text();
+        progressText.textContent = "Upload erfolgreich beendet!";
+        uploadBtn.disabled = false;
 
-                let result;
-                try {
-                    result = JSON.parse(responseText);
-                } catch (jsonError) {
-                    console.error("Server hat kein JSON gesendet. Antwort war:", responseText);
-                    throw new Error("Der Server hat einen HTML-Fehler zurückgegeben (z.B. Nginx 413 Entity Too Large oder Server-Crash). Siehe F12 Konsole.");
-                }
-
-                if (response.ok && result.success) {
-                    statusDiv.className = 'success';
-                    statusDiv.innerHTML = `<strong>Erfolg!</strong><br>${result.message}`;
-                    form.reset();
-                } else {
-                    statusDiv.className = 'error';
-                    statusDiv.innerHTML = `<strong>Fehler:</strong> ${result.message || 'Ein unbekannter Fehler ist aufgetreten.'}`;
-                }
-
-            } catch (error) {
-                statusDiv.className = 'error';
-                statusDiv.innerHTML = `<strong>Fehler:</strong> ${error.message}`;
-                console.error('Upload Error:', error);
-            } finally {
-                submitBtn.disabled = false;
-                submitBtn.innerText = 'Daten hochladen';
-            }
-        });
-    </script>
+    } catch (err) {
+        alert("Upload abgebrochen: " + err.message);
+        log("Fehler: " + err.message);
+        uploadBtn.disabled = false;
+    }
+});
+</script>
+</body>
+</html>