fix of the json upload format

Web/app.py

@@ -108,7 +108,7 @@ app.config['UPLOAD_FOLDER'] = cfg.UPLOAD_FOLDER
 app.config['THUMBNAIL_FOLDER'] = cfg.THUMBNAIL_FOLDER
 app.config['PREVIEW_FOLDER'] = cfg.PREVIEW_FOLDER
 app.config['ALLOWED_EXTENSIONS'] = set(cfg.ALLOWED_EXTENSIONS)
-app.config['MAX_CONTENT_LENGTH'] = max(cfg.MAX_UPLOAD_MB, cfg.IMAGE_MAX_UPLOAD_MB, cfg.VIDEO_MAX_UPLOAD_MB) * 1024 * 1024
+app.config['MAX_CONTENT_LENGTH'] = 1024 * 1024 * 1024
 app.config['SESSION_COOKIE_HTTPONLY'] = True
 app.config['SESSION_COOKIE_SAMESITE'] = 'Lax'
 app.config['SESSION_COOKIE_SECURE'] = cfg.SSL_ENABLED if os.getenv('INVENTAR_SESSION_COOKIE_SECURE') is None else os.getenv('INVENTAR_SESSION_COOKIE_SECURE', '').strip().lower() in ('1', 'true', 'yes', 'on')
@@ -665,11 +665,14 @@ def handle_unexpected_exception(e):
 
 
 def _csrf_error_response(message='CSRF token fehlt oder ist ungültig.'):
-    if request.is_json or request.path.startswith('/api/') or request.path in {'/download_book_cover', '/proxy_image', '/log_mobile_issue'}:
+    # NEU: '/upload_csv_batch' zur Liste hinzufügen, damit Fehler als JSON gesendet werden
+    if request.is_json or request.path.startswith('/api/') or request.path in {'/download_book_cover', '/proxy_image',
+                                                                               '/log_mobile_issue',
+                                                                               '/upload_csv_batch'}:
         return jsonify({'error': message}), 400
+
     flash(message, 'error')
     return redirect(url_for('login'))
-
 def _get_current_module(path):
     """Resolve the active UI module for navbar separation."""
     mod = cfg.MODULES.get_module_for_path(path)
@@ -11859,23 +11862,58 @@ def batch_upload_page():
 
     return render_template('upload_batch.html')
 
+def clean_db_field(val):
+    """Bereinigt Werte, die fälschlicherweise als String-Listen oder mit Klammern aus der CSV kommen."""
+    import ast
+    import pandas as pd
+
+    if not val or pd.isna(val):
+        return None
+
+    val_str = str(val).strip()
+
+    # Wenn es wie eine Liste aussieht (z.B. "['100177']" oder "['']")
+    if val_str.startswith("[") and val_str.endswith("]"):
+        try:
+            parsed = ast.literal_eval(val_str)
+            if isinstance(parsed, list):
+                # Nimm das erste Element der Liste, wenn vorhanden
+                for item in parsed:
+                    cleaned_item = str(item).strip()
+                    if cleaned_item and cleaned_item not in ("", "''", '""', "None", "nan"):
+                        return cleaned_item
+                return None
+        except Exception:
+            # Fallback bei Syntaxfehlern
+            inner = val_str[1:-1].strip().replace("'", "").replace('"', '')
+            return inner if inner and inner not in ("''", '""') else None
+
+    if val_str in ("[]", "['']", '[""]', "nan", "None", "''", '""'):
+        return None
+
+    return val_str
+
+
 
 @app.route('/upload_csv_batch', methods=['POST'])
 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):
+        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]
@@ -11890,7 +11928,7 @@ 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
@@ -11898,10 +11936,11 @@ 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)
+    # 3. Bilder verarbeiten & Duplikate im selben Durchlauf filtern (Hash-Matching)
     image_mapping = {}
+    processed_hashes = {}
     processed_count = 0
+    dedup_count = 0
     error_count = 0
 
     for index, image in enumerate(uploaded_images):
@@ -11913,14 +11952,20 @@ def upload_csv_batch():
         image_log_prefix = f"[Upload {upload_session_id}][Image {index + 1}/{len(uploaded_images)}]"
 
         try:
-            # Annahme: is_allowed, error_message = allowed_file(...)
-
             image.seek(0)
             image_bytes = image.read()
             if not image_bytes:
                 error_count += 1
                 continue
 
+            img_hash = hashlib.sha256(image_bytes).hexdigest()
+
+            if img_hash in processed_hashes:
+                existing_filename = processed_hashes[img_hash]
+                image_mapping[base_name_no_ext] = existing_filename
+                dedup_count += 1
+                continue
+
             optimized_io = io.BytesIO()
             with Image.open(io.BytesIO(image_bytes)) as img:
                 if img.mode not in ('RGB', 'RGBA'):
@@ -11937,8 +11982,7 @@ 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
-            file_id = fs.put(
+            fs.put(
                 optimized_io,
                 filename=new_filename,
                 content_type='image/webp',
@@ -11949,7 +11993,7 @@ def upload_csv_batch():
                 }
             )
 
-            # Im Mapping speichern (damit wir sie später der CSV zuordnen können)
+            processed_hashes[img_hash] = new_filename
             image_mapping[base_name_no_ext] = new_filename
             processed_count += 1
 
@@ -11957,11 +12001,14 @@ 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)
-    # Gruppierung über den Namen: Alle Zeilen mit demselben Namen gehören zur selben Serie
-    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
+    df['Name'] = df['Name'].fillna('Unbenannt').astype(str).str.strip()
     df = df.fillna({
         'Ort': 'Unbekannt',
         'Beschreibung': '',
@@ -11970,40 +12017,59 @@ def upload_csv_batch():
         'Anschaffungskosten': ''
     })
 
+    # --- WICHTIG: Gruppierung über einen normalisierten Schlüssel ermöglichen ---
+    # Erstellt eine unsichtbare Hilfsspalte, die Leerzeichen/Groß-Kleinschreibung ignoriert,
+    # damit identische Artikel-Typen sauber als Serie erkannt werden.
+    df['GroupKey'] = df['Name'].str.lower()
+
     created_item_ids = []
+    grouped_items = df.groupby('GroupKey')
 
-    grouped_items = df.groupby('Name')
-
-    for name, group in grouped_items:
+    for group_key, group in grouped_items:
         item_count = len(group)
         series_group_id = str(uuid.uuid4()) if item_count > 1 else None
         parent_item_id = None
 
+        # Originalen Namen des ersten Elements der Gruppe übernehmen
+        actual_group_name = group.iloc[0]['Name']
+
+        # Basis-Code für automatisierte Seriencodes ermitteln
+        first_row_code = clean_db_field(group.iloc[0].get('Code_4', ''))
+        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_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 zuordnen und pro Artikel deduplizieren
             item_image_filenames = []
             if 'Images' in row and pd.notna(row['Images']):
                 try:
-                    # Aus "['Bild1.JPG', 'Bild2.JPG']" wird eine Liste
                     img_list = ast.literal_eval(str(row['Images']))
                     if isinstance(img_list, list):
                         for img_name in img_list:
                             base_img_name = os.path.splitext(img_name)[0]
-                            # Falls das Bild hochgeladen wurde, die WebP GridFS ID/Name nehmen
                             if base_img_name in image_mapping:
                                 item_image_filenames.append(image_mapping[base_img_name])
-                            else:
-                                app.logger.warning(f"Bild {img_name} in CSV definiert, aber nicht hochgeladen.")
                 except (ValueError, SyntaxError):
                     pass
 
-            # Filter extrahieren (falls vorhanden, erwarte string list wie "['HSU', '', '', '']")
+            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', '[]'))
@@ -12012,46 +12078,53 @@ def upload_csv_batch():
 
             reservierbar = bool(row.get('Reservierbar', False))
 
-            # DB Insert Funktion aufrufen (orientiert an deiner upload_item)
+            # Code_4 / Barcode sauber extrahieren und bereinigen
+            raw_code = row.get('Code_4') or row.get('Barcode') or ''
+            row_code = clean_db_field(raw_code)
+
+            if row_code:
+                unique_code = row_code
+            elif item_count > 1:
+                unique_code = generate_unique_batch_code(base_code, position)
+            else:
+                unique_code = None
+
+            # DB Insert
             item_id = it.add_item(
-                name=row['Name'],
-                ort=row['Ort'],
-                beschreibung=row['Beschreibung'],
-                image_filenames=item_image_filenames,
-                filter_upload=filter_upload,
-                filter_upload2=filter_upload2,
-                filter_upload3=filter_upload3,
-                anschaffungs_jahr=str(row['Anschaffungsjahr']) if row['Anschaffungsjahr'] else None,
-                anschaffungs_kosten=str(row['Anschaffungskosten']) if row['Anschaffungskosten'] else None,
-                code_4=str(row['Code_4']) if row['Code_4'] else None,
+                str(actual_group_name),                       # 1. Name
+                ort_val,                                      # 2. Ort
+                str(row['Beschreibung']),                     # 3. Beschreibung
+                unique_image_filenames,                       # 4. Image Filenames (GridFS)
+                filter_upload,                                # 5. Filter 1
+                filter_upload2,                               # 6. Filter 2
+                filter_upload3,                               # 7. Filter 3
+                clean_db_field(row.get('Anschaffungsjahr')),  # 8. Jahr
+                clean_db_field(row.get('Anschaffungskosten')),# 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,
-                # Default Werte, falls keine Bibliotheks-CSV
-                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:
                 created_item_ids.append(item_id)
-                # Das erste Item in einer Serie wird der Parent für die restlichen
                 if position == 1:
                     parent_item_id = str(item_id)
             else:
-                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.")
+                app.logger.error(f"Fehler beim Erstellen von Item: {actual_group_name} (Index {index})")
 
     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.",
         "created_count": len(created_item_ids),
         "images_processed": processed_count,
+        "images_deduplicated": dedup_count,
         "images_failed": error_count
     }), 200

Web/templates/upload_batch.html

@@ -3,203 +3,262 @@
 <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(); // Verhindert das Neuladen der Seite
+<script>
+// 1. Ein echter CSV-Parser, der Zeilenumbrüche und Kommas in Texten korrekt ignoriert
+function parseCSV(csvString) {
+    const rows = [];
+    let currentRow = [];
+    let currentCell = '';
+    let insideQuotes = false;
 
-            const form = e.target;
-            const submitBtn = document.getElementById('submitBtn');
-            const statusDiv = document.getElementById('status-message');
+    for (let i = 0; i < csvString.length; i++) {
+        const char = csvString[i];
+        const nextChar = csvString[i + 1];
 
-            // UI auf "Laden" setzen
-            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.';
+        if (char === '"' && insideQuotes && nextChar === '"') {
+            currentCell += '"';
+            i++; // Escaped Quotes ("") überspringen
+        } else if (char === '"') {
+            insideQuotes = !insideQuotes;
+        } else if (char === ',' && !insideQuotes) {
+            currentRow.push(currentCell);
+            currentCell = '';
+        } else if ((char === '\n' || char === '\r') && !insideQuotes) {
+            if (char === '\r' && nextChar === '\n') i++; // Windows Umbrüche überspringen
+            currentRow.push(currentCell);
+            // Leere Zeilen ignorieren
+            if (currentRow.length > 1 || currentRow[0] !== '') {
+                rows.push(currentRow);
+            }
+            currentRow = [];
+            currentCell = '';
+        } else {
+            currentCell += char;
+        }
+    }
+    if (currentCell !== '' || currentRow.length > 0) {
+        currentRow.push(currentCell);
+        if (currentRow.length > 1 || currentRow[0] !== '') {
+            rows.push(currentRow);
+        }
+    }
+    return rows;
+}
 
-            // FormData sammelt alle Inputs aus dem Formular (csv_file und images)
-            const formData = new FormData(form);
+// 2. Baut das Array wieder sicher zu einer sauberen CSV-Zeile für das Backend zusammen
+function rowToCSV(rowArray) {
+    return rowArray.map(cell => {
+        if (cell === null || cell === undefined) return '';
+        let cellStr = String(cell);
+        // Wenn kritische Zeichen drin sind, sauber in Anführungszeichen verpacken
+        if (cellStr.includes(',') || cellStr.includes('"') || cellStr.includes('\n') || cellStr.includes('\r')) {
+            return '"' + cellStr.replace(/"/g, '""') + '"';
+        }
+        return cellStr;
+    }).join(',');
+}
+
+// 3. Bildnamen extrahieren (bleibt wie es war)
+function extractImageNames(cellValue) {
+    if (!cellValue) return [];
+    let raw = String(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] : [];
+}
+
+document.getElementById('batchUploadForm').addEventListener('submit', async function(e) {
+    e.preventDefault();
+
+    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 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);
+
+    const imageMap = new Map();
+    allImages.forEach(file => {
+        imageMap.set(file.name.toLowerCase(), file);
+    });
+
+    const BATCH_SIZE = 50;
+
+    try {
+        const csvText = await csvFile.text();
+        // Hier rufen wir jetzt unseren sicheren Parser auf!
+        const allRows = parseCSV(csvText);
+
+        if (allRows.length <= 1) {
+            throw new Error("CSV-Datei ist leer oder enthält nur Kopfzeilen.");
+        }
+
+        const headerRow = allRows[0];
+        const dataRows = allRows.slice(1);
+
+        log(`${dataRows.length} Einträge gefunden. Bereite Batches vor...`);
+
+        // Spalten-Index von "Images" sicher ermitteln
+        const imagesColIndex = headerRow.findIndex(h => h.toLowerCase().trim() === 'images');
+
+        // In Batches aufteilen
+        const batches = [];
+        for (let i = 0; i < dataRows.length; i += BATCH_SIZE) {
+            batches.push(dataRows.slice(i, i + BATCH_SIZE));
+        }
+
+        progressBar.max = batches.length;
+        progressBar.value = 0;
+
+        for (let b = 0; b < batches.length; b++) {
+            const batchRows = batches[b];
+            progressText.textContent = `Lade Batch ${b + 1} von ${batches.length} hoch...`;
+
+            const requiredImagesForBatch = new Set();
+
+            if (imagesColIndex !== -1) {
+                batchRows.forEach(rowCols => {
+                    if (rowCols[imagesColIndex]) {
+                        const imgNames = extractImageNames(rowCols[imagesColIndex]);
+                        imgNames.forEach(name => {
+                            const fileMatch = imageMap.get(name.toLowerCase());
+                            if (fileMatch) {
+                                requiredImagesForBatch.add(fileMatch);
+                            }
+                        });
+                    }
+                });
+            }
+
+            // Sicherer Zusammenbau des CSV-Batches
+            const batchCsvArray = [headerRow, ...batchRows];
+            const batchCsvText = batchCsvArray.map(rowToCSV).join('\n');
+            const batchCsvBlob = new Blob([batchCsvText], { type: 'text/csv' });
+
+            const formData = new FormData();
+            formData.append('csv_file', batchCsvBlob, `batch_${b + 1}.csv`);
+
+            if (csrfToken) {
+                formData.append('csrf_token', csrfToken);
+            }
+
+            requiredImagesForBatch.forEach(imgFile => {
+                formData.append('images', imgFile);
+            });
+
+            log(`Batch ${b + 1}: ${batchRows.length} Items & ${requiredImagesForBatch.size} zugehörige Bilder.`);
+
+            // Request absenden
+            const response = await fetch('/upload_csv_batch', {
+                method: 'POST',
+                body: formData,
+                headers: {
+                    'X-CSRFToken': csrfToken || ''
+                }
+            });
+
+            // 1. Antwort als rohen Text auslesen (verhindert den JSON.parse Crash)
+            const responseText = await response.text();
+            let result;
 
             try {
-                // Sende die Daten an den Flask-Endpoint
-                const response = await fetch('/upload_csv_batch', {
-                    method: 'POST',
-                    body: formData
-                });
-
-                const result = await response.json();
-
-                if (response.ok && result.success) {
-                    // Erfolgreicher Upload
-                    statusDiv.className = 'success';
-                    statusDiv.innerHTML = `
-                        <strong>Erfolg!</strong><br>
-                        ${result.message}
-                    `;
-                    form.reset(); // Formular nach Erfolg leeren
-                } else {
-                    // Fehler vom Server (z.B. falsches Format, fehlende Rechte)
-                    statusDiv.className = 'error';
-                    statusDiv.innerHTML = `<strong>Fehler:</strong> ${result.message || 'Ein unbekannter Fehler ist aufgetreten.'}`;
-                }
-            } catch (error) {
-                // Netzwerkfehler oder Server-Absturz
-                statusDiv.className = 'error';
-                statusDiv.innerHTML = `<strong>Verbindungsfehler:</strong> Konnte den Server nicht erreichen.`;
-                console.error('Upload Error:', error);
-            } finally {
-                // UI wieder freigeben
-                submitBtn.disabled = false;
-                submitBtn.innerText = 'Daten hochladen';
+                result = JSON.parse(responseText);
+            } catch (parseErr) {
+                // Wenn der Server kein JSON schickt (z.B. Python 500 Error als HTML-Seite)
+                console.error("Server-Antwort war kein JSON:", responseText);
+                throw new Error(`Server-Fehler (Status ${response.status}). Der Server hat ein HTML-Dokument statt JSON zurückgegeben. Prüfe die Flask-Konsole!`);
             }
-        });
-    </script>
+
+            if (!response.ok || !result.success) {
+                throw new Error(result.message || `Server-Fehler ${response.status}`);
+            }
+
+            log(`Batch ${b + 1} abgeschlossen: ${result.message}`);
+            progressBar.value = b + 1;
+        }
+
+        progressText.textContent = "Upload erfolgreich beendet! Keine verschobenen Spalten mehr.";
+        uploadBtn.disabled = false;
+
+    } catch (err) {
+        alert("Upload abgebrochen: " + err.message);
+        log("Fehler: " + err.message);
+        uploadBtn.disabled = false;
+    }
+});
+</script>
 </body>
 </html>