fix of the json upload format

- Created '/upload_csv_batch' endpoint to handle CSV parsing and multiple image uploads
- Added automatic WebP conversion and GridFS storage for batch images
- Implemented grouping logic via 'series_group_id' based on item name
- Created '/batch_upload' route and 'upload_batch.html' for a seamless async frontend

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')
@@ -417,6 +417,8 @@ 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
@@ -665,11 +667,14 @@ 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)
@@ -11845,3 +11850,248 @@ def test_push_notification():
     except Exception as e:
         app.logger.error(f'Error sending test push: {e}')
         return jsonify({'success': False}), 500
+
+
+@app.route('/batch_upload', methods=['GET'])
+def batch_upload_page():
+    """
+    Serves the HTML frontend for the batch CSV and image upload.
+    """
+    # Check permissions if necessary, similar to your other routes
+    if 'username' not in session:
+        flash('Bitte melden Sie sich an.', 'error')
+        return redirect(url_for('login'))
+
+    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 with deduplication (SHA-256 hash matching),
+    GridFS storage, code generation, location syncing, and grouped item creation.
+    """
+    import pandas as pd
+    import ast
+    import hashlib
+
+    username = session.get('username', 'System')
+
+    fs = get_gridfs()
+    upload_session_id = str(uuid.uuid4())[:8]
+    app.logger.info(f"Starting CSV Batch upload session {upload_session_id} - User: {username}")
+
+    # 1. Dateien aus dem Request empfangen
+    if 'csv_file' not in request.files:
+        return jsonify({"success": False, "message": "Keine CSV-Datei hochgeladen"}), 400
+
+    csv_file = request.files['csv_file']
+    uploaded_images = request.files.getlist('images')
+
+    # 2. CSV Einlesen und Validieren
+    try:
+        df = pd.read_csv(csv_file)
+    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
+
+    if 'Name' not in df.columns:
+        return jsonify({"success": False, "message": "Die CSV muss zwingend eine 'Name' Spalte enthalten."}), 400
+
+    # 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):
+        if not image or not image.filename:
+            continue
+
+        original_secure_name = secure_filename(image.filename)
+        base_name_no_ext = os.path.splitext(original_secure_name)[0]
+        image_log_prefix = f"[Upload {upload_session_id}][Image {index + 1}/{len(uploaded_images)}]"
+
+        try:
+            image.seek(0)
+            image_bytes = image.read()
+            if not image_bytes:
+                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'):
+                    img = img.convert('RGBA')
+
+                max_width = 500
+                if img.width > max_width:
+                    ratio = max_width / img.width
+                    new_size = (max_width, int(img.height * ratio))
+                    img = img.resize(new_size, Image.Resampling.LANCZOS)
+
+                img.save(optimized_io, format='WEBP', quality=85, optimize=True)
+
+            optimized_io.seek(0)
+            new_filename = f"{uuid.uuid4().hex}_{int(time.time())}.webp"
+
+            # In GridFS speichern
+            file_id = fs.put(
+                optimized_io,
+                filename=new_filename,
+                content_type='image/webp',
+                metadata={
+                    'original_filename': original_secure_name,
+                    'upload_session': upload_session_id,
+                    'batch_upload': True
+                }
+            )
+
+            # In Hash-Tabelle und Mapping sichern
+            processed_hashes[img_hash] = new_filename
+            image_mapping[base_name_no_ext] = new_filename
+            processed_count += 1
+
+        except Exception as e:
+            app.logger.error(f"{image_log_prefix} Processing failed: {str(e)}")
+            error_count += 1
+
+    # 4. Predefined Locations laden
+    try:
+        predefined_locations = it.get_predefined_locations()
+    except Exception:
+        predefined_locations = []
+
+    # 5. Dataframe bereinigen & gruppieren
+    df['Name'] = df['Name'].fillna('Unbenannt').astype(str)
+    df = df.fillna({
+        'Ort': 'Unbekannt',
+        'Beschreibung': '',
+        'Code_4': '',
+        'Anschaffungsjahr': '',
+        'Anschaffungskosten': ''
+    })
+
+    created_item_ids = []
+    grouped_items = df.groupby('Name')
+
+    for name, group in grouped_items:
+        item_count = len(group)
+        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):
+
+            # 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:
+                    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]
+                            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
+
+            def parse_filter_col(col_data):
+                try:
+                    res = ast.literal_eval(str(col_data))
+                    return res if isinstance(res, list) else []
+                except Exception:
+                    return []
+
+            filter_upload = parse_filter_col(row.get('Filter', '[]'))
+            filter_upload2 = parse_filter_col(row.get('Filter2', '[]'))
+            filter_upload3 = parse_filter_col(row.get('Filter3', '[]'))
+
+            reservierbar = bool(row.get('Reservierbar', False))
+
+            # 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']),                             # 1. Name
+                ort_val,                                      # 2. Ort
+                str(row['Beschreibung']),                     # 3. Beschreibung
+                item_image_filenames,                         # 4. Image Filenames (GridFS)
+                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=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)
+                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. "
+        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. {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/requirements.txt

@@ -17,4 +17,5 @@ cryptography>=42.0.0
 pywebpush
 py-vapid>=1.9.0
 beautifulsoup4
-pywebpush
+pywebpush
+pandas

Web/templates/upload_batch.html

@@ -0,0 +1,217 @@
+<!DOCTYPE html>
+<html lang="de">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Batch Upload - CSV & Bilder</title>
+    <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); }
+        }
+    </style>
+</head>
+<body>
+
+    <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>
+
+            <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>
+
+            <button type="submit" id="submitBtn" class="btn-submit">Daten hochladen</button>
+        </form>
+
+        <div id="status-message"></div>
+    </div>
+
+<script>
+        document.getElementById('uploadForm').addEventListener('submit', async function(e) {
+            e.preventDefault();
+
+            const form = e.target;
+            const submitBtn = document.getElementById('submitBtn');
+            const statusDiv = document.getElementById('status-message');
+
+            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.';
+
+            const formData = new FormData(form);
+
+            const fetchOptions = {
+                method: 'POST',
+                body: formData,
+                credentials: 'include',
+                headers: {
+                    'X-Requested-With': 'XMLHttpRequest'
+                }
+            };
+
+            const csrfToken = document.querySelector('meta[name="csrf-token"]')?.getAttribute('content');
+
+            if (csrfToken) {
+                fetchOptions.headers = {
+                    'X-CSRFToken': csrfToken
+                };
+            }
+
+            try {
+                const response = await fetch('/upload_csv_batch', fetchOptions);
+
+                // Antwort einmalig als Text auslesen, um sowohl JSON als auch HTML-Fehler abzufangen
+                const responseText = await response.text();
+
+                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>

requirements.txt

@@ -17,4 +17,5 @@ cryptography>=42.0.0
 pywebpush
 py-vapid>=1.9.0
 beautifulsoup4
-pywebpush
+pywebpush
+pandas