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"content": "```sql\nCREATE TABLE rag_collections (\n id INT AUTO_INCREMENT PRIMARY KEY,\n collection_id VARCHAR(100) NOT NULL UNIQUE, -- Qdrant-Name: \"documents\"\n display_name VARCHAR(100) NOT NULL, -- Anzeige: \"Dokumente\"\n description TEXT, -- \"PDF-Dokumente aus Nextcloud\"\n\n -- Qdrant-Metadaten (via Sync)\n vector_size INT, -- 1024\n distance_metric VARCHAR(20), -- \"Cosine\"\n points_count INT DEFAULT 0, -- Anzahl Vektoren\n\n -- Konfiguration\n embedding_model VARCHAR(100), -- \"mxbai-embed-large\"\n chunk_size INT, -- 2000\n chunk_overlap INT, -- 200\n\n -- Verwaltung\n source_type ENUM('nextcloud', 'mail', 'manual', 'system') DEFAULT 'manual',\n source_path VARCHAR(500), -- \"\/var\/www\/nextcloud\/data\/...\"\n is_active BOOLEAN DEFAULT TRUE, -- In Dropdowns anzeigen?\n is_searchable BOOLEAN DEFAULT TRUE, -- Für RAG verfügbar?\n sort_order INT DEFAULT 0,\n\n -- Timestamps\n last_synced_at DATETIME,\n created_at DATETIME DEFAULT CURRENT_TIMESTAMP,\n updated_at DATETIME DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP\n) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;\n```\n\n### 0b.3 Impact-Analyse: Wer nutzt Collections?\n\n| System\/Seite | Aktueller Zugriff | Neuer Zugriff | Änderung |\n|--------------|-------------------|---------------|----------|\n| **Chat** | `$qdrantService->listCollections()` | `CollectionRepository::getActive()` | Query aus DB |\n| **Content Studio** | `$qdrantService->listCollections()` | `CollectionRepository::getActive()` | Query aus DB |\n| **Content Show** | `$qdrantService->listCollections()` | `CollectionRepository::getActive()` | Query aus DB |\n| **Pipeline (Python)** | `config.py QDRANT_COLLECTIONS` | DB-Query oder Config-Sync | Python liest DB |\n| **Semantic Explorer** | Direkt Qdrant | `CollectionRepository` + Qdrant | Metadaten aus DB |",
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