feat: Add data quality verification & cleanup scripts

## Data Quality & Cleanup (Priorities 1-6)

Added comprehensive data quality verification and cleanup system:

**Scripts créés**:
- verify_data_quality.py: Analyse qualité complète œuvre par œuvre
- clean_duplicate_documents.py: Nettoyage doublons Documents
- populate_work_collection.py/clean.py: Peuplement Work collection
- fix_chunks_count.py: Correction chunksCount incohérents
- manage_orphan_chunks.py: Gestion chunks orphelins (3 options)
- clean_orphan_works.py: Suppression Works sans chunks
- add_missing_work.py: Création Work manquant
- generate_schema_stats.py: Génération stats auto
- migrate_add_work_collection.py: Migration sûre Work collection

**Documentation**:
- WEAVIATE_GUIDE_COMPLET.md: Guide consolidé complet (600+ lignes)
- WEAVIATE_SCHEMA.md: Référence schéma rapide
- NETTOYAGE_COMPLETE_RAPPORT.md: Rapport nettoyage session
- ANALYSE_QUALITE_DONNEES.md: Analyse qualité initiale
- rapport_qualite_donnees.txt: Output brut vérification

**Résultats nettoyage**:
- Documents: 16 → 9 (7 doublons supprimés)
- Works: 0 → 9 (peuplé + nettoyé)
- Chunks: 5,404 → 5,230 (174 orphelins supprimés)
- chunksCount: Corrigés (231 → 5,230 déclaré = réel)
- Cohérence parfaite: 9 Works = 9 Documents = 9 œuvres

**Modifications code**:
- schema.py: Ajout Work collection avec vectorisation
- utils/weaviate_ingest.py: Support Work ingestion
- utils/word_pipeline.py: Désactivation concepts (problème .lower())
- utils/word_toc_extractor.py: Métadonnées Word correctes
- .gitignore: Exclusion fichiers temporaires (*.wav, output/*, NUL)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

generations/library_rag/show_works.py

@@ -0,0 +1,91 @@
+"""Script to display all documents from the Weaviate Document collection in table format.
+
+Usage:
+    python show_works.py
+"""
+
+import weaviate
+from typing import Any
+from tabulate import tabulate
+from datetime import datetime
+
+
+def format_date(date_val: Any) -> str:
+    """Format date for display.
+
+    Args:
+        date_val: Date value (string or datetime).
+
+    Returns:
+        Formatted date string.
+    """
+    if date_val is None:
+        return "-"
+    if isinstance(date_val, str):
+        try:
+            dt = datetime.fromisoformat(date_val.replace('Z', '+00:00'))
+            return dt.strftime("%Y-%m-%d %H:%M")
+        except:
+            return date_val
+    return str(date_val)
+
+
+def display_documents() -> None:
+    """Connect to Weaviate and display all Document objects in table format."""
+    try:
+        # Connect to local Weaviate instance
+        client = weaviate.connect_to_local()
+
+        try:
+            # Get Document collection
+            document_collection = client.collections.get("Document")
+
+            # Fetch all documents
+            response = document_collection.query.fetch_objects(limit=1000)
+
+            if not response.objects:
+                print("No documents found in the collection.")
+                return
+
+            # Prepare data for table
+            table_data = []
+            for obj in response.objects:
+                props = obj.properties
+
+                # Extract nested work object
+                work = props.get("work", {})
+                work_title = work.get("title", "N/A") if isinstance(work, dict) else "N/A"
+                work_author = work.get("author", "N/A") if isinstance(work, dict) else "N/A"
+
+                table_data.append([
+                    props.get("sourceId", "N/A"),
+                    work_title,
+                    work_author,
+                    props.get("edition", "-"),
+                    props.get("pages", "-"),
+                    props.get("chunksCount", "-"),
+                    props.get("language", "-"),
+                    format_date(props.get("createdAt")),
+                ])
+
+            # Display header
+            print(f"\n{'='*120}")
+            print(f"Collection Document - {len(response.objects)} document(s) trouvé(s)")
+            print(f"{'='*120}\n")
+
+            # Display table
+            headers = ["Source ID", "Work Title", "Author", "Edition", "Pages", "Chunks", "Lang", "Created At"]
+            print(tabulate(table_data, headers=headers, tablefmt="grid"))
+            print()
+
+        finally:
+            client.close()
+
+    except Exception as e:
+        print(f"Error connecting to Weaviate: {e}")
+        print("\nMake sure Weaviate is running:")
+        print("  docker compose up -d")
+
+
+if __name__ == "__main__":
+    display_documents()