{
"event": "PreToolUse",
"tool_name": "Bash",
"tool_input": {
"command": "DB_PASSWORD=\"v8mFLmkF2fth_r\" timeout 300 .\/venv\/bin\/python run_demo.py 2>&1",
"timeout": 320000,
"description": "Run 2-pass entity extraction test"
}
}
{
"tool_response": {
"stdout": "[23:15:19] === START ===\n[23:15:19] 1. DB verbinden...\n[23:15:19] OK (0.0s)\n[23:15:19] 2. DB Reset (Tabellen leeren)...\n[23:15:19] entity_relations: OK\n[23:15:19] chunk_entities: OK\n[23:15:19] document_entities: OK\n[23:15:19] chunk_semantics: OK\n[23:15:19] chunk_taxonomy: OK\n[23:15:19] document_taxonomy: OK\n[23:15:19] document_pages: OK\n[23:15:19] entities: OK\n[23:15:19] chunks: OK\n[23:15:19] documents: OK\n[23:15:19] DB Reset done (0.0s)\n[23:15:19] 3. Qdrant Reset...\n[23:15:19] Qdrant: 200 (0.0s)\n[23:15:19] 4. PDF laden...\n[23:15:19] OK: 5561 chars, 3 pages (0.1s)\n[23:15:19] 5. Document in DB erstellen...\n[23:15:19] OK: doc_id=9 (0.0s)\n[23:15:19] 6. Text chunken...\n[23:15:19] OK: 4 chunks (0.0s)\n[23:15:19] 7. Chunks in DB speichern...\n[23:15:19] Chunk 1: 1899 chars -> id=29\n[23:15:19] Chunk 2: 1858 chars -> id=30\n[23:15:19] Chunk 3: 535 chars -> id=31\n[23:15:19] Chunk 4: 1521 chars -> id=32\n[23:15:19] OK: 4 chunks gespeichert (0.0s)\n[23:15:19] 8. YAML Prompt aus DB laden...\n[23:15:19] OK: Prompt geladen (0.0s)\n[23:15:19] Prompt-Preview:\nversion: \"1.0\"\nname: entity_extraction\n\ntask: |\n Extrahiere alle Fachbegriffe aus dem Text.\n Kategorisiere jeden Begriff nach den unten definierten Kriterien.\n\ncategories:\n PERSON: |\n Konkrete, namentlich genannte Einzelpersonen.\n Kriterium: Hat Vor- UND Nachname, ist eine historische\/reale Person.\n NICHT: Funktionsbezeichnungen oder Rollen.\n \n ORGANIZATION: |\n Institutionen, Grup...\n[23:15:19] 9. Entity Extraction (Ollama)...\n[23:15:19] Chunk 1\/4: 1899 chars...\n[23:16:16] -> 23 entities (57.0s)\n[23:16:16] - COACH PROFIL (ARTIFACT)\n[23:16:16] - Coaching (METHOD)\n[23:16:16] - Coach (ROLE)\n[23:16:16] - Rahmen (CONCEPT)\n[23:16:16] - Basisverhaltensweisen (CONCEPT)\n[23:16:16] ... und 18 weitere\n[23:16:16] Chunk 2\/4: 1858 chars...\n[23:17:26] -> 27 entities (69.9s)\n[23:17:26] - Kompetenzen in der Koproduktion (CONCEPT)\n[23:17:26] - individuelle Coach-Persönlichkeit (CONCEPT)\n[23:17:26] - Coach-System (MODEL)\n[23:17:26] - Coach-Rolle (ROLE)\n[23:17:26] - Wertschätzung (CONCEPT)\n[23:17:26] ... und 22 weitere\n[23:17:26] Chunk 3\/4: 535 chars...\n[23:17:44] -> 5 entities (17.9s)\n[23:17:44] - Transparenz (CONCEPT)\n[23:17:44] - Klienten (ROLE)\n[23:17:44] - Kollegen (PERSON)\n[23:17:44] - Prozess (CONCEPT)\n[23:17:44] - COACH PROFIL (ARTIFACT)\n[23:17:44] Chunk 4\/4: 1521 chars...\n[23:18:19] -> 13 entities (35.5s)\n[23:18:19] - Kompetenz-DNA (CONCEPT)\n[23:18:19] - Allparteilichkeit (PRINCIPLE)\n[23:18:19] - Coachees (ROLE)\n[23:18:19] - Neutralität (CONCEPT)\n[23:18:19] - Coachee (ROLE)\n[23:18:19] ... und 8 weitere\n[23:18:19] 10. Entities in DB speichern...\n[23:18:19] OK: 68 entities gespeichert (0.0s)\n[23:18:19] === ERGEBNIS ===\n[23:18:19] CONCEPT: 36\n[23:18:19] ROLE: 8\n[23:18:19] ARTIFACT: 4\n[23:18:19] LOCATION: 2\n[23:18:19] MODEL: 2\n[23:18:19] PRINCIPLE: 2\n[23:18:19] PERSON: 1\n[23:18:19] METHOD: 1\n[23:18:19] EVENT: 1\n[23:18:19] METAPHOR: 1\n[23:18:19] TOTAL: 58 entities\n[23:18:19] === DONE ===",
"stderr": "",
"interrupted": false,
"isImage": false
}
}