{
"event": "PreToolUse",
"tool_name": "Bash",
"tool_input": {
"command": "DB_PASSWORD=\"v8mFLmkF2fth_r\" .\/venv\/bin\/python -c \"\nimport requests\nimport json\nfrom db import db\n\ndb.connect()\n\n# 1. Get embedding with Ollama\nprint('1. Erzeuge Embedding...')\nresp = requests.post('http:\/\/localhost:11434\/api\/embeddings', json={\n 'model': 'mxbai-embed-large',\n 'prompt': 'Was ist ein Coach?'\n})\nembedding = resp.json()['embedding']\nprint(f' Dimension: {len(embedding)}')\n\n# 2. Search Qdrant\nprint('2. Suche in Qdrant...')\nresp = requests.post('http:\/\/localhost:6333\/collections\/documents\/points\/search', json={\n 'vector': embedding,\n 'limit': 3,\n 'with_payload': True\n})\nresults = resp.json()['result']\nprint(f' Gefunden: {len(results)} Chunks')\n\n# 3. Enrich with semantic data\nprint('3. Semantic Enrichment...')\nfor r in results:\n chunk_id = r['payload'].get('chunk_id')\n if chunk_id:\n # Get entities\n cursor = db.execute('''\n SELECT e.name, e.type \n FROM chunk_entities ce \n JOIN entities e ON ce.entity_id = e.id \n WHERE ce.chunk_id = %s \n ORDER BY ce.relevance_score DESC LIMIT 5\n ''', (chunk_id,))\n entities = cursor.fetchall()\n cursor.close()\n r['payload']['entities'] = entities\n\n# 4. Show results\nprint()\nprint('=== Results mit Entities ===')\nfor i, r in enumerate(results):\n print(f\\\"{i+1}. {r['payload'].get('document_title')} (Score: {r['score']:.3f})\\\")\n print(f\\\" Chunk ID: {r['payload'].get('chunk_id')}\\\")\n entities = r['payload'].get('entities', [])\n if entities:\n names = [e['name'] for e in entities[:4]]\n print(f\\\" Entities: {', '.join(names)}\\\")\n print()\n\nprint('✅ Semantic Enrichment funktioniert!')\ndb.disconnect()\n\"",
"timeout": 30000,
"description": "Test semantic enrichment with Ollama only"
}
}
{
"tool_response": {
"stdout": "1. Erzeuge Embedding...\n Dimension: 1024\n2. Suche in Qdrant...\n Gefunden: 3 Chunks\n3. Semantic Enrichment...\n\n=== Results mit Entities ===\n1. demo.pdf (Score: 0.765)\n Chunk ID: 41\n Entities: Coach, DNA, COACH PROFIL, KOMPETENZ-DNA\n\n2. demo.pdf (Score: 0.735)\n Chunk ID: 42\n Entities: Coach, Klienten, Erleben, Wertschätzung\n\n3. demo.pdf (Score: 0.686)\n Chunk ID: 43\n Entities: COACH PROFIL, Coach, Klienten\n\n✅ Semantic Enrichment funktioniert!",
"stderr": "",
"interrupted": false,
"isImage": false
}
}