{
"event": "PreToolUse",
"tool_name": "Bash",
"tool_input": {
"command": ".\/venv\/bin\/python -c \"\nfrom analyzers.relation_extractor import extract_relations\nfrom analyzers.entity_extractor import find_entity_by_name\nfrom db import db\n\ndb.connect()\n\n# Get sample text\ncursor = db.execute('SELECT content FROM chunks WHERE document_id = 1 LIMIT 3')\nchunks = cursor.fetchall()\ncursor.close()\ntext = ' '.join([c['content'] for c in chunks])\n\n# Get existing entities\ncursor = db.execute('SELECT name, type FROM entities LIMIT 10')\nentities = [{'name': e['name'], 'type': e['type']} for e in cursor.fetchall()]\ncursor.close()\n\nprint(f'Testing with {len(entities)} entities...')\nprint(f'Entities: {[e[\\\"name\\\"] for e in entities[:5]]}...')\n\n# Extract relations\nrelations = extract_relations(text[:3000], entities)\nprint(f'Extracted {len(relations)} relations')\n\n# Test find_entity_by_name\nfor rel in relations[:3]:\n source = find_entity_by_name(rel['source'])\n target = find_entity_by_name(rel['target'])\n print(f' {rel[\\\"source\\\"]} -> {rel[\\\"target\\\"]}: source={source is not None}, target={target is not None}')\n\ndb.disconnect()\n\"",
"description": "Test relation extraction with fuzzy matching"
}
}
{
"tool_response": {
"stdout": "Testing with 10 entities...\nEntities: ['Abwandlungen', 'Als-ob-Rahmen', 'Angst', 'Anlass', 'Anliegen']...\nExtracted 1 relations\n Abwandlungen -> spielerische Kreativität: source=True, target=True",
"stderr": "",
"interrupted": false,
"isImage": false
}
}