{
"event": "PreToolUse",
"tool_name": "Bash",
"tool_input": {
"command": "DB_PASSWORD=\"v8mFLmkF2fth_r\" .\/venv\/bin\/python -c \"\nfrom db import db\nfrom pipeline_config import get_step_model\nfrom step_semantic_extended import TextSemanticAnalyzeStep, TextSemanticStoreStep\n\ndb.connect()\n\n# Get chunks for doc 12\ncursor = db.execute('SELECT id, content FROM chunks WHERE document_id = 12')\nchunks = [{'id': r['id'], 'content': r['content']} for r in cursor.fetchall()]\ncursor.close()\n\nprint(f'Chunks: {len(chunks)}')\n\n# Get model\nmodel = get_step_model('text_semantic_analyze')\nprint(f'Model: {model}')\n\n# Analyze\nanalyzer = TextSemanticAnalyzeStep(db)\nanalyzed = analyzer.execute(chunks, {'model': model})\n\nprint(f'Analyzed: {len([c for c in analyzed if c.get(\\\"text_semantics\\\")])} with semantics')\n\n# Show first result\nfor c in analyzed:\n if c.get('text_semantics'):\n print(f' Chunk {c[\\\"id\\\"]}: {c[\\\"text_semantics\\\"]}')\n break\n\n# Store\nstorer = TextSemanticStoreStep(db)\nresult = storer.execute(analyzed, {})\nprint(f'Stored: {result}')\n\ndb.disconnect()\n\" 2>&1",
"timeout": 300000,
"description": "Debug semantic analysis"
}
}
{
"tool_response": {
"stdout": "Chunks: 4\nModel: gemma3:27b-it-qat\nAnalyzed: 4 with semantics\n Chunk 1926: {'statement_form': 'assertion', 'intent': 'define', 'frame': 'practical', 'is_negated': False, 'discourse_role': 'definition', 'model_used': 'gemma3:27b-it-qat'}\nStored: {'stored': 4, 'skipped': 0}",
"stderr": "",
"interrupted": false,
"isImage": false
}
}