{
"event": "PreToolUse",
"tool_name": "Grep",
"tool_input": {
"pattern": "Embed: Chunk|embed_chunks",
"path": "\/opt\/scripts\/pipeline",
"glob": "*.py",
"output_mode": "content",
"-B": 2,
"-A": 2
}
}
{
"tool_response": {
"mode": "content",
"numFiles": 0,
"filenames": [],
"content": "\/opt\/scripts\/pipeline\/pipeline.py-24-from db import PipelineProgress, db\n\/opt\/scripts\/pipeline\/pipeline.py-25-from detect import queue_files, scan_directory\n\/opt\/scripts\/pipeline\/pipeline.py:26:from embed import embed_chunks, embed_pending_chunks\n\/opt\/scripts\/pipeline\/pipeline.py-27-from enrich import run_enrichment_step\n\/opt\/scripts\/pipeline\/pipeline.py-28-from extract import extract, get_full_text\n--\n\/opt\/scripts\/pipeline\/pipeline.py-141- progress.add_log(f\"Erstelle Embeddings für {len(chunks)} Chunks...\")\n\/opt\/scripts\/pipeline\/pipeline.py-142-\n\/opt\/scripts\/pipeline\/pipeline.py:143: embedded = embed_chunks(chunks, doc_id, file_name, file_path, progress=progress)\n\/opt\/scripts\/pipeline\/pipeline.py-144- db.log(\"INFO\", f\"Embedded {embedded}\/{len(chunks)} chunks\")\n\/opt\/scripts\/pipeline\/pipeline.py-145-\n--\n\/opt\/scripts\/pipeline\/embed.py-61-\n\/opt\/scripts\/pipeline\/embed.py-62-\n\/opt\/scripts\/pipeline\/embed.py:63:def embed_chunks(chunks, document_id, document_title, source_path, progress=None):\n\/opt\/scripts\/pipeline\/embed.py-64- \"\"\"\n\/opt\/scripts\/pipeline\/embed.py-65- Generate embeddings for chunks and store in Qdrant.\n--\n\/opt\/scripts\/pipeline\/embed.py-72- # Log every 20 chunks or first\/last\n\/opt\/scripts\/pipeline\/embed.py-73- if progress and (i == 0 or (i + 1) % 20 == 0 or i + 1 == total_chunks):\n\/opt\/scripts\/pipeline\/embed.py:74: progress.add_log(f\"Embed: Chunk {i + 1}\/{total_chunks}...\")\n\/opt\/scripts\/pipeline\/embed.py-75-\n\/opt\/scripts\/pipeline\/embed.py-76- # Generate embedding",
"numLines": 23
}
}