Datasets:
File size: 2,447 Bytes
08b40b0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 | #!/usr/bin/env python3
import json
import logging
from pathlib import Path
# ---------------------------------------------------------------------------
# Config
# ---------------------------------------------------------------------------
ROOT = Path(__file__).parent.parent.parent
SOURCE_DIR = ROOT / "source" / "glossary" / "detail"
OUTPUT_FILE = ROOT / "data" / "glossary.jsonl"
PREFIX = "glossary"
logging.basicConfig(level=logging.INFO, format="%(message)s")
log = logging.getLogger(__name__)
# ---------------------------------------------------------------------------
# Mapper
# ---------------------------------------------------------------------------
def transform_glossary(data: dict) -> dict:
"""Flatten glossary JSON into a ChromaDB-ready format."""
chroma_id = f"{PREFIX}:{data['slug']}"
# Searchable text is the term + full definition
term = data.get('term')
definition = data.get('description') or data.get('short_description')
document = f"{term}: {definition}"
# Metadata
metadata = {
"slug": data["slug"],
"term": term,
"url": data.get("url")
}
metadata = {k: v for k, v in metadata.items() if v is not None}
return {
"id": chroma_id,
"document": document,
"metadata": metadata
}
# ---------------------------------------------------------------------------
# Main
# ---------------------------------------------------------------------------
def main():
if not SOURCE_DIR.exists():
log.error(f"Source directory {SOURCE_DIR} not found.")
return
OUTPUT_FILE.parent.mkdir(parents=True, exist_ok=True)
count = 0
with OUTPUT_FILE.open("w", encoding="utf-8") as out:
for shard_dir in sorted(SOURCE_DIR.iterdir()):
if not shard_dir.is_dir(): continue
for file_path in sorted(shard_dir.glob("*.json")):
try:
with file_path.open("r", encoding="utf-8") as f:
raw_data = json.load(f)
processed = transform_glossary(raw_data)
out.write(json.dumps(processed, ensure_ascii=False) + "\n")
count += 1
except Exception as e:
log.error(f"Error processing {file_path}: {e}")
log.info(f"Successfully built {count} records in {OUTPUT_FILE}")
if __name__ == "__main__":
main()
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