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Prepare external drug markdown files into DeepMed RAG-ready dataset format.
Usage:
python prepare_rag_drug_data.py --source "e:/AI/Thuốc" --target "e:/AI/DeepMed/backend/data"
This script:
1) Copies and normalizes files from:
- <source>/Thuốc nội bộ -> <target>/thông tin thuốc nội bộ
- <source>/cảnh giác dược -> <target>/cảnh giác dược
2) Cleans markdown noise (widget/image-only lines, redundant separators)
3) Ensures each drug markdown begins with:
# <DRUG_NAME>
Hoạt chất: <value or Chưa cập nhật>
4) Optionally removes long hash suffixes in filenames.
"""
from __future__ import annotations
import argparse
import hashlib
import os
import re
import shutil
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Iterable, List, Optional, Tuple
HASH_SUFFIX_RE = re.compile(r"\s+[0-9a-f]{20,}(?=\.md$)", re.IGNORECASE)
MULTI_SPACE_RE = re.compile(r"[ \t]{2,}")
EMPTY_LINE_RE = re.compile(r"\n{3,}")
HEADING_RE = re.compile(r"^#\s+(.+)$", re.MULTILINE)
ACTIVE_RE = re.compile(r"^\s*Hoạt\s*chất\s*:\s*(.+)$", re.IGNORECASE | re.MULTILINE)
WIDGET_LINK_RE = re.compile(r"^\s*\[https?://widgetbox\.app/.*\]\(https?://widgetbox\.app/.*\)\s*$", re.IGNORECASE)
IMAGE_LINE_RE = re.compile(r"^\s*!\[[^\]]*\]\([^\)]*\)\s*$")
HORIZONTAL_RULE_RE = re.compile(r"^\s*---\s*$")
@dataclass
class SyncStats:
copied: int = 0
skipped: int = 0
errors: int = 0
def _clean_filename(name: str, remove_hash_suffix: bool = True) -> str:
cleaned = name.strip()
if remove_hash_suffix and cleaned.lower().endswith(".md"):
cleaned = HASH_SUFFIX_RE.sub("", cleaned)
cleaned = MULTI_SPACE_RE.sub(" ", cleaned)
return cleaned
def _safe_output_path(dest_dir: Path, desired_name: str, content: str) -> Path:
out = dest_dir / desired_name
if not out.exists():
return out
digest = hashlib.md5(content.encode("utf-8", errors="ignore")).hexdigest()[:8]
stem = out.stem
suffix = out.suffix
return dest_dir / f"{stem}__{digest}{suffix}"
def _normalize_newlines(text: str) -> str:
return text.replace("\r\n", "\n").replace("\r", "\n")
def _strip_noise_lines(text: str) -> str:
lines = []
for raw in text.split("\n"):
line = raw.replace("\xa0", " ").rstrip()
if WIDGET_LINK_RE.match(line):
continue
if IMAGE_LINE_RE.match(line):
continue
if HORIZONTAL_RULE_RE.match(line):
continue
lines.append(line)
normalized = "\n".join(lines)
normalized = EMPTY_LINE_RE.sub("\n\n", normalized)
return normalized.strip()
def _extract_heading(content: str) -> Optional[str]:
m = HEADING_RE.search(content)
if not m:
return None
return m.group(1).strip()
def _extract_active_ingredient(content: str) -> Optional[str]:
m = ACTIVE_RE.search(content)
if not m:
return None
return m.group(1).strip()
def _ensure_rag_header(content: str, fallback_name: str) -> str:
heading = _extract_heading(content) or fallback_name
active = _extract_active_ingredient(content) or "Chưa cập nhật"
body = content
body = HEADING_RE.sub("", body, count=1).lstrip("\n")
body = ACTIVE_RE.sub("", body, count=1).lstrip("\n")
header = f"# {heading}\n\nHoạt chất: {active}\n"
out = f"{header}\n{body.strip()}\n"
out = EMPTY_LINE_RE.sub("\n\n", out)
return out
def _read_text(path: Path) -> str:
return path.read_text(encoding="utf-8", errors="ignore")
def _write_text(path: Path, content: str) -> None:
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text(content, encoding="utf-8", newline="\n")
def _iter_files(root: Path) -> Iterable[Path]:
for p in root.rglob("*"):
if p.is_file() and p.suffix.lower() in {".md", ".pdf", ".docx", ".txt", ".csv", ".xlsx", ".xls"}:
yield p
def _normalize_markdown_for_drug(md_text: str, fallback_drug_name: str) -> str:
text = _normalize_newlines(md_text)
text = _strip_noise_lines(text)
text = _ensure_rag_header(text, fallback_drug_name)
return text
def _sync_folder(
source: Path,
target: Path,
remove_hash_suffix: bool,
drug_mode: bool,
flatten_tree: bool = False,
) -> SyncStats:
stats = SyncStats()
if not source.exists():
print(f"[WARN] Source folder not found: {source}")
return stats
target.mkdir(parents=True, exist_ok=True)
seen_names: Dict[str, int] = {}
for src in _iter_files(source):
try:
rel = src.relative_to(source)
clean_name = _clean_filename(src.name, remove_hash_suffix=remove_hash_suffix)
base_target_dir = target if flatten_tree else (target / rel.parent)
base_target_dir.mkdir(parents=True, exist_ok=True)
if src.suffix.lower() == ".md":
raw = _read_text(src)
if drug_mode:
fallback = Path(clean_name).stem
cleaned = _normalize_markdown_for_drug(raw, fallback)
else:
cleaned = _strip_noise_lines(_normalize_newlines(raw)) + "\n"
out_path = _safe_output_path(base_target_dir, clean_name, cleaned)
if out_path.exists():
existing = _read_text(out_path)
if existing == cleaned:
stats.skipped += 1
continue
_write_text(out_path, cleaned)
else:
out_path = base_target_dir / clean_name
if out_path.exists() and out_path.stat().st_size == src.stat().st_size:
stats.skipped += 1
continue
shutil.copy2(src, out_path)
seen_names[out_path.name] = seen_names.get(out_path.name, 0) + 1
stats.copied += 1
except Exception as exc:
stats.errors += 1
print(f"[ERROR] Failed: {src} -> {exc}")
dup_count = sum(1 for n in seen_names.values() if n > 1)
if dup_count:
print(f"[WARN] Found {dup_count} duplicate output names; hash suffix applied.")
return stats
def run(source_root: Path, target_root: Path, remove_hash_suffix: bool = True) -> Tuple[SyncStats, SyncStats]:
source_drug = source_root / "Thuốc nội bộ"
source_alert = source_root / "cảnh giác dược"
target_drug = target_root / "thông tin thuốc nội bộ"
target_alert = target_root / "cảnh giác dược"
print("=" * 72)
print(f"Source root: {source_root}")
print(f"Target root: {target_root}")
print("=" * 72)
drug_stats = _sync_folder(
source=source_drug,
target=target_drug,
remove_hash_suffix=remove_hash_suffix,
drug_mode=True,
)
alert_stats = _sync_folder(
source=source_alert,
target=target_alert,
remove_hash_suffix=remove_hash_suffix,
drug_mode=False,
flatten_tree=True,
)
print("=" * 72)
print("Sync completed")
print(
"Drug files: copied={0.copied}, skipped={0.skipped}, errors={0.errors} | "
"Alert files: copied={1.copied}, skipped={1.skipped}, errors={1.errors}".format(
drug_stats, alert_stats
)
)
print("=" * 72)
return drug_stats, alert_stats
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser(description="Prepare Thuốc files for DeepMed RAG")
parser.add_argument(
"--source",
default=r"e:/AI/Thuốc",
help="Path to external Thuốc folder",
)
parser.add_argument(
"--target",
default=r"e:/AI/DeepMed/backend/data",
help="Path to DeepMed backend data folder",
)
parser.add_argument(
"--keep-hash-suffix",
action="store_true",
help="Keep long hash suffixes in markdown filenames",
)
return parser.parse_args()
def main() -> None:
args = parse_args()
source_root = Path(args.source).resolve()
target_root = Path(args.target).resolve()
run(
source_root=source_root,
target_root=target_root,
remove_hash_suffix=not args.keep_hash_suffix,
)
if __name__ == "__main__":
main()
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