Files
my-vault/.scripts/memory/query_pgvector.py
T

57 lines
1.5 KiB
Python
Executable File

#!/usr/bin/env python3
import argparse
from index_common import embed_text, get_conn, vector_literal
def sanitize(text: str) -> str:
return text.replace('```', '` ` `').strip()
def query(text: str, top_k: int = 5, max_chars: int = 2500) -> str:
embedding = embed_text(text)
vector = vector_literal(embedding)
with get_conn() as conn:
with conn.cursor() as cur:
cur.execute(
'''
SELECT source, content
FROM memory_primary
ORDER BY embedding <=> %s::vector
LIMIT %s
''',
(vector, top_k),
)
rows = cur.fetchall()
parts: list[str] = []
total_len = 0
for source, content in rows:
snippet = sanitize(content[:600])
block = f'<retrieved_context source="{source}">\n{snippet}\n</retrieved_context>'
if total_len + len(block) > max_chars:
break
parts.append(block)
total_len += len(block)
return '\n\n'.join(parts)
def main() -> None:
parser = argparse.ArgumentParser()
parser.add_argument('query', nargs='+')
parser.add_argument('--top-k', type=int, default=5)
parser.add_argument('--max-chars', type=int, default=2500)
args = parser.parse_args()
text = ' '.join(args.query).strip()
if not text:
return
print(query(text, top_k=args.top_k, max_chars=args.max_chars))
if __name__ == '__main__':
main()