File size: 2,037 Bytes
db32e07 | 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 | #!/usr/bin/env python
from __future__ import annotations
import argparse
import sys
from pathlib import Path
ROOT = Path(__file__).resolve().parents[1]
if str(ROOT) not in sys.path:
sys.path.insert(0, str(ROOT))
import numpy as np
from spec_rag.faiss_index import load_index
from spec_rag.io import load_embeddings, load_smiles, save_jsonl
from spec_rag.retrieval import build_smiles_to_index, recall_at_k, search_index
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser(description="Retrieve SMILES from FAISS index.")
parser.add_argument("--index-path", required=True)
parser.add_argument("--smiles-path", required=True)
parser.add_argument("--query-embeddings", required=True)
parser.add_argument("--out-jsonl", required=True)
parser.add_argument("--k", type=int, default=100)
parser.add_argument("--ground-truth-smiles", default=None)
return parser.parse_args()
def main() -> None:
args = parse_args()
index = load_index(args.index_path)
smiles = load_smiles(args.smiles_path)
queries = load_embeddings(args.query_embeddings)
scores, indices = search_index(index, queries, args.k)
rows = []
for i in range(indices.shape[0]):
retrieved = [smiles[j] if j >= 0 else "" for j in indices[i].tolist()]
rows.append(
{
"query_id": i,
"indices": indices[i].tolist(),
"scores": scores[i].tolist(),
"smiles": retrieved,
}
)
save_jsonl(args.out_jsonl, rows)
if args.ground_truth_smiles:
gt_smiles = load_smiles(args.ground_truth_smiles)
lookup = build_smiles_to_index(smiles)
gt_indices = [lookup.get(smi, -1) for smi in gt_smiles]
if not any(i >= 0 for i in gt_indices):
print("No ground-truth SMILES found in index.")
return
recall = recall_at_k(indices, gt_indices, args.k)
print(f"Recall@{args.k}: {recall:.4f}")
if __name__ == "__main__":
main()
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