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import faiss
import json
import numpy as np
import zipfile
from sentence_transformers import SentenceTransformer
class Retriever:
def __init__(self):
self.archive = zipfile.ZipFile('data/en/paragraphs.zip', 'r')
self.index = faiss.read_index("data/en/embs_IVF16384_HNSW32_2lvl_full.idx")
self.index.nprobe = 128
self.model = SentenceTransformer('sentence-transformers/all-mpnet-base-v2', device='cuda')
self.model.max_seq_length = 512
def get_paragraph_by_vec_idx(self, vec_idx):
chunk_id = vec_idx // 100000
line_id = vec_idx % 100000
with self.archive.open('enwiki_paragraphs_clean/enwiki_paragraphs_%03d.jsonl' % chunk_id) as f:
for i,l in enumerate(f):
if i == line_id:
data = json.loads(l)
break
return data
def search(self, query, k=5):
emb = self.model.encode(query)
_, neighbors = self.index.search(emb[np.newaxis, ...], k)
results = []
for n in neighbors[0]:
data = get_paragraph_by_vec_idx(n)
results.append(data)
return results
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