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from sentence_transformers import SentenceTransformer | |
import numpy as np | |
import time | |
from embedder import get_model | |
# Use the preloaded model from embedder instead of creating a new instance | |
def retrieve_chunks(index, texts, query, k=15): | |
model = get_model() # Use the preloaded model | |
query_vec = model.encode([query]) | |
distances, indices = index.search(np.array(query_vec), k) | |
results = [texts[i] for i in indices[0]] | |
return results | |