policy-analysis / utils /encoding_input.py
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# Methods to encode text
import numpy as np
from langchain_community.embeddings import HuggingFaceEmbeddings
def encode_text(text, embedding_model='sentence-transformers/all-MiniLM-L6-v2', as_array=True):
"""Encodes the input text using the provided embedding model."""
embedding_model = HuggingFaceEmbeddings(model_name=embedding_model)
encoded_input = embedding_model.embed_query(text)
if as_array:
return np.array(encoded_input)
else:
return encoded_input