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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 | |