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from langchain_huggingface import HuggingFaceEmbeddings | |
from langchain_community.vectorstores import FAISS | |
def embed_documents(documents): | |
embedding_model = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2") | |
vector_store = FAISS.from_texts([doc['text'] for doc in documents], embedding_model) | |
return vector_store | |