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from langchain_community.vectorstores import FAISS
from langchain_community.embeddings import HuggingFaceEmbeddings
def create_vectorstore(documents):
if not documents:
raise ValueError(
"No valid source code found to build vector index."
)
embeddings = HuggingFaceEmbeddings(
model_name="sentence-transformers/all-MiniLM-L6-v2"
)
return FAISS.from_documents(documents, embeddings)
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