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from langchain.document_loaders import PyPDFLoader, DirectoryLoader
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.embeddings import SentenceTransformerEmbeddings
from langchain.vectorstores import Chroma
loader = DirectoryLoader('data', glob="./*.pdf", loader_cls=PyPDFLoader)
documents = loader.load()
text_splitter = RecursiveCharacterTextSplitter(chunk_size=500, chunk_overlap=200)
texts = text_splitter.split_documents(documents)
embeddings = SentenceTransformerEmbeddings(model_name="multi-qa-mpnet-base-dot-v1")
persist_directory = "ipc_vector_data"
db = Chroma.from_documents(texts, embeddings, persist_directory=persist_directory)
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