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import os
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.vectorstores import Chroma
from langchain.embeddings import HuggingFaceBgeEmbeddings
from langchain.document_loaders import PyPDFLoader
model_name = "BAAI/bge-large-en"
model_kwargs = {'device': 'cpu'}
encode_kwargs = {'normalize_embeddings': False}
embeddings = HuggingFaceBgeEmbeddings(
model_name=model_name,
model_kwargs=model_kwargs,
encode_kwargs=encode_kwargs
)
loader = PyPDFLoader(
"./Instruccion26septiembre2023PremiosExtraordinariosMusica.pdf")
documents = loader.load()
text_splitter = RecursiveCharacterTextSplitter(
chunk_size=1000, chunk_overlap=100)
texts = text_splitter.split_documents(documents)
vector_store = Chroma.from_documents(texts, embeddings, collection_metadata={
"hnsw:space": "cosine"}, persist_directory="stores/ConserGPT")
print("Vector Store Created.......")
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