talk2carnegie / ingest.py
anpigon
feat: 데일 카네기 챗봇
02a63e4
from langchain.document_loaders import PyPDFDirectoryLoader
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.vectorstores import Chroma
from constants import persist_directory
loader = PyPDFDirectoryLoader("docs/")
documents = loader.load()
text_splitter = RecursiveCharacterTextSplitter(
chunk_size=1000,
chunk_overlap=200,
separators=["\n\n", "\n", ".", "!", ",", " ", ""],
keep_separator=True,
)
texts = text_splitter.split_documents(documents)
embedding = OpenAIEmbeddings()
vectordb = Chroma.from_documents(
documents=texts,
embedding=embedding,
persist_directory=persist_directory,
)
vectordb.persist()