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#importing dependencies
from langchain.embeddings import HuggingFaceBgeEmbeddings
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.vectorstores import Chroma
from langchain.document_loaders import PyPDFDirectoryLoader
from langchain.storage import LocalFileStore
import time
import torch
import streamlit as st
import tkinter as tk
from tkinter import filedialog
from pathlib import Path
def select_folder():
root = tk.Tk()
root.withdraw()
folder_path = filedialog.askdirectory(master=root)
root.destroy()
return folder_path
# check if CUDA is available and set the device
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
print('Using device:', device)
store = LocalFileStore("../cache/")
#loading data
root = tk.Tk()
root.withdraw()
# Make folder picker dialog appear on top of other windows
root.wm_attributes('-topmost', 1)
# Folder picker button
st.title('Pick Pdfs Folder')
st.write('Please select a folder:')
dirname = ""
pdfs_folder = ""
clicked = st.button('Browse')
if clicked:
dirname = st.text_input('Selected folder:', filedialog.askdirectory(master=root))
pdfs_folder = Path(dirname)
if pdfs_folder:
st.write("Selected folder path:", pdfs_folder)
loader = PyPDFDirectoryLoader(pdfs_folder)
documents = loader.load()
st.write(len(documents))
#splitting
splitter = RecursiveCharacterTextSplitter(chunk_size = 1000, chunk_overlap = 10)
text_chunks = splitter.split_documents(documents)
st.write(len(text_chunks))
#loading HuggingFaceBGE embeddings
model_name = "BAAI/bge-small-en"
st.write("Loading tokenizer model", model_name)
model_kwargs = {"device": device}
encode_kwargs = {"normalize_embeddings": True}
embeddings = HuggingFaceBgeEmbeddings(
model_name=model_name, model_kwargs=model_kwargs, encode_kwargs=encode_kwargs
)
st.write('Embeddings loaded!')
# creating Documents vector database.
t1 = time.time()
persist_directory = 'dbname'
vectordb = Chroma.from_documents(
documents = text_chunks,
embedding = embeddings,
collection_metadata = {"hnsw:space": "cosine"},
persist_directory = persist_directory
)
t2 = time.time()
st.write('Time taken for building db : ', (t2 - t1))
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