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embed_pdf.py
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embed_pdf.py
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from langchain.document_loaders import PagedPDFSplitter
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.vectorstores import FAISS
import os
def embed_document(file_name, file_folder="pdf", embedding_folder="index"):
file_path = f"{file_folder}/{file_name}"
loader = PagedPDFSplitter(file_path)
source_pages = loader.load_and_split()
embedding_func = OpenAIEmbeddings()
text_splitter = RecursiveCharacterTextSplitter(
chunk_size=500,
chunk_overlap=100,
length_function=len,
is_separator_regex=False,
separators=["\n\n", "\n", " ", ""],
)
source_chunks = text_splitter.split_documents(source_pages)
search_index = FAISS.from_documents(source_chunks, embedding_func)
search_index.save_local(
folder_path=embedding_folder, index_name=file_name + ".index"
)
def embed_all_pdf_docs():
# Define the directory path
pdf_directory = "pdf"
# Check if the directory exists
if os.path.exists(pdf_directory):
# List all PDF files in the directory
pdf_files = [
file for file in os.listdir(pdf_directory) if file.endswith(".pdf")
]
if pdf_files:
for pdf_file in pdf_files:
print(f"Embedding {pdf_file}...")
embed_document(file_name=pdf_file, file_folder=pdf_directory)
print("Done!")
else:
raise Exception("No PDF files found in the directory.")
else:
raise Exception(f"Directory '{pdf_directory}' does not exist.")
def get_all_index_files():
# Define the directory path
index_directory = "index"
# Check if the directory exists
if os.path.exists(index_directory):
# List all index files in the directory
postfix = ".index.faiss"
index_files = [
file.replace(postfix, "")
for file in os.listdir(index_directory)
if file.endswith(postfix)
]
if index_files:
return index_files
else:
raise Exception("No index files found in the directory.")
else:
raise Exception(f"Directory '{index_directory}' does not exist.")