Spaces:
Runtime error
Runtime error
File size: 1,885 Bytes
ed4d993 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 |
import os
from pathlib import Path
import pypdfium2 as pdfium
from langchain_community.vectorstores import Chroma
from langchain_experimental.open_clip import OpenCLIPEmbeddings
def get_images_from_pdf(pdf_path, img_dump_path):
"""
Extract images from each page of a PDF document and save as JPEG files.
:param pdf_path: A string representing the path to the PDF file.
:param img_dump_path: A string representing the path to dummp images.
"""
pdf = pdfium.PdfDocument(pdf_path)
n_pages = len(pdf)
for page_number in range(n_pages):
page = pdf.get_page(page_number)
bitmap = page.render(scale=1, rotation=0, crop=(0, 0, 0, 0))
pil_image = bitmap.to_pil()
pil_image.save(f"{img_dump_path}/img_{page_number + 1}.jpg", format="JPEG")
# Load PDF
doc_path = Path(__file__).parent / "docs/DDOG_Q3_earnings_deck.pdf"
img_dump_path = Path(__file__).parent / "docs/"
rel_doc_path = doc_path.relative_to(Path.cwd())
rel_img_dump_path = img_dump_path.relative_to(Path.cwd())
print("pdf index")
pil_images = get_images_from_pdf(rel_doc_path, rel_img_dump_path)
print("done")
vectorstore = Path(__file__).parent / "chroma_db_multi_modal"
re_vectorstore_path = vectorstore.relative_to(Path.cwd())
# Load embedding function
print("Loading embedding function")
embedding = OpenCLIPEmbeddings(model_name="ViT-H-14", checkpoint="laion2b_s32b_b79k")
# Create chroma
vectorstore_mmembd = Chroma(
collection_name="multi-modal-rag",
persist_directory=str(Path(__file__).parent / "chroma_db_multi_modal"),
embedding_function=embedding,
)
# Get image URIs
image_uris = sorted(
[
os.path.join(rel_img_dump_path, image_name)
for image_name in os.listdir(rel_img_dump_path)
if image_name.endswith(".jpg")
]
)
# Add images
print("Embedding images")
vectorstore_mmembd.add_images(uris=image_uris)
|