mirror of
https://github.com/Mintplex-Labs/vector-admin.git
synced 2026-07-19 21:23:38 -04:00
38 lines
1.3 KiB
Python
38 lines
1.3 KiB
Python
import os
|
|
from langchain.document_loaders import PyPDFLoader
|
|
from slugify import slugify
|
|
from ..utils import guid, file_creation_time, write_to_server_documents, move_source, tokenize
|
|
|
|
# Process all text-related documents.
|
|
def as_pdf(**kwargs):
|
|
parent_dir = kwargs.get('directory', 'hotdir')
|
|
filename = kwargs.get('filename')
|
|
ext = kwargs.get('ext', '.txt')
|
|
remove = kwargs.get('remove_on_complete', False)
|
|
fullpath = f"{parent_dir}/{filename}{ext}"
|
|
|
|
loader = PyPDFLoader(fullpath)
|
|
pages = loader.load_and_split()
|
|
|
|
print(f"-- Working {fullpath} --")
|
|
metadata = []
|
|
for page in pages:
|
|
pg_num = page.metadata.get('page')
|
|
print(f"-- Working page {pg_num} --")
|
|
|
|
content = page.page_content
|
|
data = {
|
|
'id': guid(),
|
|
'url': "file://"+os.path.abspath(f"{parent_dir}/processed/{filename}{ext}"),
|
|
'title': f"{filename}_pg{pg_num}{ext}",
|
|
'description': "a custom file uploaded by the user.",
|
|
'published': file_creation_time(fullpath),
|
|
'wordCount': len(content),
|
|
'pageContent': content,
|
|
'token_count_estimate': len(tokenize(content))
|
|
}
|
|
metadata.append(data)
|
|
|
|
move_source(parent_dir, f"{filename}{ext}", remove=remove)
|
|
print(f"[SUCCESS]: {filename}{ext} converted & ready for embedding.\n")
|
|
return metadata |