
Research
PyPI Package Disguised as Instagram Growth Tool Harvests User Credentials
A deceptive PyPI package posing as an Instagram growth tool collects user credentials and sends them to third-party bot services.
llama-index-readers-file
Advanced tools
pip install llama-index-readers-file
This is the default integration for different loaders that are used within SimpleDirectoryReader
.
Provides support for the following loaders:
pip install llama-index-readers-file
Once installed, You can import any of the loader. Here's an example usage of one of the loader.
from llama_index.core import SimpleDirectoryReader
from llama_index.readers.file import (
DocxReader,
HWPReader,
PDFReader,
EpubReader,
FlatReader,
HTMLTagReader,
ImageCaptionReader,
ImageReader,
ImageVisionLLMReader,
IPYNBReader,
MarkdownReader,
MboxReader,
PptxReader,
PandasCSVReader,
VideoAudioReader,
UnstructuredReader,
PyMuPDFReader,
ImageTabularChartReader,
XMLReader,
PagedCSVReader,
CSVReader,
RTFReader,
)
# PDF Reader with `SimpleDirectoryReader`
parser = PDFReader()
file_extractor = {".pdf": parser}
documents = SimpleDirectoryReader(
"./data", file_extractor=file_extractor
).load_data()
# Docx Reader example
parser = DocxReader()
file_extractor = {".docx": parser}
documents = SimpleDirectoryReader(
"./data", file_extractor=file_extractor
).load_data()
# HWP Reader example
parser = HWPReader()
file_extractor = {".hwp": parser}
documents = SimpleDirectoryReader(
"./data", file_extractor=file_extractor
).load_data()
# Epub Reader example
parser = EpubReader()
file_extractor = {".epub": parser}
documents = SimpleDirectoryReader(
"./data", file_extractor=file_extractor
).load_data()
# Flat Reader example
parser = FlatReader()
file_extractor = {".txt": parser}
documents = SimpleDirectoryReader(
"./data", file_extractor=file_extractor
).load_data()
# HTML Tag Reader example
parser = HTMLTagReader()
file_extractor = {".html": parser}
documents = SimpleDirectoryReader(
"./data", file_extractor=file_extractor
).load_data()
# Image Reader example
parser = ImageReader()
file_extractor = {
".jpg": parser,
".jpeg": parser,
".png": parser,
} # Add other image formats as needed
documents = SimpleDirectoryReader(
"./data", file_extractor=file_extractor
).load_data()
# IPYNB Reader example
parser = IPYNBReader()
file_extractor = {".ipynb": parser}
documents = SimpleDirectoryReader(
"./data", file_extractor=file_extractor
).load_data()
# Markdown Reader example
parser = MarkdownReader()
file_extractor = {".md": parser}
documents = SimpleDirectoryReader(
"./data", file_extractor=file_extractor
).load_data()
# Mbox Reader example
parser = MboxReader()
file_extractor = {".mbox": parser}
documents = SimpleDirectoryReader(
"./data", file_extractor=file_extractor
).load_data()
# Pptx Reader example
parser = PptxReader()
file_extractor = {".pptx": parser}
documents = SimpleDirectoryReader(
"./data", file_extractor=file_extractor
).load_data()
# Pandas CSV Reader example
parser = PandasCSVReader()
file_extractor = {".csv": parser} # Add other CSV formats as needed
documents = SimpleDirectoryReader(
"./data", file_extractor=file_extractor
).load_data()
# PyMuPDF Reader example
parser = PyMuPDFReader()
file_extractor = {".pdf": parser}
documents = SimpleDirectoryReader(
"./data", file_extractor=file_extractor
).load_data()
# XML Reader example
parser = XMLReader()
file_extractor = {".xml": parser}
documents = SimpleDirectoryReader(
"./data", file_extractor=file_extractor
).load_data()
# Paged CSV Reader example
parser = PagedCSVReader()
file_extractor = {".csv": parser} # Add other CSV formats as needed
documents = SimpleDirectoryReader(
"./data", file_extractor=file_extractor
).load_data()
# CSV Reader example
parser = CSVReader()
file_extractor = {".csv": parser} # Add other CSV formats as needed
documents = SimpleDirectoryReader(
"./data", file_extractor=file_extractor
).load_data()
This loader is designed to be used as a way to load data into LlamaIndex.
FAQs
llama-index readers file integration
We found that llama-index-readers-file demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Research
A deceptive PyPI package posing as an Instagram growth tool collects user credentials and sends them to third-party bot services.
Product
Socket now supports pylock.toml, enabling secure, reproducible Python builds with advanced scanning and full alignment with PEP 751's new standard.
Security News
Research
Socket uncovered two npm packages that register hidden HTTP endpoints to delete all files on command.