For quick prototyping, you can download loaders dynamically in your script.
from llama_index.readers.web import SimpleWebPageReader reader = SimpleWebPageReader(html_to_text=True) documents = reader.load_data(urls=["https://example.com"]) Use code with caution. Method 2: The download_loader Utility download loader llamaindex
LlamaHub hosts over . Here are the most commonly used loaders to get you started: Source Type Recommended Loader Installation Command Local Files SimpleDirectoryReader Included in llama-index-core Web Pages SimpleWebPageReader pip install llama-index-readers-web PDFs PDFReader pip install llama-index-readers-file Notion NotionPageReader pip install llama-index-readers-notion Slack SlackReader pip install llama-index-readers-slack Databases DatabaseReader pip install llama-index-readers-database Professional Best Practices for Loading Data For quick prototyping, you can download loaders dynamically
Master Guide: Download and Use LlamaIndex Loaders (also known as data connectors) are the primary entry point for any Retrieval-Augmented Generation (RAG) application. They bridge the gap between raw data sources—like PDFs, Slack, Notion, or SQL databases—and the structured format required for LLM indexing. Quick Start: How to Download a Loader Here are the most commonly used loaders to
With the release of LlamaIndex v0.10, the process for downloading and using loaders has evolved. You can now install them directly via or use the legacy download_loader utility. Method 1: The Modern Way (Recommended) Each loader on LlamaHub is now a standalone Python package. Find your loader on LlamaHub. Install via pip : pip install llama-index-readers-web Use code with caution. Import and Use :
Simply downloading a loader isn't enough for production-grade AI. Follow these standards to ensure high-quality retrieval: Loading Data | LlamaIndex OSS Documentation - LlamaParse
from llama_index.core import download_loader # Dynamically downloads and installs the package via pip GoogleDocsReader = download_loader("GoogleDocsReader") loader = GoogleDocsReader() documents = loader.load_data(document_ids=['your_gdoc_id']) Use code with caution. Essential LlamaIndex Loaders