Integrating document loaders

Developing LLM Applications with LangChain

Jonathan Bennion

AI Engineer & LangChain Contributor

Retrieval Augmented Generation (RAG)

Use embeddings to retrieve relevant information to integrate into the prompt

A typical RAG workflow.

RAG development steps

The general RAG workflow: a document loader, a document splitter, and the storage and retrieval process.

LangChain document loaders

Classes designed to load and configure documents for system integration
Document loaders for common file types: .pdf, .csv
3rd party loaders: S3, .ipynb, .wav

¹ https://python.langchain.com/docs/integrations/document_loaders

PDF document loader

Requires installation of the pypdf package: pip install pypdf

from langchain_community.document_loaders import PyPDFLoader

loader = PyPDFLoader("path/to/file/attention_is_all_you_need.pdf")


data = loader.load()

print(data[0])

Document(page_content='Provided proper attribution is provided, Google hereby grants 
permission to\nreproduce the tables and figures in this paper solely for use in [...]

CSV document loader

from langchain_community.document_loaders.csv_loader import CSVLoader


loader = CSVLoader('fifa_countries_audience.csv')


data = loader.load()

print(data[0])

Document(page_content='country: United States\nconfederation: CONCACAF\npopulation_share: [...]

HTML document loader

Requires installation of the unstructured package: pip install unstructured

from langchain_community.document_loaders import UnstructuredHTMLLoader


loader = UnstructuredHTMLLoader("white_house_executive_order_nov_2023.html")
data = loader.load()


print(data[0])

print(data[0].metadata)

page_content="To search this site, enter a search term\n\nSearch\n\nExecutive Order on the Safe, Secure,
and Trustworthy Development and Use of Artificial Intelligence\n\nHome\n\nBriefing Room\n\nPresidential
Actions\n\nBy the authority vested in me as President by the Constitution and the laws of the United
States of America, it is hereby ordered as follows: ..."


{'source': 'white_house_executive_order_nov_2023.html'}

Let's practice!

Developing LLM Applications with LangChain