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LangChainframework~15 mins

Loading PDFs with PyPDFLoader in LangChain - Mini Project: Build & Apply

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Loading PDFs with PyPDFLoader
📖 Scenario: You want to read the text content from a PDF file to use it in a chatbot or search tool. The PyPDFLoader from the langchain library helps you load PDF files easily.
🎯 Goal: Build a simple Python script that loads a PDF file using PyPDFLoader and extracts its pages as text.
📋 What You'll Learn
Create a variable with the PDF file path
Import PyPDFLoader from langchain.document_loaders
Use PyPDFLoader to load the PDF file
Extract the pages from the loaded PDF
💡 Why This Matters
🌍 Real World
Loading PDFs is common when you want to extract text from reports, manuals, or books to build search tools or chatbots.
💼 Career
Many jobs in data science, AI, and software development require working with documents. Knowing how to load PDFs programmatically is a useful skill.
Progress0 / 4 steps
1
Set the PDF file path
Create a variable called pdf_path and set it to the string 'example.pdf'.
LangChain
Need a hint?

Use a string to store the file name exactly as 'example.pdf'.

2
Import PyPDFLoader
Import PyPDFLoader from langchain.document_loaders.
LangChain
Need a hint?

Use the exact import statement: from langchain.document_loaders import PyPDFLoader.

3
Load the PDF file
Create a variable called loader and set it to PyPDFLoader(pdf_path) to load the PDF file.
LangChain
Need a hint?

Use PyPDFLoader with the pdf_path variable as argument.

4
Extract pages from the PDF
Create a variable called pages and set it to the result of calling loader.load() to extract the pages from the PDF.
LangChain
Need a hint?

Call the load() method on loader and assign it to pages.