Automated PDF Summarizer with LangChain
Extract text from PDFs and use LangChain to chunk and summarize long documents using a map-reduce approach.
The Problem
Extract text from PDFs and use LangChain to chunk and summarize long documents using a map-reduce approach.
Real-World Use Case
Extract text from PDFs and use LangChain to chunk and summarize long documents using a map-reduce approach.
Technology Stack
Python
Prerequisite
LangChain concepts
Prerequisite
Architecture & Design
Folder Structure
summarizer/
├── app.py
└── sample.pdfStep-by-Step Implementation
Load PDF
Install PyPDF2 and langchain.
from langchain.document_loaders import PyPDFLoader
# Map-reduce summarization logic goes here...Code Explanation
Implementation step
Split text into 1000-token chunks
Use PyPDFLoader to extract the document content.
from langchain.document_loaders import PyPDFLoader
# Map-reduce summarization logic goes here...Code Explanation
Implementation step
Summarize each chunk
Run from the command line with `python app.py sample.pdf`.
from langchain.document_loaders import PyPDFLoader
# Map-reduce summarization logic goes here...Code Explanation
Implementation step
Combine summaries
Handle files that are scanned images instead of text.
from langchain.document_loaders import PyPDFLoader
# Map-reduce summarization logic goes here...Code Explanation
Implementation step
Common Errors
Make sure your chunk size is smaller than the model's limit.
Security & Performance
Test with a 2-page PDF
Test with a 50-page PDF
Add Gradio UI
Support DOCX files
Interview Questions
Q: Does this work on images?
A: No, you need OCR for scanned PDFs.